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Python Development Environment Setup

2 min read

Tools

UV is a Python package management system that replaces pip, pip-tools, pipx, poetry, pyenv, twine, virtualenv, and more, and is said to be 10-100x faster than pip.

# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh

Alternatively, you can use homebrew to install uv

brew install uv

If installed via the standalone installer, uv can update itself to the latest version:

uv self update

Usage

 
# Insatall a specific version of Python
uv python install 3.12
 
# Create a new Python project
uv init
 
# Add a dependency to the project
uv add python-dotenv
 
# Remove a dependency from the project
uv remove python-dotenv
 
# Sync the project's dependencies with the environment
uv sync

uv supports virtual environments, e.g., to create a virtual environment at .venv:

uv venv
 
# Activate with: source .venv/bin/activate
source .venv/bin/activate
 
# Deactivate
deactivate

Environment inspection

List globally installed packages.

pip list
 
pip freeze

To visualise the package dependencies, use pipdeptree.

# Install pipdeptree
pip install pipdeptree
 
# Visualise the dependency tree
pipdeptree

Setting up .venv

It is recommended that a virtual environment be created for your project.

# Use any virtual environment
 
PROJECT_NAME=colab-notebooks
 
python3 -m venv ~/Workspace/${PROJECT_NAME}/.venv
source ~/Workspace/${PROJECT_NAME}/.venv/bin/activate

Load environment variables via python-dotenv

dotenv.load_dotenv()

Install packages listed in the requirements.txt

pip install -r /path/to/requirements.txt

Creating requirements.txt

Create a requirements.txt fire from within an existing project:

pip freeze > requirements.txt

IDE setup for Python.

Install Python LSP server (Emacs)

This is required for the lsp-mode in Emacs.

pip install "python-lsp-server[all]"

Run Jupyter Notebooks with VS Code

  1. Install Jupyter extension for VS Code.

  2. Create a virtual environment in the project directory.

# Use any virtual environment
 
python3 -m venv ~/Workspace/project_name/.venv
source ~/Workspace/project_name/.venv/bin/activate
  1. In VS Code, press Cmd+Shift+P, select Python: Select Interpreter and choose the virtual env you just created.

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