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Telegram profile photo for Ninja Learn | نینجا لرن

Channel

Ninja Learn | نینجا لرن

@ninja_learn_ir

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

1,048subscribers

-4 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1002175060322
TypeChannel
Username@ninja_learn_ir
CreatedBetween 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live29 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 29 August 2026
On Telegramt.me/ninja_learn_ir

Growth

1,0481,0521,0507 August 2026 — 1,052 subscribers8 August 2026 — 1,052 subscribers10 August 2026 — 1,050 subscribers13 August 2026 — 1,049 subscribers19 August 2026 — 1,052 subscribers22 August 2026 — 1,051 subscribers25 August 2026 — 1,052 subscribers29 August 2026 — 1,048 subscribers7 August 202629 August 2026
8 measurements spanning 22 days, net -4. 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 1,047–1,053 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
29 Aug 2026, 05:051,048-4
25 Aug 2026, 22:241,052+1
22 Aug 2026, 23:351,051-1
19 Aug 2026, 07:551,052+3
13 Aug 2026, 01:441,049-1
10 Aug 2026, 06:351,050-2
8 Aug 2026, 00:191,052no change
7 Aug 2026, 15:191,052first reading

Engagement

19 posts held, back to 30 May 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
16.2%
avg views ÷ 1,048 subscribers
Avg views / post
170
4 posts measured
Reaction rate
2.90%
reactions ÷ views · ER floor
Posts in window
4
of 19 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 3 of 4 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 4 August 2026
Posts held19 (30 May 20264 August 2026)
Views total679
Reactions total15
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 00:19 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
8s
Average length
8s

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

91 reactions across 17 posts, in 6 distinct kinds. The most used accounts for 38.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
3538.5%
🤣2123.1%
👍1314.3%
🔥1112.1%
🌚99.89%
❤‍🔥22.20%

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 17 of the 19 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 91reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 30 May 2026 to 4 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.

Recent posts

4 Aug 2026, 11:02 UTC190 views4 reactionsread 8 August 2026
Video

Video, posted without a caption

🤣4

Signed Ghetto

4 Aug 2026, 09:52 UTC150 views4 reactionsread 8 August 2026
Forwarded from @MidnightCommit

‏Database Replication دقیقاً یعنی چی؟ 🧠 ‏Replication یعنی ایجاد چند نسخه از داده‌ها روی چند Database Server مختلف. توی این معماری، معمولاً یه Node اصلی داریم که مسئول دریافت تغییرات داده هست و Nodeهای دیگه یک کپی از داده‌ها رو نگهداری می‌کنن. هدف اصلی Replication این نیست که فضای بیشتری برای ذخیره‌سازی داشته باشیم. هدف اصلی اینه که بتوانیم تعدا Request بیشتری رو مدیریت کنیم و فشار روی Database اصلی رو کم کنیم. به زبا

4

Signed Ghetto

30 Jul 2026, 12:44 UTC255 views4 reactionsread 8 August 2026
Forwarded from @MidnightCommit

‏Leaky Bucket 🪣 ‏Leaky Bucket از نظر ایده شباهت‌هایی به Token Bucket داره، اما هدف اصلی اون کنترل نرخ خروجی Requestهاست. توی این الگوریتم، Requestهای ورودی وارد یک Queue میشن و با یک سرعت ثابت پردازش میشن. یعنی حتی اگه تعداد زیادی Request در یک لحظه وارد سیستم بشه، خروجی با یک Rate مشخص انجام میشه. این رفتار باعث میشه فشار ناگهانی روی بخش‌های دیگر سیستم کاهش پیدا کنه و Traffic ورودی به شکل کنترل‌شده‌تری پردازش بشه. ا

4

Signed Ghetto

29 Jul 2026, 20:57 UTC278 views5 reactionsread 8 August 2026
Forwarded from @MidnightCommit

‏Redis چطور با یک Thread تعداد زیادی Request رو مدیریت می‌کنه؟ 🤔 وقتی درباره‌ی Performance صحبت می‌کنیم، معمولاً یکی از اولین چیزهایی که به ذهنمون میاد استفاده از Threadهای بیشتره. منطق هم ساده به نظر میرسه: Thread بیشتر یعنی کار بیشتر، پس سرعت بالاتر. اما Redis سال‌هاست با یک مدل متفاوت کار می‌کنه. Redis بخش اصلی پردازش Commandهای خودش رو با یک Thread اصلی انجام میده و با همین معماری می‌تونه تعداد زیادی Request رو د

5

Signed Ghetto

24 Jul 2026, 17:41 UTC371 views3 reactionsread 8 August 2026

حتماً توی کانال ابلفضل جوین باشید مطالب خوبی میذاره

3

Signed Ghetto

24 Jul 2026, 17:15 UTC364 views5 reactionsread 8 August 2026
Forwarded from @MidnightCommit

چرا Nginx برای هر Request یک Process جدید نمی‌سازه؟ 🤔 وقتی اسم Web Server میاد، معمولاً اولین چیزی که به ذهنمون میاد اینه که یک Request وارد میشه، سرور اون رو پردازش می‌کنه و جواب رو برمی‌گردونه. اما چیزی که کمتر بهش توجه میشه، اینه که خود Web Server چطور تصمیم می‌گیره این Requestها رو مدیریت کنه. این تصمیم تأثیر مستقیمی روی Performance، مصرف Memory و تعداد Connectionهایی داره که سرور می‌تونه همزمان مدیریت کنه. معما

🔥41

Signed Ghetto

23 Jul 2026, 09:37 UTC307 views6 reactionsread 8 August 2026
Forwarded from @MidnightCommit

‏Redis چطور تغییرات رو بدون متوقف کردن سرویس روی Disk ذخیره می‌کنه؟ 🤔 توی پست قبلی درباره‌ی RDB صحبت کردیم و دیدیم Redis چطور با استفاده از ()fork و Copy-On-Write از داده‌های داخل Memory یه Snapshot می‌گیره. اما RDB یه محدودیت مهم داره: چون Snapshotها در بازه‌های زمانی مشخص ساخته میشن، ممکنه تغییراتی که بعد از آخرین Snapshot اتفاق افتادن، در صورت Crash شدن Redis از بین برن. اینجاست که مکانیزم دیگه‌ی Redis برای Persis

6

Signed Self

20 Jul 2026, 19:52 UTC358 views5 reactionsread 8 August 2026
Forwarded from @MidnightCommit

‏RDB چه مزایا و معایبی داره؟ 💡 یکی از بزرگ‌ترین مزیت‌های RDB اینه که فایل خروجی معمولاً حجم کمی داره و ردیس بعد از Restart می‌تونه خیلی سریع‌تر داده‌ها رو دوباره Load کنه. همچنین چون نوشتن Snapshot به صورت دوره‌ای انجام میشه، فشار کمتری روی دیسک ایجاد می‌کنه. اما مشکل اصلی اینجاست: ‏RDB آخرین وضعیت Memory رو ذخیره نمی‌کنه، بلکه آخرین Snapshot گرفته‌شده رو ذخیره می‌کنه. یعنی اگر ردیس Crash بشه، ممکنه تغییراتی که بعد ا

5

Signed Self

20 Jul 2026, 09:32 UTC451 views13 reactionsread 8 August 2026

این بلا تکلیفی منو آزار میدهد 🙏

👍13

Signed Self

15 Jul 2026, 18:39 UTC676 views1 reactionsread 8 August 2026

شوروی واقعا توی شروع قوی عمل کرد ولی قابل مقایسه با حرکتای ناسا نبود واقعا (مهندسای المانی بیشتری داشت)

🤣1

Signed Self

Showing the 12 most recent of 19 posts we hold for @ninja_learn_ir. 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

Republishes

Channels on the register whose posts this channel has forwarded.

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

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.

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.

پاسخ آزمون های نهاد - جواب ازمون نهاد
@NahadChannel · 171,527
Telegram ranks this channel #18 of 68 here — alongside 67 others — read 25 August 2026
کنکور ارشد کامپیوتر
@Konkurcomputer · 50,587
Telegram ranks this channel #63 of 88 here — alongside 87 others — read 25 August 2026

This channel appears in 2 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 29 August 2026 — this entry's latest reading, not the date you are reading this.

“Ninja Learn | نینجا لرن” (@ninja_learn_ir), 1,048 subscribers as measured 29 August 2026. Telegram Register, tgregister.com/channel/ninja_learn_ir.

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.