#rpython
Live, measured metrics for the hashtag #rpython from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #rpython
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.
Day-by-day usage
measured · mastodon.social (Mastodon public tags API) · fetched 2026-10-11 11:35 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.social (Mastodon public search API) · fetched 2026-10-11 11:35 UTCNo related tags with measured usage found for #rpython.
Live pulse
measured · mastodon.social (Mastodon tag timeline) · fetched 2026-10-11 11:35 UTCEverything below is measured over the latest 8 public posts (spanning ~21752 hours).
Posting hours (UTC)
Languages: English (7) · Chinese (Taiwan) (1)
Avg boosts / post: 1.1
Top of the latest posts
New blog post: Which Interpreters are Faster, AST or Bytecode? It gives a high-level overview over our OOPLSA paper, which investigates interpreters on top of metacompilation systems. Will be presented next week at @splashcon. https://stefa
I finally think I've figured out a basic #Nix heap using the #Haskell/#GHC technique of flagging every heap object to detect infinite loops. Cache invalidation really is hard... Fortunately, Nix is pure, so I don't have to invalidate any he
🌗 RPython GC 的分配速度有多快？ ➤ 深入分析 RPython 垃圾回收器的分配效率 ✤ https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html 本文探討了 RPython 垃圾回收器 (GC) 的分配速度。作者透過一個簡單的基準測試程式，測量了在 64 位元架構上分配包含單一整數欄位的物件的效能。測試結果顯示，RPython GC 在沒有初始化欄位的情況下，可以以高達 34.35 GB/s
What “rpython” means
WikipediaPyPy is an implementation of the Python programming language. PyPy frequently runs much faster than the standard implementation CPython because PyPy uses a just-in-time compiler. Most Python code runs well on PyPy except for code that depends on CPython extensions, which either does not work or incurs some overhead when run in PyPy.
“PyPy” on Wikipedia (CC BY-SA) →#rpython across platforms
every network with a public tag surfaceFollow #rpython 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/rpython