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|---|---|
| From | Roy Smith <roy@panix.com> |
| Newsgroups | comp.lang.python |
| Subject | pyflakes best practices? |
| Date | Thu, 29 May 2014 20:13:41 -0400 |
| Organization | PANIX Public Access Internet and UNIX, NYC |
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We've recently started using pyflakes. The results seem to be similar to most tools of this genre. It found a few real problems. It generated a lot of noise about things which weren't really wrong, but were easy to fix (mostly, unused imports), and a few plain old false positives which have no easy "fix" (in the sense of, things I can change which will make pyflakes STFU). So, what's the best practice here? How do people deal with the false positives? Is there some way to annotate the source code to tell pyflakes to ignore something?
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pyflakes best practices? Roy Smith <roy@panix.com> - 2014-05-29 20:13 -0400
Re: pyflakes best practices? Mark Lawrence <breamoreboy@yahoo.co.uk> - 2014-05-30 01:50 +0100
Re: pyflakes best practices? Roy Smith <roy@panix.com> - 2014-05-29 21:14 -0400
Re: pyflakes best practices? Mark Lawrence <breamoreboy@yahoo.co.uk> - 2014-05-31 18:10 +0100
Re: pyflakes best practices? Roland Koebler <r.koebler@yahoo.de> - 2014-06-04 17:35 +0200
Re: pyflakes best practices? Miki Tebeka <miki.tebeka@gmail.com> - 2014-06-04 22:12 -0700
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