#Zarr

Live, measured metrics for the hashtag #Zarr from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #zarr

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$2,449.80/ year · 4-character #name
Claim #zarr$2,449.80/yr
Annual, renews each year
Buy on hashtag.space (web3)
one-timepay once, yours for life
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 40
1.1
Avg reactions / post
Mastodon · last 40

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 12:44 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

0 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 12:44 UTC

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 12:44 UTC

Everything below is measured over the latest 40 public posts (spanning ~19073 hours).

Posting hours (UTC) — busiest: 12:00

00:0012:0023:00

Languages: English (37) · French (2) · German (1)

Avg boosts / post: 2.2

Top of the latest posts

  • Do you work with Zarr data? The `pizzarr` package has just been published on CRAN! This is an R implementation for creating, reading, and writing chunked Zarr arrays, developed by David Blodgett and Mark Keller. It supports both Zarr V2 & V

    Krzysztof Dyba@krzysztof_dyba11142026-03-26 17:51 UTCView post →
  • made some huge af virtual #Zarr today, each var is 12Tb uncompressed, all referenced to public available netcdf servers but not using netcdf lib at all for read (Reliant on pretty recent #GDAL or #xarray if you want to explore) https://gith

    Michael Sumner@[email protected]472025-09-25 08:21 UTCView post →
  • For large microscopy datasets (e.g. >1 GB): #OMIO can materialize images directly as disk-backed #Zarr stores. This allows #MemoryMapped, slice-wise access w/o loading the entire dataset into RAM. And: It fully integrates with #Napari workf

    Fabrizio Musacchio@[email protected]322026-06-12 15:34 UTCView post →

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/zarr