Skip to content

Latest commit

 

History

History

deps-management

README.md

Python Dependencies and Package Management

I Stand with Israel

Introduction

As a C# developer, you might be familiar with NuGet for managing dependencies in your projects. Python has similar tools and practices for dependency management, but with some differences. This document will guide you through Python's dependency management tools and practices, comparing them to what you might already know from C# development.

Packages vs. Modules

In Python, packages and modules are used to organize code. A package is a directory containing a special __init__.py file, while a module is a single Python file. This is somewhat similar to namespaces and assemblies in C#.

  • Packages: Generally directories containing multiple modules.
  • Modules: Single Python files.

Python uses sys.path to search for modules and packages. You can also use the PYTHONPATH environment variable to add additional directories to the search path.

Creating a Package

  1. Create a folder and add an __init__.py file.
  2. Use the package in your code.

Example:

python -m demo_reader.compressed.bzipped test.bz2 data compressed with bz2

Executing Directories or Packages

You can execute a directory or package by adding it to sys.path and ensuring it contains a __main__.py file.

Example:

python {directory_name}

Using the -m switch:

python -m {directory_name}

Build and Distribution

Python uses setup.py for building and distributing packages, similar to .csproj files in C#.

Example:

python setup.py sdist
pip install wheel
python setup.py bdist_wheel

pip Dependencies and Package Management

pip is the package installer for Python, similar to NuGet in C#. It allows you to install and manage packages from the Python Package Index (PyPI).

Resources

Install with pip from PyPI

# Create a virtual environment
python -m venv .venv

# Activate the environment
source .venv/bin/activate
# or
. .venv/bin/activate

# Install the latest version of a package
python -m pip install "package_name"

# Install a specific version
python -m pip install "package_name==1.2.2"

# Version comparison
python -m pip install "package_name < 1.2"

# Exclude a version
python -m pip install "package_name!=1.0.0"

# Combine operators
python -m pip install "Flask>=1.0.0,!=1.1.0,<=2.0.0"

# Compatible release
python -m pip install "requests ~=2.24.0"

# Environment markers
python -m pip install "asyncio; os_name='nt'"

# Show installed packages
python -m pip list

# Upgrade to the latest version
python -m pip install --upgrade "package_name"

Install from GitHub

python -m pip install "{name of the package} @ git+{url}"

Install from Local Directory

# pyproject.toml file is required
python -m pip install ~/projects/{project_name}

Install in Editable Mode

pip install -e ~/projects/{project_name}
# or from the current directory
python -m pip install -e .

Global Utilities

python3 -V
which python3
python3 -m pip

# Install pip
sudo apt install python3-pip

# Install pipx
sudo apt install pipx
pipx ensurepath

Using requirements.txt

requirements.txt is similar to packages.config in C#. It lists the dependencies for your project.

python -m venv .venv
. .venv/bin/activate
python -m pip install SQLAlchemy
pip freeze > requirements.txt
pip install -r requirements.txt
deactivate

Alternatives: pipenv and poetry

pipenv

pipenv is focused on applications and uses Pipfile and Pipfile.lock for dependency management.

pipx install pipenv
pipenv install arrow
pipenv sync -d
pipenv graph
pipenv run python script.py
pipenv shell
pipenv check

poetry

poetry is used for both libraries and applications. It uses pyproject.toml and poetry.lock.

pipx install poetry --sync
poetry new poetry_demo
poetry init
poetry add arrow requests
poetry install
poetry show --tree
poetry remove requests
poetry add pytest --group test

Alternative Tooling for Project-Level Dependency Management

In addition to pipenv and poetry, there are other tools available for managing dependencies at the project level in Python. These tools offer various features and can be chosen based on your specific needs.

pip-tools

pip-tools helps you keep your requirements.txt files up to date, and it can generate them from a requirements.in file.

pip install pip-tools
pip-compile requirements.in
pip-sync

pdm

pdm is a modern Python package and dependency manager supporting the latest PEP standards.

pipx install pdm
pdm init
pdm add requests
pdm install
pdm list
pdm remove requests

hatch

hatch is a modern project manager for Python that aims to provide a unified solution for managing project environments, dependencies, and releases.

pipx install hatch
hatch new my_project
cd my_project
hatch env create
hatch run python -m my_project
hatch build

conda

conda is an open-source package management and environment management system that runs on Windows, macOS, and Linux. It quickly installs, runs, and updates packages and their dependencies.

conda create --name myenv
conda activate myenv
conda install numpy
conda list
conda remove numpy
conda deactivate

More Options