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My custom library for data science, trading and ML projects

Project description

EMR-Py

Documentation

Read the docs

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Current Implementation Status

  • ✅ Logging utilities
  • ✅ ML encoders
  • ✅ Telegram trading bot
  • ✅ Performance decorators
  • 🚧 Time series visualization
  • 📋 Planned: GCP utilities, trading indicators, backtesting tools

Library Structure (Tentative)

src/emrpy/
├── __init__.py
├── py.typed
├── decorators.py           # General utilities (timer, memory profiling)
├── logging/               # Logging configuration utilities
│   ├── __init__.py
│   └── logger_config.py
├── data/               # data utilities
│   ├── __init__.py
│   └── data_loaders.py
├── ml/                    # Machine Learning utilities
│   ├── __init__.py
│   └── encoders.py        # Categorical encoding functions
├── visualization/         # Plotting and visualization functions
│   ├── __init__.py
│   └── timeseries.py     # Time series plotting utilities
├── timeseries/           # Time series analysis tools
│   ├── __init__.py
│   ├── features.py       # Feature engineering
│   └── analysis.py       # Time series analysis functions
├── trading/              # Trading-specific utilities
│   ├── __init__.py
│   ├── indicators.py     # Technical indicators
│   ├── backtesting.py    # Backtesting utilities
│   └── telegrambot.py    # Trading notifications via Telegram
├── gcp/                  # Google Cloud Platform utilities
│   ├── __init__.py
│   ├── bigquery.py       # BigQuery helpers
│   └── storage.py        # Cloud Storage helpers
└── finance/              # Financial data utilities
    ├── __init__.py
    └── data_processing.py # Financial data preprocessing

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