python-project-setup

name	python-project-setup
description	Python project setup and management using the MiquelGomezCorral template. Use for virtual environments (conda), dependency management (uv), editable installs, Jupyter kernels, and project scaffolding.

Python Project Setup & Management (MiquelGomezCorral Template)

WHEN TO USE THIS SKILL

Use only for the MiquelGomezCorral template or explicit environment, dependency, editable-install, Jupyter-kernel, and scaffolding work. Ordinary Python coding follows the current repository's own tooling and conventions.

Read this file whenever the user asks to:

• Set up or repair the environment for an existing template-based Python project
• Create a new Python project or scaffold a project structure
• Set up a virtual environment or conda environment for a project
• Install dependencies with uv or manage requirements.txt
• Add a Jupyter kernel linked to a project environment
• Work with the app/ package (editable installs, pyproject.toml)
• Bootstrap, replicate, or explain the MiquelGomezCorral Python template

TEMPLATE OVERVIEW

Source: https://github.com/MiquelGomezCorral/Python-project-template-AI-TL

This template is designed for data science and software development workflows. It favors:

• conda for environment creation (Python 3.13)
• uv for fast dependency resolution
• pip install -e . for editable app/ package installs
• ipykernel for Jupyter notebooks linked to the environment

DIRECTORY STRUCTURE

<project-name>/
├── app/                  # Installable package (editable via pip install -e .)
│   ├── src/              # Core source modules
│   └── scripts/          # Runnable scripts
├── configs/              # YAML / JSON configuration files
├── data/                 # Datasets
│   ├── raw/              # Unprocessed source data
│   └── processed/        # Cleaned / transformed data
├── docs/                 # Project documentation
├── logs/                 # Runtime logs
├── models/               # Serialised model artefacts
├── notebooks/            # Jupyter notebooks for EDA and experimentation
├── .gitignore
├── example.env           # Template for .env secrets (never commit .env)
├── LICENSE
├── pyproject.toml
├── README.md
└── requirements.txt

Key rule: app/ is both a folder and a Python package. pyproject.toml declares it as an editable install so you can from src.module import ... anywhere in the project.

pyproject.toml (canonical template)

[project]
name = "app"
version = "0.1.0"

[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"

[tool.setuptools.packages.find]
where = ["app"]
include = ["src*", "scripts*"]

If the user renames the project, update name in [project] but keep where = ["app"] unless they also rename the folder.

SETUP COMMANDS (run once per project)

# 1. Create and activate conda environment
conda create --name MY_ENV python=3.13 -y
conda activate MY_ENV

# 2. Install dependencies (uv for speed)
uv pip install -r requirements.txt

# 3. Editable install of the app package
pip install -e .

# 4. Register Jupyter kernel for this environment
uv pip install ipykernel
python -m ipykernel install --user --name=MY_ENV --display-name "MY_ENV (Conda)"

Replace MY_ENV with the project name everywhere.

COMMON TASKS

Create a new project from scratch

mkdir <project-name> && cd <project-name>
# Clone or copy template structure, then:
conda create --name <project-name> python=3.13 -y
conda activate <project-name>
uv pip install -r requirements.txt
pip install -e .

Add a new dependency

# Install and then pin it:
uv pip install <package>
uv pip freeze | grep <package> >> requirements.txt
# Or edit requirements.txt manually, then:
uv pip install -r requirements.txt

Reproduce an existing project environment

conda create --name <project-name> python=3.13 -y
conda activate <project-name>
uv pip install -r requirements.txt
pip install -e .

Re-register the Jupyter kernel (after env rebuild)

python -m ipykernel install --user --name=<env-name> --display-name "<env-name> (Conda)"

Remove environment

conda deactivate
conda remove --name <env-name> --all -y

IMPORTING FROM app/

Because the package is installed as editable, use:

from src.my_module import my_function   # maps to app/src/my_module.py
from scripts.run import main            # maps to app/scripts/run.py

No sys.path hacks needed; pip install -e . handles discovery via pyproject.toml.

NOTES & PITFALLS

• Never commit .env — only commit example.env with placeholder values.
• If uv is not found, install it globally with pip install uv or pipx install uv.
• On macOS/Linux, conda activate may require conda init bash (or zsh) first.
• Python version in the template is 3.13; adjust if the project requires an older version.
• pyproject.toml uses where = ["app"], so setuptools looks for packages inside app/. Sub-packages must have __init__.py.
• requirements.txt is the single source of truth for dependencies; do not duplicate them in pyproject.toml [project.dependencies] unless packaging for distribution.