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Channel

Книги для программистов

@progbook

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

138,528subscribers

-1,812 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 100,000–316,228.

Register entry

Telegram ID-1001135553470
TypeChannel
Username@progbook
DescriptionВсе о книгах из мира IT. Наши курсы: https://clc.to/CVcXPw По рекламе: @proglib_adv Для обратной связи: @proglibrary_feeedback_bot РКН: https://www.gosuslugi.ru/snet/67931954509aba565214777d Заявка РКН: 8136481299
Created8 September 2017 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live25 October 2026
Measurements held49
Confirmed unchanged1 time, most recently 25 October 2026
On Telegramt.me/progbook

Topic

Education — 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 9 August 2026 and assigned it the closest of 31 fixed categories, at 60% 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.

Growth

138,528140,340139,4346 August 2026 — 140,340 subscribers6 August 2026 — 140,340 subscribers7 August 2026 — 140,329 subscribers8 August 2026 — 140,306 subscribers9 August 2026 — 140,271 subscribers10 August 2026 — 140,250 subscribers11 August 2026 — 140,232 subscribers12 August 2026 — 140,219 subscribers13 August 2026 — 140,186 subscribers14 August 2026 — 140,157 subscribers16 August 2026 — 140,147 subscribers17 August 2026 — 140,132 subscribers18 August 2026 — 140,101 subscribers19 August 2026 — 140,090 subscribers20 August 2026 — 140,035 subscribers21 August 2026 — 140,018 subscribers23 August 2026 — 139,989 subscribers24 August 2026 — 139,942 subscribers26 August 2026 — 139,920 subscribers27 August 2026 — 139,911 subscribers28 August 2026 — 139,905 subscribers28 August 2026 — 139,901 subscribers29 August 2026 — 139,879 subscribers30 August 2026 — 139,861 subscribers31 August 2026 — 139,834 subscribers1 September 2026 — 139,821 subscribers2 September 2026 — 139,806 subscribers4 September 2026 — 139,715 subscribers6 September 2026 — 139,678 subscribers9 September 2026 — 139,614 subscribers12 September 2026 — 139,578 subscribers13 September 2026 — 139,534 subscribers15 September 2026 — 139,481 subscribers17 September 2026 — 139,460 subscribers27 September 2026 — 139,356 subscribers4 October 2026 — 139,166 subscribers9 October 2026 — 139,041 subscribers13 October 2026 — 138,902 subscribers14 October 2026 — 138,836 subscribers15 October 2026 — 138,794 subscribers16 October 2026 — 138,772 subscribers17 October 2026 — 138,729 subscribers18 October 2026 — 138,722 subscribers19 October 2026 — 138,709 subscribers20 October 2026 — 138,692 subscribers21 October 2026 — 138,665 subscribers22 October 2026 — 138,603 subscribers23 October 2026 — 138,564 subscribers25 October 2026 — 138,528 subscribers6 August 202625 October 2026
49 measurements spanning 80 days, net -1,812. 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 138,256–140,612 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 49
Measured (UTC)SubscribersChange
25 Oct 2026, 00:56138,528-36
23 Oct 2026, 21:18138,564-39
22 Oct 2026, 20:55138,603-62
21 Oct 2026, 14:11138,665-27
20 Oct 2026, 12:28138,692-17
19 Oct 2026, 15:26138,709-13
18 Oct 2026, 14:41138,722-7
17 Oct 2026, 14:06138,729-43
16 Oct 2026, 13:27138,772-22
15 Oct 2026, 15:55138,794-42
14 Oct 2026, 17:50138,836-66
13 Oct 2026, 08:19138,902-139
9 Oct 2026, 03:41139,041-125
4 Oct 2026, 20:17139,166-190
27 Sept 2026, 09:21139,356-104
17 Sept 2026, 18:19139,460-21
15 Sept 2026, 17:57139,481-53
13 Sept 2026, 22:39139,534-44
12 Sept 2026, 03:36139,578-36
9 Sept 2026, 20:17139,614first reading

Engagement

102 posts held, back to 26 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 164 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
7.32%
avg views ÷ 138,528 subscribers
Avg views / post
10,100
30 posts measured
Reaction rate
0.098%
reactions ÷ views · ER floor
Posts in window
30
of 102 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 29 of 30 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 25 October 2026
Posts held102 (26 July 2026 – 25 October 2026)
Views total304,240
Reactions total291
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken25 Oct 2026, 13:54 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
≈1,610
Videos
≈53
Links
≈1,640

Lifetime counters from Telegram’s own channel header, read 25 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.

Reaction mix

1,557 reactions across 97 posts, in 18 distinct kinds. The most used accounts for 38.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤59738.3%
👍25816.6%
😁25816.6%
🌚1207.71%
🔥1197.64%
🥱704.50%
❤‍🔥473.02%
👏221.41%
👾171.09%
😢120.771%
🤔80.514%
🎉60.385%
🥰60.385%
🙏50.321%
⚡40.257%
😍40.257%
🤩30.193%
💯10.064%

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 100 of the 102 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 1,572 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 102 most recent posts we hold, published 26 July 2026 to 25 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
3
across the posts below
Posts paid on
1
of 102 we hold a reading for · 1.0%
Most on one post
3
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @progbook. 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 102 most recent posts we hold for this entry, published 26 July 2026 to 25 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.

Advertising

Ad load
0.98%
1 of 102 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
10,500
over 1 measured post
Median views · rest
9,530
over 101 measured posts

An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.

This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.

Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2VtzqxF9x3v17 October 20267 October 2026

A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.

Measured over the 102 most recent posts we hold, published 26 July 2026 to 25 October 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.

Recent posts

25 Oct 2026, 09:15 UTC≈2,500 views5 reactionsread 25 October 2026
Photo

📕 Think DSP: Digital Signal Processing in Python, v1.1.5 Allen B. Downey · PDF на английском · 153 страницы Спектр и преобразование Фурье здесь можно исследовать на звуковой записи: построить сигнал, посмотреть частоты и применить фильтр. Книга объясняет цифровую обработку сигналов через эксперименты на Python. ❓ Что внутри: — Гармоники, спектр и наложение частот — Спектрограммы, шум и автокорреляция — Дискретные п…

👍4🥰1

24 Oct 2026, 12:36 UTC≈4,460 views5 reactionsread 25 October 2026
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📕 Mathematics for Computer Science (2018) Eric Lehman, F Thomson Leighton, Albert R Meyer · PDF на английском Как доказать, что алгоритм работает, а цикл завершится? Учебник начинает с логики и методов доказательства, затем связывает их с машинами состояний, инвариантами и рекурсивными структурами. ❓ Что внутри: — Доказательства, обычная и сильная индукция — Инварианты, корректность и завершение вычислений — Теория…

❤5

23 Oct 2026, 08:59 UTC≈5,540 views3 reactionsread 25 October 2026
Photo

📕 OpenIntro Statistics, 4th Edition (2019) David Diez, Mine Çetinkaya-Rundel, Christopher D Barr · PDF на английском Прежде чем считать p-value, стоит понять, как собраны данные. Вводный учебник связывает выборки и эксперименты со статистическими выводами. Внутри — реальные данные, разобранные примеры и упражнения. ❓ Что внутри: — Выборка, дизайн эксперимента и описание данных — Вероятности и распределения — Довери…

❤2👍1

22 Oct 2026, 16:51 UTC≈5,860 views1 reactionsread 25 October 2026
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😎 Выбираешь один курс, второй получаешь бесплатно. Баг? Нет, акция! До 31 октября в Proglib Academy можно выбрать два курса и заплатить только за один. Например, можно совместить: 💥 ИИ для разработчиков — применение нейросетей в повседневной разработке: работа с кодом, тестирование и ревью. 💥 Разработка ИИ-агентов — архитектура агентов и создание собственных AI-решений. Вместе курсы стоят 108 000 ₽, но по акции…

❤1

22 Oct 2026, 08:53 UTC≈6,240 views6 reactionsread 25 October 2026
Photo

📕 Pro Git, 2nd Edition (2014) Scott Chacon, Ben Straub · PDF на английском · 501 страница Ветки, индекс и история перестают выглядеть набором несвязанных команд, когда понятна модель Git. Авторы проходят путь от первого коммита до устройства хранилища объектов и восстановления данных. ❓ Что внутри: — Ветвление, merge и rebase — Удалённые репозитории и совместная работа — Интерактивное добавление изменений, stash и …

❤6

21 Oct 2026, 14:02 UTC≈6,570 views10 reactionsread 25 October 2026
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📕 Beej’s Guide to Network Programming: Using Internet Sockets, v3.3.3 (2026) Brian “Beej Jorgensen” Hall · PDF на английском · 134 страницы Что должен сделать сервер до первого recv() и почему одного send() может не хватить? Beej объясняет сокеты через клиентские и серверные программы на C. Версия руководства от 15 октября 2026 года. ❓ Что внутри: — TCP/UDP, IPv4/IPv6 и сетевой порядок байтов — getaddrinfo(), socke…

❤6👍2⚡1🙏1

19 Oct 2026, 11:26 UTC≈7,780 views9 reactionsread 25 October 2026
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📕 Dive into Deep Learning — arXiv v5 (2023) Учебник соединяет математическую идею, реализацию модели и эксперимент. Формулы сопровождаются кодом, а главы ведут от линейной регрессии к нейросетям и механизмам внимания. Авторы: Aston Zhang, Zachary C. Lipton, Mu Li и Alexander J. Smola. ❓ Что внутри: — Тензоры, линейная алгебра, автоматическое дифференцирование — Линейные модели, обучение, обобщение и регуляризация —…

👍6❤3

16 Oct 2026, 14:05 UTC≈9,050 views6 reactionsread 25 October 2026
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📕 tldr pages book — сборка 13 октября 2026 Справочник команды tldr-pages для случаев, когда название утилиты знакомо, а нужный флаг опять приходится искать. Вместо длинного руководства — короткое описание и примеры типичных действий с обозначенными аргументами. ❓ Что внутри: — Git и Docker: отдельные карточки команд и подкоманд — Поиск файлов, работа с архивами, сетью и процессами — Разделы Common, Linux, macOS, Wi…

❤4👾2

16 Oct 2026, 12:05 UTC≈7,890 views5 reactionsread 25 October 2026
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📕 Open Data Structures (in Java), Edition 0.1G Пэт Морин разбирает структуры данных через реализацию и стоимость операций. Книга помогает понять, почему добавление элемента иногда требует перераспределить массив, а удачный выбор структуры меняет время поиска и объём памяти. ❓ Что внутри: — ArrayQueue и другие структуры на массивах, рост и уменьшение буфера — Skip list: поиск и индексированный доступ с вероятностным…

❤3👍2

15 Oct 2026, 15:35 UTC≈8,470 views6 reactionsread 25 October 2026

☔️ Планы на выходные снова испортила погода? У нас есть план получше. Выходные — хороший повод заняться тем, на что вечно не хватает времени. Например, освоить новый навык или углубиться в знакомую тему. 📍 В Proglib Academy покупаешь один курс, а второй получаешь в подарок. Платишь только за один! Вот несколько сочетаний: 💥 ⁠Разработка ИИ-агентов + ⁠Python 💥 ⁠Machine Learning + ⁠Математика для Data Science Можно…

❤4🤔2

15 Oct 2026, 09:15 UTC≈7,110 views6 reactionsread 25 October 2026

🧑‍💻 Какие навыки помогают вам в разработке в 2026 году? Что вы чаще используете в работе? В каких задачах помогает ИИ, а где проще справиться самостоятельно? Мы решили собрать портрет современного разработчика — и приглашаем вас поделиться своим опытом. Расскажите, какие навыки вам пригодились и как вы используете ИИ. Если обходите его стороной, нам тоже интересно узнать почему. Опрос анонимный и займёт около 5 ми…

❤4👍2

14 Oct 2026, 09:04 UTC≈8,480 views17 reactionsread 25 October 2026
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📕 Scripting: Automation with Bash, PowerShell, and Python (2024) Бэкапы, обработка файлов и обращения к API не всегда требуют отдельного приложения. Михаэль Кофлер разбирает, как решать такие задачи скриптами, выбирая между Bash, PowerShell и Python. ❓ Что внутри: — Синтаксис трёх языков и инструменты командной строки — Командлеты, фильтры и конвейеры — Регулярные выражения и обработка текста — Работа с JSON, XML …

👍11❤4🌚2

Showing the 12 most recent of 102 posts we hold for @progbook. 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

@progbook edited 1 post 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
16 September 2026
Most recent edit
16 September 2026

Polls

The 2 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.

14 Oct 2026, 08:10 UTCAnonymous Poll1,510 voters approx.

Если приходилось уходить с одного ИИ-инструмента на другой, что стало главной причиной?

  1. Качество ответов и кода стало не устраивать29%
  2. Упёрся в лимиты или не хватает функций14%
  3. Цены кусаются10%
  4. Проблемы с доступом: блокировки, нужен VPN17%
  5. Сложности с оплатой3%
  6. Стало неудобно работать3%
  7. Не менял инструмент — сижу на привычном24%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

11 Oct 2026, 17:55 UTCAnonymous Poll2,040 voters approx.

Приходится ли вам копипастить данные и какие именно, когда переходите из одной нейросети в другую?

  1. Код18%
  2. Описание задачи28%
  3. Документацию14%
  4. Результаты работы17%
  5. Настройки и контекст: историю чатов, промпты, скиллы20%
  6. Ничего, использую один инструмент50%

The shares total 147%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.

Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.

The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.

Read from the 102 most recent posts we hold, published 26 July 2026 to 25 October 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.

Forward network

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 9 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.

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

“Книги для программистов” (@progbook), 138,528 subscribers as measured 25 October 2026. Telegram Register, tgregister.com/channel/progbook.

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.