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Channel

Библиотека питониста | Python, Django, Flask

@pyproglib

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

37,384subscribers

-225 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1001138587070
TypeChannel
Username@pyproglib
DescriptionВсе самое полезное для питониста в одном канале. Учиться у нас: clc.to/6e5Csg Для обратной связи: @proglibrary_feeedback_bot По рекламе: @tproger_sales_bot РКН: https://gosuslugi.ru/snet/67b885cbd501cf3b2cdb5b36
Created23 July 2018 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live18 September 2026
Measurements held32
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/pyproglib

Topic

Education — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 98% 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

37,38437,61637,5006 August 2026 — 37,609 subscribers6 August 2026 — 37,608 subscribers7 August 2026 — 37,616 subscribers8 August 2026 — 37,602 subscribers9 August 2026 — 37,591 subscribers10 August 2026 — 37,585 subscribers11 August 2026 — 37,579 subscribers13 August 2026 — 37,580 subscribers14 August 2026 — 37,564 subscribers16 August 2026 — 37,551 subscribers17 August 2026 — 37,548 subscribers18 August 2026 — 37,547 subscribers19 August 2026 — 37,538 subscribers20 August 2026 — 37,528 subscribers22 August 2026 — 37,524 subscribers23 August 2026 — 37,513 subscribers25 August 2026 — 37,512 subscribers26 August 2026 — 37,505 subscribers27 August 2026 — 37,504 subscribers28 August 2026 — 37,502 subscribers29 August 2026 — 37,491 subscribers30 August 2026 — 37,478 subscribers31 August 2026 — 37,472 subscribers1 September 2026 — 37,470 subscribers2 September 2026 — 37,466 subscribers3 September 2026 — 37,465 subscribers7 September 2026 — 37,446 subscribers10 September 2026 — 37,426 subscribers12 September 2026 — 37,424 subscribers14 September 2026 — 37,403 subscribers16 September 2026 — 37,388 subscribers18 September 2026 — 37,384 subscribers6 August 202618 September 2026
32 measurements spanning 43 days, net -225. 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 37,349–37,651 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)SubscribersChange
18 Sept 2026, 03:4037,384-4
16 Sept 2026, 00:3737,388-15
14 Sept 2026, 07:4137,403-21
12 Sept 2026, 14:1837,424-2
10 Sept 2026, 14:3637,426-20
7 Sept 2026, 10:2237,446-19
3 Sept 2026, 02:2837,465-1
2 Sept 2026, 00:0537,466-4
1 Sept 2026, 01:4537,470-2
31 Aug 2026, 03:0837,472-6
30 Aug 2026, 05:3337,478-13
29 Aug 2026, 03:3537,491-11
28 Aug 2026, 04:0437,502-2
27 Aug 2026, 05:5737,504-1
26 Aug 2026, 06:2837,505-7
25 Aug 2026, 03:4337,512-1
23 Aug 2026, 23:1437,513-11
22 Aug 2026, 06:1737,524-4
20 Aug 2026, 20:1637,528-10
19 Aug 2026, 18:1737,538first reading

Engagement

33 posts held, back to 18 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 92 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
6.55%
avg views ÷ 37,384 subscribers
Avg views / post
2,450
10 posts measured
Reaction rate
0.247%
reactions ÷ views · ER floor
Posts in window
10
of 33 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 8 of 10 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 September 2026
Posts held33 (18 July 2026 – 25 September 2026)
Views total24,480
Reactions total52
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken27 Sept 2026, 03:09 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
≈3,300
Videos
≈105
Links
≈5,060

Lifetime counters from Telegram’s own channel header, read 27 September 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
26s
Average length
26s

Measured directly from 1 video 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

161 reactions across 21 posts, in 7 distinct kinds. The most used accounts for 36.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤5936.6%
👍4427.3%
🔥2918.0%
😁2515.5%
🤩21.24%
👾10.621%
🥱10.621%

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 24 of the 33 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 162 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 33 most recent posts we hold, published 18 July 2026 to 25 September 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
2
across the posts below
Posts paid on
2
of 33 we hold a reading for · 6%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @pyproglib. 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 33 most recent posts we hold for this entry, published 18 July 2026 to 25 September 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

25 Sept 2026, 19:00 UTC≈1,140 viewsread 27 September 2026

🔥 Курс «ИИ для разработчиков» уже стартовал И мы решили открыть первое занятие всем — можно просто взять и посмотреть, что происходит внутри курса. ⏬ ⁠Первое занятие — в открытом доступе А дальше — практика на собственном проекте. Ваш код: контекст, планирование, subagents, тесты, ревью и PR. По ходу работы разберёте MCP и научитесь контролировать расходы на модели. Если хотите попасть в этот поток — ещё не поз…

20 Sept 2026, 12:03 UTC≈2,870 views12 reactionsread 27 September 2026
Photo

👻 94% токенов уходят не на код Анализ запусков показал: основная часть токенов уходит на повторное чтение контекста. Агент снова изучает проект, подтягивает файлы и идёт на новый круг. 🔴 На курсе «ИИ для разработчиков» разбираем, как с этим работать: контекст и AGENTS.md / CLAUDE.md, subagents, планирование, ревью и маршрутизация моделей по стоимости. Всё это — на своём проекте, от задачи до PR ✅ ⬆️ Спикер — Арсе…

😁6🔥3❤2🥱1

19 Sept 2026, 20:02 UTC≈2,450 views5 reactionsread 27 September 2026

📚Напоминаем про наш полный курс «Самоучитель по Python для начинающих» Мы написали и собрали для вас в одну подборку все 25 глав и 230 практических заданий! 🐍 Часть 1: Особенности, сферы применения, установка, онлайн IDE 🐍 Часть 2: Все, что нужно для изучения Python с нуля – книги, сайты, каналы и курсы 🐍 Часть 3: Типы данных: преобразование и базовые операции 🐍 Часть 4: Методы работы со строками 🐍 Часть 5: Методы …

❤5

15 Sept 2026, 10:04 UTC≈2,790 views1 reactionsread 27 September 2026
Photo

😭 Как не потратить недельный лимит AI-кодинга за три дня? Разберём на вебинаре, как тратить меньше на AI-агентов — без потери качества кода. 🔘 Поговорим о том: — когда дорогая модель действительно нужна, а когда хватит дешёвой; — сколько стоит один прогон и куда уходят токены; — какие задачи можно отдавать субагентам; — как настроить маршрутизацию моделей; — что проверять в AI-коде перед merge. ✏️ Покажем всё на …

❤1

15 Sept 2026, 09:27 UTC≈2,330 views9 reactionsread 27 September 2026
Photo

⏱️ Справочник по Big-O в Python Для тех, кто хочет писать не просто работающий, а эффективный код, обновился ультимативный справочник — Python Time & Space Complexity Reference. Это детальная база данных по сложности операций для версий Python от 3.9 до 3.14. 📍 Навигация: Вакансии • Задачи • Собесы 🐸 Библиотека питониста

❤5👍4

14 Sept 2026, 07:00 UTC≈2,300 viewsread 27 September 2026

🤪 Если бы можно было задать один вопрос про AI в разработке — что бы вы спросили? Как выбрать инструмент? Как работать с AI-агентами? Как проверять сгенерированный код? Или как вообще встроить нейросети в свой процесс? Собираем вопросы для вебинара. Самые залайканные разберём в первую очередь 🔥 Пишите, что действительно интересно ⬇️

13 Sept 2026, 14:34 UTC≈2,390 views4 reactionsread 27 September 2026
Photo

🌸 Вселенная намекает: пора уже начать этот курс С 14 сентября цены в Proglib Academy вырастут на 20% 👀 Так что если курс давно ждёт своего часа — лучше не откладывать ещё на месяц 😏 📍 Выбрать курс

❤3🔥1

13 Sept 2026, 10:01 UTC≈2,460 views4 reactionsread 27 September 2026
Video

⚡️ psp — быстрый старт Python-проекта psp (Python Scaffolding Projects) — ультрабыстрый CLI-инструмент для создания структуры Python-проектов. Написан на Rust, поэтому работает в разы быстрее привычных scaffolding-тулов. Что умеет: ✅ в 1–100 раз быстрее аналогов ✅ сразу работает с pyproject.toml и Python 3.14 ✅ генерирует файлы и структуру проекта ✅ поддержка unittest, pytest, tox и CI ✅ генерирует Dockerfile / C…

❤4

13 Sept 2026, 09:02 UTC≈2,260 views11 reactionsread 27 September 2026
Photo

С днем программиста, коллеги! Желаем, чтобы код компилировался с первого раза, баги находились до релиза, а таски «на пять минут» действительно занимали пять минут. И конечно, пусть в жизни будет больше приятных сюрпризов — один из них мы уже подготовили. Скорее переходите по ссылке, трясите коробку и забирайте свой подарок ко Дню программиста: https://tprg.ru/5DwI

❤10🤩1

5 Sept 2026, 20:01 UTC≈3,490 views6 reactionsread 27 September 2026

📚Напоминаем про наш полный курс «Самоучитель по Python для начинающих» Мы написали и собрали для вас в одну подборку все 25 глав и 230 практических заданий! 🐍 Часть 1: Особенности, сферы применения, установка, онлайн IDE 🐍 Часть 2: Все, что нужно для изучения Python с нуля – книги, сайты, каналы и курсы 🐍 Часть 3: Типы данных: преобразование и базовые операции 🐍 Часть 4: Методы работы со строками 🐍 Часть 5: Методы …

🔥4❤2

22 Aug 2026, 20:02 UTC≈4,190 views6 reactions1 Starread 27 September 2026

📚Напоминаем про наш полный курс «Самоучитель по Python для начинающих» Мы написали и собрали для вас в одну подборку все 25 глав и 230 практических заданий! 🐍 Часть 1: Особенности, сферы применения, установка, онлайн IDE 🐍 Часть 2: Все, что нужно для изучения Python с нуля – книги, сайты, каналы и курсы 🐍 Часть 3: Типы данных: преобразование и базовые операции 🐍 Часть 4: Методы работы со строками 🐍 Часть 5: Методы …

🔥4❤2

8 Aug 2026, 20:02 UTC≈4,620 views13 reactions1 Starread 27 September 2026

📚Напоминаем про наш полный курс «Самоучитель по Python для начинающих» Мы написали и собрали для вас в одну подборку все 25 глав и 230 практических заданий! 🐍 Часть 1: Особенности, сферы применения, установка, онлайн IDE 🐍 Часть 2: Все, что нужно для изучения Python с нуля – книги, сайты, каналы и курсы 🐍 Часть 3: Типы данных: преобразование и базовые операции 🐍 Часть 4: Методы работы со строками 🐍 Часть 5: Методы …

🔥11❤1👾1

Showing the 12 most recent of 33 posts we hold for @pyproglib. 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.

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 7 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.

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.

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.

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#66
Библиотека программиста
@devs_storage · 19,138
#67
Полка Разработчика
@developer_shelf · 26,815
#68
Physics.Math.Code
@physics_lib · 146,712
#69
Эксплойт
@exploitex · 2,048,279
#70
Data jobs — вакансии по data science, анализу данных, аналитике, искусственному интеллекту
@datajob · 14,830
#71
CodeCamp
@codecamp · 181,043
#72
Бэкдор
@whackdoor · 1,603,481
#73
эйай ньюз
@ai_newz · 96,889
#74
addmeto
@addmeto · 71,835
#75
Denis Sexy IT 🤖
@denissexy · 137,325
#76
Код.ру
@d_code · 406,147
#77
Библиотека нейрокартинок | Midjourney, DALL-E, Stable Diffusion
@neurokartinka · 2,179
#78
Golang
@Golang_google · 40,461
#79
Библиотека нейрозвука | Транскрибация, синтез речи, ИИ-музыка
@neuroaudio · 2,627
#80
Сиолошная
@seeallochnaya · 79,594
#81
Love. Death. Transformers.
@lovedeathtransformers · 25,677
#82
Библиотека нейровидео | Sora AI, Runway ML, дипфейки
@neurovidos · 1,874
#83
Social Engineering
@Social_engineering · 125,008
#84

Read from Telegram’s recommendation API, most recently 1 September 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.

Python Books. Книги по питону
@pythonbooks · 38,517
Telegram ranks this channel #2 of 65 here — alongside 64 others — read 17 September 2026
hahacker_news
@hahacker_news · 25,571
Telegram ranks this channel #3 of 59 here — alongside 58 others — read 14 September 2026
Pythonist.ru - образование по питону
@pythonist_ru · 24,046
Telegram ranks this channel #4 of 82 here — alongside 81 others — read 17 September 2026
Библиотека программиста
@proglibrary · 78,288
Telegram ranks this channel #4 of 82 here — alongside 81 others — read 19 August 2026
Поколение Python 🐍
@pygen_ru · 50,072
Telegram ranks this channel #5 of 93 here — alongside 92 others — read 25 August 2026
Python Academy
@python_academy · 44,284
Telegram ranks this channel #6 of 87 here — alongside 86 others — read 28 August 2026
Senior Python Developer
@seniorpy · 39,864
Telegram ranks this channel #8 of 92 here — alongside 91 others — read 30 August 2026
Python и 1000 уязвимостей
@osint_pythons · 36,535
Telegram ranks this channel #9 of 84 here — alongside 83 others — read 1 September 2026
Python обучающий
@pythonist24 · 55,872
Telegram ranks this channel #10 of 88 here — alongside 87 others — read 23 August 2026
Однажды в трендах
@trendo · 67,788
Telegram ranks this channel #11 of 90 here — alongside 89 others — read 20 August 2026
NOP::Nuances of Programming
@nuancesprog · 56,542
Telegram ranks this channel #13 of 84 here — alongside 83 others — read 23 August 2026
Python Learning
@Python_per_month · 28,238
Telegram ranks this channel #14 of 86 here — alongside 85 others — read 9 September 2026
Простой Python | Программирование
@python_piton_javascript · 126,249
Telegram ranks this channel #14 of 84 here — alongside 83 others — read 13 August 2026
BZD • Книги для программистов
@bzd_channel · 36,402
Telegram ranks this channel #15 of 57 here — alongside 56 others — read 1 September 2026
Журнал «Код»
@thecodemedia · 49,232
Telegram ranks this channel #17 of 97 here — alongside 96 others — read 25 August 2026
Python/ django
@pythonl · 58,866
Telegram ranks this channel #18 of 84 here — alongside 83 others — read 22 August 2026
Stepik – онлайн-курсы
@stepik_courses · 24,454
Telegram ranks this channel #21 of 93 here — alongside 92 others — read 16 September 2026
Python Developer
@python_tg · 20,963
Telegram ranks this channel #22 of 85 here — alongside 84 others — read 25 September 2026
Python Hacks
@python_secrets · 40,594
Telegram ranks this channel #22 of 82 here — alongside 81 others — read 30 August 2026
Python Job | Вакансии | Стажировки
@job_python · 23,025
Telegram ranks this channel #27 of 96 here — alongside 95 others — read 19 September 2026
Python вопросы с собеседований
@python_job_interview · 24,881
Telegram ranks this channel #27 of 90 here — alongside 89 others — read 15 September 2026
Библиотека фронтендера | Frontend, JS, JavaScript, React.js, Angular.js, Vue.js
@frontendproglib · 20,930
Telegram ranks this channel #28 of 93 here — alongside 92 others — read 25 September 2026
Типичный программист
@tproger · 78,305
Telegram ranks this channel #28 of 95 here — alongside 94 others — read 19 August 2026
[PYTHON:TODAY]
@python2day · 63,764
Telegram ranks this channel #29 of 91 here — alongside 90 others — read 21 August 2026

This channel appears in 36 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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“Библиотека питониста | Python, Django, Flask” (@pyproglib), 37,384 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/pyproglib.

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.