Telegram RegisterThe public register of Telegram

Channel

Python Books. Книги по питону

@pythonbooks

On this record: Growth · Engagement · What this channel posts · Reactions · Advertising · Posts · Citations · Cite this entry

38,381subscribers

+345 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-1001495721500
TypeChannel
Username@pythonbooks
DescriptionКниги по Python Наш канал с задачами по Python: @pythonquestions Ищешь работу: @pythonrabota Реклама: @anothertechrock РКН: https://clck.ru/3R3u2x
CreatedBetween 1 May 2019 and 31 July 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/pythonbooks

Growth

38,03638,38138,208.56 August 2026 — 38,036 subscribers6 August 2026 — 38,240 subscribers7 August 2026 — 38,311 subscribers8 August 2026 — 38,327 subscribers9 August 2026 — 38,353 subscribers10 August 2026 — 38,362 subscribers11 August 2026 — 38,366 subscribers12 August 2026 — 38,381 subscribers6 August 202612 August 2026
8 measurements spanning 6 days, net +345. 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 37,984–38,433 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 14:1438,381+15
11 Aug 2026, 15:1738,366+4
10 Aug 2026, 15:2238,362+9
9 Aug 2026, 16:2638,353+26
8 Aug 2026, 16:2638,327+16
7 Aug 2026, 17:1738,311+71
6 Aug 2026, 18:5538,240+204
6 Aug 2026, 06:4538,036first reading

Engagement

23 posts held, back to 16 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 18 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
9.55%
avg views ÷ 38,381 subscribers
Avg views / post
3,660
23 posts measured
Reaction rate
0.278%
reactions ÷ views · ER floor
Posts in window
23
of 23 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 August 2026
Posts held23 (16 July 202610 August 2026)
Views total84,280
Reactions total234
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Aug 2026, 09:11 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
83
Links
90

Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

234 reactions across 23 posts, in 16 distinct kinds. The most used accounts for 38.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
9138.9%
👍4519.2%
🔥229.40%
❤‍🔥145.98%
👏145.98%
💩104.27%
🤡104.27%
🤔83.42%
🤮83.42%
🙏31.28%
👌20.855%
😎20.855%
🤩20.855%
👎10.427%
💊10.427%
🥰10.427%

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 23 of the 23 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 234reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 23 most recent posts we hold, published 16 July 2026 to 10 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.

Advertising

Ad load
4.35%
1 of 23 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
3,980
over 1 measured post
Median views · rest
3,630
over 22 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
2W5zFG9Wbyb117 July 202617 July 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 23 most recent posts we hold, published 16 July 2026 to 10 August 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

10 Aug 2026, 16:00 UTC≈2,150 views8 reactionsread 13 August 2026
Photo

Python, Django, Data Science Автор: Майтак Р.В. и др. Год издания: 2025 #python #ru Скачать книгу

4👍4

10 Aug 2026, 08:30 UTC≈2,400 views11 reactionsread 13 August 2026
Photo

⌨ Работа с SQLAlchemy и alembic в FastAPI Приглашаем на открытый урок. 🗓 11 августа в 20:00 МСК 🆓 Бесплатно. Урок в рамках старта курса «Pyhon-разработчик». На этом вебинаре вы разберётесь, как подключить базу данных к FastAPI-приложению с помощью синхронного SQLAlchemy. Опишете модели, поработаете с сессией и управлять изменениями схемы через Alembic. Результат: - Научитесь работать с базой данных через SQLAlch

4❤‍🔥3👍2🤡2

10 Aug 2026, 05:37 UTC≈2,510 views7 reactionsread 13 August 2026
Photo

50 Days of Data Analysis with Python Автор: Benjamin Bennett Alexander Год издания: 2023 #python #en Скачать книгу

7

5 Aug 2026, 13:32 UTC≈4,330 views9 reactionsread 13 August 2026
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Интерпретируемое машинное обучение на Python Автор: Серг Масис Год издания: 2023 #python #ru Скачать книгу

5👍4

5 Aug 2026, 08:01 UTC≈3,670 views13 reactionsread 13 August 2026
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Как выглядят задачи машинного обучения в бигтехе? Открыта регистрация на E-CUP 2026 Students — ежегодное соревнование от Ozon Tech. В этом сезоне — для студентов, которые интересуются ML, Data Science, Big Data и аналитикой данных. Вас ждут три трека: поиск дубликатов товаров, ИИ-модерация карточек маркетплейса и прогнозирование поведения пользователей. Все задачи основаны на реальных обезличенных данных Ozon. Уча

6🔥2🤔2🤩2🤡1

4 Aug 2026, 16:40 UTC≈3,350 views10 reactionsread 13 August 2026
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Изучаем Data Science Автор: Сэм Лау, Джозеф Гонсалес, Дебора Нолан Год издания: 2025 #python #ru Скачать книгу

6👍2🤔2

4 Aug 2026, 13:03 UTC≈3,130 views10 reactionsread 13 August 2026
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Когда микросервисов становится больше, проблемы редко возникают в бизнес-логике. Чаще всего они появляются на стыке сервисов: задержки, каскадные сбои, перегрузка и сложность получения данных. Именно здесь архитектурные решения определяют, насколько система будет быстрой и устойчивой. 4 августа в 20:00 МСК приглашаем вас на открытый урок курса «Архитектор программного обеспечения», где разберём, как проектировать вз

🔥32👏2🤡2👍1

4 Aug 2026, 12:32 UTC≈3,020 views10 reactionsread 13 August 2026
Photo

Image Processing with Python Авторы: Erik Cuevas и др. Год издания: 2026 #python #en Скачать книгу

👍6🔥31

4 Aug 2026, 08:03 UTC≈3,090 views12 reactionsread 13 August 2026
Photo

One Day Offer для Python-разработчиков!💚 15 августа открываем двери в команду Agent Execution Framework ⚡️ Коллеги создают платформу для GenAI‑агентов в банке — делают так, чтобы ИИ реально работал в серьёзных финпроцессах: с безопасностью, нагрузкой и пользой. Чем предстоит заниматься: ✔️ развивать backend на Python ✔️ подключать LLM, инструменты, базы знаний и RAG ✔️ строить пайплайны оценки качества агентов ✔️

4🤡3👍2🙏2🤔1

3 Aug 2026, 06:19 UTC≈3,460 views11 reactionsread 13 August 2026
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Программирование бэкенда на Python Автор: Тим Питерс Год издания: 2025 #python #ru Скачать книгу

8👍3

29 Jul 2026, 13:50 UTC≈4,450 views16 reactionsread 13 August 2026
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Fun with Python Автор: Hubert Piotrowski Год издания: 2025 #python #en Скачать книгу

👏10🤮42

29 Jul 2026, 07:24 UTC≈4,140 views14 reactionsread 13 August 2026
Photo

⌨ Оживляем код: первые шаги в ООП на Python Приглашаем на открытый урок. 🗓 03 августа в 20:00 МСК 🆓 Бесплатно. Урок в рамках старта курса «Pyhon-разработчик». На занятии вы узнаете: ✔ Что такое класс и объект, и зачем они нужны. ✔ Как создавать свои типы данных с атрибутами и методами. ✔ Как объединять данные и логику внутри класса. ✔ Как применить ООП на простом практическом примере. 🔗 Ссылка на регистрацию: htt

🔥5🤮4👌2👍2🙏1

Showing the 12 most recent of 23 posts we hold for @pythonbooks. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 31,571 of 1,160,990entries 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.

Mentions

Named by 38 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

Named by

Channels on the register whose posts name this channel's handle.

Машинное обучение. Книги по программированию
@maschinelearning · 10,658
6 posts
Базы данных. Книги по программированию
@dbbooks · 16,639
5 posts
Библиотека тестировщика. QaRocks
@libqa · 11,898
5 posts
Архив книг по программированию
@devbooksarchive · 15,840
4 posts
Python книги
@pythonknigi · 15,951
4 posts
Тестировщик со вкусом
@testinglib · 4,770
4 posts
Java книги по программированию
@booksjava · 11,640
3 posts
Книги по тестированию
@booksqa · 13,233
3 posts
Архив книг по программированию
@gamedevarchive · 14,656
3 posts
Книги по программированию
@python_books_archive · 12,435
3 posts
Книги по Python. Книги по программированию на Python
@pythonbooksarchive · 9,049
3 posts
TechSkills - книги по программированию
@techskill · 14,353
3 posts
Книгомир. Книги по программированию
@archivedevelop · 5,751
2 posts
Блокчейн книги. Solidity, btc, eth разработка под web3
@blockchainbook · 1,602
2 posts
Что почитать айтишнику? Архив книг. Библиотека программиста.
@booksql · 8,364
2 posts
Архив БД
@dblib · 3,806
2 posts
Techbooks - книги для программистов
@devtechbooks · 5,017
2 posts
Data Science Books
@dsbooksru · 4,325
2 posts
КНИГИ: REACT, JS, ANGULAR, NODE, VUE
@frontbooks · 7,913
2 posts
Java Книги. Книги по программированию на Java
@javabooksarchive · 4,680
2 posts
PythonBooks
@pythonbyks · 5,836
2 posts
Книги для тестировщика 📚 Библиотека тестировщика
@qabackup · 5,276
2 posts
SqlLib. Книги по SQL и Базам
@sqllibr · 4,492
2 posts
Архив программиста
@techrocksarchive · 15,841
2 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.

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

“Python Books. Книги по питону” (@pythonbooks), 38,381 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/pythonbooks.

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.