python

Python interface to the Apache Arrow-based Feather File Format

Feather efficiently stores pandas DataFrame objects on disk.

Build

Building Feather requires a C++11 compiler. We've simplified the PyPI packaging to include libfeather (the C++ core library) to be built statically as part of the Python extension build, but this may change in the future.

Static builds for easier packaging

At the moment, the libfeather sources are being built and linked with the Cython extension, rather than building the libfeather shared library and linking to that.

While we continue to do this, building from source requires you to symlink (or copy) the C++ sources. See:

# Symlink the C++ library for the static build
ln -s ../cpp/src src
python setup.py build

# To install it locally
python setup.py install

# Source distribution
python setup.py sdist

To change this and instead link to an installed libfeather.so, look in setup.py and make the following change:

FEATHER_STATIC_BUILD = False

Limitations

Some features of pandas are not supported in Feather:

• Non-string column names
• Row indexes
• Object-type columns with non-homogeneous data

Mac notes

Anaconda uses a default 10.5 deployment target which does not have C++11 properly available. This can be fixed by setting:

export MACOSX_DEPLOYMENT_TARGET=10.10