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Refactors file loading in `app.py` to use `io.TextIOWrapper` instead of `read().decode()`. This allows `pyteomics` to stream data from `Streamlit`'s uploaded files, significantly reducing memory usage for large MGF and mzTab files.
- Replaces `io.StringIO(file.read().decode('utf-8'))` with `io.TextIOWrapper(file, encoding='utf-8')`.
- Adds `tests/test_streaming_io.py` to verify streaming compatibility.
- Updates `.jules/bolt.md` with performance learning.
Co-authored-by: erayfirat <[email protected]>
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💡 What:
Refactored the file loading mechanism in
app.pyto useio.TextIOWrapperfor wrapping binary file streams from Streamlit, instead of reading the entire file content into memory, decoding it, and wrapping it inStringIO.🎯 Why:
The previous approach
mgf_file.read().decode('utf-8')forced the entire file content (and its decoded string representation) into RAM. For large proteomics files (MGFs can be GBs), this causes significant memory spikes and potential OOM errors.TextIOWrapperallows streaming the file content, keeping memory usage low (buffer size only).📊 Impact:
microscope Measurement:
tests/test_streaming_io.pythatload_mgfandload_mztabcorrectly handleTextIOWrapper.PR created automatically by Jules for task 6748135677005912306 started by @erayfirat