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Channel
Code Learning
@codelearning_tg
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
9,444subscribers
-31 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1001591786537 |
|---|---|
| Type | Channel |
| Username | @codelearning_tg |
| Description | Практические материалы для улучшения кода, обзоры ошибок и многое другое. Ссылка: @Portal_v_IT Сотрудничество: @oleginc, @tatiana_inc Канал на бирже: telega.in/c/codelearning_tg РКН: clck.ru/3Jb7Pr |
| Created | Between 1 August 2021 and 28 February 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 20 August 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 1 time, most recently 20 August 2026 |
| On Telegram | t.me/codelearning_tg |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 20 Aug 2026, 10:12 | 9,444 | -9 |
| 17 Aug 2026, 19:49 | 9,453 | -3 |
| 14 Aug 2026, 20:18 | 9,456 | -7 |
| 11 Aug 2026, 11:22 | 9,463 | -7 |
| 8 Aug 2026, 02:23 | 9,470 | -5 |
| 7 Aug 2026, 03:17 | 9,475 | first reading |
Engagement
56 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 26 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 3.67%
- avg views ÷ 9,444 subscribers
- Avg views / post
- 347
- 56 posts measured
- Reaction rate
- 0.311%
- reactions ÷ views · ER floor
- Posts in window
- 56
- of 56 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 9 of 56 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 22 August 2026 |
|---|---|
| Posts held | 56 (29 July 2026 – 22 August 2026) |
| Views total | 19,426 |
| Reactions total | 10 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 22 Aug 2026, 18:47 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.
What this channel posts
- Photos
- ≈2,940
- Videos
- ≈1,240
- Links
- ≈4,060
Lifetime counters from Telegram’s own channel header, read 22 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
- Video runtime
- 21m 09s
- Average length
- 44s
Measured directly from 29 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
10 reactions across 8 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 10 | 100.0% |
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 9 of the 56 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 10reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 56 most recent posts we hold, published 29 July 2026 to 22 August 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.
Recent posts
Text to Image Editor — как фотошоп, только с текстом Редактор изображений, который исполняет мечту тех, кто так и не освоил инструменты фотошопа. ⤷ Ознакомиться на сайте CodeLearning & Скачать видео
Figma Weave — генератор всего на свете. В приложение завезли возможность создавать рабочие доски для генерации картинок, видео, 3D-моделей и многого другого Работает почти как ComfyUI, но только онлайн — круто! ⤷ Ознакомиться на сайте CodeLearning & Max
Express — это нейронка для удаления фона и теперь она работает ИДЕАЛЬНО — при этом все ещё бесплатно и прямо в браузере в . Кроме удаления фона там можно: — Убрать или добавить конкретный объект; — Перевести текст на картинке на другой язык с сохранением шрифта; — Заапскейлить изображение; — Если картинка защищена авторским правом — тут же можно сгенерить похожую; — Ещё раз — всё это бесплатно. ⤷ Ознакомиться на с…
HY-World 2.0 — генератор 3D-моделей размером в целый мир. Генерит с текста, фото или видео — закидываете и в один клик получаете модель, которую можно вставить в Unity или в Unreal Engine. При этом мир интерактивный и учитывает физику предметов. ⤷ Ознакомиться на сайте CodeLearning & Max
Codex for (almost) everything — это ChatGPT теперь может РУЛИТЬ вашим компом. Теперь нейронка может управлять почти любыми локальными приложениями — достаточно её об этом попросить. Бонусом идут 90+ готовых плагинов. Пока только для MacOS. ⤷ Ознакомиться на сайте CodeLearning & Max
Edit Banana — это позволяет редактировать текст на любых картинках в пару кликов. — ИИ сегментирует картинку на разные блоки, позволяя редактировать текст; — Идеально работает с таблицами, формулами и диаграммами; — Сохраняет исходные цвета и положения всех блоков — Можно экспортировать в форматы DrawIO, SVG или PowerPoint; — Полностью бесплатно, можно поставить локально с GitHub. ⤷ Ознакомиться на сайте CodeLearn…
Thuki — это бесплатный ИИ-ассистент, который работает полностью офлайн и ускоряет работу над рутиной Вызывается он в один клик и подходит для быстрых задач: переписать или перевести текст, объяснить ошибку в коде, сделать саммари. А чтобы пошагово проанализировать проблему тут есть расширенное мышление 👍 ⤷ Ознакомиться на сайте CodeLearning & Max
АЙТИШНИКИ БЕСПЛАТНОЕ ОБУЧЕНИЕ Проект «Terminal» стал крупнейшей библиотекой бесплатного образования. В одном канале собраны курсы, книги, полезные инструменты и практические тренажёры для всех разработчиков: • Практические курсы и задания • Книги и статьи известных авторов • Полезные инструменты и ресурсы • IT-новости и инсайды Обучение по всем направлениям: SQL, Python, ML, Frontend, PHP, C++, Go, Git, Linux, QA,…
👍1
Kimi K2.6 — это опенсорсная ИИ-модель. — SOTA сразу нескольких бенчмарков: SWE-Bench Pro, Multilingual; — Более того, по ряду бенчмарков опережает и закрытые GPT-5.4, Claude Opus 4.6 и Gemini 3.1 Pro. — Долгие задачи теперь реально долгие: может пахать до 12 часов работы; — Можно запускать до 300 сабагентов в одной задаче; ⤷ Ознакомиться на сайте CodeLearning & Max
👍2
Уже очевидно, что ВАЙБКОДИНГ — главный навык ближайших лет Посмотрите сами. ИИ уже забирает на себя работу целых команд: пишет код, закрывает задачи джунов и позволяет стартапам запускать продукты в 2–3 раза меньшим составом. То, на что раньше нужны были несколько разработчиков, сегодня всё чаще делает один человек с ИИ-агентами. И это только начало. Те, кто освоит вайбкодинг сейчас, смогут быстрее запускать проект…
GPT-Image 2 — это генератор изображений и его не отличить от реальности. Новая модель способна генерить что угодно: реалистичные интерфейсы приложений, игр, рекламу, фотографии газет и рукописного текста — всё это будет выглядеть так, как будто вы сделали скриншот. ⤷ Ознакомиться на сайте CodeLearning & Max
Showing the 12 most recent of 56 posts we hold for @codelearning_tg. 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.
Citation-graph rank
Citation-graph rank — 1,002,270 of 1,583,249entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Names
Channels on the register whose handles appear in this channel's posts.
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 · 152,669
Telegram ranks this channel #56 of 87 here — alongside 86 others — read 12 August 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 20 August 2026 — this entry's latest reading, not the date you are reading this.
“Code Learning” (@codelearning_tg), 9,444 subscribers as measured 20 August 2026. Telegram Register, tgregister.com/channel/codelearning_tg.
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.