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https://github.com/CodSpeedHQ/pytest-codspeed

A pytest plugin to create benchmarks
https://github.com/CodSpeedHQ/pytest-codspeed

benchmarking codspeed pytest python

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A pytest plugin to create benchmarks

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pytest-codspeed

[![CI](https://github.com/CodSpeedHQ/pytest-codspeed/actions/workflows/ci.yml/badge.svg)](https://github.com/CodSpeedHQ/pytest-codspeed/actions/workflows/ci.yml)
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[![CodSpeed Badge](https://img.shields.io/endpoint?url=https://codspeed.io/badge.json)](https://codspeed.io/CodSpeedHQ/pytest-codspeed)

Pytest plugin to create CodSpeed benchmarks

---

**Documentation**: https://codspeed.io/docs/reference/pytest-codspeed

---

## Installation

```shell
pip install pytest-codspeed
```

## Usage

### Creating benchmarks

In a nutshell, `pytest-codspeed` offers two approaches to create performance benchmarks that integrate seamlessly with your existing test suite.

Use `@pytest.mark.benchmark` to measure entire test functions automatically:

```python
import pytest
from statistics import median

@pytest.mark.benchmark
def test_median_performance():
input = [1, 2, 3, 4, 5]
output = sum(i**2 for i in input)
assert output == 55
```

Since this measure the entire function, you might want to use the `benchmark` fixture for precise control over what code gets measured:

```python
def test_mean_performance(benchmark):
data = [1, 2, 3, 4, 5]
# Only the function call is measured
result = benchmark(lambda: sum(i**2 for i in data))
assert result == 55
```

Check out the [full documentation](https://codspeed.io/docs/reference/pytest-codspeed) for more details.

### Testing the benchmarks locally

If you want to run the benchmarks tests locally, you can use the `--codspeed` pytest flag:

```sh
$ pytest tests/ --codspeed
============================= test session starts ====================
platform darwin -- Python 3.13.0, pytest-7.4.4, pluggy-1.5.0
codspeed: 3.0.0 (enabled, mode: walltime, timer_resolution: 41.7ns)
rootdir: /home/user/codspeed-test, configfile: pytest.ini
plugins: codspeed-3.0.0
collected 1 items

tests/test_sum_squares.py . [ 100%]

Benchmark Results
┏━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━┓
┃ Benchmark ┃ Time (best) ┃ Rel. StdDev ┃ Run time ┃ Iters ┃
┣━━━━━━━━━━━━━━━━╋━━━━━━━━━━━━━╋━━━━━━━━━━━━━╋━━━━━━━━━━╋━━━━━━━━┫
┃test_sum_squares┃ 1,873ns ┃ 4.8% ┃ 3.00s ┃ 66,930 ┃
┗━━━━━━━━━━━━━━━━┻━━━━━━━━━━━━━┻━━━━━━━━━━━━━┻━━━━━━━━━━┻━━━━━━━━┛
=============================== 1 benchmarked ========================
=============================== 1 passed in 4.12s ====================
```

### Running the benchmarks in your CI

You can use the [CodSpeedHQ/action](https://github.com/CodSpeedHQ/action) to run the benchmarks in Github Actions and upload the results to CodSpeed.

Here is an example of a GitHub Actions workflow that runs the benchmarks and reports the results to CodSpeed on every push to the `main` branch and every pull request:

```yaml
name: CodSpeed

on:
push:
branches:
- "main" # or "master"
pull_request: # required to have reports on PRs
# `workflow_dispatch` allows CodSpeed to trigger backtest
# performance analysis in order to generate initial data.
workflow_dispatch:

jobs:
benchmarks:
name: Run benchmarks
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.13"

- name: Install dependencies
run: pip install -r requirements.txt

- name: Run benchmarks
uses: CodSpeedHQ/action@v3
with:
token: ${{ secrets.CODSPEED_TOKEN }}
run: pytest tests/ --codspeed
```