RESTful API Boilerplate

Author

Daniel

Description

This project serves as a boilerplate for creating RESTful APIs using Flask and Swagger. It is specifically designed to integrate with databases and leverages Python's Pandas and NumPy for data processing. The API can be utilized in conjunction with other programming languages to streamline complex database queries or even multiple databases for data analysis and result rendering.

Technologies Used

• Flask
• Flask-RESTx
• SQLAlchemy
• mysql.connector
• pymysql
• NumPy
• Pandas
• Gunicorn
• psutil
• cachetools

Features

• Two sample namespaces (sample_namespace and utils_namespace) located in sample.py and utils.py within the api folder.
• Database connectivity to MySQL demonstrated in database.py.
• A pandas_sample.py file that serves as a proof-of-concept for using Pandas to generate API responses. This can be thought of as a stand-in for a Jupyter Notebook with defined functions for API endpoints.
• Function caching using cachetools to avoid unnecessary queries.
• Dockerized using Gunicorn with 4 workers, configurable via the Dockerfile.

Building the Docker Image

To build the Docker image for this project, you can run the following command after copy .env.example to .env:

cp .env.example .env
make build

The build process utilizes the Makefile located in the deploy folder.

Running the Project

To start the project, you can use:

make start

And to stop it:

make stop

These commands also use the Makefile in the deploy folder.

Configuration

The deploy folder contains a docker-compose.yml file and a sample .env file for database connections. Update the .env file as needed to connect to your own database instance.

License

This project is licensed under the GNU General Public License v3.0. For more information, see GNU GPLv3 License.

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For more details, feel free to explore the codebase or reach out with questions.