Table of Contents
This project is the Python backend for the Tweets Classification Machine Learning project developed using FastAPI, PostgreSQL and Redis.
- Clone the repository
git clone https://github.com/jpcadena/tweets-classification-backend.git - Change the directory to root project
cd tweets-classification-backend - Create a virtual environment venv
python -m venv venv - Activate environment in Windows
.\venv\Scripts\activate - Install requirements with PIP
pip install -r requirements.txt
- If found sample.env, rename it to .env.
- Replace your credentials into the .env file.
- Execute with console
uvicorn main:app --reload - Visit http://localhost:8000/docs for Swagger UI documentation.
If you have a suggestion that would make this better, please fork the repo and create a pull request.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Use docstrings with reStructuredText format by adding triple double quotes
""" after function definition.
Add a brief function description, also for the parameters including the return
value and its corresponding data type.
Please use linting to check your code quality
following PEP 8.
Check documentation
for Visual Studio Code
or Jetbrains Pycharm.
Recommended plugin for
autocompletion: Tabnine
Distributed under the MIT License.
