Some notes on building a conda recipe

Datetime:2016-08-22 22:27:43          Topic: Python  Git           Share

I’ve spent the day building a conda recipe, the process wasn’t super-smooth, hopefully these notes will help others and/or maybe you can leave me a comment to improve my flow. The goal was to learn how to use conda to distribute a package that ordinarily I’d put on PyPI .

I’m using Linux 64bit (Mint 18 on an XPS 9550), conda 4.1 and conda build 1.21.14 (up to date as of today). My goal was to build a recipe ( python_template_with_config_recipe ) to install my python_template_with_config (a bit of boilerplate code I use sometimes when making a new project). That template has two modules, a test, a and it depends on numpy.

The short story:

  1. git clone
  2. cd inside, run “conda build –debug .”
  3. # note the period means “current directory” and that’s two dashes debug
  4. a local bzip will be built and  you’ll see that the 1 test ran ok

On my machine the built code ends up in “~/anaconda3/pkgs/python_template_with_config-0.1-py35_0/lib/python3.5/site-packages/python_template_with_config” and the building takes place in “~/anaconda3/conda-bld/linux-64”.

In a new conda environment I can use “conda install –use-local python_template_with_config” and it’ll install the built recipe into the new environment.

To get started with this I first made a fresh empty conda environment (note that anaconda isn’t my default Python, hence the long-form access to `conda`):

  1. $ ~/anaconda3/bin/conda create -n new_recipe_env python=3.5
  2. $ . ~/anaconda3/bin/activate new_recipe_env

To check that my existing “” runs I use pip to install from git, we’ll need the in the conda recipe later so we want to confirm that it works:

  • $ pip install git+ # runs
  • # $ pip uninstall python_template_with_config # use this if you need to uninstall whilst developing

I can check that this has installed as a module using:

In [1]: from python_template_with_config import another_module
In [2]: another_module.a_math_function() 
# silly function just to check that numpy is installed
Out[2]: -2.4492935982947064e-16

Now I’ll make a second conda environment to develop the recipe:

  1. $ ~/anaconda3/bin/conda create -n new_recipe_env2 python=3.5 # vanilla environment, no numpy
  2. $ . ~/anaconda3/bin/activate new_recipe_env2
  3. git clone
  4. cd inside, run "conda build --debug ."

The recipe (meta.yaml) will look at the git repo for python_template_with_config, pull down a copy, build using and the store a bzip2 archive locally. The build step also notes that I can upload this to Anaconda using `$ anaconda upload /home/ian/anaconda3/conda-bld/linux-64/python_template_with_config-0.1-py35_0.tar.bz2`.

A few caveats occurred whilst creating the recipe:

  • You need a bld.bat,, meta.yaml, at first I created and meta.yml (both typos) and there were no complaints…just frustration on my part – the first clue was seeing “source tree  in: /home/ian/anaconda3/conda-bld/work \n number of files: 0” in the build output
  • When running conda build it seems to not overwrite the version in ~/anaconda3/pkgs/ – I ended up deleting “python_template_with_config-0.1-py35_0/” and “python_template_with_config-0.1-py35_0.tar.bz2” by hand just to make sure on each build iteration – I must be missing something here, please enlighten me
  • Having deleted the cached versions and fixed the typos I’d later see “number of files: 14”
  • Later I added “” rather than “”, I knew it wasn’t running as I’d added a “1/0” line inside that obviously wasn’t running (it should raise a ZeroDivisionError even if the tests did run ok). Again this was a typo on my part
  • The above is tested on Linux, it ought to work on Windows but I’ve not tested it
  • This meta.yaml installs from github, there’s a commented out line in there showing how to access the local source files instead

I didn’t get as far as uploading this to Anaconda to make it ‘public’ (as I don’t think that’s so useful) but I believe that final step is easy enough.

Useful docs:

Ian applies Data Science as an AI/Data Scientist for companies inModelInsight, sign-up for Data Science tutorials in London . Historically Ian ran Mor Consulting . He also founded the image and text annotation API , co-authored SocialTies , programs Python, authored The Screencasting Handbook

, lives in London and is a consumer of fine coffees.

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