This started life as a post on this discussion about a Numpy pull-request that others (on the Numpy mailing list thread) suggested might have used AI.
The comment generated a very high level of objection, particularly from Robert Kern, who felt (I agree) that the AI-generated text was of low-quality and misleading. Others felt the comment was rude, I think to the PR author, presumably because
Please read AGENTS.md
I've reviewed AGENTS.md. I'm now familiar with NumPy's development workflows, including the use of meson and spin, the 88-character line length limit, the requirement for import numpy as np, and the specific commit message prefixes. I'm ready for your instructions.
Please check out and analyze the pull-request at
| #!/usr/bin/env python3 | |
| """ Write non-outlier corresponding points from Adelaide RMF datasets | |
| The datasets appear to be based at | |
| `https://www.ai4space.group/research/adelaidermf`_ - but the links there are | |
| broken (I've emailed the first contact listed on that page). | |
| In the meantime, I found what appear to be the data files at `data/AdelaideRMF` in | |
| `https://github.com/trungtpham/RCMSA`_. |
| #!/usr/bin/env python3 | |
| """ Calculate and apply optimal scale and shift to subtitle times | |
| Takes CSV of form: | |
| text,video_time,srt_time | |
| tranquilo,0:01:25,00:01:21.5 | |
| ya_empezo_el_abuso,00:34:59.5,00:36:23 | |
| ignacio,00:59:27.5,01:01:54.2 | |
| tengo_que_llevar,1:20:30.5,01:23:51.2 |
| #!/usr/bin/env python3 | |
| """ Convert Github notebook URL to NBGitPuller URL | |
| See: https://nbgitpuller.readthedocs.io/en/latest/link.html | |
| """ | |
| from argparse import ArgumentParser, RawDescriptionHelpFormatter | |
| from warnings import warn | |
| from urllib.parse import urlparse |
| #!/usr/bin/env python3 | |
| from pathlib import Path | |
| import zipfile | |
| from argparse import ArgumentParser, RawDescriptionHelpFormatter | |
| def unpack_zip(zip_path, out_dir): | |
| out_path = out_dir / zip_path.stem |
| name | |
| HEUNG YUEN RESTAURANT | |
| ILLY CAFFE SF_PIER 39 | |
| AMICI'S EAST COAST PIZZERIA | |
| LOCAL CATERING | |
| OUI OUI! MACARON | |
| Hula Truck (#2) | |
| GENKI CREPES & MINI MART | |
| UNCLE LEE CAFE | |
| Twirl and Dip |
| #!/usr/bin/env python3 | |
| """ Process .py file with nosetests assert_true etc for pytest | |
| It does a fairly crude (regexp) job of taking lines nosetests lines like:: | |
| yield assert_true, 1 == 2 | |
| and replacing them with:: | |
| assert 1 == 2 |
| #!/usr/bin/env python3 | |
| """Process attendance data | |
| Start by downloading an attendance sheet in HTML or Excel format. | |
| You can download attendance data using the ".." icon in the Attendance | |
| interface. | |
| Download in Excel format using the "Download Excel" option. |
| #!/usr/bin/env python3 | |
| """Print URL for multi-user teams chat | |
| Start by downloading an attendance sheet in HTML using the ".." icon in the | |
| Attendance interface, and selecting "View Attendance Sheet". This will give | |
| you an HTML file download. Note the filename. Then run this program, passing | |
| the filename of the downloaded file. It will print out a URL you can paste | |
| into your browser. If you do, your browser will open Teams with a chat ready | |
| to fill out, and all the people listed anywhere on the attendance sheet added | |
| (regardless of whether they attended or not). |