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# Template for Python Projects | ||
# A Template Repository for Data Science Projects | ||
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[](https://github.com/habedi/template-python-project-repo/actions/workflows/tests.yml) | ||
[](https://github.com/habedi/template-python-project-repo) | ||
[](https://github.com/habedi/template-python-project-repo/blob/main/LICENSE) | ||
[](https://github.com/habedi/template-python-project/actions/workflows/tests.yml) | ||
[](https://github.com/habedi/template-python-project) | ||
[](https://github.com/habedi/template-python-project/blob/main/LICENSE) | ||
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This repository is as a template for starting Python projects. It includes a basic structure for organizing the things | ||
like code, | ||
data, and notebooks, as well as a configuration file for managing the dependencies using Poetry. The repository also | ||
includes a GitHub Actions workflow for running tests on the codebase. | ||
This is a simple and minimalistic template repository for starting new data science and machine learning projects in | ||
Python. | ||
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I made it mainly for my personal and professional machine learning data science projects, but feel free to use it | ||
as a starting point for your own projects if you find it useful. | ||
I created this template to help me speed up the setup process for my projects. | ||
And to have a consistent structure across all my personal and professional projects. | ||
I'm sharing it here in the hope that others find it useful. | ||
So, feel free to use it as a starting point for your projects. | ||
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## Installing Poetry | ||
--- | ||
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We use [Poetry](https://python-poetry.org/) for managing the dependencies and virtual environment for the project. To | ||
get | ||
started, you need to install Poetry on your machine. We can install Poetry by running the following command in the | ||
command | ||
line using pip. | ||
## Notable Features | ||
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```bash | ||
pip install poetry | ||
``` | ||
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When the installation is finished, run the following command in the shell in the root folder of this repository to | ||
install the dependencies, and create a virtual environment for the project. | ||
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```bash | ||
poetry install | ||
``` | ||
- A predefined file and folder layout that should be suitable for most data science workflows. | ||
- Easy dependency and environment management with [Poetry](https://python-poetry.org/). | ||
- Extra configuration files for various tasks like linting, formatting, and testing. | ||
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After that, enter the Poetry environment by invoking the poetry shell command. | ||
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```bash | ||
poetry shell | ||
``` | ||
--- | ||
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## Folder Structure | ||
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The repository has the following structure: | ||
The repository is organized as follows: | ||
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```plaintext | ||
template-python-project/ | ||
├── bin/ # Scripts and command-line tools | ||
├── data/ # Raw and processed datasets | ||
├── notebooks/ # Jupyter notebooks for exploration, analysis, and prototyping | ||
├── src/ # Source code for the project | ||
├── models/ # ML models and related files | ||
├── tests/ # Unit tests and test files | ||
├── pyproject.toml # Project metadata and dependencies | ||
├── LICENSE # License information | ||
└── README.md # Project documentation | ||
``` | ||
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- `bin/`: scripts and executables for command line use | ||
- `data/`: data files and datasets | ||
- `src/`: source code files | ||
- `notebooks/`: Jupyter notebooks files | ||
- `models/`: trained models and model files | ||
- `tests/`: test files for the source code | ||
- `pyproject.toml`: project metadata and dependencies | ||
- `LICENSE`: license information | ||
- `README.md`: project information and instructions | ||
--- | ||
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## License | ||
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Files in this repository are licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | ||
The files in this repository are licensed under the [MIT License](LICENSE). |
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