Introduction¶
Welcome to Alpenglow introduction!
Alpenglow is an open source recommender systems research framework, aimed at providing tools for rapid prototyping and evaluation of algorithms for streaming recommendation tasks.
The framework is composed of a large number of components written in C++ and a thin python API for combining them into reusable experiments, thus enabling ease of use and fast execution at the same time. The framework also provides a number of preconfigured experiments in the alpenglow.experiments
package and various tools for evaluation, hyperparameter search, etc.
Requirements¶
Anaconda environment with Python >= 3.5
Installing¶
conda install -c conda-forge alpenglow
In case you also intend to run sample code and tutorials, you should install matplotlib as well:
conda install matplotlib
If you encounter any conflict or error, try installing Alpenglow in a clean conda environment.
Installing from source on Linux¶
cd Alpenglow
conda install libgcc sip
conda install -c conda-forge eigen
pip install .
Development¶
For faster recompilation, use
export CC=”ccache cc”
To enable compilation on 4 threads for example, use
echo 4 > .parallel
Reinstall modified version using
pip install --upgrade --force-reinstall --no-deps .
To build and use in the current folder,
use pip install --upgrade --force-reinstall --no-deps -e .
andexport PYTHONPATH=”$(pwd)/python:$PYTHONPATH”