⚡️ Speed up method AuthService.get_user_id_from_token by 254% in PR #11639 (docs-chat-refactor-and-screenshots)#11641
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The optimized code achieves a **254% speedup (10.8ms → 3.03ms)** by replacing the heavyweight `jwt.decode()` call with manual JWT payload extraction using Python's built-in `base64` and `json` modules. ## Key Optimization **What changed:** Instead of using PyJWT's `jwt.decode()` to parse the token (even with signature verification disabled), the code now: 1. Splits the JWT string on "." to access the payload segment directly 2. Manually decodes the base64url-encoded payload 3. Parses the resulting JSON with `json.loads()` 4. Extracts the "sub" claim as before **Why it's faster:** Line profiler data shows the bottleneck was `jwt.decode()`, consuming **88.3%** of the original runtime (63.9ms out of 72.3ms total). The PyJWT library has significant overhead from: - Import and initialization costs - Internal validation and normalization logic - Additional abstraction layers even when signature verification is disabled The optimized version distributes work across lightweight stdlib operations: - String split and base64 decode: **20.3%** of new runtime (3.6ms) - JSON parsing: **23.7%** of new runtime (4.2ms) - No single dominant bottleneck **Performance characteristics:** The optimization excels when: - Processing **valid, well-formed JWTs** (test cases show successful extraction from standard tokens) - Handling **invalid JWT structures** (malformed tokens now fail faster during split/decode rather than going through jwt.decode's full validation) - Processing **batches of tokens** (the large-scale tests with 100+ tokens demonstrate consistent performance) The test results confirm correctness is preserved across all edge cases: missing claims, invalid UUIDs, malformed tokens, and various UUID formats all return `UUID(int=0)` as expected. **Impact on workloads:** Since this is a utility function explicitly designed for non-security contexts (logging, debugging), the optimization provides immediate benefit anywhere user IDs need to be extracted from tokens without verification overhead. The function's role in authentication service suggests it may be called frequently during request processing, making this ~72% reduction in execution time particularly valuable.
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## docs-1.8-release #11641 +/- ##
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⚡️ This pull request contains optimizations for PR #11639
If you approve this dependent PR, these changes will be merged into the original PR branch
docs-chat-refactor-and-screenshots.📄 254% (2.54x) speedup for
AuthService.get_user_id_from_tokeninsrc/backend/base/langflow/services/auth/service.py⏱️ Runtime :
10.8 milliseconds→3.03 milliseconds(best of49runs)📝 Explanation and details
The optimized code achieves a 254% speedup (10.8ms → 3.03ms) by replacing the heavyweight
jwt.decode()call with manual JWT payload extraction using Python's built-inbase64andjsonmodules.Key Optimization
What changed: Instead of using PyJWT's
jwt.decode()to parse the token (even with signature verification disabled), the code now:json.loads()Why it's faster: Line profiler data shows the bottleneck was
jwt.decode(), consuming 88.3% of the original runtime (63.9ms out of 72.3ms total). The PyJWT library has significant overhead from:The optimized version distributes work across lightweight stdlib operations:
Performance characteristics: The optimization excels when:
The test results confirm correctness is preserved across all edge cases: missing claims, invalid UUIDs, malformed tokens, and various UUID formats all return
UUID(int=0)as expected.Impact on workloads: Since this is a utility function explicitly designed for non-security contexts (logging, debugging), the optimization provides immediate benefit anywhere user IDs need to be extracted from tokens without verification overhead. The function's role in authentication service suggests it may be called frequently during request processing, making this ~72% reduction in execution time particularly valuable.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pr11639-2026-02-07T00.01.41and push.