Telegram RegisterThe public register of Telegram
Telegram profile photo for Python/ django

Channel

Python/ django

@pythonl

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Stars · Advertising · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

58,935subscribers

-226 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-1001119855053
TypeChannel
Username@pythonl
Created24 October 2017measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live22 August 2026
Measurements held17
Confirmed unchanged1 time, most recently 22 August 2026
On Telegramt.me/pythonl

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 100% 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
@pythonl/5648 · this entry7 Aug 2026, 10:15 UTC@Python_Community_ru/32347 Aug 2026, 15:57 UTC0.995.7 hours
@pythonl/5645 · this entry5 Aug 2026, 20:53 UTC@Python_Community_ru/32305 Aug 2026, 22:03 UTC0.9970 minutes
@pythonl/5643 · this entry5 Aug 2026, 11:09 UTC@Python_Community_ru/32295 Aug 2026, 16:04 UTC0.994.9 hours
@pythonl/5634 · this entry1 Aug 2026, 10:24 UTC@Python_Community_ru/32201 Aug 2026, 16:20 UTC0.995.9 hours
@pythonl/5627 · this entry29 Jul 2026, 11:01 UTC@Python_Community_ru/321629 Jul 2026, 16:32 UTC0.995.5 hours
@pythonl/5625 · this entry28 Jul 2026, 12:40 UTC@Python_Community_ru/321428 Jul 2026, 16:36 UTC0.993.9 hours
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@Python_Community_ru10 (8/8 hand-verifiable sample passed)0.994.0 hoursthis entry (100)

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 28 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 @pythonl — 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

58,88059,16159,020.56 August 2026 — 59,161 subscribers6 August 2026 — 59,148 subscribers7 August 2026 — 59,131 subscribers8 August 2026 — 59,110 subscribers9 August 2026 — 59,086 subscribers10 August 2026 — 59,074 subscribers11 August 2026 — 59,047 subscribers12 August 2026 — 59,027 subscribers13 August 2026 — 59,004 subscribers15 August 2026 — 58,986 subscribers16 August 2026 — 58,954 subscribers17 August 2026 — 58,939 subscribers18 August 2026 — 58,903 subscribers19 August 2026 — 58,880 subscribers20 August 2026 — 58,901 subscribers21 August 2026 — 58,900 subscribers22 August 2026 — 58,935 subscribers58,9356 August 202622 August 2026
17 measurements spanning 17 days, net -226. 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 58,838–59,203 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
22 Aug 2026, 22:3658,935+35
21 Aug 2026, 15:2758,900-1
20 Aug 2026, 16:1558,901+21
19 Aug 2026, 19:4258,880-23
18 Aug 2026, 20:1558,903-36
17 Aug 2026, 22:2858,939-15
16 Aug 2026, 19:3758,954-32
15 Aug 2026, 05:0458,986-18
13 Aug 2026, 18:1459,004-23
12 Aug 2026, 14:2459,027-20
11 Aug 2026, 13:3459,047-27
10 Aug 2026, 12:3159,074-12
9 Aug 2026, 11:3159,086-24
8 Aug 2026, 14:0659,110-21
7 Aug 2026, 16:0059,131-17
6 Aug 2026, 16:2559,148-13
6 Aug 2026, 02:1859,161first reading

Engagement

43 posts held, back to 28 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 36 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
5.60%
avg views ÷ 58,935 subscribers
Avg views / post
3,300
43 posts measured
Reaction rate
0.503%
reactions ÷ views · ER floor
Posts in window
43
of 43 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 22 August 2026
Posts held43 (28 July 202622 August 2026)
Views total141,995
Reactions total714
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken22 Aug 2026, 13:51 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

Video runtime
24s
Average length
12s

Measured directly from 2 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

688 reactions across 40 posts, in 8 distinct kinds. The most used accounts for 31.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥21831.7%
20229.4%
👍19628.5%
🎉355.09%
😁273.92%
😱71.02%
🤩20.291%
😢10.145%

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 43 of the 43 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 714reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 43 most recent posts we hold, published 28 July 2026 to 22 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.

Telegram Stars

Stars received
6
across the posts below
Posts paid on
2
of 43 we hold a reading for · 5%
Most on one post
5
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @pythonl. 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 43 most recent posts we hold for this entry, published 28 July 2026 to 22 August 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
6.98%
3 of 43 posts carry an ad marker
Regulatory tokens
3
posts carrying an erid · 3 distinct tokens
Median views · ads
3,320
over 3 measured posts
Median views · rest
3,200
over 40 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
2VSb5xGRBaJ111 August 202611 August 2026
2Vtzqv3yWu814 August 20264 August 2026
2W5zFJomh13130 July 202630 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 43 most recent posts we hold, published 28 July 2026 to 22 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

22 Aug 2026, 12:04 UTC485 views6 reactions1 Starread 22 August 2026
Photo

🔥 Хочешь быстрее расти в IT? Хватит учиться в одиночку Окружение решает больше, чем кажется. Собрал папки и каналы, где можно быстрее влиться в нужное направление, следить за трендами и не вариться в своём пузыре. AI: t.me/ai_machinelearning_big_data Python: t.me/pythonl Linux: t.me/linuxacademiya Хакинг: t.me/linuxkalii DevOps: t.me/DevOPSitsec Docker: https://t.me/+90Z5TAyfuNU5YmRi Golang: t.me/Golang_google Rus

2👍2🤩1😁1

21 Aug 2026, 11:04 UTC≈1,810 views15 reactionsread 22 August 2026
Photo

Python Game Server: простой сервер для пошаговых мультиплеерных игр python-game-server — лёгкий open source-фреймворк на Python для создания пошаговых мультиплеерных игр. Он даёт готовую серверную основу, чтобы не писать с нуля комнаты, игровые сессии и сетевое взаимодействие. Из коробки есть: — единый API для разных игр — несколько параллельных игровых сессий — подключение к конкретной комнате — автоматический в

🔥64👍4🎉1

20 Aug 2026, 16:12 UTC≈2,150 views8 reactionsread 22 August 2026
Photo

Для тех, кто работает с ACP-агентами из терминала, появился простой REPL acp-repl запускает любой stdio-сервер с поддержкой Agent Client Protocol и позволяет общаться с агентом прямо из терминала: отправлять промпты, создавать сессии, переключать модель и режим, обрабатывать permission-запросы и смотреть debug-логи. Работает не с одним конкретным агентом. В README есть примеры для OpenCode, Codex, Claude Code и Pi,

👍42🔥2

20 Aug 2026, 14:12 UTC≈2,030 views7 reactionsread 22 August 2026
Photo

25 августа встречаемся на Agentic Coding Meetup в Сбер.Среде и в онлайне⚡️ AI-агенты уже умеют писать код. Но самое интересное начинается дальше — когда вместе с инструментами меняются роли инженеров, команды и сам процесс разработки. 🔥 Поговорим о том, как agentic coding выглядит на практике: новые инженерные роли и модели команд, SDD и трансформация процессов, coding-агенты и инструменты, подходы к постановке зад

👍5🔥1😁1

20 Aug 2026, 11:50 UTC≈2,140 views14 reactionsread 22 August 2026

Как нормально тестировать AI-агента, если правильный ответ ещё ничего не доказывает У обычного чат-бота можно проверить финальный ответ. С агентами этого уже мало: модель может выдать вполне убедительный текст, но перед этим выбрать не тот skill, вызвать неправильный tool, потерять контекст на втором сообщении или выполнить только половину задачи. Ed Crewe описал, как они строили eval-фреймворк для агентного чат-бо

5👍5🔥2🎉1😁1

19 Aug 2026, 13:45 UTC≈2,330 views20 reactionsread 22 August 2026
Photo

🖥 Для Python появился Interlock - современный circuit breaker без зоопарка отдельных решений для sync и async. Один CircuitBreaker умеет работать и с обычными функциями, и с async, считать процент ошибок по скользящему окну и отдельно реагировать на слишком медленные вызовы. Можно собрать полноценный pipeline отказоустойчивости: pipeline = ( Pipeline.builder() .fallback(...) .retry(attempts=4) .ci

👍85🔥5🎉2

18 Aug 2026, 19:25 UTC≈3,130 views69 reactions5 Starsread 22 August 2026
Video

Разница между C++ и Python

🔥33😁189👍6🎉2😱1

18 Aug 2026, 16:45 UTC≈3,100 views9 reactionsread 22 August 2026
Photo

⚡️ Harness Engineering - полный курс на русском Как заставить AI-агента писать код надёжно. Не «какую модель выбрать», а как спроектировать вокруг неё рабочую систему: инструкции, инструменты, среду, состояние и верификацию. Курс - от нуля до продвинутых тем: теоретическая база из 11 блоков, 14 модулей, 8 практических проектов, 14 лабораторных работ, диагностический протокол «как починить агента», библиотека готовы

🔥53👍1

18 Aug 2026, 10:00 UTC≈2,940 views22 reactionsread 22 August 2026
Photo

🔥 DeepSeek Harness - пример того, почему сегодня важна не только модель, но и всё окружение вокруг неё Harness - это слой между LLM и реальной работой: инструменты, terminal, permissions, память, tool loop и правила обработки ответов. У deepseek-harness есть Python-библиотека, CLI dsh, MCP-сервер и интеграция в формате Anthropic Skill. Проект документирует особенности протокола DeepSeek V4-Pro/V4-Flash и автоматиче

9👍7🔥5🎉1

17 Aug 2026, 15:01 UTC≈2,970 views17 reactionsread 22 August 2026
Photo

Полный инженерный курс по AI-агентам на русском: от tool calling до production Курс инженерный, а не обзорный. Здесь почти нет рассуждений о том, «изменит ли ИИ мир», зато есть: минимальные работающие реализации каждого механизма, лабораторные с критериями приёмки, шаблоны для копирования, чек-листы перед релизом, каталог антипаттернов и набор бенчмарков, по которым можно честно сравнить две версии своего агента.

👍11🔥42

16 Aug 2026, 12:00 UTC≈3,010 views16 reactionsread 22 August 2026
Photo

🐍 Python-разработчики часто тестируют код с зависимостью от времени. Но обычный mock для дат — это намного сложнее, чем кажется. Библиотека time-machine решает эту проблему: она позволяет буквально «перемещать время» внутри тестов. Например: import datetime as dt import time_machine @time_machine.travel("2030-01-01") def test_future(): assert dt.date.today() == dt.date(2030, 1, 1) В отличие от популярных п

👍8🔥53

15 Aug 2026, 12:02 UTC≈3,100 views15 reactionsread 22 August 2026

🐍 Опытный Python-разработчик рассказал, для каких проектов в 2026 году он уже не выбирает Python первым. Автор десятилетиями использовал Python практически для всего, но со временем пришёл к простой мысли: хороший универсальный язык не обязан быть лучшим инструментом для каждой задачи. В презентации разбирается, где ограничения Python начинают перевешивать его удобство и почему для некоторых проектов сегодня разумн

5👍5🔥5

Showing the 12 most recent of 43 posts we hold for @pythonl. 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.

Citation-graph rank

Citation-graph rank — 18,512 of 1,584,142entries 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

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 37 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.

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.

Machinelearning
@ai_machinelearning_big_data · 284,523
#1
Анализ данных (Data analysis)
@data_analysis_ml · 50,530
#2
Python вопросы с собеседований
@python_job_interview · 24,786
#3
Python RU
@pro_python_code · 12,387
#4
📚Python Books
@pythonlbooks · 33,588
#5
Data Science. SQL hub
@sqlhub · 35,873
#6
Data Science
@datascienceiot · 42,492
#7
Математика Дата саентиста
@data_math · 14,134
#8
[PYTHON:TODAY]
@python2day · 63,879
#9
Django Python
@Django_pythonl · 6,620
#10
Kali Linux
@linuxkalii · 55,091
#11
Python Developer
@python_tg · 21,017
#12
Big Data AI
@bigdatai · 18,149
#13
Машинное обучение RU
@machinelearning_ru · 18,144
#14
Machine learning Interview
@machinelearning_interview · 30,152
#15
Python Jobs
@python_djangojobs · 14,541
#16
Машиннное обучение | Наука о данных Библиотека
@machinelearning_books · 16,837
#17
Библиотека питониста | Python, Django, Flask
@pyproglib · 37,524
#18
Linux Academy
@linuxacademiya · 28,250
#19
Senior Python Developer
@seniorpy · 40,158
#20
IT Portal
@IT_Portal · 101,184
#21
Data Science Jobs
@datascienceml_jobs · 21,029
#22
Rust
@rust_code · 8,724
#23
Простой Python | Программирование
@python_piton_javascript · 128,051
#24
Artificial Intelligence
@ArtificialIntelligencedl · 16,784
#25
Python | Вопросы собесов
@python_easy_ru · 12,815
#26
PyLinux - Всё о Linux, Python и IT
@pylinux0 · 11,011
#27
C++ Academy
@cpluspluc · 15,468
#28
Python Learning
@Python_per_month · 28,511
#29
Python и 1000 уязвимостей
@osint_pythons · 36,612
#30
Аналитик данных
@dataanlitics · 6,207
#31
Python — вакансии и стажировки
@pythonpythonjobs · 7,288
#32
Python Portal
@PythonPortal · 51,126
#33
Однажды в трендах
@trendo · 68,975
#34
python_practics
@python_practics · 5,177
#35
Neural Networks | Нейронные сети
@neural · 11,517
#36
Data Science | Machinelearning [ru]
@devsp · 19,804
#37
Linux Books
@linux_read · 16,009
#38
Python | LeetCode
@easy_python_task · 9,189
#39
Pythoner
@pythonercode · 6,631
#40
Zen of Python
@zen_of_python · 18,978
#41
Python Job | Вакансии | Стажировки
@job_python · 22,620
#42
Библиотека С# С++
@cpluscsharp · 10,054
#43
Pro Python • IT
@PythonTechCode · 4,188
#44
Библиотека задач по Python | тесты, код, задания
@py_problems_lib · 6,442
#45
Python Academy
@python_academy · 44,600
#46
Хабр
@habr_com · 131,678
#47
Python Hacks
@python_secrets · 40,807
#48
XOR
@xor_journal · 152,006
#49
Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение
@dsproglib · 18,385
#50
Библиотека программиста
@proglibrary · 78,409
#51
Библиотека программиста
@devs_storage · 19,241
#52
Библиотека Кодера
@library_dev · 5,257
#53
About Python [ru]
@python_tesst · 6,488
#54
Python | Тесты
@easy_python_tests · 5,889
#55
Библиотека собеса по Python | вопросы с собеседований
@py_interview_lib · 5,944
#56
IT Syndicate
@ITSyndicate_23 · 8,736
#57
Golang Books
@golang_books · 16,938
#58
Python | Программирование
@Python_libr · 9,002
#59
Python jobs — вакансии по питону, Django, Flask
@pydevjob · 9,581
#60
Java Books
@java_library · 14,238
#61
Python tests
@python_testit · 6,880
#62
DevOps
@DevOPSitsec · 23,514
#63
Golang
@Golang_google · 40,290
#64
Искусственный интеллект. Высокие технологии
@vistehno · 72,222
#65
Data Secrets
@data_secrets · 92,304
#66
эйай ньюз
@ai_newz · 96,240
#67
Javascript
@javascriptv · 17,192
#68
Physics.Math.Code
@physics_lib · 145,896
#69
PHP Academy
@phpshka · 9,226
#70
Английский для программистов
@english_forprogrammers · 8,259
#71
Social Engineering
@Social_engineering · 125,143
#72
GitHub Community
@github · 152,669
#73
Denis Sexy IT 🤖
@denissexy · 135,227
#74
Java
@javatg · 16,763
#75
Сиолошная
@seeallochnaya · 77,781
#76
CodeCamp
@codecamp · 182,669
#77
UzDev Jobs – IT Jobs
@uzdev_jobs · 25,740
#78
Programmer & IT Memes
@itmemes · 124,335
#79
DeepSchool
@deep_school · 10,675
#80
infosec
@it_secur · 61,139
#81
Python Tasks & ML | Задачи по питону и машинному обучению
@python_tasks · 8,557
#82
Github
@github_code · 2,518
#83
Инжиниринг Данных
@rockyourdata · 23,811
#84

Read from Telegram’s recommendation API, most recently 22 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.

Однажды в трендах
@trendo · 68,975
Telegram ranks this channel #8 of 90 here — alongside 89 others — read 20 August 2026
Простой Python | Программирование
@python_piton_javascript · 128,051
Telegram ranks this channel #8 of 84 here — alongside 83 others — read 13 August 2026
[PYTHON:TODAY]
@python2day · 63,879
Telegram ranks this channel #19 of 91 here — alongside 90 others — read 21 August 2026
Machinelearning
@ai_machinelearning_big_data · 284,523
Telegram ranks this channel #20 of 95 here — alongside 94 others — read 10 August 2026
IT Portal
@IT_Portal · 101,184
Telegram ranks this channel #27 of 78 here — alongside 77 others — read 15 August 2026
PythonNotes
@pythonnotes1 · 78,494
Telegram ranks this channel #30 of 69 here — alongside 68 others — read 19 August 2026
Naresh IT
@nareshit · 61,269
Telegram ranks this channel #48 of 67 here — alongside 66 others — read 22 August 2026
Curious Coder
@Curious_Coder · 136,420
Telegram ranks this channel #67 of 75 here — alongside 74 others — read 13 August 2026
Искусственный интеллект. Высокие технологии
@vistehno · 72,222
Telegram ranks this channel #69 of 94 here — alongside 93 others — read 20 August 2026
Artificial Intelligence
@Artificial_intelligence_in · 65,539
Telegram ranks this channel #71 of 90 here — alongside 89 others — read 21 August 2026
Machine Learning with Python
@CodeProgrammer · 68,188
Telegram ranks this channel #73 of 84 here — alongside 83 others — read 20 August 2026
Computer Science and Programming
@computer_science_and_programming · 140,868
Telegram ranks this channel #75 of 87 here — alongside 86 others — read 13 August 2026
Python Projects & Resources
@pythondevelopersindia · 63,316
Telegram ranks this channel #81 of 86 here — alongside 85 others — read 21 August 2026
Python Programming Books
@dsabooks · 59,037
Telegram ranks this channel #87 of 89 here — alongside 88 others — read 22 August 2026

This channel appears in 14 seed channels' Telegram-generated recommendation lists in total. 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 22 August 2026 — this entry's latest reading, not the date you are reading this.

“Python/ django” (@pythonl), 58,935 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/pythonl.

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.