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Channel

Библиотека программиста

@proglibrary

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry

78,288subscribers

+314 since we began measuring on 5 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001039626561
TypeChannel
Username@proglibrary
DescriptionВсе самое полезное для программиста в одном канале. Наши курсы: https://clc.to/Jil6fg По рекламе: @tproger_sales_bot Для обратной связи: @proglibrary_feeedback_bot РКН: https://gosuslugi.ru/snet/67a5ba2901234b69883a4d46 #WXSSA
Created22 March 2016 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live25 September 2026
Measurements held36
Confirmed unchanged1 time, most recently 25 September 2026
On Telegramt.me/proglibrary

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 75% 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 why it has no browse page of its own yet.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@proglibrary/11761 · this entry23 Jul 2026, 09:00 UTC@darkcod/662345 Aug 2026, 12:14 UTC1.0013 days
@proglibrary/11767 · this entry27 Jul 2026, 08:51 UTC@darkcod/662385 Aug 2026, 12:14 UTC1.009 days
@proglibrary/11771 · this entry28 Jul 2026, 10:10 UTC@darkcod/662405 Aug 2026, 12:14 UTC1.008 days
@proglibrary/11773 · this entry30 Jul 2026, 11:02 UTC@darkcod/662425 Aug 2026, 12:14 UTC1.006 days
@proglibrary/11774 · this entry31 Jul 2026, 09:39 UTC@darkcod/662435 Aug 2026, 12:14 UTC1.005 days
@proglibrary/11776 · this entry2 Aug 2026, 11:21 UTC@darkcod/662455 Aug 2026, 12:14 UTC1.003 days
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@darkcod9 (8/8 hand-verifiable sample passed)1.006 daysthis entry (9–0)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.

“Published first” means first in this corpus. We hold 20 comparable posts for this entry, running 23 July 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Across the whole group of 2, the earliest publisher we hold is @proglibrary — which is this entry. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_source, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

77,97478,44778,210.55 August 2026 — 77,974 subscribers6 August 2026 — 77,974 subscribers6 August 2026 — 78,041 subscribers7 August 2026 — 78,052 subscribers8 August 2026 — 78,082 subscribers9 August 2026 — 78,248 subscribers10 August 2026 — 78,273 subscribers11 August 2026 — 78,382 subscribers12 August 2026 — 78,397 subscribers13 August 2026 — 78,377 subscribers14 August 2026 — 78,447 subscribers16 August 2026 — 78,438 subscribers17 August 2026 — 78,442 subscribers18 August 2026 — 78,434 subscribers19 August 2026 — 78,425 subscribers20 August 2026 — 78,414 subscribers22 August 2026 — 78,409 subscribers23 August 2026 — 78,402 subscribers25 August 2026 — 78,404 subscribers26 August 2026 — 78,394 subscribers27 August 2026 — 78,382 subscribers27 August 2026 — 78,372 subscribers28 August 2026 — 78,364 subscribers30 August 2026 — 78,355 subscribers31 August 2026 — 78,344 subscribers1 September 2026 — 78,343 subscribers2 September 2026 — 78,336 subscribers3 September 2026 — 78,321 subscribers5 September 2026 — 78,357 subscribers8 September 2026 — 78,398 subscribers11 September 2026 — 78,401 subscribers13 September 2026 — 78,379 subscribers14 September 2026 — 78,365 subscribers16 September 2026 — 78,341 subscribers18 September 2026 — 78,334 subscribers25 September 2026 — 78,288 subscribers78,2885 August 202625 September 2026
36 measurements spanning 50 days, net +314. 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 77,903–78,518 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)SubscribersChange
25 Sept 2026, 01:3878,288-46
18 Sept 2026, 22:0278,334-7
16 Sept 2026, 12:1878,341-24
14 Sept 2026, 19:4078,365-14
13 Sept 2026, 04:4078,379-22
11 Sept 2026, 08:5878,401+3
8 Sept 2026, 16:3778,398+41
5 Sept 2026, 13:2078,357+36
3 Sept 2026, 12:3678,321-15
2 Sept 2026, 08:2478,336-7
1 Sept 2026, 05:2378,343-1
31 Aug 2026, 02:3478,344-11
30 Aug 2026, 00:2878,355-9
28 Aug 2026, 23:3478,364-8
27 Aug 2026, 23:1778,372-10
27 Aug 2026, 01:5678,382-12
26 Aug 2026, 01:0778,394-10
25 Aug 2026, 02:2978,404+2
23 Aug 2026, 19:3578,402-7
22 Aug 2026, 00:4778,409first reading

Engagement

104 posts held, back to 23 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 117 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
6.40%
avg views ÷ 78,288 subscribers
Avg views / post
5,010
50 posts measured
Reaction rate
1.00%
reactions ÷ views · ER floor
Posts in window
50
of 104 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 49 of 50 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 2 October 2026
Posts held104 (23 July 2026 – 2 October 2026)
Views total250,460
Reactions total2,492
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken2 Oct 2026, 13:58 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
≈4,700
Videos
≈295
Links
≈7,830

Lifetime counters from Telegram’s own channel header, read 2 October 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
11m 23s
Average length
49s

Measured directly from 14 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

5,603 reactions across 99 posts, in 18 distinct kinds. The most used accounts for 20.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1,15820.7%
😁86015.3%
🔥74513.3%
👍58210.4%
🌚2544.53%
👾2434.34%
🤔2434.34%
😢1923.43%
💯1903.39%
🥱1733.09%
👏1462.61%
🎉1402.50%
⚡1222.18%
🥰1182.11%
❤‍🔥1122.00%
😍1122.00%
🙏1122.00%
🤩1011.80%

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 103 of the 104 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 5,814 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 104 most recent posts we hold, published 23 July 2026 to 2 October 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
17
across the posts below
Posts paid on
10
of 104 we hold a reading for · 10%
Most on one post
3
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @proglibrary. 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 104 most recent posts we hold for this entry, published 23 July 2026 to 2 October 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

2 Oct 2026, 11:51 UTC≈1,280 viewsread 2 October 2026
Photo

🎹 Что делать после ChatGPT? Следующий шаг — AI-агенты. Они не просто отвечают на запросы, а сами работают с данными, инструментами и выполняют цепочки действий. На курсе «Разработка ИИ-агентов» разбираем всё, что нужно для этого уровня: ⬇️ RAG и работа с данными ⬇️ MCP и инструменты ⬇️ структурированный вывод ⬇️ контроль качества и стоимости ⬇️ мультиагентные системы ⬇️ AgentOps Курс полностью в записи — проходит…

2 Oct 2026, 05:05 UTC≈2,250 views4 reactionsread 2 October 2026
Photo

Как собрать интерфейс обработки изображений на Gradio Workflow Workflow1111 воссоздаёт большую часть возможностей AUTOMATIC1111 на одном рабочем поле: 11 конвейеров для генерации и редактирования изображений, удаления фона, создания масок, увеличения разрешения и других задач собраны из 73 узлов. Каждый узел оборачивает функцию Python, модель, другой Gradio Space или строку набора данных. Входы и выходы становятся …

❤3👍1

1 Oct 2026, 05:03 UTC≈3,100 views26 reactionsread 2 October 2026
Photo

Как защитить API от повторного выполнения операций Клиент отправил POST, сервер выполнил операцию, но ответ потерялся из-за тайм-аута. Клиент повторяет запрос, и без защиты сервер может второй раз создать ресурс, изменить состояние или отправить письмо. Идемпотентный эндпоинт связывает уникальный ключ операции с отпечатком тела запроса и сохранённым результатом. Первый обработчик атомарно резервирует ключ, поэтому …

👍11🔥4❤3👏2👾2💯1🤔1🥰1

30 Sept 2026, 14:19 UTC≈3,560 views56 reactionsread 2 October 2026
Video

Вот почему оперативная память стоит так дорого 🙄🙄🙄 🐸 Библиотека программиста

😁36👏5🤩4😢4🌚2🔥2❤1👍1

30 Sept 2026, 11:02 UTC≈3,470 views17 reactionsread 2 October 2026
Photo

🔥 Последний день для разработчиков AI уже пишет код. Теперь важнее научиться встраивать его в разработку так, чтобы он действительно экономил время. На курсе «ИИ для разработчиков» собираете AI-workflow на своём проекте: от задачи и планирования до тестов, ревью и PR 🤩 Разберёте AI-агентов, MCP, контекст проекта, безопасность и контроль расходов на модели. 📍 Только сегодня, 30 сентября — скидка 10 000 ₽ Промоко…

❤6😁4👾2💯2🙏2🤔1

30 Sept 2026, 05:04 UTC≈3,500 views24 reactions1 Starread 2 October 2026
Photo

Как спроектировать память ИИ-агента, а не склад контекста Один индекс для диалогов, правил и предпочтений смешивает временные обходы с утверждёнными процедурами: агент помнит всё, но не понимает, чему доверять. Рабочая память хранит состояние задачи, эпизодическая хранит прошлые случаи, семантическая — устойчивые факты, процедурная хранит проверенные действия. Записям нужны тип, источник, уровень уверенности и срок…

😁6❤4👾3🤩3🌚2😍2⚡1👍1

29 Sept 2026, 10:19 UTC≈3,800 views20 reactionsread 2 October 2026
Photo

Кодить — это хорошо, а разбираться в том, что происходит за кадром, тоже полезно. Что там анализируют, зачем нужны метрики, кто такой этот ваш UX, какие задачи решает дизайн? Материалы ниже как раз об этом. Вникать во всё на сто процентов, конечно, не нужно, но базовое понимание поможет находить общий язык с коллегами и видеть чуть дальше кодовой базы. 💵 Как один лотерейный билет превратился в несколько сотен требов…

👍8😢5🎉3🥰3👾1

29 Sept 2026, 09:04 UTC≈3,750 views48 reactionsread 2 October 2026
Photo

🖥 Git ускорили и добавили несколько полезных фишек: 🟡 git add --resolved — безопаснее закрывать merge-конфликты 🟡 поиск merge-base в некоторых репозиториях стал в десятки раз быстрее 🟡 git history drop — удалять коммиты из истории 🟡 массовая очистка уже смерженных веток 🟡 git bisect теперь может сам вернуться после нахождения проблемного коммита 🟡 Git умеет подсказывать очевидные ошибки в командах И это только част…

👍21❤7🔥7👾5🎉2😁2❤‍🔥1🤔1

29 Sept 2026, 05:02 UTC≈3,830 views22 reactionsread 2 October 2026
Photo

Почему Big O недостаточно для выбора структуры данных в C++ Автор создал hashbrowns, набор тестов для массивов, связных списков и хеш-таблиц. В замерах линейный поиск по массиву обгонял хеш-таблицу до примерно 150 элементов: вычисление хеша съедало выигрыш от быстрого доступа. На создание тестов ушло четыре месяца: пришлось исключить влияние виртуальных вызовов, добавить прогрев процессора и фиксировать условия зап…

❤6🔥6🙏5😁2👍1🤔1🥰1

28 Sept 2026, 11:30 UTC≈6,680 views29 reactionsread 2 October 2026
Photo

👩‍💻 Что на самом деле происходит внутри Go map? После Go 1.24 обычный map внутри работает уже не так, как раньше: вместо старой схемы с overflow buckets используется Swiss Tables. И там довольно много интересного: хеш делится на части, поиск идёт группами по 8 слотов, SIMD сразу сравнивает несколько значений, а при росте таблица может дробиться. 📍 В статье всё это разбирают буквально по шагам — от m["cow"] = 4 до …

🔥9❤‍🔥5🙏5👍4🤩2⚡1👾1💯1

28 Sept 2026, 05:02 UTC≈3,940 views28 reactionsread 2 October 2026
Photo

Как сделать системную утилиту понятнее и приятнее Системная утилита не должна молча выполнять команду и исчезать. Если программа не показывает ход работы и итог, пользователю сложнее понять результат и доверять ему. Автор предлагает объяснять действие до запуска, показывать изменения по ходу процесса и завершать сценарий ясным результатом. Подход команды MacPaw к служебным приложениям пригодится и для внутренних и…

❤5🎉4🤔4💯3🔥3👍2😍2😢2

27 Sept 2026, 05:02 UTC≈4,130 views34 reactionsread 2 October 2026
Photo

Как модернизировать устаревшее приложение с ИИ без полного переписывания ИИ может перенести старый код на новый стек вместе с неясными правилами и проблемами развёртывания. Получится та же система, только переписанная быстрее. Сначала составьте карту кодовой базы: правила, зависимости, побочные эффекты и внешние вызовы. Затем зафиксируйте текущее поведение характеристическими тестами, чтобы видеть изменения после п…

❤9🌚5👏5😁5👍3🎉2👾2🙏2

Showing the 12 most recent of 104 posts we hold for @proglibrary. 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.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Posts edited after publishing

@proglibrary 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
9 September 2026
Most recent edit
16 September 2026

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 10 registered channels — 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.

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.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

Типичный программист
@tproger · 78,167
#1
Хабр
@habr_com · 132,764
#2
hahacker_news
@hahacker_news · 25,493
#3
Библиотека питониста | Python, Django, Flask
@pyproglib · 37,310
#4
Библиотека Go-разработчика | Golang
@goproglib · 24,076
#5
IT Юмор
@ithumor · 60,568
#6
Библиотека шарписта | C#, F#, .NET, ASP.NET
@csharpproglib · 21,652
#7
Библиотека фронтендера | Frontend, JS, JavaScript, React.js, Angular.js, Vue.js
@frontendproglib · 20,856
#8
NOP::Nuances of Programming
@nuancesprog · 56,424
#9
Библиотека IT-мемов
@itmemlib · 9,546
#10
BZD • Книги для программистов
@bzd_channel · 36,402
#11
Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение
@dsproglib · 18,339
#12
Код.ру
@d_code · 406,147
#13
Библиотека C/C++ разработчика | cpp, boost, qt
@cppproglib · 16,865
#14
Rozetked
@rozetked · 672,965
#15
Библиотека джависта | Java, Spring, Maven, Hibernate
@javaproglib · 22,022
#16
Библиотека девопса | DevOps, SRE, Sysadmin
@devopsslib · 10,381
#17
Библиотека пхпшника | PHP, Laravel, Symfony, CodeIgniter
@phpproglib · 10,492
#18
Golang
@Golang_google · 40,461
#19
CodeCamp
@codecamp · 180,482
#20
Библиотека Go для собеса | вопросы с собеседований
@go_interview_lib · 7,468
#21
Machinelearning
@ai_machinelearning_big_data · 279,417
#22
Библиотека хакера | Hacking, Infosec, ИБ, информационная безопасность
@hackproglib · 12,691
#23
Говнокод
@g_code · 14,872
#24
Журнал «Код»
@thecodemedia · 49,232
#25
Библиотека ИИ для айтишников
@neuro_text · 6,493
#26
GitHub Community
@github · 155,991
#27
Библиотека мобильного разработчика | Android, iOS, Swift, Retrofit, Moshi, Chuck
@mobileproglib · 9,155
#28
Веб-страница
@tproger_web · 22,429
#29
Programmer & IT Memes
@itmemes · 123,290
#30
Библиотека задач по Go | тесты, код, задания
@go_problems_lib · 6,746
#31
Denis Sexy IT 🤖
@denissexy · 137,610
#32
Программирование | книги
@it_boooks · 47,460
#33
Clean Code
@codeclean · 12,039
#34
FrontEndDev
@front_end_dev · 25,875
#35
Библиотека собеса по C# | вопросы с собеседований
@csharp_interview_lib · 5,653
#36
Технотренды
@techno_media · 781,663
#37
Минцифры России
@mintsifry · 234,926
#38
Golang Books
@golang_books · 16,949
#39
Николай Тузов
@ntuzov · 16,870
#40
Азбука айтишника
@abc_for_it · 3,480
#41
Библиотека задач по Python | тесты, код, задания
@py_problems_lib · 6,381
#42
Библиотека собеса по PHP | вопросы с собеседований
@php_interview_lib · 3,089
#43
Proglib.academy | IT-курсы
@proglib_academy · 3,898
#44
Не баг, а фича
@bugfeature · 571,363
#45
WebDEV
@webb_dev · 8,299
#46
.NET Разработчик
@NetDeveloperDiary · 6,744
#47
The After Times
@theaftertimes · 16,799
#48
Инструменты программиста
@prog_tools · 12,927
#49
эйай ньюз
@ai_newz · 97,070
#50
Библиотека задач по C# | тесты, код, задания
@csharp_problems_lib · 4,940
#51
Библиотека задач по C++ | тесты, код, задания
@cpp_problems_lib · 5,448
#52
Data Secrets
@data_secrets · 94,138
#53
Java библиотека
@javalib · 30,600
#54
Golang вопросы собеседований
@golang_interview · 15,058
#55
CodeMode | Программирование
@code_m0de · 10,783
#56
Metanit
@metanit · 8,040
#57
vc.ru
@vcnews · 112,057
#58
Библиотека собеса по Python | вопросы с собеседований
@py_interview_lib · 5,907
#59
Библиотека собеса по C++ | вопросы с собеседований
@cpp_interview_lib · 4,615
#60
IT Portal
@IT_Portal · 99,978
#61
Social Engineering
@Social_engineering · 125,007
#62
Библиотека задач по Java | тесты, код, задания
@java_problems_lib · 5,626
#63
Frontender's notes [ru]
@frontendnoteschannel_ru · 31,297
#64
Programmer memes
@programmer_memes · 51,106
#65
Data Science. SQL hub
@sqlhub · 35,960
#66
Программирование {BookFlow}
@bookflow · 15,607
#67
XOR
@xor_journal · 182,317
#68
Библиотека собеса по DevOps | вопросы с собеседований
@devops_interview_lib · 3,451
#69
[PYTHON:TODAY]
@python2day · 63,764
#70
Physics.Math.Code
@physics_lib · 146,712
#71
Эксплойт
@exploitex · 2,048,279
#72
Бэкдор
@whackdoor · 1,590,187
#73
addmeto
@addmeto · 71,835
#74
Go jobs — вакансии по Go
@godevjob · 11,360
#75
THINGS PROGRAMMERS DO
@thingsprogrammersdo · 15,989
#76
Библиотека собеса по Java | вопросы с собеседований
@java_interview_lib · 6,433
#77
C# jobs — вакансии по C#, .NET, Unity
@csharpdevjob · 10,288
#78
Reddit
@Reddit · 162,045
#79
Утечки информации
@dataleak · 119,057
#80
Рестарт
@remedia · 698,207
#81
Python jobs — вакансии по питону, Django, Flask
@pydevjob · 9,645
#82

Read from Telegram’s recommendation API, most recently 19 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

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.

Библиотека фронтендера | Frontend, JS, JavaScript, React.js, Angular.js, Vue.js
@frontendproglib · 20,856
Telegram ranks this channel #1 of 93 here — alongside 92 others — read 25 September 2026
hahacker_news
@hahacker_news · 25,493
Telegram ranks this channel #1 of 59 here — alongside 58 others — read 14 September 2026
Библиотека питониста | Python, Django, Flask
@pyproglib · 37,310
Telegram ranks this channel #1 of 84 here — alongside 83 others — read 1 September 2026
NOP::Nuances of Programming
@nuancesprog · 56,424
Telegram ranks this channel #1 of 84 here — alongside 83 others — read 23 August 2026
BZD • Книги для программистов
@bzd_channel · 36,402
Telegram ranks this channel #2 of 57 here — alongside 56 others — read 1 September 2026
Типичный программист
@tproger · 78,167
Telegram ranks this channel #3 of 95 here — alongside 94 others — read 19 August 2026
Журнал «Код»
@thecodemedia · 49,232
Telegram ranks this channel #4 of 97 here — alongside 96 others — read 25 August 2026
Библиотека джависта | Java, Spring, Maven, Hibernate
@javaproglib · 22,022
Telegram ranks this channel #5 of 88 here — alongside 87 others — read 21 September 2026
[404] — программирование
@procode404 · 40,508
Telegram ranks this channel #6 of 83 here — alongside 82 others — read 30 August 2026
Веб-страница
@tproger_web · 22,429
Telegram ranks this channel #9 of 96 here — alongside 95 others — read 20 September 2026
Учебные фильмы 🎞
@maths_lib · 25,423
Telegram ranks this channel #10 of 67 here — alongside 66 others — read 14 September 2026
GitHub Community
@github · 155,991
Telegram ranks this channel #10 of 87 here — alongside 86 others — read 12 August 2026
Полка Разработчика
@developer_shelf · 26,815
Telegram ranks this channel #12 of 63 here — alongside 62 others — read 11 September 2026
Книги и Аудиокниги | Флибуста
@skachat_chitat_besplatno · 89,949
Telegram ranks this channel #12 of 73 here — alongside 72 others — read 17 August 2026
Physics.Math.Code
@physics_lib · 146,712
Telegram ranks this channel #13 of 72 here — alongside 71 others — read 13 August 2026
Pythonist.ru - образование по питону
@pythonist_ru · 24,046
Telegram ranks this channel #15 of 82 here — alongside 81 others — read 17 September 2026
Библиотека Go-разработчика | Golang
@goproglib · 24,076
Telegram ranks this channel #15 of 91 here — alongside 90 others — read 17 September 2026
Windows Community
@wind_community · 41,213
Telegram ranks this channel #15 of 74 here — alongside 73 others — read 29 August 2026
Английский для программиста | EnglishScript
@EnglishScript · 45,107
Telegram ranks this channel #16 of 82 here — alongside 81 others — read 27 August 2026
Python Academy
@python_academy · 44,284
Telegram ranks this channel #19 of 87 here — alongside 86 others — read 28 August 2026
IT Юмор
@ithumor · 60,568
Telegram ranks this channel #19 of 94 here — alongside 93 others — read 22 August 2026
Selectel
@Selectel · 63,164
Telegram ranks this channel #20 of 96 here — alongside 95 others — read 21 August 2026
Хабр
@habr_com · 132,764
Telegram ranks this channel #20 of 92 here — alongside 91 others — read 13 August 2026
Книжное хранилище
@knijnoe_xranilishe · 19,635
Telegram ranks this channel #25 of 73 here — alongside 72 others — read 30 September 2026

This channel appears in 64 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 25 September 2026 — this entry's latest reading, not the date you are reading this.

“Библиотека программиста” (@proglibrary), 78,288 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/proglibrary.

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.