#вопросы_с_собеседований Что такое и чем отличается old-style от new-style classes? — Old-style классы наследуются непосредственно от объекта класса type. New-style классы наследуются от объекта класса object. — New-style классы поддерживают дополнительные возможности, например descriptors, properties, slots. В old-style классах они не работают. — В new-style классах метод init вызывается при наследовании, в отлич…

Channel
Senior Python Developer
@seniorpy
On this record: Growth · Engagement · What this channel posts · Advertising · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry
39,996subscribers
-363 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1001558186588 |
|---|---|
| Type | Channel |
| Username | @seniorpy |
| Description | № 4931117861 Публикуем интересные/полезные фичи/библиотеки языка. По вопросам сотрудничества: @adv_and_pr Канал на бирже: https://telega.in/c/seniorpy |
| Created | Between 1 August 2021 and 28 February 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 6 September 2026 |
| Measurements held | 28 |
| Confirmed unchanged | 1 time, most recently 6 September 2026 |
| On Telegram | t.me/seniorpy |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 6 Sept 2026, 23:59 | 39,996 | -41 |
| 4 Sept 2026, 08:17 | 40,037 | -28 |
| 2 Sept 2026, 22:04 | 40,065 | -20 |
| 1 Sept 2026, 19:06 | 40,085 | -17 |
| 31 Aug 2026, 16:27 | 40,102 | -4 |
| 30 Aug 2026, 19:08 | 40,106 | -7 |
| 29 Aug 2026, 15:54 | 40,113 | -26 |
| 28 Aug 2026, 14:16 | 40,139 | -16 |
| 27 Aug 2026, 12:14 | 40,155 | -1 |
| 26 Aug 2026, 10:46 | 40,156 | -13 |
| 25 Aug 2026, 12:02 | 40,169 | +32 |
| 24 Aug 2026, 12:47 | 40,137 | -21 |
| 22 Aug 2026, 18:55 | 40,158 | -6 |
| 21 Aug 2026, 12:27 | 40,164 | -1 |
| 20 Aug 2026, 15:16 | 40,165 | -22 |
| 19 Aug 2026, 13:52 | 40,187 | -7 |
| 18 Aug 2026, 16:38 | 40,194 | -13 |
| 17 Aug 2026, 16:35 | 40,207 | -24 |
| 16 Aug 2026, 14:17 | 40,231 | -22 |
| 15 Aug 2026, 00:57 | 40,253 | first reading |
Engagement
46 posts held, back to 12 July 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 68 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 6.62%
- avg views ÷ 39,996 subscribers
- Avg views / post
- 2,650
- 25 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 25
- of 46 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 7 September 2026 |
|---|---|
| Posts held | 46 (12 July 2026 – 7 September 2026) |
| Views total | 66,186 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Sept 2026, 00:03 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
- ≈2,280
- Videos
- ≈6
- Links
- ≈562
Lifetime counters from Telegram’s own channel header, read 8 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.
Advertising
- Ad load
- 2.17%
- 1 of 46 posts carry an ad marker
- Regulatory tokens
- 1
- posts carrying an erid · 1 distinct token
- Median views · ads
- 2,830
- over 1 measured post
- Median views · rest
- 3,200
- over 45 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 |
|---|---|---|---|
| 2VtzquuHE37 | 1 | 19 August 2026 | 19 August 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 46 most recent posts we hold, published 12 July 2026 to 7 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
#вопросы_с_собеседований В чем отличие @foobar от @foobar()? @foobar и @foobar() — это разные способы применения декораторов. @foobar применяет декоратор без аргументов, а @foobar() применяет декоратор с аргументами. То есть @foobar() вызывает декоратор foobar, передавая ему аргументы, а затем результат (декорированная функция) применяется к функции.
LineaPy LineaPy — это библиотека для работы с временными рядами и анализа временных данных. Эта библиотека позволяет быстро решать типовые задачи анализа временных рядов без необходимости "изобретать велосипед". Она удобна для анализа временных данных в задачах прогнозирования, мониторинга, выявления сезонности, трендов и аномалий. Имеет интуитивный API и хорошую документацию. В этом примере мы получили прогнозные…
Владение, заимствование и ссылки в Rust: как компилятор делает ваш код безопасным В Rust одна из самых непривычных для разработчиков тем — это ownership (владение) и borrowing (заимствование). Многие пытаются писать на Rust как на C++ или Python, натыкаются на компилятор, и правила borrow checker'а поначалу кажутся слишком строгими. На деле компилятор просто защищает вас от ошибок, которые в других языках приводят к…
#вопросы_с_собеседований Что такое Diamond problem? Diamond problem - это проблема, возникающая при использовании множественного наследования. Суть проблемы заключается в том, что если есть два базовых класса A и B, от которых наследуется класс C, а классы A и B в свою очередь наследуются от общего предка D, то при обращении к членам класса D из объекта класса C возникает неоднозначность - непонятно, члены из каког…
7,2 млн рублей призового фонда и реальные задачи космической отрасли 🚀 В сентябре пройдет серия КосмоХакатонов для студентов, молодых ученых и специалистов. Участникам предстоит за два дня разработать собственное решение, поработать с экспертами и представить проект жюри. Участников ждут: 🛰 реальные задачи космической отрасли 👥 команды от 3 до 5 человек 💻 очный и онлайн-форматы 🧑💻 работа с экспертами и трекерами 🏆…
Завершение программы sys.exit() — это функция, которая позволяет завершить выполнение программы и возвратить код возврата операционной системе. Принимает один необязательный числовой аргумент — код возврата программы. По умолчанию это 0, что означает успешное завершение, а код возврата отличный от нуля сигнализирует об ошибке или нештатной ситуации. Используется для завершения программы в случае критической ошибки,…
Fugue Fugue — это библиотека, которая используется для создания и оркестровки workflow машинного обучения. Она позволяет быстро создавать, тестировать и масштабировать ML приложения, автоматизируя рутинные этапы. Основные возможности: — Описание этапов workflow как отдельных функций. — Автоматическое определение зависимостей между функциями. — Планирование выполнения функций с учетом зависимостей. — Кэширование про…
Метод count() count() - простой и удобный способ получить число вхождений элемента в последовательности за линейное время. Полезен при подсчете статистики, анализе данных и других задачах. Метод принимает в качестве аргумента элемент, количество которого нужно посчитать и возвращает число - количество найденных вхождений элемента. Работает для списков, кортежей, строк. #это_база
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Showing the 12 most recent of 46 posts we hold for @seniorpy. 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.
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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 1
- vacant every time we have ever looked
@seniorpy named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 2 posts, 2 September 2026 – 4 September 2026
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.
@python2day · 63,854#1
@osint_pythons · 36,576#2
@Python_per_month · 28,389#3
@python_piton_javascript · 127,895#4
@trendo · 68,433#5
@python_academy · 44,465#6
@pythonl · 58,944#7
@pyproglib · 37,446#8
@python_tg · 20,928#9
@zen_of_python · 18,917#10
@python_easy_ru · 12,779#11
@job_python · 22,761#12
@pythonguide_it · 16,007#13
@PythonPortal · 50,774#14
@pylinux0 · 11,009#15
@python_tricks · 5,092#16
@python_practics · 5,161#17
@easy_python_task · 9,137#18
@python_pssss · 6,999#19
@python_job_interview · 24,863#20
@pythonpythonjobs · 7,373#21
@devs_storage · 19,183#22
@Python_libr · 8,965#23
@seniorcpp · 11,635#24
@structuredata · 7,714#25
@pro_python_code · 12,384#26
@pythonist_ru · 24,095#27
@xo_py · 17,182#28
@data_analysis_ml · 50,599#29
@pythonexpert_it · 10,578#30
@pythonist24 · 56,122#31
@python_secrets · 40,692#32
@IT_Portal · 100,558#33
@justpython_it · 9,867#34
@artemshumeiko · 19,908#35
@pro100_python · 9,616#36
@developer_shelf · 26,849#37
@Leetcode_fans · 9,428#38
@devsp · 19,791#39
@easy_python_tests · 5,848#40
@ithumor · 60,753#41
@backend_it · 19,056#42
@BackendPortal · 16,146#43
@uneed_it · 2,893#44
@Python_Community_ru · 11,645#45
@django_prog · 1,293#46
@progersbooks · 8,244#47
@machinelearning_interview · 30,264#48
@p_rabota · 4,593#49
@ML_secrets · 7,423#50
@seniorjavist · 20,669#51
@proglibrary · 78,357#52
@PythonTechCode · 4,184#53
@githubdevs · 4,744#54
@bkstorage · 6,551#55
@pythonboost · 10,836#56
@github · 155,464#57
@seniorsql · 14,377#58
@itmemes · 123,844#59
@pythontest_it · 15,093#60
@data_secrets · 93,011#61
@ai_machinelearning_big_data · 282,429#62
@xor_journal · 151,183#63
@codecamp · 182,003#64
@quiz_python · 6,947#65
@python_tasks · 8,540#66
@senior_front · 19,493#67
@habr_com · 132,178#68
@howdyho_official · 79,490#69
@t0digital · 28,564#70
@physics_lib · 146,369#71
@techno_media · 803,544#72
@devs_store · 11,805#73
@programmer_memes · 51,541#74
@ai_newz · 96,728#75
@Social_engineering · 125,064#76
@remedia · 711,393#77
@open_source_friend · 52,042#78
@bugfeature · 581,205#79
@tproger · 78,629#80
@netstalkerscom · 7,858#81
@pydevjob · 9,611#82
@bashdays · 23,701#83
@black_triangle_tg · 63,816#84
@Golang_google · 40,442#85
@nuancesprog · 56,702#86
@dvachannel · 937,263#87
@exploitex · 2,022,579#88
@whackdoor · 1,613,979#89
@pekagame · 1,094,826#90
@rozetked · 659,047#91
@d_code · 390,858#92
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.
@python_academy · 44,465
Telegram ranks this channel #1 of 87 here — alongside 86 others — read 28 August 2026
@osint_pythons · 36,576
Telegram ranks this channel #2 of 84 here — alongside 83 others — read 1 September 2026
@trendo · 68,433
Telegram ranks this channel #2 of 90 here — alongside 89 others — read 20 August 2026
@pythonist24 · 56,122
Telegram ranks this channel #3 of 88 here — alongside 87 others — read 23 August 2026
@python_piton_javascript · 127,895
Telegram ranks this channel #4 of 84 here — alongside 83 others — read 13 August 2026
@python2day · 63,854
Telegram ranks this channel #7 of 91 here — alongside 90 others — read 21 August 2026
@pyproglib · 37,446
Telegram ranks this channel #15 of 84 here — alongside 83 others — read 1 September 2026
@python_secrets · 40,692
Telegram ranks this channel #15 of 82 here — alongside 81 others — read 30 August 2026
@pygen_ru · 49,647
Telegram ranks this channel #17 of 93 here — alongside 92 others — read 25 August 2026
@procode404 · 41,082
Telegram ranks this channel #20 of 83 here — alongside 82 others — read 30 August 2026
@pythonl · 58,944
Telegram ranks this channel #20 of 84 here — alongside 83 others — read 22 August 2026
@PythonPortal · 50,774
Telegram ranks this channel #21 of 80 here — alongside 79 others — read 25 August 2026
@databases_secrets · 30,038
Telegram ranks this channel #42 of 82 here — alongside 81 others — read 7 September 2026
@wind_community · 41,396
Telegram ranks this channel #52 of 74 here — alongside 73 others — read 29 August 2026
@github · 155,464
Telegram ranks this channel #55 of 87 here — alongside 86 others — read 12 August 2026
@EnglishScript · 45,407
Telegram ranks this channel #65 of 82 here — alongside 81 others — read 27 August 2026
@skillget · 81,333
Telegram ranks this channel #68 of 88 here — alongside 87 others — read 18 August 2026
@nuancesprog · 56,702
Telegram ranks this channel #79 of 84 here — alongside 83 others — read 23 August 2026
@xor_journal · 151,183
Telegram ranks this channel #88 of 93 here — alongside 92 others — read 12 August 2026
This channel appears in 19 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 6 September 2026 — this entry's latest reading, not the date you are reading this.
“Senior Python Developer” (@seniorpy), 39,996 subscribers as measured 6 September 2026. Telegram Register, tgregister.com/channel/seniorpy.
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.