76cb49e908
- Add python-dotenv loading in main.py so DATABASE_URL is read from .env before db.py module initializes - Add MLFLOW_TRACKING_URI to .env.example pointing to PostgreSQL - Add python-dotenv>=1.0.0 to pyproject.toml dependencies - Initialize MLflow schema in candle_annotator PostgreSQL database MLflow server now starts without filesystem deprecation warnings and with full job execution support. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
33 lines
776 B
TOML
33 lines
776 B
TOML
[project]
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name = "candle-ml"
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version = "0.1.0"
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description = "ML service for candlestick pattern recognition"
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requires-python = ">=3.11"
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dependencies = [
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"fastapi>=0.109.0",
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"uvicorn[standard]>=0.27.0",
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"scikit-learn>=1.4.0",
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"xgboost>=2.0.3",
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"pandas>=2.2.0",
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"numpy>=1.26.0",
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"joblib>=1.3.2",
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"mlflow>=2.10.0",
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"pyyaml>=6.0.1",
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"TA-Lib>=0.4.28",
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"dvc>=3.40.0",
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"sqlalchemy>=2.0.25",
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"psycopg2-binary>=2.9.9",
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"pydantic>=2.5.0",
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"pydantic-settings>=2.1.0",
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"python-dotenv>=1.0.0",
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"matplotlib>=3.8.2",
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"seaborn>=0.13.1",
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]
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[build-system]
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requires = ["setuptools>=61.0"]
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build-backend = "setuptools.build_meta"
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[tool.setuptools.packages.find]
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where = ["."]
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include = ["app*", "features*", "training*"]
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