Telegram RegisterThe public register of Telegram

Channel

Хитрый Питон

@tricky_python

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

2,510subscribers

+7 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001481827438
TypeChannel
Username@tricky_python
Created15 January 2021measured — cross-checked against a third-party dataset (TGDataset)
First recorded7 August 2026
Last confirmed live10 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 10 August 2026
On Telegramt.me/tricky_python

Growth

2,5032,5102,506.56 August 2026 — 2,503 subscribers7 August 2026 — 2,503 subscribers7 August 2026 — 2,505 subscribers10 August 2026 — 2,510 subscribers6 August 202610 August 2026
4 measurements spanning 4 days, net +7. 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 2,502–2,511 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 16:532,510+5
7 Aug 2026, 13:212,505+2
7 Aug 2026, 00:012,503no change
6 Aug 2026, 23:562,503first reading

Engagement

21 posts held, back to 3 December 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
41.8%
avg views ÷ 2,510 subscribers
Avg views / post
1,050
9 posts measured
Reaction rate
1.74%
reactions ÷ views · ER floor
Posts in window
9
of 21 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 7 August 2026
Posts held21 (3 December 20257 August 2026)
Views total9,450
Reactions total164
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:26 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.

Reaction mix

390 reactions across 21 posts, in 3 distinct kinds. The most used accounts for 51.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍20251.8%
🔥18747.9%
👎10.256%

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 21 of the 21 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 390reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 21 most recent posts we hold, published 3 December 2025 to 7 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

7 Aug 2026, 04:13 UTC593 views10 reactionsread 7 August 2026

Запустили опрос python-разработчиков про типизацию - в авторах опроса Astral, JetBrains, Microsoft, Meta, discuss.python.org - т.е. очень многие из тех кто реально занимается типаии/туллингом. Это ежегодная история, предыдущий отчет тут https://engineering.fb.com/2025/12/22/developer-tools/python-typing-survey-2025-code-quality-flexibility-typing-adoption/ - мы кажется обсуждали его в подкасте. Если вы активно испол

🔥7👍3

6 Aug 2026, 09:26 UTC655 views11 reactionsread 7 August 2026

Уже завтра в 14:00 (по мск) обсудим новости июля в прямом эфире Moscow Python Podcast 🎙 Разберём самые интересные события последних недель: 🟤 PEP 836: новый план развития JIT-компилятора для CPython; 🟤 Ruff 0.16: теперь по умолчанию включены 413 правил вместо 59; 🟤 GitHub усиливает безопасность CI; 🟤 Релиз Django 6.1; 🟤 Обсудим статью In Defense of Not Understanding Your Codebase. 📍 Когда и во сколько: 7 августа в

🔥11

6 Aug 2026, 05:45 UTC723 views16 reactionsread 7 August 2026

Вышел релиз Django 6.1. Изменений не очень много: - QuerySet.fetch_mode позволяет более гибко управлять тем, что происходит при обращении к незагруженному полю модели - делать запрос в базу, делать запрос загружая связанные сущности одним запросом или выдавать исключение. Выглядит как действительно полезная фича - on_delete для ForeignKey теперь можно перевесить на уровень базы данных через SQL ON DELETE, раньше это

👍15👎1

4 Aug 2026, 10:41 UTC929 views8 reactionsread 7 August 2026

Вместе с прогрессом llm-ок растет нагрузка на мейнтенеров проектов, это не новость и мы много раз обсуждали это в подкасте. Но вот подъехала статья с нитересными графиками по нагрузке именно связанноы с безопасностью: - Security-отчеты на github - ~40 за весь 2025 и уже 175 за первую половину 2026 - Полноценные CVE - ~20 за 2025 и столько же только за первую треть 2026, т.е. за весь год предполагается рост в три раз

👍8

3 Aug 2026, 06:45 UTC≈1,040 views37 reactionsread 7 August 2026

Поддержка free-threading в библиотеках сейчас один из ключевых блокеров перехода на free-treading. Поэтому я с интересом читаю статьи, которые публикуют на этот счет разработчики библиотек - не то чтобы мне это было нужно для работы, просто очень интересно. На днях наткнулся на статью, про оптимизацию NumPy - проблема была в том, что с отключенным GIL, ThreadPoolExecutor все равно работал медленнее, чем ProcessPoolEx

🔥32👍5

30 Jul 2026, 08:09 UTC≈1,420 views16 reactionsread 7 August 2026

Вышла библиотека django-orjson, которая позволяет легко перевести Django и DRF на быстрый orjson. В комплекте — JsonResponse, renderer и parser для DRF и даже сериализатор для сессий. В принципе, идея не новая: мы у себя перевели DRF на orjson ещё года четыре назад. Но с готовым пакетом это будет гораздо проще сделать. Тем, у кого плюс-минус нагруженный проект или просто большие JSON-запросы и ответы, рекомендую при

👍16

29 Jul 2026, 05:12 UTC≈1,390 views17 reactionsread 7 August 2026

GitHub запустил пару полезных фич для безопасности CI. Во-первых, Malware Alerts. Эта штука проверяет, нет ли зависимостей проекта в базе OpenSSF Malicious Packages, и, если находит совпадение, присылает алерт. Глобально включить её пока нельзя — только отдельно для каждого репозитория. Я у себя уже включил, вот тут инструкция https://docs.github.com/en/code-security/how-tos/secure-your-supply-chain/secure-your-depe

👍17

28 Jul 2026, 03:20 UTC≈1,450 views34 reactionsread 7 August 2026

Вышла новая версия Ruff 0.16. Казалось бы, минорный релиз, но на самом деле нет. Теперь по умолчанию включено 413 правил вместо 59, поэтому, если в конфиге у вас не зафиксирован список правил, используемых на проекте, вас ждёт сюрприз. Ради интереса прогнал Ruff на своём пет-проекте, где до обновления всё было зелёненьким. После перехода на 0.16 получил: Found 50 errors, 34 fixable. Пойду чинить 🙂 Если планируете об

👍34

27 Jul 2026, 04:48 UTC≈1,250 views15 reactionsread 7 August 2026

Прикольный проект — интерпретатор «старого» Бейсика на Python. Сам проект маленький, всего около 1000 строк, поэтому, если вам интересно немного разобраться в том, как работают интерпретаторы, рекомендую посмотреть: https://github.com/nedbat/acidica

👍12🔥3

3 Jul 2026, 06:53 UTC≈1,860 views12 reactionsread 7 August 2026

Уже сегодня в 14:00 (по мск) обсудим новости июня в прямом эфире Moscow Python Podcast 🎙 Обсудим с Никитой Соболевым последние интересные релизы: 🟤Что нового будет в Python 3.15 🟤Django 6.1 Beta: главные изменения и новые возможности 🟤PEP 835: сокращённый синтаксис для метаданных Annotated 🟤Небезопасные подсказки кода: можно ли считать их уязвимостью? Основные ведущие: Михаил Корнеев и Григорий Петров 📍Когда и во

🔥12

9 Jun 2026, 10:50 UTC≈2,040 views14 reactionsread 7 August 2026

Завтра, 10 июня обсудим новости мира Python в прямом эфире Moscow Python🎙 Перенесли выпуск с пятницы на эту среду, а всё остальное будет, как вы любите — обсудим новости с Мишей Корнеевым и Гришей Петровым. 📍Когда и во сколько: 10 июня в 14:00 по Москве. Подключайтесь к удобной площадке YouTube / Rutube / на VK Видео ссылка будет позже

👍12🔥2

1 May 2026, 06:29 UTC≈2,370 views15 reactionsread 7 August 2026

Сегодня в первую пятницу месяца как обычно в 14:00 (по мск) обсудим новости апреля в прямом эфире Moscow Python Podcast 🎙 Новости про откат GC, packaging и жизнь с БД в эпоху агентов Ведущие: Михаил Корнеев и Григорий Петров 📍Когда и во сколько: 1 мая в 14:00 по Москве. Подключайтесь к удобной площадке YouTube / Rutube / VK Видео

🔥15

Showing the 12 most recent of 21 posts we hold for @tricky_python. 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 — 454,785 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.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

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

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 August 2026 — this entry's latest reading, not the date you are reading this.

“Хитрый Питон” (@tricky_python), 2,510 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/tricky_python.

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.