Auto coordinate and variable exclusion in encryption transformers for zarr v3 #41
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WalkthroughThe pull request introduces a new parameter, Changes
Sequence Diagram(s)sequenceDiagram
participant Caller
participant Transformer
participant DecryptionHandler
Caller->>Transformer: Call create_zarr_encryption_transformers(encryption_key, header, exclude_vars, detect_exclude)
Transformer->>Transformer: Adjust exclude_vars using detect_exclude parameter
alt Encryption succeeds
Transformer-->>Caller: Return configured transformer
else Decryption error occurs
Transformer->>DecryptionHandler: Handle error and check detect_exclude mode
DecryptionHandler-->>Transformer: Add unencrypted variable to exclusion list (if "auto-from-read")
Transformer-->>Caller: Return error response or updated transformer
end
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Codecov ReportAll modified and coverable lines are covered by tests ✅
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Actionable comments posted: 1
🧹 Nitpick comments (2)
tests/test_zarr_ipfs.py (2)
206-211: Empty header is acceptable but consider broader test coverage.
Defining a deliberately empty header for testing is reasonable, but you may expand test coverage by using various header values to demonstrate diverse encryption scenarios.
229-247: Use a more specific exception instead ofException.
Raising or catchingExceptionis discouraged (B017). Prefer a more precise exception type (e.g.ValueError,OSError, or a custom class) for clearer error handling and fewer false positives.- with pytest.raises(Exception): + with pytest.raises(ValueError):🧰 Tools
🪛 Ruff (0.8.2)
234-234:
pytest.raises(Exception)should be considered evil(B017)
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py_hamt/zarr_encryption_transformers.py(5 hunks)tests/test_zarr_ipfs.py(2 hunks)
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🪛 Ruff (0.8.2)
tests/test_zarr_ipfs.py
234-234: pytest.raises(Exception) should be considered evil
(B017)
🔇 Additional comments (4)
tests/test_zarr_ipfs.py (2)
190-192: Usedetect_excludeeffectively for coordinate variables.
By providingtest_dstodetect_exclude, all coordinate variables intest_dswill be auto-excluded from encryption. This aligns well with the partial encryption strategy.
199-199: Good approach to ensure read-only usage.
Re-instantiatingIPFSZarr3withread_only=Trueis a clean way to verify the dataset can be read correctly from immutable storage.py_hamt/zarr_encryption_transformers.py (2)
74-78: Auto-adding coordinates is correct and convenient.
Including all coordinates fromdetect_excludedatasets inexclude_var_setensures typical dimension variables remain unencrypted. This maintains partial encryption consistency.
105-152: Robust partial-encryption handling.
The logic correctly handles unencrypted metadata, gracefully falls back for partially encrypted datasets when in"auto-from-read"mode, and re-raises otherwise. This approach helps maintain functionality even if some variables are left unencrypted.
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Actionable comments posted: 0
🧹 Nitpick comments (1)
py_hamt/zarr_encryption_transformers.py (1)
137-152: Good resilience for mixed encrypted/unencrypted datasets.The error handling for decryption failures when
detect_exclude = "auto-from-read"allows for graceful recovery when encountering unencrypted variables in a dataset. This makes the solution more robust for real-world scenarios where partial encryption is used.However, consider catching specific encryption-related exceptions rather than all exceptions to avoid masking unrelated errors.
- except Exception as e: + except (ValueError, KeyError) as e: # Or specific ChaCha20_Poly1305 exceptions
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py_hamt/zarr_encryption_transformers.py(5 hunks)
🔇 Additional comments (7)
py_hamt/zarr_encryption_transformers.py (7)
16-18: Fix mismatch between docstring and parameter type.The docstring (line 33) states "set
detect_excludeto None" to disable auto detection, but the type definition only allowsFalse. Update either the parameter type to includeNoneor update the docstring to maintain consistency.
74-78: Well implemented automatic coordinate detection from Dataset.The implementation correctly extracts coordinate variables from the provided dataset and adds them to the exclusion set. This provides a convenient way for users to automatically exclude coordinate variables without having to list them manually.
79-92: Good approach for variable identification in zarr v3 paths.The implementation correctly extracts the variable name from the zarr v3 path structure by finding the first directory name. This is a robust way to identify which variables should be excluded from encryption.
🧰 Tools
🪛 Ruff (0.8.2)
89-92: Return the condition
not key[-9:] == "zarr.json"directlyReplace with
return not key[-9:] == "zarr.json"(SIM103)
105-133: Great feature for coordinate auto-detection from metadata.The implementation intelligently extracts coordinate variables from zarr metadata files, including both consolidated metadata and individual variable metadata. This provides a fallback mechanism for detecting coordinates when a dataset isn't provided upfront.
31-34: Comprehensive documentation of the new feature.The documentation clearly explains the purpose and behavior of the
detect_excludeparameter, including its three possible values. This helps users understand and utilize this powerful feature appropriately.
37-60: Helpful example demonstrating auto-detection features.The example code effectively demonstrates how to use both the explicit coordinate exclusion feature with a dataset and the automatic detection feature when reading with incorrect encryption parameters. This gives users a clear pattern to follow.
105-106:❓ Verification inconclusive
Be cautious about thread safety.
The
seen_metadataset is a mutable state shared between multiple decrypt calls. This could cause issues in multi-threaded environments.Consider if this function might be used in multi-threaded contexts and if so, document this limitation or implement a thread-safe approach.
🏁 Script executed:
#!/bin/bash # Search for any threading or concurrent uses in the codebase rg -i "thread|concurrent|asyncio|parallel" --type pyLength of output: 1105
THREAD SAFETY REVIEW: Revisit Concurrency Considerations in
py_hamt/zarr_encryption_transformers.py
- The mutable state (
seen_metadata: set[str] = set()) is shared across decrypt calls. This could lead to race conditions if these calls are executed concurrently.- While the rest of the codebase (e.g., in
py_hamt/hamt.py) explicitly addresses thread safety—using locks and clear documentation—this file does not currently implement any synchronization.- Action Required:
- Determine whether these decryption routines may be invoked from multiple threads in your use cases.
- If concurrent access is possible:
- Consider adding synchronization (e.g., wrapping access to
seen_metadatawith aLock), or- Clearly document the thread-safety limitation to set proper expectations.
Summary by CodeRabbit
New Features
Documentation