Quick Project Template

Below is a bare‑bones, data‑science‑oriented Python module template that uses pyproject.toml and a Conda environment. It’s designed to be:

• Easy to clone and set up via Conda

• Minimal

• PEP 517/518‑compliant for modern packaging

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📌 Quick‑Start Checklist

1. Fork & clone

2. Conda‑create: conda env create -f environment.yml

3. Activate: conda activate my_project

4. Install: pip install -e .

5. Run: import your module in a Python REPL or script

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📁 Project Structure

my_project/
├── environment.yml        # Conda environment spec
├── pyproject.toml         # Build system & metadata
├── README.md              # Overview + setup instructions
├── .gitignore             # Files & dirs to ignore in Git
└── src/
    └── my_project/
        ├── __init__.py    # Makes this a Python package
        └── core.py        # Your module’s main code

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📋 File Descriptions

File / Directory	Purpose	Details
environment.yml	Conda env spec	Lists Python version & dependencies (e.g. numpy, pandas, matplotlib).
pyproject.toml	Build config & metadata	Specifies package name, version, author, and build backend (setuptools or poetry).
README.md	Project overview + setup guide	Explains project purpose, how to install, usage examples.
.gitignore	Git ignore rules	Excludes pycache/, .env/, .ipynb_checkpoints/, etc.
src/my_project/	Python package source	All your .py modules live here.
src/my_project/init.py	Package initializer	Keeps package namespace clean; optionally exposes key functions.

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🛠️ Setup Instructions

1. Clone the repository

git clone https://github.com/<your‑username>/my_project.git
cd my_project

2. Create & activate the Conda environment

conda env create -f environment.yml
conda activate my_project

Alternative

Contents Use requirements.txt instead of environment.yml with

python -m venv .env source .env/bin/activate # macOS/Linux ..env\Scripts\activate # Windows pip install -r requirements.txt

3. Install your package in “editable” mode

pip install -e .

This lets you modify src/my_project/ and see changes immediately.

4. Verify installation

python -c "import my_project; print(my_project.__version__)"

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⚙️ environment.yml

 Example

name: my_project
channels:
  - conda-forge
dependencies:
  - python=3.10
  - numpy
  - pandas
  - matplotlib
  - pip          # for pip‑only packages
  - pip:
      - scikit-learn  # example pip package

---

📐 pyproject.toml

 Example

[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "my_project"
version = "0.1.0"
description = "A minimal data science Python module."
authors = [
  { name="Your Name", email="you@example.com" }
]
readme = "README.md"
license = { file="LICENSE" }
dependencies = [
  "numpy>=1.20",
  "pandas>=1.3"
]

[tool.setuptools.packages.find]
where = ["src"]

---

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Tip for careful readers:

• You can replace Setuptools with Poetry by swapping the [build-system] section and using poetry.lock/pyproject.toml for dependency management.

• Add a tests/ directory and CI workflow (e.g., GitHub Actions) later for automated testing.