Stream downloads to temp file to reduce memory usage
- Download packages in 64KB chunks to temp file instead of loading into memory - Upload to S3 from temp file (streaming) - Clean up temp file after processing - Reduces memory footprint from 2x file size to 1x file size
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@@ -7,8 +7,10 @@ Artifacts are cached on first access through configured upstream sources.
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import hashlib
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import logging
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import os
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import re
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import tarfile
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import tempfile
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import zipfile
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from io import BytesIO
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from typing import Optional, List, Tuple
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@@ -635,16 +637,32 @@ async def pypi_download_file(
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detail=f"Upstream returned {response.status_code}"
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)
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content = response.content
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content_type = response.headers.get('content-type', 'application/octet-stream')
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# Store in S3 (computes hash and deduplicates automatically)
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from io import BytesIO
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result = storage.store(BytesIO(content))
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sha256 = result.sha256
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size = result.size
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# Stream to temp file to avoid loading large packages into memory
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# This keeps memory usage constant regardless of package size
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tmp_path = None
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try:
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with tempfile.NamedTemporaryFile(delete=False, suffix=f"_{filename}") as tmp_file:
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tmp_path = tmp_file.name
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for chunk in response.iter_bytes(chunk_size=65536): # 64KB chunks
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tmp_file.write(chunk)
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logger.info(f"PyPI proxy: downloaded {filename}, {size} bytes, sha256={sha256[:12]}")
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# Store in S3 from temp file (computes hash and deduplicates automatically)
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with open(tmp_path, 'rb') as f:
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result = storage.store(f)
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sha256 = result.sha256
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size = result.size
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# Read content for metadata extraction and response
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with open(tmp_path, 'rb') as f:
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content = f.read()
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logger.info(f"PyPI proxy: downloaded {filename}, {size} bytes, sha256={sha256[:12]}")
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finally:
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# Clean up temp file
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if tmp_path and os.path.exists(tmp_path):
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os.unlink(tmp_path)
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# Check if artifact already exists
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existing = db.query(Artifact).filter(Artifact.id == sha256).first()
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