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ASV Memray Benchmark Plugin documentation
=========================================
``asv_bench_memray`` is an externally defined ``memray`` benchmark plugin for
:doc:`asv <asv:index>` using :doc:`asv_runner <asv_runner:index>`.
.. toctree::
:maxdepth: 2
:caption: Contents:
development
apidocs/index
Usage
=====
In your ``asv.conf.json`` add the following to the requirements matrix:
.. code:: json
"matrix": {
"req": {
"numpy": ["1.21"],
"asv_plugin_memray": [""]
},
},
This should be enough for an example like the following to run:
.. code:: python
import numpy as np
class MyBenchmark:
params = [10, int(2e4)]
def ray_sum(self, n):
self.data = np.random.rand(n)
np.sum(self.data)
Which should result in something roughly like:
.. code:: sh
ASV_RUNNER_PATH="../asv_runner" asv run --bench sum
· Creating environments.......
· Discovering benchmarks
·· Uninstalling from virtualenv-py3.9-asv_bench_memray.._asv_bench_memray-numpy1.21
·· Building 30a650cb <main> for virtualenv-py3.9-asv_bench_memray.._asv_bench_memray-numpy1.21.
·· Installing 30a650cb <main> into virtualenv-py3.9-asv_bench_memray.._asv_bench_memray-numpy1.21
· Running 1 total benchmarks (1 commits * 1 environments * 1 benchmarks)
[ 0.00%] · For project commit 30a650cb <main>:
[ 0.00%] ·· Benchmarking virtualenv-py3.9-asv_bench_memray.._asv_bench_memray-numpy1.21
[100.00%] ··· benchmarks.MyBenchmark.ray_sum ok
[100.00%] ··· ======== =======
param1
-------- -------
10 1.72k
20000 162k
======== =======
ASV_RUNNER_PATH="../asv_runner" asv run --bench sum 8.72s user 3.04s system 99% cpu 11.877 total
.. note::
The GitHub repository at `asv_samples
<https://github.com/HaoZeke/asv_samples>`_ has a dedicated branch for
testing ``asv_bench_memray``.
License
-------
MIT.
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
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