mirror of
https://github.com/django-components/django-components.git
synced 2025-07-07 17:34:59 +00:00
f36581ed86
* feat: add benchmarking dashboard, CI hook on PR, and store lifetime results * refactor: change python env to 3.13 in benchmarks * refactor: add verbosity, use 3.11 for benchmarking * fix: OSError: [Errno 7] Argument list too long * refactor: add debug statements * refactor: remove extraneous -e * refactor: fix tests and linter errors * fix: track main package in coverage * refactor: fix test coverage testing * refactor: fix repo owner name in benchmark on pushing comment * refactor: add asv monkeypatch to docs workflow * refactor: temporarily allow building docs in forks * refactor: use py 3.13 for benchmarking * refactor: run only a single benchmark for PRs to speed them up * refactor: install asv in the docs build workflow * refactor: use hatch docs env to generate benhcmarks in docs CI * refactor: more trying * refactor: move tests * Add benchmark results for 0.137 * Trigger Build * Add benchmark results for 0.138 * refactor: set constant machine name when benchmarking * Add benchmark results for 0.139 * refactor: fix issue with paths too long * Add benchmark results for 0.140 * docs: update comment * refactor: remove test benchmarking data * refactor: fix comment * refactor: allow the benchmark workflow to write to PRs * refactor: use personal access token to set up the PR benchmark bot * refactor: split the benchmark PR flow into two to make it work with PRs from forks * refactor: update deprecated actions/upload-artifact@v3 to v4 * refactor: fix missing directory in benchmarking workflow * refactor: fix triggering of second workflow * refactor: fix workflow finally? * docs: add comments to cut-offs and direct people to benchmarks PR --------- Co-authored-by: github-actions <github-actions@github.com>
99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
import os
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import sys
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from importlib.abc import Loader
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from importlib.util import spec_from_loader, module_from_spec
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from types import ModuleType
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from typing import Any, Dict, List, Optional
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# NOTE: benchmark_name constraints:
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# - MUST BE UNIQUE
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# - MUST NOT CONTAIN `-`
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# - MUST START WITH `time_`, `mem_`, `peakmem_`
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# See https://github.com/airspeed-velocity/asv/pull/1470
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def benchmark(
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*,
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pretty_name: Optional[str] = None,
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timeout: Optional[int] = None,
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group_name: Optional[str] = None,
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params: Optional[Dict[str, List[Any]]] = None,
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number: Optional[int] = None,
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min_run_count: Optional[int] = None,
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include_in_quick_benchmark: bool = False,
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**kwargs,
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):
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def decorator(func):
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# For pull requests, we want to run benchmarks only for a subset of tests,
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# because the full set of tests takes about 10 minutes to run (5 min per commit).
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# This is done by setting DJC_BENCHMARK_QUICK=1 in the environment.
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if os.getenv("DJC_BENCHMARK_QUICK") and not include_in_quick_benchmark:
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# By setting the benchmark name to something that does NOT start with
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# valid prefixes like `time_`, `mem_`, or `peakmem_`, this function will be ignored by asv.
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func.benchmark_name = "noop"
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return func
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# "group_name" is our custom field, which we actually convert to asv's "benchmark_name"
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if group_name is not None:
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benchmark_name = f"{group_name}.{func.__name__}"
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func.benchmark_name = benchmark_name
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# Also "params" is custom, so we normalize it to "params" and "param_names"
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if params is not None:
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func.params, func.param_names = list(params.values()), list(params.keys())
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if pretty_name is not None:
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func.pretty_name = pretty_name
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if timeout is not None:
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func.timeout = timeout
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if number is not None:
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func.number = number
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if min_run_count is not None:
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func.min_run_count = min_run_count
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# Additional, untyped kwargs
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for k, v in kwargs.items():
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setattr(func, k, v)
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return func
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return decorator
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class VirtualModuleLoader(Loader):
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def __init__(self, code_string):
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self.code_string = code_string
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def exec_module(self, module):
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exec(self.code_string, module.__dict__)
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def create_virtual_module(name: str, code_string: str, file_path: str) -> ModuleType:
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"""
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To avoid the headaches of importing the tested code from another diretory,
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we create a "virtual" module that we can import from anywhere.
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E.g.
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```py
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from benchmarks.utils import create_virtual_module
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create_virtual_module("my_module", "print('Hello, world!')", __file__)
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# Now you can import my_module from anywhere
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import my_module
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```
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"""
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# Create the module specification
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spec = spec_from_loader(name, VirtualModuleLoader(code_string))
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# Create the module
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module = module_from_spec(spec) # type: ignore[arg-type]
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module.__file__ = file_path
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module.__name__ = name
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# Add it to sys.modules
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sys.modules[name] = module
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# Execute the module
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spec.loader.exec_module(module) # type: ignore[union-attr]
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return module
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