Continuum Analytics: Documentation

# Building conda packages with conda skeleton

## Overview

In this tutorial you will learn how to quickly build a conda package for a Python module that is already available on PyPi. The conda skeleton command will pick up the PyPi package metadata and prepare the conda build recipe. The final step is to build the package itself and install it into your conda environment.

## Who is this for?

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

### Conda build summary

Building a conda package from a PyPi package can be done in two steps. Three additional steps can be performed if you wish to install the package in conda environment with a different version of Python or on a different architecture.

1. Before you start
2. Build a simple package with conda skeleton pypi
3. Optional - Build for a different Python version
4. Optional - Convert conda package for other platforms
5. Optional - Upload packages to Anaconda.org
6. Troubleshooting
7. Additional Information

## Before you start

You should already have installed Miniconda or Anaconda.

Install conda-build:

    conda install conda-build

It is recommended that you use the latest versions of conda and conda-build. To upgrade both packages run:

    conda upgrade conda
    conda upgrade conda-build

Now you are ready to start building your own conda packages.

## Build a simple package with conda skeleton pypi

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 three skeleton files in that directory: meta.yaml, build.sh, and bld.bat. Use the `ls` command on OS X 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.

> build.sh: Linux and OS X commands to build the package.

Now that you have the conda build recipe ready, you can use the conda-build tool to create the package.

    conda build pyinstrument

When conda-build is finished, it displays the exact path and filename of the conda package. See the Troubleshooting section if the conda-build command fails.

Windows example file path:

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

OS X example file path:

    /Users/jsmith/miniconda/conda-bld/osx-64/pyinstrument-0.13.1-py27_0.tar.bz2

Linux example file path:

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

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 will show you how to make packages for other Python versions, other architectures and how to upload them to your Anaconda.org account.

## Optional - Build for a different Python version

By default, conda-build will build 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

You’ll 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:

    C:\Users\jsmith\Miniconda\conda-bld\win-64\pyinstrument-0.13.1-py33_0.tar.bz2

OS X example file path:

    /Users/jsmith/miniconda/conda-bld/osx-64/pyinstrument-0.13.1-py33_0.tar.bz2

Linux example file path:

    /home/jsmith/miniconda/conda-bld/linux-64/pyinstrument-0.13.1-py33_0.tar.bz2

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

## Optional - Convert 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 the list {osx-64,linux-32,linux-64,win-32,win-64,all}. In the output directory, one folder will be created for each of the one or more platforms you chose, and each folder will contain a .tar.bz2 package file for that platform.

Windows users:

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

Linux and OS X users:

    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 Step 2.

In order to use these packages they will have to be transferred to other computers and placed in the correct `conda-bld/$ARCH` directory as shown above, where `$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 Anaconda.org as described in the next section.

## Optional - Upload packages to Anaconda.org

Anaconda.org, formerly known as binstar.org, is a repository for public or private packages. Uploading to Anaconda.org 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 info about Anaconda.org visit the Anaconda.org documentation page.

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

Now you can upload the new local packages to Anaconda.org

Windows users:

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

Linux and OS X users:

    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 Step 2. 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 they will each have to be uploaded using the anaconda upload command. 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 Anaconda.org, run:

    conda config --set anaconda_upload yes

You can log out of your Anaconda.org account with the command:

    anaconda logout

For more information about Anaconda.org, see the Anaconda.org documentation page.

## Troubleshooting

There are a number of things that can go wrong when using conda skeleton and conda-build to build conda packages from PyPi packages. This section explains just a few of the most common errors and how you can correct them.

### A. Build Package missing

Conda build may produce the following error that it couldn’t find a package. Let’s try to make a conda skeleton package for Skyfield. The `conda skeleton` command is

    conda skeleton pypi skyfield

This command will create the Skyfield conda build recipe. Running `conda build skyfield` will fail with the following output.

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

In this example sgp4 is required by my conda recipe for the package named skyfield. The skyfield recipe was created by conda skeleton. This error means that conda could not find spg package and install it.

Since many PyPi packages depend on other PyPi packages to build or run the solution is sometimes as simple as first creating a conda recipe for some-package using conda skeleton and then building it.

    conda skeleton sgp4
    conda build sgp4

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

## Additional Information

See the full conda skeleton documentation for more options.