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A Python package for time series analysis and forecasting

Project description

⏳ TimeCraft

Welcome to TimeCraft! This project was created to simplify time series analysis, database integration, and task automation.

MIT License Last Commit Repo Size


🚀 Key Features

  • 📈 Time Series Analysis Robust scripts for modeling, forecasting, and evaluating temporal data.

  • 🛢️ Database Integration Tools to efficiently connect to and query various database systems.

  • ⚙️ Automation & Notifications Modules to automate data workflows and send notifications or alerts.


📁 Project Structure

timecraft/
├── /src/                # Core logic and modules
├── /docs/               # Documentation files (README, INSTALL, CONTRIBUTING)
├── /tutorials/          # Step-by-step guides and advanced use cases
├── /data/               # Sample datasets and generated results
├── /assets/             # Visual content for outreach and publications
├── /venv/               # Virtual environment and dependency management
└── requirements.txt     # Python dependencies

🧭 Getting Started

  1. Clone the repository:

    git clone https://github.com/faelmori/timecraft.git
    cd timecraft
    
  2. Create and activate a virtual environment (optional but recommended):

    python -m venv venv
    source venv/bin/activate  # On Windows: venv\Scripts\activate
    
  3. Install the dependencies:

    pip install -r requirements.txt
    
  4. Explore the tutorials: Navigate to the /tutorials folder for usage examples and best practices.


📚 Tutorials & Examples

Topic Description
Time Series Forecasting Learn how to model and predict future data points.
Database Connection Connect to and retrieve data from supported databases.
Automation Pipeline Build and schedule tasks using TimeCraft’s automation tools.

🤝 Contributing

Contributions of all kinds are welcome! Please read our CONTRIBUTING.md for detailed guidelines on how to help improve TimeCraft.


🛣️ Planned Features (Roadmap)

  • ✅ Plug-and-play models for ARIMA, Prophet, and LSTM
  • 🚧 Support for cloud-based data sources (e.g., BigQuery, Snowflake)
  • 🔔 Email and webhook notification system
  • 📊 Dashboard interface for visual result presentation (optional module)

📄 License

This project is licensed under the MIT License.

📧 Contact

If you have any questions or feedback, please feel free to reach out:

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