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django-asv
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Benchmarks for Django using asv
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django-asv
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# **Django ASV** This repository contains the benchmarks for measuring Django's performance over time. The benchmarking process is carried out by the benchmarking tool [airspeed velocity](https://asv.readthedocs.io/en/stable/) and the results can be viewed [here](https://django.github.io/django-asv/) ## **Running the benchmarks** --- ### **If you have installed Anaconda or miniconda** `Conda` is being used to run the benchmarks against different versions of python If you already have conda or miniconda installed,you can run the benchmarks by using the commands ``` pip install asv asv run ``` to run the benchmarks against the latest commit. ### **If you have not installed Anaconda or miniconda** If you do not have conda or miniconda installed, change the contents of the file `asv.conf.json` as follows to use `virutalenv` to run the benchmarks ```json { "version": 1, "project": "Django", "project_url": "https://www.djangoproject.com/", "repo": "https://github.com/django/django.git", "branches": ["main"], "environment_type": "virtualenv", "show_commit_url": "http://github.com/django/django/commit/", } ``` and run the benchmarks using the commands ``` pip install asv asv run ``` **Note**: `ASV` prompts you to set a machine name on the first run, please do not set it to 'ubuntu-22.04', 'windows-2022' or 'macos-12' as the results for the machines with these names are currently being stored in the repository ## **Comparing Benchmarks Results Of Different Commits Or Branches** --- Benchmarking results of differnt branches can be compared using the following method ``` asv run <commit1 SHA or branch1 name> asv run <commit2 SHA or branch2 name> asv compare <commit1 SHA or branch name> <commit2 SHA or branch name> ``` ## **Writing New Benchmarks And Contributing** --- - Fork this repository and create a new branch - Install `pre-commit` and run `pre-commit install` to install pre-commit hooks which will be used to format the code - Create a new directory with the name `benchmark_name` under the appropriate category of benchmarks - Add the files `__init__.py` and `benchmark.py` to the directory - Add the directory to the list of `INSTALLLED_APPS` in settings.py - Use the following format to write your benchmark in the file `benchmark.py` ```python from ...utils import bench_setup() class BenchmarkClass: def setup(): bench_setup() # if your benchmark makes use of models then use # bench_setup(migrate=True) ... def time_benchmark_name(): ... ``` - Commit changes and create a pull request
