fedfred
A feature-rich python package for interacting with the Federal Reserve Bank of St. Louis Economic Database: FRED
Features
- Now available on Conda-Forge!
- Pandas/Polars/Dask DataFrame native support.
- GeoPandas/Polars-ST/Geopandas-Dask GeoDataframe native support
- Native support for asynchronous requests (async).
- Local caching for easier data access and faster execution times.
- Built-in rate limiter that doesn't exceed 120 calls per minute (ignores local caching).
Installation
You can install the package using pip:
pip install fedfred
Or install from conda-forge:
conda install -c conda-forge fedfred
For type checking support, install with optional type stubs:
pip install fedfred[types]
For use with Polars DataFrames and GeoDataFrames, install with:
pip install fedfred[polars]
For use with Dask DataFrames and GeoDataFrames, install with:
pip install fedfred[dask]
We recommend using a virtual environment with either installation method.
Rest API Usage
I recommend consulting the documentation at: https://nikhilxsunder.github.io/fedfred/
Here is a simple example of how to use the package:
# FredAPI
import fedfred as fd
api_key = 'your_api_key'
fred = fd.FredAPI(api_key)
# Get Series Observations as a pandas DataFrame
gdp = fred.get_series_observations('GDP')
gdp.head()
# Get Series Observations as a pandas DataFrame (async)
import asyncio
async def main():
fred = fd.FredAPI(api_key).Async
gdp = fred.get_series_observations('GNPCA')
print(observations.head())
asyncio.run(main())
Important Notes
- Store your API keys and secrets in environment variables or secure storage solutions.
- Do not hardcode your API keys and secrets in your scripts.
- XML filetype (file_type='xml') is currently not supported but will be in a future update
Continuous Integration
FedFred uses GitHub Actions for continuous integration. The following workflows run automatically:
- Build and Test: Triggered on every push and pull request to verify the codebase builds and tests pass
- Analyze: Runs static code analysis to identify potential issues
- Test: Comprehensive test suite with coverage reporting
- CodeQL: Security analysis to detect vulnerabilities
- Docs: Deploys Github Pages website for documentation, built off of sphinx docs.
These checks ensure that all contributions maintain code quality and don't introduce regressions.
Status badges at the top of this README reflect the current state of our CI pipelines.
Development
FedFred uses standard Python packaging tools:
- Poetry: For dependency management and package building
- pytest: For testing
- Sphinx: For documentation generation
To set up the development environment:
# Install Poetry
curl -sSL https://install.python-poetry.org | python3 -
# Clone the repository
git clone https://github.com/nikhilxsunder/fedfred.git
cd fedfred
# Install dependencies
poetry install
# Run tests
poetry run pytest
Testing
The project uses pytest as its testing framework. Tests are located in the tests/ directory.
To run the complete test suite:
poetry run pytest
For running tests with coverage reports:
poetry run pytest --cov=fedfred tests/
To run a specific test file:
poetry run pytest tests/specific_module_test.py
Test Coverage
We aim to maintain a minimum of 80% code coverage across the codebase. This includes:
- Core functionality: 90%+ coverage
- Edge cases and error handling: 80%+ coverage
- Utility functions: 75%+ coverage
Continuous integration automatically runs tests on all pull requests and commits to the main branch.
Test Policy
FedFred requires tests for all new functionality. When contributing:
- All new features must include appropriate tests
- Bug fixes should include tests that verify the fix
- Tests should be added to the automated test suite in the
tests/directory
Security
For information about reporting security vulnerabilities in FedFred, please see our Security Policy.
Contributing
Contributions are welcome! Please open an issue or submit a pull request.
Citation
If you use fedfred in your research, projects, or publications, please cite it as follows:
Plain Text:
Sunder, Nikhil. (2025). fedfred: A Python client for the Federal Reserve Economic Database (FRED) API.
Version 2.1.5. Available at: https://github.com/nikhilxsunder/fedfred
BibTeX:
@software{fedfred,
author = {Nikhil Sunder},
title = {fedfred: A Python client for the Federal Reserve Economic Database (FRED) API},
year = {2025},
publisher = {GitHub},
version = {2.1.5},
doi = {10.5281/zenodo.17180397},
url = {https://github.com/nikhilxsunder/fedfred},
orcid = {https://orcid.org/0009-0007-3323-1760}
}
You can also download a ready-made citation file from the GitHub repository
License
This project is licensed under the MIT License - see the LICENSE file for details.
1 maintainer
Metadata
1 maintainer
Release files for fedfred 3.0.0
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Source distribution (sdist)
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Built distribution (wheel)
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| fedfred-3.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 92.6 kB
Release files / fedfred-3.0.0.tar.gz
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| Tags | Python 3 |
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Security for fedfred 3.0.0
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