Benchmarks#

The pyarrow package comes with a suite of benchmarks meant to run with ASV. You’ll need to install the asv package first (pip install asv or conda install -c conda-forge asv).

Running the benchmarks#

To run the benchmarks for a locally-built Arrow, run asv dev or asv run --python=same.

We use conda environments as part of running the benchmarks. To use the asv setup, you must set the $CONDA_HOME environment variable to point to the root of your conda installation.

Running for arbitrary Git revisions#

ASV allows to store results and generate graphs of the benchmarks over the project’s evolution. You need to have the latest development version of ASV:

pip install git+https://github.com/airspeed-velocity/asv

Now you should be ready to run asv run or whatever other command suits your needs. Note that this can be quite long, as each Arrow needs to be rebuilt for each Git revision you’re running the benchmarks for.

Compatibility#

We only expect the benchmarking setup to work on a Unix-like system with bash.