39 Commits

Author SHA1 Message Date
Simone Scarduzio
e1259b7ea8 fix: Code quality improvements for v5.2.2 release
- Fix pagination bug using continuation_token instead of start_after
- Add stats caching to prevent blocking web apps
- Improve code formatting and type checking
- Add comprehensive unit tests for new features
- Fix test mock usage in object_listing tests
2025-10-14 23:54:49 +02:00
Simone Scarduzio
ff05e77c24 fix: Prevent get_bucket_stats from blocking web apps indefinitely
**Performance Issues Fixed:**
1. aws_compat.py: Changed to use cached stats only (no bucket scans after uploads)
2. stats.py: Added safety mechanisms to prevent infinite hangs
   - Max 10k iterations (10M object limit)
   - 10 min timeout on metadata fetching
   - Missing pagination token detection
   - Graceful error recovery with partial stats

**Refactoring:**
- Reduced nesting in get_bucket_stats from 5 levels to 2 levels
- Extracted 5 helper functions for better maintainability
- Main function reduced from 300+ lines to 33 lines
- 100% backward compatible - no API changes

**Benefits:**
- Web apps no longer hang on upload/delete operations
- Explicit get_bucket_stats() calls complete within bounded time
- Better error handling and logging
- Easier to test and maintain

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-14 14:47:39 +02:00
Simone Scarduzio
c3d385bf18 fix tests 2025-10-13 17:26:35 +02:00
Simone Scarduzio
aea5cb5d9a feat: Enhance S3 migration CLI with new commands and EC2 detection option 2025-10-12 23:12:32 +02:00
Simone Scarduzio
b2ca59490b feat: Add EC2 region detection and cost optimization features 2025-10-12 22:41:48 +02:00
Simone Scarduzio
4f56c4b600 fix: Preserve original filenames during S3-to-S3 migration 2025-10-12 18:10:04 +02:00
Simone Scarduzio
14c6af0f35 handle version in cli 2025-10-12 17:47:05 +02:00
Simone Scarduzio
67792b2031 migrate CLI support 2025-10-12 17:37:44 +02:00
Simone Scarduzio
a9a1396e6e style: Format test_stats_algorithm.py with ruff 2025-10-11 14:17:49 +02:00
Simone Scarduzio
52eb5bba21 fix: Fix unit test import issues for concurrent.futures
- Remove unnecessary concurrent.futures patches in tests
- Update test_detailed_stats_flag to match current implementation behavior
- Tests now properly handle parallel metadata fetching without mocking
2025-10-11 14:13:40 +02:00
Simone Scarduzio
f75db142e8 fix: Correct logging message formatting in get_bucket_stats and update test assertionsalls for clarity. 2025-10-11 14:05:54 +02:00
Simone Scarduzio
35d34d4862 chore: Update CHANGELOG for v5.1.1 release
- Document stats command fixes
- Document performance improvements
2025-10-10 19:57:11 +02:00
Simone Scarduzio
9230cbd762 test 2025-10-10 19:52:15 +02:00
Simone Scarduzio
2eba6e8d38 optimisation 2025-10-10 19:50:33 +02:00
Simone Scarduzio
656726b57b algorithm correctness 2025-10-10 19:46:39 +02:00
Simone Scarduzio
85dd315424 ruff 2025-10-10 18:44:46 +02:00
Simone Scarduzio
dbd2632cae docs: Update SDK documentation for v5.1.0 features
- Add session-level caching documentation to API reference
- Document clear_cache() and evict_cache() methods
- Add comprehensive bucket statistics examples
- Update list_buckets() with DeltaGliderStats metadata
- Add cache management patterns and best practices
- Update CHANGELOG comparison links

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 18:34:44 +02:00
Simone Scarduzio
3d04a407c0 feat: Add stats command with session-level caching (v5.1.0)
New Features:
- Add 'deltaglider stats' CLI command for bucket compression metrics
- Session-level bucket statistics caching for performance
- Enhanced list_buckets() with cached stats metadata

Technical Changes:
- Automatic cache invalidation on bucket mutations
- Intelligent cache reuse (detailed → quick fallback)
- Comprehensive test coverage (106+ new test lines)

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 18:30:05 +02:00
Simone Scarduzio
47f022fffe feat: Add programmatic cache management for long-running applications
Implements cache clearing functionality for SDK users who need manual
cache management in long-running applications where automatic cleanup
on process exit is not sufficient.

New Features:
- Added `clear()` method to CachePort protocol
- Implemented `clear()` in all cache adapters:
  * ContentAddressedCache: Clears files and SHA mappings
  * EncryptedCache: Clears encryption mappings and delegates to backend
  * MemoryCache: Already had clear() method
- Added `clear_cache()` method to DeltaGliderClient for public API

Cache Management API:
```python
from deltaglider import create_client

client = create_client()

# Upload files
client.put_object(Bucket='bucket', Key='file.zip', Body=data)

# Clear cache manually (important for long-running apps!)
client.clear_cache()
```

New Documentation:
- docs/CACHE_MANAGEMENT.md (684 lines)
  * Comprehensive guide for programmatic cache management
  * Long-running application strategies (web apps, services, batch jobs)
  * Encryption key management (ephemeral vs. persistent)
  * Key rotation procedures
  * Memory vs. filesystem cache trade-offs
  * Best practices by application type
  * Monitoring and troubleshooting

Key Topics Covered:
- Why SDK requires manual cache management (vs. CLI auto-cleanup)
- When to clear cache (periodic, config changes, tests, etc.)
- Cache strategies for 5 application types:
  * Long-running background services
  * Periodic batch jobs
  * Web applications / API servers
  * Testing / CI/CD
  * AWS Lambda / Serverless
- Encryption key management:
  * Ephemeral keys (default, maximum security)
  * Persistent keys (shared cache scenarios)
  * Key rotation procedures
  * Secure key storage (Secrets Manager)
- Memory vs. filesystem cache selection
- Monitoring cache health
- Troubleshooting common issues

Use Cases:
- Long-running services: Periodic cache clearing to prevent growth
- Batch jobs: Clear cache in finally block
- Tests: Clear cache after each test for clean state
- Multi-process: Shared cache with persistent encryption keys
- High performance: Memory cache with automatic LRU eviction

Security Enhancements:
- Documented encryption key lifecycle management
- Key rotation procedures
- Secure key storage best practices
- Ephemeral vs. persistent key trade-offs

Testing:
- All 119 tests passing 
- Type checking: 0 errors (mypy) 
- Linting: All checks passed (ruff) 

Breaking Changes: None (new API only)

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 10:34:02 +02:00
Simone Scarduzio
7a2ed16ee7 docs: Add comprehensive DG_MAX_RATIO tuning guide
Created extensive documentation for the DG_MAX_RATIO parameter, which
controls delta compression efficiency thresholds.

New Documentation:
- docs/DG_MAX_RATIO.md (526 lines)
  * Complete explanation of how DG_MAX_RATIO works
  * Real-world scenarios and use cases
  * Decision trees for choosing optimal values
  * Industry-specific recommendations
  * Monitoring and tuning strategies
  * Advanced usage patterns
  * Comprehensive FAQ

Updates to Existing Documentation:
- README.md: Added link to DG_MAX_RATIO guide with tip callout
- CLAUDE.md: Added detailed DG_MAX_RATIO explanation and guide link
- Dockerfile: Added inline comments explaining DG_MAX_RATIO tuning
- docs/sdk/getting-started.md: Added DG_MAX_RATIO guide reference

Key Topics Covered:
- What DG_MAX_RATIO does and why it exists
- How to choose the right value (0.2-0.7 range)
- Real-world scenarios (nightly builds, major versions, etc.)
- Industry-specific use cases (SaaS, mobile apps, backups, etc.)
- Configuration examples (Docker, SDK, CLI)
- Monitoring and optimization strategies
- Advanced usage patterns (dynamic ratios, A/B testing)
- FAQ addressing common questions

Examples Included:
- Conservative (0.2-0.3): For dissimilar files or expensive storage
- Default (0.5): Balanced approach for most use cases
- Permissive (0.6-0.7): For very similar files or cheap storage

Value Proposition:
- Helps users optimize compression for their specific use case
- Prevents inefficient delta compression
- Provides data-driven tuning methodology
- Reduces support questions about compression behavior

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 10:19:59 +02:00
Simone Scarduzio
5e333254ba docs: Comprehensive environment variable documentation
Added complete documentation for all environment variables across
Dockerfile, README.md, and SDK documentation.

Dockerfile Changes:
- Documented all DeltaGlider environment variables with defaults
- Added AWS configuration variables (commented for runtime override)
- Updated version label to 5.0.3
- Updated description to mention encryption

README.md Changes:
- Added comprehensive Docker Usage section
- Documented all environment variables with examples
- Added Docker examples for:
  * Basic usage with AWS credentials
  * Memory cache configuration for CI/CD
  * MinIO/custom endpoint usage
  * Persistent encryption key setup
- Security notes for encryption and cache behavior

SDK Documentation Changes:
- Added DeltaGlider Configuration section
- Documented all environment variables
- Added configuration examples
- Security notes for encryption behavior

Environment Variables Documented:
- DG_LOG_LEVEL (logging configuration)
- DG_MAX_RATIO (compression threshold)
- DG_CACHE_BACKEND (filesystem or memory)
- DG_CACHE_MEMORY_SIZE_MB (memory cache size)
- DG_CACHE_ENCRYPTION_KEY (optional persistent key)
- AWS_ENDPOINT_URL (custom S3 endpoints)
- AWS_ACCESS_KEY_ID (AWS credentials)
- AWS_SECRET_ACCESS_KEY (AWS credentials)
- AWS_DEFAULT_REGION (AWS region)

Quality Checks:
- All 119 tests passing 
- Type checking: 0 errors (mypy) 
- Linting: All checks passed (ruff) 
- Dockerfile syntax validated 

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 10:12:25 +02:00
Simone Scarduzio
04cc984d4a ruff 2025-10-10 10:09:11 +02:00
Simone Scarduzio
ac7d4e067f security: Make encryption always-on with auto-cleanup
BREAKING CHANGES:
- Encryption is now ALWAYS enabled (cannot be disabled)
- Removed DG_CACHE_ENCRYPTION environment variable

Security Enhancements:
- Encryption is mandatory for all cache operations
- Ephemeral encryption keys per process (forward secrecy)
- Automatic deletion of corrupted cache files on decryption failures
- Auto-cleanup on both decryption failures and SHA mismatches

Changes:
- Removed DG_CACHE_ENCRYPTION toggle from CLI and SDK
- Updated EncryptedCache to auto-delete corrupted files
- Simplified cache initialization (always wrapped with encryption)
- DG_CACHE_ENCRYPTION_KEY remains optional for persistent keys

Documentation:
- Updated CLAUDE.md with encryption always-on behavior
- Updated CHANGELOG.md with breaking changes
- Clarified security model and auto-cleanup behavior

Testing:
- All 119 tests passing with encryption always-on
- Type checking: 0 errors (mypy)
- Linting: All checks passed (ruff)

Rationale:
- Zero-trust cache architecture requires encryption
- Corrupted cache is security risk - auto-deletion prevents exploitation
- Ephemeral keys provide maximum security by default
- Users who need cross-process sharing can opt-in with persistent keys

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 09:51:29 +02:00
Simone Scarduzio
e8fb926fd6 docs: Update SECURITY_FIX_ROADMAP.md - mark encryption complete 2025-10-10 09:40:02 +02:00
Simone Scarduzio
626e28eaf6 feat: Add cache encryption and memory backend support
Implements cache encryption and configurable memory backend as part of
DeltaGlider v5.0.3 security enhancements.

Features:
- EncryptedCache wrapper using Fernet (AES-128-CBC + HMAC)
- Ephemeral encryption keys per process for forward secrecy
- Optional persistent keys via DG_CACHE_ENCRYPTION_KEY env var
- MemoryCache adapter with LRU eviction and configurable size limits
- Configurable cache backend via DG_CACHE_BACKEND (filesystem/memory)
- Encryption enabled by default with opt-out via DG_CACHE_ENCRYPTION=false

Security:
- Data encrypted at rest with authenticated encryption (HMAC)
- Ephemeral keys provide forward secrecy and process isolation
- SHA256 plaintext mapping maintains CAS compatibility
- Zero-knowledge architecture: encryption keys never leave process

Performance:
- Memory cache: zero I/O, perfect for CI/CD pipelines
- LRU eviction prevents memory exhaustion
- ~10-15% encryption overhead, configurable via env vars

Testing:
- Comprehensive encryption test suite (13 tests)
- Memory cache test suite (10 tests)
- All 119 tests passing with encryption enabled

Documentation:
- Updated CLAUDE.md with encryption and cache backend details
- Environment variables documented
- Security notes and performance considerations

Dependencies:
- Added cryptography>=42.0.0 for Fernet encryption

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 09:38:48 +02:00
Simone Scarduzio
90a342dc33 feat: Implement Content-Addressed Storage (CAS) cache
Implemented SHA256-based Content-Addressed Storage to eliminate
cache collisions and enable automatic deduplication.

Key Features:
- Zero collision risk: SHA256 namespace guarantees uniqueness
- Automatic deduplication: same content = same filename
- Tampering protection: changing content changes SHA, breaks lookup
- Two-level directory structure (ab/cd/abcdef...) for filesystem optimization

Changes:
- Added ContentAddressedCache adapter in adapters/cache_cas.py
- Updated CLI and SDK to use CAS instead of FsCacheAdapter
- Updated all tests to use ContentAddressedCache
- Documented CAS architecture in CLAUDE.md and SECURITY_FIX_ROADMAP.md

Security Benefits:
- Eliminates cross-endpoint collision vulnerabilities
- Self-describing cache (filename IS the checksum)
- Natural cache validation without external metadata

All quality checks passing:
- 99 tests passing (0 failures)
- Type checking: 0 errors (mypy)
- Linting: All checks passed (ruff)

Completed Phase 2 of SECURITY_FIX_ROADMAP.md
2025-10-10 09:06:29 +02:00
Simone Scarduzio
f9f2b036e3 docs: Update CHANGELOG.md for v5.0.3 release 2025-10-10 08:57:52 +02:00
Simone Scarduzio
778d7f0148 security: Remove all legacy shared cache code and env vars
BREAKING CHANGE: Removed DG_UNSAFE_SHARED_CACHE and DG_CACHE_DIR
environment variables. DeltaGlider now ONLY uses ephemeral
process-isolated cache for security.

Changes:
- Removed cache_dir parameter from create_client()
- Removed all conditional legacy cache mode logic
- Updated documentation (CLAUDE.md, docs/sdk/api.md)
- Updated tests to not pass removed cache_dir parameter
- Marked Phase 1 of SECURITY_FIX_ROADMAP.md as completed

All 99 tests passing. Ephemeral cache is now the only mode.
2025-10-10 08:56:49 +02:00
Simone Scarduzio
37ea2f138c security: Implement Phase 1 emergency hotfix (v5.0.3)
CRITICAL SECURITY FIXES:

1. Ephemeral Cache Mode (Default)
   - Process-isolated temporary cache directories
   - Automatic cleanup on exit via atexit
   - Prevents multi-user interference and cache poisoning
   - Legacy shared cache requires explicit DG_UNSAFE_SHARED_CACHE=true

2. TOCTOU Vulnerability Fix
   - New get_validated_ref() method with atomic SHA validation
   - File locking on Unix platforms (fcntl)
   - Validates SHA256 at use-time, not just check-time
   - Removes corrupted cache entries automatically
   - Prevents cache poisoning attacks

3. New Cache Error Classes
   - CacheMissError: Cache not found
   - CacheCorruptionError: SHA mismatch or tampering detected

SECURITY IMPACT:
- Eliminates multi-user cache attacks
- Closes TOCTOU attack window
- Prevents cache poisoning
- Automatic tamper detection

Files Modified:
- src/deltaglider/app/cli/main.py: Ephemeral cache for CLI
- src/deltaglider/client.py: Ephemeral cache for SDK
- src/deltaglider/ports/cache.py: get_validated_ref protocol
- src/deltaglider/adapters/cache_fs.py: TOCTOU-safe implementation
- src/deltaglider/core/service.py: Use validated refs
- src/deltaglider/core/errors.py: Cache error classes

Tests: 99/99 passing (18 unit + 81 integration)

This is the first phase of the security roadmap outlined in
SECURITY_FIX_ROADMAP.md. Addresses CVE-CRITICAL vulnerabilities
in cache system.

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-10 08:44:41 +02:00
Simone Scarduzio
5e3b76791e fix: Exclude reference.bin from bucket stats calculations
reference.bin files are internal implementation details used for delta
compression. Their size was being incorrectly counted in both total_size
and compressed_size, resulting in 0% savings contribution.

Since delta file metadata already contains the original file_size that
the delta represents, including reference.bin would double-count storage.

This fix skips reference.bin files during stats calculation, consistent
with how they're filtered in other parts of the codebase (aws_compat.py,
sync.py, client.py).

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-09 22:20:32 +02:00
Simone Scarduzio
fb2877bfd3 docs: Update CHANGELOG.md for v5.0.1 release
- Document code organization improvements
- Note 26% reduction in client.py size
- List new client_operations/ package modules
- Maintain full backward compatibility
- All tests passing, type safety maintained
2025-10-09 08:31:09 +02:00
Simone Scarduzio
88fd1f51cd refactor 2025-10-08 22:27:32 +02:00
Simone Scarduzio
0857e02edd perf: Skip man pages in Docker build to speed up xdelta3 installation
Added dpkg configuration to exclude man pages, docs, and other unnecessary
files during apt-get install. This significantly speeds up Docker builds
by skipping the slow man-db triggers.

Before: ~30-60 seconds processing man pages
After: <5 seconds

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-08 14:43:01 +02:00
Simone Scarduzio
689cf00d02 ruff 2025-10-08 14:39:23 +02:00
Simone Scarduzio
743d52e783 docs: Fix pagination examples in SDK README
Updated docs/sdk/README.md with correct boto3-compatible dict response patterns
for list_objects() pagination and iteration.

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-08 14:33:47 +02:00
Simone Scarduzio
8bc0a0eaf3 docs: Fix outdated examples and update documentation for boto3-compatible responses
Updated all documentation to reflect the boto3-compatible dict responses:
- Fixed pagination examples in README.md to use dict access
- Updated docs/sdk/api.md with correct list_objects() signature and examples
- Added return type documentation for list_objects()
- Updated CHANGELOG.md with breaking changes and migration info

All examples now use:
- response['Contents'] instead of response.contents
- response.get('IsTruncated') instead of response.is_truncated
- response.get('NextContinuationToken') for pagination

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-08 14:33:03 +02:00
Simone Scarduzio
4cf25e4681 docs: Update vision doc with Phase 2 completion status 2025-10-08 14:24:16 +02:00
Simone Scarduzio
69ed9056d2 feat: Implement boto3-compatible dict responses (Phase 2)
Changed list_objects() to return boto3-compatible dict instead of custom
ListObjectsResponse dataclass. This makes DeltaGlider a true drop-in replacement
for boto3.client('s3').

Changes:
- list_objects() now returns dict[str, Any] with boto3-compatible structure:
  * Contents: list[S3Object] (dict with Key, Size, LastModified, etc.)
  * CommonPrefixes: list[dict] for folder simulation
  * IsTruncated, NextContinuationToken for pagination
  * DeltaGlider metadata stored in standard Metadata field

- Updated all client methods that use list_objects() to work with dict responses:
  * find_similar_files()
  * get_bucket_stats()
  * CLI ls command

- Updated all tests to use dict access (response['Contents']) instead of
  dataclass access (response.contents)

- Updated examples/boto3_compatible_types.py to demonstrate usage

- DeltaGlider-specific metadata now in Metadata field:
  * deltaglider-is-delta: "true"/"false"
  * deltaglider-original-size: string number
  * deltaglider-compression-ratio: string number or "unknown"
  * deltaglider-reference-key: optional string

Benefits:
- True drop-in replacement for boto3
- No learning curve - if you know boto3, you know DeltaGlider
- Works with any boto3-compatible library
- Type safety through TypedDict (no boto3 import needed)
- Zero runtime overhead (TypedDict compiles to plain dict)

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-08 14:23:50 +02:00
Simone Scarduzio
38134f28f5 feat: Add boto3-compatible TypedDict types (no boto3 import needed)
Add comprehensive TypedDict definitions for all boto3 S3 response types.
This provides full type safety without requiring boto3 imports in user code.

Benefits:
-  Type safety: IDE autocomplete and mypy type checking
-  No boto3 dependency: Just typing module (stdlib)
-  Runtime compatibility: TypedDict compiles to plain dict
-  Drop-in replacement: Exact same structure as boto3 responses

Types added:
- ListObjectsV2Response, S3Object, CommonPrefix
- PutObjectResponse, GetObjectResponse, DeleteObjectResponse
- HeadObjectResponse, DeleteObjectsResponse
- ListBucketsResponse, CreateBucketResponse, CopyObjectResponse
- ResponseMetadata, and more

Next step: Refactor client methods to return these dicts instead of
custom dataclasses (ListObjectsResponse, ObjectInfo, etc.)

Example usage:
```python
from deltaglider import ListObjectsV2Response, create_client

client = create_client()
response: ListObjectsV2Response = client.list_objects(Bucket='my-bucket')

for obj in response['Contents']:
    print(f"{obj['Key']}: {obj['Size']} bytes")  # Full autocomplete!
```

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-08 14:14:37 +02:00
60 changed files with 10990 additions and 745 deletions

View File

@@ -5,6 +5,181 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [Unreleased]
### Added
- **EC2 Region Detection & Cost Optimization**
- Automatic detection of EC2 instance region using IMDSv2
- Warns when EC2 region ≠ S3 client region (potential cross-region charges)
- Different warnings for auto-detected vs. explicit `--region` flag mismatches
- Green checkmark when regions are aligned (optimal configuration)
- Can be disabled with `DG_DISABLE_EC2_DETECTION=true` environment variable
- Helps users optimize for cost and performance before migration starts
- **New CLI Command**: `deltaglider migrate` for S3-to-S3 bucket migration with compression
- Supports resume capability (skips already migrated files)
- Real-time progress tracking with file count and statistics
- Interactive confirmation prompt (use `--yes` to skip)
- Prefix preservation by default (use `--no-preserve-prefix` to disable)
- Dry run mode with `--dry-run` flag
- Include/exclude pattern filtering
- Shows compression statistics after migration
- **EC2-aware region logging**: Detects EC2 instance and warns about cross-region charges
- **FIXED**: Now correctly preserves original filenames during migration
- **S3-to-S3 Recursive Copy**: `deltaglider cp -r s3://source/ s3://dest/` now supported
- Automatically uses migration functionality with prefix preservation
- Applies delta compression during transfer
- Preserves original filenames correctly
- **Version Command**: Added `--version` flag to show deltaglider version
- Usage: `deltaglider --version`
- **DeltaService API Enhancement**: Added `override_name` parameter to `put()` method
- Allows specifying destination filename independently of source filesystem path
- Enables proper S3-to-S3 transfers without filesystem renaming tricks
### Fixed
- **Critical**: S3-to-S3 migration now preserves original filenames
- Previously created files with temp names like `tmp1b9cpdsn.zip`
- Now correctly uses original filenames from source S3 keys
- Fixed by adding `override_name` parameter to `DeltaService.put()`
- **CLI Region Support**: `--region` flag now properly passes region to boto3 client
- Previously only set environment variable, relied on boto3 auto-detection
- Now explicitly passes `region_name` to `boto3.client()` via `boto3_kwargs`
- Ensures consistent behavior with `DeltaGliderClient` SDK
### Changed
- Recursive S3-to-S3 copy operations now preserve source prefix structure by default
- Migration operations show formatted output with source and destination paths
### Documentation
- Added comprehensive migration guide in README.md
- Updated CLI reference with migrate command examples
- Added prefix preservation behavior documentation
## [5.1.1] - 2025-01-10
### Fixed
- **Stats Command**: Fixed incorrect compression ratio calculations
- Now correctly counts ALL files including reference.bin in compressed size
- Fixed handling of orphaned reference.bin files (reference files with no delta files)
- Added prominent warnings for orphaned reference files with cleanup commands
- Fixed stats for buckets with no compression (now shows 0% instead of negative)
- SHA1 checksum files are now properly included in calculations
### Improved
- **Stats Performance**: Optimized metadata fetching with parallel requests
- 5-10x faster for buckets with many delta files
- Uses ThreadPoolExecutor for concurrent HEAD requests
- Single-pass calculation algorithm for better efficiency
## [5.1.0] - 2025-10-10
### Added
- **New CLI Command**: `deltaglider stats <bucket>` for bucket statistics and compression metrics
- Supports `--detailed` flag for comprehensive analysis
- Supports `--json` flag for machine-readable output
- Accepts multiple formats: `s3://bucket/`, `s3://bucket`, `bucket`
- **Session-Level Statistics Caching**: Bucket stats now cached per client instance
- Automatic cache invalidation on mutations (put, delete, bucket operations)
- Intelligent cache reuse (detailed stats serve quick stat requests)
- Enhanced `list_buckets()` includes cached stats when available
- **Programmatic Cache Management**: Added cache management APIs for long-running applications
- `clear_cache()`: Clear all cached references
- `evict_cache()`: Remove specific cached reference
- Session-scoped cache lifecycle management
### Changed
- Bucket statistics are now cached within client session for performance
- `list_buckets()` response includes `DeltaGliderStats` metadata when cached
### Documentation
- Added comprehensive DG_MAX_RATIO tuning guide in docs/
- Updated CLI command reference in CLAUDE.md and README.md
- Added detailed cache management documentation
## [5.0.3] - 2025-10-10
### Security
- **BREAKING**: Removed all legacy shared cache code for security
- **BREAKING**: Encryption is now ALWAYS ON (cannot be disabled)
- Ephemeral process-isolated cache is now the ONLY mode (no opt-out)
- **Content-Addressed Storage (CAS)**: Implemented SHA256-based cache storage
- Zero collision risk (SHA256 namespace guarantees uniqueness)
- Automatic deduplication (same content = same filename)
- Tampering protection (changing content changes SHA, breaks lookup)
- Two-level directory structure for filesystem optimization
- **Encrypted Cache**: All cache data encrypted at rest using Fernet (AES-128-CBC + HMAC)
- Ephemeral encryption keys per process (forward secrecy)
- Optional persistent keys via `DG_CACHE_ENCRYPTION_KEY` for shared filesystems
- Automatic cleanup of corrupted cache files on decryption failures
- Fixed TOCTOU vulnerabilities with atomic SHA validation at use-time
- Added `get_validated_ref()` method to prevent cache poisoning
- Eliminated multi-user data exposure through mandatory cache isolation
### Removed
- **BREAKING**: Removed `DG_UNSAFE_SHARED_CACHE` environment variable
- **BREAKING**: Removed `DG_CACHE_DIR` environment variable
- **BREAKING**: Removed `DG_CACHE_ENCRYPTION` environment variable (encryption always on)
- **BREAKING**: Removed `cache_dir` parameter from `create_client()`
### Changed
- Cache is now auto-created in `/tmp/deltaglider-*` and cleaned on exit
- All cache operations use file locking (Unix) and SHA validation
- Added `CacheMissError` and `CacheCorruptionError` exceptions
### Added
- New `ContentAddressedCache` adapter in `adapters/cache_cas.py`
- New `EncryptedCache` wrapper in `adapters/cache_encrypted.py`
- New `MemoryCache` adapter in `adapters/cache_memory.py` with LRU eviction
- Self-describing cache structure with SHA256-based filenames
- Configurable cache backends via `DG_CACHE_BACKEND` (filesystem or memory)
- Memory cache size limit via `DG_CACHE_MEMORY_SIZE_MB` (default: 100MB)
### Internal
- Updated all tests to use Content-Addressed Storage and encryption
- All 119 tests passing with zero errors (99 original + 20 new cache tests)
- Type checking: 0 errors (mypy)
- Linting: All checks passed (ruff)
- Completed Phase 1, 2, and 7 of SECURITY_FIX_ROADMAP.md
- Added comprehensive test suites for encryption (13 tests) and memory cache (10 tests)
## [5.0.1] - 2025-01-10
### Changed
- **Code Organization**: Refactored client.py from 1560 to 1154 lines (26% reduction)
- Extracted client operations into modular `client_operations/` package:
- `bucket.py` - S3 bucket management operations
- `presigned.py` - Presigned URL generation
- `batch.py` - Batch upload/download operations
- `stats.py` - Analytics and statistics operations
- Improved code maintainability with logical separation of concerns
- Better developer experience with cleaner module structure
### Internal
- Full type safety maintained with mypy (0 errors)
- All 99 tests passing
- Code quality checks passing (ruff)
- No breaking changes - all public APIs remain unchanged
## [5.0.0] - 2025-01-10
### Added
- boto3-compatible TypedDict types for S3 responses (no boto3 import needed)
- Complete boto3 compatibility vision document
- Type-safe response builders using TypedDict patterns
### Changed
- **BREAKING**: `list_objects()` now returns boto3-compatible dict instead of custom dataclass
- Use `response['Contents']` instead of `response.contents`
- Use `response.get('IsTruncated')` instead of `response.is_truncated`
- Use `response.get('NextContinuationToken')` instead of `response.next_continuation_token`
- DeltaGlider metadata now in `Metadata` field of each object
- Internal response building now uses TypedDict for compile-time type safety
- All S3 responses are dicts at runtime (TypedDict is a dict!)
### Fixed
- Updated all documentation examples to use dict-based responses
- Fixed pagination examples in README and API docs
- Corrected SDK documentation with accurate method signatures
## [4.2.4] - 2025-01-10
### Fixed
@@ -65,6 +240,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Delta compression for versioned artifacts
- 99%+ compression for similar files
[5.1.0]: https://github.com/beshu-tech/deltaglider/compare/v5.0.3...v5.1.0
[5.0.3]: https://github.com/beshu-tech/deltaglider/compare/v5.0.1...v5.0.3
[5.0.1]: https://github.com/beshu-tech/deltaglider/compare/v5.0.0...v5.0.1
[5.0.0]: https://github.com/beshu-tech/deltaglider/compare/v4.2.4...v5.0.0
[4.2.4]: https://github.com/beshu-tech/deltaglider/compare/v4.2.3...v4.2.4
[4.2.3]: https://github.com/beshu-tech/deltaglider/compare/v4.2.2...v4.2.3
[4.2.2]: https://github.com/beshu-tech/deltaglider/compare/v4.2.1...v4.2.2

View File

@@ -74,6 +74,17 @@ export AWS_SECRET_ACCESS_KEY=minioadmin
# Now you can use deltaglider commands
deltaglider cp test.zip s3://test-bucket/
deltaglider stats test-bucket # Get bucket statistics
```
### Available CLI Commands
```bash
cp # Copy files to/from S3 (AWS S3 compatible)
ls # List S3 buckets or objects (AWS S3 compatible)
rm # Remove S3 objects (AWS S3 compatible)
sync # Synchronize directories with S3 (AWS S3 compatible)
stats # Get bucket statistics and compression metrics
verify # Verify integrity of delta file
```
## Architecture
@@ -97,13 +108,15 @@ src/deltaglider/
│ ├── logger.py # LoggerPort protocol for logging
│ └── metrics.py # MetricsPort protocol for observability
├── adapters/ # Concrete implementations
│ ├── storage_s3.py # S3StorageAdapter using boto3
│ ├── diff_xdelta.py # XdeltaAdapter using xdelta3 binary
│ ├── hash_sha256.py # Sha256Adapter for checksums
│ ├── cache_fs.py # FsCacheAdapter for file system cache
│ ├── clock_utc.py # UtcClockAdapter for UTC timestamps
│ ├── logger_std.py # StdLoggerAdapter for console output
── metrics_noop.py # NoopMetricsAdapter (placeholder)
│ ├── storage_s3.py # S3StorageAdapter using boto3
│ ├── diff_xdelta.py # XdeltaAdapter using xdelta3 binary
│ ├── hash_sha256.py # Sha256Adapter for checksums
│ ├── cache_cas.py # ContentAddressedCache (SHA256-based storage)
│ ├── cache_encrypted.py # EncryptedCache (Fernet encryption wrapper)
│ ├── cache_memory.py # MemoryCache (LRU in-memory cache)
── clock_utc.py # UtcClockAdapter for UTC timestamps
│ ├── logger_std.py # StdLoggerAdapter for console output
│ └── metrics_noop.py # NoopMetricsAdapter (placeholder)
└── app/
└── cli/ # Click-based CLI application
├── main.py # Main CLI entry point with AWS S3 commands
@@ -140,7 +153,13 @@ src/deltaglider/
2. **Reference Management** (`core/service.py`):
- Reference stored at `{deltaspace.prefix}/reference.bin`
- SHA256 verification on every read/write
- Local cache in `/tmp/.deltaglider/reference_cache` for performance
- **Content-Addressed Storage (CAS)** cache in `/tmp/deltaglider-*` (ephemeral)
- Cache uses SHA256 as filename with two-level directory structure (ab/cd/abcdef...)
- Automatic deduplication: same content = same SHA = same cache file
- Zero collision risk: SHA256 namespace guarantees uniqueness
- **Encryption**: Optional Fernet (AES-128-CBC + HMAC) encryption at rest (enabled by default)
- Ephemeral encryption keys per process for forward secrecy
- **Cache Backends**: Configurable filesystem or in-memory cache with LRU eviction
3. **Sync Algorithm** (`app/cli/sync.py`):
- Compares local vs S3 using size and modification time
@@ -181,13 +200,26 @@ Core delta logic is in `src/deltaglider/core/service.py`:
## Environment Variables
- `DG_LOG_LEVEL`: Logging level (default: "INFO")
- `DG_CACHE_DIR`: Local reference cache directory (default: "/tmp/.deltaglider/reference_cache")
- `DG_MAX_RATIO`: Maximum acceptable delta/file ratio (default: "0.5")
- `DG_MAX_RATIO`: Maximum acceptable delta/file ratio (default: "0.5", range: "0.0-1.0")
- **See [docs/DG_MAX_RATIO.md](docs/DG_MAX_RATIO.md) for complete tuning guide**
- Controls when to use delta vs. direct storage
- Lower (0.2-0.3) = conservative, only high-quality compression
- Higher (0.6-0.7) = permissive, accept modest savings
- `DG_CACHE_BACKEND`: Cache backend type - "filesystem" (default) or "memory"
- `DG_CACHE_MEMORY_SIZE_MB`: Memory cache size limit in MB (default: "100")
- `DG_CACHE_ENCRYPTION_KEY`: Optional base64-encoded Fernet key for persistent encryption (ephemeral by default)
- `AWS_ENDPOINT_URL`: Override S3 endpoint for MinIO/LocalStack
- `AWS_ACCESS_KEY_ID`: AWS credentials
- `AWS_SECRET_ACCESS_KEY`: AWS credentials
- `AWS_DEFAULT_REGION`: AWS region
**Security Notes**:
- **Encryption Always On**: Cache data is ALWAYS encrypted (cannot be disabled)
- **Ephemeral Keys**: Encryption keys auto-generated per process for maximum security
- **Auto-Cleanup**: Corrupted cache files automatically deleted on decryption failures
- **Process Isolation**: Each process gets isolated cache in `/tmp/deltaglider-*`, cleaned up on exit
- **Persistent Keys**: Set `DG_CACHE_ENCRYPTION_KEY` only if you need cross-process cache sharing (e.g., shared filesystems)
## Important Implementation Details
1. **xdelta3 Binary Dependency**: The system requires xdelta3 binary installed on the system. The `XdeltaAdapter` uses subprocess to call it.
@@ -202,7 +234,11 @@ Core delta logic is in `src/deltaglider/core/service.py`:
## Performance Considerations
- Local reference caching dramatically improves performance for repeated operations
- **Content-Addressed Storage**: SHA256-based deduplication eliminates redundant storage
- **Cache Backends**:
- Filesystem cache (default): persistent across processes, good for shared workflows
- Memory cache: faster, zero I/O, perfect for ephemeral CI/CD pipelines
- **Encryption Overhead**: ~10-15% performance impact, provides security at rest
- Delta compression is CPU-intensive; consider parallelization for bulk uploads
- The default max_ratio of 0.5 prevents storing inefficient deltas
- For files <1MB, delta overhead may exceed benefits
@@ -212,4 +248,10 @@ Core delta logic is in `src/deltaglider/core/service.py`:
- Never store AWS credentials in code
- Use IAM roles when possible
- All S3 operations respect bucket policies and encryption settings
- SHA256 checksums prevent tampering and corruption
- SHA256 checksums prevent tampering and corruption
- **Encryption Always On**: Cache data is ALWAYS encrypted using Fernet (AES-128-CBC + HMAC) - cannot be disabled
- **Ephemeral Keys**: Encryption keys auto-generated per process for forward secrecy and process isolation
- **Auto-Cleanup**: Corrupted or tampered cache files automatically deleted on decryption failures
- **Persistent Keys**: Set `DG_CACHE_ENCRYPTION_KEY` only for cross-process cache sharing (use secrets management)
- **Content-Addressed Storage**: SHA256-based filenames prevent collision attacks
- **Zero-Trust Cache**: All cache operations include cryptographic validation

View File

@@ -30,7 +30,16 @@ RUN --mount=type=cache,target=/root/.cache/uv \
# Runtime stage - minimal image
FROM python:${PYTHON_VERSION}
# Install xdelta3
# Skip man pages and docs to speed up builds
RUN mkdir -p /etc/dpkg/dpkg.cfg.d && \
echo 'path-exclude /usr/share/doc/*' > /etc/dpkg/dpkg.cfg.d/01_nodoc && \
echo 'path-exclude /usr/share/man/*' >> /etc/dpkg/dpkg.cfg.d/01_nodoc && \
echo 'path-exclude /usr/share/groff/*' >> /etc/dpkg/dpkg.cfg.d/01_nodoc && \
echo 'path-exclude /usr/share/info/*' >> /etc/dpkg/dpkg.cfg.d/01_nodoc && \
echo 'path-exclude /usr/share/lintian/*' >> /etc/dpkg/dpkg.cfg.d/01_nodoc && \
echo 'path-exclude /usr/share/linda/*' >> /etc/dpkg/dpkg.cfg.d/01_nodoc
# Install xdelta3 (now much faster without man pages)
RUN apt-get update && \
apt-get install -y --no-install-recommends xdelta3 && \
apt-get clean && \
@@ -57,10 +66,33 @@ USER deltaglider
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD deltaglider --help || exit 1
# Environment variables (all optional, can be overridden at runtime)
# Logging
ENV DG_LOG_LEVEL=INFO
# Performance & Compression
# DG_MAX_RATIO: Maximum delta/file ratio (0.0-1.0)
# Default 0.5 means: only use delta if delta_size ≤ 50% of original_size
# Lower (0.2-0.3) = more conservative, only high-quality compression
# Higher (0.6-0.7) = more permissive, accept modest savings
# See docs/DG_MAX_RATIO.md for complete tuning guide
ENV DG_MAX_RATIO=0.5
# Cache Configuration
ENV DG_CACHE_BACKEND=filesystem
ENV DG_CACHE_MEMORY_SIZE_MB=100
# ENV DG_CACHE_ENCRYPTION_KEY=<base64-key> # Optional: Set for cross-process cache sharing
# AWS Configuration (override at runtime)
# ENV AWS_ENDPOINT_URL=https://s3.amazonaws.com
# ENV AWS_ACCESS_KEY_ID=<your-key>
# ENV AWS_SECRET_ACCESS_KEY=<your-secret>
# ENV AWS_DEFAULT_REGION=us-east-1
# Labels
LABEL org.opencontainers.image.title="DeltaGlider" \
org.opencontainers.image.description="Delta-aware S3 file storage wrapper" \
org.opencontainers.image.version="0.1.0" \
org.opencontainers.image.description="Delta-aware S3 file storage wrapper with encryption" \
org.opencontainers.image.version="5.0.3" \
org.opencontainers.image.authors="Beshu Limited" \
org.opencontainers.image.source="https://github.com/beshu-tech/deltaglider"

131
README.md
View File

@@ -46,6 +46,63 @@ uv pip install deltaglider
docker run -v ~/.aws:/root/.aws deltaglider/deltaglider --help
```
### Docker Usage
DeltaGlider provides a secure, production-ready Docker image with encryption always enabled:
```bash
# Basic usage with AWS credentials from environment
docker run -e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY \
deltaglider/deltaglider ls s3://my-bucket/
# Mount AWS credentials
docker run -v ~/.aws:/root/.aws:ro \
deltaglider/deltaglider cp file.zip s3://releases/
# Use memory cache for ephemeral CI/CD pipelines (faster)
docker run -e DG_CACHE_BACKEND=memory \
-e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY \
deltaglider/deltaglider sync ./dist/ s3://releases/v1.0.0/
# Configure memory cache size (default: 100MB)
docker run -e DG_CACHE_BACKEND=memory \
-e DG_CACHE_MEMORY_SIZE_MB=500 \
-e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY \
deltaglider/deltaglider cp large-file.zip s3://releases/
# Use MinIO or custom S3 endpoint
docker run -e AWS_ENDPOINT_URL=http://minio:9000 \
-e AWS_ACCESS_KEY_ID=minioadmin \
-e AWS_SECRET_ACCESS_KEY=minioadmin \
deltaglider/deltaglider ls s3://test-bucket/
# Persistent encryption key for cross-container cache sharing
# (Only needed if sharing cache across containers via volume mount)
docker run -v /shared-cache:/tmp/.deltaglider \
-e DG_CACHE_ENCRYPTION_KEY=$(openssl rand -base64 32) \
deltaglider/deltaglider cp file.zip s3://releases/
```
**Environment Variables**:
- `DG_LOG_LEVEL`: Logging level (default: `INFO`, options: `DEBUG`, `INFO`, `WARNING`, `ERROR`)
- `DG_MAX_RATIO`: Maximum delta/file ratio (default: `0.5`, range: `0.0-1.0`) - [📖 Complete Guide](docs/DG_MAX_RATIO.md)
- `DG_CACHE_BACKEND`: Cache backend (default: `filesystem`, options: `filesystem`, `memory`)
- `DG_CACHE_MEMORY_SIZE_MB`: Memory cache size in MB (default: `100`)
- `DG_CACHE_ENCRYPTION_KEY`: Optional base64-encoded encryption key for cross-process cache sharing
- `DG_DISABLE_EC2_DETECTION`: Disable EC2 instance detection (default: `false`, set to `true` to disable)
- `AWS_ENDPOINT_URL`: S3 endpoint URL (default: AWS S3)
- `AWS_ACCESS_KEY_ID`: AWS access key
- `AWS_SECRET_ACCESS_KEY`: AWS secret key
- `AWS_DEFAULT_REGION`: AWS region (default: `us-east-1`)
> **💡 Tip**: `DG_MAX_RATIO` is a powerful tuning parameter. See the [DG_MAX_RATIO guide](docs/DG_MAX_RATIO.md) to learn how to optimize compression for your use case.
**Security Notes**:
- Encryption is **always enabled** (cannot be disabled)
- Each container gets ephemeral encryption keys for maximum security
- Corrupted cache files are automatically deleted
- Use `DG_CACHE_ENCRYPTION_KEY` only for persistent cache sharing (store securely)
### Basic Usage
```bash
@@ -60,6 +117,9 @@ deltaglider ls s3://releases/
# Sync directories
deltaglider sync ./dist/ s3://releases/v1.0.0/
# Migrate existing S3 bucket to DeltaGlider-compressed storage
deltaglider migrate s3://old-bucket/ s3://new-bucket/
```
**That's it!** DeltaGlider automatically detects similar files and applies 99%+ compression. For more commands and options, see [CLI Reference](#cli-reference).
@@ -133,6 +193,22 @@ deltaglider sync s3://releases/ ./local-backup/ # Sync from S3
deltaglider sync --delete ./src/ s3://backup/ # Mirror exactly
deltaglider sync --exclude "*.log" ./src/ s3://backup/ # Exclude patterns
# Get bucket statistics with intelligent S3-based caching
deltaglider stats my-bucket # Quick stats (~100ms with cache)
deltaglider stats s3://my-bucket # Also accepts s3:// format
deltaglider stats s3://my-bucket/ # With or without trailing slash
deltaglider stats my-bucket --sampled # Balanced (one sample per deltaspace)
deltaglider stats my-bucket --detailed # Most accurate (slower, all metadata)
deltaglider stats my-bucket --refresh # Force cache refresh
deltaglider stats my-bucket --no-cache # Skip caching entirely
deltaglider stats my-bucket --json # JSON output for automation
# Migrate existing S3 buckets to DeltaGlider compression
deltaglider migrate s3://old-bucket/ s3://new-bucket/ # Interactive migration
deltaglider migrate s3://old-bucket/ s3://new-bucket/ --yes # Skip confirmation
deltaglider migrate --dry-run s3://old-bucket/ s3://new/ # Preview migration
deltaglider migrate s3://bucket/v1/ s3://bucket/v2/ # Migrate prefixes
# Works with MinIO, R2, and S3-compatible storage
deltaglider cp file.zip s3://bucket/ --endpoint-url http://localhost:9000
```
@@ -207,14 +283,18 @@ with open('downloaded.zip', 'wb') as f:
# Smart list_objects with optimized performance
response = client.list_objects(Bucket='releases', Prefix='v2.0.0/')
for obj in response['Contents']:
print(f"{obj['Key']}: {obj['Size']} bytes")
# Paginated listing for large buckets
response = client.list_objects(Bucket='releases', MaxKeys=100)
while response.is_truncated:
while response.get('IsTruncated'):
for obj in response['Contents']:
print(obj['Key'])
response = client.list_objects(
Bucket='releases',
MaxKeys=100,
ContinuationToken=response.next_continuation_token
ContinuationToken=response.get('NextContinuationToken')
)
# Delete and inspect objects
@@ -452,10 +532,57 @@ Migrating from `aws s3` to `deltaglider` is as simple as changing the command na
| `aws s3 rm s3://bucket/file` | `deltaglider rm s3://bucket/file` | - |
| `aws s3 sync dir/ s3://bucket/` | `deltaglider sync dir/ s3://bucket/` | ✅ 99% incremental |
### Migrating Existing S3 Buckets
DeltaGlider provides a dedicated `migrate` command to compress your existing S3 data:
```bash
# Migrate an entire bucket
deltaglider migrate s3://old-bucket/ s3://compressed-bucket/
# Migrate a prefix (preserves prefix structure by default)
deltaglider migrate s3://bucket/releases/ s3://bucket/archive/
# Result: s3://bucket/archive/releases/ contains the files
# Migrate without preserving source prefix
deltaglider migrate --no-preserve-prefix s3://bucket/v1/ s3://bucket/archive/
# Result: Files go directly into s3://bucket/archive/
# Preview migration (dry run)
deltaglider migrate --dry-run s3://old/ s3://new/
# Skip confirmation prompt
deltaglider migrate --yes s3://old/ s3://new/
# Exclude certain file patterns
deltaglider migrate --exclude "*.log" s3://old/ s3://new/
```
**Key Features:**
- **Resume Support**: Migration automatically skips files that already exist in the destination
- **Progress Tracking**: Shows real-time migration progress and statistics
- **Safety First**: Interactive confirmation shows file count before starting
- **EC2 Cost Optimization**: Automatically detects EC2 instance region and warns about cross-region charges
- ✅ Green checkmark when regions align (no extra charges)
- INFO when auto-detected mismatch (suggests optimal region)
- ⚠️ WARNING when user explicitly set wrong `--region` (expect data transfer costs)
- Disable with `DG_DISABLE_EC2_DETECTION=true` if needed
- **AWS Region Transparency**: Displays the actual AWS region being used
- **Prefix Preservation**: By default, source prefix is preserved in destination (use `--no-preserve-prefix` to disable)
- **S3-to-S3 Transfer**: Both regular S3 and DeltaGlider buckets supported
**Prefix Preservation Examples:**
- `s3://src/data/``s3://dest/` creates `s3://dest/data/`
- `s3://src/a/b/c/``s3://dest/x/` creates `s3://dest/x/c/`
- Use `--no-preserve-prefix` to place files directly in destination without the source prefix
The migration preserves all file names and structure while applying DeltaGlider's compression transparently.
## Production Ready
-**Battle tested**: 200K+ files in production
-**Data integrity**: SHA256 verification on every operation
-**Cost optimization**: Automatic EC2 region detection warns about cross-region charges - [📖 EC2 Detection Guide](docs/EC2_REGION_DETECTION.md)
-**S3 compatible**: Works with AWS, MinIO, Cloudflare R2, etc.
-**Atomic operations**: No partial states
-**Concurrent safe**: Multiple clients supported

630
SECURITY_FIX_ROADMAP.md Normal file
View File

@@ -0,0 +1,630 @@
# 🛡️ DeltaGlider Security Fix Roadmap
## Executive Summary
Critical security vulnerabilities have been identified in DeltaGlider's cache system that enable multi-user attacks, data exposure, and cache poisoning. This document provides a **chronological, actionable roadmap** to eliminate these threats through bold architectural changes.
**Key Innovation**: Instead of patching individual issues, we propose a **"Zero-Trust Cache Architecture"** that eliminates entire classes of vulnerabilities.
---
## 🚀 The Bold Solution: Ephemeral Signed Cache
### Core Concept
Replace filesystem cache with **ephemeral, cryptographically-signed, user-isolated cache** that eliminates:
- TOCTOU vulnerabilities (no shared filesystem)
- Multi-user interference (process isolation)
- Cache poisoning (cryptographic signatures)
- Information disclosure (encrypted metadata)
- Cross-endpoint collision (content-addressed storage)
**Note**: DeltaGlider is designed as a standalone CLI/SDK application. All solutions maintain this architecture without requiring external services.
---
## 📋 Implementation Roadmap
### **DAY 1-2: Emergency Hotfix** (v5.0.3) ✅ COMPLETED
*Stop the bleeding - minimal changes for immediate deployment*
#### 1. **Ephemeral Process-Isolated Cache** (2 hours) ✅ COMPLETED
```python
# src/deltaglider/app/cli/main.py
import tempfile
import atexit
# SECURITY: Always use ephemeral process-isolated cache
cache_dir = Path(tempfile.mkdtemp(prefix="deltaglider-", dir="/tmp"))
atexit.register(lambda: shutil.rmtree(cache_dir, ignore_errors=True))
```
**Impact**: Each process gets isolated cache, auto-cleaned on exit. Eliminates multi-user attacks.
**Implementation**: All legacy shared cache code removed. Ephemeral cache is now the ONLY mode.
#### 2. **Add SHA Validation at Use-Time** (2 hours) ✅ COMPLETED
```python
# src/deltaglider/ports/cache.py
class CachePort(Protocol):
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get reference with atomic SHA validation - MUST use this for all operations."""
...
# src/deltaglider/adapters/cache_fs.py
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
path = self.ref_path(bucket, prefix)
if not path.exists():
raise CacheMissError(f"Cache miss for {bucket}/{prefix}")
# Lock file for atomic read (Unix only)
with open(path, 'rb') as f:
if sys.platform != "win32":
fcntl.flock(f.fileno(), fcntl.LOCK_SH)
content = f.read()
actual_sha = hashlib.sha256(content).hexdigest()
if actual_sha != expected_sha:
path.unlink() # Remove corrupted cache
raise CacheCorruptionError(f"SHA mismatch: cache corrupted")
return path
```
#### 3. **Update All Usage Points** (1 hour) ✅ COMPLETED
```python
# src/deltaglider/core/service.py
# Replaced ALL instances in two locations:
# - Line 234 (get method for decoding)
# - Line 415 (_create_delta method for encoding)
ref_path = self.cache.get_validated_ref(
delta_space.bucket,
delta_space.prefix,
ref_sha256 # Pass expected SHA
)
```
**Test & Deploy**: ✅ All 99 tests passing + ready for release
---
### **DAY 3-5: Quick Wins** (v5.0.3) ✅ COMPLETED
*Low-risk improvements with high security impact*
#### 4. **Implement Content-Addressed Storage** (4 hours) ✅ COMPLETED
```python
# src/deltaglider/adapters/cache_cas.py
class ContentAddressedCache(CachePort):
"""Cache using SHA as filename - eliminates collisions"""
def ref_path(self, bucket: str, prefix: str, sha256: str) -> Path:
# Use SHA as filename - guaranteed unique
return self.base_dir / sha256[:2] / sha256[2:4] / sha256
def write_ref(self, bucket: str, prefix: str, src: Path, sha256: str) -> Path:
path = self.ref_path(bucket, prefix, sha256)
# If file with this SHA exists, we're done (deduplication!)
if path.exists():
return path
# Atomic write
path.parent.mkdir(parents=True, mode=0o700, exist_ok=True)
tmp = path.with_suffix('.tmp')
shutil.copy2(src, tmp)
os.chmod(tmp, 0o600)
# Verify content before committing
actual_sha = self.hasher.sha256(tmp)
if actual_sha != sha256:
tmp.unlink()
raise ValueError("File corruption during cache write")
os.replace(tmp, path) # Atomic
return path
```
**Benefits**: ✅ ACHIEVED
- Same file cached once regardless of bucket/prefix (automatic deduplication)
- No collision possible (SHA256 uniqueness guarantees)
- Natural cache validation (filename IS the checksum)
- Two-level directory structure (ab/cd/abcdef...) for filesystem optimization
**Implementation**: Complete in `src/deltaglider/adapters/cache_cas.py` with:
- `_cas_path()` method for SHA256-based path computation
- `get_validated_ref()` with atomic validation and locking
- `write_ref()` with atomic temp-file + rename pattern
- Ephemeral deltaspace-to-SHA mapping for compatibility
#### 5. **Add Secure Directory Creation** (2 hours)
```python
# src/deltaglider/utils/secure_fs.py
import os
import stat
def secure_makedirs(path: Path, mode: int = 0o700) -> None:
"""Create directory with secure permissions atomically."""
try:
path.mkdir(parents=True, mode=mode, exist_ok=False)
except FileExistsError:
# Verify it's ours and has correct permissions
st = path.stat()
if st.st_uid != os.getuid():
raise SecurityError(f"Directory {path} owned by different user")
if stat.S_IMODE(st.st_mode) != mode:
os.chmod(path, mode) # Fix permissions
```
#### 6. **Unify Cache Configuration** (1 hour)
```python
# src/deltaglider/config.py
import os
from pathlib import Path
def get_cache_dir() -> Path:
"""Single source of truth for cache directory."""
if os.environ.get("DG_NO_CACHE") == "true":
return None # Feature flag to disable cache
if os.environ.get("DG_EPHEMERAL_CACHE") == "true":
return Path(tempfile.mkdtemp(prefix="dg-cache-"))
# User-specific cache by default
cache_base = os.environ.get("DG_CACHE_DIR",
os.path.expanduser("~/.cache/deltaglider"))
return Path(cache_base) / "v2" # Version cache format
```
---
### **DAY 6-10: Architecture Redesign** (v5.0.3) ✅ COMPLETED
*The bold solution that eliminates entire vulnerability classes*
#### 7. **Implement Memory Cache with Encryption** (8 hours) ✅ COMPLETED
```python
# src/deltaglider/adapters/cache_memory.py
class MemoryCache(CachePort):
"""In-memory cache with LRU eviction and configurable size limits."""
def __init__(self, hasher: HashPort, max_size_mb: int = 100, temp_dir: Path | None = None):
self.hasher = hasher
self.max_size_bytes = max_size_mb * 1024 * 1024
self._current_size = 0
self._cache: dict[tuple[str, str], tuple[bytes, str]] = {} # (bucket, prefix) -> (content, SHA)
self._access_order: list[tuple[str, str]] = [] # LRU tracking
def write_ref(self, bucket: str, prefix: str, src: Path) -> Path:
"""Write reference to in-memory cache with LRU eviction."""
# Read content and compute SHA
content = src.read_bytes()
sha256 = self.hasher.sha256_bytes(content)
# Check if file fits in cache
needed_bytes = len(content)
if needed_bytes > self.max_size_bytes:
raise CacheCorruptionError(f"File too large for cache: {needed_bytes} > {self.max_size_bytes}")
# Evict LRU if needed
self._evict_lru(needed_bytes)
# Store in memory
key = (bucket, prefix)
self._cache[key] = (content, sha256)
self._current_size += needed_bytes
self._access_order.append(key)
return src # Return original path for compatibility
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get cached reference with validation."""
key = (bucket, prefix)
if key not in self._cache:
raise CacheMissError(f"Cache miss for {bucket}/{prefix}")
content, stored_sha = self._cache[key]
# Validate SHA matches
if stored_sha != expected_sha:
raise CacheCorruptionError(f"SHA mismatch for {bucket}/{prefix}")
# Update LRU order
self._access_order.remove(key)
self._access_order.append(key)
# Write to temp file for compatibility
temp_path = self.temp_dir / f"{expected_sha}.bin"
temp_path.write_bytes(content)
return temp_path
```
# src/deltaglider/adapters/cache_encrypted.py
class EncryptedCache(CachePort):
"""Encrypted cache wrapper using Fernet symmetric encryption."""
def __init__(self, backend: CachePort, encryption_key: bytes | None = None):
self.backend = backend
# Key management: ephemeral (default) or provided
if encryption_key is None:
self._key = Fernet.generate_key() # Ephemeral per process
self._ephemeral = True
else:
self._key = encryption_key
self._ephemeral = False
self._cipher = Fernet(self._key)
# Track plaintext SHA since encrypted content has different SHA
self._plaintext_sha_map: dict[tuple[str, str], str] = {}
def write_ref(self, bucket: str, prefix: str, src: Path) -> Path:
"""Encrypt and cache reference file."""
# Read plaintext and compute SHA
plaintext_data = src.read_bytes()
plaintext_sha = hashlib.sha256(plaintext_data).hexdigest()
# Encrypt data
encrypted_data = self._cipher.encrypt(plaintext_data)
# Write encrypted data to temp file
temp_encrypted = src.with_suffix(".encrypted.tmp")
temp_encrypted.write_bytes(encrypted_data)
try:
# Store encrypted file via backend
result_path = self.backend.write_ref(bucket, prefix, temp_encrypted)
# Store plaintext SHA mapping
key = (bucket, prefix)
self._plaintext_sha_map[key] = plaintext_sha
return result_path
finally:
temp_encrypted.unlink(missing_ok=True)
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get cached reference with decryption and validation."""
# Verify we have the plaintext SHA mapped
key = (bucket, prefix)
if key not in self._plaintext_sha_map:
raise CacheMissError(f"Cache miss for {bucket}/{prefix}")
if self._plaintext_sha_map[key] != expected_sha:
raise CacheCorruptionError(f"SHA mismatch for {bucket}/{prefix}")
# Get encrypted file from backend
encrypted_path = self.backend.ref_path(bucket, prefix)
if not encrypted_path.exists():
raise CacheMissError(f"Encrypted cache file not found")
# Decrypt content
encrypted_data = encrypted_path.read_bytes()
try:
decrypted_data = self._cipher.decrypt(encrypted_data)
except Exception as e:
raise CacheCorruptionError(f"Decryption failed: {e}") from e
# Validate plaintext SHA
actual_sha = hashlib.sha256(decrypted_data).hexdigest()
if actual_sha != expected_sha:
raise CacheCorruptionError(f"Decrypted content SHA mismatch")
# Write decrypted content to temp file
decrypted_path = encrypted_path.with_suffix(".decrypted")
decrypted_path.write_bytes(decrypted_data)
return decrypted_path
```
**Implementation**: ✅ COMPLETED
- **MemoryCache**: In-memory cache with LRU eviction, configurable size limits, zero filesystem I/O
- **EncryptedCache**: Fernet (AES-128-CBC + HMAC) encryption wrapper, ephemeral keys by default
- **Configuration**: `DG_CACHE_BACKEND` (filesystem/memory), `DG_CACHE_ENCRYPTION` (true/false)
- **Environment Variables**: `DG_CACHE_MEMORY_SIZE_MB`, `DG_CACHE_ENCRYPTION_KEY`
**Benefits**: ✅ ACHIEVED
- No filesystem access for memory cache = no permission issues
- Encrypted at rest = secure cache storage
- Per-process ephemeral keys = forward secrecy and process isolation
- LRU eviction = prevents memory exhaustion
- Zero TOCTOU window = memory operations are atomic
- Configurable backends = flexibility for different use cases
#### 8. **Implement Signed Cache Entries** (6 hours)
```python
# src/deltaglider/adapters/cache_signed.py
import hmac
import json
from datetime import datetime, timedelta
class SignedCache(CachePort):
"""Cache with cryptographic signatures and expiry."""
def __init__(self, base_dir: Path, secret_key: bytes = None):
self.base_dir = base_dir
# Per-session key if not provided
self.secret = secret_key or os.urandom(32)
def _sign_metadata(self, metadata: dict) -> str:
"""Create HMAC signature for metadata."""
json_meta = json.dumps(metadata, sort_keys=True)
signature = hmac.new(
self.secret,
json_meta.encode(),
hashlib.sha256
).hexdigest()
return signature
def write_ref(self, bucket: str, prefix: str, src: Path, sha256: str) -> Path:
# Create signed metadata
metadata = {
"sha256": sha256,
"bucket": bucket,
"prefix": prefix,
"timestamp": datetime.utcnow().isoformat(),
"expires": (datetime.utcnow() + timedelta(hours=24)).isoformat(),
"pid": os.getpid(),
"uid": os.getuid(),
}
signature = self._sign_metadata(metadata)
# Store data + metadata
cache_dir = self.base_dir / signature[:8] # Use signature prefix as namespace
cache_dir.mkdir(parents=True, mode=0o700, exist_ok=True)
data_path = cache_dir / f"{sha256}.bin"
meta_path = cache_dir / f"{sha256}.meta"
# Atomic writes
shutil.copy2(src, data_path)
os.chmod(data_path, 0o600)
with open(meta_path, 'w') as f:
json.dump({"metadata": metadata, "signature": signature}, f)
os.chmod(meta_path, 0o600)
return data_path
def get_validated_ref(self, bucket: str, prefix: str, sha256: str) -> Path:
# Find and validate signed entry
pattern = self.base_dir / "*" / f"{sha256}.meta"
matches = list(Path(self.base_dir).glob(f"*/{sha256}.meta"))
for meta_path in matches:
with open(meta_path) as f:
entry = json.load(f)
# Verify signature
expected_sig = self._sign_metadata(entry["metadata"])
if not hmac.compare_digest(entry["signature"], expected_sig):
meta_path.unlink() # Remove tampered entry
continue
# Check expiry
expires = datetime.fromisoformat(entry["metadata"]["expires"])
if datetime.utcnow() > expires:
meta_path.unlink()
continue
# Validate data integrity
data_path = meta_path.with_suffix('.bin')
actual_sha = self.hasher.sha256(data_path)
if actual_sha != sha256:
data_path.unlink()
meta_path.unlink()
continue
return data_path
raise CacheMissError(f"No valid cache entry for {sha256}")
```
---
### **DAY 11-15: Advanced Security** (v6.0.0)
*Next-generation features for standalone security*
#### 9. **Add Integrity Monitoring** (4 hours)
```python
# src/deltaglider/security/monitor.py
import inotify
import logging
class CacheIntegrityMonitor:
"""Detect and alert on cache tampering attempts."""
def __init__(self, cache_dir: Path):
self.cache_dir = cache_dir
self.notifier = inotify.INotify()
self.watch_desc = self.notifier.add_watch(
str(cache_dir),
inotify.IN_MODIFY | inotify.IN_DELETE | inotify.IN_ATTRIB
)
self.logger = logging.getLogger("security")
async def monitor(self):
"""Monitor for unauthorized cache modifications."""
async for event in self.notifier:
if event.mask & inotify.IN_MODIFY:
# File modified - verify it was by our process
if not self._is_our_modification(event):
self.logger.critical(
f"SECURITY: Unauthorized cache modification detected: {event.path}"
)
# Immediately invalidate affected cache
Path(event.path).unlink(missing_ok=True)
elif event.mask & inotify.IN_ATTRIB:
# Permission change - always suspicious
self.logger.warning(
f"SECURITY: Cache permission change: {event.path}"
)
```
---
### **DAY 16-20: Testing & Rollout** (v6.0.0 release)
#### 10. **Security Test Suite** (8 hours)
```python
# tests/security/test_cache_attacks.py
import pytest
import os
import threading
import time
class TestCacheSecurity:
"""Test all known attack vectors."""
def test_toctou_attack_prevented(self, cache):
"""Verify TOCTOU window is eliminated."""
sha = "abc123"
cache.write_ref("bucket", "prefix", test_file, sha)
# Attacker thread tries to replace file during read
def attacker():
time.sleep(0.0001) # Try to hit the TOCTOU window
cache_path = cache.ref_path("bucket", "prefix", sha)
cache_path.write_bytes(b"malicious")
thread = threading.Thread(target=attacker)
thread.start()
# Should detect tampering
with pytest.raises(CacheCorruptionError):
cache.get_validated_ref("bucket", "prefix", sha)
def test_multi_user_isolation(self, cache):
"""Verify users can't access each other's cache."""
# Create cache as user A
cache_a = SignedCache(Path("/tmp/cache"), secret=b"key_a")
cache_a.write_ref("bucket", "prefix", test_file, "sha_a")
# Try to read as user B with different key
cache_b = SignedCache(Path("/tmp/cache"), secret=b"key_b")
with pytest.raises(CacheMissError):
cache_b.get_validated_ref("bucket", "prefix", "sha_a")
def test_cache_poisoning_prevented(self, cache):
"""Verify corrupted cache is detected."""
sha = "abc123"
cache.write_ref("bucket", "prefix", test_file, sha)
# Corrupt the cache file
cache_path = cache.ref_path("bucket", "prefix", sha)
with open(cache_path, 'ab') as f:
f.write(b"corrupted")
# Should detect corruption
with pytest.raises(CacheCorruptionError):
cache.get_validated_ref("bucket", "prefix", sha)
```
#### 11. **Migration Guide** (4 hours)
```python
# src/deltaglider/migration/v5_to_v6.py
def migrate_cache():
"""Migrate from v5 shared cache to v6 secure cache."""
old_cache = Path("/tmp/.deltaglider/cache")
if old_cache.exists():
print("WARNING: Old insecure cache detected at", old_cache)
print("This cache had security vulnerabilities and will not be migrated.")
response = input("Delete old cache? [y/N]: ")
if response.lower() == 'y':
shutil.rmtree(old_cache)
print("Old cache deleted. New secure cache will be created on demand.")
else:
print("Old cache retained at", old_cache)
print("Set DG_CACHE_DIR to use a different location.")
```
#### 12. **Performance Benchmarks** (4 hours)
```python
# benchmarks/cache_performance.py
def benchmark_cache_implementations():
"""Compare performance of cache implementations."""
implementations = [
("Filesystem (v5)", FsCacheAdapter),
("Content-Addressed", ContentAddressedCache),
("Memory", MemoryCache),
("Signed", SignedCache),
]
for name, cache_class in implementations:
cache = cache_class(test_dir)
# Measure write performance
start = time.perf_counter()
for i in range(1000):
cache.write_ref("bucket", f"prefix{i}", test_file, f"sha{i}")
write_time = time.perf_counter() - start
# Measure read performance
start = time.perf_counter()
for i in range(1000):
cache.get_validated_ref("bucket", f"prefix{i}", f"sha{i}")
read_time = time.perf_counter() - start
print(f"{name}: Write={write_time:.3f}s Read={read_time:.3f}s")
```
---
## 📊 Decision Matrix
| Solution | Security | Performance | Complexity | Breaking Change |
|----------|----------|-------------|------------|-----------------|
| Hotfix (Day 1-2) | ⭐⭐⭐ | ⭐⭐ | ⭐ | No |
| Content-Addressed | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐ | No |
| Memory Cache | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | No |
| Signed Cache | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ | No |
---
## 🎯 Recommended Approach
### For Immediate Production (Next 48 hours)
Deploy **Hotfix v5.0.3** with ephemeral cache + SHA validation
### For Next Release (1 week)
Implement **Content-Addressed Storage** (v5.1.0) - best balance of security and simplicity
### For Enterprise (1 month)
Deploy **Signed Cache** (v6.0.0) for maximum security with built-in TTL and integrity
---
## 🚦 Success Metrics
After implementation, verify:
1. **Security Tests Pass**: All attack vectors prevented
2. **Performance Maintained**: <10% degradation vs v5
3. **Zero CVEs**: No security vulnerabilities in cache
4. **User Isolation**: Multi-user systems work safely
5. **Backward Compatible**: Existing workflows unaffected
---
## 📞 Support
For questions or security concerns:
- Security Team: security@deltaglider.io
- Lead Developer: @architect
- Immediate Issues: Create SECURITY labeled issue
---
## ⚠️ Disclosure Timeline
- **Day 0**: Vulnerabilities discovered
- **Day 1**: Hotfix released (v5.0.3)
- **Day 7**: Improved version released (v5.1.0)
- **Day 30**: Full disclosure published
- **Day 45**: v6.0.0 with complete redesign
---
*Document Version: 1.0*
*Classification: SENSITIVE - INTERNAL USE ONLY*
*Last Updated: 2024-10-09*

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@@ -0,0 +1,316 @@
# boto3 Compatibility Vision
## Current State (v4.2.3)
DeltaGlider currently uses custom dataclasses for responses:
```python
from deltaglider import create_client, ListObjectsResponse, ObjectInfo
client = create_client()
response: ListObjectsResponse = client.list_objects(Bucket='my-bucket')
for obj in response.contents: # Custom field name
print(f"{obj.key}: {obj.size}") # Custom ObjectInfo dataclass
```
**Problems:**
- ❌ Not a true drop-in replacement for boto3
- ❌ Users need to learn DeltaGlider-specific types
- ❌ Can't use with tools expecting boto3 responses
- ❌ Different API surface (`.contents` vs `['Contents']`)
## Target State (v5.0.0)
DeltaGlider should return native boto3-compatible dicts with TypedDict type hints:
```python
from deltaglider import create_client, ListObjectsV2Response
client = create_client()
response: ListObjectsV2Response = client.list_objects(Bucket='my-bucket')
for obj in response['Contents']: # boto3-compatible!
print(f"{obj['Key']}: {obj['Size']}") # Works exactly like boto3
```
**Benefits:**
-**True drop-in replacement** - swap `boto3.client('s3')` with `create_client()`
-**No learning curve** - if you know boto3, you know DeltaGlider
-**Tool compatibility** - works with any library expecting boto3 types
-**Type safety** - TypedDict provides IDE autocomplete without boto3 import
-**Zero runtime overhead** - TypedDict compiles to plain dict
## Implementation Plan
### Phase 1: Type Definitions ✅ (DONE)
Created `deltaglider/types.py` with comprehensive TypedDict definitions:
```python
from typing import TypedDict, NotRequired
from datetime import datetime
class S3Object(TypedDict):
Key: str
Size: int
LastModified: datetime
ETag: NotRequired[str]
StorageClass: NotRequired[str]
class ListObjectsV2Response(TypedDict):
Contents: list[S3Object]
CommonPrefixes: NotRequired[list[dict[str, str]]]
IsTruncated: NotRequired[bool]
NextContinuationToken: NotRequired[str]
```
**Key insight:** TypedDict provides type safety at development time but compiles to plain `dict` at runtime!
### Phase 2: Refactor Client Methods (TODO)
Update all client methods to return boto3-compatible dicts:
#### `list_objects()`
**Before:**
```python
def list_objects(...) -> ListObjectsResponse: # Custom dataclass
return ListObjectsResponse(
name=bucket,
contents=[ObjectInfo(...), ...] # Custom dataclass
)
```
**After:**
```python
def list_objects(...) -> ListObjectsV2Response: # TypedDict
return {
'Contents': [
{
'Key': 'file.zip', # .delta suffix already stripped
'Size': 1024,
'LastModified': datetime(...),
'ETag': '"abc123"',
}
],
'CommonPrefixes': [{'Prefix': 'dir/'}],
'IsTruncated': False,
}
```
**Key changes:**
1. Return plain dict instead of custom dataclass
2. Use boto3 field names: `Contents` not `contents`, `Key` not `key`
3. Strip `.delta` suffix transparently (already done)
4. Hide `reference.bin` files (already done)
#### `put_object()`
**Before:**
```python
def put_object(...) -> dict[str, Any]:
return {
"ETag": etag,
"VersionId": None,
"DeltaGliderInfo": {...} # Custom field
}
```
**After:**
```python
def put_object(...) -> PutObjectResponse: # TypedDict
return {
'ETag': etag,
'ResponseMetadata': {'HTTPStatusCode': 200},
# DeltaGlider metadata goes in Metadata field
'Metadata': {
'deltaglider-is-delta': 'true',
'deltaglider-compression-ratio': '0.99'
}
}
```
#### `get_object()`
**Before:**
```python
def get_object(...) -> dict[str, Any]:
return {
"Body": data,
"ContentLength": len(data),
"DeltaGliderInfo": {...} # Custom field
}
```
**After:**
```python
def get_object(...) -> GetObjectResponse: # TypedDict
return {
'Body': data, # bytes, not StreamingBody (simpler!)
'ContentLength': len(data),
'LastModified': datetime(...),
'ETag': '"abc123"',
'Metadata': { # DeltaGlider metadata here
'deltaglider-is-delta': 'true'
}
}
```
#### `delete_object()`, `delete_objects()`, `head_object()`, etc.
All follow the same pattern: return boto3-compatible dicts with TypedDict hints.
### Phase 3: Backward Compatibility (TODO)
Keep old dataclasses for 1-2 versions with deprecation warnings:
```python
class ListObjectsResponse:
"""DEPRECATED: Use dict responses with ListObjectsV2Response type hint.
This will be removed in v6.0.0. Update your code:
Before:
response.contents[0].key
After:
response['Contents'][0]['Key']
"""
def __init__(self, data: dict):
warnings.warn(
"ListObjectsResponse dataclass is deprecated. "
"Use dict responses with ListObjectsV2Response type hint.",
DeprecationWarning,
stacklevel=2
)
self._data = data
@property
def contents(self):
return [ObjectInfo(obj) for obj in self._data.get('Contents', [])]
```
### Phase 4: Update Documentation (TODO)
1. Update all examples to use dict responses
2. Add migration guide from v4.x to v5.0
3. Update BOTO3_COMPATIBILITY.md
4. Add "Drop-in Replacement" marketing language
### Phase 5: Update Tests (TODO)
Convert all tests from:
```python
assert response.contents[0].key == "file.zip"
```
To:
```python
assert response['Contents'][0]['Key'] == "file.zip"
```
## Migration Guide (for users)
### v4.x → v5.0
**Old code (v4.x):**
```python
from deltaglider import create_client
client = create_client()
response = client.list_objects(Bucket='my-bucket')
for obj in response.contents: # Dataclass attribute
print(f"{obj.key}: {obj.size}") # Dataclass attributes
```
**New code (v5.0):**
```python
from deltaglider import create_client, ListObjectsV2Response
client = create_client()
response: ListObjectsV2Response = client.list_objects(Bucket='my-bucket')
for obj in response['Contents']: # Dict key (boto3-compatible)
print(f"{obj['Key']}: {obj['Size']}") # Dict keys (boto3-compatible)
```
**Or even simpler - no type hint needed:**
```python
client = create_client()
response = client.list_objects(Bucket='my-bucket')
for obj in response['Contents']:
print(f"{obj['Key']}: {obj['Size']}")
```
## Benefits Summary
### For Users
- **Zero learning curve** - if you know boto3, you're done
- **Drop-in replacement** - literally change one line (client creation)
- **Type safety** - TypedDict provides autocomplete without boto3 dependency
- **Tool compatibility** - works with all boto3-compatible libraries
### For DeltaGlider
- **Simpler codebase** - no custom dataclasses to maintain
- **Better marketing** - true "drop-in replacement" claim
- **Easier testing** - test against boto3 behavior directly
- **Future-proof** - if boto3 adds fields, users can access them immediately
## Technical Details
### How TypedDict Works
```python
from typing import TypedDict
class MyResponse(TypedDict):
Key: str
Size: int
# At runtime, this is just a dict!
response: MyResponse = {'Key': 'file.zip', 'Size': 1024}
print(type(response)) # <class 'dict'>
# But mypy and IDEs understand the structure
response['Key'] # ✅ Autocomplete works!
response['Nonexistent'] # ❌ Mypy error: Key 'Nonexistent' not found
```
### DeltaGlider-Specific Metadata
Store in standard boto3 `Metadata` field:
```python
{
'Key': 'file.zip',
'Size': 1024,
'Metadata': {
# DeltaGlider-specific fields (prefixed for safety)
'deltaglider-is-delta': 'true',
'deltaglider-compression-ratio': '0.99',
'deltaglider-original-size': '100000',
'deltaglider-reference-key': 'releases/v1.0.0/reference.bin',
}
}
```
This is:
- ✅ boto3-compatible (Metadata is a standard field)
- ✅ Namespaced (deltaglider- prefix prevents conflicts)
- ✅ Optional (tools can ignore it)
- ✅ Type-safe (Metadata: NotRequired[dict[str, str]])
## Status
-**Phase 1:** TypedDict definitions created
-**Phase 2:** `list_objects()` refactored to return boto3-compatible dict
-**Phase 3:** Refactor remaining methods (`put_object`, `get_object`, etc.) (TODO)
-**Phase 4:** Backward compatibility with deprecation warnings (TODO)
-**Phase 5:** Documentation updates (TODO)
-**Phase 6:** Full test coverage updates (PARTIAL - list_objects tests done)
**Current:** v4.2.3+ (Phase 2 complete - `list_objects()` boto3-compatible)
**Target:** v5.0.0 release (all phases complete)

684
docs/CACHE_MANAGEMENT.md Normal file
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# Cache Management for Long-Running Applications
## Overview
DeltaGlider uses caching to store reference files locally for efficient delta compression. However, unlike the CLI which automatically cleans up cache on exit, **programmatic SDK usage requires manual cache management** for long-running applications.
This guide explains how to manage cache in production applications, including:
- When and how to clear cache
- Encryption key management strategies
- Memory vs. filesystem cache trade-offs
- Best practices for different application types
## The Problem
**CLI (Automatic Cleanup)**:
```bash
# Cache created in /tmp/deltaglider-xyz123/
deltaglider cp file.zip s3://bucket/
# Process exits → Cache automatically deleted via atexit handler
# ✅ No manual cleanup needed
```
**SDK (Manual Cleanup Required)**:
```python
from deltaglider import create_client
client = create_client()
# Long-running application (runs for hours/days)
while True:
client.put_object(Bucket='releases', Key='file.zip', Body=data)
time.sleep(600) # Upload every 10 minutes
# ❌ Process never exits → Cache never cleaned
# ❌ Cache grows indefinitely
# ❌ Memory/disk exhaustion after days/weeks
```
## Solution: Manual Cache Management
### Basic Cache Clearing
```python
from deltaglider import create_client
client = create_client()
# Do some uploads
client.put_object(Bucket='releases', Key='file1.zip', Body=data1)
client.put_object(Bucket='releases', Key='file2.zip', Body=data2)
# Clear cache to free resources
client.clear_cache()
# ✅ All cached references removed
# ✅ Memory/disk freed
# ✅ Next upload will fetch fresh reference from S3
```
### When to Clear Cache
| Scenario | Frequency | Reason |
|----------|-----------|--------|
| **Long-running services** | Every 1-4 hours | Prevent memory/disk growth |
| **After config changes** | Immediately | Old cache is invalid |
| **High memory pressure** | As needed | Free resources |
| **Test cleanup** | After each test | Ensure clean state |
| **Scheduled jobs** | After job completes | Clean up before next run |
| **Key rotation** | After rotation | Old encrypted cache unusable |
## Cache Strategies by Application Type
### 1. Long-Running Background Service
**Scenario**: Continuous upload service running 24/7
```python
from deltaglider import create_client
import schedule
import time
import logging
logger = logging.getLogger(__name__)
client = create_client()
def upload_task():
"""Upload latest build."""
try:
with open('latest-build.zip', 'rb') as f:
response = client.put_object(
Bucket='releases',
Key=f'builds/{datetime.now().isoformat()}.zip',
Body=f
)
logger.info(f"Uploaded: {response['ETag']}")
except Exception as e:
logger.error(f"Upload failed: {e}")
def cleanup_task():
"""Clear cache to prevent growth."""
client.clear_cache()
logger.info("Cache cleared - freed resources")
# Upload every 10 minutes
schedule.every(10).minutes.do(upload_task)
# Clear cache every 2 hours (balance performance vs. memory)
schedule.every(2).hours.do(cleanup_task)
# Run indefinitely
while True:
schedule.run_pending()
time.sleep(60)
```
**Cache Clearing Frequency Guidelines**:
- Every 1 hour: High upload frequency (>100/day), memory-constrained
- Every 2-4 hours: Moderate upload frequency (10-100/day), normal memory
- Every 6-12 hours: Low upload frequency (<10/day), abundant memory
### 2. Periodic Batch Job
**Scenario**: Daily backup script
```python
from deltaglider import create_client
import glob
from pathlib import Path
def daily_backup():
"""Upload daily backups and clean up."""
client = create_client()
try:
# Upload all backup files
for backup in glob.glob('/backups/*.zip'):
with open(backup, 'rb') as f:
client.put_object(
Bucket='backups',
Key=f'daily/{Path(backup).name}',
Body=f
)
print(f"Backed up: {backup}")
finally:
# ALWAYS clear cache at end of job
client.clear_cache()
print("Cache cleared - job complete")
# Run daily via cron/systemd timer
if __name__ == '__main__':
daily_backup()
```
**Best Practice**: Always clear cache in `finally` block to ensure cleanup even if job fails.
### 3. Web Application / API Server
**Scenario**: Flask/FastAPI app with upload endpoints
```python
from fastapi import FastAPI, UploadFile, BackgroundTasks
from deltaglider import create_client
import asyncio
app = FastAPI()
# Create client once at startup
client = create_client()
async def periodic_cache_cleanup():
"""Background task to clear cache periodically."""
while True:
await asyncio.sleep(3600) # Every hour
client.clear_cache()
print("Cache cleared in background")
@app.on_event("startup")
async def startup_event():
"""Start background cache cleanup task."""
asyncio.create_task(periodic_cache_cleanup())
@app.post("/upload")
async def upload_file(file: UploadFile):
"""Upload endpoint with automatic cache management."""
content = await file.read()
response = client.put_object(
Bucket='uploads',
Key=f'files/{file.filename}',
Body=content
)
return {"message": "Uploaded", "etag": response['ETag']}
@app.post("/admin/clear-cache")
async def admin_clear_cache():
"""Manual cache clear endpoint for admin."""
client.clear_cache()
return {"message": "Cache cleared"}
```
**Best Practice**: Run periodic cache cleanup in background task, provide manual clear endpoint for emergencies.
### 4. Testing / CI/CD
**Scenario**: Test suite using DeltaGlider
```python
import pytest
from deltaglider import create_client
@pytest.fixture
def deltaglider_client():
"""Provide clean client for each test."""
client = create_client()
yield client
# ALWAYS clear cache after test
client.clear_cache()
def test_upload(deltaglider_client):
"""Test upload with automatic cleanup."""
response = deltaglider_client.put_object(
Bucket='test-bucket',
Key='test-file.zip',
Body=b'test data'
)
assert response['ETag'] is not None
# Cache automatically cleared by fixture
def test_download(deltaglider_client):
"""Test download with clean cache."""
# Cache is clean from previous test
deltaglider_client.put_object(Bucket='test', Key='file.zip', Body=b'data')
response = deltaglider_client.get_object(Bucket='test', Key='file.zip')
assert response['Body'].read() == b'data'
# Cache automatically cleared by fixture
```
**Best Practice**: Use pytest fixtures to ensure cache is cleared after each test.
### 5. AWS Lambda / Serverless
**Scenario**: Lambda function with warm container reuse
```python
import os
from deltaglider import create_client
# Initialize client outside handler (reused across invocations)
client = create_client()
# Track invocation count for cache clearing
invocation_count = 0
def lambda_handler(event, context):
"""Lambda handler with periodic cache clearing."""
global invocation_count
invocation_count += 1
try:
# Upload file
response = client.put_object(
Bucket='lambda-uploads',
Key=event['filename'],
Body=event['data']
)
# Clear cache every 50 invocations (warm container optimization)
if invocation_count % 50 == 0:
client.clear_cache()
print(f"Cache cleared after {invocation_count} invocations")
return {'statusCode': 200, 'etag': response['ETag']}
except Exception as e:
# Clear cache on error to prevent poisoned state
client.clear_cache()
return {'statusCode': 500, 'error': str(e)}
```
**Best Practice**: Clear cache periodically (every N invocations) and on errors. Lambda warm containers can reuse cache across invocations for performance.
## Encryption Key Management
DeltaGlider always encrypts cache data. Understanding key management is critical for programmatic usage.
### Ephemeral Keys (Default - Recommended)
**How It Works**:
- New encryption key generated per client instance
- Cache encrypted with instance-specific key
- Key lost when client is garbage collected
- **Maximum security** - keys never persist
**When to Use**:
- Single-process applications
- Short-lived scripts
- CI/CD pipelines
- Testing
- Maximum security requirements
**Example**:
```python
from deltaglider import create_client
# Create client (generates ephemeral key automatically)
client = create_client()
# Upload file (encrypted with ephemeral key)
client.put_object(Bucket='bucket', Key='file.zip', Body=data)
# Clear cache
client.clear_cache()
# ✅ Encrypted cache cleared
# ✅ Key was never persisted
# ✅ Perfect forward secrecy
```
**Characteristics**:
- ✅ Maximum security (keys never leave process)
- ✅ Perfect forward secrecy
- ✅ No key management overhead
- ❌ Cache not shareable between processes
- ❌ Cache not reusable after client recreation
### Persistent Keys (Advanced - Shared Cache)
**How It Works**:
- Use same encryption key across multiple processes/clients
- Key stored in environment variable or secrets manager
- All processes can read each other's encrypted cache
- **Trade-off**: Convenience vs. security
**When to Use**:
- Multi-process applications (workers, replicas)
- Shared cache across containers
- Cache persistence across application restarts
- Horizontal scaling scenarios
**Example - Environment Variable**:
```python
import os
from cryptography.fernet import Fernet
import base64
# Generate persistent key (do this ONCE, securely)
key = Fernet.generate_key()
key_b64 = base64.b64encode(key).decode('utf-8')
print(f"DG_CACHE_ENCRYPTION_KEY={key_b64}") # Store in secrets manager!
# Set in environment (or use secrets manager)
os.environ['DG_CACHE_ENCRYPTION_KEY'] = key_b64
# All client instances use same key
client1 = create_client()
client2 = create_client()
# Client1 writes to cache
client1.put_object(Bucket='bucket', Key='file.zip', Body=data)
# Client2 can read same cached data (same key!)
client2.get_object(Bucket='bucket', Key='file.zip')
# ✅ Cache shared between processes
# ⚠️ Key must be securely managed
```
**Example - AWS Secrets Manager**:
```python
import boto3
import json
from deltaglider import create_client
def get_encryption_key_from_secrets_manager():
"""Retrieve encryption key from AWS Secrets Manager."""
secrets = boto3.client('secretsmanager', region_name='us-west-2')
response = secrets.get_secret_value(SecretId='deltaglider/cache-encryption-key')
secret = json.loads(response['SecretString'])
return secret['encryption_key']
# Retrieve key securely
os.environ['DG_CACHE_ENCRYPTION_KEY'] = get_encryption_key_from_secrets_manager()
# Create client with persistent key
client = create_client()
```
**Security Best Practices for Persistent Keys**:
1. **Generate once**: Never regenerate unless rotating
2. **Store securely**: AWS Secrets Manager, HashiCorp Vault, etc.
3. **Rotate regularly**: Follow your key rotation policy
4. **Audit access**: Log who accesses encryption keys
5. **Principle of least privilege**: Only processes that need shared cache get the key
### Key Rotation
**When to Rotate**:
- Regular schedule (every 90 days recommended)
- After security incident
- When team members leave
- After key exposure
**How to Rotate**:
```python
import os
from deltaglider import create_client
# OLD KEY (existing cache encrypted with this)
old_key = os.environ.get('DG_CACHE_ENCRYPTION_KEY')
# Generate NEW KEY
from cryptography.fernet import Fernet
new_key = Fernet.generate_key()
new_key_b64 = base64.b64encode(new_key).decode('utf-8')
# Steps for rotation:
# 1. Clear old cache (encrypted with old key)
client_old = create_client() # Uses old key from env
client_old.clear_cache()
# 2. Update environment with new key
os.environ['DG_CACHE_ENCRYPTION_KEY'] = new_key_b64
# 3. Create new client with new key
client_new = create_client() # Uses new key
# 4. Continue operations
client_new.put_object(Bucket='bucket', Key='file.zip', Body=data)
# ✅ Cache now encrypted with new key
# ✅ Old encrypted cache cleared
```
## Memory vs. Filesystem Cache
### Filesystem Cache (Default)
**Characteristics**:
- Stored in `/tmp/deltaglider-*/`
- Persistent across client recreations (within same process)
- Can be shared between processes (with persistent encryption key)
- Slower than memory cache (disk I/O)
**Configuration**:
```python
import os
# Explicitly set filesystem cache (this is the default)
os.environ['DG_CACHE_BACKEND'] = 'filesystem'
from deltaglider import create_client
client = create_client()
```
**When to Use**:
- Default choice for most applications
- When cache should persist across client recreations
- Multi-process applications (with persistent key)
- Memory-constrained environments
**Cache Clearing**:
```python
client.clear_cache()
# Removes all files from /tmp/deltaglider-*/
# Frees disk space
```
### Memory Cache
**Characteristics**:
- Stored in process memory (RAM)
- Fast access (no disk I/O)
- Automatically freed when process exits
- LRU eviction prevents unlimited growth
- Not shared between processes
**Configuration**:
```python
import os
# Enable memory cache
os.environ['DG_CACHE_BACKEND'] = 'memory'
os.environ['DG_CACHE_MEMORY_SIZE_MB'] = '200' # Default: 100MB
from deltaglider import create_client
client = create_client()
```
**When to Use**:
- High-performance requirements
- Ephemeral environments (containers, Lambda)
- Short-lived applications
- CI/CD pipelines
- When disk I/O is bottleneck
**Cache Clearing**:
```python
client.clear_cache()
# Frees memory immediately
# No disk I/O
```
**LRU Eviction**:
Memory cache automatically evicts least recently used entries when size limit is reached. No manual intervention needed.
## Best Practices Summary
### ✅ DO
1. **Clear cache periodically** in long-running applications
2. **Clear cache in `finally` blocks** for batch jobs
3. **Use fixtures for tests** to ensure clean state
4. **Monitor cache size** in production
5. **Use ephemeral keys** when possible (maximum security)
6. **Store persistent keys securely** (Secrets Manager, Vault)
7. **Rotate encryption keys** regularly
8. **Use memory cache** for ephemeral environments
9. **Clear cache after config changes**
10. **Document cache strategy** for your application
### ❌ DON'T
1. **Never let cache grow unbounded** in long-running apps
2. **Don't share ephemeral encrypted cache** between processes
3. **Don't store persistent keys in code** or version control
4. **Don't forget to clear cache in tests**
5. **Don't assume cache is automatically cleaned** in SDK usage
6. **Don't use persistent keys** unless you need cross-process sharing
7. **Don't skip key rotation**
8. **Don't ignore memory limits** for memory cache
## Monitoring Cache Health
### Cache Size Tracking
```python
import os
from pathlib import Path
from deltaglider import create_client
def get_cache_size_mb(cache_dir: Path) -> float:
"""Calculate total cache size in MB."""
total_bytes = sum(f.stat().st_size for f in cache_dir.rglob('*') if f.is_file())
return total_bytes / (1024 * 1024)
# Get cache directory (ephemeral, changes per process)
cache_dir = Path(tempfile.gettempdir())
deltaglider_caches = list(cache_dir.glob('deltaglider-*'))
if deltaglider_caches:
cache_path = deltaglider_caches[0]
cache_size_mb = get_cache_size_mb(cache_path)
print(f"Cache size: {cache_size_mb:.2f} MB")
# Clear if over threshold
if cache_size_mb > 500:
client = create_client()
client.clear_cache()
print("Cache cleared - exceeded 500MB")
```
### Memory Cache Monitoring
```python
import os
os.environ['DG_CACHE_BACKEND'] = 'memory'
from deltaglider import create_client
client = create_client()
# Memory cache auto-evicts at configured limit
# Monitor via application memory usage tools (not direct API)
# Example with memory_profiler
from memory_profiler import profile
@profile
def upload_many_files():
for i in range(1000):
client.put_object(Bucket='test', Key=f'file{i}.zip', Body=b'data' * 1000)
# Check memory profile to see cache memory usage
upload_many_files()
```
## Troubleshooting
### Problem: Cache Growing Too Large
**Symptoms**:
- Disk space running out (`/tmp` filling up)
- High memory usage
**Solution**:
```python
# Implement automatic cache clearing
import psutil
client = create_client()
def smart_cache_clear():
"""Clear cache if memory/disk pressure detected."""
# Check disk space
disk = psutil.disk_usage('/tmp')
if disk.percent > 80:
client.clear_cache()
print("Cache cleared - disk pressure")
return
# Check memory usage
memory = psutil.virtual_memory()
if memory.percent > 80:
client.clear_cache()
print("Cache cleared - memory pressure")
# Call periodically
schedule.every(15).minutes.do(smart_cache_clear)
```
### Problem: Decryption Failures After Key Rotation
**Symptoms**:
- `CacheCorruptionError: Decryption failed`
- After rotating encryption keys
**Solution**:
```python
# Clear cache before using new key
old_client = create_client() # Old key
old_client.clear_cache()
# Update encryption key
os.environ['DG_CACHE_ENCRYPTION_KEY'] = new_key
# Create new client
new_client = create_client() # New key
```
### Problem: Tests Failing Due to Cached Data
**Symptoms**:
- Tests pass in isolation, fail when run together
- Unexpected data in downloads
**Solution**:
```python
# Always clear cache in test teardown
@pytest.fixture(autouse=True)
def clear_cache_after_test():
"""Automatically clear cache after every test."""
yield
# Teardown
client = create_client()
client.clear_cache()
```
## Related Documentation
- [docs/sdk/getting-started.md](sdk/getting-started.md) - SDK configuration
- [README.md](../README.md) - Docker and environment variables
- [CLAUDE.md](../CLAUDE.md) - Development guide
## Quick Reference
```python
from deltaglider import create_client
# Create client
client = create_client()
# Clear all cache
client.clear_cache()
# Use memory cache
os.environ['DG_CACHE_BACKEND'] = 'memory'
# Use persistent encryption key
os.environ['DG_CACHE_ENCRYPTION_KEY'] = 'base64-encoded-key'
```

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# DG_MAX_RATIO - Delta Compression Efficiency Guard
## Overview
`DG_MAX_RATIO` is a **safety threshold** that prevents inefficient delta compression. It controls the maximum acceptable ratio of `delta_size / original_file_size`.
**Default**: `0.5` (50%)
**Range**: `0.0` to `1.0`
**Environment Variable**: `DG_MAX_RATIO`
## The Problem It Solves
When files are **too different**, xdelta3 can create a delta file that's **almost as large as the original file** (or even larger!). This defeats the purpose of compression and wastes:
- ❌ Storage space (storing a large delta instead of the original)
- ❌ CPU time (creating and applying the delta)
- ❌ Network bandwidth (downloading delta + reference instead of just the file)
## How It Works
```
1. Upload file → Create delta using xdelta3
2. Calculate ratio = delta_size / original_file_size
3. If ratio > DG_MAX_RATIO:
❌ Discard delta, store original file directly
Else:
✅ Keep delta, save storage space
```
### Example Flow
```
Original file: 100MB
Reference file: 100MB (uploaded previously)
xdelta3 creates delta: 60MB
Ratio = 60MB / 100MB = 0.6 (60%)
With DG_MAX_RATIO=0.5:
❌ Delta rejected (60% > 50%)
Action: Store 100MB original file
Reason: Delta not efficient enough
With DG_MAX_RATIO=0.7:
✅ Delta accepted (60% ≤ 70%)
Action: Store 60MB delta
Savings: 40MB (40%)
```
## Default Value: 0.5 (50%)
**Meaning**: Only use delta compression if the delta is **≤50% of the original file size**
This default provides:
- ✅ Minimum 50% storage savings when delta compression is used
- ✅ Prevents wasting CPU on inefficient compression
- ✅ Works well for typical versioned releases (minor updates between versions)
- ✅ Balanced approach without manual tuning
## When to Adjust
### 🔽 Lower Value (More Conservative)
**Set `DG_MAX_RATIO=0.2-0.3` when:**
- Files change significantly between versions (major updates, refactors)
- Storage cost is **very high** (premium S3 tiers, small quotas)
- You want to avoid **any** inefficient compression
- You need guaranteed high-quality compression (≥70% savings)
**Example**:
```bash
export DG_MAX_RATIO=0.3
# Only accept deltas that are ≤30% of original size
# More files stored directly, but guaranteed ≥70% savings when using deltas
```
**Trade-off**:
- ✅ Higher quality compression when deltas are used
- ❌ Fewer files will use delta compression
- ❌ More direct uploads (higher storage for dissimilar files)
### 🔼 Higher Value (More Permissive)
**Set `DG_MAX_RATIO=0.6-0.8` when:**
- Files are very similar (minor patches, nightly builds, incremental changes)
- Storage cost is **cheap** (large S3 buckets, unlimited quotas)
- CPU time is **expensive** (you want to save re-uploading even with modest compression)
- You want to maximize delta compression usage
**Example**:
```bash
export DG_MAX_RATIO=0.7
# Accept deltas up to 70% of original size
# More files use delta compression, even with modest 30% savings
```
**Trade-off**:
- ✅ More files use delta compression
- ✅ Save bandwidth even with modest compression
- ❌ Some deltas may only save 20-30% space
- ❌ More CPU time spent on marginal compressions
## Real-World Scenarios
### Scenario 1: Nightly Builds (Minimal Changes) ⭐ IDEAL
```
my-app-v1.0.0.zip → 100MB (reference)
my-app-v1.0.1.zip → 100MB (0.1% code change)
Delta: 200KB (0.2% of original)
Ratio: 0.002
With ANY DG_MAX_RATIO: ✅ Use delta (99.8% savings!)
Result: Store 200KB instead of 100MB
```
**This is what DeltaGlider excels at!**
### Scenario 2: Major Version (Significant Changes)
```
my-app-v1.0.0.zip → 100MB (reference)
my-app-v2.0.0.zip → 100MB (complete rewrite, 85% different)
Delta: 85MB (85% of original)
Ratio: 0.85
With DG_MAX_RATIO=0.5: ❌ Store original (85% > 50%)
→ Stores 100MB directly
→ No compression benefit, but no CPU waste
With DG_MAX_RATIO=0.9: ✅ Use delta (85% ≤ 90%)
→ Stores 85MB delta
→ Only 15% savings, questionable benefit
```
**Recommendation**: For major versions, default `0.5` correctly rejects inefficient compression.
### Scenario 3: Different File Format (Same Content)
```
my-app-v1.0.0.zip → 100MB (ZIP archive)
my-app-v1.0.0.tar → 100MB (TAR archive, same content)
Delta: 70MB (completely different format structure)
Ratio: 0.70
With DG_MAX_RATIO=0.5: ❌ Store original (70% > 50%)
→ Stores 100MB directly
→ Correct decision: formats too different
With DG_MAX_RATIO=0.8: ✅ Use delta (70% ≤ 80%)
→ Stores 70MB delta
→ 30% savings, but CPU-intensive
```
**Recommendation**: Use consistent file formats for better compression. Default `0.5` correctly rejects cross-format compression.
### Scenario 4: Incremental Updates (Sweet Spot) ⭐
```
my-app-v1.0.0.zip → 100MB (reference)
my-app-v1.0.1.zip → 100MB (minor bugfix, 5% code change)
Delta: 5MB (5% of original)
Ratio: 0.05
With ANY DG_MAX_RATIO: ✅ Use delta (95% savings!)
Result: Store 5MB instead of 100MB
```
**This is the target use case for delta compression!**
## How to Choose the Right Value
### Decision Tree
```
Do your files have minimal changes between versions? (< 5% different)
├─ YES → Use default 0.5 ✅
│ Delta compression will work perfectly
└─ NO → Are your files significantly different? (> 50% different)
├─ YES → Lower to 0.2-0.3 🔽
│ Avoid wasting time on inefficient compression
└─ NO → Are they moderately different? (20-50% different)
├─ Storage is expensive → Lower to 0.3 🔽
│ Only high-quality compression
└─ Storage is cheap → Raise to 0.6-0.7 🔼
Accept modest savings
```
### Quick Reference Table
| File Similarity | Recommended DG_MAX_RATIO | Expected Behavior |
|----------------|--------------------------|-------------------|
| Nearly identical (< 5% change) | **0.5 (default)** | 🟢 95%+ savings |
| Minor updates (5-20% change) | **0.5 (default)** | 🟢 80-95% savings |
| Moderate changes (20-50% change) | **0.4-0.6** | 🟡 50-80% savings |
| Major changes (50-80% change) | **0.3 or lower** | 🔴 Store directly |
| Complete rewrites (> 80% change) | **0.3 or lower** | 🔴 Store directly |
### Use Cases by Industry
**Software Releases (SaaS)**:
```bash
export DG_MAX_RATIO=0.5 # Default
# Nightly builds with minor changes compress perfectly
```
**Mobile App Builds**:
```bash
export DG_MAX_RATIO=0.4 # Slightly conservative
# iOS/Android builds can vary, want quality compression only
```
**Database Backups**:
```bash
export DG_MAX_RATIO=0.7 # Permissive
# Daily backups are very similar, accept modest savings
```
**Document Archives**:
```bash
export DG_MAX_RATIO=0.6 # Moderate
# Documents change incrementally, accept good savings
```
**Video/Media Archives**:
```bash
export DG_MAX_RATIO=0.2 # Very conservative
# Media files are unique, only compress if very similar
```
## Configuration Examples
### Docker
**Conservative (Premium Storage)**:
```bash
docker run -e DG_MAX_RATIO=0.3 \
-e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY \
deltaglider/deltaglider cp file.zip s3://releases/
```
**Default (Balanced)**:
```bash
docker run -e DG_MAX_RATIO=0.5 \
-e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY \
deltaglider/deltaglider cp file.zip s3://releases/
```
**Permissive (Cheap Storage)**:
```bash
docker run -e DG_MAX_RATIO=0.7 \
-e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY \
deltaglider/deltaglider cp file.zip s3://releases/
```
### Python SDK
```python
import os
# Conservative (only high-quality compression)
os.environ['DG_MAX_RATIO'] = '0.3'
# Default (balanced)
os.environ['DG_MAX_RATIO'] = '0.5'
# Permissive (accept modest savings)
os.environ['DG_MAX_RATIO'] = '0.7'
from deltaglider import create_client
client = create_client()
summary = client.upload("file.zip", "s3://bucket/")
print(f"Delta ratio: {summary.delta_ratio:.2f}")
print(f"Used delta: {summary.is_delta}")
```
### CLI
```bash
# Conservative
export DG_MAX_RATIO=0.3
deltaglider cp my-app-v2.0.0.zip s3://releases/
# Default
export DG_MAX_RATIO=0.5
deltaglider cp my-app-v2.0.0.zip s3://releases/
# Permissive
export DG_MAX_RATIO=0.7
deltaglider cp my-app-v2.0.0.zip s3://releases/
```
### Override Per-Upload (CLI)
```bash
# Use custom ratio for specific file
deltaglider cp large-file.zip s3://releases/ --max-ratio 0.3
```
## Monitoring and Tuning
### Check Delta Ratios After Upload
```python
from deltaglider import create_client
client = create_client()
summary = client.upload("file.zip", "s3://bucket/")
print(f"Delta ratio: {summary.delta_ratio:.2f}")
print(f"Savings: {summary.savings_percent:.0f}%")
print(f"Used delta: {summary.is_delta}")
if summary.is_delta:
print(f"✅ Used delta compression (ratio {summary.delta_ratio:.2f})")
if summary.delta_ratio > 0.4:
print(f"⚠️ Consider lowering DG_MAX_RATIO for better quality")
else:
print(f"❌ Stored directly (delta would have been ratio ~{summary.delta_ratio:.2f})")
if summary.delta_ratio < 0.6:
print(f"💡 Consider raising DG_MAX_RATIO to enable compression")
```
### Batch Analysis
```python
from deltaglider import create_client
from pathlib import Path
client = create_client()
ratios = []
for file in Path("releases").glob("*.zip"):
summary = client.upload(str(file), f"s3://bucket/{file.name}")
if summary.is_delta:
ratios.append(summary.delta_ratio)
if ratios:
avg_ratio = sum(ratios) / len(ratios)
max_ratio = max(ratios)
print(f"Average delta ratio: {avg_ratio:.2f}")
print(f"Maximum delta ratio: {max_ratio:.2f}")
print(f"Files compressed: {len(ratios)}")
if avg_ratio < 0.2:
print("💡 Consider raising DG_MAX_RATIO - you're getting excellent compression")
elif max_ratio > 0.6:
print("⚠️ Consider lowering DG_MAX_RATIO - some deltas are inefficient")
```
### Optimization Strategy
1. **Start with default (0.5)**
2. **Monitor delta ratios** for 1 week of uploads
3. **Analyze results**:
- If most ratios < 0.2: Consider raising to 0.6-0.7
- If many ratios > 0.4: Consider lowering to 0.3-0.4
- If ratios vary widely: Keep default 0.5
4. **Adjust and re-test** for 1 week
5. **Repeat until optimal** for your use case
## Advanced Usage
### Dynamic Ratio Based on File Type
```python
import os
from pathlib import Path
from deltaglider import create_client
def get_optimal_ratio(file_path: str) -> float:
"""Determine optimal ratio based on file type."""
suffix = Path(file_path).suffix.lower()
# Very compressible (source code archives)
if suffix in ['.zip', '.tar', '.gz']:
return 0.6
# Moderately compressible (compiled binaries)
elif suffix in ['.jar', '.war', '.deb', '.rpm']:
return 0.5
# Rarely compressible (media, already compressed)
elif suffix in ['.mp4', '.jpg', '.png']:
return 0.2
# Default
return 0.5
file = "my-app.zip"
os.environ['DG_MAX_RATIO'] = str(get_optimal_ratio(file))
client = create_client()
summary = client.upload(file, "s3://bucket/")
```
### A/B Testing Different Ratios
```python
from deltaglider import create_client
import os
def test_ratios(file_path: str, ratios: list[float]):
"""Test different ratios and report results."""
results = []
for ratio in ratios:
os.environ['DG_MAX_RATIO'] = str(ratio)
client = create_client()
# Simulate upload (don't actually upload)
summary = client.estimate_compression(file_path, "s3://bucket/test/")
results.append({
'ratio_threshold': ratio,
'would_use_delta': summary.delta_ratio <= ratio,
'delta_ratio': summary.delta_ratio,
'savings': summary.savings_percent if summary.delta_ratio <= ratio else 0
})
return results
# Test different ratios
file = "my-app-v2.0.0.zip"
test_results = test_ratios(file, [0.3, 0.5, 0.7])
for result in test_results:
print(f"Ratio {result['ratio_threshold']}: "
f"Delta={result['would_use_delta']}, "
f"Savings={result['savings']:.0f}%")
```
## FAQ
### Q: What happens if I set DG_MAX_RATIO=1.0?
**A**: Delta compression will **always** be used, even if the delta is larger than the original file! This is generally a bad idea and defeats the purpose of the threshold.
**Example**:
```bash
export DG_MAX_RATIO=1.0
# File: 100MB, Delta: 120MB
# Ratio: 1.2
# With DG_MAX_RATIO=1.0: ✅ Use delta (1.2 > 1.0 but we accept anything ≤1.0)
# Wait, that's wrong! The delta is LARGER than the original!
# NEVER set DG_MAX_RATIO to 1.0 or higher
```
### Q: What happens if I set DG_MAX_RATIO=0.0?
**A**: Delta compression will **never** be used. All files will be stored directly. This is equivalent to disabling DeltaGlider's compression entirely.
### Q: Can I disable the ratio check?
**A**: No, and you shouldn't want to. The ratio check is a critical safety feature that prevents wasting storage and CPU on inefficient compression.
### Q: Does DG_MAX_RATIO affect downloading?
**A**: No, `DG_MAX_RATIO` only affects **uploads**. During download, DeltaGlider automatically detects whether a file is stored as a delta or directly and handles reconstruction accordingly.
### Q: Can I set different ratios for different buckets?
**A**: Not directly via environment variables, but you can change `DG_MAX_RATIO` before each upload in your code:
```python
import os
from deltaglider import create_client
# High-quality compression for production releases
os.environ['DG_MAX_RATIO'] = '0.3'
client = create_client()
client.upload("prod-release.zip", "s3://production/")
# Permissive compression for dev builds
os.environ['DG_MAX_RATIO'] = '0.7'
client = create_client()
client.upload("dev-build.zip", "s3://development/")
```
### Q: How do I know if my DG_MAX_RATIO is set correctly?
**A**: Monitor your upload summaries. If most deltas have ratios close to your threshold (e.g., 0.45-0.50 with default 0.5), you might want to lower it. If most deltas have very low ratios (e.g., < 0.2), you could raise it.
**Ideal scenario**: Most successful delta compressions have ratios < 0.3, and inefficient deltas (> 0.5) are correctly rejected.
## Summary
**`DG_MAX_RATIO` prevents wasting time and storage on inefficient delta compression.**
### Quick Takeaways
**Default 0.5 works for 90% of use cases**
**Lower values (0.2-0.3) for dissimilar files or expensive storage**
**Higher values (0.6-0.7) for very similar files or cheap storage**
**Monitor delta ratios to tune for your use case**
**Never set to 1.0 or higher (defeats the purpose)**
**Never set to 0.0 (disables delta compression entirely)**
### Golden Rule
**If you're not sure, keep the default `0.5`.**
It's a sensible balance that:
- Prevents inefficient compression (no deltas > 50% of original size)
- Allows excellent savings on similar files (most deltas are < 20%)
- Works well for typical versioned releases
- Requires no manual tuning for most use cases
---
**Related Documentation**:
- [CLAUDE.md](../CLAUDE.md) - Environment variables reference
- [README.md](../README.md) - Docker usage and configuration
- [docs/sdk/getting-started.md](sdk/getting-started.md) - SDK configuration guide

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# EC2 Region Detection & Cost Optimization
DeltaGlider automatically detects when you're running on an EC2 instance and warns you about potential cross-region data transfer charges.
## Overview
When running `deltaglider migrate` on an EC2 instance, DeltaGlider:
1. **Detects EC2 Environment**: Uses IMDSv2 (Instance Metadata Service v2) to determine if running on EC2
2. **Retrieves Instance Region**: Gets the actual AWS region where your EC2 instance is running
3. **Compares Regions**: Checks if your EC2 region matches the S3 client region
4. **Warns About Costs**: Displays clear warnings when regions don't match
## Why This Matters
**AWS Cross-Region Data Transfer Costs**:
- **Same region**: No additional charges for data transfer
- **Cross-region**: $0.02 per GB transferred (can add up quickly for large migrations)
- **NAT Gateway**: Additional charges if going through NAT
**Example Cost Impact**:
- Migrating 1TB from `us-east-1` EC2 → `us-west-2` S3 = ~$20 in data transfer charges
- Same migration within same region = $0 in data transfer charges
## Output Examples
### Scenario 1: Regions Aligned (Optimal) ✅
```bash
$ deltaglider migrate s3://old-bucket/ s3://new-bucket/
EC2 Instance: us-east-1a
S3 Client Region: us-east-1
✓ Regions aligned - no cross-region charges
Migrating from s3://old-bucket/
to s3://new-bucket/
...
```
**Result**: No warnings, optimal configuration, no extra charges.
---
### Scenario 2: Auto-Detected Mismatch (INFO)
```bash
$ deltaglider migrate s3://old-bucket/ s3://new-bucket/
EC2 Instance: us-west-2a
S3 Client Region: us-east-1
INFO: EC2 region (us-west-2) differs from configured S3 region (us-east-1)
Consider using --region us-west-2 to avoid cross-region charges.
Migrating from s3://old-bucket/
to s3://new-bucket/
...
```
**Result**: Informational warning, suggests optimal region. User didn't explicitly set wrong region, so it's likely from their AWS config.
---
### Scenario 3: Explicit Region Override Mismatch (WARNING) ⚠️
```bash
$ deltaglider migrate --region us-east-1 s3://old-bucket/ s3://new-bucket/
EC2 Instance: us-west-2a
S3 Client Region: us-east-1
⚠️ WARNING: EC2 region=us-west-2 != S3 client region=us-east-1
Expect cross-region/NAT data charges. Align regions (set client region=us-west-2)
before proceeding. Or drop --region for automatic region resolution.
Migrating from s3://old-bucket/
to s3://new-bucket/
...
```
**Result**: Strong warning because user explicitly set the wrong region with `--region` flag. They might not realize the cost implications.
---
### Scenario 4: Not on EC2
```bash
$ deltaglider migrate s3://old-bucket/ s3://new-bucket/
S3 Client Region: us-east-1
Migrating from s3://old-bucket/
to s3://new-bucket/
...
```
**Result**: Simple region display, no EC2 warnings (not applicable).
## Configuration
### Disable EC2 Detection
If you want to disable EC2 detection (e.g., for testing or if it causes issues):
```bash
export DG_DISABLE_EC2_DETECTION=true
deltaglider migrate s3://old/ s3://new/
```
Or in your script:
```python
import os
os.environ["DG_DISABLE_EC2_DETECTION"] = "true"
```
### How It Works
DeltaGlider uses **IMDSv2** (Instance Metadata Service v2) for security:
1. **Token Request** (PUT with TTL):
```
PUT http://169.254.169.254/latest/api/token
X-aws-ec2-metadata-token-ttl-seconds: 21600
```
2. **Metadata Request** (GET with token):
```
GET http://169.254.169.254/latest/meta-data/placement/region
X-aws-ec2-metadata-token: <token>
```
3. **Fast Timeout**: 1 second timeout for non-EC2 environments (no delay if not on EC2)
### Security Notes
- **IMDSv2 Only**: DeltaGlider uses the more secure IMDSv2, not the legacy IMDSv1
- **No Credentials**: Only reads metadata, never accesses credentials
- **Graceful Fallback**: Silently skips detection if IMDS unavailable
- **No Network Impact**: Uses local-only IP (169.254.169.254), never leaves the instance
## Best Practices
### For Cost Optimization
1. **Same Region**: Always try to keep EC2 instance and S3 bucket in the same region
2. **Check First**: Run with `--dry-run` to verify the setup before actual migration
3. **Use Auto-Detection**: Don't specify `--region` unless you have a specific reason
4. **Monitor Costs**: Use AWS Cost Explorer to track cross-region data transfer
### For Terraform/IaC
```hcl
# Good: EC2 and S3 in same region
resource "aws_instance" "app" {
region = "us-west-2"
}
resource "aws_s3_bucket" "data" {
region = "us-west-2" # Same region
}
```
### For Multi-Region Setups
If you MUST do cross-region transfers:
1. **Use VPC Endpoints**: Reduce NAT Gateway costs
2. **Schedule Off-Peak**: AWS charges less during off-peak hours in some regions
3. **Consider S3 Transfer Acceleration**: May be cheaper for very large transfers
4. **Batch Operations**: Minimize number of API calls
## Technical Details
### EC2MetadataAdapter
Location: `src/deltaglider/adapters/ec2_metadata.py`
Key methods:
- `is_running_on_ec2()`: Detects EC2 environment
- `get_region()`: Returns AWS region code (e.g., "us-east-1")
- `get_availability_zone()`: Returns AZ (e.g., "us-east-1a")
### Region Logging
Location: `src/deltaglider/app/cli/aws_compat.py`
Function: `log_aws_region(service, region_override=False)`
Logic:
- If not EC2: Show S3 region only
- If EC2 + regions match: Green checkmark ✅
- If EC2 + auto-detected mismatch: Blue INFO
- If EC2 + `--region` mismatch: Yellow WARNING ⚠️
## Troubleshooting
### "Cannot connect to IMDS"
**Cause**: Network policy blocks access to 169.254.169.254
**Solution**:
```bash
# Test IMDS connectivity
TOKEN=$(curl -X PUT "http://169.254.169.254/latest/api/token" \
-H "X-aws-ec2-metadata-token-ttl-seconds: 21600")
curl -H "X-aws-ec2-metadata-token: $TOKEN" \
http://169.254.169.254/latest/meta-data/placement/region
# If it fails, disable detection
export DG_DISABLE_EC2_DETECTION=true
```
### "Wrong region detected"
**Cause**: Cached metadata or race condition
**Solution**: DeltaGlider caches metadata for performance. Restart the process to refresh.
### "Warning appears but I want cross-region"
**Cause**: You intentionally need cross-region transfer
**Solution**: This is just a warning, not an error. The migration will proceed. The warning helps you confirm you understand the cost implications.
## FAQ
**Q: Does this slow down my migrations?**
A: No. EC2 detection happens once before migration starts (< 100ms). It doesn't affect migration performance.
**Q: What if I'm not on EC2 but the detection is slow?**
A: The timeout is 1 second. If IMDS is unreachable, it fails fast. Disable with `DG_DISABLE_EC2_DETECTION=true`.
**Q: Does this work on Fargate/ECS/Lambda?**
A: Yes! All AWS compute services support IMDSv2. The detection works the same way.
**Q: Can I use this with LocalStack/MinIO?**
A: Yes. When using `--endpoint-url`, DeltaGlider skips EC2 detection (not applicable for non-AWS S3).
**Q: Will this detect VPC endpoints?**
A: No. VPC endpoints don't change the "region" from an EC2 perspective. The warning still applies if regions don't match.
## Related Documentation
- [AWS Data Transfer Pricing](https://aws.amazon.com/ec2/pricing/on-demand/#Data_Transfer)
- [AWS IMDSv2 Documentation](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/configuring-instance-metadata-service.html)
- [S3 Transfer Costs](https://aws.amazon.com/s3/pricing/)

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# Metadata Issue Diagnosis and Resolution
## Issue Summary
**Date**: 2025-10-14
**Severity**: Medium (affects stats accuracy, not functionality)
**Status**: Diagnosed, enhanced logging added
## The Problem
When running `deltaglider stats`, you saw warnings like:
```
Delta build/1.66.1/universal/readonlyrest_kbn_universal-1.66.1_es9.1.3.zip.delta:
no original_size metadata (original_size=342104, size=342104).
Using compressed size as fallback. This may undercount space savings.
```
This indicates that delta files are missing the `file_size` metadata key, which causes stats to undercount compression savings.
## Root Cause
The delta files in your bucket **do not have S3 object metadata** attached to them. Specifically, they're missing the `file_size` key that DeltaGlider uses to calculate the original file size before compression.
### Why Metadata is Missing
Possible causes (in order of likelihood):
1. **Uploaded with older DeltaGlider version**: Files uploaded before `file_size` metadata was added
2. **Direct S3 upload**: Files copied directly via AWS CLI, s3cmd, or other tools (bypassing DeltaGlider)
3. **Upload failure**: Metadata write failed during upload but file upload succeeded
4. **S3 storage issue**: Metadata was lost due to S3 provider issue (rare)
### What DeltaGlider Expects
When DeltaGlider uploads a delta file, it stores these metadata keys:
```python
{
"tool": "deltaglider/5.x.x",
"original_name": "file.zip",
"file_sha256": "abc123...",
"file_size": "1048576", # ← MISSING in your files
"created_at": "2025-01-01T00:00:00Z",
"ref_key": "prefix/reference.bin",
"ref_sha256": "def456...",
"delta_size": "524288",
"delta_cmd": "xdelta3 -e -9 -s reference.bin file.zip file.zip.delta"
}
```
Without `file_size`, DeltaGlider can't calculate the space savings accurately.
## Impact
### What Works
- ✅ File upload/download - completely unaffected
- ✅ Delta compression - works normally
- ✅ Verification - integrity checks work fine
- ✅ All other operations - sync, ls, cp, etc.
### What's Affected
-**Stats accuracy**: Compression metrics are undercounted
- Files without metadata: counted as if they saved 0 bytes
- Actual compression ratio: underestimated
- Space saved: underestimated
### Example Impact
If you have 100 delta files:
- 90 files with metadata: accurate stats
- 10 files without metadata: counted at compressed size (no savings shown)
- **Result**: Stats show ~90% of actual compression savings
## The Fix (Already Applied)
### Enhanced Logging
We've improved the logging in `src/deltaglider/client_operations/stats.py` to help diagnose the issue:
**1. During metadata fetch (lines 317-333)**:
```python
if "file_size" in metadata:
original_size = int(metadata["file_size"])
logger.debug(f"Delta {key}: using original_size={original_size} from metadata")
else:
logger.warning(
f"Delta {key}: metadata missing 'file_size' key. "
f"Available keys: {list(metadata.keys())}. "
f"Using compressed size={size} as fallback"
)
```
This will show you exactly which metadata keys ARE present on the object.
**2. During stats calculation (lines 395-405)**:
```python
logger.warning(
f"Delta {obj.key}: no original_size metadata "
f"(original_size={obj.original_size}, size={obj.size}). "
f"Using compressed size as fallback. "
f"This may undercount space savings."
)
```
This shows both values so you can see if they're equal (metadata missing) or different (metadata present).
### CLI Help Improvement
We've also improved the `stats` command help (line 750):
```python
@cli.command(short_help="Get bucket statistics and compression metrics")
```
And enhanced the option descriptions to be more informative.
## Verification
To check which files are missing metadata, you can use the diagnostic script:
```bash
# Create and run the metadata checker
python scripts/check_metadata.py <your-bucket-name>
```
This will show:
- Total delta files
- Files with complete metadata
- Files missing metadata
- Specific missing fields for each file
## Resolution Options
### Option 1: Re-upload Files (Recommended)
Re-uploading files will attach proper metadata:
```bash
# Re-upload a single file
deltaglider cp local-file.zip s3://bucket/path/file.zip
# Re-upload a directory
deltaglider sync local-dir/ s3://bucket/path/
```
**Pros**:
- Accurate stats for all files
- Proper metadata for future operations
- One-time fix
**Cons**:
- Takes time to re-upload
- Uses bandwidth
### Option 2: Accept Inaccurate Stats
Keep files as-is and accept that stats are undercounted:
**Pros**:
- No work required
- Files still work perfectly for download/verification
**Cons**:
- Stats show less compression than actually achieved
- Missing metadata for future features
### Option 3: Metadata Repair Tool (Future)
We could create a tool that:
1. Downloads each delta file
2. Reconstructs it to get original size
3. Updates metadata in-place
**Status**: Not implemented yet, but feasible if needed.
## Prevention
For future uploads, DeltaGlider **will always** attach complete metadata (assuming current version is used).
The code in `src/deltaglider/core/service.py` (lines 445-467) ensures metadata is set:
```python
delta_meta = DeltaMeta(
tool=self.tool_version,
original_name=original_name,
file_sha256=file_sha256,
file_size=file_size, # ← Always set
created_at=self.clock.now(),
ref_key=ref_key,
ref_sha256=ref_sha256,
delta_size=delta_size,
delta_cmd=f"xdelta3 -e -9 -s reference.bin {original_name} {original_name}.delta",
)
self.storage.put(
full_delta_key,
delta_path,
delta_meta.to_dict(), # ← Includes file_size
)
```
## Testing
After reinstalling from source, run stats with enhanced logging:
```bash
# Install from source
pip install -e .
# Run stats with INFO logging to see detailed messages
DG_LOG_LEVEL=INFO deltaglider stats mybucket --detailed
# Look for warnings like:
# "Delta X: metadata missing 'file_size' key. Available keys: [...]"
```
The warning will now show which metadata keys ARE present, helping you understand if:
- Metadata is completely empty: `Available keys: []`
- Metadata exists but incomplete: `Available keys: ['tool', 'ref_key', ...]`
## Summary
| Aspect | Status |
|--------|--------|
| File operations | ✅ Unaffected |
| Stats accuracy | ⚠️ Undercounted for files missing metadata |
| Logging | ✅ Enhanced to show missing keys |
| Future uploads | ✅ Will have complete metadata |
| Resolution | 📋 Re-upload or accept inaccuracy |
## Related Files
- `src/deltaglider/client_operations/stats.py` - Enhanced logging
- `src/deltaglider/core/service.py` - Metadata creation
- `src/deltaglider/core/models.py` - DeltaMeta definition
- `scripts/check_metadata.py` - Diagnostic tool (NEW)
- `docs/PAGINATION_BUG_FIX.md` - Related performance fix

258
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# Pagination Bug Fix - Critical Issue Resolution
## Summary
**Date**: 2025-10-14
**Severity**: Critical (infinite loop causing operations to never complete)
**Status**: Fixed
Fixed a critical pagination bug that caused S3 LIST operations to loop infinitely, returning the same objects repeatedly instead of advancing through the bucket.
## The Bug
### Symptoms
- LIST operations would take minutes or never complete
- Pagination logs showed linear growth: page 10 = 9,000 objects, page 20 = 19,000 objects, etc.
- Buckets with ~hundreds of objects showed 169,000+ objects after 170+ pages
- System meters showed continuous 3MB/s download during listing
- Operation would eventually hit max_iterations limit (10,000 pages) and return partial results
### Root Cause
The code was using **StartAfter** with **NextContinuationToken**, which is incorrect according to AWS S3 API:
**Incorrect behavior (before fix)**:
```python
# In list_objects_page() call
response = storage.list_objects(
bucket=bucket,
start_after=page.next_continuation_token, # ❌ WRONG!
)
# In storage_s3.py
if start_after:
params["StartAfter"] = start_after # ❌ Expects object key, not token!
```
**Problem**:
- `NextContinuationToken` is an opaque token from S3's `list_objects_v2` response
- `StartAfter` expects an **actual object key** (string), not a continuation token
- When boto3 receives an invalid StartAfter value (a token instead of a key), it ignores it and restarts from the beginning
- This caused pagination to restart on every page, returning the same objects repeatedly
### Why It Happened
The S3 LIST pagination API has two different mechanisms:
1. **StartAfter** (S3 v1 style): Resume listing after a specific object key
- Used for the **first page** when you want to start from a specific key
- Example: `StartAfter="my-object-123.txt"`
2. **ContinuationToken** (S3 v2 style): Resume from an opaque token
- Used for **subsequent pages** in paginated results
- Example: `ContinuationToken="1vD6KR5W...encrypted_token..."`
- This is what `NextContinuationToken` from the response should be used with
Our code mixed these two mechanisms, using StartAfter for pagination when it should use ContinuationToken.
## The Fix
### Changed Files
1. **src/deltaglider/adapters/storage_s3.py**
- Added `continuation_token` parameter to `list_objects()`
- Changed boto3 call to use `ContinuationToken` instead of `StartAfter` for pagination
- Kept `StartAfter` support for initial page positioning
2. **src/deltaglider/core/object_listing.py**
- Added `continuation_token` parameter to `list_objects_page()`
- Changed `list_all_objects()` to use `continuation_token` variable instead of `start_after`
- Updated pagination loop to pass continuation tokens correctly
- Added debug logging showing continuation token in use
### Code Changes
**storage_s3.py - Before**:
```python
def list_objects(
self,
bucket: str,
prefix: str = "",
delimiter: str = "",
max_keys: int = 1000,
start_after: str | None = None,
) -> dict[str, Any]:
params: dict[str, Any] = {"Bucket": bucket, "MaxKeys": max_keys}
if start_after:
params["StartAfter"] = start_after # ❌ Used for pagination
response = self.client.list_objects_v2(**params)
```
**storage_s3.py - After**:
```python
def list_objects(
self,
bucket: str,
prefix: str = "",
delimiter: str = "",
max_keys: int = 1000,
start_after: str | None = None,
continuation_token: str | None = None, # ✅ NEW
) -> dict[str, Any]:
params: dict[str, Any] = {"Bucket": bucket, "MaxKeys": max_keys}
# ✅ Use ContinuationToken for pagination, StartAfter only for first page
if continuation_token:
params["ContinuationToken"] = continuation_token
elif start_after:
params["StartAfter"] = start_after
response = self.client.list_objects_v2(**params)
```
**object_listing.py - Before**:
```python
def list_all_objects(...) -> ObjectListing:
aggregated = ObjectListing()
start_after: str | None = None # ❌ Wrong variable name
while True:
page = list_objects_page(
storage,
bucket=bucket,
start_after=start_after, # ❌ Passing token as start_after
)
aggregated.objects.extend(page.objects)
if not page.is_truncated:
break
start_after = page.next_continuation_token # ❌ Token → start_after
```
**object_listing.py - After**:
```python
def list_all_objects(...) -> ObjectListing:
aggregated = ObjectListing()
continuation_token: str | None = None # ✅ Correct variable
while True:
page = list_objects_page(
storage,
bucket=bucket,
continuation_token=continuation_token, # ✅ Token → token
)
aggregated.objects.extend(page.objects)
if not page.is_truncated:
break
continuation_token = page.next_continuation_token # ✅ Token → token
```
## Testing
### Unit Tests
Created comprehensive unit tests in `tests/unit/test_object_listing.py`:
1. **test_list_objects_page_passes_continuation_token**: Verifies token is passed correctly
2. **test_list_all_objects_uses_continuation_token_for_pagination**: Verifies 3-page pagination works
3. **test_list_all_objects_prevents_infinite_loop**: Verifies max_iterations protection
### Manual Verification
Created verification script that checks for:
- `continuation_token` parameter in both files
- `ContinuationToken` usage in boto3 call
- Token priority logic (`if continuation_token:` before `elif start_after:`)
- Correct variable names throughout pagination loop
All checks passed ✅
## Expected Behavior After Fix
### Before (Broken)
```
[21:26:16.663] LIST pagination: page 1, 0 objects so far
[21:26:18.884] LIST pagination: page 10, 9000 objects so far
[21:26:20.930] LIST pagination: page 20, 19000 objects so far
[21:26:52.290] LIST pagination: page 170, 169000 objects so far
... continues indefinitely ...
```
### After (Fixed)
```
[21:26:16.663] LIST pagination: page 1, 0 objects so far
[21:26:17.012] LIST pagination: page 2, 1000 objects so far, token=AbCd1234EfGh5678...
[21:26:17.089] LIST complete: 2 pages, 1234 objects total in 0.43s
```
## Performance Impact
For a bucket with ~1,000 objects:
**Before**:
- 170+ pages × ~200ms per page = 34+ seconds
- Would eventually timeout or hit max_iterations
**After**:
- 2 pages × ~200ms per page = <1 second
- ~34x improvement for this case
- Actual speedup scales with bucket size (more objects = bigger speedup)
For a bucket with 200,000 objects (typical production case):
- **Before**: Would never complete (would hit 10,000 page limit)
- **After**: ~200 pages × ~200ms = ~40 seconds (200x fewer pages!)
## AWS S3 Pagination Documentation Reference
From AWS S3 API documentation:
> **ContinuationToken** (string) - Indicates that the list is being continued on this bucket with a token. ContinuationToken is obfuscated and is not a real key.
>
> **StartAfter** (string) - Starts after this specified key. StartAfter can be any key in the bucket.
>
> **NextContinuationToken** (string) - NextContinuationToken is sent when isTruncated is true, which means there are more keys in the bucket that can be listed. The next list requests to Amazon S3 can be continued with this NextContinuationToken.
Source: [AWS S3 ListObjectsV2 API Documentation](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListObjectsV2.html)
## Related Issues
This bug also affected:
- `get_bucket_stats()` - Would take 20+ minutes due to infinite pagination
- Any operation using `list_all_objects()` - sync, ls, etc.
All these operations are now fixed by this pagination fix.
## Prevention
To prevent similar issues in the future:
1.**Unit tests added**: Verify pagination token handling
2.**Debug logging added**: Shows continuation token in use
3.**Type checking**: mypy catches parameter mismatches
4.**Max iterations limit**: Prevents truly infinite loops (fails safely)
5.**Documentation**: This document explains the fix
## Verification Checklist
- [x] Code changes implemented
- [x] Unit tests added
- [x] Type checking passes (mypy)
- [x] Linting passes (ruff)
- [x] Manual verification script passes
- [x] Documentation created
- [x] Performance characteristics documented
- [x] AWS API documentation referenced
## Author Notes
This was a classic case of mixing two similar but different API mechanisms. The bug was subtle because:
1. boto3 didn't throw an error - it silently ignored the invalid StartAfter value
2. The pagination appeared to work (returned objects), just the wrong objects
3. The linear growth pattern (9K, 19K, 29K) made it look like a counting bug, not a pagination bug
The fix is simple but critical: use the right parameter (`ContinuationToken`) with the right value (`NextContinuationToken`).

342
docs/STATS_CACHING.md Normal file
View File

@@ -0,0 +1,342 @@
# Bucket Statistics Caching
**TL;DR**: Bucket stats are now cached in S3 with automatic validation. What took 20 minutes now takes ~100ms when the bucket hasn't changed.
## Overview
DeltaGlider's `get_bucket_stats()` operation now includes intelligent S3-based caching that dramatically improves performance for read-heavy workloads while maintaining accuracy through automatic validation.
## The Problem
Computing bucket statistics requires:
1. **LIST operation**: Get all objects (~50-100ms per 1000 objects)
2. **HEAD operations**: Fetch metadata for delta files (expensive!)
- For a bucket with 10,000 delta files: 10,000 HEAD calls
- Even with 10 parallel workers: ~1,000 sequential batches
- At ~100ms per batch: **100+ seconds minimum**
- With network issues or throttling: **20+ minutes** 😱
This made monitoring dashboards and repeated stats checks impractical.
## The Solution
### S3-Based Cache with Automatic Validation
Statistics are cached in S3 at `.deltaglider/stats_{mode}.json` (one per mode). On every call:
1. **Quick LIST operation** (~50-100ms) - always performed for validation
2. **Compare** current object_count + compressed_size with cache
3. **If unchanged** → Return cached stats instantly ✅ (**~100ms total**)
4. **If changed** → Recompute and update cache automatically
### Three Stats Modes
```bash
# Quick mode (default): Fast listing-only, approximate compression metrics
deltaglider stats my-bucket
# Sampled mode: One HEAD per deltaspace, balanced accuracy/speed
deltaglider stats my-bucket --sampled
# Detailed mode: All HEAD calls, most accurate (slowest)
deltaglider stats my-bucket --detailed
```
Each mode has its own independent cache file.
## Performance
| Scenario | Before | After | Speedup |
|----------|--------|-------|---------|
| **First run** (cold cache) | 20 min | 20 min | 1x (must compute) |
| **Bucket unchanged** (warm cache) | 20 min | **100ms** | **200x** ✨ |
| **Bucket changed** (stale cache) | 20 min | 20 min | 1x (auto-recompute) |
| **Dashboard monitoring** | 20 min/check | **100ms/check** | **200x** ✨ |
## CLI Usage
### Basic Usage
```bash
# Use cache (default behavior)
deltaglider stats my-bucket
# Force recomputation even if cache valid
deltaglider stats my-bucket --refresh
# Skip cache entirely (both read and write)
deltaglider stats my-bucket --no-cache
# Different modes with caching
deltaglider stats my-bucket --sampled
deltaglider stats my-bucket --detailed
```
### Cache Control Flags
| Flag | Description | Use Case |
|------|-------------|----------|
| *(none)* | Use cache if valid | **Default** - Fast monitoring |
| `--refresh` | Force recomputation | Updated data needed now |
| `--no-cache` | Skip caching entirely | Testing, one-off analysis |
| `--sampled` | Balanced mode | Good accuracy, faster than detailed |
| `--detailed` | Most accurate mode | Analytics, reports |
## Python SDK Usage
```python
from deltaglider import create_client
client = create_client()
# Use cache (fast, ~100ms with cache hit)
stats = client.get_bucket_stats('releases')
# Force refresh (slow, recomputes everything)
stats = client.get_bucket_stats('releases', refresh_cache=True)
# Skip cache entirely
stats = client.get_bucket_stats('releases', use_cache=False)
# Different modes with caching
stats = client.get_bucket_stats('releases', mode='quick') # Fast
stats = client.get_bucket_stats('releases', mode='sampled') # Balanced
stats = client.get_bucket_stats('releases', mode='detailed') # Accurate
```
## Cache Structure
Cache files are stored at `.deltaglider/stats_{mode}.json` in your bucket:
```json
{
"version": "1.0",
"mode": "quick",
"computed_at": "2025-10-14T10:30:00Z",
"validation": {
"object_count": 1523,
"compressed_size": 1234567890
},
"stats": {
"bucket": "releases",
"object_count": 1523,
"total_size": 50000000000,
"compressed_size": 1234567890,
"space_saved": 48765432110,
"average_compression_ratio": 0.9753,
"delta_objects": 1500,
"direct_objects": 23
}
}
```
## How Validation Works
**Smart Staleness Detection**:
1. Always perform quick LIST operation (required anyway, ~50-100ms)
2. Calculate current `object_count` and `compressed_size` from LIST
3. Compare with cached values
4. If **both match** → Cache valid, return instantly
5. If **either differs** → Bucket changed, recompute automatically
This catches:
- ✅ Objects added (count increases)
- ✅ Objects removed (count decreases)
- ✅ Objects replaced (size changes)
- ✅ Content modified (size changes)
**Edge Case**: If only metadata changes (tags, headers) but not content/count/size, cache remains valid. This is acceptable since metadata changes are rare and don't affect core statistics.
## Use Cases
### ✅ Perfect For
1. **Monitoring Dashboards**
- Check stats every minute
- Bucket rarely changes
- **20 min → 100ms per check** ✨
2. **CI/CD Status Checks**
- Verify upload success
- Check compression effectiveness
- Near-instant feedback
3. **Repeated Analysis**
- Multiple stats queries during investigation
- Cache persists across sessions
- Huge time savings
### ⚠️ Less Beneficial For
1. **Write-Heavy Buckets**
- Bucket changes on every check
- Cache always stale
- **No benefit, but no harm either** (graceful degradation)
2. **One-Off Queries**
- Single stats check
- Cache doesn't help (cold cache)
- Still works normally
## Cache Management
### Automatic Management
- **Creation**: Automatic on first `get_bucket_stats()` call
- **Validation**: Automatic on every call (always current)
- **Updates**: Automatic when bucket changes
- **Cleanup**: Not needed (cache files are tiny ~1-10KB)
### Manual Management
```bash
# View cache files
deltaglider ls s3://my-bucket/.deltaglider/
# Delete cache manually (will be recreated automatically)
deltaglider rm s3://my-bucket/.deltaglider/stats_quick.json
deltaglider rm s3://my-bucket/.deltaglider/stats_sampled.json
deltaglider rm s3://my-bucket/.deltaglider/stats_detailed.json
# Or delete entire .deltaglider prefix
deltaglider rm -r s3://my-bucket/.deltaglider/
```
## Technical Details
### Cache Files
- **Location**: `.deltaglider/` prefix in each bucket
- **Naming**: `stats_{mode}.json` (quick, sampled, detailed)
- **Size**: ~1-10KB per file
- **Format**: JSON with version, mode, validation data, and stats
### Validation Logic
```python
def is_cache_valid(cached, current):
"""Cache is valid if object count and size unchanged."""
return (
cached['object_count'] == current['object_count'] and
cached['compressed_size'] == current['compressed_size']
)
```
### Error Handling
Cache operations are **non-fatal**:
- ✅ Cache read fails → Compute normally, log warning
- ✅ Cache write fails → Return computed stats, log warning
- ✅ Corrupted cache → Ignore, recompute, overwrite
- ✅ Version mismatch → Ignore, recompute with new version
- ✅ Permission denied → Log warning, continue without caching
**The stats operation never fails due to cache issues.**
## Future Enhancements
Potential improvements for the future:
1. **TTL-Based Expiration**: Auto-refresh after N hours even if unchanged
2. **Cache Cleanup Command**: `deltaglider cache clear` for manual invalidation
3. **Cache Statistics**: Show hit/miss rates, staleness info
4. **Async Cache Updates**: Background refresh for very large buckets
5. **Cross-Bucket Cache**: Share reference data across related buckets
## Comparison with Old Implementation
| Aspect | Old (In-Memory) | New (S3-Based) |
|--------|----------------|----------------|
| **Storage** | Process memory | S3 bucket |
| **Persistence** | Lost on restart | Survives restarts |
| **Sharing** | Per-process | Shared across all clients |
| **Validation** | None | Automatic on every call |
| **Staleness** | Always fresh | Automatically detected |
| **Use Case** | Single session | Monitoring, dashboards |
## Examples
### Example 1: Monitoring Dashboard
```python
from deltaglider import create_client
import time
client = create_client()
while True:
# Fast stats check (~100ms with cache)
stats = client.get_bucket_stats('releases')
print(f"Objects: {stats.object_count}, "
f"Compression: {stats.average_compression_ratio:.1%}")
time.sleep(60) # Check every minute
# First run: 20 min (computes and caches)
# All subsequent runs: ~100ms (cache hit)
```
### Example 2: CI/CD Pipeline
```python
from deltaglider import create_client
client = create_client()
# Upload new release
client.upload("v2.0.0.zip", "s3://releases/v2.0.0/")
# Quick verification (fast with cache)
stats = client.get_bucket_stats('releases')
if stats.average_compression_ratio < 0.90:
print("Warning: Lower than expected compression")
```
### Example 3: Force Fresh Stats
```python
from deltaglider import create_client
client = create_client()
# Force recomputation for accurate report
stats = client.get_bucket_stats(
'releases',
mode='detailed',
refresh_cache=True
)
print(f"Accurate compression report:")
print(f" Original: {stats.total_size / 1e9:.1f} GB")
print(f" Stored: {stats.compressed_size / 1e9:.1f} GB")
print(f" Saved: {stats.space_saved / 1e9:.1f} GB ({stats.average_compression_ratio:.1%})")
```
## FAQ
**Q: Does caching affect accuracy?**
A: No! Cache is automatically validated on every call. If the bucket changed, stats are recomputed automatically.
**Q: What if I need fresh stats immediately?**
A: Use `--refresh` flag (CLI) or `refresh_cache=True` (SDK) to force recomputation.
**Q: Can I disable caching?**
A: Yes, use `--no-cache` flag (CLI) or `use_cache=False` (SDK).
**Q: How much space do cache files use?**
A: ~1-10KB per mode, negligible for any bucket.
**Q: What happens if cache write fails?**
A: The operation continues normally - computed stats are returned and a warning is logged. Caching is optional and non-fatal.
**Q: Do I need to clean up cache files?**
A: No, they're tiny and automatically managed. But you can delete `.deltaglider/` prefix if desired.
**Q: Does cache work across different modes?**
A: Each mode (quick, sampled, detailed) has its own independent cache file.
---
**Implementation**: See [PR #XX] for complete implementation details and test coverage.
**Related**: [SDK Documentation](sdk/README.md) | [CLI Reference](../README.md#cli-reference) | [Architecture](sdk/architecture.md)

View File

@@ -9,6 +9,8 @@ DeltaGlider provides AWS S3 CLI compatible commands with automatic delta compres
- `deltaglider ls [s3_url]` - List buckets and objects
- `deltaglider rm <s3_url>` - Remove objects
- `deltaglider sync <source> <destination>` - Synchronize directories
- `deltaglider migrate <source> <destination>` - Migrate S3 buckets with compression and EC2 cost warnings
- `deltaglider stats <bucket>` - Get bucket statistics and compression metrics
- `deltaglider verify <s3_url>` - Verify file integrity
### Current Usage Examples

View File

@@ -38,17 +38,29 @@ response = client.get_object(Bucket='releases', Key='v1.0.0/app.zip')
# Optimized list_objects with smart performance defaults (NEW!)
# Fast by default - no unnecessary metadata fetching
response = client.list_objects(Bucket='releases', Prefix='v1.0.0/')
for obj in response['Contents']:
print(f"{obj['Key']}: {obj['Size']} bytes")
# Pagination for large buckets
response = client.list_objects(Bucket='releases', MaxKeys=100,
ContinuationToken=response.next_continuation_token)
response = client.list_objects(Bucket='releases', MaxKeys=100)
while response.get('IsTruncated'):
# Process current page
for obj in response['Contents']:
print(obj['Key'])
# Get next page
response = client.list_objects(
Bucket='releases',
MaxKeys=100,
ContinuationToken=response.get('NextContinuationToken')
)
# Get detailed compression stats only when needed
response = client.list_objects(Bucket='releases', FetchMetadata=True) # Slower but detailed
# Quick bucket statistics
stats = client.get_bucket_stats('releases') # Fast overview
stats = client.get_bucket_stats('releases', detailed_stats=True) # With compression metrics
# Bucket statistics with intelligent S3-based caching (NEW!)
stats = client.get_bucket_stats('releases') # Fast (~100ms with cache)
stats = client.get_bucket_stats('releases', mode='detailed') # Accurate compression metrics
stats = client.get_bucket_stats('releases', refresh_cache=True) # Force fresh computation
client.delete_object(Bucket='releases', Key='old-version.zip')
```

View File

@@ -21,7 +21,6 @@ Factory function to create a configured DeltaGlider client with sensible default
def create_client(
endpoint_url: Optional[str] = None,
log_level: str = "INFO",
cache_dir: str = "/tmp/.deltaglider/cache",
**kwargs
) -> DeltaGliderClient
```
@@ -30,11 +29,12 @@ def create_client(
- **endpoint_url** (`Optional[str]`): S3 endpoint URL for MinIO, R2, or other S3-compatible storage. If None, uses AWS S3.
- **log_level** (`str`): Logging verbosity level. Options: "DEBUG", "INFO", "WARNING", "ERROR". Default: "INFO".
- **cache_dir** (`str`): Directory for local reference cache. Default: "/tmp/.deltaglider/cache".
- **kwargs**: Additional arguments passed to `DeltaService`:
- **tool_version** (`str`): Version string for metadata. Default: "deltaglider/0.1.0"
- **max_ratio** (`float`): Maximum acceptable delta/file ratio. Default: 0.5
**Security Note**: DeltaGlider automatically uses ephemeral, process-isolated cache (`/tmp/deltaglider-*`) that is cleaned up on exit. No configuration needed.
#### Returns
`DeltaGliderClient`: Configured client instance ready for use.
@@ -48,11 +48,8 @@ client = create_client()
# Custom endpoint for MinIO
client = create_client(endpoint_url="http://localhost:9000")
# Debug mode with custom cache
client = create_client(
log_level="DEBUG",
cache_dir="/var/cache/deltaglider"
)
# Debug mode
client = create_client(log_level="DEBUG")
# Custom delta ratio threshold
client = create_client(max_ratio=0.3) # Only use delta if <30% of original
@@ -94,7 +91,7 @@ def list_objects(
StartAfter: Optional[str] = None,
FetchMetadata: bool = False,
**kwargs
) -> ListObjectsResponse
) -> dict[str, Any]
```
##### Parameters
@@ -117,19 +114,32 @@ The method intelligently optimizes performance by:
2. Only fetching metadata for delta files when explicitly requested
3. Supporting efficient pagination for large buckets
##### Returns
boto3-compatible dict with:
- **Contents** (`list[dict]`): List of S3Object dicts with Key, Size, LastModified, Metadata
- **CommonPrefixes** (`list[dict]`): Optional list of common prefixes (folders)
- **IsTruncated** (`bool`): Whether more results are available
- **NextContinuationToken** (`str`): Token for next page
- **KeyCount** (`int`): Number of keys returned
##### Examples
```python
# Fast listing for UI display (no metadata fetching)
response = client.list_objects(Bucket='releases')
for obj in response['Contents']:
print(f"{obj['Key']}: {obj['Size']} bytes")
# Paginated listing for large buckets
response = client.list_objects(Bucket='releases', MaxKeys=100)
while response.is_truncated:
while response.get('IsTruncated'):
for obj in response['Contents']:
print(obj['Key'])
response = client.list_objects(
Bucket='releases',
MaxKeys=100,
ContinuationToken=response.next_continuation_token
ContinuationToken=response.get('NextContinuationToken')
)
# Get detailed compression stats (slower, only for analytics)
@@ -137,11 +147,16 @@ response = client.list_objects(
Bucket='releases',
FetchMetadata=True # Only fetches for delta files
)
for obj in response['Contents']:
metadata = obj.get('Metadata', {})
if metadata.get('deltaglider-is-delta') == 'true':
compression = metadata.get('deltaglider-compression-ratio', 'unknown')
print(f"{obj['Key']}: {compression} compression")
```
#### `get_bucket_stats`
Get statistics for a bucket with optional detailed compression metrics.
Get statistics for a bucket with optional detailed compression metrics. Results are cached per client session for performance.
```python
def get_bucket_stats(
@@ -158,16 +173,46 @@ def get_bucket_stats(
- With `detailed_stats=False`: ~50ms for any bucket size (LIST calls only)
- With `detailed_stats=True`: ~2-3s per 1000 objects (adds HEAD calls for delta files)
##### Caching Behavior
- **Session-scoped cache**: Results cached within client instance lifetime
- **Automatic invalidation**: Cache cleared on bucket mutations (put, delete, bucket operations)
- **Intelligent reuse**: Detailed stats can serve quick stat requests
- **Manual cache control**: Use `clear_cache()` to invalidate all cached stats
##### Returns
`BucketStats`: Dataclass containing:
- **bucket** (`str`): Bucket name
- **object_count** (`int`): Total number of objects
- **total_size** (`int`): Original size in bytes (before compression)
- **compressed_size** (`int`): Actual stored size in bytes
- **space_saved** (`int`): Bytes saved through compression
- **average_compression_ratio** (`float`): Average compression ratio (0.0-1.0)
- **delta_objects** (`int`): Number of delta-compressed objects
- **direct_objects** (`int`): Number of directly stored objects
##### Examples
```python
# Quick stats for dashboard display
# Quick stats for dashboard display (cached after first call)
stats = client.get_bucket_stats('releases')
print(f"Objects: {stats.object_count}, Size: {stats.total_size}")
# Detailed stats for analytics (slower but accurate)
# Second call hits cache (instant response)
stats = client.get_bucket_stats('releases')
print(f"Space saved: {stats.space_saved} bytes")
# Detailed stats for analytics (slower but accurate, also cached)
stats = client.get_bucket_stats('releases', detailed_stats=True)
print(f"Compression ratio: {stats.average_compression_ratio:.1%}")
# Quick call after detailed call reuses detailed cache (more accurate)
quick_stats = client.get_bucket_stats('releases') # Uses detailed cache
# Clear cache to force refresh
client.clear_cache()
stats = client.get_bucket_stats('releases') # Fresh computation
```
#### `put_object`
@@ -289,7 +334,7 @@ client.delete_bucket(Bucket='old-releases')
#### `list_buckets`
List all S3 buckets (boto3-compatible).
List all S3 buckets (boto3-compatible). Includes cached statistics when available.
```python
def list_buckets(
@@ -300,7 +345,32 @@ def list_buckets(
##### Returns
Dict with list of buckets and owner information (identical to boto3).
Dict with list of buckets and owner information (identical to boto3). Each bucket may include optional `DeltaGliderStats` metadata if statistics have been previously cached.
##### Response Structure
```python
{
'Buckets': [
{
'Name': 'bucket-name',
'CreationDate': datetime(2025, 1, 1),
'DeltaGliderStats': { # Optional, only if cached
'Cached': True,
'Detailed': bool, # Whether detailed stats were fetched
'ObjectCount': int,
'TotalSize': int,
'CompressedSize': int,
'SpaceSaved': int,
'AverageCompressionRatio': float,
'DeltaObjects': int,
'DirectObjects': int
}
}
],
'Owner': {...}
}
```
##### Examples
@@ -309,6 +379,17 @@ Dict with list of buckets and owner information (identical to boto3).
response = client.list_buckets()
for bucket in response['Buckets']:
print(f"{bucket['Name']} - Created: {bucket['CreationDate']}")
# Check if stats are cached
if 'DeltaGliderStats' in bucket:
stats = bucket['DeltaGliderStats']
print(f" Cached stats: {stats['ObjectCount']} objects, "
f"{stats['AverageCompressionRatio']:.1%} compression")
# Fetch stats first, then list buckets to see cached data
client.get_bucket_stats('my-bucket', detailed_stats=True)
response = client.list_buckets()
# Now 'my-bucket' will include DeltaGliderStats in response
```
### Simple API Methods
@@ -445,6 +526,104 @@ else:
# Re-upload or investigate
```
### Cache Management Methods
DeltaGlider maintains two types of caches for performance optimization:
1. **Reference cache**: Binary reference files used for delta reconstruction
2. **Statistics cache**: Bucket statistics (session-scoped)
#### `clear_cache`
Clear all cached data including reference files and bucket statistics.
```python
def clear_cache(self) -> None
```
##### Description
Removes all cached reference files from the local filesystem and invalidates all bucket statistics. Useful for:
- Forcing fresh statistics computation
- Freeing disk space in long-running applications
- Ensuring latest data after external bucket modifications
- Testing and development workflows
##### Cache Types Cleared
1. **Reference Cache**: Binary reference files stored in `/tmp/deltaglider-*/`
- Encrypted at rest with ephemeral keys
- Content-addressed storage (SHA256-based filenames)
- Automatically cleaned up on process exit
2. **Statistics Cache**: Bucket statistics cached per client session
- Metadata about compression ratios and object counts
- Session-scoped (not persisted to disk)
- Automatically invalidated on bucket mutations
##### Examples
```python
# Long-running application
client = create_client()
# Work with files
for i in range(1000):
client.upload(f"file_{i}.zip", "s3://bucket/")
# Periodic cache cleanup to prevent disk buildup
if i % 100 == 0:
client.clear_cache()
# Force fresh statistics after external changes
stats_before = client.get_bucket_stats('releases') # Cached
# ... external tool modifies bucket ...
client.clear_cache()
stats_after = client.get_bucket_stats('releases') # Fresh data
# Development workflow
client.clear_cache() # Start with clean state
```
#### `evict_cache`
Remove a specific cached reference file from the local cache.
```python
def evict_cache(self, s3_url: str) -> None
```
##### Parameters
- **s3_url** (`str`): S3 URL of the reference file to evict (e.g., `s3://bucket/prefix/reference.bin`)
##### Description
Removes a specific reference file from the cache without affecting other cached files or statistics. Useful for:
- Selective cache invalidation when specific references are updated
- Memory management in applications with many delta spaces
- Testing specific delta compression scenarios
##### Examples
```python
# Evict specific reference after update
client.upload("new-reference.zip", "s3://releases/v2.0.0/")
client.evict_cache("s3://releases/v2.0.0/reference.bin")
# Next upload will fetch fresh reference
client.upload("similar-file.zip", "s3://releases/v2.0.0/")
# Selective eviction for specific delta spaces
delta_spaces = ["v1.0.0", "v1.1.0", "v1.2.0"]
for space in delta_spaces:
client.evict_cache(f"s3://releases/{space}/reference.bin")
```
##### See Also
- [docs/CACHE_MANAGEMENT.md](../../CACHE_MANAGEMENT.md): Complete cache management guide
- `clear_cache()`: Clear all caches
#### `lifecycle_policy`
Set lifecycle policy for S3 prefix (placeholder for future implementation).
@@ -708,9 +887,10 @@ DeltaGlider respects these environment variables:
### DeltaGlider Configuration
- **DG_LOG_LEVEL**: Logging level (DEBUG, INFO, WARNING, ERROR)
- **DG_CACHE_DIR**: Local cache directory
- **DG_MAX_RATIO**: Default maximum delta ratio
**Note**: Cache is automatically managed (ephemeral, process-isolated) and requires no configuration.
### Example
```bash
@@ -721,10 +901,9 @@ export AWS_SECRET_ACCESS_KEY=minioadmin
# Configure DeltaGlider
export DG_LOG_LEVEL=DEBUG
export DG_CACHE_DIR=/var/cache/deltaglider
export DG_MAX_RATIO=0.3
# Now use normally
# Now use normally (cache managed automatically)
python my_script.py
```

View File

@@ -5,15 +5,17 @@ Real-world examples and patterns for using DeltaGlider in production application
## Table of Contents
1. [Performance-Optimized Bucket Listing](#performance-optimized-bucket-listing)
2. [Bucket Management](#bucket-management)
3. [Software Release Management](#software-release-management)
4. [Database Backup System](#database-backup-system)
5. [CI/CD Pipeline Integration](#cicd-pipeline-integration)
6. [Container Registry Storage](#container-registry-storage)
7. [Machine Learning Model Versioning](#machine-learning-model-versioning)
8. [Game Asset Distribution](#game-asset-distribution)
9. [Log Archive Management](#log-archive-management)
10. [Multi-Region Replication](#multi-region-replication)
2. [Bucket Statistics and Monitoring](#bucket-statistics-and-monitoring)
3. [Session-Level Cache Management](#session-level-cache-management)
4. [Bucket Management](#bucket-management)
5. [Software Release Management](#software-release-management)
6. [Database Backup System](#database-backup-system)
7. [CI/CD Pipeline Integration](#cicd-pipeline-integration)
8. [Container Registry Storage](#container-registry-storage)
9. [Machine Learning Model Versioning](#machine-learning-model-versioning)
10. [Game Asset Distribution](#game-asset-distribution)
11. [Log Archive Management](#log-archive-management)
12. [Multi-Region Replication](#multi-region-replication)
## Performance-Optimized Bucket Listing
@@ -199,6 +201,322 @@ performance_comparison('releases')
2. **Never Fetch for Non-Deltas**: The SDK automatically skips metadata fetching for non-delta files even when `FetchMetadata=True`.
## Bucket Statistics and Monitoring
DeltaGlider provides powerful bucket statistics with session-level caching for performance.
### Quick Dashboard Stats (Cached)
```python
from deltaglider import create_client
client = create_client()
def show_bucket_dashboard(bucket: str):
"""Display real-time bucket statistics with caching."""
# First call: computes stats (~50ms)
stats = client.get_bucket_stats(bucket)
# Second call: instant (cached)
stats = client.get_bucket_stats(bucket)
print(f"Dashboard for {stats.bucket}")
print(f"=" * 60)
print(f"Total Objects: {stats.object_count:,}")
print(f" Delta Objects: {stats.delta_objects:,}")
print(f" Direct Objects: {stats.direct_objects:,}")
print()
print(f"Original Size: {stats.total_size / (1024**3):.2f} GB")
print(f"Stored Size: {stats.compressed_size / (1024**3):.2f} GB")
print(f"Space Saved: {stats.space_saved / (1024**3):.2f} GB")
print(f"Compression Ratio: {stats.average_compression_ratio:.1%}")
# Example: Show stats for multiple buckets (each cached separately)
for bucket_name in ['releases', 'backups', 'archives']:
show_bucket_dashboard(bucket_name)
```
### Detailed Compression Analysis
```python
def detailed_compression_report(bucket: str):
"""Generate detailed compression report with accurate ratios."""
# Detailed stats fetch metadata for delta files (slower, accurate)
stats = client.get_bucket_stats(bucket, detailed_stats=True)
efficiency = (stats.space_saved / stats.total_size * 100) if stats.total_size > 0 else 0
print(f"Detailed Compression Report: {stats.bucket}")
print(f"=" * 60)
print(f"Object Distribution:")
print(f" Total: {stats.object_count:,}")
print(f" Delta-Compressed: {stats.delta_objects:,} ({stats.delta_objects/stats.object_count*100:.1f}%)")
print(f" Direct Storage: {stats.direct_objects:,} ({stats.direct_objects/stats.object_count*100:.1f}%)")
print()
print(f"Storage Efficiency:")
print(f" Original Data: {stats.total_size / (1024**3):.2f} GB")
print(f" Actual Storage: {stats.compressed_size / (1024**3):.2f} GB")
print(f" Space Saved: {stats.space_saved / (1024**3):.2f} GB")
print(f" Efficiency: {efficiency:.1f}%")
print(f" Avg Compression: {stats.average_compression_ratio:.2%}")
# Calculate estimated monthly costs (example: $0.023/GB S3 Standard)
cost_without = stats.total_size / (1024**3) * 0.023
cost_with = stats.compressed_size / (1024**3) * 0.023
monthly_savings = cost_without - cost_with
print()
print(f"Estimated Monthly S3 Costs ($0.023/GB):")
print(f" Without DeltaGlider: ${cost_without:.2f}")
print(f" With DeltaGlider: ${cost_with:.2f}")
print(f" Monthly Savings: ${monthly_savings:.2f}")
# Example: Detailed report
detailed_compression_report('releases')
```
### List Buckets with Cached Stats
```python
def list_buckets_with_stats():
"""List all buckets and show cached statistics if available."""
# Pre-fetch stats for important buckets
important_buckets = ['releases', 'backups']
for bucket_name in important_buckets:
client.get_bucket_stats(bucket_name, detailed_stats=True)
# List all buckets (includes cached stats automatically)
response = client.list_buckets()
print("All Buckets:")
print(f"{'Name':<30} {'Objects':<10} {'Compression':<15} {'Cached'}")
print("=" * 70)
for bucket in response['Buckets']:
name = bucket['Name']
# Check if stats are cached
if 'DeltaGliderStats' in bucket:
stats = bucket['DeltaGliderStats']
obj_count = f"{stats['ObjectCount']:,}"
compression = f"{stats['AverageCompressionRatio']:.1%}"
cached = "✓ (detailed)" if stats['Detailed'] else "✓ (quick)"
else:
obj_count = "N/A"
compression = "N/A"
cached = ""
print(f"{name:<30} {obj_count:<10} {compression:<15} {cached}")
# Example: List with stats
list_buckets_with_stats()
```
### Monitoring Dashboard (Real-Time)
```python
import time
def monitoring_dashboard(buckets: list[str], refresh_seconds: int = 60):
"""Real-time monitoring dashboard with periodic refresh."""
while True:
print("\033[2J\033[H") # Clear screen
print(f"DeltaGlider Monitoring Dashboard - {time.strftime('%Y-%m-%d %H:%M:%S')}")
print("=" * 80)
for bucket_name in buckets:
# Get cached stats (instant) or compute fresh
stats = client.get_bucket_stats(bucket_name)
print(f"\n{bucket_name}:")
print(f" Objects: {stats.object_count:,} | "
f"Delta: {stats.delta_objects:,} | "
f"Direct: {stats.direct_objects:,}")
print(f" Size: {stats.compressed_size/(1024**3):.2f} GB | "
f"Saved: {stats.space_saved/(1024**3):.2f} GB | "
f"Compression: {stats.average_compression_ratio:.1%}")
print(f"\n{'=' * 80}")
print(f"Refreshing in {refresh_seconds} seconds... (Ctrl+C to exit)")
time.sleep(refresh_seconds)
# Clear cache for fresh data on next iteration
client.clear_cache()
# Example: Monitor key buckets
try:
monitoring_dashboard(['releases', 'backups', 'archives'], refresh_seconds=30)
except KeyboardInterrupt:
print("\nMonitoring stopped.")
```
## Session-Level Cache Management
DeltaGlider maintains session-level caches for optimal performance in long-running applications.
### Long-Running Application Pattern
```python
from deltaglider import create_client
import time
def long_running_upload_service():
"""Upload service with periodic cache cleanup."""
client = create_client()
processed_count = 0
while True:
# Simulate file processing
files_to_upload = get_pending_files() # Your file queue
for file_path in files_to_upload:
try:
summary = client.upload(file_path, "s3://releases/")
processed_count += 1
print(f"Uploaded {file_path}: {summary.savings_percent:.0f}% saved")
# Periodic cache cleanup (every 100 files)
if processed_count % 100 == 0:
client.clear_cache()
print(f"Cache cleared after {processed_count} files")
except Exception as e:
print(f"Error uploading {file_path}: {e}")
time.sleep(60) # Check for new files every minute
# Example: Run upload service
# long_running_upload_service()
```
### Cache Invalidation After External Changes
```python
def handle_external_bucket_changes(bucket: str):
"""Refresh statistics after external tools modify bucket."""
# Get initial stats (cached)
stats_before = client.get_bucket_stats(bucket)
print(f"Before: {stats_before.object_count} objects")
# External process modifies bucket
print("External backup tool running...")
run_external_backup_tool(bucket) # Your external tool
# Clear cache to get fresh data
client.clear_cache()
# Get updated stats
stats_after = client.get_bucket_stats(bucket)
print(f"After: {stats_after.object_count} objects")
print(f"Added: {stats_after.object_count - stats_before.object_count} objects")
# Example usage
handle_external_bucket_changes('backups')
```
### Selective Cache Eviction
```python
def selective_cache_management():
"""Manage cache for specific delta spaces."""
client = create_client()
# Upload to multiple delta spaces
versions = ['v1.0.0', 'v1.1.0', 'v1.2.0']
for version in versions:
client.upload(f"app-{version}.zip", f"s3://releases/{version}/")
# Update reference for specific version
print("Updating v1.1.0 reference...")
client.upload("new-reference.zip", "s3://releases/v1.1.0/")
# Evict only v1.1.0 cache (others remain cached)
client.evict_cache("s3://releases/v1.1.0/reference.bin")
# Next upload to v1.1.0 fetches fresh reference
# v1.0.0 and v1.2.0 still use cached references
client.upload("similar-file.zip", "s3://releases/v1.1.0/")
# Example: Selective eviction
selective_cache_management()
```
### Testing with Clean Cache
```python
import pytest
from deltaglider import create_client
def test_upload_workflow():
"""Test with clean cache state."""
client = create_client()
client.clear_cache() # Start with clean state
# Test first upload (no reference exists)
summary1 = client.upload("file1.zip", "s3://test-bucket/prefix/")
assert not summary1.is_delta # First file is reference
# Test subsequent upload (uses cached reference)
summary2 = client.upload("file2.zip", "s3://test-bucket/prefix/")
assert summary2.is_delta # Should use delta
# Clear and test again
client.clear_cache()
summary3 = client.upload("file3.zip", "s3://test-bucket/prefix/")
assert summary3.is_delta # Still delta (reference in S3)
# Run test
# test_upload_workflow()
```
### Cache Performance Monitoring
```python
import time
def measure_cache_performance(bucket: str):
"""Measure performance impact of caching."""
client = create_client()
# Test 1: Cold cache
client.clear_cache()
start = time.time()
stats1 = client.get_bucket_stats(bucket, detailed_stats=True)
cold_time = (time.time() - start) * 1000
# Test 2: Warm cache
start = time.time()
stats2 = client.get_bucket_stats(bucket, detailed_stats=True)
warm_time = (time.time() - start) * 1000
# Test 3: Quick stats from detailed cache
start = time.time()
stats3 = client.get_bucket_stats(bucket, detailed_stats=False)
reuse_time = (time.time() - start) * 1000
print(f"Cache Performance for {bucket}:")
print(f" Cold Cache (detailed): {cold_time:.0f}ms")
print(f" Warm Cache (detailed): {warm_time:.0f}ms")
print(f" Cache Reuse (quick): {reuse_time:.0f}ms")
print(f" Speedup (detailed): {cold_time/warm_time:.1f}x")
print(f" Speedup (reuse): {cold_time/reuse_time:.1f}x")
# Example: Measure cache performance
measure_cache_performance('releases')
```
3. **Use Pagination**: For large buckets, use `MaxKeys` and `ContinuationToken` to paginate results.
4. **Cache Results**: If you need metadata frequently, consider caching the results to avoid repeated HEAD requests.

View File

@@ -69,6 +69,42 @@ Or via environment variable:
export AWS_ENDPOINT_URL=http://minio.local:9000
```
### DeltaGlider Configuration
DeltaGlider supports the following environment variables:
**Logging & Performance**:
- `DG_LOG_LEVEL`: Logging level (default: `INFO`, options: `DEBUG`, `INFO`, `WARNING`, `ERROR`)
- `DG_MAX_RATIO`: Maximum delta/file ratio (default: `0.5`, range: `0.0-1.0`)
- **See [DG_MAX_RATIO.md](../DG_MAX_RATIO.md) for complete tuning guide**
- Controls when to use delta compression vs. direct storage
- Lower (0.2-0.3) = conservative, only high-quality compression
- Higher (0.6-0.7) = permissive, accept modest savings
**Cache Configuration**:
- `DG_CACHE_BACKEND`: Cache backend type (default: `filesystem`, options: `filesystem`, `memory`)
- `DG_CACHE_MEMORY_SIZE_MB`: Memory cache size in MB (default: `100`)
- `DG_CACHE_ENCRYPTION_KEY`: Optional base64-encoded Fernet key for persistent encryption
**Security**:
- Encryption is **always enabled** (cannot be disabled)
- Ephemeral encryption keys per process (forward secrecy)
- Corrupted cache files automatically deleted
- Set `DG_CACHE_ENCRYPTION_KEY` only for cross-process cache sharing
**Example**:
```bash
# Use memory cache for faster performance in CI/CD
export DG_CACHE_BACKEND=memory
export DG_CACHE_MEMORY_SIZE_MB=500
# Enable debug logging
export DG_LOG_LEVEL=DEBUG
# Adjust delta compression threshold
export DG_MAX_RATIO=0.3 # More aggressive compression
```
## Your First Upload
### Basic Example

View File

@@ -0,0 +1,64 @@
"""Example: Using boto3-compatible responses without importing boto3.
This demonstrates how DeltaGlider provides full type safety and boto3 compatibility
without requiring boto3 imports in user code.
As of v5.0.0, DeltaGlider returns plain dicts (not custom dataclasses) that are
100% compatible with boto3 S3 responses. You get IDE autocomplete through TypedDict
type hints without any runtime overhead.
"""
from deltaglider import ListObjectsV2Response, S3Object, create_client
# Create client (no boto3 import needed!)
client = create_client()
# Type hints work perfectly without boto3
def process_files(bucket: str, prefix: str) -> None:
"""Process files in S3 with full type safety."""
# Return type is fully typed - IDE autocomplete works!
response: ListObjectsV2Response = client.list_objects(
Bucket=bucket, Prefix=prefix, Delimiter="/"
)
# Response is a plain dict - 100% boto3-compatible
# TypedDict provides autocomplete and type checking
for obj in response["Contents"]:
# obj is typed as S3Object - all fields have autocomplete!
key: str = obj["Key"] # ✅ IDE knows this is str
size: int = obj["Size"] # ✅ IDE knows this is int
print(f"{key}: {size} bytes")
# DeltaGlider metadata is in the standard Metadata field
metadata = obj.get("Metadata", {})
if metadata.get("deltaglider-is-delta") == "true":
compression = metadata.get("deltaglider-compression-ratio", "unknown")
print(f" └─ Delta file (compression: {compression})")
# Optional fields work too
for prefix_dict in response.get("CommonPrefixes", []):
print(f"Directory: {prefix_dict['Prefix']}")
# Pagination info
if response.get("IsTruncated"):
next_token = response.get("NextContinuationToken")
print(f"More results available, token: {next_token}")
# This is 100% compatible with boto3 code!
def works_with_boto3_or_deltaglider(s3_client) -> None:
"""This function works with EITHER boto3 or DeltaGlider client."""
# Because the response structure is identical!
response = s3_client.list_objects(Bucket="my-bucket")
for obj in response["Contents"]:
print(obj["Key"])
if __name__ == "__main__":
# Example usage
print("✅ Full type safety without boto3 imports!")
print("✅ 100% compatible with boto3")
print("✅ Drop-in replacement")
print("✅ Plain dict responses (not custom dataclasses)")
print("✅ DeltaGlider metadata in standard Metadata field")

View File

@@ -51,7 +51,9 @@ classifiers = [
dependencies = [
"boto3>=1.35.0",
"click>=8.1.0",
"cryptography>=42.0.0",
"python-dateutil>=2.9.0",
"requests>=2.32.0",
]
[project.urls]
@@ -108,6 +110,7 @@ dev-dependencies = [
"mypy>=1.13.0",
"boto3-stubs[s3]>=1.35.0",
"types-python-dateutil>=2.9.0",
"types-requests>=2.32.0",
"setuptools-scm>=8.0.0",
]

101
scripts/check_metadata.py Normal file
View File

@@ -0,0 +1,101 @@
#!/usr/bin/env python3
"""Check which delta files are missing metadata."""
import sys
from pathlib import Path
# Add src to path for imports
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from deltaglider import create_client
def check_bucket_metadata(bucket: str) -> None:
"""Check all delta files in a bucket for missing metadata.
Args:
bucket: S3 bucket name
"""
client = create_client()
print(f"Checking delta files in bucket: {bucket}\n")
print("=" * 80)
# List all objects
response = client.service.storage.list_objects(bucket=bucket, max_keys=10000)
missing_metadata = []
has_metadata = []
total_delta_files = 0
for obj in response["objects"]:
key = obj["key"]
# Only check .delta files
if not key.endswith(".delta"):
continue
total_delta_files += 1
# Get metadata
obj_head = client.service.storage.head(f"{bucket}/{key}")
if not obj_head:
print(f"{key}: Object not found")
continue
metadata = obj_head.metadata
# Check for required metadata fields
required_fields = ["file_size", "file_sha256", "ref_key", "ref_sha256", "delta_size"]
missing_fields = [f for f in required_fields if f not in metadata]
if missing_fields:
missing_metadata.append({
"key": key,
"missing_fields": missing_fields,
"has_metadata": bool(metadata),
"available_keys": list(metadata.keys()) if metadata else [],
})
status = "⚠️ MISSING"
detail = f"missing: {', '.join(missing_fields)}"
else:
has_metadata.append(key)
status = "✅ OK"
detail = f"file_size={metadata.get('file_size')}"
print(f"{status} {key}")
print(f" {detail}")
if metadata:
print(f" Available keys: {', '.join(metadata.keys())}")
print()
# Summary
print("=" * 80)
print(f"\nSummary:")
print(f" Total delta files: {total_delta_files}")
print(f" With complete metadata: {len(has_metadata)} ({len(has_metadata)/total_delta_files*100:.1f}%)")
print(f" Missing metadata: {len(missing_metadata)} ({len(missing_metadata)/total_delta_files*100:.1f}%)")
if missing_metadata:
print(f"\n❌ Files with missing metadata:")
for item in missing_metadata:
print(f" - {item['key']}")
print(f" Missing: {', '.join(item['missing_fields'])}")
if item['available_keys']:
print(f" Has: {', '.join(item['available_keys'])}")
print(f"\n💡 Recommendation:")
print(f" These files should be re-uploaded to get proper metadata and accurate stats.")
print(f" You can re-upload with: deltaglider cp <local-file> s3://{bucket}/<path>")
else:
print(f"\n✅ All delta files have complete metadata!")
if __name__ == "__main__":
if len(sys.argv) != 2:
print("Usage: python check_metadata.py <bucket-name>")
sys.exit(1)
bucket_name = sys.argv[1]
check_bucket_metadata(bucket_name)

View File

@@ -17,12 +17,26 @@ from .client_models import (
)
from .core import DeltaService, DeltaSpace, ObjectKey
# Import boto3-compatible type aliases (no boto3 import required!)
from .types import (
CopyObjectResponse,
CreateBucketResponse,
DeleteObjectResponse,
DeleteObjectsResponse,
GetObjectResponse,
HeadObjectResponse,
ListBucketsResponse,
ListObjectsV2Response,
PutObjectResponse,
S3Object,
)
__all__ = [
"__version__",
# Client
"DeltaGliderClient",
"create_client",
# Data classes
# Data classes (legacy - will be deprecated in favor of TypedDict)
"UploadSummary",
"CompressionEstimate",
"ObjectInfo",
@@ -32,4 +46,15 @@ __all__ = [
"DeltaService",
"DeltaSpace",
"ObjectKey",
# boto3-compatible types (no boto3 import needed!)
"ListObjectsV2Response",
"PutObjectResponse",
"GetObjectResponse",
"DeleteObjectResponse",
"DeleteObjectsResponse",
"HeadObjectResponse",
"ListBucketsResponse",
"CreateBucketResponse",
"CopyObjectResponse",
"S3Object",
]

View File

@@ -1,19 +1,27 @@
"""Adapters for DeltaGlider."""
from .cache_cas import ContentAddressedCache
from .cache_encrypted import EncryptedCache
from .cache_fs import FsCacheAdapter
from .cache_memory import MemoryCache
from .clock_utc import UtcClockAdapter
from .diff_xdelta import XdeltaAdapter
from .ec2_metadata import EC2MetadataAdapter
from .hash_sha import Sha256Adapter
from .logger_std import StdLoggerAdapter
from .metrics_noop import NoopMetricsAdapter
from .storage_s3 import S3StorageAdapter
__all__ = [
"S3StorageAdapter",
"XdeltaAdapter",
"Sha256Adapter",
"ContentAddressedCache",
"EC2MetadataAdapter",
"EncryptedCache",
"FsCacheAdapter",
"UtcClockAdapter",
"StdLoggerAdapter",
"MemoryCache",
"NoopMetricsAdapter",
"S3StorageAdapter",
"Sha256Adapter",
"StdLoggerAdapter",
"UtcClockAdapter",
"XdeltaAdapter",
]

View File

@@ -0,0 +1,270 @@
"""Content-Addressed Storage (CAS) cache adapter.
This adapter stores cached references using their SHA256 hash as the filename,
eliminating collision risks and enabling automatic deduplication.
"""
import hashlib
import shutil
import sys
from pathlib import Path
# Unix-only imports for file locking
if sys.platform != "win32":
import fcntl
from ..core.errors import CacheCorruptionError, CacheMissError
from ..ports.cache import CachePort
from ..ports.hash import HashPort
class ContentAddressedCache(CachePort):
"""Content-addressed storage cache using SHA256 as filename.
Key Features:
- Zero collision risk (SHA256 namespace is the filename)
- Automatic deduplication (same content = same filename)
- No metadata tracking needed (self-describing)
- Secure by design (tampering changes SHA, breaks lookup)
Storage Layout:
- base_dir/
- ab/
- cd/
- abcdef123456... (full SHA256 as filename)
The two-level directory structure (first 2 chars, next 2 chars) prevents
filesystem performance degradation from too many files in one directory.
"""
def __init__(self, base_dir: Path, hasher: HashPort):
"""Initialize content-addressed cache.
Args:
base_dir: Root directory for cache storage
hasher: Hash adapter for SHA256 computation
"""
self.base_dir = base_dir
self.hasher = hasher
# Mapping of (bucket, prefix) -> sha256 for compatibility
# This is ephemeral and only used within a single process
self._deltaspace_to_sha: dict[tuple[str, str], str] = {}
def _cas_path(self, sha256: str) -> Path:
"""Get content-addressed path from SHA256 hash.
Uses two-level directory structure for filesystem optimization:
- First 2 hex chars as L1 directory (256 buckets)
- Next 2 hex chars as L2 directory (256 buckets per L1)
- Full SHA as filename
Example: abcdef1234... -> ab/cd/abcdef1234...
Args:
sha256: Full SHA256 hash (64 hex chars)
Returns:
Path to file in content-addressed storage
"""
if len(sha256) < 4:
raise ValueError(f"Invalid SHA256: {sha256}")
# Two-level directory structure
l1_dir = sha256[:2] # First 2 chars
l2_dir = sha256[2:4] # Next 2 chars
return self.base_dir / l1_dir / l2_dir / sha256
def ref_path(self, bucket: str, prefix: str) -> Path:
"""Get path where reference should be cached.
For CAS, we need the SHA to compute the path. This method looks up
the SHA from the ephemeral mapping. If not found, it returns a
placeholder path (backward compatibility with has_ref checks).
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
Returns:
Path to cached reference (may not exist)
"""
key = (bucket, prefix)
# If we have the SHA mapping, use CAS path
if key in self._deltaspace_to_sha:
sha = self._deltaspace_to_sha[key]
return self._cas_path(sha)
# Fallback: return a non-existent placeholder
# This enables has_ref to return False for unmapped deltaspaces
return self.base_dir / "_unmapped" / bucket / prefix / "reference.bin"
def has_ref(self, bucket: str, prefix: str, sha: str) -> bool:
"""Check if reference exists with given SHA.
In CAS, existence check is simple: if file exists at SHA path,
it MUST have that SHA (content-addressed guarantee).
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
sha: Expected SHA256 hash
Returns:
True if reference exists with this SHA
"""
path = self._cas_path(sha)
return path.exists()
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get cached reference with atomic SHA validation.
In CAS, the SHA IS the filename, so if the file exists, it's already
validated by definition. We still perform an integrity check to detect
filesystem corruption.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
expected_sha: Expected SHA256 hash
Returns:
Path to validated cached file
Raises:
CacheMissError: File not found in cache
CacheCorruptionError: SHA mismatch (filesystem corruption)
"""
path = self._cas_path(expected_sha)
if not path.exists():
raise CacheMissError(f"Cache miss for SHA {expected_sha[:8]}...")
# Lock file and validate content atomically
try:
with open(path, "rb") as f:
# Acquire shared lock (Unix only)
if sys.platform != "win32":
fcntl.flock(f.fileno(), fcntl.LOCK_SH)
# Read and hash content
content = f.read()
actual_sha = hashlib.sha256(content).hexdigest()
# Release lock automatically when exiting context
# Validate SHA (should never fail in CAS unless filesystem corruption)
if actual_sha != expected_sha:
# Filesystem corruption detected
try:
path.unlink()
except OSError:
pass # Best effort cleanup
raise CacheCorruptionError(
f"Filesystem corruption detected: file {path.name} has wrong content. "
f"Expected SHA {expected_sha}, got {actual_sha}"
)
# Update mapping for ref_path compatibility
self._deltaspace_to_sha[(bucket, prefix)] = expected_sha
return path
except OSError as e:
raise CacheMissError(f"Cache read error for SHA {expected_sha[:8]}...: {e}") from e
def write_ref(self, bucket: str, prefix: str, src: Path) -> Path:
"""Cache reference file using content-addressed storage.
The file is stored at a path determined by its SHA256 hash.
If a file with the same content already exists, it's reused
(automatic deduplication).
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
src: Source file to cache
Returns:
Path to cached file (content-addressed)
"""
# Compute SHA of source file
sha = self.hasher.sha256(src)
path = self._cas_path(sha)
# If file already exists, we're done (deduplication)
if path.exists():
# Update mapping
self._deltaspace_to_sha[(bucket, prefix)] = sha
return path
# Create directory structure with secure permissions
path.parent.mkdir(parents=True, mode=0o700, exist_ok=True)
# Atomic write using temp file + rename
temp_path = path.parent / f".tmp.{sha}"
try:
shutil.copy2(src, temp_path)
# Atomic rename (POSIX guarantee)
temp_path.rename(path)
except Exception:
# Cleanup on failure
if temp_path.exists():
temp_path.unlink()
raise
# Update mapping
self._deltaspace_to_sha[(bucket, prefix)] = sha
return path
def evict(self, bucket: str, prefix: str) -> None:
"""Remove cached reference for given deltaspace.
In CAS, eviction is more complex because:
1. Multiple deltaspaces may reference the same SHA (deduplication)
2. We can't delete the file unless we know no other deltaspace uses it
For safety, we only remove the mapping, not the actual file.
Orphaned files will be cleaned up by cache expiry (future feature).
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
"""
key = (bucket, prefix)
# Remove mapping (safe operation)
if key in self._deltaspace_to_sha:
del self._deltaspace_to_sha[key]
# NOTE: We don't delete the actual CAS file because:
# - Other deltaspaces may reference the same SHA
def clear(self) -> None:
"""Clear all cached references.
Removes all cached files and mappings. This is a destructive operation
that forcibly removes the entire cache directory.
Use cases:
- Long-running applications that need to free disk space
- Manual cache invalidation
- Test cleanup
- Ensuring fresh data fetch after configuration changes
"""
import shutil
# Clear in-memory mapping
self._deltaspace_to_sha.clear()
# Remove all cache files (destructive!)
if self.base_dir.exists():
shutil.rmtree(self.base_dir, ignore_errors=True)
# Recreate base directory with secure permissions
self.base_dir.mkdir(parents=True, mode=0o700, exist_ok=True)
# - The ephemeral cache will be cleaned on process exit anyway
# - For persistent cache (future), we'd need reference counting

View File

@@ -0,0 +1,305 @@
"""Encrypted cache wrapper using Fernet symmetric encryption.
This adapter wraps any CachePort implementation and adds transparent encryption/decryption.
It uses Fernet (symmetric encryption based on AES-128-CBC with HMAC authentication).
"""
import os
from pathlib import Path
from cryptography.fernet import Fernet
from ..core.errors import CacheCorruptionError, CacheMissError
from ..ports.cache import CachePort
class EncryptedCache(CachePort):
"""Encrypted cache wrapper using Fernet symmetric encryption.
Wraps any CachePort implementation and transparently encrypts data at rest.
Uses Fernet which provides:
- AES-128-CBC encryption
- HMAC authentication (prevents tampering)
- Automatic key rotation support
- Safe for ephemeral process-isolated caches
Key Management:
- Ephemeral key generated per process (default, most secure)
- Or use DG_CACHE_ENCRYPTION_KEY env var (base64-encoded Fernet key)
- For production: use secrets management system (AWS KMS, HashiCorp Vault, etc.)
Security Properties:
- Confidentiality: Data encrypted at rest
- Integrity: HMAC prevents tampering
- Authenticity: Only valid keys can decrypt
- Forward Secrecy: Ephemeral keys destroyed on process exit
"""
def __init__(self, backend: CachePort, encryption_key: bytes | None = None):
"""Initialize encrypted cache wrapper.
Args:
backend: Underlying cache implementation (CAS, filesystem, memory, etc.)
encryption_key: Optional Fernet key (32 bytes base64-encoded).
If None, generates ephemeral key for this process.
"""
self.backend = backend
# Key management: ephemeral (default) or provided
if encryption_key is None:
# Generate ephemeral key for this process (most secure)
self._key = Fernet.generate_key()
self._ephemeral = True
else:
# Use provided key (for persistent cache scenarios)
self._key = encryption_key
self._ephemeral = False
self._cipher = Fernet(self._key)
# Mapping: (bucket, prefix) -> plaintext_sha256
# Needed because backend uses SHA for storage, but encrypted content has different SHA
self._plaintext_sha_map: dict[tuple[str, str], str] = {}
@classmethod
def from_env(cls, backend: CachePort) -> "EncryptedCache":
"""Create encrypted cache with key from environment.
Looks for DG_CACHE_ENCRYPTION_KEY environment variable.
If not found, generates ephemeral key.
Args:
backend: Underlying cache implementation
Returns:
EncryptedCache instance
"""
key_str = os.environ.get("DG_CACHE_ENCRYPTION_KEY")
if key_str:
# Decode base64-encoded key
encryption_key = key_str.encode("utf-8")
else:
# Use ephemeral key
encryption_key = None
return cls(backend, encryption_key)
def ref_path(self, bucket: str, prefix: str) -> Path:
"""Get path where reference should be cached.
Delegates to backend. Path structure determined by backend
(e.g., CAS uses SHA256-based paths).
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
Returns:
Path from backend
"""
return self.backend.ref_path(bucket, prefix)
def has_ref(self, bucket: str, prefix: str, sha: str) -> bool:
"""Check if reference exists with given SHA.
Note: SHA is of the *unencrypted* content. The backend may store
encrypted data, but we verify against original content hash.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
sha: SHA256 of unencrypted content
Returns:
True if encrypted reference exists with this SHA
"""
# Delegate to backend
# Backend may use SHA for content-addressed storage of encrypted data
return self.backend.has_ref(bucket, prefix, sha)
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get cached reference with decryption and validation.
Retrieves encrypted data from backend, decrypts it, validates SHA,
and returns path to decrypted temporary file.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
expected_sha: Expected SHA256 of *decrypted* content
Returns:
Path to decrypted validated file (temporary)
Raises:
CacheMissError: File not in cache
CacheCorruptionError: Decryption failed or SHA mismatch
"""
# Check if we have this plaintext SHA mapped
key = (bucket, prefix)
if key not in self._plaintext_sha_map:
raise CacheMissError(f"Cache miss for {bucket}/{prefix}")
# Verify the requested SHA matches our mapping
if self._plaintext_sha_map[key] != expected_sha:
raise CacheCorruptionError(
f"SHA mismatch for {bucket}/{prefix}: "
f"expected {expected_sha}, have {self._plaintext_sha_map[key]}"
)
# Get encrypted file from backend using ref_path (not validated, we validate plaintext)
encrypted_path = self.backend.ref_path(bucket, prefix)
if not encrypted_path.exists():
raise CacheMissError(f"Encrypted cache file not found for {bucket}/{prefix}")
# Read encrypted content
try:
with open(encrypted_path, "rb") as f:
encrypted_data = f.read()
except OSError as e:
raise CacheMissError(f"Cannot read encrypted cache: {e}") from e
# Decrypt
try:
decrypted_data = self._cipher.decrypt(encrypted_data)
except Exception as e:
# Fernet raises InvalidToken for tampering/wrong key
# SECURITY: Auto-delete corrupted cache files
try:
encrypted_path.unlink(missing_ok=True)
# Clean up mapping
if key in self._plaintext_sha_map:
del self._plaintext_sha_map[key]
except Exception:
pass # Best effort cleanup
raise CacheCorruptionError(
f"Decryption failed for {bucket}/{prefix}: {e}. "
f"Corrupted cache deleted automatically."
) from e
# Validate SHA of decrypted content
import hashlib
actual_sha = hashlib.sha256(decrypted_data).hexdigest()
if actual_sha != expected_sha:
# SECURITY: Auto-delete corrupted cache files
try:
encrypted_path.unlink(missing_ok=True)
# Clean up mapping
if key in self._plaintext_sha_map:
del self._plaintext_sha_map[key]
except Exception:
pass # Best effort cleanup
raise CacheCorruptionError(
f"Decrypted content SHA mismatch for {bucket}/{prefix}: "
f"expected {expected_sha}, got {actual_sha}. "
f"Corrupted cache deleted automatically."
)
# Write decrypted content to temporary file
# Use same path as encrypted file but with .decrypted suffix
decrypted_path = encrypted_path.with_suffix(".decrypted")
try:
with open(decrypted_path, "wb") as f:
f.write(decrypted_data)
except OSError as e:
raise CacheCorruptionError(f"Cannot write decrypted cache: {e}") from e
return decrypted_path
def write_ref(self, bucket: str, prefix: str, src: Path) -> Path:
"""Encrypt and cache reference file.
Reads source file, encrypts it, and stores encrypted version via backend.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
src: Source file to encrypt and cache
Returns:
Path to encrypted cached file (from backend)
"""
# Read source file
try:
with open(src, "rb") as f:
plaintext_data = f.read()
except OSError as e:
raise CacheCorruptionError(f"Cannot read source file {src}: {e}") from e
# Compute plaintext SHA for mapping
import hashlib
plaintext_sha = hashlib.sha256(plaintext_data).hexdigest()
# Encrypt
encrypted_data = self._cipher.encrypt(plaintext_data)
# Write encrypted data to temporary file
temp_encrypted = src.with_suffix(".encrypted.tmp")
try:
with open(temp_encrypted, "wb") as f:
f.write(encrypted_data)
# Store encrypted file via backend
result_path = self.backend.write_ref(bucket, prefix, temp_encrypted)
# Store mapping of plaintext SHA
key = (bucket, prefix)
self._plaintext_sha_map[key] = plaintext_sha
return result_path
finally:
# Cleanup temporary file
if temp_encrypted.exists():
temp_encrypted.unlink()
def evict(self, bucket: str, prefix: str) -> None:
"""Remove cached reference (encrypted version).
Delegates to backend. Also cleans up any .decrypted temporary files and mappings.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
"""
# Remove from plaintext SHA mapping
key = (bucket, prefix)
if key in self._plaintext_sha_map:
del self._plaintext_sha_map[key]
# Get path to potentially clean up .decrypted files
try:
path = self.backend.ref_path(bucket, prefix)
decrypted_path = path.with_suffix(".decrypted")
if decrypted_path.exists():
decrypted_path.unlink()
except Exception:
# Best effort cleanup
pass
# Evict from backend
self.backend.evict(bucket, prefix)
def clear(self) -> None:
"""Clear all cached references and encryption mappings.
Removes all cached data and clears encryption key mappings.
This is the proper way to forcibly clean up cache in long-running
applications.
Use cases:
- Long-running applications needing to free resources
- Manual cache invalidation after key rotation
- Test cleanup
- Memory pressure situations
Note: After clearing, the cache will use a fresh encryption key
(ephemeral mode) or the same persistent key (if DG_CACHE_ENCRYPTION_KEY set).
"""
# Clear encryption mapping
self._plaintext_sha_map.clear()
# Delegate to backend to clear actual files/memory
self.backend.clear()

View File

@@ -1,8 +1,15 @@
"""Filesystem cache adapter."""
import hashlib
import shutil
import sys
from pathlib import Path
# Unix-only imports for file locking
if sys.platform != "win32":
import fcntl
from ..core.errors import CacheCorruptionError, CacheMissError
from ..ports.cache import CachePort
from ..ports.hash import HashPort
@@ -29,6 +36,60 @@ class FsCacheAdapter(CachePort):
actual_sha = self.hasher.sha256(path)
return actual_sha == sha
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get cached reference with atomic SHA validation.
This method prevents TOCTOU attacks by validating the SHA at use-time,
not just at check-time.
Args:
bucket: S3 bucket name
prefix: Prefix/deltaspace within bucket
expected_sha: Expected SHA256 hash
Returns:
Path to validated cached file
Raises:
CacheMissError: File not found in cache
CacheCorruptionError: SHA mismatch detected
"""
path = self.ref_path(bucket, prefix)
if not path.exists():
raise CacheMissError(f"Cache miss for {bucket}/{prefix}")
# Lock file and validate content atomically
try:
with open(path, "rb") as f:
# Acquire shared lock (Unix only)
if sys.platform != "win32":
fcntl.flock(f.fileno(), fcntl.LOCK_SH)
# Read and hash content
content = f.read()
actual_sha = hashlib.sha256(content).hexdigest()
# Release lock automatically when exiting context
# Validate SHA
if actual_sha != expected_sha:
# File corrupted or tampered - remove it
try:
path.unlink()
except OSError:
pass # Best effort cleanup
raise CacheCorruptionError(
f"Cache corruption detected for {bucket}/{prefix}: "
f"expected {expected_sha}, got {actual_sha}"
)
return path
except OSError as e:
raise CacheMissError(f"Cache read error for {bucket}/{prefix}: {e}") from e
def write_ref(self, bucket: str, prefix: str, src: Path) -> Path:
"""Cache reference file."""
path = self.ref_path(bucket, prefix)

View File

@@ -0,0 +1,279 @@
"""In-memory cache implementation with optional size limits.
This adapter stores cached references entirely in memory, avoiding filesystem I/O.
Useful for:
- High-performance scenarios where memory is abundant
- Containerized environments with limited filesystem access
- Testing and development
"""
import hashlib
import sys
from pathlib import Path
# Unix-only imports for compatibility
if sys.platform != "win32":
import fcntl # noqa: F401
from ..core.errors import CacheCorruptionError, CacheMissError
from ..ports.cache import CachePort
from ..ports.hash import HashPort
class MemoryCache(CachePort):
"""In-memory cache implementation with LRU eviction.
Stores cached references in memory as bytes. Useful for high-performance
scenarios or when filesystem access is limited.
Features:
- Zero filesystem I/O (everything in RAM)
- Optional size limits with LRU eviction
- Thread-safe operations
- Temporary file creation for compatibility with file-based APIs
Limitations:
- Data lost on process exit (ephemeral only)
- Memory usage proportional to cache size
- Not suitable for very large reference files
Storage Layout:
- Key: (bucket, prefix) tuple
- Value: (content_bytes, sha256) tuple
"""
def __init__(
self,
hasher: HashPort,
max_size_mb: int = 100,
temp_dir: Path | None = None,
):
"""Initialize in-memory cache.
Args:
hasher: Hash adapter for SHA256 computation
max_size_mb: Maximum cache size in megabytes (default 100MB)
temp_dir: Directory for temporary files (default: system temp)
"""
self.hasher = hasher
self.max_size_bytes = max_size_mb * 1024 * 1024
# Storage: (bucket, prefix) -> (content_bytes, sha256)
self._cache: dict[tuple[str, str], tuple[bytes, str]] = {}
# Size tracking
self._current_size = 0
# Access order for LRU eviction: (bucket, prefix) list
self._access_order: list[tuple[str, str]] = []
# Temp directory for file-based API compatibility
if temp_dir is None:
import tempfile
self.temp_dir = Path(tempfile.gettempdir()) / "deltaglider-mem-cache"
else:
self.temp_dir = temp_dir
self.temp_dir.mkdir(parents=True, exist_ok=True, mode=0o700)
def _update_access(self, key: tuple[str, str]) -> None:
"""Update LRU access order.
Args:
key: Cache key (bucket, prefix)
"""
# Remove old position if exists
if key in self._access_order:
self._access_order.remove(key)
# Add to end (most recently used)
self._access_order.append(key)
def _evict_lru(self, needed_bytes: int) -> None:
"""Evict least recently used entries to free space.
Args:
needed_bytes: Bytes needed for new entry
"""
while self._current_size + needed_bytes > self.max_size_bytes and self._access_order:
# Evict least recently used
lru_key = self._access_order[0]
bucket, prefix = lru_key
# Remove from cache
if lru_key in self._cache:
content, _ = self._cache[lru_key]
self._current_size -= len(content)
del self._cache[lru_key]
# Remove from access order
self._access_order.remove(lru_key)
def ref_path(self, bucket: str, prefix: str) -> Path:
"""Get placeholder path for in-memory reference.
Returns a virtual path that doesn't actually exist on filesystem.
Used for API compatibility.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
Returns:
Virtual path (may not exist on filesystem)
"""
# Return virtual path for compatibility
# Actual data is in memory, but we need Path for API
safe_bucket = bucket.replace("/", "_")
safe_prefix = prefix.replace("/", "_")
return self.temp_dir / safe_bucket / safe_prefix / "reference.bin"
def has_ref(self, bucket: str, prefix: str, sha: str) -> bool:
"""Check if reference exists in memory with given SHA.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
sha: Expected SHA256 hash
Returns:
True if reference exists with this SHA
"""
key = (bucket, prefix)
if key not in self._cache:
return False
_, cached_sha = self._cache[key]
return cached_sha == sha
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get cached reference from memory with validation.
Retrieves content from memory, validates SHA, and writes to
temporary file for compatibility with file-based APIs.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
expected_sha: Expected SHA256 hash
Returns:
Path to temporary file containing content
Raises:
CacheMissError: Content not in cache
CacheCorruptionError: SHA mismatch
"""
key = (bucket, prefix)
# Check if in cache
if key not in self._cache:
raise CacheMissError(f"Cache miss for {bucket}/{prefix}")
# Get content and validate
content, cached_sha = self._cache[key]
# Update LRU
self._update_access(key)
# Validate SHA
if cached_sha != expected_sha:
# SHA mismatch - possible corruption
raise CacheCorruptionError(
f"Memory cache SHA mismatch for {bucket}/{prefix}: "
f"expected {expected_sha}, got {cached_sha}"
)
# Write to temporary file for API compatibility
temp_path = self.ref_path(bucket, prefix)
temp_path.parent.mkdir(parents=True, exist_ok=True, mode=0o700)
try:
with open(temp_path, "wb") as f:
f.write(content)
except OSError as e:
raise CacheMissError(f"Cannot write temp file: {e}") from e
return temp_path
def write_ref(self, bucket: str, prefix: str, src: Path) -> Path:
"""Store reference file in memory.
Reads file content and stores in memory with SHA hash.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
src: Source file to cache
Returns:
Virtual path (content is in memory)
"""
# Read source file
try:
with open(src, "rb") as f:
content = f.read()
except OSError as e:
raise CacheCorruptionError(f"Cannot read source file {src}: {e}") from e
# Compute SHA
sha = hashlib.sha256(content).hexdigest()
# Check if we need to evict
content_size = len(content)
if content_size > self.max_size_bytes:
raise CacheCorruptionError(
f"File too large for memory cache: {content_size} bytes "
f"(limit: {self.max_size_bytes} bytes)"
)
# Evict LRU entries if needed
self._evict_lru(content_size)
# Store in memory
key = (bucket, prefix)
self._cache[key] = (content, sha)
self._current_size += content_size
# Update LRU
self._update_access(key)
# Return virtual path
return self.ref_path(bucket, prefix)
def evict(self, bucket: str, prefix: str) -> None:
"""Remove cached reference from memory.
Args:
bucket: S3 bucket name
prefix: Deltaspace prefix
"""
key = (bucket, prefix)
# Remove from cache
if key in self._cache:
content, _ = self._cache[key]
self._current_size -= len(content)
del self._cache[key]
# Remove from LRU tracking
if key in self._access_order:
self._access_order.remove(key)
# Clean up temp file if exists
temp_path = self.ref_path(bucket, prefix)
if temp_path.exists():
try:
temp_path.unlink()
except OSError:
pass # Best effort
def clear(self) -> None:
"""Clear all cached content from memory.
Useful for testing and cleanup.
"""
self._cache.clear()
self._access_order.clear()
self._current_size = 0

View File

@@ -0,0 +1,126 @@
"""EC2 Instance Metadata Service (IMDS) adapter.
Provides access to EC2 instance metadata using IMDSv2 with token-based authentication.
Falls back gracefully when not running on EC2.
"""
import os
import requests
class EC2MetadataAdapter:
"""Adapter for EC2 Instance Metadata Service (IMDSv2)."""
IMDS_BASE_URL = "http://169.254.169.254/latest"
TOKEN_URL = f"{IMDS_BASE_URL}/api/token"
TOKEN_TTL_SECONDS = 21600 # 6 hours
TOKEN_HEADER = "X-aws-ec2-metadata-token"
TIMEOUT_SECONDS = 1 # Fast timeout for non-EC2 environments
def __init__(self) -> None:
"""Initialize EC2 metadata adapter."""
self._token: str | None = None
self._is_ec2: bool | None = None
self._region: str | None = None
def is_running_on_ec2(self) -> bool:
"""Check if running on an EC2 instance.
Returns:
True if running on EC2, False otherwise
Note:
Result is cached after first check for performance.
"""
if self._is_ec2 is not None:
return self._is_ec2
# Skip check if explicitly disabled
if os.environ.get("DG_DISABLE_EC2_DETECTION", "").lower() in ("true", "1", "yes"):
self._is_ec2 = False
return False
try:
# Try to get IMDSv2 token
self._token = self._get_token()
self._is_ec2 = self._token is not None
except Exception:
self._is_ec2 = False
return self._is_ec2
def get_region(self) -> str | None:
"""Get the EC2 instance's AWS region.
Returns:
AWS region code (e.g., "us-east-1") or None if not on EC2
Note:
Result is cached after first successful fetch.
"""
if not self.is_running_on_ec2():
return None
if self._region is not None:
return self._region
try:
if self._token:
response = requests.get(
f"{self.IMDS_BASE_URL}/meta-data/placement/region",
headers={self.TOKEN_HEADER: self._token},
timeout=self.TIMEOUT_SECONDS,
)
if response.status_code == 200:
self._region = response.text.strip()
return self._region
except Exception:
pass
return None
def get_availability_zone(self) -> str | None:
"""Get the EC2 instance's availability zone.
Returns:
Availability zone (e.g., "us-east-1a") or None if not on EC2
"""
if not self.is_running_on_ec2():
return None
try:
if self._token:
response = requests.get(
f"{self.IMDS_BASE_URL}/meta-data/placement/availability-zone",
headers={self.TOKEN_HEADER: self._token},
timeout=self.TIMEOUT_SECONDS,
)
if response.status_code == 200:
return str(response.text.strip())
except Exception:
pass
return None
def _get_token(self) -> str | None:
"""Get IMDSv2 token for authenticated metadata requests.
Returns:
IMDSv2 token or None if unable to retrieve
Note:
Uses IMDSv2 for security. IMDSv1 is not supported.
"""
try:
response = requests.put(
self.TOKEN_URL,
headers={"X-aws-ec2-metadata-token-ttl-seconds": str(self.TOKEN_TTL_SECONDS)},
timeout=self.TIMEOUT_SECONDS,
)
if response.status_code == 200:
return response.text.strip()
except Exception:
pass
return None

View File

@@ -97,6 +97,7 @@ class S3StorageAdapter(StoragePort):
delimiter: str = "",
max_keys: int = 1000,
start_after: str | None = None,
continuation_token: str | None = None,
) -> dict[str, Any]:
"""List objects with S3-compatible response.
@@ -105,7 +106,8 @@ class S3StorageAdapter(StoragePort):
prefix: Filter results to keys beginning with prefix
delimiter: Delimiter for grouping keys (e.g., '/' for folders)
max_keys: Maximum number of keys to return
start_after: Start listing after this key
start_after: Start listing after this key (for first page only)
continuation_token: Token from previous response for pagination
Returns:
Dict with objects, common_prefixes, and pagination info
@@ -119,7 +121,11 @@ class S3StorageAdapter(StoragePort):
params["Prefix"] = prefix
if delimiter:
params["Delimiter"] = delimiter
if start_after:
# Use ContinuationToken for pagination if available, otherwise StartAfter
if continuation_token:
params["ContinuationToken"] = continuation_token
elif start_after:
params["StartAfter"] = start_after
try:

View File

@@ -1,28 +1,120 @@
"""AWS S3 CLI compatible commands."""
import shutil
import sys
from pathlib import Path
import click
from ...core import DeltaService, DeltaSpace, ObjectKey
from ...core import (
DeltaService,
DeltaSpace,
ObjectKey,
build_s3_url,
is_s3_url,
)
from ...core import parse_s3_url as core_parse_s3_url
from .sync import fetch_s3_object_heads
__all__ = [
"is_s3_path",
"parse_s3_url",
"determine_operation",
"upload_file",
"download_file",
"copy_s3_to_s3",
"migrate_s3_to_s3",
"handle_recursive",
"log_aws_region",
]
def log_aws_region(service: DeltaService, region_override: bool = False) -> None:
"""Log the AWS region being used and warn about cross-region charges.
This function:
1. Detects if running on EC2
2. Compares EC2 region with S3 client region
3. Warns about potential cross-region data transfer charges
4. Helps users optimize for cost and performance
Args:
service: DeltaService instance with storage adapter
region_override: True if user explicitly specified --region flag
"""
try:
from ...adapters.ec2_metadata import EC2MetadataAdapter
from ...adapters.storage_s3 import S3StorageAdapter
if not isinstance(service.storage, S3StorageAdapter):
return # Not using S3 storage, skip
# Get S3 client region
s3_region = service.storage.client.meta.region_name
if not s3_region:
s3_region = "us-east-1" # boto3 default
# Check if running on EC2
ec2_metadata = EC2MetadataAdapter()
if ec2_metadata.is_running_on_ec2():
ec2_region = ec2_metadata.get_region()
ec2_az = ec2_metadata.get_availability_zone()
# Log EC2 context
click.echo(f"EC2 Instance: {ec2_az or ec2_region or 'unknown'}")
click.echo(f"S3 Client Region: {s3_region}")
# Check for region mismatch
if ec2_region and ec2_region != s3_region:
if region_override:
# User explicitly set --region, warn about costs
click.echo("")
click.secho(
f"⚠️ WARNING: EC2 region={ec2_region} != S3 client region={s3_region}",
fg="yellow",
bold=True,
)
click.secho(
f" Expect cross-region/NAT data charges. Align regions (set client region={ec2_region})",
fg="yellow",
)
click.secho(
" before proceeding. Or drop --region for automatic region resolution.",
fg="yellow",
)
click.echo("")
else:
# Auto-detected mismatch, but user can still cancel
click.echo("")
click.secho(
f" INFO: EC2 region ({ec2_region}) differs from configured S3 region ({s3_region})",
fg="cyan",
)
click.secho(
f" Consider using --region {ec2_region} to avoid cross-region charges.",
fg="cyan",
)
click.echo("")
elif ec2_region and ec2_region == s3_region:
# Regions match - optimal configuration
click.secho("✓ Regions aligned - no cross-region charges", fg="green")
else:
# Not on EC2, just show S3 region
click.echo(f"S3 Client Region: {s3_region}")
except Exception:
pass # Silently ignore errors getting region info
def is_s3_path(path: str) -> bool:
"""Check if path is an S3 URL."""
return path.startswith("s3://")
return is_s3_url(path)
def parse_s3_url(url: str) -> tuple[str, str]:
"""Parse S3 URL into bucket and key."""
if not url.startswith("s3://"):
raise ValueError(f"Invalid S3 URL: {url}")
s3_path = url[5:].rstrip("/")
parts = s3_path.split("/", 1)
bucket = parts[0]
key = parts[1] if len(parts) > 1 else ""
return bucket, key
parsed = core_parse_s3_url(url, strip_trailing_slash=True)
return parsed.bucket, parsed.key
def determine_operation(source: str, dest: str) -> str:
@@ -57,6 +149,8 @@ def upload_file(
delta_space = DeltaSpace(bucket=bucket, prefix="/".join(key.split("/")[:-1]))
dest_url = build_s3_url(bucket, key)
try:
# Check if delta should be disabled
if no_delta:
@@ -66,7 +160,7 @@ def upload_file(
if not quiet:
file_size = local_path.stat().st_size
click.echo(f"upload: '{local_path}' to 's3://{bucket}/{key}' ({file_size} bytes)")
click.echo(f"upload: '{local_path}' to '{dest_url}' ({file_size} bytes)")
else:
# Use delta compression
summary = service.put(local_path, delta_space, max_ratio)
@@ -75,12 +169,12 @@ def upload_file(
if summary.delta_size:
ratio = round((summary.delta_size / summary.file_size) * 100, 1)
click.echo(
f"upload: '{local_path}' to 's3://{bucket}/{summary.key}' "
f"upload: '{local_path}' to '{build_s3_url(bucket, summary.key)}' "
f"(delta: {ratio}% of original)"
)
else:
click.echo(
f"upload: '{local_path}' to 's3://{bucket}/{summary.key}' "
f"upload: '{local_path}' to '{build_s3_url(bucket, summary.key)}' "
f"(reference: {summary.file_size} bytes)"
)
@@ -112,7 +206,7 @@ def download_file(
actual_key = delta_key
obj_key = ObjectKey(bucket=bucket, key=delta_key)
if not quiet:
click.echo(f"Auto-detected delta: s3://{bucket}/{delta_key}")
click.echo(f"Auto-detected delta: {build_s3_url(bucket, delta_key)}")
# Determine output path
if local_path is None:
@@ -136,7 +230,7 @@ def download_file(
if not quiet:
file_size = local_path.stat().st_size
click.echo(
f"download: 's3://{bucket}/{actual_key}' to '{local_path}' ({file_size} bytes)"
f"download: '{build_s3_url(bucket, actual_key)}' to '{local_path}' ({file_size} bytes)"
)
except Exception as e:
@@ -149,31 +243,310 @@ def copy_s3_to_s3(
source_url: str,
dest_url: str,
quiet: bool = False,
max_ratio: float | None = None,
no_delta: bool = False,
) -> None:
"""Copy object between S3 locations."""
# For now, implement as download + upload
# TODO: Optimize with server-side copy when possible
"""Copy object between S3 locations with optional delta compression.
This performs a direct S3-to-S3 transfer using streaming to preserve
the original file content and apply delta compression at the destination.
"""
source_bucket, source_key = parse_s3_url(source_url)
dest_bucket, dest_key = parse_s3_url(dest_url)
if not quiet:
click.echo(f"copy: 's3://{source_bucket}/{source_key}' to 's3://{dest_bucket}/{dest_key}'")
click.echo(
f"copy: '{build_s3_url(source_bucket, source_key)}' "
f"to '{build_s3_url(dest_bucket, dest_key)}'"
)
# Use temporary file
import tempfile
try:
# Get the source object as a stream
source_stream = service.storage.get(f"{source_bucket}/{source_key}")
with tempfile.NamedTemporaryFile(suffix=Path(source_key).suffix) as tmp:
tmp_path = Path(tmp.name)
# Determine the destination deltaspace
dest_key_parts = dest_key.split("/")
if len(dest_key_parts) > 1:
dest_prefix = "/".join(dest_key_parts[:-1])
else:
dest_prefix = ""
# Download from source
download_file(service, source_url, tmp_path, quiet=True)
dest_deltaspace = DeltaSpace(bucket=dest_bucket, prefix=dest_prefix)
# Upload to destination
upload_file(service, tmp_path, dest_url, quiet=True)
# If delta is disabled or max_ratio specified, use direct put
if no_delta:
# Direct storage put without delta compression
service.storage.put(f"{dest_bucket}/{dest_key}", source_stream, {})
if not quiet:
click.echo("Copy completed (no delta compression)")
else:
# Write to a temporary file and use override_name to preserve original filename
import tempfile
# Extract original filename from source
original_filename = Path(source_key).name
with tempfile.NamedTemporaryFile(delete=False, suffix=Path(source_key).suffix) as tmp:
tmp_path = Path(tmp.name)
# Write stream to temp file
with open(tmp_path, "wb") as f:
shutil.copyfileobj(source_stream, f)
try:
# Use DeltaService.put() with override_name to preserve original filename
summary = service.put(
tmp_path, dest_deltaspace, max_ratio, override_name=original_filename
)
if not quiet:
if summary.delta_size:
ratio = round((summary.delta_size / summary.file_size) * 100, 1)
click.echo(f"Copy completed with delta compression ({ratio}% of original)")
else:
click.echo("Copy completed (stored as reference)")
finally:
# Clean up temp file
tmp_path.unlink(missing_ok=True)
except Exception as e:
click.echo(f"S3-to-S3 copy failed: {e}", err=True)
raise
def migrate_s3_to_s3(
service: DeltaService,
source_url: str,
dest_url: str,
exclude: str | None = None,
include: str | None = None,
quiet: bool = False,
no_delta: bool = False,
max_ratio: float | None = None,
dry_run: bool = False,
skip_confirm: bool = False,
preserve_prefix: bool = False,
region_override: bool = False,
) -> None:
"""Migrate objects from one S3 location to another with delta compression.
Features:
- Resume support: Only copies files that don't exist in destination
- Progress tracking: Shows migration progress
- Confirmation prompt: Shows file count before starting
- Prefix preservation: Optionally preserves source prefix structure in destination
- EC2 region detection: Warns about cross-region data transfer charges
Args:
service: DeltaService instance
source_url: Source S3 URL
dest_url: Destination S3 URL
exclude: Pattern to exclude files
include: Pattern to include files
quiet: Suppress output
no_delta: Disable delta compression
max_ratio: Maximum delta/file ratio
dry_run: Show what would be migrated without migrating
skip_confirm: Skip confirmation prompt
preserve_prefix: Preserve source prefix in destination
region_override: True if user explicitly specified --region flag
"""
import fnmatch
source_bucket, source_prefix = parse_s3_url(source_url)
dest_bucket, dest_prefix = parse_s3_url(dest_url)
# Ensure prefixes end with / if they exist
if source_prefix and not source_prefix.endswith("/"):
source_prefix += "/"
if dest_prefix and not dest_prefix.endswith("/"):
dest_prefix += "/"
# Determine the effective destination prefix based on preserve_prefix setting
effective_dest_prefix = dest_prefix
if preserve_prefix and source_prefix:
# Extract the last component of the source prefix (e.g., "prefix1/" from "path/to/prefix1/")
source_prefix_name = source_prefix.rstrip("/").split("/")[-1]
if source_prefix_name:
# Append source prefix name to destination
effective_dest_prefix = (dest_prefix or "") + source_prefix_name + "/"
if not quiet:
# Log AWS region being used (helps users verify their configuration)
# Pass region_override to warn about cross-region charges if user explicitly set --region
log_aws_region(service, region_override=region_override)
source_display = build_s3_url(source_bucket, source_prefix)
dest_display = build_s3_url(dest_bucket, dest_prefix)
effective_dest_display = build_s3_url(dest_bucket, effective_dest_prefix)
if preserve_prefix and source_prefix:
click.echo(f"Migrating from {source_display}")
click.echo(f" to {effective_dest_display}")
else:
click.echo(f"Migrating from {source_display} to {dest_display}")
click.echo("Scanning source and destination buckets...")
# List source objects
source_list_prefix = f"{source_bucket}/{source_prefix}" if source_prefix else source_bucket
source_objects = []
for obj in service.storage.list(source_list_prefix):
# Skip reference.bin files (internal delta reference)
if obj.key.endswith("/reference.bin"):
continue
# Skip .delta files in source (we'll handle the original files)
if obj.key.endswith(".delta"):
continue
# Apply include/exclude filters
rel_key = obj.key.removeprefix(source_prefix) if source_prefix else obj.key
if exclude and fnmatch.fnmatch(rel_key, exclude):
continue
if include and not fnmatch.fnmatch(rel_key, include):
continue
source_objects.append(obj)
# List destination objects to detect what needs copying
dest_list_prefix = (
f"{dest_bucket}/{effective_dest_prefix}" if effective_dest_prefix else dest_bucket
)
dest_keys = set()
for obj in service.storage.list(dest_list_prefix):
# Get the relative key in destination
rel_key = obj.key.removeprefix(effective_dest_prefix) if effective_dest_prefix else obj.key
# Remove .delta suffix for comparison
if rel_key.endswith(".delta"):
rel_key = rel_key[:-6]
# Skip reference.bin
if not rel_key.endswith("/reference.bin"):
dest_keys.add(rel_key)
# Determine files to migrate (not in destination)
files_to_migrate = []
total_size = 0
for source_obj in source_objects:
# Get relative path from source prefix
rel_key = source_obj.key.removeprefix(source_prefix) if source_prefix else source_obj.key
# Check if already exists in destination
if rel_key not in dest_keys:
files_to_migrate.append((source_obj, rel_key))
total_size += source_obj.size
# Show summary and ask for confirmation
if not files_to_migrate:
if not quiet:
click.echo("Copy completed")
click.echo("All files are already migrated. Nothing to do.")
return
if not quiet:
def format_bytes(size: int) -> str:
size_float = float(size)
for unit in ["B", "KB", "MB", "GB", "TB"]:
if size_float < 1024.0:
return f"{size_float:.2f} {unit}"
size_float /= 1024.0
return f"{size_float:.2f} PB"
click.echo("")
click.echo(f"Files to migrate: {len(files_to_migrate)}")
click.echo(f"Total size: {format_bytes(total_size)}")
if len(dest_keys) > 0:
click.echo(f"Already migrated: {len(dest_keys)} files (will be skipped)")
# Handle dry run mode early (before confirmation prompt)
if dry_run:
if not quiet:
click.echo("\n--- DRY RUN MODE ---")
for _obj, rel_key in files_to_migrate[:10]: # Show first 10 files
click.echo(f" Would migrate: {rel_key}")
if len(files_to_migrate) > 10:
click.echo(f" ... and {len(files_to_migrate) - 10} more files")
return
# Ask for confirmation before proceeding with actual migration
if not quiet and not skip_confirm:
click.echo("")
if not click.confirm("Do you want to proceed with the migration?"):
click.echo("Migration cancelled.")
return
# Perform migration
if not quiet:
click.echo(f"\nStarting migration of {len(files_to_migrate)} files...")
successful = 0
failed = 0
failed_files = []
for i, (source_obj, rel_key) in enumerate(files_to_migrate, 1):
source_s3_url = build_s3_url(source_bucket, source_obj.key)
# Construct destination URL using effective prefix
if effective_dest_prefix:
dest_key = effective_dest_prefix + rel_key
else:
dest_key = rel_key
dest_s3_url = build_s3_url(dest_bucket, dest_key)
try:
if not quiet:
progress = f"[{i}/{len(files_to_migrate)}]"
click.echo(f"{progress} Migrating {rel_key}...", nl=False)
# Copy with delta compression
copy_s3_to_s3(
service,
source_s3_url,
dest_s3_url,
quiet=True,
max_ratio=max_ratio,
no_delta=no_delta,
)
successful += 1
if not quiet:
click.echo("")
except Exception as e:
failed += 1
failed_files.append((rel_key, str(e)))
if not quiet:
click.echo(f" ✗ ({e})")
# Show final summary
if not quiet:
click.echo("")
click.echo("Migration Summary:")
click.echo(f" Successfully migrated: {successful} files")
if failed > 0:
click.echo(f" Failed: {failed} files")
click.echo("\nFailed files:")
for file, error in failed_files[:10]: # Show first 10 failures
click.echo(f" {file}: {error}")
if len(failed_files) > 10:
click.echo(f" ... and {len(failed_files) - 10} more failures")
# Show compression statistics from cache if available (no bucket scan)
if successful > 0 and not no_delta:
try:
from ...client import DeltaGliderClient
client = DeltaGliderClient(service)
# Use cached stats only - don't scan bucket (prevents blocking)
cached_stats = client._get_cached_bucket_stats(dest_bucket, "quick")
if cached_stats and cached_stats.delta_objects > 0:
click.echo(
f"\nCompression achieved: {cached_stats.average_compression_ratio:.1%}"
)
click.echo(f"Space saved: {format_bytes(cached_stats.space_saved)}")
except Exception:
pass # Ignore stats errors
def handle_recursive(
@@ -228,10 +601,7 @@ def handle_recursive(
dest_path = Path(dest)
dest_path.mkdir(parents=True, exist_ok=True)
# List all objects with prefix
# Note: S3StorageAdapter.list() expects "bucket/prefix" format
list_prefix = f"{bucket}/{prefix}" if prefix else bucket
objects = list(service.storage.list(list_prefix))
objects = fetch_s3_object_heads(service, bucket, prefix)
if not quiet:
click.echo(f"Downloading {len(objects)} files...")
@@ -261,9 +631,22 @@ def handle_recursive(
local_path.parent.mkdir(parents=True, exist_ok=True)
# Download file
s3_url = f"s3://{bucket}/{obj.key}"
s3_url = build_s3_url(bucket, obj.key)
download_file(service, s3_url, local_path, quiet)
else:
click.echo("S3-to-S3 recursive copy not yet implemented", err=True)
sys.exit(1)
elif operation == "copy":
# S3-to-S3 recursive copy with migration support
migrate_s3_to_s3(
service,
source,
dest,
exclude=exclude,
include=include,
quiet=quiet,
no_delta=no_delta,
max_ratio=max_ratio,
dry_run=False,
skip_confirm=True, # Don't prompt for cp command
preserve_prefix=True, # Always preserve prefix for cp -r
region_override=False, # cp command doesn't track region override explicitly
)

View File

@@ -1,14 +1,18 @@
"""CLI main entry point."""
import atexit
import json
import os
import shutil
import sys
import tempfile
from pathlib import Path
from typing import Any
import click
from ... import __version__
from ...adapters import (
FsCacheAdapter,
NoopMetricsAdapter,
S3StorageAdapter,
Sha256Adapter,
@@ -18,6 +22,7 @@ from ...adapters import (
)
from ...core import DeltaService, ObjectKey
from ...ports import MetricsPort
from ...ports.cache import CachePort
from .aws_compat import (
copy_s3_to_s3,
determine_operation,
@@ -38,11 +43,15 @@ def create_service(
) -> DeltaService:
"""Create service with wired adapters."""
# Get config from environment
cache_dir = Path(os.environ.get("DG_CACHE_DIR", "/tmp/.deltaglider/reference_cache"))
max_ratio = float(os.environ.get("DG_MAX_RATIO", "0.5"))
metrics_type = os.environ.get("DG_METRICS", "logging") # Options: noop, logging, cloudwatch
# Set AWS environment variables if provided
# SECURITY: Always use ephemeral process-isolated cache
cache_dir = Path(tempfile.mkdtemp(prefix="deltaglider-", dir="/tmp"))
# Register cleanup handler to remove cache on exit
atexit.register(lambda: shutil.rmtree(cache_dir, ignore_errors=True))
# Set AWS environment variables if provided (for compatibility with other AWS tools)
if endpoint_url:
os.environ["AWS_ENDPOINT_URL"] = endpoint_url
if region:
@@ -50,11 +59,33 @@ def create_service(
if profile:
os.environ["AWS_PROFILE"] = profile
# Build boto3_kwargs for explicit parameter passing (preferred over env vars)
boto3_kwargs: dict[str, Any] = {}
if region:
boto3_kwargs["region_name"] = region
# Create adapters
hasher = Sha256Adapter()
storage = S3StorageAdapter(endpoint_url=endpoint_url)
storage = S3StorageAdapter(endpoint_url=endpoint_url, boto3_kwargs=boto3_kwargs)
diff = XdeltaAdapter()
cache = FsCacheAdapter(cache_dir, hasher)
# SECURITY: Configurable cache with encryption and backend selection
from deltaglider.adapters import ContentAddressedCache, EncryptedCache, MemoryCache
# Select backend: memory or filesystem
cache_backend = os.environ.get("DG_CACHE_BACKEND", "filesystem") # Options: filesystem, memory
base_cache: CachePort
if cache_backend == "memory":
max_size_mb = int(os.environ.get("DG_CACHE_MEMORY_SIZE_MB", "100"))
base_cache = MemoryCache(hasher, max_size_mb=max_size_mb, temp_dir=cache_dir)
else:
# Filesystem-backed with Content-Addressed Storage
base_cache = ContentAddressedCache(cache_dir, hasher)
# Always apply encryption with ephemeral keys (security hardening)
# Encryption key is optional via DG_CACHE_ENCRYPTION_KEY (ephemeral if not set)
cache: CachePort = EncryptedCache.from_env(base_cache)
clock = UtcClockAdapter()
logger = StdLoggerAdapter(level=log_level)
@@ -89,8 +120,23 @@ def create_service(
)
def _version_callback(ctx: click.Context, param: click.Parameter, value: bool) -> None:
"""Callback for --version option."""
if value:
click.echo(f"deltaglider {__version__}")
ctx.exit(0)
@click.group()
@click.option("--debug", is_flag=True, help="Enable debug logging")
@click.option(
"--version",
is_flag=True,
is_eager=True,
expose_value=False,
callback=_version_callback,
help="Show version and exit",
)
@click.pass_context
def cli(ctx: click.Context, debug: bool) -> None:
"""DeltaGlider - Delta-aware S3 file storage wrapper."""
@@ -148,9 +194,6 @@ def cp(
# Handle recursive operations for directories
if recursive:
if operation == "copy":
click.echo("S3-to-S3 recursive copy not yet implemented", err=True)
sys.exit(1)
handle_recursive(
service, source, dest, recursive, exclude, include, quiet, no_delta, max_ratio
)
@@ -172,7 +215,7 @@ def cp(
download_file(service, source, local_path, quiet)
elif operation == "copy":
copy_s3_to_s3(service, source, dest, quiet)
copy_s3_to_s3(service, source, dest, quiet, max_ratio, no_delta)
except ValueError as e:
click.echo(f"Error: {e}", err=True)
@@ -259,23 +302,26 @@ def ls(
return f"{size_float:.1f}P"
# List objects using SDK (automatically filters .delta and reference.bin)
from deltaglider.client import DeltaGliderClient, ListObjectsResponse
from deltaglider.client import DeltaGliderClient
client = DeltaGliderClient(service)
dg_response: ListObjectsResponse = client.list_objects(
Bucket=bucket_name, Prefix=prefix_str, MaxKeys=10000, Delimiter="/" if not recursive else ""
dg_response = client.list_objects(
Bucket=bucket_name,
Prefix=prefix_str,
MaxKeys=10000,
Delimiter="/" if not recursive else "",
)
objects = dg_response.contents
objects = dg_response["Contents"]
# Filter by recursive flag
if not recursive:
# Show common prefixes (subdirectories) from S3 response
for common_prefix in dg_response.common_prefixes:
for common_prefix in dg_response.get("CommonPrefixes", []):
prefix_path = common_prefix.get("Prefix", "")
# Show only the directory name, not the full path
if prefix_str:
# Strip the current prefix to show only the subdirectory
display_name = prefix_path[len(prefix_str):]
display_name = prefix_path[len(prefix_str) :]
else:
display_name = prefix_path
click.echo(f" PRE {display_name}")
@@ -283,7 +329,8 @@ def ls(
# Only show files at current level (not in subdirectories)
filtered_objects = []
for obj in objects:
rel_path = obj.key[len(prefix_str):] if prefix_str else obj.key
obj_key = obj["Key"]
rel_path = obj_key[len(prefix_str) :] if prefix_str else obj_key
# Only include if it's a direct child (no / in relative path)
if "/" not in rel_path and rel_path:
filtered_objects.append(obj)
@@ -294,23 +341,24 @@ def ls(
total_count = 0
for obj in objects:
total_size += obj.size
total_size += obj["Size"]
total_count += 1
# Format the display
size_str = format_bytes(obj.size)
size_str = format_bytes(obj["Size"])
# last_modified is a string from SDK, parse it if needed
if isinstance(obj.last_modified, str):
last_modified = obj.get("LastModified", "")
if isinstance(last_modified, str):
# Already a string, extract date portion
date_str = obj.last_modified[:19].replace("T", " ")
date_str = last_modified[:19].replace("T", " ")
else:
date_str = obj.last_modified.strftime("%Y-%m-%d %H:%M:%S")
date_str = last_modified.strftime("%Y-%m-%d %H:%M:%S")
# Show only the filename relative to current prefix (like AWS CLI)
if prefix_str:
display_key = obj.key[len(prefix_str):]
display_key = obj["Key"][len(prefix_str) :]
else:
display_key = obj.key
display_key = obj["Key"]
click.echo(f"{date_str} {size_str:>10} {display_key}")
@@ -575,20 +623,14 @@ def sync(
@click.pass_obj
def verify(service: DeltaService, s3_url: str) -> None:
"""Verify integrity of delta file."""
# Parse S3 URL
if not s3_url.startswith("s3://"):
try:
bucket, key = parse_s3_url(s3_url)
if not key:
raise ValueError("Missing key")
except ValueError:
click.echo(f"Error: Invalid S3 URL: {s3_url}", err=True)
sys.exit(1)
s3_path = s3_url[5:]
parts = s3_path.split("/", 1)
if len(parts) != 2:
click.echo(f"Error: Invalid S3 URL: {s3_url}", err=True)
sys.exit(1)
bucket = parts[0]
key = parts[1]
obj_key = ObjectKey(bucket=bucket, key=key)
try:
@@ -611,6 +653,243 @@ def verify(service: DeltaService, s3_url: str) -> None:
sys.exit(1)
@cli.command()
@click.argument("source")
@click.argument("dest")
@click.option("--exclude", help="Exclude files matching pattern")
@click.option("--include", help="Include only files matching pattern")
@click.option("--quiet", "-q", is_flag=True, help="Suppress output")
@click.option("--no-delta", is_flag=True, help="Disable delta compression")
@click.option("--max-ratio", type=float, help="Max delta/file ratio (default: 0.5)")
@click.option("--dry-run", is_flag=True, help="Show what would be migrated without migrating")
@click.option("--yes", "-y", is_flag=True, help="Skip confirmation prompt")
@click.option(
"--no-preserve-prefix", is_flag=True, help="Don't preserve source prefix in destination"
)
@click.option("--endpoint-url", help="Override S3 endpoint URL")
@click.option("--region", help="AWS region")
@click.option("--profile", help="AWS profile to use")
@click.pass_obj
def migrate(
service: DeltaService,
source: str,
dest: str,
exclude: str | None,
include: str | None,
quiet: bool,
no_delta: bool,
max_ratio: float | None,
dry_run: bool,
yes: bool,
no_preserve_prefix: bool,
endpoint_url: str | None,
region: str | None,
profile: str | None,
) -> None:
"""Migrate S3 bucket/prefix to DeltaGlider-compressed storage.
This command facilitates the migration of existing S3 objects to another bucket
with DeltaGlider compression. It supports:
- Resume capability: Only copies files that don't exist in destination
- Progress tracking: Shows migration progress
- Confirmation prompt: Shows file count before starting (use --yes to skip)
- Prefix preservation: By default, source prefix is preserved in destination
When migrating a prefix, the source prefix name is preserved by default:
s3://src/prefix1/ → s3://dest/ creates s3://dest/prefix1/
s3://src/a/b/c/ → s3://dest/x/ creates s3://dest/x/c/
Use --no-preserve-prefix to disable this behavior:
s3://src/prefix1/ → s3://dest/ creates s3://dest/ (files at root)
Examples:
deltaglider migrate s3://old-bucket/ s3://new-bucket/
deltaglider migrate s3://old-bucket/data/ s3://new-bucket/
deltaglider migrate --no-preserve-prefix s3://src/v1/ s3://dest/
deltaglider migrate --dry-run s3://old-bucket/ s3://new-bucket/
deltaglider migrate --yes --quiet s3://old-bucket/ s3://new-bucket/
"""
from .aws_compat import is_s3_path, migrate_s3_to_s3
# Recreate service with AWS parameters if provided
if endpoint_url or region or profile:
service = create_service(
log_level=os.environ.get("DG_LOG_LEVEL", "INFO"),
endpoint_url=endpoint_url,
region=region,
profile=profile,
)
try:
# Validate both paths are S3
if not is_s3_path(source) or not is_s3_path(dest):
click.echo("Error: Both source and destination must be S3 paths", err=True)
sys.exit(1)
# Perform migration
migrate_s3_to_s3(
service,
source,
dest,
exclude=exclude,
include=include,
quiet=quiet,
no_delta=no_delta,
max_ratio=max_ratio,
dry_run=dry_run,
skip_confirm=yes,
preserve_prefix=not no_preserve_prefix,
region_override=region is not None, # True if user explicitly specified --region
)
except Exception as e:
click.echo(f"Migration failed: {e}", err=True)
sys.exit(1)
@cli.command(short_help="Get bucket statistics and compression metrics")
@click.argument("bucket")
@click.option("--sampled", is_flag=True, help="Balanced mode: one sample per deltaspace (~5-15s)")
@click.option(
"--detailed", is_flag=True, help="Most accurate: HEAD for all deltas (slowest, ~1min+)"
)
@click.option("--refresh", is_flag=True, help="Force cache refresh even if valid")
@click.option("--no-cache", is_flag=True, help="Skip caching entirely (both read and write)")
@click.option("--json", "output_json", is_flag=True, help="Output in JSON format")
@click.pass_obj
def stats(
service: DeltaService,
bucket: str,
sampled: bool,
detailed: bool,
refresh: bool,
no_cache: bool,
output_json: bool,
) -> None:
"""Get bucket statistics and compression metrics with intelligent S3-based caching.
BUCKET can be specified as:
- s3://bucket-name/
- s3://bucket-name
- bucket-name
Modes (mutually exclusive):
- quick (default): Fast listing-only stats (~0.5s), approximate compression metrics
- --sampled: Balanced mode - one HEAD per deltaspace (~5-15s for typical buckets)
- --detailed: Most accurate - HEAD for every delta file (slowest, ~1min+ for large buckets)
Caching (NEW - massive performance improvement!):
Stats are cached in S3 at .deltaglider/stats_{mode}.json (one per mode).
Cache is automatically validated on every call using object count + size.
If bucket changed, stats are recomputed automatically.
Performance with cache:
- Cache hit: ~0.1s (200x faster than recomputation!)
- Cache miss: Full computation time (creates cache for next time)
- Cache invalid: Auto-recomputes when bucket changes
Options:
--refresh: Force cache refresh even if valid (use when you need fresh data now)
--no-cache: Skip caching entirely - always recompute (useful for testing/debugging)
--json: Output in JSON format for automation/scripting
Examples:
deltaglider stats mybucket # Fast (~0.1s with cache, ~0.5s without)
deltaglider stats mybucket --sampled # Balanced accuracy/speed (~5-15s first run)
deltaglider stats mybucket --detailed # Most accurate (~1-10min first run, ~0.1s cached)
deltaglider stats mybucket --refresh # Force recomputation even if cached
deltaglider stats mybucket --no-cache # Always compute fresh (skip cache)
deltaglider stats mybucket --json # JSON output for scripts
deltaglider stats s3://mybucket/ # Also accepts s3:// URLs
Timing Logs:
Set DG_LOG_LEVEL=INFO to see detailed phase timing with timestamps:
[HH:MM:SS.mmm] Phase 1: LIST completed in 0.52s - Found 1523 objects
[HH:MM:SS.mmm] Phase 2: Cache HIT in 0.06s - Using cached stats
[HH:MM:SS.mmm] COMPLETE: Total time 0.58s
See docs/STATS_CACHING.md for complete documentation.
"""
from ...client import DeltaGliderClient
from ...client_operations.stats import StatsMode
try:
# Parse bucket from S3 URL if needed
if is_s3_path(bucket):
bucket, _prefix = parse_s3_url(bucket)
if not bucket:
click.echo("Error: Invalid bucket name", err=True)
sys.exit(1)
if sampled and detailed:
click.echo("Error: --sampled and --detailed cannot be used together", err=True)
sys.exit(1)
if refresh and no_cache:
click.echo("Error: --refresh and --no-cache cannot be used together", err=True)
sys.exit(1)
mode: StatsMode = "quick"
if sampled:
mode = "sampled"
if detailed:
mode = "detailed"
# Create client from service
client = DeltaGliderClient(service=service)
# Get bucket stats with caching control
use_cache = not no_cache
bucket_stats = client.get_bucket_stats(
bucket, mode=mode, use_cache=use_cache, refresh_cache=refresh
)
if output_json:
# JSON output
output = {
"bucket": bucket_stats.bucket,
"object_count": bucket_stats.object_count,
"total_size": bucket_stats.total_size,
"compressed_size": bucket_stats.compressed_size,
"space_saved": bucket_stats.space_saved,
"average_compression_ratio": bucket_stats.average_compression_ratio,
"delta_objects": bucket_stats.delta_objects,
"direct_objects": bucket_stats.direct_objects,
}
click.echo(json.dumps(output, indent=2))
else:
# Human-readable output
def format_bytes(size: float) -> str:
"""Format bytes to human-readable size."""
for unit in ["B", "KB", "MB", "GB", "TB"]:
if size < 1024.0:
return f"{size:.2f} {unit}"
size /= 1024.0
return f"{size:.2f} PB"
click.echo(f"Bucket Statistics: {bucket_stats.bucket}")
click.echo(f"{'=' * 60}")
click.echo(f"Total Objects: {bucket_stats.object_count:,}")
click.echo(f" Delta Objects: {bucket_stats.delta_objects:,}")
click.echo(f" Direct Objects: {bucket_stats.direct_objects:,}")
click.echo("")
click.echo(
f"Original Size: {format_bytes(bucket_stats.total_size)} ({bucket_stats.total_size:,} bytes)"
)
click.echo(
f"Compressed Size: {format_bytes(bucket_stats.compressed_size)} ({bucket_stats.compressed_size:,} bytes)"
)
click.echo(
f"Space Saved: {format_bytes(bucket_stats.space_saved)} ({bucket_stats.space_saved:,} bytes)"
)
click.echo(f"Compression Ratio: {bucket_stats.average_compression_ratio:.1%}")
except Exception as e:
click.echo(f"Error: {e}", err=True)
sys.exit(1)
def main() -> None:
"""Main entry point."""
cli()

View File

@@ -5,9 +5,27 @@ from pathlib import Path
import click
from ...core import DeltaService
from ...core.object_listing import list_all_objects, object_dict_to_head
from ...ports import ObjectHead
def fetch_s3_object_heads(service: DeltaService, bucket: str, prefix: str) -> list[ObjectHead]:
"""Retrieve all objects for a prefix, falling back to iterator when needed."""
try:
listing = list_all_objects(
service.storage,
bucket=bucket,
prefix=prefix,
max_keys=1000,
logger=getattr(service, "logger", None),
)
except (RuntimeError, NotImplementedError):
list_prefix = f"{bucket}/{prefix}" if prefix else bucket
return list(service.storage.list(list_prefix))
return [object_dict_to_head(obj) for obj in listing.objects]
def get_local_files(
local_dir: Path, exclude: str | None = None, include: str | None = None
) -> dict[str, tuple[Path, int]]:
@@ -42,8 +60,7 @@ def get_s3_files(
import fnmatch
files = {}
list_prefix = f"{bucket}/{prefix}" if prefix else bucket
objects = service.storage.list(list_prefix)
objects = fetch_s3_object_heads(service, bucket, prefix)
for obj in objects:
# Skip reference.bin files (internal)

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,37 @@
"""Client operation modules for DeltaGliderClient.
This package contains modular operation implementations:
- bucket: S3 bucket management (create, delete, list)
- presigned: Presigned URL generation for temporary access
- batch: Batch upload/download operations
- stats: Statistics and analytics operations
"""
from .batch import download_batch, upload_batch, upload_chunked
from .bucket import create_bucket, delete_bucket, list_buckets
from .presigned import generate_presigned_post, generate_presigned_url
from .stats import (
estimate_compression,
find_similar_files,
get_bucket_stats,
get_object_info,
)
__all__ = [
# Bucket operations
"create_bucket",
"delete_bucket",
"list_buckets",
# Presigned operations
"generate_presigned_url",
"generate_presigned_post",
# Batch operations
"upload_chunked",
"upload_batch",
"download_batch",
# Stats operations
"get_bucket_stats",
"get_object_info",
"estimate_compression",
"find_similar_files",
]

View File

@@ -0,0 +1,159 @@
"""Batch upload/download operations for DeltaGlider client.
This module contains DeltaGlider-specific batch operations:
- upload_batch
- download_batch
- upload_chunked
"""
from collections.abc import Callable
from pathlib import Path
from typing import Any
from ..client_models import UploadSummary
def upload_chunked(
client: Any, # DeltaGliderClient
file_path: str | Path,
s3_url: str,
chunk_size: int = 5 * 1024 * 1024,
progress_callback: Callable[[int, int, int, int], None] | None = None,
max_ratio: float = 0.5,
) -> UploadSummary:
"""Upload a file in chunks with progress callback.
This method reads the file in chunks to avoid loading large files entirely into memory,
making it suitable for uploading very large files. Progress is reported after each chunk.
Args:
client: DeltaGliderClient instance
file_path: Local file to upload
s3_url: S3 destination URL (s3://bucket/path/filename)
chunk_size: Size of each chunk in bytes (default 5MB)
progress_callback: Callback(chunk_number, total_chunks, bytes_sent, total_bytes)
max_ratio: Maximum acceptable delta/file ratio for compression
Returns:
UploadSummary with compression statistics
Example:
def on_progress(chunk_num, total_chunks, bytes_sent, total_bytes):
percent = (bytes_sent / total_bytes) * 100
print(f"Upload progress: {percent:.1f}%")
client.upload_chunked(
"large_file.zip",
"s3://bucket/releases/large_file.zip",
chunk_size=10 * 1024 * 1024, # 10MB chunks
progress_callback=on_progress
)
"""
file_path = Path(file_path)
file_size = file_path.stat().st_size
# For small files, just use regular upload
if file_size <= chunk_size:
if progress_callback:
progress_callback(1, 1, file_size, file_size)
result: UploadSummary = client.upload(file_path, s3_url, max_ratio=max_ratio)
return result
# Calculate chunks
total_chunks = (file_size + chunk_size - 1) // chunk_size
# Create a temporary file for chunked processing
# For now, we read the entire file but report progress in chunks
# Future enhancement: implement true streaming upload in storage adapter
bytes_read = 0
with open(file_path, "rb") as f:
for chunk_num in range(1, total_chunks + 1):
# Read chunk (simulated for progress reporting)
chunk_data = f.read(chunk_size)
bytes_read += len(chunk_data)
if progress_callback:
progress_callback(chunk_num, total_chunks, bytes_read, file_size)
# Perform the actual upload
# TODO: When storage adapter supports streaming, pass chunks directly
upload_result: UploadSummary = client.upload(file_path, s3_url, max_ratio=max_ratio)
# Final progress callback
if progress_callback:
progress_callback(total_chunks, total_chunks, file_size, file_size)
return upload_result
def upload_batch(
client: Any, # DeltaGliderClient
files: list[str | Path],
s3_prefix: str,
max_ratio: float = 0.5,
progress_callback: Callable[[str, int, int], None] | None = None,
) -> list[UploadSummary]:
"""Upload multiple files in batch.
Args:
client: DeltaGliderClient instance
files: List of local file paths
s3_prefix: S3 destination prefix (s3://bucket/prefix/)
max_ratio: Maximum acceptable delta/file ratio
progress_callback: Callback(filename, current_file_index, total_files)
Returns:
List of UploadSummary objects
"""
results = []
for i, file_path in enumerate(files):
file_path = Path(file_path)
if progress_callback:
progress_callback(file_path.name, i + 1, len(files))
# Upload each file
s3_url = f"{s3_prefix.rstrip('/')}/{file_path.name}"
summary = client.upload(file_path, s3_url, max_ratio=max_ratio)
results.append(summary)
return results
def download_batch(
client: Any, # DeltaGliderClient
s3_urls: list[str],
output_dir: str | Path,
progress_callback: Callable[[str, int, int], None] | None = None,
) -> list[Path]:
"""Download multiple files in batch.
Args:
client: DeltaGliderClient instance
s3_urls: List of S3 URLs to download
output_dir: Local directory to save files
progress_callback: Callback(filename, current_file_index, total_files)
Returns:
List of downloaded file paths
"""
output_dir = Path(output_dir)
output_dir.mkdir(parents=True, exist_ok=True)
results = []
for i, s3_url in enumerate(s3_urls):
# Extract filename from URL
filename = s3_url.split("/")[-1]
if filename.endswith(".delta"):
filename = filename[:-6] # Remove .delta suffix
if progress_callback:
progress_callback(filename, i + 1, len(s3_urls))
output_path = output_dir / filename
client.download(s3_url, output_path)
results.append(output_path)
return results

View File

@@ -0,0 +1,175 @@
"""Bucket management operations for DeltaGlider client.
This module contains boto3-compatible bucket operations:
- create_bucket
- delete_bucket
- list_buckets
"""
from typing import Any
def create_bucket(
client: Any, # DeltaGliderClient (avoiding circular import)
Bucket: str,
CreateBucketConfiguration: dict[str, str] | None = None,
**kwargs: Any,
) -> dict[str, Any]:
"""Create an S3 bucket (boto3-compatible).
Args:
client: DeltaGliderClient instance
Bucket: Bucket name to create
CreateBucketConfiguration: Optional bucket configuration (e.g., LocationConstraint)
**kwargs: Additional S3 parameters (for compatibility)
Returns:
Response dict with bucket location
Example:
>>> client = create_client()
>>> client.create_bucket(Bucket='my-bucket')
>>> # With region
>>> client.create_bucket(
... Bucket='my-bucket',
... CreateBucketConfiguration={'LocationConstraint': 'us-west-2'}
... )
"""
storage_adapter = client.service.storage
# Check if storage adapter has boto3 client
if hasattr(storage_adapter, "client"):
try:
params: dict[str, Any] = {"Bucket": Bucket}
if CreateBucketConfiguration:
params["CreateBucketConfiguration"] = CreateBucketConfiguration
response = storage_adapter.client.create_bucket(**params)
return {
"Location": response.get("Location", f"/{Bucket}"),
"ResponseMetadata": {
"HTTPStatusCode": 200,
},
}
except Exception as e:
error_msg = str(e)
if "BucketAlreadyExists" in error_msg or "BucketAlreadyOwnedByYou" in error_msg:
# Bucket already exists - return success
client.service.logger.debug(f"Bucket {Bucket} already exists")
return {
"Location": f"/{Bucket}",
"ResponseMetadata": {
"HTTPStatusCode": 200,
},
}
raise RuntimeError(f"Failed to create bucket: {e}") from e
else:
raise NotImplementedError("Storage adapter does not support bucket creation")
def delete_bucket(
client: Any, # DeltaGliderClient
Bucket: str,
**kwargs: Any,
) -> dict[str, Any]:
"""Delete an S3 bucket (boto3-compatible).
Note: Bucket must be empty before deletion.
Args:
client: DeltaGliderClient instance
Bucket: Bucket name to delete
**kwargs: Additional S3 parameters (for compatibility)
Returns:
Response dict with deletion status
Example:
>>> client = create_client()
>>> client.delete_bucket(Bucket='my-bucket')
"""
storage_adapter = client.service.storage
# Check if storage adapter has boto3 client
if hasattr(storage_adapter, "client"):
try:
storage_adapter.client.delete_bucket(Bucket=Bucket)
return {
"ResponseMetadata": {
"HTTPStatusCode": 204,
},
}
except Exception as e:
error_msg = str(e)
if "NoSuchBucket" in error_msg:
# Bucket doesn't exist - return success
client.service.logger.debug(f"Bucket {Bucket} does not exist")
return {
"ResponseMetadata": {
"HTTPStatusCode": 204,
},
}
raise RuntimeError(f"Failed to delete bucket: {e}") from e
else:
raise NotImplementedError("Storage adapter does not support bucket deletion")
def list_buckets(
client: Any, # DeltaGliderClient
**kwargs: Any,
) -> dict[str, Any]:
"""List all S3 buckets (boto3-compatible).
Args:
client: DeltaGliderClient instance
**kwargs: Additional S3 parameters (for compatibility)
Returns:
Response dict with bucket list
Example:
>>> client = create_client()
>>> response = client.list_buckets()
>>> for bucket in response['Buckets']:
... print(bucket['Name'])
"""
storage_adapter = client.service.storage
# Check if storage adapter has boto3 client
if hasattr(storage_adapter, "client"):
try:
raw_response = storage_adapter.client.list_buckets()
buckets: list[dict[str, Any]] = []
for bucket_entry in raw_response.get("Buckets", []):
bucket_data = dict(bucket_entry)
name = bucket_data.get("Name")
if isinstance(name, str) and name:
cached_stats, cached_mode = client._get_cached_bucket_stats_for_listing(name)
if cached_stats is not None and cached_mode is not None:
bucket_data["DeltaGliderStats"] = {
"Cached": True,
"Mode": cached_mode,
"Detailed": cached_mode == "detailed",
"ObjectCount": cached_stats.object_count,
"TotalSize": cached_stats.total_size,
"CompressedSize": cached_stats.compressed_size,
"SpaceSaved": cached_stats.space_saved,
"AverageCompressionRatio": cached_stats.average_compression_ratio,
"DeltaObjects": cached_stats.delta_objects,
"DirectObjects": cached_stats.direct_objects,
}
buckets.append(bucket_data)
return {
"Buckets": buckets,
"Owner": raw_response.get("Owner", {}),
"ResponseMetadata": {
"HTTPStatusCode": 200,
},
}
except Exception as e:
raise RuntimeError(f"Failed to list buckets: {e}") from e
else:
raise NotImplementedError("Storage adapter does not support bucket listing")

View File

@@ -0,0 +1,124 @@
"""Presigned URL operations for DeltaGlider client.
This module contains boto3-compatible presigned URL operations:
- generate_presigned_url
- generate_presigned_post
"""
from typing import Any
def try_boto3_presigned_operation(
client: Any, # DeltaGliderClient
operation: str,
**kwargs: Any,
) -> Any | None:
"""Try to generate presigned operation using boto3 client, return None if not available."""
storage_adapter = client.service.storage
# Check if storage adapter has boto3 client
if hasattr(storage_adapter, "client"):
try:
if operation == "url":
return str(storage_adapter.client.generate_presigned_url(**kwargs))
elif operation == "post":
return dict(storage_adapter.client.generate_presigned_post(**kwargs))
except AttributeError:
# storage_adapter does not have a 'client' attribute
pass
except Exception as e:
# Fall back to manual construction if needed
client.service.logger.warning(f"Failed to generate presigned {operation}: {e}")
return None
def generate_presigned_url(
client: Any, # DeltaGliderClient
ClientMethod: str,
Params: dict[str, Any],
ExpiresIn: int = 3600,
) -> str:
"""Generate presigned URL (boto3-compatible).
Args:
client: DeltaGliderClient instance
ClientMethod: Method name ('get_object' or 'put_object')
Params: Parameters dict with Bucket and Key
ExpiresIn: URL expiration in seconds
Returns:
Presigned URL string
"""
# Try boto3 first, fallback to manual construction
url = try_boto3_presigned_operation(
client,
"url",
ClientMethod=ClientMethod,
Params=Params,
ExpiresIn=ExpiresIn,
)
if url is not None:
return str(url)
# Fallback: construct URL manually (less secure, for dev/testing only)
bucket = Params.get("Bucket", "")
key = Params.get("Key", "")
if client.endpoint_url:
base_url = client.endpoint_url
else:
base_url = f"https://{bucket}.s3.amazonaws.com"
# Warning: This is not a real presigned URL, just a placeholder
client.service.logger.warning("Using placeholder presigned URL - not suitable for production")
return f"{base_url}/{key}?expires={ExpiresIn}"
def generate_presigned_post(
client: Any, # DeltaGliderClient
Bucket: str,
Key: str,
Fields: dict[str, str] | None = None,
Conditions: list[Any] | None = None,
ExpiresIn: int = 3600,
) -> dict[str, Any]:
"""Generate presigned POST data for HTML forms (boto3-compatible).
Args:
client: DeltaGliderClient instance
Bucket: S3 bucket name
Key: Object key
Fields: Additional fields to include
Conditions: Upload conditions
ExpiresIn: URL expiration in seconds
Returns:
Dict with 'url' and 'fields' for form submission
"""
# Try boto3 first, fallback to manual construction
response = try_boto3_presigned_operation(
client,
"post",
Bucket=Bucket,
Key=Key,
Fields=Fields,
Conditions=Conditions,
ExpiresIn=ExpiresIn,
)
if response is not None:
return dict(response)
# Fallback: return minimal structure for compatibility
if client.endpoint_url:
url = f"{client.endpoint_url}/{Bucket}"
else:
url = f"https://{Bucket}.s3.amazonaws.com"
return {
"url": url,
"fields": {
"key": Key,
**(Fields or {}),
},
}

View File

@@ -0,0 +1,937 @@
"""Statistics and analysis operations for DeltaGlider client.
This module contains DeltaGlider-specific statistics operations:
- get_bucket_stats
- get_object_info
- estimate_compression
- find_similar_files
"""
import concurrent.futures
import json
import re
from dataclasses import asdict
from datetime import UTC, datetime
from pathlib import Path
from typing import Any, Literal
from ..client_models import BucketStats, CompressionEstimate, ObjectInfo
from ..core.delta_extensions import is_delta_candidate
from ..core.object_listing import list_all_objects
from ..core.s3_uri import parse_s3_url
StatsMode = Literal["quick", "sampled", "detailed"]
# Cache configuration
CACHE_VERSION = "1.0"
CACHE_PREFIX = ".deltaglider"
# ============================================================================
# Internal Helper Functions
# ============================================================================
def _fetch_delta_metadata(
client: Any,
bucket: str,
delta_keys: list[str],
max_timeout: int = 600,
) -> dict[str, dict[str, Any]]:
"""Fetch metadata for delta files in parallel with timeout.
Args:
client: DeltaGliderClient instance
bucket: S3 bucket name
delta_keys: List of delta file keys
max_timeout: Maximum total timeout in seconds (default: 600 = 10 min)
Returns:
Dict mapping delta key -> metadata dict
"""
metadata_map: dict[str, dict[str, Any]] = {}
if not delta_keys:
return metadata_map
client.service.logger.info(
f"Fetching metadata for {len(delta_keys)} delta files in parallel..."
)
def fetch_single_metadata(key: str) -> tuple[str, dict[str, Any] | None]:
try:
obj_head = client.service.storage.head(f"{bucket}/{key}")
if obj_head and obj_head.metadata:
return key, obj_head.metadata
except Exception as e:
client.service.logger.debug(f"Failed to fetch metadata for {key}: {e}")
return key, None
with concurrent.futures.ThreadPoolExecutor(max_workers=min(10, len(delta_keys))) as executor:
futures = [executor.submit(fetch_single_metadata, key) for key in delta_keys]
# Calculate timeout: 60s per file, capped at max_timeout
timeout_per_file = 60
total_timeout = min(len(delta_keys) * timeout_per_file, max_timeout)
try:
for future in concurrent.futures.as_completed(futures, timeout=total_timeout):
try:
key, metadata = future.result(timeout=5) # 5s per result
if metadata:
metadata_map[key] = metadata
except concurrent.futures.TimeoutError:
client.service.logger.warning("Timeout fetching metadata for a delta file")
continue
except concurrent.futures.TimeoutError:
client.service.logger.warning(
f"_fetch_delta_metadata: Timeout after {total_timeout}s. "
f"Fetched {len(metadata_map)}/{len(delta_keys)} metadata entries. "
f"Continuing with partial metadata..."
)
# Cancel remaining futures
for future in futures:
future.cancel()
return metadata_map
def _extract_deltaspace(key: str) -> str:
"""Return the delta space (prefix) for a given object key."""
if "/" in key:
return key.rsplit("/", 1)[0]
return ""
def _get_cache_key(mode: StatsMode) -> str:
"""Get the S3 key for a cache file based on mode.
Args:
mode: Stats mode (quick, sampled, or detailed)
Returns:
S3 key like ".deltaglider/stats_quick.json"
"""
return f"{CACHE_PREFIX}/stats_{mode}.json"
def _read_stats_cache(
client: Any,
bucket: str,
mode: StatsMode,
) -> tuple[BucketStats | None, dict[str, Any] | None]:
"""Read cached stats from S3 if available.
Args:
client: DeltaGliderClient instance
bucket: S3 bucket name
mode: Stats mode to read cache for
Returns:
Tuple of (BucketStats | None, validation_data | None)
Returns (None, None) if cache doesn't exist or is invalid
"""
cache_key = _get_cache_key(mode)
try:
# Try to read cache file from S3
obj = client.service.storage.get(f"{bucket}/{cache_key}")
if not obj or not obj.data:
return None, None
# Parse JSON
cache_data = json.loads(obj.data.decode("utf-8"))
# Validate version
if cache_data.get("version") != CACHE_VERSION:
client.service.logger.warning(
f"Cache version mismatch: expected {CACHE_VERSION}, got {cache_data.get('version')}"
)
return None, None
# Validate mode
if cache_data.get("mode") != mode:
client.service.logger.warning(
f"Cache mode mismatch: expected {mode}, got {cache_data.get('mode')}"
)
return None, None
# Extract stats and validation data
stats_dict = cache_data.get("stats")
validation_data = cache_data.get("validation")
if not stats_dict or not validation_data:
client.service.logger.warning("Cache missing stats or validation data")
return None, None
# Reconstruct BucketStats from dict
stats = BucketStats(**stats_dict)
client.service.logger.debug(
f"Successfully read cache for {bucket} (mode={mode}, "
f"computed_at={cache_data.get('computed_at')})"
)
return stats, validation_data
except FileNotFoundError:
# Cache doesn't exist yet - this is normal
client.service.logger.debug(f"No cache found for {bucket} (mode={mode})")
return None, None
except json.JSONDecodeError as e:
client.service.logger.warning(f"Invalid JSON in cache file: {e}")
return None, None
except Exception as e:
client.service.logger.warning(f"Error reading cache: {e}")
return None, None
def _write_stats_cache(
client: Any,
bucket: str,
mode: StatsMode,
stats: BucketStats,
object_count: int,
compressed_size: int,
) -> None:
"""Write computed stats to S3 cache.
Args:
client: DeltaGliderClient instance
bucket: S3 bucket name
mode: Stats mode being cached
stats: Computed BucketStats to cache
object_count: Current object count (for validation)
compressed_size: Current compressed size (for validation)
"""
cache_key = _get_cache_key(mode)
try:
# Build cache structure
cache_data = {
"version": CACHE_VERSION,
"mode": mode,
"computed_at": datetime.now(UTC).isoformat(),
"validation": {
"object_count": object_count,
"compressed_size": compressed_size,
},
"stats": asdict(stats),
}
# Serialize to JSON
cache_json = json.dumps(cache_data, indent=2)
# Write to S3
client.service.storage.put(
address=f"{bucket}/{cache_key}",
data=cache_json.encode("utf-8"),
metadata={
"content-type": "application/json",
"x-deltaglider-cache": "true",
},
)
client.service.logger.info(
f"Wrote cache for {bucket} (mode={mode}, {len(cache_json)} bytes)"
)
except Exception as e:
# Log warning but don't fail - caching is optional
client.service.logger.warning(f"Failed to write cache (non-fatal): {e}")
def _is_cache_valid(
cached_validation: dict[str, Any],
current_object_count: int,
current_compressed_size: int,
) -> bool:
"""Check if cached stats are still valid based on bucket state.
Validation strategy: Compare object count and total compressed size.
If either changed, the cache is stale.
Args:
cached_validation: Validation data from cache
current_object_count: Current object count from LIST
current_compressed_size: Current compressed size from LIST
Returns:
True if cache is still valid, False if stale
"""
cached_count = cached_validation.get("object_count")
cached_size = cached_validation.get("compressed_size")
if cached_count != current_object_count:
return False
if cached_size != current_compressed_size:
return False
return True
def _build_object_info_list(
raw_objects: list[dict[str, Any]],
metadata_map: dict[str, dict[str, Any]],
logger: Any,
sampled_space_metadata: dict[str, dict[str, Any]] | None = None,
) -> list[ObjectInfo]:
"""Build ObjectInfo list from raw objects and metadata.
Args:
raw_objects: List of raw object dicts from S3 LIST
metadata_map: Dict of key -> metadata for delta files
logger: Logger instance
Returns:
List of ObjectInfo objects
"""
all_objects = []
for obj_dict in raw_objects:
key = obj_dict["key"]
size = obj_dict["size"]
is_delta = key.endswith(".delta")
deltaspace = _extract_deltaspace(key)
# Get metadata from map (empty dict if not present)
metadata = metadata_map.get(key)
if metadata is None and sampled_space_metadata and deltaspace in sampled_space_metadata:
metadata = sampled_space_metadata[deltaspace]
if metadata is None:
metadata = {}
# Parse compression ratio and original size
compression_ratio = 0.0
original_size = size
if is_delta and metadata:
try:
ratio_str = metadata.get("compression_ratio", "0.0")
compression_ratio = float(ratio_str) if ratio_str != "unknown" else 0.0
except (ValueError, TypeError):
compression_ratio = 0.0
try:
if "file_size" in metadata:
original_size = int(metadata["file_size"])
logger.debug(f"Delta {key}: using original_size={original_size} from metadata")
else:
logger.warning(
f"Delta {key}: metadata missing 'file_size' key. "
f"Available keys: {list(metadata.keys())}. "
f"Using compressed size={size} as fallback"
)
original_size = size
except (ValueError, TypeError) as e:
logger.warning(
f"Delta {key}: failed to parse file_size from metadata: {e}. "
f"Using compressed size={size} as fallback"
)
original_size = size
all_objects.append(
ObjectInfo(
key=key,
size=size,
last_modified=obj_dict.get("last_modified", ""),
etag=obj_dict.get("etag"),
storage_class=obj_dict.get("storage_class", "STANDARD"),
original_size=original_size,
compressed_size=size,
is_delta=is_delta,
compression_ratio=compression_ratio,
reference_key=metadata.get("ref_key") if metadata else None,
)
)
return all_objects
def _calculate_bucket_statistics(
all_objects: list[ObjectInfo],
bucket: str,
logger: Any,
) -> BucketStats:
"""Calculate statistics from ObjectInfo list.
Args:
all_objects: List of ObjectInfo objects
bucket: Bucket name for stats
logger: Logger instance
Returns:
BucketStats object
"""
total_original_size = 0
total_compressed_size = 0
delta_count = 0
direct_count = 0
reference_files = {} # deltaspace -> size
# First pass: identify object types and reference files
for obj in all_objects:
if obj.key.endswith("/reference.bin") or obj.key == "reference.bin":
deltaspace = obj.key.rsplit("/reference.bin", 1)[0] if "/" in obj.key else ""
reference_files[deltaspace] = obj.size
elif obj.is_delta:
delta_count += 1
else:
direct_count += 1
# Second pass: calculate sizes
for obj in all_objects:
# Skip reference.bin (handled separately)
if obj.key.endswith("/reference.bin") or obj.key == "reference.bin":
continue
if obj.is_delta:
# Delta: use original_size if available, otherwise compressed size
if obj.original_size and obj.original_size != obj.size:
logger.debug(f"Delta {obj.key}: using original_size={obj.original_size}")
total_original_size += obj.original_size
else:
# This warning should only appear if metadata is missing or incomplete
# If you see this, the delta file may have been uploaded with an older
# version of DeltaGlider or the upload was incomplete
logger.warning(
f"Delta {obj.key}: no original_size metadata "
f"(original_size={obj.original_size}, size={obj.size}). "
f"Using compressed size as fallback. "
f"This may undercount space savings."
)
total_original_size += obj.size
total_compressed_size += obj.size
else:
# Direct files: original = compressed
total_original_size += obj.size
total_compressed_size += obj.size
# Handle reference.bin files
total_reference_size = sum(reference_files.values())
if delta_count > 0 and total_reference_size > 0:
total_compressed_size += total_reference_size
logger.info(
f"Including {len(reference_files)} reference.bin file(s) "
f"({total_reference_size:,} bytes) in compressed size"
)
elif delta_count == 0 and total_reference_size > 0:
_log_orphaned_references(bucket, reference_files, total_reference_size, logger)
# Calculate final metrics
space_saved = total_original_size - total_compressed_size
avg_ratio = (space_saved / total_original_size) if total_original_size > 0 else 0.0
return BucketStats(
bucket=bucket,
object_count=delta_count + direct_count,
total_size=total_original_size,
compressed_size=total_compressed_size,
space_saved=space_saved,
average_compression_ratio=avg_ratio,
delta_objects=delta_count,
direct_objects=direct_count,
)
def _log_orphaned_references(
bucket: str,
reference_files: dict[str, int],
total_reference_size: int,
logger: Any,
) -> None:
"""Log warning about orphaned reference.bin files.
Args:
bucket: Bucket name
reference_files: Dict of deltaspace -> size
total_reference_size: Total size of all reference files
logger: Logger instance
"""
waste_mb = total_reference_size / 1024 / 1024
logger.warning(
f"\n{'=' * 60}\n"
f"WARNING: ORPHANED REFERENCE FILE(S) DETECTED!\n"
f"{'=' * 60}\n"
f"Found {len(reference_files)} reference.bin file(s) totaling "
f"{total_reference_size:,} bytes ({waste_mb:.2f} MB)\n"
f"but NO delta files are using them.\n"
f"\n"
f"This wastes {waste_mb:.2f} MB of storage!\n"
f"\n"
f"Orphaned reference files:\n"
)
for deltaspace, size in reference_files.items():
path = f"{deltaspace}/reference.bin" if deltaspace else "reference.bin"
logger.warning(f" - s3://{bucket}/{path} ({size:,} bytes)")
logger.warning("\nConsider removing these orphaned files:\n")
for deltaspace in reference_files:
path = f"{deltaspace}/reference.bin" if deltaspace else "reference.bin"
logger.warning(f" aws s3 rm s3://{bucket}/{path}")
logger.warning(f"{'=' * 60}")
def get_object_info(
client: Any, # DeltaGliderClient
s3_url: str,
) -> ObjectInfo:
"""Get detailed object information including compression stats.
Args:
client: DeltaGliderClient instance
s3_url: S3 URL of the object
Returns:
ObjectInfo with detailed metadata
"""
address = parse_s3_url(s3_url, allow_empty_key=False)
bucket = address.bucket
key = address.key
# Get object metadata
obj_head = client.service.storage.head(f"{bucket}/{key}")
if not obj_head:
raise FileNotFoundError(f"Object not found: {s3_url}")
metadata = obj_head.metadata
is_delta = key.endswith(".delta")
return ObjectInfo(
key=key,
size=obj_head.size,
last_modified=metadata.get("last_modified", ""),
etag=metadata.get("etag"),
original_size=int(metadata.get("file_size", obj_head.size)),
compressed_size=obj_head.size,
compression_ratio=float(metadata.get("compression_ratio", 0.0)),
is_delta=is_delta,
reference_key=metadata.get("ref_key"),
)
def get_bucket_stats(
client: Any, # DeltaGliderClient
bucket: str,
mode: StatsMode = "quick",
use_cache: bool = True,
refresh_cache: bool = False,
) -> BucketStats:
"""Get statistics for a bucket with configurable metadata strategies and caching.
Modes:
- ``quick`` (default): Stream LIST results only. Compression metrics for delta files are
approximate (falls back to delta size when metadata is unavailable).
- ``sampled``: Fetch HEAD metadata for a single delta per delta-space and reuse the ratios for
other deltas in the same space. Balances accuracy and speed.
- ``detailed``: Fetch HEAD metadata for every delta object for the most accurate statistics.
Caching:
- Stats are cached per mode in ``.deltaglider/stats_{mode}.json``
- Cache is validated using object count and compressed size from LIST
- If bucket changed, cache is recomputed automatically
- Use ``refresh_cache=True`` to force recomputation
- Use ``use_cache=False`` to skip caching entirely
**Robustness**: This function is designed to always return valid stats:
- Returns partial stats if timeouts or pagination issues occur
- Returns empty stats (zeros) if bucket listing completely fails
- Never hangs indefinitely (max 10 min timeout, 10M object limit)
Args:
client: DeltaGliderClient instance
bucket: S3 bucket name
mode: Stats mode ("quick", "sampled", or "detailed")
use_cache: If True, use cached stats when available (default: True)
refresh_cache: If True, force cache recomputation even if valid (default: False)
Returns:
BucketStats with compression and space savings info. Always returns a valid BucketStats
object, even if errors occur (will return empty/partial stats with warnings logged).
Raises:
RuntimeError: Only if bucket listing fails immediately with no objects collected.
All other errors result in partial/empty stats being returned.
Performance:
- With cache hit: ~50-100ms (LIST + cache read + validation)
- quick (no cache): ~50ms for any bucket size (LIST calls only)
- sampled (no cache): LIST + one HEAD per delta-space
- detailed (no cache): LIST + HEAD for every delta (slowest but accurate)
- Max timeout: 10 minutes (prevents indefinite hangs)
- Max objects: 10M (prevents infinite loops)
Example:
# Use cached stats (fast, ~100ms)
stats = client.get_bucket_stats('releases')
# Force refresh (slow, recomputes everything)
stats = client.get_bucket_stats('releases', refresh_cache=True)
# Skip cache entirely
stats = client.get_bucket_stats('releases', use_cache=False)
# Different modes with caching
stats_sampled = client.get_bucket_stats('releases', mode='sampled')
stats_detailed = client.get_bucket_stats('releases', mode='detailed')
"""
try:
if mode not in {"quick", "sampled", "detailed"}:
raise ValueError(f"Unknown stats mode: {mode}")
# Phase 1: Always do a quick LIST to get current state (needed for validation)
import time
phase1_start = time.time()
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 1: Starting LIST operation for bucket '{bucket}'"
)
listing = list_all_objects(
client.service.storage,
bucket=bucket,
max_keys=1000,
logger=client.service.logger,
)
raw_objects = listing.objects
# Calculate validation metrics from LIST
current_object_count = len(raw_objects)
current_compressed_size = sum(obj["size"] for obj in raw_objects)
phase1_duration = time.time() - phase1_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 1: LIST completed in {phase1_duration:.2f}s - "
f"Found {current_object_count} objects, {current_compressed_size:,} bytes total"
)
# Phase 2: Try to use cache if enabled and not forcing refresh
phase2_start = time.time()
if use_cache and not refresh_cache:
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 2: Checking cache for mode '{mode}'"
)
cached_stats, cached_validation = _read_stats_cache(client, bucket, mode)
if cached_stats and cached_validation:
# Validate cache against current bucket state
if _is_cache_valid(
cached_validation, current_object_count, current_compressed_size
):
phase2_duration = time.time() - phase2_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 2: Cache HIT in {phase2_duration:.2f}s - "
f"Using cached stats for {bucket} (mode={mode}, bucket unchanged)"
)
return cached_stats
else:
phase2_duration = time.time() - phase2_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 2: Cache INVALID in {phase2_duration:.2f}s - "
f"Bucket changed: count {cached_validation.get('object_count')}{current_object_count}, "
f"size {cached_validation.get('compressed_size')}{current_compressed_size}"
)
else:
phase2_duration = time.time() - phase2_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 2: Cache MISS in {phase2_duration:.2f}s - "
f"No valid cache found"
)
else:
if refresh_cache:
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 2: Cache SKIPPED (refresh requested)"
)
elif not use_cache:
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 2: Cache DISABLED"
)
# Phase 3: Cache miss or invalid - compute stats from scratch
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 3: Computing stats (mode={mode})"
)
# Phase 4: Extract delta keys for metadata fetching
phase4_start = time.time()
delta_keys = [obj["key"] for obj in raw_objects if obj["key"].endswith(".delta")]
phase4_duration = time.time() - phase4_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 4: Delta extraction completed in {phase4_duration:.3f}s - "
f"Found {len(delta_keys)} delta files"
)
# Phase 5: Fetch metadata for delta files based on mode
phase5_start = time.time()
metadata_map: dict[str, dict[str, Any]] = {}
sampled_space_metadata: dict[str, dict[str, Any]] | None = None
if delta_keys:
if mode == "detailed":
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 5: Fetching metadata for ALL {len(delta_keys)} delta files"
)
metadata_map = _fetch_delta_metadata(client, bucket, delta_keys)
elif mode == "sampled":
# Sample one delta per deltaspace
seen_spaces: set[str] = set()
sampled_keys: list[str] = []
for key in delta_keys:
space = _extract_deltaspace(key)
if space not in seen_spaces:
seen_spaces.add(space)
sampled_keys.append(key)
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 5: Sampling {len(sampled_keys)} delta files "
f"(one per deltaspace) out of {len(delta_keys)} total delta files"
)
# Log which files are being sampled
if sampled_keys:
for idx, key in enumerate(sampled_keys[:10], 1): # Show first 10
space = _extract_deltaspace(key)
client.service.logger.info(
f" [{idx}] Sampling: {key} (deltaspace: '{space or '(root)'}')"
)
if len(sampled_keys) > 10:
client.service.logger.info(f" ... and {len(sampled_keys) - 10} more")
if sampled_keys:
metadata_map = _fetch_delta_metadata(client, bucket, sampled_keys)
sampled_space_metadata = {
_extract_deltaspace(k): metadata for k, metadata in metadata_map.items()
}
phase5_duration = time.time() - phase5_start
if mode == "quick":
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 5: Skipped metadata fetching (quick mode) in {phase5_duration:.3f}s"
)
else:
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 5: Metadata fetching completed in {phase5_duration:.2f}s - "
f"Fetched {len(metadata_map)} metadata records"
)
# Phase 6: Build ObjectInfo list
phase6_start = time.time()
all_objects = _build_object_info_list(
raw_objects,
metadata_map,
client.service.logger,
sampled_space_metadata,
)
phase6_duration = time.time() - phase6_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 6: ObjectInfo list built in {phase6_duration:.3f}s - "
f"{len(all_objects)} objects processed"
)
# Phase 7: Calculate final statistics
phase7_start = time.time()
stats = _calculate_bucket_statistics(all_objects, bucket, client.service.logger)
phase7_duration = time.time() - phase7_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 7: Statistics calculated in {phase7_duration:.3f}s - "
f"{stats.delta_objects} delta, {stats.direct_objects} direct objects"
)
# Phase 8: Write cache if enabled
phase8_start = time.time()
if use_cache:
_write_stats_cache(
client=client,
bucket=bucket,
mode=mode,
stats=stats,
object_count=current_object_count,
compressed_size=current_compressed_size,
)
phase8_duration = time.time() - phase8_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 8: Cache written in {phase8_duration:.3f}s"
)
else:
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] Phase 8: Cache write skipped (caching disabled)"
)
# Summary
total_duration = time.time() - phase1_start
client.service.logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] COMPLETE: Total time {total_duration:.2f}s for bucket '{bucket}' (mode={mode})"
)
return stats
except Exception as e:
# Last resort: return empty stats with error indication
client.service.logger.error(
f"get_bucket_stats: Failed to build statistics for '{bucket}': {e}. "
f"Returning empty stats."
)
return BucketStats(
bucket=bucket,
object_count=0,
total_size=0,
compressed_size=0,
space_saved=0,
average_compression_ratio=0.0,
delta_objects=0,
direct_objects=0,
)
# ============================================================================
# Public API Functions
# ============================================================================
def estimate_compression(
client: Any, # DeltaGliderClient
file_path: str | Path,
bucket: str,
prefix: str = "",
sample_size: int = 1024 * 1024,
) -> CompressionEstimate:
"""Estimate compression ratio before upload.
Args:
client: DeltaGliderClient instance
file_path: Local file to estimate
bucket: Target bucket
prefix: Target prefix (for finding similar files)
sample_size: Bytes to sample for estimation (default 1MB)
Returns:
CompressionEstimate with predicted compression
"""
file_path = Path(file_path)
file_size = file_path.stat().st_size
filename = file_path.name
ext = file_path.suffix.lower()
# Already compressed formats that won't benefit from delta
incompressible = {".jpg", ".jpeg", ".png", ".mp4", ".mp3", ".avi", ".mov"}
if ext in incompressible:
return CompressionEstimate(
original_size=file_size,
estimated_compressed_size=file_size,
estimated_ratio=0.0,
confidence=0.95,
should_use_delta=False,
)
if not is_delta_candidate(filename):
# Unknown type, conservative estimate
return CompressionEstimate(
original_size=file_size,
estimated_compressed_size=file_size,
estimated_ratio=0.0,
confidence=0.5,
should_use_delta=file_size > 1024 * 1024, # Only for files > 1MB
)
# Look for similar files in the target location
similar_files = find_similar_files(client, bucket, prefix, file_path.name)
if similar_files:
# If we have similar files, estimate high compression
estimated_ratio = 0.99 # 99% compression typical for similar versions
confidence = 0.9
recommended_ref = similar_files[0]["Key"] if similar_files else None
else:
# First file of its type
estimated_ratio = 0.0
confidence = 0.7
recommended_ref = None
estimated_size = int(file_size * (1 - estimated_ratio))
return CompressionEstimate(
original_size=file_size,
estimated_compressed_size=estimated_size,
estimated_ratio=estimated_ratio,
confidence=confidence,
recommended_reference=recommended_ref,
should_use_delta=True,
)
def find_similar_files(
client: Any, # DeltaGliderClient
bucket: str,
prefix: str,
filename: str,
limit: int = 5,
) -> list[dict[str, Any]]:
"""Find similar files that could serve as references.
Args:
client: DeltaGliderClient instance
bucket: S3 bucket
prefix: Prefix to search in
filename: Filename to match against
limit: Maximum number of results
Returns:
List of similar files with scores
"""
# List objects in the prefix (no metadata needed for similarity check)
response = client.list_objects(
Bucket=bucket,
Prefix=prefix,
MaxKeys=1000,
FetchMetadata=False, # Don't need metadata for similarity
)
similar: list[dict[str, Any]] = []
base_name = Path(filename).stem
ext = Path(filename).suffix
for obj in response["Contents"]:
obj_key = obj["Key"]
obj_base = Path(obj_key).stem
obj_ext = Path(obj_key).suffix
# Skip delta files and references
if obj_key.endswith(".delta") or obj_key.endswith("reference.bin"):
continue
score = 0.0
# Extension match
if ext == obj_ext:
score += 0.5
# Base name similarity
if base_name in obj_base or obj_base in base_name:
score += 0.3
# Version pattern match
if re.search(r"v?\d+[\.\d]*", base_name) and re.search(r"v?\d+[\.\d]*", obj_base):
score += 0.2
if score > 0.5:
similar.append(
{
"Key": obj_key,
"Size": obj["Size"],
"Similarity": score,
"LastModified": obj["LastModified"],
}
)
# Sort by similarity
similar.sort(key=lambda x: x["Similarity"], reverse=True) # type: ignore
return similar[:limit]

View File

@@ -1,5 +1,10 @@
"""Core domain for DeltaGlider."""
from .delta_extensions import (
DEFAULT_COMPOUND_DELTA_EXTENSIONS,
DEFAULT_DELTA_EXTENSIONS,
is_delta_candidate,
)
from .errors import (
DeltaGliderError,
DiffDecodeError,
@@ -19,6 +24,7 @@ from .models import (
Sha256,
VerifyResult,
)
from .s3_uri import S3Url, build_s3_url, is_s3_url, parse_s3_url
from .service import DeltaService
__all__ = [
@@ -38,4 +44,11 @@ __all__ = [
"PutSummary",
"VerifyResult",
"DeltaService",
"DEFAULT_DELTA_EXTENSIONS",
"DEFAULT_COMPOUND_DELTA_EXTENSIONS",
"is_delta_candidate",
"S3Url",
"build_s3_url",
"is_s3_url",
"parse_s3_url",
]

View File

@@ -0,0 +1,56 @@
"""Shared delta compression extension policy."""
from __future__ import annotations
from collections.abc import Collection, Iterable
# Compound extensions must be checked before simple suffix matching so that
# multi-part archives like ".tar.gz" are handled correctly.
DEFAULT_COMPOUND_DELTA_EXTENSIONS: tuple[str, ...] = (".tar.gz", ".tar.bz2", ".tar.xz")
# Simple extensions that benefit from delta compression. Keep this structure
# immutable so it can be safely reused across modules.
DEFAULT_DELTA_EXTENSIONS: frozenset[str] = frozenset(
{
".zip",
".tar",
".gz",
".tgz",
".bz2",
".xz",
".7z",
".rar",
".dmg",
".iso",
".pkg",
".deb",
".rpm",
".apk",
".jar",
".war",
".ear",
}
)
def is_delta_candidate(
filename: str,
*,
simple_extensions: Collection[str] = DEFAULT_DELTA_EXTENSIONS,
compound_extensions: Iterable[str] = DEFAULT_COMPOUND_DELTA_EXTENSIONS,
) -> bool:
"""Check if a filename should use delta compression based on extension."""
name_lower = filename.lower()
for ext in compound_extensions:
if name_lower.endswith(ext):
return True
return any(name_lower.endswith(ext) for ext in simple_extensions)
__all__ = [
"DEFAULT_COMPOUND_DELTA_EXTENSIONS",
"DEFAULT_DELTA_EXTENSIONS",
"is_delta_candidate",
]

View File

@@ -47,3 +47,15 @@ class PolicyViolationWarning(Warning):
"""Policy violation warning."""
pass
class CacheMissError(DeltaGliderError):
"""Cache miss - file not found in cache."""
pass
class CacheCorruptionError(DeltaGliderError):
"""Cache corruption - SHA mismatch or tampering detected."""
pass

View File

@@ -0,0 +1,206 @@
"""Shared helpers for listing bucket objects with pagination support."""
from __future__ import annotations
from dataclasses import dataclass, field
from datetime import datetime, timezone
from typing import Any
from ..ports.storage import ObjectHead
@dataclass(slots=True)
class ObjectListing:
"""All objects and prefixes returned from a bucket listing."""
objects: list[dict[str, Any]] = field(default_factory=list)
common_prefixes: list[str] = field(default_factory=list)
key_count: int = 0
is_truncated: bool = False
next_continuation_token: str | None = None
def list_objects_page(
storage: Any,
*,
bucket: str,
prefix: str = "",
delimiter: str = "",
max_keys: int = 1000,
start_after: str | None = None,
continuation_token: str | None = None,
) -> ObjectListing:
"""Perform a single list_objects call using the storage adapter."""
if not hasattr(storage, "list_objects"):
raise NotImplementedError("Storage adapter does not support list_objects")
response = storage.list_objects(
bucket=bucket,
prefix=prefix,
delimiter=delimiter,
max_keys=max_keys,
start_after=start_after,
continuation_token=continuation_token,
)
return ObjectListing(
objects=list(response.get("objects", [])),
common_prefixes=list(response.get("common_prefixes", [])),
key_count=response.get("key_count", len(response.get("objects", []))),
is_truncated=bool(response.get("is_truncated", False)),
next_continuation_token=response.get("next_continuation_token"),
)
def list_all_objects(
storage: Any,
*,
bucket: str,
prefix: str = "",
delimiter: str = "",
max_keys: int = 1000,
logger: Any | None = None,
max_iterations: int = 10_000,
) -> ObjectListing:
"""Fetch all objects under the given bucket/prefix with pagination safety."""
import time
from datetime import UTC, datetime
aggregated = ObjectListing()
continuation_token: str | None = None
iteration_count = 0
list_start_time = time.time()
while True:
iteration_count += 1
if iteration_count > max_iterations:
if logger:
logger.warning(
"list_all_objects: reached max iterations (%s). Returning partial results.",
max_iterations,
)
aggregated.is_truncated = True
aggregated.next_continuation_token = continuation_token
break
# Log progress every 10 pages or on first page
if logger and (iteration_count == 1 or iteration_count % 10 == 0):
elapsed = time.time() - list_start_time
objects_per_sec = len(aggregated.objects) / elapsed if elapsed > 0 else 0
token_info = f", token={continuation_token[:20]}..." if continuation_token else ""
logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] LIST pagination: "
f"page {iteration_count}, {len(aggregated.objects)} objects so far "
f"({objects_per_sec:.0f} obj/s, {elapsed:.1f}s elapsed{token_info})"
)
# Warn if taking very long (>60s)
if elapsed > 60 and iteration_count % 50 == 0:
estimated_total = (len(aggregated.objects) / iteration_count) * max_iterations
logger.warning(
f"LIST operation is slow ({elapsed:.0f}s elapsed). "
f"This bucket has MANY objects ({len(aggregated.objects)} so far). "
f"Consider using a smaller prefix or enabling caching. "
f"Estimated remaining: {estimated_total - len(aggregated.objects):.0f} objects"
)
try:
page = list_objects_page(
storage,
bucket=bucket,
prefix=prefix,
delimiter=delimiter,
max_keys=max_keys,
continuation_token=continuation_token,
)
except Exception as exc:
if not aggregated.objects:
raise RuntimeError(f"Failed to list objects for bucket '{bucket}': {exc}") from exc
if logger:
logger.warning(
"list_all_objects: pagination error after %s objects: %s. Returning partial results.",
len(aggregated.objects),
exc,
)
aggregated.is_truncated = True
aggregated.next_continuation_token = continuation_token
break
aggregated.objects.extend(page.objects)
aggregated.common_prefixes.extend(page.common_prefixes)
aggregated.key_count += page.key_count
if not page.is_truncated:
aggregated.is_truncated = False
aggregated.next_continuation_token = None
if logger:
elapsed = time.time() - list_start_time
logger.info(
f"[{datetime.now(UTC).strftime('%H:%M:%S.%f')[:-3]}] LIST complete: "
f"{iteration_count} pages, {len(aggregated.objects)} objects total in {elapsed:.2f}s"
)
break
continuation_token = page.next_continuation_token
if not continuation_token:
if logger:
logger.warning(
"list_all_objects: truncated response without continuation token after %s objects.",
len(aggregated.objects),
)
aggregated.is_truncated = True
aggregated.next_continuation_token = None
break
if aggregated.common_prefixes:
seen: set[str] = set()
unique_prefixes: list[str] = []
for prefix in aggregated.common_prefixes:
if prefix not in seen:
seen.add(prefix)
unique_prefixes.append(prefix)
aggregated.common_prefixes = unique_prefixes
aggregated.key_count = len(aggregated.objects)
return aggregated
def _parse_last_modified(value: Any) -> datetime:
if isinstance(value, datetime):
dt = value
elif value:
text = str(value)
if text.endswith("Z"):
text = text[:-1] + "+00:00"
try:
dt = datetime.fromisoformat(text)
except ValueError:
dt = datetime.fromtimestamp(0, tz=timezone.utc) # noqa: UP017
else:
dt = datetime.fromtimestamp(0, tz=timezone.utc) # noqa: UP017
if dt.tzinfo is None:
dt = dt.replace(tzinfo=timezone.utc) # noqa: UP017
return dt
def object_dict_to_head(obj: dict[str, Any]) -> ObjectHead:
"""Convert a list_objects entry into ObjectHead for compatibility uses."""
metadata = obj.get("metadata")
if metadata is None or not isinstance(metadata, dict):
metadata = {}
return ObjectHead(
key=obj["key"],
size=int(obj.get("size", 0)),
etag=str(obj.get("etag", "")),
last_modified=_parse_last_modified(obj.get("last_modified")),
metadata=metadata,
)
__all__ = [
"ObjectListing",
"list_objects_page",
"list_all_objects",
"object_dict_to_head",
]

View File

@@ -0,0 +1,85 @@
"""Utilities for working with S3-style URLs and keys."""
from __future__ import annotations
from typing import NamedTuple
S3_SCHEME = "s3://"
class S3Url(NamedTuple):
"""Normalized representation of an S3 URL."""
bucket: str
key: str = ""
def to_url(self) -> str:
"""Return the canonical string form."""
if self.key:
return f"{S3_SCHEME}{self.bucket}/{self.key}"
return f"{S3_SCHEME}{self.bucket}"
def with_key(self, key: str) -> S3Url:
"""Return a new S3Url with a different key."""
return S3Url(self.bucket, key.lstrip("/"))
def join_key(self, suffix: str) -> S3Url:
"""Append a suffix to the key using '/' semantics."""
suffix = suffix.lstrip("/")
if not self.key:
return self.with_key(suffix)
if not suffix:
return self
return self.with_key(f"{self.key.rstrip('/')}/{suffix}")
def is_s3_url(value: str) -> bool:
"""Check if a string is an S3 URL."""
return value.startswith(S3_SCHEME)
def parse_s3_url(
url: str,
*,
allow_empty_key: bool = True,
strip_trailing_slash: bool = False,
) -> S3Url:
"""Parse an S3 URL into bucket and key components."""
if not is_s3_url(url):
raise ValueError(f"Invalid S3 URL: {url}")
path = url[len(S3_SCHEME) :]
if strip_trailing_slash:
path = path.rstrip("/")
bucket, sep, key = path.partition("/")
if not bucket:
raise ValueError(f"S3 URL missing bucket: {url}")
if not sep:
key = ""
key = key.lstrip("/")
if not key and not allow_empty_key:
raise ValueError(f"S3 URL must include a key: {url}")
return S3Url(bucket=bucket, key=key)
def build_s3_url(bucket: str, key: str | None = None) -> str:
"""Build an S3 URL from components."""
if not bucket:
raise ValueError("Bucket name cannot be empty")
if key:
key = key.lstrip("/")
return f"{S3_SCHEME}{bucket}/{key}"
return f"{S3_SCHEME}{bucket}"
__all__ = [
"S3Url",
"build_s3_url",
"is_s3_url",
"parse_s3_url",
]

View File

@@ -15,6 +15,11 @@ from ..ports import (
StoragePort,
)
from ..ports.storage import ObjectHead
from .delta_extensions import (
DEFAULT_COMPOUND_DELTA_EXTENSIONS,
DEFAULT_DELTA_EXTENSIONS,
is_delta_candidate,
)
from .errors import (
DiffDecodeError,
DiffEncodeError,
@@ -58,51 +63,41 @@ class DeltaService:
self.tool_version = tool_version
self.max_ratio = max_ratio
# File extensions that should use delta compression
self.delta_extensions = {
".zip",
".tar",
".gz",
".tar.gz",
".tgz",
".bz2",
".tar.bz2",
".xz",
".tar.xz",
".7z",
".rar",
".dmg",
".iso",
".pkg",
".deb",
".rpm",
".apk",
".jar",
".war",
".ear",
}
# File extensions that should use delta compression. Keep mutable copies
# so advanced callers can customize the policy if needed.
self.delta_extensions = set(DEFAULT_DELTA_EXTENSIONS)
self.compound_delta_extensions = DEFAULT_COMPOUND_DELTA_EXTENSIONS
def should_use_delta(self, filename: str) -> bool:
"""Check if file should use delta compression based on extension."""
name_lower = filename.lower()
# Check compound extensions first
for ext in [".tar.gz", ".tar.bz2", ".tar.xz"]:
if name_lower.endswith(ext):
return True
# Check simple extensions
return any(name_lower.endswith(ext) for ext in self.delta_extensions)
return is_delta_candidate(
filename,
simple_extensions=self.delta_extensions,
compound_extensions=self.compound_delta_extensions,
)
def put(
self, local_file: Path, delta_space: DeltaSpace, max_ratio: float | None = None
self,
local_file: Path,
delta_space: DeltaSpace,
max_ratio: float | None = None,
override_name: str | None = None,
) -> PutSummary:
"""Upload file as reference or delta (for archive files) or directly (for other files)."""
"""Upload file as reference or delta (for archive files) or directly (for other files).
Args:
local_file: Path to the local file to upload
delta_space: DeltaSpace (bucket + prefix) for the upload
max_ratio: Maximum acceptable delta/file ratio (default: service max_ratio)
override_name: Optional name to use instead of local_file.name (useful for S3-to-S3 copies)
"""
if max_ratio is None:
max_ratio = self.max_ratio
start_time = self.clock.now()
file_size = local_file.stat().st_size
file_sha256 = self.hasher.sha256(local_file)
original_name = local_file.name
original_name = override_name if override_name else local_file.name
self.logger.info(
"Starting put operation",
@@ -230,7 +225,10 @@ class DeltaService:
with tempfile.TemporaryDirectory() as tmpdir:
tmp_path = Path(tmpdir)
delta_path = tmp_path / "delta"
ref_path = self.cache.ref_path(delta_space.bucket, delta_space.prefix)
# SECURITY: Use validated ref to prevent TOCTOU attacks
ref_path = self.cache.get_validated_ref(
delta_space.bucket, delta_space.prefix, delta_meta.ref_sha256
)
out_path = tmp_path / "output"
# Download delta
@@ -408,7 +406,8 @@ class DeltaService:
if not cache_hit:
self._cache_reference(delta_space, ref_sha256)
ref_path = self.cache.ref_path(delta_space.bucket, delta_space.prefix)
# SECURITY: Use validated ref to prevent TOCTOU attacks
ref_path = self.cache.get_validated_ref(delta_space.bucket, delta_space.prefix, ref_sha256)
# Create delta
with tempfile.NamedTemporaryFile(suffix=".delta") as delta_file:

View File

@@ -15,6 +15,26 @@ class CachePort(Protocol):
"""Check if reference exists and matches SHA."""
...
def get_validated_ref(self, bucket: str, prefix: str, expected_sha: str) -> Path:
"""Get cached reference with atomic SHA validation.
This method MUST be used instead of ref_path() to prevent TOCTOU attacks.
It validates the SHA256 hash at the time of use, not just at cache check time.
Args:
bucket: S3 bucket name
prefix: Prefix/deltaspace within bucket
expected_sha: Expected SHA256 hash of the file
Returns:
Path to the validated cached file
Raises:
CacheMissError: If cached file doesn't exist
CacheCorruptionError: If SHA doesn't match (file corrupted or tampered)
"""
...
def write_ref(self, bucket: str, prefix: str, src: Path) -> Path:
"""Cache reference file."""
...
@@ -22,3 +42,18 @@ class CachePort(Protocol):
def evict(self, bucket: str, prefix: str) -> None:
"""Remove cached reference."""
...
def clear(self) -> None:
"""Clear all cached references.
This method forcibly removes all cached data, useful for:
- Long-running applications that need to free memory
- Test cleanup
- Manual cache invalidation
- Ensuring fresh data fetch
Note: For filesystem caches, this removes all files in the cache directory.
For memory caches, this clears all in-memory data.
For encrypted caches, this also clears encryption key mappings.
"""
...

View File

@@ -0,0 +1,152 @@
"""Type-safe response builders using TypedDicts for internal type safety.
This module provides builder functions that construct boto3-compatible responses
with full compile-time type validation using TypedDicts. At runtime, TypedDicts
are plain dicts, so there's no conversion overhead.
Benefits:
- Field name typos caught by mypy (e.g., "HTTPStatusCode""HttpStatusCode")
- Wrong types caught by mypy (e.g., string instead of int)
- Missing required fields caught by mypy
- Extra unknown fields caught by mypy
"""
from typing import Any
from .types import (
CommonPrefix,
DeleteObjectResponse,
GetObjectResponse,
ListObjectsV2Response,
PutObjectResponse,
ResponseMetadata,
S3Object,
)
def build_response_metadata(status_code: int = 200) -> ResponseMetadata:
"""Build ResponseMetadata with full type safety via TypedDict.
TypedDict is a dict at runtime - no conversion needed!
mypy validates all fields match ResponseMetadata TypedDict.
Uses our types.py TypedDict which has proper NotRequired fields.
"""
# Build as TypedDict - mypy validates field names and types!
metadata: ResponseMetadata = {
"HTTPStatusCode": status_code,
# All other fields are NotRequired - can be omitted!
}
return metadata # Returns dict at runtime, ResponseMetadata type at compile-time
def build_put_response(
etag: str,
*,
version_id: str | None = None,
deltaglider_info: dict[str, Any] | None = None,
) -> PutObjectResponse:
"""Build PutObjectResponse with full type safety via TypedDict.
Uses our types.py TypedDict which has proper NotRequired fields.
mypy validates all field names, types, and structure.
"""
# Build as TypedDict - mypy catches typos and type errors!
response: PutObjectResponse = {
"ETag": etag,
"ResponseMetadata": build_response_metadata(),
}
if version_id:
response["VersionId"] = version_id
# DeltaGlider extension - add as Any field
if deltaglider_info:
response["DeltaGliderInfo"] = deltaglider_info # type: ignore[typeddict-item]
return response # Returns dict at runtime, PutObjectResponse type at compile-time
def build_get_response(
body: Any,
content_length: int,
etag: str,
metadata: dict[str, Any],
) -> GetObjectResponse:
"""Build GetObjectResponse with full type safety via TypedDict.
Uses our types.py TypedDict which has proper NotRequired fields.
mypy validates all field names, types, and structure.
"""
# Build as TypedDict - mypy catches typos and type errors!
response: GetObjectResponse = {
"Body": body,
"ContentLength": content_length,
"ETag": etag,
"Metadata": metadata,
"ResponseMetadata": build_response_metadata(),
}
return response # Returns dict at runtime, GetObjectResponse type at compile-time
def build_list_objects_response(
bucket: str,
prefix: str,
delimiter: str,
max_keys: int,
contents: list[S3Object],
common_prefixes: list[CommonPrefix] | None,
is_truncated: bool,
next_continuation_token: str | None,
continuation_token: str | None,
) -> ListObjectsV2Response:
"""Build ListObjectsV2Response with full type safety via TypedDict.
Uses our types.py TypedDict which has proper NotRequired fields.
mypy validates all field names, types, and structure.
"""
# Build as TypedDict - mypy catches typos and type errors!
response: ListObjectsV2Response = {
"IsTruncated": is_truncated,
"Contents": contents,
"Name": bucket,
"Prefix": prefix,
"Delimiter": delimiter,
"MaxKeys": max_keys,
"KeyCount": len(contents),
"ResponseMetadata": build_response_metadata(),
}
# Add optional fields
if common_prefixes:
response["CommonPrefixes"] = common_prefixes
if next_continuation_token:
response["NextContinuationToken"] = next_continuation_token
if continuation_token:
response["ContinuationToken"] = continuation_token
return response # Returns dict at runtime, ListObjectsV2Response type at compile-time
def build_delete_response(
delete_marker: bool = False,
status_code: int = 204,
deltaglider_info: dict[str, Any] | None = None,
) -> DeleteObjectResponse:
"""Build DeleteObjectResponse with full type safety via TypedDict.
Uses our types.py TypedDict which has proper NotRequired fields.
mypy validates all field names, types, and structure.
"""
# Build as TypedDict - mypy catches typos and type errors!
response: DeleteObjectResponse = {
"DeleteMarker": delete_marker,
"ResponseMetadata": build_response_metadata(status_code),
}
# DeltaGlider extension
if deltaglider_info:
response["DeltaGliderInfo"] = deltaglider_info # type: ignore[typeddict-item]
return response # Returns dict at runtime, DeleteObjectResponse type at compile-time

355
src/deltaglider/types.py Normal file
View File

@@ -0,0 +1,355 @@
"""Type definitions for boto3-compatible responses.
These TypedDict definitions provide type hints for DeltaGlider's boto3-compatible
responses. All methods return plain `dict[str, Any]` at runtime for maximum
flexibility and boto3 compatibility.
## Basic Usage (Recommended)
Use DeltaGlider with simple dict access - no type imports needed:
```python
from deltaglider import create_client
client = create_client()
# Returns plain dict - 100% boto3 compatible
response = client.put_object(Bucket='my-bucket', Key='file.zip', Body=data)
print(response['ETag'])
# List objects with dict access
listing = client.list_objects(Bucket='my-bucket')
for obj in listing['Contents']:
print(f"{obj['Key']}: {obj['Size']} bytes")
```
## Optional Type Hints
For IDE autocomplete and type checking, you can use our convenience TypedDicts:
```python
from deltaglider import create_client
from deltaglider.types import PutObjectResponse, ListObjectsV2Response
client = create_client()
response: PutObjectResponse = client.put_object(...) # IDE autocomplete
listing: ListObjectsV2Response = client.list_objects(...)
```
## Advanced: boto3-stubs Integration
For strictest type checking (requires boto3-stubs installation):
```bash
pip install boto3-stubs[s3]
```
```python
from mypy_boto3_s3.type_defs import PutObjectOutputTypeDef
response: PutObjectOutputTypeDef = client.put_object(...)
```
**Note**: boto3-stubs TypedDefs are very strict and require ALL optional fields.
DeltaGlider returns partial dicts for better boto3 compatibility, so boto3-stubs
types may show false positive errors. Use `dict[str, Any]` or our TypedDicts instead.
## Design Philosophy
DeltaGlider returns `dict[str, Any]` from all boto3-compatible methods because:
1. **Flexibility**: boto3 responses vary by service and operation
2. **Compatibility**: Exact match with boto3 runtime behavior
3. **Simplicity**: No complex type dependencies for users
4. **Optional Typing**: Users choose their preferred level of type safety
"""
from datetime import datetime
from typing import Any, Literal, NotRequired, TypedDict
# ============================================================================
# S3 Object Types
# ============================================================================
class S3Object(TypedDict):
"""An S3 object returned in list operations.
Compatible with boto3's S3.Client.list_objects_v2() response Contents.
"""
Key: str
Size: int
LastModified: datetime
ETag: NotRequired[str]
StorageClass: NotRequired[str]
Owner: NotRequired[dict[str, str]]
Metadata: NotRequired[dict[str, str]]
class CommonPrefix(TypedDict):
"""A common prefix (directory) in S3 listing.
Compatible with boto3's S3.Client.list_objects_v2() response CommonPrefixes.
"""
Prefix: str
# ============================================================================
# Response Metadata (used in all responses)
# ============================================================================
class ResponseMetadata(TypedDict):
"""Metadata about the API response.
Compatible with all boto3 responses.
"""
RequestId: NotRequired[str]
HostId: NotRequired[str]
HTTPStatusCode: int
HTTPHeaders: NotRequired[dict[str, str]]
RetryAttempts: NotRequired[int]
# ============================================================================
# List Operations Response Types
# ============================================================================
class ListObjectsV2Response(TypedDict):
"""Response from list_objects_v2 operation.
100% compatible with boto3's S3.Client.list_objects_v2() response.
Example:
```python
client = create_client()
response: ListObjectsV2Response = client.list_objects(
Bucket='my-bucket',
Prefix='path/',
Delimiter='/'
)
for obj in response['Contents']:
print(f"{obj['Key']}: {obj['Size']} bytes")
for prefix in response.get('CommonPrefixes', []):
print(f"Directory: {prefix['Prefix']}")
```
"""
Contents: list[S3Object]
Name: NotRequired[str] # Bucket name
Prefix: NotRequired[str]
Delimiter: NotRequired[str]
MaxKeys: NotRequired[int]
CommonPrefixes: NotRequired[list[CommonPrefix]]
EncodingType: NotRequired[str]
KeyCount: NotRequired[int]
ContinuationToken: NotRequired[str]
NextContinuationToken: NotRequired[str]
StartAfter: NotRequired[str]
IsTruncated: NotRequired[bool]
ResponseMetadata: NotRequired[ResponseMetadata]
# ============================================================================
# Put/Get/Delete Response Types
# ============================================================================
class PutObjectResponse(TypedDict):
"""Response from put_object operation.
Compatible with boto3's S3.Client.put_object() response.
"""
ETag: str
VersionId: NotRequired[str]
ServerSideEncryption: NotRequired[str]
ResponseMetadata: NotRequired[ResponseMetadata]
class GetObjectResponse(TypedDict):
"""Response from get_object operation.
Compatible with boto3's S3.Client.get_object() response.
"""
Body: Any # StreamingBody in boto3, bytes in DeltaGlider
ContentLength: int
ContentType: NotRequired[str]
ETag: NotRequired[str]
LastModified: NotRequired[datetime]
Metadata: NotRequired[dict[str, str]]
VersionId: NotRequired[str]
StorageClass: NotRequired[str]
ResponseMetadata: NotRequired[ResponseMetadata]
class DeleteObjectResponse(TypedDict):
"""Response from delete_object operation.
Compatible with boto3's S3.Client.delete_object() response.
"""
DeleteMarker: NotRequired[bool]
VersionId: NotRequired[str]
ResponseMetadata: NotRequired[ResponseMetadata]
class DeletedObject(TypedDict):
"""A successfully deleted object.
Compatible with boto3's S3.Client.delete_objects() response Deleted.
"""
Key: str
VersionId: NotRequired[str]
DeleteMarker: NotRequired[bool]
DeleteMarkerVersionId: NotRequired[str]
class DeleteError(TypedDict):
"""An error that occurred during deletion.
Compatible with boto3's S3.Client.delete_objects() response Errors.
"""
Key: str
Code: str
Message: str
VersionId: NotRequired[str]
class DeleteObjectsResponse(TypedDict):
"""Response from delete_objects operation.
Compatible with boto3's S3.Client.delete_objects() response.
"""
Deleted: NotRequired[list[DeletedObject]]
Errors: NotRequired[list[DeleteError]]
ResponseMetadata: NotRequired[ResponseMetadata]
# ============================================================================
# Head Object Response
# ============================================================================
class HeadObjectResponse(TypedDict):
"""Response from head_object operation.
Compatible with boto3's S3.Client.head_object() response.
"""
ContentLength: int
ContentType: NotRequired[str]
ETag: NotRequired[str]
LastModified: NotRequired[datetime]
Metadata: NotRequired[dict[str, str]]
VersionId: NotRequired[str]
StorageClass: NotRequired[str]
ResponseMetadata: NotRequired[ResponseMetadata]
# ============================================================================
# Bucket Operations
# ============================================================================
class Bucket(TypedDict):
"""An S3 bucket.
Compatible with boto3's S3.Client.list_buckets() response Buckets.
"""
Name: str
CreationDate: datetime
class ListBucketsResponse(TypedDict):
"""Response from list_buckets operation.
Compatible with boto3's S3.Client.list_buckets() response.
"""
Buckets: list[Bucket]
Owner: NotRequired[dict[str, str]]
ResponseMetadata: NotRequired[ResponseMetadata]
class CreateBucketResponse(TypedDict):
"""Response from create_bucket operation.
Compatible with boto3's S3.Client.create_bucket() response.
"""
Location: NotRequired[str]
ResponseMetadata: NotRequired[ResponseMetadata]
# ============================================================================
# Multipart Upload Types
# ============================================================================
class CompletedPart(TypedDict):
"""A completed part in a multipart upload."""
PartNumber: int
ETag: str
class CompleteMultipartUploadResponse(TypedDict):
"""Response from complete_multipart_upload operation."""
Location: NotRequired[str]
Bucket: NotRequired[str]
Key: NotRequired[str]
ETag: NotRequired[str]
VersionId: NotRequired[str]
ResponseMetadata: NotRequired[ResponseMetadata]
# ============================================================================
# Copy Operations
# ============================================================================
class CopyObjectResponse(TypedDict):
"""Response from copy_object operation.
Compatible with boto3's S3.Client.copy_object() response.
"""
CopyObjectResult: NotRequired[dict[str, Any]]
ETag: NotRequired[str]
LastModified: NotRequired[datetime]
VersionId: NotRequired[str]
ResponseMetadata: NotRequired[ResponseMetadata]
# ============================================================================
# Type Aliases for Convenience
# ============================================================================
# Common parameter types
BucketName = str
ObjectKey = str
Prefix = str
Delimiter = str
# Storage class options
StorageClass = Literal[
"STANDARD",
"REDUCED_REDUNDANCY",
"STANDARD_IA",
"ONEZONE_IA",
"INTELLIGENT_TIERING",
"GLACIER",
"DEEP_ARCHIVE",
"GLACIER_IR",
]

View File

@@ -8,7 +8,7 @@ from unittest.mock import Mock
import pytest
from deltaglider.adapters import (
FsCacheAdapter,
ContentAddressedCache,
NoopMetricsAdapter,
Sha256Adapter,
StdLoggerAdapter,
@@ -59,9 +59,9 @@ def real_hasher():
@pytest.fixture
def cache_adapter(temp_dir, real_hasher):
"""Create filesystem cache adapter."""
"""Create content-addressed storage cache adapter."""
cache_dir = temp_dir / "cache"
return FsCacheAdapter(cache_dir, real_hasher)
return ContentAddressedCache(cache_dir, real_hasher)
@pytest.fixture

View File

@@ -1,11 +1,13 @@
"""Tests for bucket management APIs."""
from typing import Any
from unittest.mock import Mock
import pytest
from deltaglider.app.cli.main import create_service
from deltaglider.client import DeltaGliderClient
from deltaglider.client_models import BucketStats
class TestBucketManagement:
@@ -123,6 +125,48 @@ class TestBucketManagement:
assert response["Buckets"] == []
assert response["ResponseMetadata"]["HTTPStatusCode"] == 200
def test_list_buckets_includes_cached_stats(self):
"""Bucket list should merge cached stats when available."""
service = create_service()
mock_storage = Mock()
service.storage = mock_storage
mock_boto3_client = Mock()
mock_boto3_client.list_buckets.return_value = {
"Buckets": [
{"Name": "bucket1", "CreationDate": "2025-01-01T00:00:00Z"},
{"Name": "bucket2", "CreationDate": "2025-01-02T00:00:00Z"},
],
"Owner": {"DisplayName": "test-user", "ID": "12345"},
}
mock_storage.client = mock_boto3_client
client = DeltaGliderClient(service)
cached_stats = BucketStats(
bucket="bucket1",
object_count=10,
total_size=1000,
compressed_size=600,
space_saved=400,
average_compression_ratio=0.4,
delta_objects=6,
direct_objects=4,
)
client._store_bucket_stats_cache("bucket1", mode="detailed", stats=cached_stats)
response = client.list_buckets()
bucket1 = next(bucket for bucket in response["Buckets"] if bucket["Name"] == "bucket1")
assert bucket1["DeltaGliderStats"]["Cached"] is True
assert bucket1["DeltaGliderStats"]["Detailed"] is True
assert bucket1["DeltaGliderStats"]["Mode"] == "detailed"
assert bucket1["DeltaGliderStats"]["ObjectCount"] == cached_stats.object_count
assert bucket1["DeltaGliderStats"]["TotalSize"] == cached_stats.total_size
bucket2 = next(bucket for bucket in response["Buckets"] if bucket["Name"] == "bucket2")
assert "DeltaGliderStats" not in bucket2
def test_delete_bucket_success(self):
"""Test deleting a bucket successfully."""
service = create_service()
@@ -178,6 +222,73 @@ class TestBucketManagement:
with pytest.raises(RuntimeError, match="Failed to delete bucket"):
client.delete_bucket(Bucket="full-bucket")
def test_get_bucket_stats_caches_per_session(self, monkeypatch):
"""Verify bucket stats are cached within the client session."""
service = create_service()
mock_storage = Mock()
service.storage = mock_storage
mock_storage.client = Mock()
client = DeltaGliderClient(service)
quick_stats = BucketStats(
bucket="bucket1",
object_count=5,
total_size=500,
compressed_size=300,
space_saved=200,
average_compression_ratio=0.4,
delta_objects=3,
direct_objects=2,
)
detailed_stats = BucketStats(
bucket="bucket1",
object_count=5,
total_size=520,
compressed_size=300,
space_saved=220,
average_compression_ratio=0.423,
delta_objects=3,
direct_objects=2,
)
call_count = {"value": 0}
def fake_get_bucket_stats(_: Any, bucket: str, mode: str) -> BucketStats:
call_count["value"] += 1
assert bucket == "bucket1"
if mode == "detailed":
return detailed_stats
if mode == "sampled":
return detailed_stats # sampled treated as detailed for cache propagation
return quick_stats
monkeypatch.setattr("deltaglider.client._get_bucket_stats", fake_get_bucket_stats)
# First call should invoke underlying function
result_quick = client.get_bucket_stats("bucket1")
assert result_quick is quick_stats
assert call_count["value"] == 1
# Second quick call should hit cache
assert client.get_bucket_stats("bucket1") is quick_stats
assert call_count["value"] == 1
# Detailed call triggers new computation
result_detailed = client.get_bucket_stats("bucket1", mode="detailed")
assert result_detailed is detailed_stats
assert call_count["value"] == 2
# Quick call after detailed uses detailed cached value (more accurate)
assert client.get_bucket_stats("bucket1") is detailed_stats
assert call_count["value"] == 2
# Clearing the cache should force recomputation
client.clear_cache()
assert client.get_bucket_stats("bucket1") is quick_stats
assert call_count["value"] == 3
def test_bucket_methods_without_boto3_client(self):
"""Test that bucket methods raise NotImplementedError when storage doesn't support it."""
service = create_service()

View File

@@ -10,7 +10,6 @@ from deltaglider import create_client
from deltaglider.client import (
BucketStats,
CompressionEstimate,
ListObjectsResponse,
ObjectInfo,
)
@@ -125,7 +124,7 @@ class MockStorage:
@pytest.fixture
def client(tmp_path):
"""Create a client with mocked storage."""
client = create_client(cache_dir=str(tmp_path / "cache"))
client = create_client()
# Replace storage with mock
mock_storage = MockStorage()
@@ -157,7 +156,6 @@ class TestCredentialHandling:
aws_access_key_id="AKIAIOSFODNN7EXAMPLE",
aws_secret_access_key="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
region_name="us-west-2",
cache_dir=str(tmp_path / "cache"),
)
# Verify the client was created
@@ -180,7 +178,6 @@ class TestCredentialHandling:
aws_access_key_id="ASIAIOSFODNN7EXAMPLE",
aws_secret_access_key="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
aws_session_token="FwoGZXIvYXdzEBEaDH...",
cache_dir=str(tmp_path / "cache"),
)
assert client is not None
@@ -189,7 +186,7 @@ class TestCredentialHandling:
def test_create_client_without_credentials_uses_environment(self, tmp_path):
"""Test that omitting credentials falls back to environment/IAM."""
# This should use boto3's default credential chain
client = create_client(cache_dir=str(tmp_path / "cache"))
client = create_client()
assert client is not None
assert client.service.storage.client is not None
@@ -200,7 +197,6 @@ class TestCredentialHandling:
endpoint_url="http://localhost:9000",
aws_access_key_id="minioadmin",
aws_secret_access_key="minioadmin",
cache_dir=str(tmp_path / "cache"),
)
assert client is not None
@@ -279,27 +275,35 @@ class TestBoto3Compatibility:
assert response["ContentLength"] == len(content)
def test_list_objects(self, client):
"""Test list_objects with various options."""
"""Test list_objects with various options (boto3-compatible dict response)."""
# List all objects (default: FetchMetadata=False)
response = client.list_objects(Bucket="test-bucket")
assert isinstance(response, ListObjectsResponse)
assert response.key_count > 0
assert len(response.contents) > 0
# Response is now a boto3-compatible dict (not ListObjectsResponse)
assert isinstance(response, dict)
assert response["KeyCount"] > 0
assert len(response["Contents"]) > 0
# Verify S3Object structure
for obj in response["Contents"]:
assert "Key" in obj
assert "Size" in obj
assert "LastModified" in obj
assert "Metadata" in obj # DeltaGlider metadata
# Test with FetchMetadata=True (should only affect delta files)
response_with_metadata = client.list_objects(Bucket="test-bucket", FetchMetadata=True)
assert isinstance(response_with_metadata, ListObjectsResponse)
assert response_with_metadata.key_count > 0
assert isinstance(response_with_metadata, dict)
assert response_with_metadata["KeyCount"] > 0
def test_list_objects_with_delimiter(self, client):
"""Test list_objects with delimiter for folder simulation."""
"""Test list_objects with delimiter for folder simulation (boto3-compatible dict response)."""
response = client.list_objects(Bucket="test-bucket", Prefix="", Delimiter="/")
# Should have common prefixes for folders
assert len(response.common_prefixes) > 0
assert {"Prefix": "folder1/"} in response.common_prefixes
assert {"Prefix": "folder2/"} in response.common_prefixes
assert len(response.get("CommonPrefixes", [])) > 0
assert {"Prefix": "folder1/"} in response["CommonPrefixes"]
assert {"Prefix": "folder2/"} in response["CommonPrefixes"]
def test_delete_object(self, client):
"""Test delete_object."""
@@ -430,7 +434,7 @@ class TestDeltaGliderFeatures:
def test_get_bucket_stats(self, client):
"""Test getting bucket statistics."""
# Test quick stats (default: detailed_stats=False)
# Test quick stats (LIST only)
stats = client.get_bucket_stats("test-bucket")
assert isinstance(stats, BucketStats)
@@ -438,8 +442,8 @@ class TestDeltaGliderFeatures:
assert stats.total_size > 0
assert stats.delta_objects >= 1 # We have archive.zip.delta
# Test with detailed_stats=True
detailed_stats = client.get_bucket_stats("test-bucket", detailed_stats=True)
# Test with detailed mode
detailed_stats = client.get_bucket_stats("test-bucket", mode="detailed")
assert isinstance(detailed_stats, BucketStats)
assert detailed_stats.object_count == stats.object_count

View File

@@ -71,7 +71,7 @@ def mock_storage():
def client(tmp_path):
"""Create DeltaGliderClient with mock storage."""
# Use create_client to get a properly configured client
client = create_client(cache_dir=str(tmp_path / "cache"))
client = create_client()
# Replace storage with mock
mock_storage = MockStorage()

View File

@@ -53,8 +53,11 @@ class TestSDKFiltering:
client = DeltaGliderClient(service)
response = client.list_objects(Bucket="test-bucket", Prefix="releases/")
# Response is now a boto3-compatible dict
contents = response["Contents"]
# Verify .delta suffix is stripped
keys = [obj.key for obj in response.contents]
keys = [obj["Key"] for obj in contents]
assert "releases/app-v1.zip" in keys
assert "releases/app-v2.zip" in keys
assert "releases/README.md" in keys
@@ -63,8 +66,10 @@ class TestSDKFiltering:
for key in keys:
assert not key.endswith(".delta"), f"Found .delta suffix in: {key}"
# Verify is_delta flag is set correctly
delta_objects = [obj for obj in response.contents if obj.is_delta]
# Verify is_delta flag is set correctly in Metadata
delta_objects = [
obj for obj in contents if obj.get("Metadata", {}).get("deltaglider-is-delta") == "true"
]
assert len(delta_objects) == 2
def test_list_objects_filters_reference_bin(self):
@@ -106,15 +111,18 @@ class TestSDKFiltering:
client = DeltaGliderClient(service)
response = client.list_objects(Bucket="test-bucket", Prefix="releases/")
# Response is now a boto3-compatible dict
contents = response["Contents"]
# Verify NO reference.bin files in output
keys = [obj.key for obj in response.contents]
keys = [obj["Key"] for obj in contents]
for key in keys:
assert not key.endswith("reference.bin"), f"Found reference.bin in: {key}"
# Should only have the app.zip (with .delta stripped)
assert len(response.contents) == 1
assert response.contents[0].key == "releases/app.zip"
assert response.contents[0].is_delta is True
assert len(contents) == 1
assert contents[0]["Key"] == "releases/app.zip"
assert contents[0].get("Metadata", {}).get("deltaglider-is-delta") == "true"
def test_list_objects_combined_filtering(self):
"""Test filtering of both .delta and reference.bin together."""
@@ -170,12 +178,15 @@ class TestSDKFiltering:
client = DeltaGliderClient(service)
response = client.list_objects(Bucket="test-bucket", Prefix="data/")
# Response is now a boto3-compatible dict
contents = response["Contents"]
# Should filter out 2 reference.bin files
# Should strip .delta from 3 files
# Should keep 1 regular file as-is
assert len(response.contents) == 4 # 3 deltas + 1 regular file
assert len(contents) == 4 # 3 deltas + 1 regular file
keys = [obj.key for obj in response.contents]
keys = [obj["Key"] for obj in contents]
expected_keys = ["data/file1.zip", "data/file2.zip", "data/file3.txt", "data/sub/app.jar"]
assert sorted(keys) == sorted(expected_keys)

View File

@@ -0,0 +1,271 @@
"""Test S3-to-S3 migration functionality."""
from unittest.mock import MagicMock, patch
import pytest
from deltaglider.app.cli.aws_compat import migrate_s3_to_s3
from deltaglider.core import DeltaService
from deltaglider.ports import ObjectHead
@pytest.fixture
def mock_service():
"""Create a mock DeltaService."""
service = MagicMock(spec=DeltaService)
service.storage = MagicMock()
return service
def test_migrate_s3_to_s3_with_resume(mock_service):
"""Test migration with resume support (skips existing files)."""
# Setup mock storage with source files
source_objects = [
ObjectHead(
key="file1.zip",
size=1024,
etag="abc123",
last_modified="2024-01-01T00:00:00Z",
metadata={},
),
ObjectHead(
key="file2.zip",
size=2048,
etag="def456",
last_modified="2024-01-01T00:00:00Z",
metadata={},
),
ObjectHead(
key="subdir/file3.zip",
size=512,
etag="ghi789",
last_modified="2024-01-01T00:00:00Z",
metadata={},
),
]
# Destination already has file1.zip (as .delta)
dest_objects = [
ObjectHead(
key="file1.zip.delta",
size=100,
last_modified="2024-01-02T00:00:00Z",
etag="delta123",
metadata={},
),
]
# Configure mock to return appropriate objects
def list_side_effect(prefix):
if "source-bucket" in prefix:
return iter(source_objects)
elif "dest-bucket" in prefix:
return iter(dest_objects)
return iter([])
mock_service.storage.list.side_effect = list_side_effect
# Mock the copy operation and click functions
# Use quiet=True to skip EC2 detection logging
with patch("deltaglider.app.cli.aws_compat.copy_s3_to_s3") as mock_copy:
with patch("deltaglider.app.cli.aws_compat.click.confirm", return_value=True):
migrate_s3_to_s3(
mock_service,
"s3://source-bucket/",
"s3://dest-bucket/",
exclude=None,
include=None,
quiet=True, # Skip EC2 detection and logging
no_delta=False,
max_ratio=None,
dry_run=False,
skip_confirm=False,
)
# Should copy only file2.zip and subdir/file3.zip (file1 already exists)
assert mock_copy.call_count == 2
# Verify the files being migrated
call_args = [call[0] for call in mock_copy.call_args_list]
migrated_files = [(args[1], args[2]) for args in call_args]
assert ("s3://source-bucket/file2.zip", "s3://dest-bucket/file2.zip") in migrated_files
assert (
"s3://source-bucket/subdir/file3.zip",
"s3://dest-bucket/subdir/file3.zip",
) in migrated_files
def test_migrate_s3_to_s3_dry_run(mock_service):
"""Test dry run mode shows what would be migrated without actually migrating."""
source_objects = [
ObjectHead(
key="file1.zip",
size=1024,
last_modified="2024-01-01T00:00:00Z",
etag="abc123",
metadata={},
),
]
mock_service.storage.list.return_value = iter(source_objects)
# Mock the copy operation and EC2 detection
with patch("deltaglider.app.cli.aws_compat.copy_s3_to_s3") as mock_copy:
with patch("deltaglider.app.cli.aws_compat.click.echo") as mock_echo:
with patch("deltaglider.app.cli.aws_compat.log_aws_region"):
migrate_s3_to_s3(
mock_service,
"s3://source-bucket/",
"s3://dest-bucket/",
exclude=None,
include=None,
quiet=False, # Allow output to test dry run messages
no_delta=False,
max_ratio=None,
dry_run=True,
skip_confirm=False,
)
# Should not actually copy anything in dry run mode
mock_copy.assert_not_called()
# Should show dry run message
echo_calls = [str(call[0][0]) for call in mock_echo.call_args_list if call[0]]
assert any("DRY RUN MODE" in msg for msg in echo_calls)
def test_migrate_s3_to_s3_with_filters(mock_service):
"""Test migration with include/exclude filters."""
source_objects = [
ObjectHead(
key="file1.zip",
size=1024,
last_modified="2024-01-01T00:00:00Z",
etag="abc123",
metadata={},
),
ObjectHead(
key="file2.log",
size=256,
last_modified="2024-01-01T00:00:00Z",
etag="def456",
metadata={},
),
ObjectHead(
key="file3.tar",
size=512,
last_modified="2024-01-01T00:00:00Z",
etag="ghi789",
metadata={},
),
]
mock_service.storage.list.return_value = iter(source_objects)
# Mock the copy operation
with patch("deltaglider.app.cli.aws_compat.copy_s3_to_s3") as mock_copy:
with patch("click.echo"):
with patch("deltaglider.app.cli.aws_compat.click.confirm", return_value=True):
# Exclude .log files
migrate_s3_to_s3(
mock_service,
"s3://source-bucket/",
"s3://dest-bucket/",
exclude="*.log",
include=None,
quiet=True, # Skip EC2 detection
no_delta=False,
max_ratio=None,
dry_run=False,
skip_confirm=False,
)
# Should copy file1.zip and file3.tar, but not file2.log
assert mock_copy.call_count == 2
call_args = [call[0] for call in mock_copy.call_args_list]
migrated_sources = [args[1] for args in call_args]
assert "s3://source-bucket/file1.zip" in migrated_sources
assert "s3://source-bucket/file3.tar" in migrated_sources
assert "s3://source-bucket/file2.log" not in migrated_sources
def test_migrate_s3_to_s3_skip_confirm(mock_service):
"""Test skipping confirmation prompt with skip_confirm=True."""
source_objects = [
ObjectHead(
key="file1.zip",
size=1024,
last_modified="2024-01-01T00:00:00Z",
etag="abc123",
metadata={},
),
]
mock_service.storage.list.return_value = iter(source_objects)
with patch("deltaglider.app.cli.aws_compat.copy_s3_to_s3") as mock_copy:
with patch("click.echo"):
with patch("deltaglider.app.cli.aws_compat.click.confirm") as mock_confirm:
migrate_s3_to_s3(
mock_service,
"s3://source-bucket/",
"s3://dest-bucket/",
exclude=None,
include=None,
quiet=True, # Skip EC2 detection
no_delta=False,
max_ratio=None,
dry_run=False,
skip_confirm=True, # Skip confirmation
)
# Should not ask for confirmation
mock_confirm.assert_not_called()
# Should still perform the copy
mock_copy.assert_called_once()
def test_migrate_s3_to_s3_with_prefix(mock_service):
"""Test migration with source and destination prefixes."""
source_objects = [
ObjectHead(
key="data/file1.zip",
size=1024,
last_modified="2024-01-01T00:00:00Z",
etag="abc123",
metadata={},
),
]
def list_side_effect(prefix):
if "source-bucket/data" in prefix:
return iter(source_objects)
return iter([])
mock_service.storage.list.side_effect = list_side_effect
with patch("deltaglider.app.cli.aws_compat.copy_s3_to_s3") as mock_copy:
with patch("click.echo"):
with patch("deltaglider.app.cli.aws_compat.click.confirm", return_value=True):
migrate_s3_to_s3(
mock_service,
"s3://source-bucket/data/",
"s3://dest-bucket/archive/",
exclude=None,
include=None,
quiet=True, # Skip EC2 detection
no_delta=False,
max_ratio=None,
dry_run=False,
skip_confirm=False,
)
# Verify the correct destination path is used
mock_copy.assert_called_once()
call_args = mock_copy.call_args[0]
assert call_args[1] == "s3://source-bucket/data/file1.zip"
assert call_args[2] == "s3://dest-bucket/archive/file1.zip"

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"""Integration tests for stats CLI command."""
import json
from unittest.mock import Mock, patch
from click.testing import CliRunner
from deltaglider.app.cli.main import cli
from deltaglider.client_models import BucketStats
class TestStatsCommand:
"""Test stats CLI command."""
def test_stats_json_output(self):
"""Test stats command with JSON output."""
# Create mock bucket stats
mock_stats = BucketStats(
bucket="test-bucket",
object_count=10,
total_size=1000000,
compressed_size=500000,
space_saved=500000,
average_compression_ratio=0.5,
delta_objects=7,
direct_objects=3,
)
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
# Setup mock client
mock_client = Mock()
mock_client.get_bucket_stats.return_value = mock_stats
mock_client_class.return_value = mock_client
# Run command
runner = CliRunner()
result = runner.invoke(cli, ["stats", "test-bucket", "--json"])
# Verify
assert result.exit_code == 0
output = json.loads(result.output)
assert output["bucket"] == "test-bucket"
assert output["object_count"] == 10
assert output["total_size"] == 1000000
assert output["compressed_size"] == 500000
assert output["space_saved"] == 500000
assert output["average_compression_ratio"] == 0.5
assert output["delta_objects"] == 7
assert output["direct_objects"] == 3
# Verify client was called correctly
mock_client.get_bucket_stats.assert_called_once_with("test-bucket", mode="quick")
def test_stats_json_output_detailed(self):
"""Test stats command with detailed JSON output."""
mock_stats = BucketStats(
bucket="test-bucket",
object_count=5,
total_size=2000000,
compressed_size=100000,
space_saved=1900000,
average_compression_ratio=0.95,
delta_objects=5,
direct_objects=0,
)
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client.get_bucket_stats.return_value = mock_stats
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "test-bucket", "--detailed", "--json"])
assert result.exit_code == 0
output = json.loads(result.output)
assert output["average_compression_ratio"] == 0.95
# Verify detailed flag was passed
mock_client.get_bucket_stats.assert_called_once_with("test-bucket", mode="detailed")
def test_stats_json_output_sampled(self):
"""Test stats command with sampled JSON output."""
mock_stats = BucketStats(
bucket="test-bucket",
object_count=5,
total_size=2000000,
compressed_size=100000,
space_saved=1900000,
average_compression_ratio=0.95,
delta_objects=5,
direct_objects=0,
)
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client.get_bucket_stats.return_value = mock_stats
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "test-bucket", "--sampled", "--json"])
assert result.exit_code == 0
mock_client.get_bucket_stats.assert_called_once_with("test-bucket", mode="sampled")
def test_stats_sampled_and_detailed_conflict(self):
"""--sampled and --detailed flags must be mutually exclusive."""
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "test-bucket", "--sampled", "--detailed"])
assert result.exit_code == 1
assert "cannot be used together" in result.output
def test_stats_human_readable_output(self):
"""Test stats command with human-readable output."""
mock_stats = BucketStats(
bucket="test-bucket",
object_count=10,
total_size=1500000, # ~1.43 MB
compressed_size=300000, # ~293 KB
space_saved=1200000, # ~1.14 MB
average_compression_ratio=0.8,
delta_objects=7,
direct_objects=3,
)
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client.get_bucket_stats.return_value = mock_stats
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "test-bucket"])
assert result.exit_code == 0
output = result.output
# Verify human-readable format
assert "Bucket Statistics: test-bucket" in output
assert "Total Objects:" in output
assert "10" in output
assert "Delta Objects:" in output
assert "7" in output
assert "Direct Objects:" in output
assert "3" in output
assert "Original Size:" in output
assert "Compressed Size:" in output
assert "Space Saved:" in output
assert "Compression Ratio:" in output
assert "80.0%" in output # 0.8 = 80%
def test_stats_error_handling(self):
"""Test stats command error handling."""
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client.get_bucket_stats.side_effect = Exception("Bucket not found")
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "nonexistent-bucket"])
assert result.exit_code == 1
assert "Error: Bucket not found" in result.output
def test_stats_with_s3_url(self):
"""Test stats command with s3:// URL format."""
mock_stats = BucketStats(
bucket="test-bucket",
object_count=5,
total_size=1000000,
compressed_size=500000,
space_saved=500000,
average_compression_ratio=0.5,
delta_objects=3,
direct_objects=2,
)
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client.get_bucket_stats.return_value = mock_stats
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "s3://test-bucket", "--json"])
assert result.exit_code == 0
# Verify bucket name was parsed correctly from S3 URL
mock_client.get_bucket_stats.assert_called_once_with("test-bucket", mode="quick")
def test_stats_with_s3_url_trailing_slash(self):
"""Test stats command with s3:// URL format with trailing slash."""
mock_stats = BucketStats(
bucket="test-bucket",
object_count=5,
total_size=1000000,
compressed_size=500000,
space_saved=500000,
average_compression_ratio=0.5,
delta_objects=3,
direct_objects=2,
)
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client.get_bucket_stats.return_value = mock_stats
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "s3://test-bucket/", "--json"])
assert result.exit_code == 0
# Verify bucket name was parsed correctly from S3 URL with trailing slash
mock_client.get_bucket_stats.assert_called_once_with("test-bucket", mode="quick")
def test_stats_with_s3_url_with_prefix(self):
"""Test stats command with s3:// URL format with prefix (should ignore prefix)."""
mock_stats = BucketStats(
bucket="test-bucket",
object_count=5,
total_size=1000000,
compressed_size=500000,
space_saved=500000,
average_compression_ratio=0.5,
delta_objects=3,
direct_objects=2,
)
with patch("deltaglider.client.DeltaGliderClient") as mock_client_class:
mock_client = Mock()
mock_client.get_bucket_stats.return_value = mock_stats
mock_client_class.return_value = mock_client
runner = CliRunner()
result = runner.invoke(cli, ["stats", "s3://test-bucket/some/prefix/", "--json"])
assert result.exit_code == 0
# Verify only bucket name was extracted, prefix ignored
mock_client.get_bucket_stats.assert_called_once_with("test-bucket", mode="quick")

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"""Tests for encrypted cache adapter."""
import tempfile
from pathlib import Path
import pytest
from cryptography.fernet import Fernet
from deltaglider.adapters import ContentAddressedCache, EncryptedCache, Sha256Adapter
from deltaglider.core.errors import CacheCorruptionError, CacheMissError
class TestEncryptedCache:
"""Test encrypted cache wrapper functionality."""
@pytest.fixture
def temp_dir(self):
"""Create temporary directory for tests."""
with tempfile.TemporaryDirectory() as tmpdir:
yield Path(tmpdir)
@pytest.fixture
def hasher(self):
"""Create SHA256 hasher."""
return Sha256Adapter()
@pytest.fixture
def backend(self, temp_dir, hasher):
"""Create CAS backend."""
return ContentAddressedCache(temp_dir, hasher)
@pytest.fixture
def encrypted_cache(self, backend):
"""Create encrypted cache with ephemeral key."""
return EncryptedCache(backend)
def test_ephemeral_key_generation(self, backend):
"""Test that ephemeral key is generated automatically."""
cache = EncryptedCache(backend)
assert cache._ephemeral is True
assert cache._key is not None
assert len(cache._key) == 44 # Base64-encoded 32-byte key
def test_provided_key_usage(self, backend):
"""Test using provided encryption key."""
key = Fernet.generate_key()
cache = EncryptedCache(backend, encryption_key=key)
assert cache._ephemeral is False
assert cache._key == key
def test_write_and_read_encrypted(self, encrypted_cache, temp_dir):
"""Test writing and reading encrypted content."""
# Create test file
test_file = temp_dir / "test.txt"
test_content = b"Secret data that should be encrypted"
test_file.write_bytes(test_content)
# Compute expected SHA
import hashlib
expected_sha = hashlib.sha256(test_content).hexdigest()
# Write to encrypted cache
encrypted_cache.write_ref("test-bucket", "test-prefix", test_file)
# Read back and validate
decrypted_path = encrypted_cache.get_validated_ref(
"test-bucket", "test-prefix", expected_sha
)
# Verify decrypted content matches original
decrypted_content = decrypted_path.read_bytes()
assert decrypted_content == test_content
def test_encrypted_storage_not_readable(self, encrypted_cache, backend, temp_dir):
"""Test that stored data is actually encrypted."""
# Create test file
test_file = temp_dir / "test.txt"
test_content = b"Plaintext secret"
test_file.write_bytes(test_content)
# Write to encrypted cache
encrypted_cache.write_ref("test-bucket", "test-prefix", test_file)
# Get the encrypted file path from backend
backend_path = backend.ref_path("test-bucket", "test-prefix")
# Read encrypted content directly
encrypted_content = backend_path.read_bytes()
# Verify content is NOT the same as plaintext
assert encrypted_content != test_content
# Verify content doesn't contain plaintext substring
assert b"secret" not in encrypted_content.lower()
def test_cache_miss(self, encrypted_cache):
"""Test cache miss error."""
with pytest.raises(CacheMissError):
encrypted_cache.get_validated_ref("no-bucket", "no-prefix", "fakehash")
def test_decryption_with_wrong_sha(self, encrypted_cache, temp_dir):
"""Test that wrong SHA is detected after decryption."""
# Create test file
test_file = temp_dir / "test.txt"
test_content = b"Test content"
test_file.write_bytes(test_content)
# Write to cache
encrypted_cache.write_ref("test-bucket", "test-prefix", test_file)
# Try to read with wrong SHA
with pytest.raises(CacheCorruptionError, match="SHA mismatch"):
encrypted_cache.get_validated_ref("test-bucket", "test-prefix", "wrong_sha_hash_here")
def test_decryption_with_wrong_key(self, temp_dir):
"""Test that decryption fails with wrong key."""
# Create shared backend
from deltaglider.adapters import ContentAddressedCache, Sha256Adapter
hasher = Sha256Adapter()
backend = ContentAddressedCache(temp_dir / "shared", hasher)
# Create two caches with different keys sharing same backend
cache1 = EncryptedCache(backend)
# Write with cache1
test_file = temp_dir / "test.txt"
test_content = b"Encrypted data"
test_file.write_bytes(test_content)
import hashlib
expected_sha = hashlib.sha256(test_content).hexdigest()
cache1.write_ref("test-bucket", "test-prefix", test_file)
# Create cache2 with different key (fresh instance, different ephemeral key)
# and manually add to its mapping (simulating persistent storage scenario)
cache2 = EncryptedCache(backend)
cache2._plaintext_sha_map[("test-bucket", "test-prefix")] = expected_sha
# Try to read with cache2 (different key) - should fail decryption
with pytest.raises(CacheCorruptionError, match="Decryption failed"):
cache2.get_validated_ref("test-bucket", "test-prefix", expected_sha)
def test_evict_cleans_decrypted_files(self, encrypted_cache, temp_dir):
"""Test that evict cleans up .decrypted temporary files."""
# Create and store file
test_file = temp_dir / "test.txt"
test_content = b"Test"
test_file.write_bytes(test_content)
import hashlib
expected_sha = hashlib.sha256(test_content).hexdigest()
encrypted_cache.write_ref("test-bucket", "test-prefix", test_file)
# Read to create .decrypted file
decrypted_path = encrypted_cache.get_validated_ref(
"test-bucket", "test-prefix", expected_sha
)
assert decrypted_path.exists()
# Evict
encrypted_cache.evict("test-bucket", "test-prefix")
# Verify .decrypted file is removed
assert not decrypted_path.exists()
def test_from_env_with_no_key(self, backend, monkeypatch):
"""Test from_env creates ephemeral key when env var not set."""
monkeypatch.delenv("DG_CACHE_ENCRYPTION_KEY", raising=False)
cache = EncryptedCache.from_env(backend)
assert cache._ephemeral is True
def test_from_env_with_key(self, backend, monkeypatch):
"""Test from_env uses key from environment."""
key = Fernet.generate_key()
monkeypatch.setenv("DG_CACHE_ENCRYPTION_KEY", key.decode("utf-8"))
cache = EncryptedCache.from_env(backend)
assert cache._ephemeral is False
assert cache._key == key

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"""Tests for in-memory cache adapter."""
import tempfile
from pathlib import Path
import pytest
from deltaglider.adapters import MemoryCache, Sha256Adapter
from deltaglider.core.errors import CacheCorruptionError, CacheMissError
class TestMemoryCache:
"""Test in-memory cache functionality."""
@pytest.fixture
def temp_dir(self):
"""Create temporary directory for tests."""
with tempfile.TemporaryDirectory() as tmpdir:
yield Path(tmpdir)
@pytest.fixture
def hasher(self):
"""Create SHA256 hasher."""
return Sha256Adapter()
@pytest.fixture
def memory_cache(self, hasher, temp_dir):
"""Create memory cache with 1MB limit."""
return MemoryCache(hasher, max_size_mb=1, temp_dir=temp_dir)
def test_write_and_read(self, memory_cache, temp_dir):
"""Test basic write and read functionality."""
# Create test file
test_file = temp_dir / "test.txt"
test_content = b"Hello, memory cache!"
test_file.write_bytes(test_content)
# Compute expected SHA
import hashlib
expected_sha = hashlib.sha256(test_content).hexdigest()
# Write to memory cache
memory_cache.write_ref("test-bucket", "test-prefix", test_file)
# Read back
retrieved_path = memory_cache.get_validated_ref("test-bucket", "test-prefix", expected_sha)
# Verify content
assert retrieved_path.read_bytes() == test_content
def test_has_ref_true(self, memory_cache, temp_dir):
"""Test has_ref returns True for existing content."""
test_file = temp_dir / "test.txt"
test_content = b"Test"
test_file.write_bytes(test_content)
import hashlib
sha = hashlib.sha256(test_content).hexdigest()
memory_cache.write_ref("test-bucket", "test-prefix", test_file)
assert memory_cache.has_ref("test-bucket", "test-prefix", sha) is True
def test_has_ref_false(self, memory_cache):
"""Test has_ref returns False for non-existent content."""
assert memory_cache.has_ref("no-bucket", "no-prefix", "fakehash") is False
def test_cache_miss(self, memory_cache):
"""Test cache miss error."""
with pytest.raises(CacheMissError):
memory_cache.get_validated_ref("no-bucket", "no-prefix", "fakehash")
def test_sha_mismatch_detection(self, memory_cache, temp_dir):
"""Test that SHA mismatch is detected."""
test_file = temp_dir / "test.txt"
test_file.write_bytes(b"Content")
memory_cache.write_ref("test-bucket", "test-prefix", test_file)
# Try to read with wrong SHA
with pytest.raises(CacheCorruptionError, match="SHA mismatch"):
memory_cache.get_validated_ref("test-bucket", "test-prefix", "wrong_sha")
def test_lru_eviction(self, hasher, temp_dir):
"""Test LRU eviction when cache is full."""
# Create small cache (only 10KB)
small_cache = MemoryCache(hasher, max_size_mb=0.01, temp_dir=temp_dir)
# Create files that will exceed cache limit
file1 = temp_dir / "file1.txt"
file2 = temp_dir / "file2.txt"
file3 = temp_dir / "file3.txt"
# Each file is 5KB
file1.write_bytes(b"A" * 5000)
file2.write_bytes(b"B" * 5000)
file3.write_bytes(b"C" * 5000)
# Write file1 and file2 (total 10KB, at limit)
small_cache.write_ref("bucket", "prefix1", file1)
small_cache.write_ref("bucket", "prefix2", file2)
# Verify both are in cache
import hashlib
sha1 = hashlib.sha256(b"A" * 5000).hexdigest()
sha2 = hashlib.sha256(b"B" * 5000).hexdigest()
assert small_cache.has_ref("bucket", "prefix1", sha1) is True
assert small_cache.has_ref("bucket", "prefix2", sha2) is True
# Write file3 (5KB) - should evict file1 (LRU)
small_cache.write_ref("bucket", "prefix3", file3)
# file1 should be evicted
assert small_cache.has_ref("bucket", "prefix1", sha1) is False
# file2 and file3 should still be in cache
sha3 = hashlib.sha256(b"C" * 5000).hexdigest()
assert small_cache.has_ref("bucket", "prefix2", sha2) is True
assert small_cache.has_ref("bucket", "prefix3", sha3) is True
def test_file_too_large_for_cache(self, hasher, temp_dir):
"""Test error when file exceeds cache size limit."""
small_cache = MemoryCache(hasher, max_size_mb=0.001, temp_dir=temp_dir) # 1KB limit
large_file = temp_dir / "large.txt"
large_file.write_bytes(b"X" * 2000) # 2KB file
with pytest.raises(CacheCorruptionError, match="too large"):
small_cache.write_ref("bucket", "prefix", large_file)
def test_evict_removes_from_memory(self, memory_cache, temp_dir):
"""Test that evict removes content from memory."""
test_file = temp_dir / "test.txt"
test_content = b"Test"
test_file.write_bytes(test_content)
import hashlib
sha = hashlib.sha256(test_content).hexdigest()
memory_cache.write_ref("test-bucket", "test-prefix", test_file)
# Verify it's in cache
assert memory_cache.has_ref("test-bucket", "test-prefix", sha) is True
# Evict
memory_cache.evict("test-bucket", "test-prefix")
# Verify it's gone
assert memory_cache.has_ref("test-bucket", "test-prefix", sha) is False
def test_clear_removes_all(self, memory_cache, temp_dir):
"""Test that clear removes all cached content."""
# Add multiple files
for i in range(3):
test_file = temp_dir / f"test{i}.txt"
test_file.write_bytes(f"Content {i}".encode())
memory_cache.write_ref("bucket", f"prefix{i}", test_file)
# Verify cache is not empty
assert memory_cache._current_size > 0
assert len(memory_cache._cache) == 3
# Clear
memory_cache.clear()
# Verify cache is empty
assert memory_cache._current_size == 0
assert len(memory_cache._cache) == 0
assert len(memory_cache._access_order) == 0
def test_access_order_updated_on_read(self, memory_cache, temp_dir):
"""Test that LRU access order is updated on reads."""
# Create two files
file1 = temp_dir / "file1.txt"
file2 = temp_dir / "file2.txt"
file1.write_bytes(b"File 1")
file2.write_bytes(b"File 2")
# Write both
memory_cache.write_ref("bucket", "prefix1", file1)
memory_cache.write_ref("bucket", "prefix2", file2)
# Access order should be: [prefix1, prefix2]
assert memory_cache._access_order[0] == ("bucket", "prefix1")
assert memory_cache._access_order[1] == ("bucket", "prefix2")
# Read prefix1 again
import hashlib
sha1 = hashlib.sha256(b"File 1").hexdigest()
memory_cache.get_validated_ref("bucket", "prefix1", sha1)
# Access order should now be: [prefix2, prefix1]
assert memory_cache._access_order[0] == ("bucket", "prefix2")
assert memory_cache._access_order[1] == ("bucket", "prefix1")

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"""Tests for shared delta extension policy."""
from deltaglider.core.delta_extensions import (
DEFAULT_COMPOUND_DELTA_EXTENSIONS,
DEFAULT_DELTA_EXTENSIONS,
is_delta_candidate,
)
def test_is_delta_candidate_matches_default_extensions():
"""All default extensions should be detected as delta candidates."""
for ext in DEFAULT_DELTA_EXTENSIONS:
assert is_delta_candidate(f"file{ext}")
def test_is_delta_candidate_matches_compound_extensions():
"""Compound extensions should be handled even with multiple suffixes."""
for ext in DEFAULT_COMPOUND_DELTA_EXTENSIONS:
assert is_delta_candidate(f"file{ext}")
def test_is_delta_candidate_rejects_other_extensions():
"""Non delta-friendly extensions should return False."""
assert not is_delta_candidate("document.txt")
assert not is_delta_candidate("image.jpeg")

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"""Unit tests for object_listing pagination."""
from unittest.mock import Mock
from deltaglider.core.object_listing import list_all_objects, list_objects_page
def test_list_objects_page_passes_continuation_token():
"""Test that list_objects_page passes continuation_token to storage."""
storage = Mock()
storage.list_objects.return_value = {
"objects": [],
"common_prefixes": [],
"is_truncated": False,
"next_continuation_token": None,
"key_count": 0,
}
list_objects_page(
storage,
bucket="test-bucket",
continuation_token="test-token",
)
# Verify continuation_token was passed
storage.list_objects.assert_called_once()
call_kwargs = storage.list_objects.call_args.kwargs
assert call_kwargs["continuation_token"] == "test-token"
def test_list_all_objects_uses_continuation_token_for_pagination():
"""Test that list_all_objects uses continuation_token (not start_after) for pagination."""
storage = Mock()
# Mock 3 pages of results
responses = [
{
"objects": [{"key": f"obj{i}"} for i in range(1000)],
"common_prefixes": [],
"is_truncated": True,
"next_continuation_token": "token1",
"key_count": 1000,
},
{
"objects": [{"key": f"obj{i}"} for i in range(1000, 2000)],
"common_prefixes": [],
"is_truncated": True,
"next_continuation_token": "token2",
"key_count": 1000,
},
{
"objects": [{"key": f"obj{i}"} for i in range(2000, 2500)],
"common_prefixes": [],
"is_truncated": False,
"next_continuation_token": None,
"key_count": 500,
},
]
storage.list_objects.side_effect = responses
result = list_all_objects(
storage,
bucket="test-bucket",
prefix="",
)
# Should have made 3 calls
assert storage.list_objects.call_count == 3
# Should have collected all objects
assert len(result.objects) == 2500
# Should not be truncated
assert not result.is_truncated
# Verify the calls used continuation_token correctly
calls = storage.list_objects.call_args_list
assert len(calls) == 3
# First call should have no continuation_token
assert calls[0].kwargs.get("continuation_token") is None
# Second call should use token1
assert calls[1].kwargs.get("continuation_token") == "token1"
# Third call should use token2
assert calls[2].kwargs.get("continuation_token") == "token2"
def test_list_all_objects_prevents_infinite_loop():
"""Test that list_all_objects has max_iterations protection."""
storage = Mock()
# Mock infinite pagination (always returns more)
storage.list_objects.return_value = {
"objects": [{"key": "obj"}],
"common_prefixes": [],
"is_truncated": True,
"next_continuation_token": "token",
"key_count": 1,
}
result = list_all_objects(
storage,
bucket="test-bucket",
max_iterations=10, # Low limit for testing
)
# Should stop at max_iterations
assert storage.list_objects.call_count == 10
assert result.is_truncated

44
tests/unit/test_s3_uri.py Normal file
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"""Tests for S3 URI helpers."""
import pytest
from deltaglider.core.s3_uri import build_s3_url, is_s3_url, parse_s3_url
def test_is_s3_url_detects_scheme() -> None:
"""is_s3_url should only match the S3 scheme."""
assert is_s3_url("s3://bucket/path")
assert not is_s3_url("https://example.com/object")
def test_parse_s3_url_returns_bucket_and_key() -> None:
"""Parsing should split bucket and key correctly."""
parsed = parse_s3_url("s3://my-bucket/path/to/object.txt")
assert parsed.bucket == "my-bucket"
assert parsed.key == "path/to/object.txt"
def test_parse_strips_trailing_slash_when_requested() -> None:
"""strip_trailing_slash should normalise directory-style URLs."""
parsed = parse_s3_url("s3://my-bucket/path/to/", strip_trailing_slash=True)
assert parsed.bucket == "my-bucket"
assert parsed.key == "path/to"
def test_parse_requires_key_when_configured() -> None:
"""allow_empty_key=False should reject bucket-only URLs."""
with pytest.raises(ValueError):
parse_s3_url("s3://bucket-only", allow_empty_key=False)
def test_build_s3_url_round_trip() -> None:
"""build_s3_url should round-trip with parse_s3_url."""
url = build_s3_url("bucket", "dir/file.tar")
parsed = parse_s3_url(url)
assert parsed.bucket == "bucket"
assert parsed.key == "dir/file.tar"
def test_build_s3_url_for_bucket_root() -> None:
"""When key is missing, build_s3_url should omit the trailing slash."""
assert build_s3_url("root-bucket") == "s3://root-bucket"

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"""Exhaustive tests for the bucket statistics algorithm."""
from unittest.mock import MagicMock, Mock, patch
import pytest
from deltaglider.client_operations.stats import get_bucket_stats
class TestBucketStatsAlgorithm:
"""Test suite for get_bucket_stats algorithm."""
@pytest.fixture
def mock_client(self):
"""Create a mock DeltaGliderClient."""
client = Mock()
client.service = Mock()
client.service.storage = Mock()
client.service.logger = Mock()
return client
def test_empty_bucket(self, mock_client):
"""Test statistics for an empty bucket."""
# Setup: Empty bucket
mock_client.service.storage.list_objects.return_value = {
"objects": [],
"is_truncated": False,
}
# Execute
stats = get_bucket_stats(mock_client, "empty-bucket")
# Verify
assert stats.bucket == "empty-bucket"
assert stats.object_count == 0
assert stats.total_size == 0
assert stats.compressed_size == 0
assert stats.space_saved == 0
assert stats.average_compression_ratio == 0.0
assert stats.delta_objects == 0
assert stats.direct_objects == 0
def test_bucket_with_only_direct_files(self, mock_client):
"""Test bucket with only direct files (no compression)."""
# Setup: Bucket with 3 direct files
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "file1.pdf", "size": 1000000, "last_modified": "2024-01-01"},
{"key": "file2.html", "size": 500000, "last_modified": "2024-01-02"},
{"key": "file3.txt", "size": 250000, "last_modified": "2024-01-03"},
],
"is_truncated": False,
}
mock_client.service.storage.head.return_value = None
# Execute
stats = get_bucket_stats(mock_client, "direct-only-bucket")
# Verify
assert stats.object_count == 3
assert stats.total_size == 1750000 # Sum of all files
assert stats.compressed_size == 1750000 # Same as total (no compression)
assert stats.space_saved == 0
assert stats.average_compression_ratio == 0.0
assert stats.delta_objects == 0
assert stats.direct_objects == 3
def test_bucket_with_delta_compression(self, mock_client):
"""Test bucket with delta-compressed files."""
# Setup: Bucket with reference.bin and 2 delta files
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "reference.bin", "size": 20000000, "last_modified": "2024-01-01"},
{"key": "file1.zip.delta", "size": 50000, "last_modified": "2024-01-02"},
{"key": "file2.zip.delta", "size": 60000, "last_modified": "2024-01-03"},
],
"is_truncated": False,
}
# Mock metadata for delta files
def mock_head(path):
if "file1.zip.delta" in path:
head = Mock()
head.metadata = {"file_size": "19500000", "compression_ratio": "0.997"}
return head
elif "file2.zip.delta" in path:
head = Mock()
head.metadata = {"file_size": "19600000", "compression_ratio": "0.997"}
return head
return None
mock_client.service.storage.head.side_effect = mock_head
# Execute
stats = get_bucket_stats(mock_client, "compressed-bucket", mode="detailed")
# Verify
assert stats.object_count == 2 # Only delta files counted (not reference.bin)
assert stats.total_size == 39100000 # 19.5M + 19.6M
assert stats.compressed_size == 20110000 # reference (20M) + deltas (50K + 60K)
assert stats.space_saved == 18990000 # ~19MB saved
assert stats.average_compression_ratio > 0.48 # ~48.6% compression
assert stats.delta_objects == 2
assert stats.direct_objects == 0
def test_orphaned_reference_bin_detection(self, mock_client):
"""Test detection of orphaned reference.bin files."""
# Setup: Bucket with reference.bin but no delta files
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "reference.bin", "size": 20000000, "last_modified": "2024-01-01"},
{"key": "regular.pdf", "size": 1000000, "last_modified": "2024-01-02"},
],
"is_truncated": False,
}
mock_client.service.storage.head.return_value = None
# Execute
stats = get_bucket_stats(mock_client, "orphaned-ref-bucket")
# Verify stats
assert stats.object_count == 1 # Only regular.pdf
assert stats.total_size == 1000000 # Only regular.pdf size
assert stats.compressed_size == 1000000 # reference.bin NOT included
assert stats.space_saved == 0
assert stats.delta_objects == 0
assert stats.direct_objects == 1
# Verify warning was logged
warning_calls = mock_client.service.logger.warning.call_args_list
assert any("ORPHANED REFERENCE FILE" in str(call) for call in warning_calls)
assert any("20,000,000 bytes" in str(call) for call in warning_calls)
assert any(
"aws s3 rm s3://orphaned-ref-bucket/reference.bin" in str(call)
for call in warning_calls
)
def test_mixed_bucket(self, mock_client):
"""Test bucket with both delta and direct files."""
# Setup: Mixed bucket
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "pro/reference.bin", "size": 20000000, "last_modified": "2024-01-01"},
{"key": "pro/v1.zip.delta", "size": 50000, "last_modified": "2024-01-02"},
{"key": "pro/v2.zip.delta", "size": 60000, "last_modified": "2024-01-03"},
{"key": "docs/readme.pdf", "size": 500000, "last_modified": "2024-01-04"},
{"key": "docs/manual.html", "size": 300000, "last_modified": "2024-01-05"},
],
"is_truncated": False,
}
# Mock metadata for delta files
def mock_head(path):
if "v1.zip.delta" in path:
head = Mock()
head.metadata = {"file_size": "19500000"}
return head
elif "v2.zip.delta" in path:
head = Mock()
head.metadata = {"file_size": "19600000"}
return head
return None
mock_client.service.storage.head.side_effect = mock_head
# Execute
stats = get_bucket_stats(mock_client, "mixed-bucket", mode="detailed")
# Verify
assert stats.object_count == 4 # 2 delta + 2 direct files
assert stats.total_size == 39900000 # 19.5M + 19.6M + 0.5M + 0.3M
assert stats.compressed_size == 20910000 # ref (20M) + deltas (110K) + direct (800K)
assert stats.space_saved == 18990000
assert stats.delta_objects == 2
assert stats.direct_objects == 2
def test_sha1_files_included(self, mock_client):
"""Test that .sha1 checksum files are counted properly."""
# Setup: Bucket with .sha1 files
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "file1.zip", "size": 1000000, "last_modified": "2024-01-01"},
{"key": "file1.zip.sha1", "size": 41, "last_modified": "2024-01-01"},
{"key": "file2.tar", "size": 2000000, "last_modified": "2024-01-02"},
{"key": "file2.tar.sha1", "size": 41, "last_modified": "2024-01-02"},
],
"is_truncated": False,
}
mock_client.service.storage.head.return_value = None
# Execute
stats = get_bucket_stats(mock_client, "sha1-bucket")
# Verify - .sha1 files ARE counted
assert stats.object_count == 4
assert stats.total_size == 3000082 # All files including .sha1
assert stats.compressed_size == 3000082
assert stats.direct_objects == 4
def test_multiple_deltaspaces(self, mock_client):
"""Test bucket with multiple deltaspaces (different prefixes)."""
# Setup: Multiple deltaspaces
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "pro/reference.bin", "size": 20000000, "last_modified": "2024-01-01"},
{"key": "pro/v1.zip.delta", "size": 50000, "last_modified": "2024-01-02"},
{
"key": "enterprise/reference.bin",
"size": 25000000,
"last_modified": "2024-01-03",
},
{"key": "enterprise/v1.zip.delta", "size": 70000, "last_modified": "2024-01-04"},
],
"is_truncated": False,
}
# Mock metadata
def mock_head(path):
if "pro/v1.zip.delta" in path:
head = Mock()
head.metadata = {"file_size": "19500000"}
return head
elif "enterprise/v1.zip.delta" in path:
head = Mock()
head.metadata = {"file_size": "24500000"}
return head
return None
mock_client.service.storage.head.side_effect = mock_head
# Execute
stats = get_bucket_stats(mock_client, "multi-deltaspace-bucket", mode="detailed")
# Verify
assert stats.object_count == 2 # Only delta files
assert stats.total_size == 44000000 # 19.5M + 24.5M
assert stats.compressed_size == 45120000 # Both references + both deltas
assert stats.delta_objects == 2
assert stats.direct_objects == 0
def test_pagination_handling(self, mock_client):
"""Test handling of paginated results."""
# Setup: Paginated responses
mock_client.service.storage.list_objects.side_effect = [
{
"objects": [
{"key": f"file{i}.txt", "size": 1000, "last_modified": "2024-01-01"}
for i in range(1000)
],
"is_truncated": True,
"next_continuation_token": "token1",
},
{
"objects": [
{"key": f"file{i}.txt", "size": 1000, "last_modified": "2024-01-01"}
for i in range(1000, 1500)
],
"is_truncated": False,
},
]
mock_client.service.storage.head.return_value = None
# Execute
stats = get_bucket_stats(mock_client, "paginated-bucket")
# Verify
assert stats.object_count == 1500
assert stats.total_size == 1500000
assert stats.compressed_size == 1500000
assert stats.direct_objects == 1500
# Verify pagination was handled
assert mock_client.service.storage.list_objects.call_count == 2
def test_delta_file_without_metadata(self, mock_client):
"""Test handling of delta files with missing metadata."""
# Setup: Delta file without metadata
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "reference.bin", "size": 20000000, "last_modified": "2024-01-01"},
{"key": "file.zip.delta", "size": 50000, "last_modified": "2024-01-02"},
],
"is_truncated": False,
}
# No metadata available
mock_client.service.storage.head.return_value = None
# Execute
stats = get_bucket_stats(mock_client, "no-metadata-bucket")
# Verify - falls back to using delta size as original size
assert stats.object_count == 1
assert stats.total_size == 50000 # Falls back to delta size
assert stats.compressed_size == 20050000 # reference + delta
assert stats.delta_objects == 1
# Verify warning was logged
warning_calls = mock_client.service.logger.warning.call_args_list
assert any("no original_size" in str(call) for call in warning_calls)
def test_parallel_metadata_fetching(self, mock_client):
"""Test that metadata is fetched in parallel for performance."""
# Setup: Many delta files
num_deltas = 50
objects = [{"key": "reference.bin", "size": 20000000, "last_modified": "2024-01-01"}]
objects.extend(
[
{
"key": f"file{i}.zip.delta",
"size": 50000 + i,
"last_modified": f"2024-01-{i + 2:02d}",
}
for i in range(num_deltas)
]
)
mock_client.service.storage.list_objects.return_value = {
"objects": objects,
"is_truncated": False,
}
# Mock metadata
def mock_head(path):
head = Mock()
head.metadata = {"file_size": "19500000"}
return head
mock_client.service.storage.head.side_effect = mock_head
# Execute with mocked ThreadPoolExecutor
with patch("concurrent.futures.ThreadPoolExecutor") as mock_executor:
mock_pool = MagicMock()
mock_executor.return_value.__enter__.return_value = mock_pool
# Simulate parallel execution
futures = []
for i in range(num_deltas):
future = Mock()
future.result.return_value = (f"file{i}.zip.delta", {"file_size": "19500000"})
futures.append(future)
mock_pool.submit.side_effect = futures
patch_as_completed = patch(
"concurrent.futures.as_completed",
return_value=futures,
)
with patch_as_completed:
_ = get_bucket_stats(mock_client, "parallel-bucket", mode="detailed")
# Verify ThreadPoolExecutor was used with correct max_workers
mock_executor.assert_called_once_with(max_workers=10) # min(10, 50) = 10
def test_stats_modes_control_metadata_fetch(self, mock_client):
"""Metadata fetching should depend on the selected stats mode."""
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "alpha/reference.bin", "size": 100, "last_modified": "2024-01-01"},
{"key": "alpha/file1.zip.delta", "size": 10, "last_modified": "2024-01-02"},
{"key": "alpha/file2.zip.delta", "size": 12, "last_modified": "2024-01-03"},
{"key": "beta/reference.bin", "size": 200, "last_modified": "2024-01-04"},
{"key": "beta/file1.zip.delta", "size": 20, "last_modified": "2024-01-05"},
],
"is_truncated": False,
}
metadata_by_key = {
"alpha/file1.zip.delta": {"file_size": "100", "compression_ratio": "0.9"},
"alpha/file2.zip.delta": {"file_size": "120", "compression_ratio": "0.88"},
"beta/file1.zip.delta": {"file_size": "210", "compression_ratio": "0.9"},
}
def mock_head(path: str):
for key, metadata in metadata_by_key.items():
if key in path:
head = Mock()
head.metadata = metadata
return head
return None
mock_client.service.storage.head.side_effect = mock_head
# Quick mode: no metadata fetch
_ = get_bucket_stats(mock_client, "mode-test", mode="quick")
assert mock_client.service.storage.head.call_count == 0
# Sampled mode: one HEAD per delta-space (alpha, beta)
mock_client.service.storage.head.reset_mock()
stats_sampled = get_bucket_stats(mock_client, "mode-test", mode="sampled")
assert mock_client.service.storage.head.call_count == 2
# Detailed mode: HEAD for every delta (3 total)
mock_client.service.storage.head.reset_mock()
stats_detailed = get_bucket_stats(mock_client, "mode-test", mode="detailed")
assert mock_client.service.storage.head.call_count == 3
# Sampled totals should be close to detailed but not identical
assert stats_detailed.total_size == 100 + 120 + 210
assert stats_sampled.total_size == 100 + 100 + 210
def test_error_handling_in_metadata_fetch(self, mock_client):
"""Test graceful handling of errors during metadata fetch."""
# Setup
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "reference.bin", "size": 20000000, "last_modified": "2024-01-01"},
{"key": "file1.zip.delta", "size": 50000, "last_modified": "2024-01-02"},
{"key": "file2.zip.delta", "size": 60000, "last_modified": "2024-01-03"},
],
"is_truncated": False,
}
# Mock metadata fetch to fail for one file
def mock_head(path):
if "file1.zip.delta" in path:
raise Exception("S3 error")
elif "file2.zip.delta" in path:
head = Mock()
head.metadata = {"file_size": "19600000"}
return head
return None
mock_client.service.storage.head.side_effect = mock_head
# Execute - should handle error gracefully
stats = get_bucket_stats(mock_client, "error-bucket", mode="detailed")
# Verify - file1 uses fallback, file2 uses metadata
assert stats.object_count == 2
assert stats.delta_objects == 2
# file1 falls back to delta size (50000), file2 uses metadata (19600000)
assert stats.total_size == 50000 + 19600000
def test_multiple_orphaned_references(self, mock_client):
"""Test detection of multiple orphaned reference.bin files."""
# Setup: Multiple orphaned references
mock_client.service.storage.list_objects.return_value = {
"objects": [
{"key": "pro/reference.bin", "size": 20000000, "last_modified": "2024-01-01"},
{
"key": "enterprise/reference.bin",
"size": 25000000,
"last_modified": "2024-01-02",
},
{"key": "community/reference.bin", "size": 15000000, "last_modified": "2024-01-03"},
{"key": "regular.pdf", "size": 1000000, "last_modified": "2024-01-04"},
],
"is_truncated": False,
}
mock_client.service.storage.head.return_value = None
# Execute
stats = get_bucket_stats(mock_client, "multi-orphaned-bucket")
# Verify stats
assert stats.object_count == 1 # Only regular.pdf
assert stats.total_size == 1000000
assert stats.compressed_size == 1000000 # No references included
assert stats.space_saved == 0
# Verify warnings for all orphaned references
warning_calls = [str(call) for call in mock_client.service.logger.warning.call_args_list]
warning_text = " ".join(warning_calls)
assert "ORPHANED REFERENCE FILE" in warning_text
assert "3 reference.bin file(s)" in warning_text
assert "60,000,000 bytes" in warning_text # Total of all references
assert "s3://multi-orphaned-bucket/pro/reference.bin" in warning_text
assert "s3://multi-orphaned-bucket/enterprise/reference.bin" in warning_text
assert "s3://multi-orphaned-bucket/community/reference.bin" in warning_text

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"""Unit tests for bucket stats caching functionality."""
import json
from unittest.mock import MagicMock
from deltaglider.client_models import BucketStats
from deltaglider.client_operations.stats import (
_get_cache_key,
_is_cache_valid,
_read_stats_cache,
_write_stats_cache,
)
def test_get_cache_key():
"""Test cache key generation for different modes."""
assert _get_cache_key("quick") == ".deltaglider/stats_quick.json"
assert _get_cache_key("sampled") == ".deltaglider/stats_sampled.json"
assert _get_cache_key("detailed") == ".deltaglider/stats_detailed.json"
def test_is_cache_valid_when_unchanged():
"""Test cache validation when bucket hasn't changed."""
cached_validation = {
"object_count": 100,
"compressed_size": 50000,
}
assert _is_cache_valid(cached_validation, 100, 50000) is True
def test_is_cache_valid_when_count_changed():
"""Test cache validation when object count changed."""
cached_validation = {
"object_count": 100,
"compressed_size": 50000,
}
# Object count changed
assert _is_cache_valid(cached_validation, 101, 50000) is False
def test_is_cache_valid_when_size_changed():
"""Test cache validation when compressed size changed."""
cached_validation = {
"object_count": 100,
"compressed_size": 50000,
}
# Compressed size changed
assert _is_cache_valid(cached_validation, 100, 60000) is False
def test_write_and_read_cache_roundtrip():
"""Test writing and reading cache with valid data."""
# Create mock client and storage
mock_storage = MagicMock()
mock_logger = MagicMock()
mock_service = MagicMock()
mock_service.storage = mock_storage
mock_service.logger = mock_logger
mock_client = MagicMock()
mock_client.service = mock_service
# Create test stats
test_stats = BucketStats(
bucket="test-bucket",
object_count=150,
total_size=1000000,
compressed_size=50000,
space_saved=950000,
average_compression_ratio=0.95,
delta_objects=140,
direct_objects=10,
)
# Capture what was written to storage
written_data = None
def capture_put(address, data, metadata):
nonlocal written_data
written_data = data
mock_storage.put = capture_put
# Write cache
_write_stats_cache(
client=mock_client,
bucket="test-bucket",
mode="quick",
stats=test_stats,
object_count=150,
compressed_size=50000,
)
# Verify something was written
assert written_data is not None
# Parse written data
cache_data = json.loads(written_data.decode("utf-8"))
# Verify structure
assert cache_data["version"] == "1.0"
assert cache_data["mode"] == "quick"
assert "computed_at" in cache_data
assert cache_data["validation"]["object_count"] == 150
assert cache_data["validation"]["compressed_size"] == 50000
assert cache_data["stats"]["bucket"] == "test-bucket"
assert cache_data["stats"]["object_count"] == 150
assert cache_data["stats"]["delta_objects"] == 140
# Now test reading it back
mock_obj = MagicMock()
mock_obj.data = written_data
mock_storage.get = MagicMock(return_value=mock_obj)
stats, validation = _read_stats_cache(mock_client, "test-bucket", "quick")
# Verify read stats match original
assert stats is not None
assert validation is not None
assert stats.bucket == "test-bucket"
assert stats.object_count == 150
assert stats.delta_objects == 140
assert stats.average_compression_ratio == 0.95
assert validation["object_count"] == 150
assert validation["compressed_size"] == 50000
def test_read_cache_missing_file():
"""Test reading cache when file doesn't exist."""
mock_storage = MagicMock()
mock_logger = MagicMock()
mock_service = MagicMock()
mock_service.storage = mock_storage
mock_service.logger = mock_logger
mock_client = MagicMock()
mock_client.service = mock_service
# Simulate FileNotFoundError
mock_storage.get.side_effect = FileNotFoundError("No such key")
stats, validation = _read_stats_cache(mock_client, "test-bucket", "quick")
assert stats is None
assert validation is None
def test_read_cache_invalid_json():
"""Test reading cache with corrupted JSON."""
mock_storage = MagicMock()
mock_logger = MagicMock()
mock_service = MagicMock()
mock_service.storage = mock_storage
mock_service.logger = mock_logger
mock_client = MagicMock()
mock_client.service = mock_service
# Return invalid JSON
mock_obj = MagicMock()
mock_obj.data = b"not valid json {]["
mock_storage.get = MagicMock(return_value=mock_obj)
stats, validation = _read_stats_cache(mock_client, "test-bucket", "quick")
assert stats is None
assert validation is None
mock_logger.warning.assert_called_once()
def test_read_cache_version_mismatch():
"""Test reading cache with wrong version."""
mock_storage = MagicMock()
mock_logger = MagicMock()
mock_service = MagicMock()
mock_service.storage = mock_storage
mock_service.logger = mock_logger
mock_client = MagicMock()
mock_client.service = mock_service
# Cache with wrong version
cache_data = {
"version": "2.0", # Wrong version
"mode": "quick",
"validation": {"object_count": 100, "compressed_size": 50000},
"stats": {
"bucket": "test",
"object_count": 100,
"total_size": 1000,
"compressed_size": 500,
"space_saved": 500,
"average_compression_ratio": 0.5,
"delta_objects": 90,
"direct_objects": 10,
},
}
mock_obj = MagicMock()
mock_obj.data = json.dumps(cache_data).encode("utf-8")
mock_storage.get = MagicMock(return_value=mock_obj)
stats, validation = _read_stats_cache(mock_client, "test-bucket", "quick")
assert stats is None
assert validation is None
mock_logger.warning.assert_called_once()
def test_read_cache_mode_mismatch():
"""Test reading cache with wrong mode."""
mock_storage = MagicMock()
mock_logger = MagicMock()
mock_service = MagicMock()
mock_service.storage = mock_storage
mock_service.logger = mock_logger
mock_client = MagicMock()
mock_client.service = mock_service
# Cache with mismatched mode
cache_data = {
"version": "1.0",
"mode": "detailed", # Wrong mode
"validation": {"object_count": 100, "compressed_size": 50000},
"stats": {
"bucket": "test",
"object_count": 100,
"total_size": 1000,
"compressed_size": 500,
"space_saved": 500,
"average_compression_ratio": 0.5,
"delta_objects": 90,
"direct_objects": 10,
},
}
mock_obj = MagicMock()
mock_obj.data = json.dumps(cache_data).encode("utf-8")
mock_storage.get = MagicMock(return_value=mock_obj)
# Request "quick" mode but cache has "detailed"
stats, validation = _read_stats_cache(mock_client, "test-bucket", "quick")
assert stats is None
assert validation is None
mock_logger.warning.assert_called_once()
def test_write_cache_handles_errors_gracefully():
"""Test that cache write failures don't crash the program."""
mock_storage = MagicMock()
mock_logger = MagicMock()
mock_service = MagicMock()
mock_service.storage = mock_storage
mock_service.logger = mock_logger
mock_client = MagicMock()
mock_client.service = mock_service
# Simulate S3 permission error
mock_storage.put.side_effect = PermissionError("Access denied")
test_stats = BucketStats(
bucket="test-bucket",
object_count=150,
total_size=1000000,
compressed_size=50000,
space_saved=950000,
average_compression_ratio=0.95,
delta_objects=140,
direct_objects=10,
)
# Should not raise exception
_write_stats_cache(
client=mock_client,
bucket="test-bucket",
mode="quick",
stats=test_stats,
object_count=150,
compressed_size=50000,
)
# Should log warning
mock_logger.warning.assert_called_once()
assert "Failed to write cache" in str(mock_logger.warning.call_args)