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Find your Python dependency manager

Compare Python dependency managers by locking behavior, virtual environment workflow, packaging support, and fit for scientific or application projects.

Find your Python dependency manager

Compare Python dependency managers by locking behavior, virtual environment workflow, packaging support, and fit for scientific or application projects.

Showing 10 of 10 vendors that match

1st

pip + requirements.txt

The baseline Python installer and requirements file workflow built into almost every Python environment.

Free

Free open-source tooling; operational cost is the manual process around it.

  • Universal compatibility with Python hosting, CI, and containers
  • Simple enough for small scripts and legacy projects
  • Works well as an output format from other tools
  • Plain requirements files are not a resolver lock format
  • Virtual environments, builds, and publishing require separate tools
  • Dependency grouping is convention-driven rather than first-class
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2nd

pip-tools (pip-compile)

A focused resolver that compiles abstract requirements into pinned requirements files for repeatable installs.

Free

Free open-source CLI tools.

  • Produces familiar requirements.txt-style lock outputs
  • Easy to adopt incrementally in existing pip workflows
  • Good fit for applications that deploy from requirements files
  • Environment creation remains external
  • Not a full project manager or publishing workflow
  • Locks are usually generated per target environment
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3rd

Poetry

A mature Python project manager with dependency resolution, virtualenvs, packaging, publishing, and a dedicated lock file.

Free

Free open-source CLI.

  • Strong all-in-one workflow for apps and libraries
  • First-class dependency groups and virtualenv management
  • Large ecosystem familiarity and documentation
  • Resolver and install speed can lag newer Rust-based tools
  • Poetry-specific conventions still matter in many projects
  • Can be heavier than needed for small scripts or simple services
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4th

PDM

A standards-oriented Python project manager centered on pyproject.toml, PEP 621 metadata, lock files, and flexible environment workflows.

Free

Free open-source CLI.

  • Strong standards alignment around pyproject.toml and PEP 621
  • Supports dependency groups, locking, and publishing
  • Good choice for teams that want modern metadata without Poetry conventions
  • Smaller mindshare than Poetry and pip
  • Some workflows require understanding PDM-specific lock strategies
  • Not aimed at Conda-style binary scientific stacks
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5th

Hatch

A Python project manager from the PyPA ecosystem focused on packaging, environments, build backends, and release workflows.

Free

Free open-source CLI and build backend.

  • Excellent for library authors, build matrices, and publishing
  • Uses modern PEP 621 project metadata
  • Environment management is flexible and scriptable
  • Not primarily a lockfile-first dependency manager
  • Application deployment workflows often need another resolver strategy
  • More packaging-oriented than beginner-oriented
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6th

Pipenv

An application-focused Python workflow that combines pip, virtualenv, Pipfile, and Pipfile.lock.

Free

Free open-source CLI.

  • Simple app-centric workflow with automatic virtualenvs
  • Pipfile.lock gives better repeatability than loose requirements
  • Still useful for teams already standardized on Pipenv
  • Less momentum than Poetry, PDM, and uv
  • Not a strong library build and publish tool
  • Pipfile metadata is outside the modern PEP 621 mainstream
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7th

uv (Astral)

A Rust-based Python package and project manager designed to replace pip, pip-tools, virtualenv, pipx, and parts of Poetry-style workflows.

Free

Free open-source CLI from Astral.

  • Very fast installs and resolution with a universal lockfile
  • Covers projects, scripts, Python versions, tools, builds, and publishing
  • Strong fit for modern service and monorepo workflows
  • Newer than pip, Poetry, and Conda in conservative environments
  • Some teams may need migration time from established lock formats
  • Does not replace Conda for non-Python scientific binaries
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8th

Conda/Miniconda

A cross-language package and environment manager widely used for data science, native libraries, and Python stacks with binary dependencies.

Free

Miniconda and conda are free to use; review channel licensing and enterprise repository requirements.

  • Strongest option here for scientific packages and native dependencies
  • Manages Python, system libraries, and non-Python packages together
  • Common in notebooks, ML, HPC, and data engineering environments
  • Python packaging and PyPI publishing are not the main workflow
  • Environment files are not the same as deterministic lockfiles without add-ons
  • Can be heavier than needed for web services or libraries
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9th

Rye

A Rust-based Python project workflow that influenced uv and is now best treated as a migration path toward uv.

Free

Free open-source CLI; Astral recommends uv for new work.

  • Fast, modern workflow with pyproject.toml-based projects
  • Includes Python toolchain and virtualenv management
  • Reasonable for existing Rye projects migrating gradually
  • Not the best default for new projects now that uv has absorbed the direction
  • Smaller future ecosystem than uv
  • Conda-style scientific binary management is out of scope
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10th

micromamba

A small, fast Conda-compatible environment manager for reproducible scientific and container workflows.

Free

Free open-source CLI; package channel terms still matter.

  • Fast Conda-compatible environment creation with a small footprint
  • Excellent for containers, CI images, and data science stacks
  • Handles native scientific packages better than pure PyPI tooling
  • Not a PyPI project publishing workflow
  • Locking usually depends on companion tools such as conda-lock
  • Less natural for ordinary Python application dependency groups
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About this comparison

Compare pip with requirements.txt, pip-tools, Poetry, PDM, Hatch, Pipenv, uv, Conda, Rye, and micromamba for Python dependency management. Filter by lockfile support, built-in virtual environments, package build and publishing workflows, dependency groups, Rust-fast installs, PEP 621 metadata, multi-platform locks, and Conda ecosystem support.