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License

A valid Kodo license is required if you wish to use this project.

Please request a license by filling out the license request form.

Kodo is available under a research- and education-friendly license, you can see the details here.

If you try to configure without a valid license, then you will get an error!

About

kodo-python contains a set of high-level Python bindings for the Kodo Network Coding C++ library. The bindings provide access to basic functionality provided by Kodo, such as encoding and decoding data. The examples folder contains sample applications showing the usage of the Python API.

Buildbot status

If you have any questions or suggestions about this library, please contact us at our developer mailing list (hosted at Google Groups):

Requirements

First of all, follow this Getting Started guide to install the basic tools required for the compilation (C++11 compiler, Git, Python).

The compilers used by Steinwurf are listed at the bottom of the buildbot page.

Linux

These steps may not work with your specific Linux distribution, but they may guide you in the right direction.

First, acquire the required packages from your package management system:

sudo apt-get update
sudo apt-get install python build-essential libpython-dev python-dev

If you are using Python 3, you'll need to install libpython3-dev instead.

Mac OSX

Install the latest XCode and Command Line Tools from the Mac Store.

Python 2.7 is pre-installed on OSX, and the required Python headers should also be available. If you are having trouble with the pre-installed Python version, then you can install a more recent Python version with MacPorts or Homebrew.

Windows

Install Python 2.7 (32-bit) and Visual Studio Express 2015 for Windows Desktop. Then set the VS90COMNTOOLS environment variable to:

C:\Program Files (x86)\Microsoft Visual Studio 14.0\Common7\Tools\

so that Python distutils can detect your new compiler.

Building From Source

It is recommended to build the Python bindings from source.

First, clone the project:

git clone [email protected]:steinwurf/kodo-python.git

Configure and build the project:

cd kodo-python
python waf configure
python waf build

After building the project, you should find the resulting kodo.so, kodo.dylib or kodo.pyd file here (the actual path and extension depend on your OS):

build/linux/src/kodo_python/kodo.so
build/darwin/src/kodo_python/kodo.dylib
build/win32/src/kodo_python/kodo.pyd

You can copy this file to the same folder as your Python scripts, or you can copy it to your PYTHONPATH (so that you can import it from anywhere).

Then you can import the module in your Python script:

>>> import kodo

Special Options

With the enable_codecs option, you can configure kodo-python to only enable some desired codecs and disable all others. For example:

python waf configure --enable_codecs=full_vector

Run python waf --help to list the available codecs. You can even select multiple codecs with a comma-separated list:

python waf configure --enable_codecs=full_vector,on_the_fly,nocode

Compilation Issues on Linux

The compilation process might take a long time on certain Linux systems if less than 4 GB RAM is available. The g++ optimizer might consume a lot of RAM during the compilation, so if you see that all your RAM is used up, then it is recommended to constrain the number of parallel jobs to one during the build step:

python waf build -j 1

With this change, a fast compilation is possible with 2 GB RAM.

This issue is specific to g++ (which is the default compiler on Linux), but the RAM usage and the compilation time can be much better with clang. The code produced by clang is also fast.

If the compilation does not work with g++, then you can install clang like this (on Ubuntu and Debian):

sudo apt-get install clang-3.5

Then you should configure the project with the appropriate mkspec. Use the following command on 32-bit Linux:

python waf configure --cxx_mkspec=cxx_clang35_x86

Or use this one on 64-bit Linux:

python waf configure --cxx_mkspec=cxx_clang35_x64

Compiling on the Raspberry Pi

The detailed instructions for compiling the project on the Raspberry Pi are found in our Raspberry guide.

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  • C++ 72.8%
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