Telegram RegisterThe public register of Telegram
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Channel

GitHub Trends

@githubtrending

On this record: Topic · Growth · Engagement · Reactions · Stars · Posts · Citations · Telegram's recommendations · Cite this entry

12,031subscribers

+844 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001080389054
TypeChannel
Username@githubtrending
Created27 November 2016 — measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live11 November 2026
Measurements held65
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/githubtrending

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 99% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.

Growth

11,18712,03111,6096 August 202611 November 2026
65 measurements spanning 98 days, net +844. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 11,060–12,158 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 65
Measured (UTC)SubscribersChange
11 Nov 2026, 21:4012,031+24
10 Nov 2026, 01:2912,007+29
8 Nov 2026, 17:5511,978+21
7 Nov 2026, 12:3111,957+17
6 Nov 2026, 11:4611,940+13
5 Nov 2026, 09:3911,927+7
4 Nov 2026, 10:1911,920+9
3 Nov 2026, 09:3111,911+9
2 Nov 2026, 05:5711,902+14
1 Nov 2026, 09:1011,888+12
31 Oct 2026, 06:1011,876+1
30 Oct 2026, 04:3111,875+4
29 Oct 2026, 06:5811,871+7
28 Oct 2026, 03:2911,864+13
27 Oct 2026, 00:0711,851+12
25 Oct 2026, 20:5911,839+5
24 Oct 2026, 18:2011,834+6
23 Oct 2026, 20:4711,828+3
22 Oct 2026, 23:5611,825+10
21 Oct 2026, 18:4511,815first reading

Engagement

130 posts held, back to 29 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 61 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
4.83%
avg views ÷ 12,031 subscribers
Avg views / post
581
23 posts measured
Reaction rate
0.282%
reactions ÷ views · ER floor
Posts in window
23
of 130 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 22 of 23 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 11 November 2026
Posts held130 (29 July 2026 – 11 November 2026)
Views total13,369
Reactions total37
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 21:02 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Reaction mix

149 reactions across 85 posts, in 8 distinct kinds. The most used accounts for 59.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍8959.7%
❤3926.2%
⚡64.03%
👌53.36%
👎42.68%
🎉21.34%
🔥21.34%
🥰21.34%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 93 of the 130 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 150 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 130 most recent posts we hold, published 29 July 2026 to 11 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Telegram Stars

Stars received
1
across the posts below
Posts paid on
1
of 130 we hold a reading for · 0.8%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @githubtrending. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 130 most recent posts we hold for this entry, published 29 July 2026 to 11 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 23 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

11 Nov 2026, 12:30 UTC231 views1 reactionsread 11 November 2026

#typescript #ai_security #application_security #cli #code_scanning #codex #codex_security #cybersecurity #devsecops #nodejs #npm #openai #sdk #security #typescript #vulnerability_scanning Codex Security helps find, investigate, and fix security weaknesses in code. It can scan entire repositories, selected files, or Git changes, check findings, suggest patches, and verify fixes. It also helps teams assess severity, i…

❤1

11 Nov 2026, 12:00 UTC245 views1 reactionsread 11 November 2026

#other improve is an agent skill that reviews codebases and writes detailed plans for fixing problems or adding features. It checks areas such as security, performance, tests, and documentation, then ranks findings so users can choose what to address. Its plans include context, steps, checks, and limits, making them easier for another agent or a person to follow. It can also send a plan to a cheaper agent, review th…

❤1

11 Nov 2026, 11:30 UTC268 viewsread 11 November 2026

#typescript Modern Web Guidance gives AI coding agents expert guidance on modern web features, browser support, and best practices. It searches and retrieves guides on topics such as layouts, accessibility, performance, and security, and can scan code for outdated patterns. It helps agents use built-in browser features instead of older, more complex solutions, while choosing sensible alternatives for browsers that l…

10 Nov 2026, 11:30 UTC473 views3 reactionsread 11 November 2026

#ruby Sure is a personal finance app that helps people view their cash flow, net worth, and spending in one place. It can also use an AI assistant to answer questions about savings. Users can host Sure themselves and access it through a browser, desktop or mobile app, API clients, and AI agents. It is a community-maintained fork of Maybe Finance. https://github.com/we-promise/sure

👍2❤1

9 Nov 2026, 13:30 UTC584 views1 reactionsread 11 November 2026

#typescript GBrain gives AI agents a shared memory that users can control. It stores facts with their sources, supports corrections, and can search notes and other connected information. Optional features can produce answers with citations, identify gaps in knowledge, and maintain information in the background. This helps agents keep useful context across tasks and makes it easier to find and use stored knowledge. G…

👍1

9 Nov 2026, 13:00 UTC543 views2 reactionsread 11 November 2026

#python #ai #claude #hacs #home_assistant #home_automation #llm #mcp #model_context_protocol HA-MCP connects AI assistants such as Claude and ChatGPT to Home Assistant, letting users manage their smart home through everyday language. It can control devices, create and edit automations, scripts and dashboards, check device history, and help diagnose problems. It also supports backups and safety controls such as read-…

❤1👍1

9 Nov 2026, 12:30 UTC522 views2 reactionsread 11 November 2026

#css #dark_mode #dark_theme #light_theme #obsidian #obsidian_md #obsidian_theme #theme Minimal is a theme for Obsidian on desktop, mobile, and tablet. It lets users change the look of their workspace with color schemes, fonts, background styles, and layout options. Focus mode hides parts of the interface, while image grids, card layouts, and table styles help organize visual content. Companion plugins provide more c…

❤1👍1

8 Nov 2026, 12:30 UTC628 views2 reactionsread 11 November 2026

#kotlin #android #ikev2 #java #kotlin #openvpn #protonvpn #strongswan #vpn ProtonVPN for Android is an open-source VPN app for Android devices. It provides a way to use ProtonVPN on a phone or tablet. Its source code is available under the GPLv3 license, which is useful for people who want to inspect or contribute to the app. https://github.com/ProtonVPN/android-app

❤1👍1

7 Nov 2026, 12:30 UTC706 views2 reactionsread 11 November 2026

#typescript #dsh_plugin billion-context helps AI coding agents manage long conversations by compressing older messages into layered summaries before sending them to a model. The model can search summaries or restore original details when needed. It works with many coding clients and supports Anthropic and OpenAI-style APIs. This can reduce token use and help sessions continue without exceeding the model’s context li…

👍2

7 Nov 2026, 12:00 UTC643 views1 reactionsread 11 November 2026

#go #bare_metal #cluster_api #gpu #kubernetes #nvidia NVIDIA Kubernetes Engine (NVKE) helps platform teams run a managed Kubernetes service on their own NVIDIA GPU infrastructure. It creates separate Kubernetes clusters for customers and helps manage their node pools, upgrades, and node replacements. Customers can use their clusters through standard Kubernetes tools. NVKE makes it easier to provide and operate multi…

👍1

7 Nov 2026, 11:30 UTC636 views1 reactionsread 11 November 2026

#python #coap_protocol #coap_server #custom_component #dtls #hacs #hacs_integration #home_assistant #home_automation #samsung #smartthings LocalThings connects Samsung appliances to Home Assistant over a home network without a cloud account. It supports washers, dryers, refrigerators, air conditioners, ovens and other appliances that work with SmartThings. Depending on the appliance, it provides controls and informa…

👍1

5 Nov 2026, 12:30 UTC794 views5 reactionsread 11 November 2026

#rust agent-browser is a command-line tool that lets AI agents control a web browser one step at a time. It opens pages, presents their contents as compact text, and gives elements references that agents can use to click, fill forms, and perform other actions. The browser stays open between commands, so agents can check results and continue working. It also supports screenshots, downloads, multiple sessions, and bro…

👍3🥰2

Showing the 12 most recent of 130 posts we hold for @githubtrending. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

GitHub repos
@github_repos · 28,145
Telegram ranks this channel #2 of 76 here — alongside 75 others — read 11 September 2026
The Devs
@thedevs · 31,910
Telegram ranks this channel #17 of 82 here — alongside 81 others — read 5 September 2026
Indian Army Navy AirForce Jobs
@indian_army_navy_airforce_jobs · 48,706
Telegram ranks this channel #48 of 70 here — alongside 69 others — read 25 August 2026
Computer Science and Programming
@computer_science_and_programming · 138,623
Telegram ranks this channel #48 of 87 here — alongside 86 others — read 13 August 2026
Web Development
@webde · 31,405
Telegram ranks this channel #56 of 84 here — alongside 83 others — read 5 September 2026
🤖 Coding News ⚡️
@CodingNews · 22,634
Telegram ranks this channel #63 of 68 here — alongside 67 others — read 19 September 2026
Placement Fellas-Off Campus Drives
@placement_fellas · 47,341
Telegram ranks this channel #68 of 79 here — alongside 78 others — read 26 August 2026
Front End World
@front_end_first · 25,604
Telegram ranks this channel #78 of 90 here — alongside 89 others — read 13 September 2026

This channel appears in 8 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 11 November 2026 — this entry's latest reading, not the date you are reading this.

“GitHub Trends” (@githubtrending), 12,031 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/githubtrending.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.