Photo, posted without a caption
🔥1

Channel
@pythonfreebootcamp
On this record: Topic · Growth · Engagement · Reactions · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry
40,266subscribers
-593 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001218627802 |
|---|---|
| Type | Channel |
| Username | @pythonfreebootcamp |
| Created | Between 1 April 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 | 11 November 2026 |
| Measurements held | 63 |
| Confirmed unchanged | 1 time, most recently 11 November 2026 |
| On Telegram | t.me/pythonfreebootcamp |
Education — 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 100% 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 the other topics.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Nov 2026, 04:20 | 40,266 | -17 |
| 9 Nov 2026, 09:36 | 40,283 | -38 |
| 8 Nov 2026, 00:57 | 40,321 | -15 |
| 6 Nov 2026, 20:45 | 40,336 | -16 |
| 5 Nov 2026, 18:26 | 40,352 | -12 |
| 4 Nov 2026, 18:06 | 40,364 | -19 |
| 3 Nov 2026, 21:15 | 40,383 | -15 |
| 2 Nov 2026, 23:46 | 40,398 | +5 |
| 2 Nov 2026, 01:37 | 40,393 | -11 |
| 1 Nov 2026, 00:05 | 40,404 | -1 |
| 31 Oct 2026, 02:39 | 40,405 | -5 |
| 30 Oct 2026, 03:18 | 40,410 | -5 |
| 29 Oct 2026, 05:00 | 40,415 | -6 |
| 28 Oct 2026, 05:45 | 40,421 | -11 |
| 27 Oct 2026, 04:46 | 40,432 | -12 |
| 26 Oct 2026, 03:50 | 40,444 | -8 |
| 25 Oct 2026, 02:08 | 40,452 | -22 |
| 24 Oct 2026, 02:38 | 40,474 | -13 |
| 23 Oct 2026, 00:06 | 40,487 | -5 |
| 21 Oct 2026, 23:29 | 40,492 | first reading |
25 posts held, back to 2 April 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 185 pages of Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 3 November 2026 |
|---|---|
| Posts held | 25 (2 April 2026 – 3 November 2026) |
| Views total | 710 |
| Reactions total | 1 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 10 Nov 2026, 23:09 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.
94 reactions across 20 posts, in 5 distinct kinds. The most used accounts for 48.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 46 | 48.9% | |
| 👍 | 37 | 39.4% | |
| 🥰 | 8 | 8.51% | |
| 👏 | 2 | 2.13% | |
| 🤩 | 1 | 1.06% |
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 25 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 94 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 25 most recent posts we hold, published 2 April 2026 to 3 November 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’s own ‘edited’ marker: 0 of 1 post held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Photo, posted without a caption
🔥1
Data Analytics A-Z
🔥5
Let’s dive into our first mini project using Python: Project 1: Number Guessing Game 🎯 Goal: The computer randomly picks a number between 1 and 100. The user has to guess it — and the program gives hints like “Too High” or “Too Low” until the user gets it right. Code: import random number_to_guess = random.randint(1, 100) guess = None attempts = 0 print("Welcome to the Number Guessing Game!") print("I'm thinkin…
👍2👏2🔥1
Learn AI for Free in 2026👇 1/ Kaggle Learn: https://www.kaggle.com/learn 2/ Anthropic Learn: https://www.anthropic.com/learn 3/ OpenAI Academy: https://academy.openai.com/ 4/ Google AI: https://grow.google/ai/ 5/ LangChain Academy: https://academy.langchain.com/
👍6
Roadmap to become a data analyst 1. Foundation Skills: •Strengthen Mathematics: Focus on statistics relevant to data analysis. •Excel Basics: Master fundamental Excel functions and formulas. 2. SQL Proficiency: •Learn SQL Basics: Understand SELECT statements, JOINs, and filtering. •Practice Database Queries: Work with databases to retrieve and manipulate data. 3. Excel Advanced Techniques: •Data Cleaning in Excel:…
👍3
🐍 Python Roadmap 1️⃣ Basics: 📝📜 Syntax, Variables, Data Types 2️⃣ Control Flow: 🔄🤖 If-Else, Loops, Functions 3️⃣ Data Structures: 🗂️🔢 Lists, Tuples, Dictionaries, Sets 4️⃣ OOP in Python: 📦🎭 Classes, Inheritance, Decorators 5️⃣ File Handling: 📄📂 Read/Write, JSON, CSV 6️⃣ Modules & Libraries: 📦🚀 NumPy, Pandas, Matplotlib 7️⃣ Web Development: 🌍🔧 Flask, Django, FastAPI 8️⃣ Automation & Scripting: 🤖🛠️ Web Scraping, Selen…
🔥10🥰1
🔰 Comprehensions in python with example
If you’re a student, graduate, or someone looking for a career switch, read this. Most people spend months watching random YouTube videos and still don’t become job-ready. Instead, learn in a structured offline classroom. 📌 Data Analytics with GenAI 📌 Python + SQL + Power BI 📌 6-Month Program 📌 1:1 Mentorship 📌 Job Assistance 📍Now available in your city. Seats are limited. 👉 Register Here: https://lp.pwskills.c…
✅ Complete Roadmap to Learn Python Programming 🐍💻 Week 1: Python Basics • Install Python and VS Code • Learn variables, data types, input, output • Practice arithmetic and string operations • Write 10 small programs Example: Calculator, temperature converter Week 2: Control Flow • Learn if, else, elif • Learn for and while loops • Use break and continue • Solve 20 logic problems Example: Number guessing game W…
🔥8👍1
🔰 Comprehensions in python with example
🔥4
Aaj hi ek certified Hackar bano!💻 Shuru se saari cheeze seekho bilkul basic se!! PW skills leke aaya h certified Ethical Hacking ka course!! Isme milega : ✅ Hands on Practice ✅ LIVE Hacking Labs ✅ Certificate after Completion Sirf Rs 4999 mai Abhi enroll karo HACK30 Coupon code use karke 30% OFF milega! Enroll NOW : https://pwskills.com/web-development/certified-ethical-hacking-course-035473/?source=pwskills.com…
Here are some tricky🧩 SQL interview questions! 1. Find the second-highest salary in a table without using LIMIT or TOP. 2. Write a SQL query to find all employees who earn more than their managers. 3. Find the duplicate rows in a table without using GROUP BY. 4. Write a SQL query to find the top 10% of earners in a table. 5. Find the cumulative sum of a column in a table. 6. Write a SQL query to find all employ…
Showing the 12 most recent of 25 posts we hold for @pythonfreebootcamp. 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.
We recorded 1 post on @pythonfreebootcamp as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
Named by 5 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.
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.
Read from Telegram’s recommendation API, most recently 30 August 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.
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.
This channel appears in 69 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.
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 11 November 2026 — this entry's latest reading, not the date you are reading this.
“Python Projects & Free Books” (@pythonfreebootcamp), 40,266 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/pythonfreebootcamp.
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.