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 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.