#numpydoc
Live, measured metrics for the hashtag #numpydoc from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #numpydoc
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Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-10-17 18:43 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-10-17 18:43 UTCNo related tags with measured usage found for #numpydoc.
Live pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-10-17 18:43 UTCEverything below is measured over the latest 5 public posts (spanning ~9470 hours).
Posting hours (UTC)
Languages: English (5)
Avg boosts / post: 0
Used together with
Top of the latest posts
Ok, I think this is strictly a numpydoc feature that involves the use of their built in xref's which sphinx.ext.napoleon does not have access to. #sphinx #numpydoc
Looking at the docstrings for numpy, they appear to use the same style of annotations: ``` range : (float, float) The lower and upper range of the bins. ``` Suppose I should take a closer look at their conf.py and see if there is magic ther
#sphinx #numpydoc folks, I have a question. When specifying a parameter ``` """ ... levels : (float, float) description. ... “”” ``` sphinx is givingm e warnings: WARNING: py:class reference target not found (float [ref.class] WARNING: py:c
#numpydoc across platforms
every network with a public tag surfaceFollow #numpydoc straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/numpydoc