'QuantStream' is a Python library for financial data analysis and visualization.
Project description
QuantStream
QuantStream is a Python-based financial modeling platform designed to interact with real-time financial data via APIs, including the Financial Modeling Prep (FMP) API. The platform provides tools for model training, real-time data integration, and visualization.
Features
- API Wrapper: Integration with the FMP API for fetching financial data.
- Model Training: Train models using financial data directly within the platform.
- Real-time Visualization: Display and interact with real-time financial data.
- Data Export: Download financial data in various formats such as CSV.
- Extensible Architecture: Easily add new models or financial data providers.
Installation
Requirements
- Python 3.11 or higher
uvpackage for environment and dependency managementrufffor linting
Setup
-
Clone the repository:
git clone https://github.com/yourusername/quantstream.git cd quantstream
-
Install
uvand sync dependencies:curl -sSL https://install.astral.sh | sh uv sync --all-extras --dev
-
Set up the environment variable for your API key:
export FMP_API_KEY=your_api_key_here
-
Run the application:
uv run python -m quantstream
Usage
Train a Model
uv run python -m quantstream.train_model --symbol AAPL --model linear
This command trains a linear model for Apple Inc. using real-time financial data.
Get Real-Time Data
uv run python -m quantstream.fetch_data --symbol AAPL
Fetches the latest financial data for Apple Inc. from the FMP API.
Visualize Data
The platform comes with visualization tools for real-time financial data. You can run the visualization module using:
uv run python -m quantstream.visualize --symbol AAPL
Development Workflow
Code Style and Linting
We use ruff for code linting. You can check for any style issues by running:
uv run ruff check .
Running Tests
Tests are managed using pytest. You can run all tests with:
uv run pytest tests/
Pre-commit Hooks
This project uses pre-commit hooks to enforce code quality. Install the hooks by running:
pre-commit install
Contributing
We welcome contributions! Please see the CONTRIBUTING.md file for guidelines.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Project details
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