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Dependency Management in Python

Python offers several methods for specifying project dependencies, each suited for different use cases:

1. requirements.txt

The traditional and simplest approach:

requests==2.28.1
numpy>=1.20.0
pandas~=1.5.0
  • Uses pip's format with version specifiers (==, >=, ~=, !=)
  • Common convention: requirements.txt for production, requirements-dev.txt for development dependencies
  • Installed via pip install -r requirements.txt

2. setup.py / setup.cfg

For creating installable packages:

setup(
    name="mypackage",
    install_requires=[
        "requests>=2.20.0",
        "numpy",
    ],
    extras_require={
        "dev": ["pytest", "black"],
    }
)
  • Defines both package metadata and dependencies
  • Supports optional dependency groups via extras_require
  • Used when distributing packages to PyPI

3. pyproject.toml

The modern, standardized approach (PEP 518, 621):

[project]
dependencies = [
    "requests>=2.20.0",
    "numpy>=1.20",
]

[project.optional-dependencies]
dev = ["pytest", "black"]
  • Unified configuration file for build systems and tools
  • Replaces setup.py for many use cases
  • Supported by modern tools like Poetry, Flit, and pip

4. Pipfile / Pipfile.lock

Used by Pipenv:

[packages]
requests = "*"

[dev-packages]
pytest = "*"
  • Separates abstract dependencies (Pipfile) from concrete locked versions (Pipfile.lock)
  • Provides deterministic builds via lock file

5. poetry.lock / pyproject.toml

Poetry's approach combines both:

  • Dependencies specified in pyproject.toml
  • Exact versions locked in poetry.lock
  • Handles dependency resolution automatically

6. Conda environment.yml

For conda environments:

dependencies:
  - python=3.9
  - numpy
  - pip:
    - requests
  • Can specify both conda and pip packages
  • Useful for scientific computing with non-Python dependencies

Common Version Specifiers

  • ==2.0.0 - exact version
  • >=1.5.0 - minimum version
  • ~=1.5.0 - compatible release (>=1.5.0, <1.6.0)
  • >=1.0,<2.0 - version range

Current trend: The ecosystem is moving toward pyproject.toml as the standard for all Python projects, with lock files (Poetry, PDM, or pip-tools) for reproducible environments.