⚙️ Shed Skin — перевод ограниченного подмножества Python в C++ Shed Skin — транспилятор программ на чистом Python 3 с неявной статической типизацией в оптимизированный C++. Создает самостоятельные программы или модули расширения для импорта в другие Python-программы. Поддерживает около 25 модулей стандартной библиотеки, включая random и re, но не сторонние библиотеки. Вложенные функции и переменное число аргументов…

Channel
Python и 1000 уязвимостей
@osint_pythons
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry
36,480subscribers
-162 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 | -1001310194575 |
|---|---|
| Type | Channel |
| Username | @osint_pythons |
| Description | Сила в единстве. Сотрудничество: @workhouse_price № 5383975776 РКН: https://clck.ru/3FtTDH |
| Created | Between 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 24 October 2026 |
| Measurements held | 45 |
| Confirmed unchanged | 1 time, most recently 24 October 2026 |
| On Telegram | t.me/osint_pythons |
Topic
Hacking & security — 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 92% 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
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 24 Oct 2026, 19:39 | 36,480 | -4 |
| 23 Oct 2026, 17:51 | 36,484 | +2 |
| 22 Oct 2026, 14:56 | 36,482 | +1 |
| 21 Oct 2026, 11:06 | 36,481 | -6 |
| 20 Oct 2026, 05:51 | 36,487 | -3 |
| 19 Oct 2026, 08:38 | 36,490 | -2 |
| 18 Oct 2026, 09:06 | 36,492 | -4 |
| 17 Oct 2026, 07:57 | 36,496 | -3 |
| 16 Oct 2026, 08:55 | 36,499 | -9 |
| 15 Oct 2026, 09:39 | 36,508 | -3 |
| 14 Oct 2026, 12:41 | 36,511 | -4 |
| 13 Oct 2026, 00:46 | 36,515 | -2 |
| 8 Oct 2026, 15:56 | 36,517 | -4 |
| 4 Oct 2026, 05:01 | 36,521 | -14 |
| 25 Sept 2026, 08:42 | 36,535 | -11 |
| 18 Sept 2026, 22:39 | 36,546 | -7 |
| 16 Sept 2026, 15:01 | 36,553 | +8 |
| 14 Sept 2026, 19:18 | 36,545 | -9 |
| 13 Sept 2026, 04:19 | 36,554 | +5 |
| 11 Sept 2026, 04:57 | 36,549 | first reading |
Engagement
172 posts held, back to 28 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 152 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.924%
- avg views ÷ 36,480 subscribers
- Avg views / post
- 337
- 61 posts measured
- Reaction rate
- 0.755%
- reactions ÷ views · ER floor
- Posts in window
- 61
- of 172 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 37 of 61 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 24 October 2026 |
|---|---|
| Posts held | 172 (28 July 2026 – 24 October 2026) |
| Views total | 20,556 |
| Reactions total | 101 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 25 Oct 2026, 02:21 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
- ≈2,390
- Videos
- ≈647
- Links
- ≈2,610
Lifetime counters from Telegram’s own channel header, read 25 October 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.
- Video runtime
- 13h 09m
- Average length
- 1h 00m
Measured directly from 13 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
463 reactions across 147 posts, in 5 distinct kinds. The most used accounts for 36.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 171 | 36.9% | |
| 👍 | 143 | 30.9% | |
| ❤ | 130 | 28.1% | |
| 🤔 | 12 | 2.59% | |
| 🤯 | 7 | 1.51% |
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 148 of the 172 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 463 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 172 most recent posts we hold, published 28 July 2026 to 24 October 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.
Recent posts
⚙️ Py-ART — обработка данных метеорадаров на Python Py-ART — открытый Python-модуль с алгоритмами и утилитами для обработки и анализа данных метеорадаров. Рассчитан на специалистов по радиолокации и исследователей атмосферы. Позволяет отображать сеточные данные на географических картах при установленном Cartopy. Для экспорта объектов Grid в GeoTIFF нужен gdal. — Работа модуля протестирована с Python 3.11, 3.12 и 3…
❤1
⚙️ Bruin — конвейеры данных на SQL, Python и R Bruin — инструмент для построения конвейеров данных. Объединяет загрузку данных, преобразования на SQL, Python и R и проверки качества в одном фреймворке. Python выполняется в изолированных окружениях с помощью uv. Есть шаблоны Jinja для сокращения повторений и сквозная проверка конвейеров в режиме dry-run. — Можно запускать локально, на экземпляре EC2 или в GitHub Ac…
⚙️ Awkward Array — вложенные данные с операциями в стиле NumPy Awkward Array — библиотека для работы с вложенными данными переменного размера в стиле NumPy. Поддерживает списки произвольной длины, записи, смешанные типы и пропущенные значения. Массивы имеют динамическую типизацию, а операции над ними компилируются. При регулярных размерностях поведение совпадает с NumPy и обобщается на нерегулярные структуры. — В …
ℹ️ DVT: как устроено чтение больших таблиц через Dask DVT — open‑source платформа визуального ETL: пайплайн собирается из нод (чтение → преобразования → запись) и выполняется на воркерах поверх Dask. Нода чтения из БД должна одинаково работать на таблице в 10 тыс. и в 100 млн строк, на шести СУБД (PostgreSQL, MySQL/MariaDB, MS SQL, Oracle, SQLite, ClickHouse), в воркере с ограниченной памятью и без избыточной нагру…
⚙️ Manim — математические анимации на Python Manim — Python-фреймворк для создания математических анимаций. Эту версию поддерживает и развивает сообщество. Есть интеграция с JupyterLab и классическим Jupyter: с анимациями можно работать прямо в блокнотах. — Перед использованием нужно установить зависимости. Попробовать инструмент без локальной установки можно в онлайн-среде Jupyter проекта. 🖥 Репозиторий на GitHu
⚙️ djLint — форматирование и проверка HTML-шаблонов djLint — форматтер и линтер HTML-шаблонов для Django, Jinja, Twig и других движков. Форматирует разметку вместе с синтаксисом шаблонов. Исправляет отступы и регистр тегов, нормализует шаблонные теги и убирает лишние пустые строки. Линтер находит непарные теги, отсутствующие атрибуты alt и жестко заданные URL. — Можно запускать при каждом коммите через pre-commit.…
⚙️ pyngrok — управление туннелями ngrok из Python pyngrok — Python-обертка для программного управления туннелями ngrok. Загружает агент ngrok и управляет им, предоставляя Python API и доступ из командной строки. ngrok открывает защищенные туннели от публичных URL к localhost. Подходит для тестирования вебхуков и демонстрации локальных сайтов. — В документации есть примеры интеграции с Flask, Django, Docker и Googl…
❤1
⚙️ Cosmos — запуск проектов dbt Core в Apache Airflow Cosmos — инструмент для запуска проектов dbt Core в Apache Airflow в виде DAG и групп задач. Превращает каждую модель dbt в задачу или группу задач с повторными попытками и оповещениями. Тесты можно запускать сразу после завершения модели, чтобы раньше обнаруживать ошибки. — Поддерживает установку и запуск dbt в виртуальном окружении, чтобы избежать конфликтов …
⚙️ Osintgram — анализ публичных профилей Instagram Osintgram — инструмент для анализа публичных профилей Instagram. Собирает подписи, хештеги и геометки в веб-интерфейсе на вашем компьютере. Показывает геометки на карте и время публикаций на тепловой карте по дням недели и часам. Есть сравнение двух аккаунтов и экспорт результатов в самостоятельный HTML-отчет. Для получения данных нужен ключ HikerAPI либо бесплатн…
⚙️ Citizen Intelligence Agency — OSINT-анализ политики Швеции OSINT-платформа для анализа деятельности парламента, правительства и государственных ведомств Швеции. Работает с открытыми данными начиная с 1971 года. Анализирует политические тенденции, формирует рейтинги политиков и сравнивает эффективность партий и продуктивность комитетов. Есть финансовые показатели политиков и государственных органов. — Каждую мет…
ℹ️ HTTP-клиент на Python: таймауты, повторы и очередь перед семафором Написать HTTP‑клиент к другому сервису — обычная задача в бэкенде. В первой версии все просто: отправить запрос, прочитать ответ, вернуть результат. Затем приходится решать, сколько ждать медленный сервис, какие ошибки повторять и сколько запросов разрешать одновременно. Клиент обрастает ограничениями: таймаутом на попытку, повторами с паузами, …
Showing the 12 most recent of 172 posts we hold for @osint_pythons. 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 edited after publishing
@osint_pythons edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
- First edit seen
- 14 August 2026
- Most recent edit
- 30 August 2026
Mentions
Named by 3 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.
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.
@python2day · 63,547#1
@seniorpy · 39,402#2
@Python_per_month · 28,018#3
@python_piton_javascript · 124,737#4
@python_tg · 21,178#5
@trendo · 66,960#6
@python_practics · 5,117#7
@pylinux0 · 11,058#8
@pyproglib · 37,118#9
@pythonexpert_it · 10,493#10
@pythonl · 58,595#11
@code_library · 17,507#12
@python_secrets · 40,496#13
@Python_libr · 8,871#14
@pythonguide_it · 15,817#15
@pro100_python · 9,495#16
@python_easy_ru · 12,598#17
@secure_archive · 10,963#18
@devs_storage · 19,025#19
@zen_of_python · 18,752#20
@PythonPortal · 51,122#21
@pro_python_code · 12,332#22
@pythontest_it · 15,119 (as read 1 September 2026)#23
@PythonTechCode · 4,164#24
@devs_store · 11,694#25
@python_job_interview · 24,959#26
@pythonist_ru · 23,929#27
@python_tricks · 5,071#28
@justpython_it · 9,876 (as read 1 September 2026)#29
@python_academy · 43,983#30
@IT_Portal · 38#31
@developer_shelf · 26,767#32
@cyberins · 11,543#33
@python_pssss · 6,933#34
@it_sensei · 11,097#35
@open_source_friend · 52,501#36
@devops_sc · 14,796#37
@data_analysis_ml · 51,730#38
@structuredata · 7,628#39
@job_python · 23,330#40
@data_secrets · 95,343#41
@sysadmin_library · 25,831#42
@easy_python_task · 8,989#43
@xo_py · 16,881#44
@pythonercode · 6,568#45
@learn_bd_sql · 6,154#46
@admguides · 12,016#47
@quiz_python · 6,886#48
@codeguru_tg · 8,751#49
@ITSyndicate_23 · 8,529#50
@itles_tg · 15,907#51
@itmemes · 122,337#52
@py_problems_lib · 6,342#53
@databases_secrets · 30,101#54
@pycodecamp · 8,069#55
@haccking · 63,113#56
@pythonpythonjobs · 7,700#57
@proglibrary · 77,910#58
@ML_secrets · 7,384#59
@pythonist24 · 55,481#60
@githubdevs · 4,776#61
@Social_engineering · 124,936#62
@elliot_cybersec · 39,063#63
@codecamp · 178,438#64
@nsis_cybersec · 21,278#65
@infosec_globe · 17,965#66
@physics_lib · 146,875#67
@searchack · 18,116#68
@github · 155,209#69
@netstalkerscom · 7,829#70
@it_secur · 62,855#71
@whackdoor · 1,559,388#72
@ai_machinelearning_big_data · 277,589#73
@black_triangle_tg · 63,906#74
@linuxkalii · 55,861#75
@xor_journal · 200,850#76
@kind_hack · 11,932#77
@school_network · 26,503#78
@techno_media · 935,888#79
@sql_tg · 9,505#80
@os_linux_ru · 19,563#81
@bashdays · 23,620#82
@exploitex · 2,013,394#83
@python_tasks · 8,473#84
Read from Telegram’s recommendation API, most recently 1 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.
@seniorpy · 39,402
Telegram ranks this channel #2 of 92 here — alongside 91 others — read 30 August 2026
@Python_per_month · 28,018
Telegram ranks this channel #3 of 86 here — alongside 85 others — read 9 September 2026
@python_secrets · 40,496
Telegram ranks this channel #4 of 82 here — alongside 81 others — read 30 August 2026
@trendo · 66,960
Telegram ranks this channel #4 of 90 here — alongside 89 others — read 20 August 2026
@python_piton_javascript · 124,737
Telegram ranks this channel #5 of 84 here — alongside 83 others — read 13 August 2026
@pythonist_ru · 23,929
Telegram ranks this channel #6 of 82 here — alongside 81 others — read 17 September 2026
@pythonist24 · 55,481
Telegram ranks this channel #7 of 88 here — alongside 87 others — read 23 August 2026
@python2day · 63,547
Telegram ranks this channel #8 of 91 here — alongside 90 others — read 21 August 2026
@maths_lib · 25,562
Telegram ranks this channel #9 of 67 here — alongside 66 others — read 14 September 2026
@python_academy · 43,983
Telegram ranks this channel #10 of 87 here — alongside 86 others — read 28 August 2026
@zen_of_python · 18,752
Telegram ranks this channel #13 of 91 here — alongside 90 others — read 5 October 2026
@pygen_ru · 50,184
Telegram ranks this channel #16 of 93 here — alongside 92 others — read 25 August 2026
@databases_secrets · 30,101
Telegram ranks this channel #17 of 82 here — alongside 81 others — read 7 September 2026
@pyproglib · 37,118
Telegram ranks this channel #19 of 84 here — alongside 83 others — read 1 September 2026
@python_tg · 21,178
Telegram ranks this channel #20 of 85 here — alongside 84 others — read 25 September 2026
@developer_shelf · 26,767
Telegram ranks this channel #24 of 63 here — alongside 62 others — read 11 September 2026
@EnglishScript · 44,654
Telegram ranks this channel #24 of 82 here — alongside 81 others — read 27 August 2026
@job_python · 23,330
Telegram ranks this channel #26 of 96 here — alongside 95 others — read 19 September 2026
@PythonPortal · 51,122
Telegram ranks this channel #26 of 80 here — alongside 79 others — read 25 August 2026
@algebra_shpargalki · 23,961
Telegram ranks this channel #29 of 86 here — alongside 85 others — read 17 September 2026
@pythonl · 58,595
Telegram ranks this channel #30 of 84 here — alongside 83 others — read 22 August 2026
@python_job_interview · 24,959
Telegram ranks this channel #32 of 90 here — alongside 89 others — read 15 September 2026
@pythonbooks · 38,438
Telegram ranks this channel #35 of 65 here — alongside 64 others — read 17 September 2026
@trojan_anonym · 64,138
Telegram ranks this channel #35 of 82 here — alongside 81 others — read 21 August 2026
This channel appears in 41 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 24 October 2026 — this entry's latest reading, not the date you are reading this.
“Python и 1000 уязвимостей” (@osint_pythons), 36,480 subscribers as measured 24 October 2026. Telegram Register, tgregister.com/channel/osint_pythons.
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.