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Channel

Кодим на Коленке | Уроки по программированию

@code_on_tg

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry

9,011subscribers

-37 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-1001641747805
TypeChannel
Username@code_on_tg
DescriptionАйти и точка. Ссылка: @Portal_v_IT Сотрудничество: @oleginc, @tatiana_inc Канал на бирже: telega.in/c/code_on_tg РКН: clck.ru/3Jb7JX
CreatedBetween 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live26 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 26 August 2026
On Telegramt.me/code_on_tg

Growth

9,0119,0489,029.57 August 2026 — 9,048 subscribers7 August 2026 — 9,046 subscribers10 August 2026 — 9,043 subscribers14 August 2026 — 9,038 subscribers17 August 2026 — 9,029 subscribers20 August 2026 — 9,019 subscribers23 August 2026 — 9,016 subscribers26 August 2026 — 9,011 subscribers7 August 202626 August 2026
8 measurements spanning 19 days, net -37. 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 9,005–9,054 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
26 Aug 2026, 06:189,011-5
23 Aug 2026, 14:589,016-3
20 Aug 2026, 03:069,019-10
17 Aug 2026, 12:059,029-9
14 Aug 2026, 10:349,038-5
10 Aug 2026, 19:159,043-3
7 Aug 2026, 16:549,046-2
7 Aug 2026, 03:179,048first reading

Engagement

73 posts held, back to 29 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 35 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.99%
avg views ÷ 9,011 subscribers
Avg views / post
269
71 posts measured
Reaction rate
0.525%
reactions ÷ views · ER floor
Posts in window
71
of 73 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 71 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 28 August 2026
Posts held73 (29 July 202628 August 2026)
Views total19,128
Reactions total14
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 15:40 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
3,210
Videos
17
Links
2,740

Lifetime counters from Telegram’s own channel header, read 28 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
42s
Average length
21s

Measured directly from 2 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

14 reactions across 9 posts, in 5 distinct kinds. The most used accounts for 28.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍428.6%
😁428.6%
321.4%
🔥214.3%
👏17.14%

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 73 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 14reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 73 most recent posts we hold, published 29 July 2026 to 28 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

28 Aug 2026, 11:22 UTC112 viewsread 28 August 2026
Photo

Делаем нейросеть с нуля Как бы вас не запугивали, нейросети писать не сложно и можно сделать это даже в 90 строк кода. Достаточно просто хорошо разбираться в математике. Автор рассказывает про принципы работы нейронных сетей и создаёт проекты на их основе. Например, определение числа на основе пикселей. Подробнее: 👉 тут #видео #ai ⬇️ Скачать видео Кодим на Коленке

28 Aug 2026, 10:36 UTC60 viewsread 28 August 2026
Forwarded from @aliexpress_prgPhoto

📣Универсальный держатель Цена: ~1300₽ Рейтинг: 5😀 Отзывы: 119 💬 🖱 Заказать Универсальный регулируемый держатель для планшета или телефона, поможет удобно разместить устройство на кровати или столе, освобождая руки для просмотра видео, чтения, работы и учёбы. #держатель #девайс Больше товаров — Находки Программиста

27 Aug 2026, 16:12 UTC184 viewsread 28 August 2026
Photo

Уроки #Android Studio для начинающих Видеоуроки: 1. Создание Андроид приложения (E-Commerce) 2. Дизайн основного окна 3. Категории товаров 4. Основные товары приложения 5. Страница с товаром 6. Переход между страницами с анимацией 7. Сортировка товаров по категориям 8. Добавление в корзину 9. Заключительный урок 🗝 Смотреть курс Кодим на Коленке & Скачать видео

27 Aug 2026, 11:21 UTC193 viewsread 28 August 2026
Photo

Что такое Kubernetes? Контейнеризация проектов — это то, что отлично упрощает перенос проектов на разные устройства, а также позволяет контролировать использование ресурсов. Для работы с контейнерами был придуман Kubernetes. Автор видео подробно рассказал о контейнерах и в общих чертах описал, как ими пользоваться. Подробнее: 👉 тут #видео #devops ⬇️ Скачать видео Кодим на Коленке

27 Aug 2026, 08:36 UTC211 viewsread 28 August 2026

#Вопрос_с_собеседования За что отвечает команда git stash? Ответ: Команда git stash позволяет на время «сдать в архив» (или отложить) изменения, сделанные в рабочей копии, чтобы вы могли применить их позже Кодим на Коленке

26 Aug 2026, 16:10 UTC225 viewsread 28 August 2026
Photo

Нашел 10 репозиториев на GitHub для изучения ИИ-агентов 1. ИИ-агенты для начинающих (Microsoft) — github.com/microsoft/ai-a 2. Бесплатные ресурсы по ИИ-агентам — github.com/avinash201199/ 3. Потрясающие приложения на основе больших языковых моделей — github.com/Shubhamsaboo/a 4. Курс Hugging Face Agents — github.com/huggingface/ag 5. GenAl Agents (учебные материалы + реализации) — github.com/NirDiamant/Gen 6. Потряс

26 Aug 2026, 08:32 UTC220 viewsread 28 August 2026

#Вопрос_с_собеседования Чем отличается энумератор map от each в Ruby? Ответ: each возвращает исходный массив, а . map - новый массив Кодим на Коленке

25 Aug 2026, 16:11 UTC234 viewsread 28 August 2026
Photo

Хватайте 7 репозиториев на GitHub для изучения больших языковых моделей Вам не нужно читать десятки случайных руководств, чтобы разобраться в больших языковых моделях. Эти 7 проектов на GitHub помогут вам пройти путь от основ трансформеров до самостоятельного создания и обучения языковых моделей. 1. Создание больших языковых моделей с нуля — Себастьян Рашка → Пошаговое создание большой языковой модели с помощью Py

25 Aug 2026, 11:15 UTC243 viewsread 28 August 2026
Photo

Учебный курс «Язык SQL» В этом курсе вы без предварительной подготовки сможете разобраться, что представляет собой система баз данных PostgreSQL, и научиться с ней работать. Начиная с разработки простых запросов на языке SQL вы постепенно осваиваете более сложные конструкции (такие как общие табличные выражения), знакомитесь с концепцией транзакций и вопросами оптимизации производительности. Учебные примеры использу

Showing the 12 most recent of 73 posts we hold for @code_on_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.

Posts edited after publishing

@code_on_tg edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
26 August 2026
Most recent edit
28 August 2026

Citation-graph rank

Citation-graph rank — 1,564,601 of 1,624,174entries 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

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.

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.

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 26 August 2026 — this entry's latest reading, not the date you are reading this.

“Кодим на Коленке | Уроки по программированию” (@code_on_tg), 9,011 subscribers as measured 26 August 2026. Telegram Register, tgregister.com/channel/code_on_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.