⚡ Bolt: Use CSafeLoader for faster PyYAML parsing#546
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Co-authored-by: aafre <8656674+aafre@users.noreply.github.com>
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Code Review
This pull request optimizes PyYAML parsing performance by implementing CSafeLoader with a fallback mechanism across several modules. It also includes a significant codebase-wide reformatting of imports, data structures, and test files to improve consistency. The review feedback suggests specifying explicit UTF-8 encoding when opening files to ensure consistent behavior across different environments.
| @@ -838,20 +840,22 @@ def generate_latex_pdf(yaml_data, icons_dir, output_path, template_name="classic | |||
| def load_resume_data(yaml_file_path): | |||
| """Load and validate resume data from YAML file.""" | |||
| with open(yaml_file_path, "r") as file: | |||
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When opening text files for reading, it is recommended to specify an explicit encoding (e.g., encoding="utf-8") to ensure consistent behavior across different platforms and environments.
| with open(yaml_file_path, "r") as file: | |
| with open(yaml_file_path, "r", encoding="utf-8") as file: |
| @@ -1897,7 +1918,7 @@ def generate_resume(): | |||
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| # Parse YAML to extract icon references | |||
| with open(yaml_path, "r") as f: | |||
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Specify an explicit encoding when opening the YAML file to avoid potential issues with platform-dependent default encodings.
| with open(yaml_path, "r") as f: | |
| with open(yaml_path, "r", encoding="utf-8") as f: |
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Closing duplicate — the most recent version of this change is PR #549. |
Understood. Acknowledging that this work is now obsolete and stopping work on this task. |
1 participant
What: Replaced
yaml.safe_loadwithyaml.load(..., Loader=yaml.CSafeLoader)with a fallback toyaml.SafeLoaderacross all backend parsing sites.Why: PyYAML's
safe_loaddefaults to a pure Python implementation which is slower than the C extension for parsing large configuration or data files.Impact: Faster YAML parsing speed for file loading and DB JSONB conversions, improving latency.
Measurement: Verified optimization via manual local benchmark using test data, and validated with existing test suite using
pytest.PR created automatically by Jules for task 8499870962363146812 started by @aafre