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Building conda packages with conda skeleton

This tutorial describes how to quickly build a conda package for a Python module that is already available on PyPI.

In the first procedure, building a simple package, you build a package that can be installed in any conda environment of the same Python version as your root environment. The remaining optional procedures describe how to build packages for other Python versions and other architectures, as well as how to upload packages to your account.

Who is this for?

This tutorial is for Windows, macOS and Linux users who wish to build a conda package from a PyPI package. No prior knowledge of conda build or conda recipes is required.

Before you start

Before you start, check the :doc:`prerequisites <index>`.

Building a simple package with conda skeleton pypi

The conda skeleton command picks up the PyPI package metadata and prepares the conda build recipe. The final step is to build the package itself and install it into your conda environment.

It is easy to build a skeleton recipe for any Python package that is hosted on PyPI, the official third-party software repository for the Python programming language.

In this section you are going to use conda skeleton to generate a conda recipe, which informs conda build about where the source files are located and how to build and install the package.

You'll be working with a package named Pyinstrument that is hosted on PyPI. Pyinstrument is a Python statistical profiler that records the whole call stack once each millisecond, so programmers can see which parts of their code are slowest and how to make them faster.

First, in your user home directory, run the conda skeleton command:

conda skeleton pypi pyinstrument

The two arguments to conda skeleton are the hosting location, in this case pypi, and the name of the package.

This creates a directory named Pyinstrument and creates the skeleton file, meta.yaml in that directory. Download the other two skeleton files: :download:` <>` , :download:`bld.bat <bld.bat>`. Save these files in the same pyinstrument directory where the meta.yaml file is present. Use the ls command on macOS or Linux or the dir command on Windows to verify that these files have been created. The three files have been populated with information from the PyPI metadata and in most cases will not need to be edited.

These three files are collectively referred to as the "conda build recipe":

  • meta.yaml---Contains all the metadata in the recipe. Only the package name and package version sections are required---everything else is optional.
  • bld.bat---Windows commands to build the package.
  • and Linux commands to build the package.

Now that you have the conda build recipe ready, you can use conda build to create the package:

conda-build pyinstrument

When conda build is finished, it displays the exact path and filename of the conda package. See :ref:`troubleshooting` if the conda-build command fails.

Windows example file path:


macOS example file path:


Linux example file path:


NOTE: Your path and filename will vary depending on your installation and operating system. Save the path and filename information for the next step.

Now you can install your newly-built package in your conda environment by using the use-local flag:

conda install --use-local pyinstrument

Now verify that Pyinstrument installed successfully:

conda list

At this point you now have a conda package for pyinstrument that can be installed in any conda environment of the same Python version as your root environment. The remaining optional sections show you how to make packages for other Python versions, other architectures and how to upload them to your account.

Optional---Building for a different Python version

By default, conda build creates packages for the version of Python installed in the root environment. To build packages for other versions of Python, you use the --python flag, followed by a version. For example, to explicitly build a version of the Pyinstrument package for Python 3.3, use:

conda-build --python 3.3 pyinstrument

Notice that the file printed at the end of the conda-build output has changed to reflect the requested version of Python. conda install will look in the package directory for the file that matches your current Python version.

Windows example file path:


macOS example file path:


Linux example file path:


NOTE: Your path and filename will vary depending on your installation and operating system. Save the path and filename information for the next task.

Optional---Converting conda package for other platforms

Now that you have built a package for your current platform with conda build, you can convert it for use on other platforms with the conda convert command and a platform specifier from this list:

  • osx-64.
  • linux-32.
  • linux-64.
  • win-32.
  • win-64.
  • all.

In the output directory, 1 folder will be created for each of the 1 or more platforms you chose, and each folder will contain a .tar.bz2 package file for that platform.


conda convert -f --platform all C:\Users\jsmith\Miniconda\conda-bld\win-64\pyinstrument-0.13.1-py27_0.tar.bz2
-o outputdir\

macOS and Linux:

conda convert --platform all /home/jsmith/miniconda/conda-bld/linux-64/pyinstrument-0.13.1-py27_0.tar.bz2
-o outputdir/

NOTE: Change your path and filename to the exact path and filename you saved in :ref:`python-versions`.

To use these packages, you need to transfer them to other computers and place them in the correct conda-bld/$ARCH directory for the platform, where $ARCH can be osx-64, linux-32, linux-64, win-32 or win-64.

A simpler way is to upload all of the bz2 files to as described in the next task.

Optional---Uploading packages to, formerly known as, is a repository for public or private packages. Uploading to allows you to easily install your package in any environment with just the conda install command, rather than manually copying or moving the tarball file from one location to another. You can choose to make your files public or private. For more information about, see the documentation.

  1. Create a free account and record your new username and password.
  2. Run conda install anaconda-client and enter your username and password.
  3. Log into your account from your Terminal or an Anaconda Prompt with the command anaconda login.

Now you can upload the new local packages to


anaconda upload C:\Users\jsmith\Miniconda\conda-bld\win-64\pyinstrument-0.13.1-py27_0.tar.bz2

macOS and Linux:

anaconda upload /home/jsmith/miniconda/conda-bld/linux-64/pyinstrument-0.13.1-py27_0.tar.bz2

NOTE: Change your path and filename to the exact path and filename you saved in :ref:`python-versions`. Your path and filename will vary depending on your installation and operating system.

If you created packages for multiple versions of Python or used conda convert to make packages for each supported architecture, you must use the anaconda upload command to upload each one. It is considered best practice to create packages for Python versions 2.7, 3.4 and 3.5 along with all of the architectures.

TIP: If you want to always automatically upload a successful build to, run:

conda config --set anaconda_upload yes

You can log out of your account with the command:

anaconda logout

Troubleshooting a sample issue

Conda build may produce the error message "Build Package missing."

To explore this error:

  1. Create a conda skeleton package for skyfield. The conda skeleton command is:

    conda skeleton pypi skyfield

    This command creates the skyfield conda build recipe.

  2. Run conda-build skyfield and observe that it fails with the following output:

    Removing old build environment
    Removing old work directory
    BUILD START: skyfield-0.8-py35_0
    Using Anaconda Cloud api site
    Fetching package metadata: ......
    Solving package specifications: .
    Error:  Package missing in current osx-64 channels:
      - sgp4 >=1.4

In this example, the conda recipe requires sgp4 for the skyfield package. The skyfield recipe was created by conda skeleton. This error means that conda could not find the spg4 package and install it.

Since many PyPI packages depend on other PyPI packages to build or run, the solution is sometimes as simple as using conda skeleton to create a conda recipe for the missing package and then building it:

conda skeleton sgp4
conda build sgp4

You may also try using the --recursive flag with conda skeleton, but this makes conda recipes for all required packages, even those that are already available to conda install.

Working Around MITM Proxies

Some corporate environments use proxy services that use Man-In-The-Middle (MITM) attacks to sniff encrypted traffic. These services can interfere with SSL connections such as those used by conda and pip to download packages from repositories such as PyPI.

If you encounter this interference, you should set up the proxy service's certificates so that the requests package used by conda can recognize and use the certificates.

For cases where this is not possible, conda-build versions 3.0.31 and higher have an option that disables SSL certificate verification and allows this traffic to continue:


More information

For more options, see the full :doc:`conda skeleton command documentation <../../commands>`.