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Channel

Я (Лена) и моя (не)работа: nelenkin.club

@lenka_ne_work

On this record: Growth · Engagement · Reactions · Stars · Posts · Citations · Cite this entry

2,769subscribers

+5 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001447276607
TypeChannel
Username@lenka_ne_work
CreatedBetween 1 April 2019 and 30 September 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/lenka_ne_work

Growth

2,7642,7692,766.56 August 2026 — 2,764 subscribers7 August 2026 — 2,764 subscribers10 August 2026 — 2,767 subscribers13 August 2026 — 2,769 subscribers6 August 202613 August 2026
4 measurements spanning 6 days, net +5. 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 2,763–2,770 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 01:162,769+2
10 Aug 2026, 04:142,767+3
7 Aug 2026, 04:222,764no change
6 Aug 2026, 22:462,764first reading

Engagement

12 posts held, back to 26 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
67.1%
avg views ÷ 2,769 subscribers
Avg views / post
1,860
5 posts measured
Reaction rate
3.44%
reactions ÷ views · ER floor
Posts in window
5
of 12 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 6 August 2026
Posts held12 (26 June 20266 August 2026)
Views total9,290
Reactions total320
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:11 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.

Reaction mix

1,301 reactions across 12 posts, in 15 distinct kinds. The most used accounts for 29.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
37729.0%
🔥34126.2%
😢1309.99%
custom 53460736673925251681047.99%
🎉1047.99%
👍816.23%
🤯544.15%
🫡352.69%
❤‍🔥302.31%
💯161.23%
👀151.15%
80.615%
😨30.231%
👎20.154%
😭10.077%

Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.

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 12 of the 12 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 1,301reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 12 most recent posts we hold, published 26 June 2026 to 6 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.

Telegram Stars

Stars received
105
across the posts below
Posts paid on
2
of 12 we hold a reading for · 17%
Most on one post
103
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @lenka_ne_work. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 12 most recent posts we hold for this entry, published 26 June 2026 to 6 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

6 Aug 2026, 05:29 UTC≈1,080 views43 reactionsread 7 August 2026
Photo

Jeff Dean уходит из Гугла!🤯🤯🤯 Чел был тридцатым сотрудником Гугла, придумал во все датацентры Гугла поставить по атомным часам, Protobuf, MapReduce, TensorFlow и очень много всего другого! С 2018 года он был в Google AI, а теперь ушел делать свою компанию DiscoveryLoop, чтобы с помощью AI решать научные задачи. Видимо пора продавать свои GOOG (не инвестиционная рекомендация)

🫡355😨3

3 Aug 2026, 14:37 UTC≈1,290 views66 reactionsread 7 August 2026
Photo

Andy Pavlo (вы его можете знать по лекциям про базы данных на YouTube) теперь в ClickHouse! 🤯

👍37👀15🤯13🔥1

30 Jul 2026, 14:10 UTC≈2,100 views141 reactionsread 7 August 2026
Photo

Контента не будет, админ в Риме мочит ручки в фонтане и кушает джелато

88custom 534607366739252516837❤‍🔥14👍2

17 Jul 2026, 10:56 UTC≈2,740 views43 reactionsread 7 August 2026
Photo

А тем временем в клубе закончился третий поток по Leetcode Grind — поток совместного решения задач из списка Blind 75 на самые популярные темы с собеседований. У каждого потока в клубе есть куратор -- тот, кому надо больше всех и кто не забросит поток даже если другие забросят. Я познакомилась с Владимиром в марте, на звонке по чтению Designing Data-Intensive Applications. Он мне рассказал, что сам прорешивает литк

31🔥7custom 53460736673925251685

16 Jul 2026, 11:24 UTC≈2,080 views27 reactionsread 7 August 2026

Bun, Zig и Rust: я не договорил!! Прочитала две ответочки на пост про переписывание Bun на Rust. 1. Естественно, пост автора языка Zig Andrew Kelly. Andrew — панк в мире программирования. В посте есть разбор характера Jarred-а (создатель Bun, который и переписал сейчас его на Rust) и много нефильтрованного презрения. Andrew остается верен своим принципам и публично говорит о ситуациях, где миллиардные компании рас

💯12🔥86🤯1

13 Jul 2026, 13:45 UTC≈1,880 views33 reactionsread 7 August 2026

Прочитала большой пост про переписывание Bun на Rust, чтобы вам не надо было! Напомню, что 14 мая Bun смерждил пулл-реквест с 6755 коммитами, который переписывал весь проект с языка Zig на язык Rust. Переписать проект в полмиллиона строк кода заняло 11 дней, а написать про это блог-пост — еще два месяца😄 https://bun.com/blog/bun-in-rust tl;dr: - Переписывание заняло 11 дней, 64 Claud-ов управляемые через dynamic

16🔥7👍6💯3😢1

7 Jul 2026, 12:13 UTC≈2,520 views220 reactionsread 7 August 2026
Photo

Как у меня попытались украсть еще не написанный курс Я планировала читать курс по System Design Case Studies в Harbour Space в Барселоне уже через две недели. Вчера я села за слайды к лекциями и заодно решила поговорить с кем-то опытным, как лучше рассчитать нагрузку на домашку для студентов. Для этого я полезла на сайт университета и поискала похожие курсы, чтобы найти коллегу, с кем можно будет обсудить учебный п

😢12943🤯37👍73😭1

6 Jul 2026, 16:15 UTC≈2,150 views114 reactions2 Starsread 7 August 2026
Photo

Когда я увольнялась, я говорила, что у меня две большие цели: сделать видео-курс по System Design и дальше развивать свой клуб чтения сложных книг по программированию Над клубом я работаю уже почти полтора года full-time, а вот видео-курс по system design буксует. Осенью я прочитала курс по System Design в университете в Германии, но никак руки не дошли его выложить в интернет. Через две недели уже я буду читать кур

90👍23👎1

2 Jul 2026, 16:08 UTC≈2,730 views527 reactions103 Starsread 7 August 2026
Photo

personal update: я теперь замужняя женщина!

🔥305🎉104custom 53460736673925251686042❤‍🔥16

1 Jul 2026, 14:56 UTC≈2,550 views27 reactionsread 7 August 2026
Photo

а я все еще провожу консультации по system design! если у вас собес на следующей неделе, вы в принципе что-то читали, но хочется систематизировать + уложить в формат + потренироваться на английском + получить обратную связь, пишите мне! @lenka_colenka

25👍2

30 Jun 2026, 10:31 UTC≈2,100 views19 reactionsread 7 August 2026

Алишер поделился моим постом про опен-сорс в виде статьи у себя на сайте! Кстати, если хотите позвать меня к себе на подкаст (например как это сделали linkmeup), или интервью взять, или совместно статью написать, пишите мне в личку @lenka_colenka! Расскажу вам и про работу в Google, и про Kafka, и про преподавание в университете заграницей, и что на system design собеседованиях спрашивают!

12🔥3👍2custom 53460736673925251682

26 Jun 2026, 10:28 UTC≈2,540 views41 reactionsread 7 August 2026

Как я полгода (не) обновляла access token для Patreon # Что такое `access token` и как он используется У меня в клубе nelenkin.club подписку можно получить либо за презентации, либо за донаты на Boosty или Patreon. И естественно, список патронов я веду не руками, а получаю по Patreon API. Для этого создала клиента, Patreon выдал access token, запросы летают! Казалось бы, все хорошо, но через месяц работы я стала по

24🔥10🤯3👍2👎1💯1

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

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Citation-graph rank

Citation-graph rank — 683,969 of 1,336,469entries 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 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.

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.

“Я (Лена) и моя (не)работа: nelenkin.club” (@lenka_ne_work), 2,769 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/lenka_ne_work.

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.