Conda packages

What is a conda package?

A conda package is a compressed tarball file (.tar.bz2) or .conda file that contains:

  • system-level libraries

  • Python or other modules

  • executable programs and other components

  • metadata under the info/ directory

  • a collection of files that are installed directly into an install prefix

Conda keeps track of the dependencies between packages and platforms. The conda package format is identical across platforms and operating systems.

Only files, including symbolic links, are part of a conda package. Directories are not included. Directories are created and removed as needed, but you cannot create an empty directory from the tar archive directly.

.conda file format

The .conda file format was introduced in conda 4.7 as a more compact, and thus faster, alternative to a tarball.

The .conda file format consists of an outer, uncompressed ZIP-format container, with two inner compressed .tar files.

For the .conda format's initial internal compression format support, we chose Zstandard (zstd). The actual compression format used does not matter, as long as the format is supported by libarchive. The compression format may change in the future as more advanced compression algorithms are developed and no change to the .conda format is necessary. Only an updated libarchive would be required to add a new compression format to .conda files.

These compressed files can be significantly smaller than their bzip2 equivalents. In addition, they decompress much more quickly. .conda is the preferred file format to use where available, although we continue to provide .tar.bz2 files in tandem.

Read more about the introduction of the .conda file format.


In conda 4.7 and later, you cannot use package names that end in “.conda” as they conflict with the .conda file format for packages.

Using packages

  • You may search for packages

conda search scipy
  • You may install a package

conda install scipy
conda build my_fun_package

Package structure

├── bin
│   └── pyflakes
├── info
│   ├── LICENSE.txt
│   ├── files
│   ├── index.json
│   ├── paths.json
│   └── recipe
└── lib
    └── python3.5
  • bin contains relevant binaries for the package

  • lib contains the relevant library files (eg. the .py files)

  • info contains package metadata

Noarch packages

Noarch packages are packages that are not architecture specific and therefore only have to be built once. Noarch packages are either generic or Python. Noarch generic packages allow users to distribute docs, datasets, and source code in conda packages. Noarch Python packages are described below.

Declaring these packages as noarch in the build section of the meta.yaml reduces shared CI resources. Therefore, all packages that qualify to be noarch packages should be declared as such.

Noarch Python

The noarch: python directive in the build section makes pure-Python packages that only need to be built once.

Noarch Python packages cut down on the overhead of building multiple different pure Python packages on different architectures and Python versions by sorting out platform and Python version-specific differences at install time.

In order to qualify as a noarch Python package, all of the following criteria must be fulfilled:

  • No compiled extensions

  • No post-link or pre-link or pre-unlink scripts

  • No OS-specific build scripts

  • No python version specific requirements

  • No skips except for Python version. If the recipe is py3 only, remove skip statement and add version constraint on Python in host and run section.

  • 2to3 is not used

  • Scripts argument in is not used

  • If console_script entrypoints are in, they are listed in meta.yaml

  • No activate scripts

  • Not a dependency of conda


While noarch: python does not work with selectors, it does work with version constraints. skip: True  # [py2k] can sometimes be replaced with a constrained Python version in the host and run subsections, for example: python >=3 instead of just python.


Only console_script entry points have to be listed in meta.yaml. Other entry points do not conflict with noarch and therefore do not require extra treatment.

Read more about conda's noarch packages.

More information

Go deeper on how to manage packages. Learn more about package metadata, repository structure and index, and package match specifications at Package specifications.