| Name | pyquickbench JSON |
| Version |
0.2.0
JSON |
| download |
| home_page | |
| Summary | A pure Pyton tool to perform time and accuracy benchmarks |
| upload_time | 2024-03-13 17:34:51 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.7 |
| license | BSD 2-Clause License Copyright (c) 2021, Gabriel Fougeron All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
python
benchmark
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
numpy
matplotlib
tqdm
ipywidgets
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<p align="center">
<a href="https://github.com/gabrielfougeron/pyquickbench"><img alt="pyquickbench" src="https://gabrielfougeron.github.io/pyquickbench/_static/plot_icon.png" width="30%"></a>
</p>
[](https://pypi.org/project/pyquickbench/)
[](https://pypi.org/pypi/pyquickbench/)
[](https://pypi.org/project/pyquickbench/)
[](https://anaconda.org/conda-forge/pyquickbench)
# Pyquickbench
Pyquickbench is an open source, easy to use benchmarking tool written in pure Python. Checkout the [example gallery](https://gabrielfougeron.github.io/pyquickbench/gallery.html) to get an idea of what pyquickbench is capable.
- **Tutorial:** https://gabrielfougeron.github.io/pyquickbench/tutorial.html
- **Documentation:** https://gabrielfougeron.github.io/pyquickbench/
- **Source code:** https://github.com/gabrielfougeron/pyquickbench
- **Bug reports:** https://github.com/gabrielfougeron/pyquickbench/issues
- **Changelog:** https://github.com/gabrielfougeron/pyquickbench/releases/
## Main features
- Timings / repeatability / output benchmarks
- Error handling
- Benchmark results caching
- Multithreaded / multiprocessed benchmarks
- Benchmark timeout
- Multidimensional benchmarks
- Transformed data plotting (relative values, convergence order, ...)
- Intelligent plots
- Sensible defaults
## Installation
Pyquickbench is available on the [Python Package Index](https://pypi.org/project/pyquickbench/). To install using pip, simply type:
```
pip install pyquickbench
```
Pyquickbench is available on [conda-forge](https://anaconda.org/conda-forge/pyquickbench). To install using conda, simply type:
```
conda install pyquickbench -c conda-forge
```
To install the current development version of pyquickbench from the [github repository](https://github.com/gabrielfougeron/pyquickbench), you can type:
```
pip install git+ssh://git@github.com/gabrielfougeron/pyquickbench.git
```
## Tests
To run tests locally on your machine, first checkout this reposity and install dependencies using pip:
```
git clone git@github.com:gabrielfougeron/pyquickbench.git
cd pyquickbench
pip install .[tests]
```
Then, run tests using [pytest](https://docs.pytest.org/en/latest/):
```
pytest
```
## License
This software is published under the [BSD 2-Clause License](https://github.com/gabrielfougeron/pyquickbench/blob/main/LICENSE).
## Other open source alternatives
You might like [perfplot](https://github.com/nschloe/perfplot), one of the inspirations for this work.
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