This is a Heroku Buildpack for Conda, the Python distribution for scientific computing by Continuum Analytics.
Note: Heroku now recommends using their beta Docker support to achieve similar results.
This buildpack enables the installation of binary packages through the open source conda application. Conda is recognized as being core to Continuum's Anaconda Scientific Python distro but it's also at the heart of the lighter weight Miniconda distro which we use here to install only the binary packages we need for our apps deployed on Heroku.
To control what binary packages are installed by conda, supply a
conda-requirements.txt
file (which can be created by capturing the output
of conda list -e
for your working conda environment).
Like when using the standard buildpack for python from Heroku, you can also
still supply a requirements.txt
file for pip
to process. In this way, you can install binary packages via conda for
everything you can and still use pip for anything you can't.
Usage
Example usage:
$ ls
Procfile conda-requirements.txt numbercrunch.py
$ heroku create --buildpack https://github.com/kennethreitz/conda-buildpack.git
$ git push heroku master
...
-----> Fetching custom git buildpack... done
-----> Python/Miniconda app detected
-----> Preparing Python/Miniconda Environment (3.5.2)
installing: python-2.7.6-2 ...
-----> Installing dependencies using Conda
Fetching packages ...
bitarray-0.8.1 100% |###############################| Time: 0:00:00 17.53 MB/s00 B/s
dateutil-2.1-p 100% |###############################| Time: 0:00:00 2.29 MB/s00 B/s
h5py-2.3.0-np1 100% |###############################| Time: 0:00:00 13.49 MB/s00 B/s
hdf5-1.8.9-1.t 100% |###############################| Time: 0:00:00 12.20 MB/s00 B/s
libpng-1.5.13- 100% |###############################| Time: 0:00:00 8.05 MB/s00 B/s
llvm-3.3-0.tar 100% |###############################| Time: 0:00:03 10.65 MB/s00 B/s
llvmpy-0.12.6- 100% |###############################| Time: 0:00:00 9.65 MB/s00 B/s
nltk-2.0.4-np1 100% |###############################| Time: 0:00:00 6.26 MB/s00 B/s
numba-0.13.2-n 100% |###############################| Time: 0:00:00 11.54 MB/s00 B/s
numexpr-2.3.1- 100% |###############################| Time: 0:00:00 6.80 MB/s00 B/s
numpy-1.8.1-py 100% |###############################| Time: 0:00:00 8.82 MB/s00 B/s
pandas-0.14.0- 100% |###############################| Time: 0:00:00 9.90 MB/s00 B/s
pyside-1.2.1-p 100% |###############################| Time: 0:00:00 6.00 MB/s00 B/s
pytables-3.1.1 100% |###############################| Time: 0:00:00 9.24 MB/s00 B/s
pytz-2014.3-py 100% |###############################| Time: 0:00:00 1.54 MB/s00 B/s
qt-4.8.5-0.tar 100% |###############################| Time: 0:00:01 17.36 MB/s00 B/s
reportlab-3.1. 100% |###############################| Time: 0:00:00 4.87 MB/s00 B/s
scikit-image-0 100% |###############################| Time: 0:00:01 12.81 MB/s00 B/s
scikit-learn-0 100% |###############################| Time: 0:00:00 8.70 MB/s00 B/s
scipy-0.14.0-n 100% |###############################| Time: 0:00:02 15.16 MB/s00 B/s
shiboken-1.2.1 100% |###############################| Time: 0:00:00 3.33 MB/s00 B/s
six-1.6.1-py27 100% |###############################| Time: 0:00:00 12.54 MB/s00 B/s
You can also add it to upcoming builds of an existing application:
$ heroku config:add BUILDPACK_URL=https://github.com/kennethreitz/conda-buildpack.git
Simple test:
>>> bitarray.test()
bitarray is installed in: /app/.heroku/anaconda/lib/python2.7/site-packages/bitarray
bitarray version: 0.8.0
2.7.3 |Continuum Analytics, Inc.| (default, Feb 25 2013, 18:46:31)
[GCC 4.1.2 20080704 (Red Hat 4.1.2-52)]
.................................................................................................................................
----------------------------------------------------------------------
Ran 129 tests in 1.375s
OK
<unittest.runner.TextTestResult run=129 errors=0 failures=0>
Heroku limits the final application footprint (slug) size to 300MB. Start small. In case the slug size limit is exceeded, deleting the build cache through the heroku-repo plugin might help.
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