Three proposals addressing the 2026-02-25 trace pipeline OOM crash (114K CIDs): 1. trace-events-memory-triage: fetchmany iterator (read_sql_df_slow_iter), admission control (50K CID limit for non-MSD), cache skip for large queries, early memory release with gc.collect() 2. trace-async-job-queue: RQ-based async jobs for queries >20K CIDs, separate worker process with isolated memory, frontend polling via useTraceProgress composable, systemd service + deploy scripts 3. trace-streaming-response: chunked Redis storage (TRACE_STREAM_BATCH_SIZE=5000), NDJSON stream endpoint (GET /api/trace/job/<id>/stream), frontend ReadableStream consumer for progressive rendering, backward-compatible with legacy single-key storage All three proposals archived. 1101 tests pass, frontend builds clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
41 lines
1.1 KiB
Plaintext
41 lines
1.1 KiB
Plaintext
# MES Dashboard Dependencies
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# ===========================
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#
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# Version Strategy:
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# Use bounded version ranges (>=,<) to avoid accidental major-version breaks.
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# For reproducible builds, generate a lock file: pip freeze > requirements.lock
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#
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# Python Version: >=3.9 (recommended: 3.11)
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# Core Framework
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flask>=3.0.0,<4.0.0
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# Database
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oracledb>=2.0.0,<4.0.0
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sqlalchemy>=2.0.0,<3.0.0
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# Data Processing
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pandas==2.3.3 # pandas 3.x removed DBAPI2 flow used by current pd.read_sql + SQLAlchemy usage
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pyarrow>=17.0.0,<20.0.0 # Parquet serialization for Redis DataFrame cache
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openpyxl>=3.0.0 # Excel file support
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# Cache (Redis)
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redis>=5.0.0,<6.0.0
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hiredis>=2.0.0,<4.0.0 # C parser for better Redis performance
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# Task Queue (async trace jobs)
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rq>=1.16.0,<2.0.0
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# HTTP Client
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requests>=2.28.0,<3.0.0
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# Configuration
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python-dotenv>=1.0.0,<2.0.0
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# WSGI Server
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gunicorn>=21.2.0,<25.0.0 # Linux/macOS production server
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waitress>=2.1.2,<4.0.0; platform_system=="Windows" # Windows alternative
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# System Monitoring
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psutil>=5.9.0,<7.0.0 # Process and system utilities
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