9 measurements spanning 7 days, net -38. 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 24,770–24,821 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 01:43
24,776
-4
12 Aug 2026, 00:53
24,780
-3
11 Aug 2026, 02:53
24,783
-11
10 Aug 2026, 00:41
24,794
-3
9 Aug 2026, 01:51
24,797
-7
7 Aug 2026, 23:13
24,804
-3
7 Aug 2026, 02:05
24,807
-8
6 Aug 2026, 04:00
24,815
+1
6 Aug 2026, 02:18
24,814
first reading
Engagement
23 posts held, back to 13 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 17 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
7.11%
avg views ÷ 24,776 subscribers
Avg views / post
1,760
22 posts measured
Reaction rate
0.357%
reactions ÷ views · ER floor
Posts in window
22
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. It is computed over the 20 of 22 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 11 August 2026
Posts held
23 (13 July 2026 – 11 August 2026)
Views total
38,770
Reactions total
127
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 22:33 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
1m 07s
Average length
1m 07s
Measured directly from 1 video 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
122 reactions across 19 posts, in 6 distinct kinds. The most used accounts for 35.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
43
35.2%
🔥
35
28.7%
👍
28
23.0%
😁
14
11.5%
😐
1
0.82%
🥰
1
0.82%
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 20 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 127reactions 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 13 July 2026 to 11 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.
Advertising
Ad load
4.35%
1 of 23 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
1,120
over 1 measured post
Median views · rest
1,610
over 22 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
erid
Posts
First seen
Last seen
2Vtzqv5TWBU
1
4 August 2026
4 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 23 most recent posts we hold, published 13 July 2026 to 11 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.
Главный секрет bool: он на самом деле int
Складываю True и True, получаю 2
Складываешь два True в Python и получаешь 2. Не баг и не магия: bool наследуется от int, поэтому True это единица, а False это ноль. Минута, и ты больше никогда не удивишься sum по списку булевых значений.
#python
⚡️ Как узнать количество CPU в Python одной строкой
Для этого не нужны сторонние библиотеки — всё есть в стандартном multiprocessing:
import multiprocessing
print(multiprocessing.cpu_count())
Например:
8
Но есть важный нюанс: функция обычно возвращает количество логических процессоров, доступных системе, а не обязательно число физических ядер.
То же самое можно получить через:
import os
print(os.cpu_cou…
🚀 ИИ-агент ускорил SQLite до 59% меньше чем за 8 часов
Ускорить SQLite хотя бы на 5% уже было бы серьёзным результатом. Это один из самых зрелых и оптимизированных проектов в мире — его команда почти 20 лет выжимает из кода каждую долю производительности.
Но AI-агент KISS Sorcar менее чем за 8 часов и с затратами меньше $150 добился заметного ускорения сразу в нескольких типах нагрузки.
Результаты:
- 2,06× быстре…
🚀 Neo4j без сервера: GraphForge запускает полноценный Cypher прямо внутри Python-скрипта
GraphForge занимает редкую нишу между NetworkX и серверными графовыми БД. Вы получаете встроенный графовый движок на Rust, полный openCypher и хранение проекта в обычной директории.
Что внутри:
- четыре независимых слоя на Rust: parser → IR → planning → execution;
- результаты сразу возвращаются как Apache Arrow Table;
- данны…
Открыли регистрацию на E-CUP 2026 Students 🎓
В этом сезоне — только для студентов. Будет интересно тем, кто изучает ML / DS / big data / аналитику данных.
Сможете ускорить модель по поиску дубликатов на 20%? Получится создать классификатор для модерации товаров? Сумеете предсказать поведение покупателя?
Как минимум — попробуете и получите фидбэк от тех, кто делает это в Ozon Tech каждый день. Как максимум — раздел…
✔️ Liquid AI выпустила локального агента, который работает на телефоне
LFM2.5-2.6B - компактная агентная модель на 2,6 млрд параметров. Она умеет планировать действия, вызывать инструменты и выполнять многошаговые задачи полностью на устройстве, без облачного API.
Модель обучили примерно на 34 трлн токенов, расширили словарь до 128 тысяч токенов и добавили контекст 128K.
Особенно интересно устроено дообучение:
- …
🔴 Завтра тестовое собеседование на Middle Python с разработчиком из Авито
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 чего от …
🔥 PyTorch Monarch теперь поддерживает AMD GPU через ROCm
Monarch позволяет управлять распределённым обучением на сотнях GPU из одной Python-программы. Вместо ручной координации процессов разработчик работает с акторами и группами устройств, а runtime берёт оркестрацию на себя.
Главное преимущество - отказоустойчивость. Если один узел выходит из строя, исправные реплики продолжают обучение. Система перезапускает пов…
Python-сервис не должен падать вслед за чужим API
Interlock - современная реализация circuit breaker для Python. Она временно блокирует обращения к нестабильному сервису, а затем аккуратно проверяет, восстановился ли он. Синхронный и асинхронный код поддерживаются одним классом.
Вместо примитивного подсчёта ошибок подряд библиотека умеет оценивать долю сбоев в скользящем окне - по числу запросов или времени. Медлен…
🐍 Python-совет: когда `deque` лучше обычного списка
collections.deque — двусторонняя очередь, оптимизированная для быстрых операций с обоих концов.
from collections import deque
queue = deque(["a", "b", "c"])
queue.append("d") # добавить справа
queue.appendleft("z") # добавить слева
queue.pop() # удалить справа
queue.popleft() # удалить слева
У deque добавление и удаление с краёв вы…
One Day Offer для Python-разработчиков!💚
15 августа открываем двери в команду Agent Execution Framework ⚡️
Коллеги создают платформу для GenAI‑агентов в банке — делают так, чтобы ИИ реально работал в серьёзных финпроцессах: с безопасностью, нагрузкой и пользой.
Чем предстоит заниматься:
✔️ развивать backend на Python
✔️ подключать LLM, инструменты, базы знаний и RAG
✔️ строить пайплайны оценки качества агентов
✔️…
🐍 Python-совет: как объединить списки разной длины
Обычный zip() прекращает работу, когда заканчивается самый короткий список:
x = [1, 2, 3, 4, 5]
y = ["a", "b", "c"]
print(list(zip(x, y)))
# [(1, "a"), (2, "b"), (3, "c")]
Чтобы сохранить все элементы, используйте zip_longest()
from itertools import zip_longest
print(list(zip_longest(x, y)))
# [(1, "a"), (2, "b"), (3, "c"), (4, None), (5, None)]
Для пустых п…
❤6🔥3🥰1
Showing the 12 most recent of 23 posts we hold for @python_job_interview. 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.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none.The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100.Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 23 most recent posts we hold, published 13 July 2026 to 11 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Citation-graph rank
Citation-graph rank — 86,252 of 1,160,990entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 30 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.
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.
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.
Machinelearning @ai_machinelearning_big_data · 286,250 Telegram ranks this channel #42 of 95 here — alongside 94 others — read 10 August 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“Python вопросы с собеседований” (@python_job_interview), 24,776 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/python_job_interview.
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.