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faq/programming.po

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# eric R <[email protected]>, 2018
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# Meng Du <[email protected]>, 2019
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# ppcfish <[email protected]>, 2019
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# Dai Xu <[email protected]>, 2021
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# Freesand Leo <[email protected]>, 2021
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# Dai Xu <[email protected]>, 2021
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#
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#, fuzzy
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msgid ""
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2021-04-29 06:12+0000\n"
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"PO-Revision-Date: 2017-02-16 17:43+0000\n"
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"Last-Translator: Freesand Leo <yuqinju@163.com>, 2021\n"
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"Last-Translator: Dai Xu <daixu61@hotmail.com>, 2021\n"
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"Language-Team: Chinese (China) (https://www.transifex.com/python-doc/teams/5390/zh_CN/)\n"
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"MIME-Version: 1.0\n"
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"Content-Type: text/plain; charset=UTF-8\n"
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"It is highly recommended to have good code coverage (through unit testing or"
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" any other technique) before potentially introducing regressions hidden in "
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"sophisticated optimizations."
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msgstr "强烈建议在可能引入隐藏在复杂优化中的回归之前,要有良好的代码覆盖率(通过单元测试或任何其他技术)。"
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msgstr "强烈建议首先要保证足够高的代码测试覆盖率(通过单元测试或其他技术),因为复杂的优化有可能会导致代码回退。"
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#: ../../faq/programming.rst:1018
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msgid ""
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"That being said, there are many tricks to speed up Python code. Here are "
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"some general principles which go a long way towards reaching acceptable "
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"performance levels:"
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msgstr "话虽如此,加速Python代码有很多技巧。以下是一些可以达到可接受的性能水平的一般原则:"
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msgstr "话虽如此,Python 代码的提速还是有很多技巧的。以下列出了一些普适性的原则,对于让性能达到可接受的水平会有很大帮助: "
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#: ../../faq/programming.rst:1022
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msgid ""
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"Making your algorithms faster (or changing to faster ones) can yield much "
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"larger benefits than trying to sprinkle micro-optimization tricks all over "
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"your code."
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msgstr "使您的算法更快(或更改为更快的算法)可以产生比尝试在代码中使用微优化技巧更大的好处。"
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msgstr "相较于试图对全部代码铺开做微观优化,优化算法(或换用更快的算法)可以产出更大的收益。 "
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#: ../../faq/programming.rst:1026
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msgid ""

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