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Channel

Python Learning

@Python_per_month

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

28,238subscribers

-415 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001500680235
TypeChannel
Username@Python_per_month
Description№ 4974297878 Обучающий канал по Python Ссылка для друга - https://t.me/+I7jrAQKR5xAyYTAy По всем вопросам @mascarov_valentin Реклама на бирже - https://telega.in/c/Python_per_month
CreatedBetween 1 July 2021 and 28 February 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live26 September 2026
Measurements held36
Confirmed unchanged1 time, most recently 26 September 2026
On Telegramt.me/Python_per_month

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 10 September 2026 and assigned it the closest of 31 fixed categories, at 59% 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

28,23828,65328,445.57 August 2026 — 28,653 subscribers7 August 2026 — 28,653 subscribers7 August 2026 — 28,652 subscribers8 August 2026 — 28,645 subscribers9 August 2026 — 28,633 subscribers10 August 2026 — 28,625 subscribers11 August 2026 — 28,622 subscribers12 August 2026 — 28,608 subscribers13 August 2026 — 28,601 subscribers14 August 2026 — 28,582 subscribers16 August 2026 — 28,574 subscribers17 August 2026 — 28,568 subscribers18 August 2026 — 28,553 subscribers19 August 2026 — 28,546 subscribers20 August 2026 — 28,532 subscribers21 August 2026 — 28,527 subscribers22 August 2026 — 28,511 subscribers24 August 2026 — 28,493 subscribers25 August 2026 — 28,482 subscribers26 August 2026 — 28,474 subscribers27 August 2026 — 28,470 subscribers28 August 2026 — 28,466 subscribers29 August 2026 — 28,459 subscribers30 August 2026 — 28,457 subscribers31 August 2026 — 28,446 subscribers1 September 2026 — 28,433 subscribers2 September 2026 — 28,420 subscribers3 September 2026 — 28,403 subscribers5 September 2026 — 28,389 subscribers9 September 2026 — 28,368 subscribers11 September 2026 — 28,347 subscribers13 September 2026 — 28,336 subscribers15 September 2026 — 28,319 subscribers17 September 2026 — 28,305 subscribers19 September 2026 — 28,283 subscribers26 September 2026 — 28,238 subscribers7 August 202626 September 2026
36 measurements spanning 51 days, net -415. 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 28,176–28,715 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)SubscribersChange
26 Sept 2026, 18:0128,238-45
19 Sept 2026, 15:1928,283-22
17 Sept 2026, 02:1828,305-14
15 Sept 2026, 00:3628,319-17
13 Sept 2026, 12:3728,336-11
11 Sept 2026, 15:5528,347-21
9 Sept 2026, 00:3928,368-21
5 Sept 2026, 16:5628,389-14
3 Sept 2026, 17:3728,403-17
2 Sept 2026, 12:3428,420-13
1 Sept 2026, 11:3528,433-13
31 Aug 2026, 13:3528,446-11
30 Aug 2026, 12:5528,457-2
29 Aug 2026, 10:4328,459-7
28 Aug 2026, 08:1328,466-4
27 Aug 2026, 07:2428,470-4
26 Aug 2026, 10:0428,474-8
25 Aug 2026, 13:0528,482-11
24 Aug 2026, 12:1528,493-18
22 Aug 2026, 20:4828,511first reading

Engagement

23 posts held, back to 23 January 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 70 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
5.91%
avg views ÷ 28,238 subscribers
Avg views / post
1,670
1 post measured
Reaction rate
0.359%
reactions ÷ views · ER floor
Posts in window
1
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 14 September 2026
Posts held23 (23 January 2026 – 14 September 2026)
Views total1,670
Reactions total6
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken27 Sept 2026, 19:39 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
≈2,000
Videos
≈8
Links
≈1,020

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.

Reaction mix

173 reactions across 23 posts, in 10 distinct kinds. The most used accounts for 86.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍15086.7%
🔥52.89%
🍾42.31%
🤔42.31%
❤‍🔥21.16%
🆒21.16%
🎉21.16%
😁21.16%
💔10.578%
🥰10.578%

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 173 reactions 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 23 January 2026 to 14 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.

Advertising

Ad load
13.0%
3 of 23 posts carry an ad marker
Regulatory tokens
3
posts carrying an erid · 3 distinct tokens
Median views · ads
3,900
over 3 measured posts
Median views · rest
4,380
over 20 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
2Vtzqw9sKdb123 June 202623 June 2026
2VtzqwRtpJu19 July 20269 July 2026
2VtzqwWTgtz113 July 202613 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 23 January 2026 to 14 September 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

14 Sept 2026, 08:18 UTC≈1,670 views6 reactionsread 27 September 2026
Photo

➡️ Memray — профилирование памяти для Python Memray — это современный инструмент для профилирования памяти в Python, разработанный командой Bloomberg. Он позволяет детально отслеживать выделение и использование памяти в ваших приложениях, что помогает выявлять утечки и оптимизировать производительность. • Глубокий анализ: Memray отслеживает все выделения памяти, включая те, что происходят в нативных расширениях на …

👍5🔥1

17 Aug 2026, 17:13 UTC≈3,060 views15 reactionsread 27 September 2026
Photo

Срезы Срезы (slices) в Python — это способ получения подстроки (подсписка) из последовательности, такой как строка (str), список (list) или кортеж (tuple). Python Learning 👩‍💻

👍13🎉1🥰1

11 Aug 2026, 16:12 UTC≈3,720 views6 reactionsread 27 September 2026
Photo

Нейросеть, LLM (большие языковые модели) и ИИ-агент Эти слова в разговорах часто используют как синонимы. Но за ними стоят разные механизмы, и от того, с чем вы работаете, зависит результат. LLM генерирует текст на основе того, на чем ее обучили. Запускается только по запросу человека, работает в один цикл «промпт → ответ», между сессиями ничего не помнит и умеет ровно одно — писать текст. Как эрудированный консуль…

👍5🔥1

23 Jul 2026, 09:08 UTC≈4,080 views4 reactionsread 27 September 2026
Photo

👩‍💻 Задача по Python Создайте функцию find_longest_substring для поиска самой длинной подстроки в строке, содержащей уникальные символы. Функция должна возвращать длину этой подстроки. Пример: print(find_longest_substring("abcabcbb")) # Вернёт 3, т.к. самая длинная уникальная подстрока "abc" print(find_longest_substring("bbbbb")) # Вернёт 1, т.к. самая длинная уникальная подстрока "b" print(find_longest_subst…

👍4

13 Jul 2026, 14:10 UTC≈4,040 views2 reactionsread 27 September 2026
Advertisementerid 2VtzqwWTgtz

🔥 Три разных человека. Три разных проекта. Один и тот же подход. — Юра взял «скучную» нишу с готовым спросом → сначала печальные $100/мес, через год уже ~$10K/мес — Денис сделал Telegram-игру в одиночку на основе AI → ~ $1500 за 1,5 месяца после запуска — Аня без кода запустила AI-бота для изучения английского → первые ~$200 уже в 1 месяц Разные результаты. Разный масштаб. Но общие правила: 1. не придумывать «гени…

👍1💔1

11 Jul 2026, 17:50 UTC≈3,530 views13 reactionsread 27 September 2026
Photo

⚙️ enumerate() Когда тебе нужно итерировать по списку с доступом к индексу элемента, используй enumerate(). Эта встроенная функция возвращает и индекс, и сам элемент в одном цикле, что удобно и лаконично. Python Learning 👩‍💻

👍12🔥1

9 Jul 2026, 14:56 UTC≈3,610 views6 reactionsread 27 September 2026
Advertisementerid 2VtzqwRtpJuPhoto

Почему Python — основной язык в offensive security? Большинство задач в ИБ так или иначе упирается в скрипты: автоматизация, работа с сетью, парсинг, фаззинг, свои утилиты под конкретную инфраструктуру. Готовых инструментов часто недостаточно — нужен код, который можно написать и доработать под себя. Python для Пентестера от Codeby — курс для тех, кто уже знает Python на базовом уровне и хочет применять его в инфор…

👍2🍾1🔥1😁1🆒1

9 Jul 2026, 14:55 UTC≈2,730 views4 reactionsread 27 September 2026

❓ Вопрос на собеседовании Как в Python работают функции с переменным количеством аргументов (*args и **kwargs), и как это можно использовать для создания гибких функций? Ответ ⬇️ Функции с *args принимают произвольное количество позиционных аргументов, а с **kwargs — именованных аргументов. Это позволяет передавать любое количество значений и делать интерфейс функций более гибким. *args упаковывает аргументы в корт…

👍4

2 Jul 2026, 14:04 UTC≈3,330 views6 reactionsread 27 September 2026
Photo

➡️ Использование cachetools для кэширования в Python cachetools — это небольшая, но мощная библиотека для кэширования, которая предоставляет различные стратегии кэширования, такие как LRU (Least Recently Used), LFU (Least Frequently Used) и другие. Она позволяет оптимизировать производительность, избегая повторных вычислений или запросов. • cachetools полезна, когда требуется хранить временные результаты или промеж…

👍5😁1

23 Jun 2026, 17:08 UTC≈3,900 views1 reactionsread 27 September 2026
Advertisementerid 2Vtzqw9sKdbPhoto

🔍Тестовое собеседование на Middle Python с разработчиком из Авито завтра вечером Уже завтра вечером в 19:00 по мск приходи онлайн на открытое собеседование, чтобы посмотреть на настоящее интервью на Middle Python-разработчика. Как это будет: 📂 Даня, старший разработчик в Авито, будет задавать реальные вопросы и задачи разработчику-добровольцу 📂 Даня будет комментировать каждый ответ респондента, чтобы дать понять ч…

👍1

17 Jun 2026, 15:38 UTC≈4,120 views4 reactionsread 27 September 2026
Photo

➡️ Использование функции itertools.tee() для дублирования итераторов itertools.tee() — это интересная функция из модуля itertools, позволяющая создавать несколько независимых копий одного и того же итератора. 🗣️ Это полезно, когда вам нужно одновременно итерировать по одним и тем же данным в разных частях кода, не повторяя вычисления. ✔️ itertools.tee() делает работу с итераторами гибче и удобнее. Python Learning…

👍4

28 May 2026, 08:52 UTC≈4,750 views11 reactionsread 27 September 2026
Photo

Библиотека python-decouple Библиотека python-decouple для Python помогает отделить конфигурационные параметры от вашего исходного кода. Это означает, что вы можете хранить секретные данные, такие как ключи API, пароли и URL-адреса базы данных, вне вашего кода, улучшая безопасность. Python Learning 👩‍💻

👍8❤‍🔥2🆒1

Showing the 12 most recent of 23 posts we hold for @Python_per_month. 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.

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.

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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#75
Python Вакансии Junior/Middle
@p_rabota · 4,682
#76
Open IT | Программирование
@openit_tg · 34,867
#77
GitHub Community
@github · 155,991
#78
Эксплойт
@exploitex · 2,048,279
#79
Бэкдор
@whackdoor · 1,603,481
#80
CodeCamp
@codecamp · 181,043
#81
Python Tasks & ML | Задачи по питону и машинному обучению
@python_tasks · 8,520
#82
Physics.Math.Code
@physics_lib · 146,712
#83
Технотренды
@techno_media · 790,765
#84
Не баг, а фича
@bugfeature · 571,363
#85
Windows Community
@wind_community · 41,313
#86

Read from Telegram’s recommendation API, most recently 9 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 и 1000 уязвимостей
@osint_pythons · 36,535
Telegram ranks this channel #3 of 84 here — alongside 83 others — read 1 September 2026
Senior Python Developer
@seniorpy · 39,864
Telegram ranks this channel #3 of 92 here — alongside 91 others — read 30 August 2026
Python обучающий
@pythonist24 · 55,872
Telegram ranks this channel #5 of 88 here — alongside 87 others — read 23 August 2026
Однажды в трендах
@trendo · 67,788
Telegram ranks this channel #7 of 90 here — alongside 89 others — read 20 August 2026
Python Hacks
@python_secrets · 40,594
Telegram ranks this channel #13 of 82 here — alongside 81 others — read 30 August 2026
Python Academy
@python_academy · 44,284
Telegram ranks this channel #14 of 87 here — alongside 86 others — read 28 August 2026
[PYTHON:TODAY]
@python2day · 63,764
Telegram ranks this channel #16 of 91 here — alongside 90 others — read 21 August 2026
Pythonist.ru - образование по питону
@pythonist_ru · 24,046
Telegram ranks this channel #17 of 82 here — alongside 81 others — read 17 September 2026
Python Developer
@python_tg · 20,963
Telegram ranks this channel #19 of 85 here — alongside 84 others — read 25 September 2026
Python Portal
@PythonPortal · 50,417
Telegram ranks this channel #25 of 80 here — alongside 79 others — read 25 August 2026
Python/ django
@pythonl · 58,866
Telegram ranks this channel #29 of 84 here — alongside 83 others — read 22 August 2026
Простой Python | Программирование
@python_piton_javascript · 126,249
Telegram ranks this channel #38 of 84 here — alongside 83 others — read 13 August 2026
Библиотека питониста | Python, Django, Flask
@pyproglib · 37,384
Telegram ranks this channel #39 of 84 here — alongside 83 others — read 1 September 2026
Базы данных | Access, SQL, Big Data
@databases_secrets · 30,002
Telegram ranks this channel #41 of 82 here — alongside 81 others — read 7 September 2026
Python вопросы с собеседований
@python_job_interview · 24,881
Telegram ranks this channel #43 of 90 here — alongside 89 others — read 15 September 2026
Python learning
@python3learning · 22,563
Telegram ranks this channel #60 of 71 here — alongside 70 others — read 20 September 2026
Полка Разработчика
@developer_shelf · 26,815
Telegram ranks this channel #62 of 63 here — alongside 62 others — read 11 September 2026
Python Job | Вакансии | Стажировки
@job_python · 23,025
Telegram ranks this channel #68 of 96 here — alongside 95 others — read 19 September 2026
Поколение Python 🐍
@pygen_ru · 50,072
Telegram ranks this channel #69 of 93 here — alongside 92 others — read 25 August 2026
Windows Community
@wind_community · 41,313
Telegram ranks this channel #71 of 74 here — alongside 73 others — read 29 August 2026

This channel appears in 20 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 26 September 2026 — this entry's latest reading, not the date you are reading this.

“Python Learning” (@Python_per_month), 28,238 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/Python_per_month.

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.