آموزش ساخت ربات تلگرام با پایتون و گوگل کولب از مبتدی تا حرفه ای : قسمت اول: https://t.me/sourcefurushi/61 قسمت دوم: https://t.me/sourcefurushi/63 قسمت سوم: https://t.me/sourcefurushi/64 قسمت چهارم: https://t.me/sourcefurushi/65 قسمت پنجم: https://t.me/sourcefurushi/66 قسمت ششم: https://t.me/sourcefurushi/67 قسمت هفتم : https://t.me/sourcefurushi/68 قسمت هشتم: https://t.me/sourcefurushi/70 قسمت نهم: https:/…

Channel
W3schoolsfa | پایتون ،برنامه نویسی و هوش مصنوعی آموزش رایگان
@pyfaw3schools
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
10,148subscribers
+52 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1001787506085 |
|---|---|
| Type | Channel |
| Username | @pyfaw3schools |
| Created | Between 1 December 2021 and 31 March 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 9 |
| Confirmed unchanged | 1 time, most recently 14 August 2026 |
| On Telegram | t.me/pyfaw3schools |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Aug 2026, 13:35 | 10,148 | +8 |
| 13 Aug 2026, 07:16 | 10,140 | +16 |
| 12 Aug 2026, 08:03 | 10,124 | -3 |
| 11 Aug 2026, 05:25 | 10,127 | +13 |
| 10 Aug 2026, 07:07 | 10,114 | +9 |
| 9 Aug 2026, 05:11 | 10,105 | +8 |
| 8 Aug 2026, 03:31 | 10,097 | +1 |
| 7 Aug 2026, 13:01 | 10,096 | no change |
| 7 Aug 2026, 12:56 | 10,096 | first reading |
Engagement
31 posts held, back to 2 August 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 19 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 9.19%
- avg views ÷ 10,148 subscribers
- Avg views / post
- 933
- 30 posts measured
- Reaction rate
- 0.261%
- reactions ÷ views · ER floor
- Posts in window
- 31
- of 31 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 30 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 31 (2 August 2026 – 12 August 2026) |
| Views total | 27,991 |
| Reactions total | 54 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 13 Aug 2026, 05:24 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
- 23m 56s
- Average length
- 2m 40s
Measured directly from 9 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
54 reactions across 19 posts, in 4 distinct kinds. The most used accounts for 77.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 42 | 77.8% | |
| 🔥 | 6 | 11.1% | |
| 👍 | 4 | 7.41% | |
| 🙏 | 2 | 3.70% |
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 31 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 54reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 31 most recent posts we hold, published 2 August 2026 to 12 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
🕔مهلت تخفیف ها و دریافت هدیه تا آخر جمعه شب 😍این پک برای کیه؟ 🔹 دانشجویی که میخواد سریع تو این تابستون بیش ترز ۵ تا مهارت یاد بگیره 🔹 کارمندی که وقت دورهرفتن نداره 🔹کسایی که دوست دارن با گوشی از صفر پایتون و الگوریتمای ماشین لرنینگ یاد بگیرن برای سفارش، کلمه "پک" رو به آیدی زیر بفرست @w3schoolfaadmin
نمونه کتاب یادگیری عمیق برای مبتدیان پیش نیاز: پایتون، پانداس،نامپای
اگه پایاننامهت مرتبط با هوش مصنوعیه، یادگیری PyTorch واقعاً لازمه برات🤖 ولی قبلش باید پیشنیازاش رو بلد باشی: پایتون، یادگیری ماشین و یادگیری عمیق 🧠💻 برای همین یه پک کامل از فایل های "بای (بخون، اجرا کن، یاد بگیر) " آماده کردم که این مسیرو قدمبهقدم پوشش میده: 1️⃣ پایتون و ریاضیات هوش مصنوعی از صفر : قیمت ۳۵۰ هزار تومن ۱۰۸ هزار تومن 2️⃣ یادگیری ماشین مبتدی (Scikit-learn): قیمت ۳۲۰هزارتومن ۱۱۰ هزار تومن 3️⃣ یا…
گیت هاب چطور کار میکنه؟ 🤔 جزوه گیت هاب زیر ۳۰ ثانیه: 🚀👇👇 https://t.me/pyfaw3schools/2022
❤4
۴۷ تا کوییز پایتون
ظرفیت تخفیف یادگیری ماشین مبتدیان شد برای ۷ نفر مشغول شاغلین و کسایی که فقط روزی یه ساعت وقت دارند "بخون،اجرا کن، یادبگیر" برای سفارش به ایدی زیر کلمه "ماشین لرنینگ " رو پیام بدید @w3schoolfaadmin
پرامپتهای آموزش پایتون از صفر تا صد راهنمای استفاده: هر پرامپت رو کپی کن و به هوش مصنوعی بده. بعد از یادگیری و تمرین هر بخش، برو سراغ پرامپت بعدی. ۱. مقدمات و نصب من صفر تا صد پایتون رو دارم یاد میگیرم و هیچ پیشزمینهای ندارم. برام خیلی ساده و با مثال توضیح بده: - پایتون چیه و چرا محبوبه - چطور پایتون رو نصب کنم و اولین برنامه رو اجرا کنم - متغیر چیه و چطور تعریف میشه - انواع داده ساده: عدد صحیح، اعشاری، رشته متنی…
❤7👍1
اگر کافه داری،این یه پروژه کاربردی با پایتون برای کم کردن هزینه هات و بالا رفتن فروشه پیش نیاز: پایتون و اشنایی با کتابخانه های pandas و matplotlib
🔥3
ظرفیت تخفیف یادگیری ماشین مبتدیان شد برای ۸ نفر مشغول شاغلین و کسایی که فقط روزی یه ساعت وقت دارند "بخون،اجرا کن، یادبگیر" برای سفارش به ایدی زیر پیام بدید @w3schoolfaadmin
👍2
۵ الگوریتم پرکاربرد ماشین لرنینگ توی ترید
🔥3
برای کسانی که پایتون بلدند و با کتابخانههای نامپای و پانداس آشنایی دارند، این کتاب بهترین گزینه برای شروع کار با الگوریتمهای ماشین لرنینگه 🐍📊. مطالب ساده و روانه و زیر هر کد لینک اجراش رو گذاشتیم (به سبک سایت w3schools) 💻. توی گوشی هم میتونید بخونید و اجرا کنید 📱✨. با تخفیف ویژه ۳۸۰ هزار تومن ۱۲۰ هزار تومن 💸، ظرفیت فقط برای ۱۰ نفر ⚠️. برای سفارش به آیدی زیر پیام بدید 👇: @w3schoolfaadmin 📩
❤2
Showing the 12 most recent of 31 posts we hold for @pyfaw3schools. 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.
@PythonForever · 129,963
Telegram ranks this channel #2 of 76 here — alongside 75 others — read 13 August 2026
@Computer_IT_Engineering · 188,270
Telegram ranks this channel #56 of 76 here — alongside 75 others — read 11 August 2026
@cofeeng · 113,950
Telegram ranks this channel #66 of 76 here — alongside 75 others — read 14 August 2026
This channel appears in 3 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 14 August 2026 — this entry's latest reading, not the date you are reading this.
“W3schoolsfa | پایتون ،برنامه نویسی و هوش مصنوعی آموزش رایگان” (@pyfaw3schools), 10,148 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/pyfaw3schools.
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.