Python: 3.7 and later
pytest: any recent version
pip install pytest-codspeed
Creating benchmarks with pytest-codspeed
is compatible with the standard pytest-benchmark
API. So if you already have benchmarks written with it, you can start using pytest-codspeed
right away.
pytest.mark.benchmark
import pytest
from statistics import median
@pytest.mark.benchmark
def test_median_performance():
return median([1, 2, 3, 4, 5])
benchmark
fixtureimport pytest
from statistics import mean
def test_mean_performance(benchmark):
# Precompute some data useful for the benchmark but that should not be
# included in the benchmark time
data = [1, 2, 3, 4, 5]
# Benchmark the execution of the function
benchmark(lambda: mean(data))
def test_mean_and_median_performance(benchmark):
# Precompute some data useful for the benchmark but that should not be
# included in the benchmark time
data = [1, 2, 3, 4, 5]
# Benchmark the execution of the function:
# The `@benchmark` decorator will automatically call the function and
# measure its execution
@benchmark
def bench():
mean(data)
median(data)
If you want to run only the benchmarks tests locally, you can use the --codspeed
pytest flag:
pytest tests/ --codspeed
Note: Running
pytest-codspeed
locally will not produce any performance reporting. It's only useful for making sure that your benchmarks are working as expected. If you want to get performance reporting, you should run the benchmarks in your CI.
You can use the CodSpeedHQ/action to run the benchmarks in Github Actions and upload the results to CodSpeed.
Example workflow:
name: benchmarks
on:
push:
branches:
- "main" # or "master"
pull_request:
jobs:
benchmarks:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v3
with:
python-version: "3.9"
- name: Install dependencies
run: pip install -r requirements.txt
- name: Run benchmarks
uses: CodSpeedHQ/action@v2
with:
token: ${{ secrets.CODSPEED_TOKEN }}
run: pytest tests/ --codspeed