A cross-platform, language-agnostic package manager created by Anaconda Inc.

Mamba is a reimplementation of the conda package manager in C++.

• parallel downloading of repository data and package files using multi-threading
• libsolv for much faster dependency solving, a state of the art library used in the RPM package manager of Red Hat, Fedora and OpenSUSE
• core parts of mamba are implemented in C++ for maximum efficiency

At the same time, mamba utilize the same command line parser, package installation and deinstallation code and transaction verification routines as conda to stay as compatible as possible.

micromamba is a tiny version of the mamba package manager. It is a pure C++ package with a separate command line interface. It can be used to bootstrap environments (as an alternative to miniconda), but it’s currently experimental. The benefit is that it’s very tiny and does not come with a default version of Python.

micromamba works in the bash & zsh shell on Linux & OS X. It’s completely statically linked, which allows you to drop it in some place and just execute it.

pip is the package installer for Python. You can use it to install packages from the Python Package Index and other indexes.

Poetry helps you declare, manage and install dependencies of Python projects, ensuring you have the right stack everywhere.

Flit is a simple way to put Python packages and modules on PyPI. It tries to require less thought about packaging and help you avoid common mistakes.

A conda tool to work with multiple projects in development mode.

Pipenv harnesses Pipfile, pip, and virtualenv into one single command.

The de facto tool to create conda packages. It creates environments to isolate build-times dependencies and performs checks after compilation to ensure relocatability and correct runtime dependencies.

boa is a package builder for conda packages. It is re-using a lot of the conda-build infrastructure, but replaces some parts. Specifically the solving stage is done using mamba, the fast conda-alternative (implemented in C++ and based on libsolv).

A drop-in replacement for conda-build provided by Boa. It relies on conda-build for most parts, but replaces the solver and the error reports. It provides the conda mambabuild command.

Meson is an open source build system meant to be both extremely fast, and, even more importantly, as user friendly as possible. It can produce Python wheels through the mesonpep517 package.

A simple module that implements PEP517 for the meson build system.

It invokes the PEP 517 hooks to build a distribution package. It is a simple build tool and does not perform any dependency management.

Improved build system generator for CPython C/C++/Fortran/Cython extensions. The scikit-build package is fundamentally just glue between the setuptools Python module and CMake.

Setuptools is a collection of enhancements to the Python distutils library to easily build and distribute Python packages.

The distutils package in the standard library provides support for building and installing additional modules into a Python installation. Most Python users will not want to use this module directly, but enhanced alternatives like setuptools.

This Numpy subpackage provides enhanced distutils functionality to make it easier to build and install sub-packages, auto-generate code, and extension modules that use Fortran-compiled libraries.

Constructor is a tool which allows constructing an installer for a collection of conda packages. It solves needed packages using user-provided specifications, and bundles those packages.

pex is a library for generating .pex (Python EXecutable) files which are executable Python environments in the spirit of virtualenvs. pex is an expansion upon the ideas outlined in PEP 441.

shiv is a command line utility for building fully self contained Python zipapps as outlined in PEP 441, but with all their dependencies included.

PyInstaller freezes (packages) Python applications into stand-alone executables, under Windows, GNU/Linux, Mac OS X, FreeBSD, Solaris and AIX.

conda-pack is a command line tool for creating relocatable archives of conda environments that can be installed on other systems and locations.

Create minimal Docker images from conda environments, without using Docker.

The core philosophy of conda-store is to serve identical conda environments in as many ways as possible. Conda Store controls the environment lifecycle: management, builds, and serving of environments.

This is a command line client that provides an interface to Anaconda Cloud. Primarily used to upload packages to Anaconda.org channels.

A utility for publishing Python packages on PyPI. It provides build system independent uploads of source and binary distribution artifacts for both new and existing projects.

zest.releaser is collection of command-line programs to help you automate the task of releasing a Python project. It updates the version number, populates the changelog, creates the tags and, optionally, publishes to PyPI.

setuptools_scm handles managing your Python package versions in SCM metadata instead of declaring them as the version argument or in a SCM managed file.

This is a tool for managing a recorded version number in distutils-based python projects. The goal is to remove the tedious and error-prone “update the embedded version string” step from your release process. Making a new release should be as easy as recording a new tag in your version-control system, and maybe making new tarballs.

conda-smithy is a tool for combining a conda recipe with configurations to build using freely hosted CI services into a single repository, also known as a feedstock.

A package installed by conda-forge each time a build is run on CI. It normalizes the system settings found on different CI providers for a consistent build configuration across platforms.

The baseline versions of software for the conda-forge ecosystem, essential to maintain ABI compatibility across the channel.

Build Python wheels for all the platforms on CI with minimal configuration.

Machinery for building and testing Python Wheels for Linux, OSX and (less flexibly) Windows.

The conda-skeleton command picks up the PyPI package metadata and prepares an equivalent conda-build recipe you can use to build a conda package.

Create, extract and convert conda packages of various formats.

The Grayskull project was created with the intention to eventually replace the conda skeleton. The main goal of this project is to generate concise recipes for conda-forge.

Press conda packages into wheels. Is allows us to build out a pip-usable package index which is ABI compatible with conda packages.

conda-verify is a tool for (passively) verifying conda recipes and conda packages. The purpose of this verification process is to ensure that recipes don’t contain obvious bugs.

Signing and verification tools for Conda based on The Update Framework

a command line tool to facilitate the creation of Python wheel packages for Linux (containing pre-compiled binary extensions) that are compatible with a wide variety of Linux distributions

Verify installed packages have compatible dependencies.

Find and copy needed dynamic libraries into python wheels on MacOS

Check the contents of your wheel. It will notify you of several common errors & mistakes that can be detected.

This is a little library for mangling Mach-O and PE files in various ways. These are the formats used for executables and shared libraries on MacOS and Windows, respectively.

A small utility to modify the dynamic linker and RPATH of ELF executables.

The purpose of this project is to provide a cross platform library which can parse, modify and abstract ELF, PE and MachO formats.

virtualenv is a tool to create isolated Python environments. Since Python 3.3, a subset of it has been integrated into the standard library under the venv module.

The venv module in the standard library provides support for creating lightweight virtual environments with their own site directories, optionally isolated from system site directories.

virtualenvwrapper is a set of extensions to Ian Bicking’s virtualenv tool. The extensions include wrappers for creating and deleting virtual environments and otherwise managing your development workflow.

Python Env Wrapper is a set of commands to manage multiple virtual environments. Pew can create, delete and copy your environments, using a single command to switch to them wherever you are, while keeping them in a single (configurable) location.

Conda/Mamba/Micromamba are able to handle their own virtual environments through ‘conda env’. They are not compatible with virtualenv-type environments, but they serve the same purpose.

Update package index metadata files (channeldata.json, repodata.json) in directories containing conda packages.

Mirrors an upstream conda channel to a local directory.

The quetz project is an open source server for conda packages. It reimplements Anaconda.org functionalities with an API-first approach.

Warehouse is the software that powers PyPI.

Python PyPi staging server and packaging, testing, release tool

pypiserver is a minimal PyPI compatible server for pip or easy_install. It is based on bottle and serves packages from regular directories.

The ensurepip standard library package provides support for bootstrapping the pip installer into an existing Python installation or virtual environment.

Ensureconda is a CLI tool that will find a preexisting conda/mamba executable, install one if none was found, and return the path of the found/installed location.

A Python package to install Conda (and friends) on live Google Colab instances.

An action to enable the preinstalled Miniconda or download and install Miniconda/Miniforge/Mambaforge on Github Actions workflows.

A GitHub Actions action to create conda environments with micromamba.

The Mamba Navigator, a Web UI for managing conda environments. Provides Conda/Mamba environment and package management as a standalone application or as extension for JupyterLab.

Provides a convenient way to install developer tools in VSCode workspaces from conda-forge with micromamba. Get NodeJS, Go, Rust, Python or JupyterLab installed by running a single command.