github: issues: 1 row where comments = 0, "created_at" is on date 2023-10-25 and user = 14371165 sorted by updated

1 row where comments = 0, "created_at" is on date 2023-10-25 and user = 14371165 sorted by updated_at descending

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id	node_id	number	title	user	state	locked	assignee	milestone	comments	created_at	updated_at ▲	closed_at	author_association	active_lock_reason	draft	pull_request	body	reactions	performed_via_github_app	state_reason	repo	type
1962432308	PR_kwDOAMm_X85dzwDL	8376	Add chunkedduckarray to _typing	Illviljan 14371165	closed	0			0	2023-10-25T23:09:46Z	2023-10-26T19:10:41Z	2023-10-26T01:13:54Z	MEMBER		0	pydata/xarray/pulls/8376	Add more chunkedarray typing options. Also clean up some ideas that didn't work out. Using TypeVar for arrays for example has turned out to not work that great because of the very common dtype changes. If you want to check if an ArrayLike is a chunked array: `python if isinstance(data, _chunkedarrayfunction_or_api): data.chunk()` However try to rely on mypy in private functions over isinstance checks for better performance: `python def _do_compute(data: chunkedduckarray[Any, _DType]) -> duckarray[Any, _DType]: return data.compute()`	{ "url": "https://api.github.com/repos/pydata/xarray/issues/8376/reactions", "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0 }			xarray 13221727	pull

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   [active_lock_reason] TEXT,
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   [reactions] TEXT,
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   [state_reason] TEXT,
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CREATE INDEX [idx_issues_assignee]
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CREATE INDEX [idx_issues_user]
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