#NetCDF4
Live, measured metrics for the hashtag #NetCDF4 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #netcdf4
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 12:39 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 12:39 UTCNo related tags with measured usage found for #netcdf4.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 12:39 UTCEverything below is measured over the latest 8 public posts (spanning ~18776 hours).
Posting hours (UTC)
Languages: English (7) · German (1)
Avg boosts / post: 0.3
Top of the latest posts
For post-processed data though, I think #NetCDF4 is the best format with its multiple structured and indexed array data fields which can have arbitrary metadata attached and work flawlessly with #Python's #xarray package: https://xarray.dev
@thfriedrich I benchmarked the different compression algorithms in #HDF5 once if you're interested: https://gitlab.com/-/snippets/2043808 With the metric I use there (distance to optimum 'fast and small'), blosc:lz4 is the best compromise.
@thfriedrich Also, I've had problems with #NetCDF4 bindings not being thread-safe, so I couldn't parallelize operations very well. With compressed CSV, just throw threads (or processes) onto the problem. Files just work, no weird library in
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/netcdf4