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Channel
Python Hacks
@python_secrets
On this record: Topic · Growth · Engagement · What this channel posts · Advertising · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry
40,332subscribers
-628 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 | -1001374393457 |
|---|---|
| Type | Channel |
| Username | @python_secrets |
| Description | Всё о языке Python простым языком. По всем вопросам: @max_excel РКН: vk.cc/cHhGJh |
| Created | 23 November 2019 — measured — cross-checked against a third-party dataset (TGDataset) |
| First recorded | 7 August 2026 |
| Last confirmed live | 10 November 2026 |
| Measurements held | 63 |
| Confirmed unchanged | 1 time, most recently 10 November 2026 |
| On Telegram | t.me/python_secrets |
Topic
Technology — 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 95% 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 the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Nov 2026, 01:27 | 40,332 | -25 |
| 8 Nov 2026, 15:20 | 40,357 | -9 |
| 7 Nov 2026, 10:08 | 40,366 | -4 |
| 6 Nov 2026, 10:45 | 40,370 | -6 |
| 5 Nov 2026, 13:37 | 40,376 | -11 |
| 4 Nov 2026, 11:09 | 40,387 | -11 |
| 3 Nov 2026, 11:37 | 40,398 | -11 |
| 2 Nov 2026, 13:16 | 40,409 | -18 |
| 1 Nov 2026, 12:20 | 40,427 | -7 |
| 31 Oct 2026, 12:36 | 40,434 | -8 |
| 30 Oct 2026, 14:09 | 40,442 | -12 |
| 29 Oct 2026, 14:00 | 40,454 | -10 |
| 28 Oct 2026, 14:20 | 40,464 | -12 |
| 27 Oct 2026, 13:10 | 40,476 | -6 |
| 26 Oct 2026, 15:16 | 40,482 | -9 |
| 25 Oct 2026, 15:27 | 40,491 | -5 |
| 24 Oct 2026, 12:46 | 40,496 | +2 |
| 23 Oct 2026, 15:04 | 40,494 | +1 |
| 22 Oct 2026, 16:19 | 40,493 | -6 |
| 21 Oct 2026, 08:38 | 40,499 | first reading |
Engagement
212 posts held, back to 23 June 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 191 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 3.66%
- avg views ÷ 40,332 subscribers
- Avg views / post
- 1,480
- 54 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 54
- of 212 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.
| Window | Rolling 30 days · latest post in window 11 November 2026 |
|---|---|
| Posts held | 212 (23 June 2026 – 11 November 2026) |
| Views total | 79,790 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 11 Nov 2026, 10:02 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
- 172
- Videos
- 71
- Links
- 255
Lifetime counters from Telegram’s own channel header, read 11 November 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.
- Video runtime
- 30h 14m
- Average length
- 51m 51s
Measured directly from 35 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.
Advertising
- Ad load
- 1.42%
- 3 of 212 posts carry an ad marker
- Regulatory tokens
- 3
- posts carrying an erid · 3 distinct tokens
- Median views · ads
- 1,550
- over 3 measured posts
- Median views · rest
- 1,840
- over 209 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.
| erid | Posts | First seen | Last seen |
|---|---|---|---|
| 2VtzqvtzAiV | 1 | 8 July 2026 | 8 July 2026 |
| 2Vtzqx82WHy | 1 | 31 August 2026 | 31 August 2026 |
| 2W5zFJkJXSh | 1 | 14 September 2026 | 14 September 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 212 most recent posts we hold, published 23 June 2026 to 11 November 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
Telegram’s own ‘edited’ marker: 0 of 54 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Функциональное программирование в Python: ежедневные рецепты Функциональное программирование - это программирование через функции в их математическом понимании, то есть когда функция принимает что-то на вход и что-то возвращает на выходе, не меняя глобального состояния. В этой статье автор расскажет о том, какие функциональные приемы можно использовать в Python, сконцентрируясь на практике — на тех примерах, которы…
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Разработка событийно-ориентированных микросервисов с помощью Python В этой статье автор разберет нюансы разработки событийно-ориентированных микросервисов на Python. Вы узнаете, почему Python подходит для разработки микросервисов и на что стоит обращать внимание при их разработке. Python Hacks
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Спецсимволы, экранирование символов и raw-строки в Python В этом видеоуроке автор подробно говорит о raw-строках (сырые строки), рассматривает на примерах понятие экранирования и для чего оно нужно, а также разбирает работу со спецсимволами строк: • \n - перевод строки • \t - табуляция • \ - обратный слеш • ' и " - экранирование кавычек Смотреть это видео на youtube: youtu.be/VZsWVN6QaKc
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Полезные методы работы с данными в Pandas. Часть 3 В этой статье мы рассмотрим различные подходы к работе со вложенными структурами данных в Pandas, а также обсудим процесс нормализации JSON- структур. На примерах автор продемонстрирует, как можно эффективно извлекать и обрабатывать вложенные данные, преобразовывая их в удобный для анализа формат. Python Hacks
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Многопоточность в Python: очевидное и невероятное В этой статье автор на практическом примере покажет как устроена многопоточность в Python, расскажет про потоки, примитивы синхронизации и о том зачем они нужны. Python Hacks
Хочешь разбираться в 1С? Для тебя уже всё сделали. ⚙️ Канал 1С Hacks рассказывает обо всех возможностях, приёмах и лайфхаках по работе в 1С. Подписывайтесь и прокачивайте свои навыки: @secrets_1C
Полезные методы работы с данными в Pandas. Часть 2 В этой статье мы погрузимся в применение скользящих окон для вычислений и смещение данных для анализа временных рядов. Скользящие окна позволяют проводить агрегированные вычисления на подмножествах данных, что может быть полезно для определения трендов, сезонности и аномалий во временных рядах. Python Hacks
Showing the 12 most recent of 212 posts we hold for @python_secrets. 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.
Posts recorded as deleted after publishing
We recorded 6 posts on @python_secrets as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
- First seen missing
- 9 August 2026
- Most recent seen missing
- 8 September 2026
- Median time before seen missing
- 2 days
- Seen missing in the last 30 days
- 0
Mentions
Named by 2 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.
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.
@secrets_1C · 46,4592 postsСекреты аналитики | Data Science, BI, Tableau
@analytics_secrets · 46,8141 postСистемный и Бизнес-анализ
@ba_sa_analytics · 52,4841 postБазы данных | Access, SQL, Big Data
@databases_secrets · 30,0121 postФинансовый анализ
@fin_analytics · 41,5381 postLumio Pay
@lumiopay · 1,3001 postУправление проектами и продуктами в IT | Project & Product Management
@product_and_project · 16,5811 postУправление персоналом | hr, карьера, кадры
@secrets_hr · 21,7701 postStudent invest
@studentinvest · 51 postСекреты сисадмина | DevOps, Linux, SRE
@sysadmin_library · 25,7231 postПереход Что за инвестор
@WhatTheInvestor · 2251 post
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.
@hacks_excel · 283,052#1
@databases_secrets · 30,012#2
@analytics_secrets · 46,814#3
@osint_pythons · 36,463#4
@ba_sa_analytics · 52,484#5
@trendo · 66,431#6
@fin_analytics · 41,538#7
@python_piton_javascript · 123,691#8
@ML_secrets · 7,365#9
@sysadmin_library · 25,723#10
@python2day · 63,348#11
@devops_sc · 14,756#12
@Python_per_month · 27,870#13
@secrets_1C · 46,459#14
@seniorpy · 39,134#15
@python_academy · 43,823#16
@pythonl · 58,287#17
@python_tg · 21,216#18
@pylinux0 · 11,049#19
@PythonTechCode · 4,141#20
@IT_Portal · 119,243#21
@pyproglib · 36,972#22
@secrets_hr · 21,770#23
@python_practics · 5,110#24
@data_analysis_ml · 51,923#25
@pythonist_ru · 23,873#26
@pythonguide_it · 15,754#27
@bugfeature · 552,118#28
@product_and_project · 16,581#29
@github · 154,995#30
@pythontest_it · 15,127 (as read 30 August 2026)#31
@devs_storage · 18,976#32
@pythonist24 · 55,221#33
@pro_python_code · 12,302#34
@python_easy_ru · 12,520#35
@zen_of_python · 18,645#36
@PythonPortal · 50,915#37
@justpython_it · 9,886 (as read 30 August 2026)#38
@pythonercode · 6,536#39
@ai_machinelearning_big_data · 275,659#40
@itmemes · 121,903#41
@Python_libr · 8,848#42
@data_secrets · 96,159#43
@python_pssss · 6,885#44
@developer_shelf · 26,715#45
@habr_com · 134,497#46
@pythonexpert_it · 10,443#47
@python_job_interview · 24,906#48
@bzd_channel · 36,213#49
@open_source_friend · 52,669#50
@pro100_python · 9,447#51
@code_library · 17,529#52
@proglibrary · 77,612#53
@sqlhub · 36,025#54
@pythonpythonjobs · 7,832#55
@hahacker_news · 25,231#56
@py_problems_lib · 6,330#57
@nsis_cybersec · 21,166#58
@job_python · 23,452#59
@bezopasno_soft · 29,601#60
@knijnoe_xranilishe · 19,509#61
@DevOPSitsec · 23,892#62
@it_sensei · 11,059#63
@it_tochka · 17,883#64
@devsp · 19,659#65
@learn_bd_sql · 6,123#66
@whackdoor · 1,538,229#67
@codecamp · 177,564#68
@Social_engineering · 124,696#69
@python_tasks · 8,445#70
@it_secur · 63,440#71
@linuxkalii · 55,842#72
@os_linux_ru · 19,536#73
@bashdays · 23,621#74
@google_sheets · 59,478#75
@pcTeapot · 39,425#76
@physics_lib · 146,676#77
@wind_community · 40,852#78
@school_network · 26,411#79
@linux_sup · 7,380#80
@EnglishScript · 44,381#81
@CScience1 · 7,683#82
Read from Telegram’s recommendation API, most recently 30 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.
@databases_secrets · 30,012
Telegram ranks this channel #3 of 82 here — alongside 81 others — read 7 September 2026
@analytics_secrets · 46,814
Telegram ranks this channel #5 of 85 here — alongside 84 others — read 27 August 2026
@hacks_excel · 283,052
Telegram ranks this channel #5 of 85 here — alongside 84 others — read 10 August 2026
@secrets_1C · 46,459
Telegram ranks this channel #6 of 79 here — alongside 78 others — read 27 August 2026
@ba_sa_analytics · 52,484
Telegram ranks this channel #6 of 90 here — alongside 89 others — read 24 August 2026
@fin_analytics · 41,538
Telegram ranks this channel #7 of 87 here — alongside 86 others — read 29 August 2026
@secrets_hr · 21,770
Telegram ranks this channel #8 of 93 here — alongside 92 others — read 22 September 2026
@pythonist24 · 55,221
Telegram ranks this channel #8 of 88 here — alongside 87 others — read 23 August 2026
@trendo · 66,431
Telegram ranks this channel #9 of 90 here — alongside 89 others — read 20 August 2026
@python_piton_javascript · 123,691
Telegram ranks this channel #12 of 84 here — alongside 83 others — read 13 August 2026
@osint_pythons · 36,463
Telegram ranks this channel #13 of 84 here — alongside 83 others — read 1 September 2026
@python_academy · 43,823
Telegram ranks this channel #15 of 87 here — alongside 86 others — read 28 August 2026
@pythonist_ru · 23,873
Telegram ranks this channel #18 of 82 here — alongside 81 others — read 17 September 2026
@Python_per_month · 27,870
Telegram ranks this channel #19 of 86 here — alongside 85 others — read 9 September 2026
@lemur_excel · 49,845
Telegram ranks this channel #19 of 95 here — alongside 94 others — read 25 August 2026
@teacherus · 34,718
Telegram ranks this channel #29 of 94 here — alongside 93 others — read 3 September 2026
@seniorpy · 39,134
Telegram ranks this channel #32 of 92 here — alongside 91 others — read 30 August 2026
@pythonbooks · 38,321
Telegram ranks this channel #33 of 65 here — alongside 64 others — read 17 September 2026
@excel_everyday · 52,038
Telegram ranks this channel #35 of 97 here — alongside 96 others — read 24 August 2026
@excelhackru · 74,003
Telegram ranks this channel #37 of 87 here — alongside 86 others — read 19 August 2026
@sysadmin_library · 25,723
Telegram ranks this channel #41 of 85 here — alongside 84 others — read 13 September 2026
@algebra_shpargalki · 23,756
Telegram ranks this channel #42 of 86 here — alongside 85 others — read 17 September 2026
@pythonl · 58,287
Telegram ranks this channel #48 of 84 here — alongside 83 others — read 22 August 2026
@procode404 · 40,080
Telegram ranks this channel #52 of 83 here — alongside 82 others — read 30 August 2026
This channel appears in 33 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 10 November 2026 — this entry's latest reading, not the date you are reading this.
“Python Hacks” (@python_secrets), 40,332 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/python_secrets.
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.