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Reorganize tags on benchmarks

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#210 2 則留言 1 個 reaction 已指派 0 人 在 GitHub 檢視

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評估

難度
5/5
預估耗時
一週以上
新手友好度
25/100
Issue 類型
功能
描述清晰度
需要釐清
活躍度
停滯
技術堆疊
python
領域
performance

研究方向

先檢視 issue 208,接著調查現有 benchmark 標籤的使用位置,以及變更這些標籤是否會影響其他消費者。完成的標準是就標籤分類體系達成共識,包括提議的 workload、feature 和 web 標籤,並記錄任何變更的影響。

由索引模型根據 Issue 內容生成。

描述

Once https://github.com/python/pyperformance/issues/208 is complete, we will probably want to reorganize the benchmarks into tags so that they are more useful and meaningful. This issue can hopefully provide a place for discussion.

Most importantly: Are there other places where the tags are used such that changing them would be an issue? How can I identify these folks other than posting here?

The currently assigned tags are:

apps: {'2to3', 'tornado_http', 'html5lib', 'chameleon'}
math: {'pidigits', 'float', 'nbody'}
regex: {'regex_v8', 'regex_compile', 'regex_effbot', 'regex_dna'}
serialize: {'xml_etree_generate', 'pickle_dict', 'json_dumps', 'unpickle_pure_python', 'unpickle', 'xml_etree_process', 'json_loads', 'pickle', 'xml_etree_parse', 'pickle_list', 'xml_etree_iterparse', 'unpickle_list', 'pickle_pure_python'}
startup: {'python_startup_no_site', 'python_startup'}
template: {'genshi_xml', 'mako', 'genshi_text', 'django_template'}

For the most part, I think the existing tags are fine, though apps is perhaps a little vague and perhaps should be removed.

I would propose adding the following tags (each benchmark can have multiple tags):

  • Size:
    • workload: This would be for benchmarks that represent real world workloads. These would roll up into "one big number" that we report in places like the CPython release notes. I'm not crazy about the name of this tag. Suggestions?
    • feature: The opposite of a macrobenchmark, for benchmarks that test a very specific feature.
  • Domain:
    • web: Typical tasks used in server-side web development: for example, serializing/deserializing HTML, JSON, XML, l10n and i18n related things
主要語言
Python
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分支
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平均合併
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30 天內合併 PR
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  3. Fork 儲存庫,在一個分支上完成修改。
  4. 送出 Pull Request,並在描述裡引用這個 Issue 編號。

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