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base repository: aio-libs/yarl
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base: v1.4.1
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head repository: aio-libs/yarl
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compare: v1.4.2
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- 7 commits
- 9 files changed
- 3 contributors
Commits on Dec 1, 2019
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Commits on Dec 2, 2019
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Bumps [mypy](https://github.com/python/mypy) from 0.740 to 0.750. - [Release notes](https://github.com/python/mypy/releases) - [Commits](python/mypy@v0.740...v0.750) Signed-off-by: dependabot-preview[bot] <support@dependabot.com>
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* Setup towncrier * Fix CI * Fix CI * Drop extra lines
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Commits on Dec 3, 2019
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Bump sphinx from 2.2.1 to 2.2.2
Bumps [sphinx](https://github.com/sphinx-doc/sphinx) from 2.2.1 to 2.2.2. - [Release notes](https://github.com/sphinx-doc/sphinx/releases) - [Changelog](https://github.com/sphinx-doc/sphinx/blob/master/CHANGES) - [Commits](sphinx-doc/sphinx@v2.2.1...v2.2.2) Signed-off-by: dependabot-preview[bot] <support@dependabot.com>
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Commits on Dec 4, 2019
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Workaround for missing str.isascii() in Python 3.6 (#389)
* Workaround for missing str.isascii() in Python 3.6 This would allow for checking if `host` contains only ASCII characters with Python 3.6 and 3.5. Performance tests with `%timeit` in `ipython` on Python 3.6 show that this check takes about 0.18 μs, if the first character in `host` is non-ASCII. 0.87 μs if the 10th character is the first non-ASCII character and 1.46 μs if the 20th character is non-ASCII. The times are about the same, if `host` is purely ASCII and 1, 10 or 20 characters long, respectively. While this is quite a bit slower than `str.isascii()` on Python 3.8 on the same machine (about 0.038 μs, independ of length or position of the characters) it is about 25 times faster than running IDNA encoding needlessly: for 20 characters `idna.encode(host, uts46=True).decode("ascii")` takes about 40 μs if `host` is ASCII. If some unicode character is found, the added time is negligible in comparison to the time needed for encoding: on 20 characters it takes 64 μs if one character is Unicode and about 85 - 150 μs if it contains only Unicode characters (There seems to be quite a spread depending on the characters used). So about 0.1 - 2.3 % more time, depending on where the first Unicode character is placed and how many there ares. * Do lexical comparison Lexical comparison of two single letter strings ("characters") looks to be faster than first calling `ord()` on the character and doing a numerical comparison.
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