Python Tips: 🚀 DAY 105/150 – Number guessing game Code: https://www.clcoding.com/2026/08/day-105150-number-guessing-game.html
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Channel
@pythonclcoding
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
9,613subscribers
+28 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001249563470 |
|---|---|
| Type | Channel |
| Username | @pythonclcoding |
| Created | Between 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 2 September 2026 |
| Measurements held | 10 |
| Confirmed unchanged | 1 time, most recently 2 September 2026 |
| On Telegram | t.me/pythonclcoding |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 2 Sept 2026, 08:34 | 9,613 | +3 |
| 30 Aug 2026, 16:02 | 9,610 | +2 |
| 27 Aug 2026, 23:34 | 9,608 | +2 |
| 24 Aug 2026, 16:14 | 9,606 | +4 |
| 20 Aug 2026, 23:24 | 9,602 | +6 |
| 17 Aug 2026, 20:34 | 9,596 | +5 |
| 14 Aug 2026, 23:38 | 9,591 | +1 |
| 11 Aug 2026, 08:06 | 9,590 | +5 |
| 8 Aug 2026, 08:54 | 9,585 | no change |
| 7 Aug 2026, 22:03 | 9,585 | first reading |
124 posts held, back to 5 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 33 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. It is computed over the 115 of 124 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 29 August 2026 |
|---|---|
| Posts held | 124 (5 August 2026 – 29 August 2026) |
| Views total | 35,789 |
| Reactions total | 150 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 29 Aug 2026, 05:42 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.
150 reactions across 115 posts, in 2 distinct kinds. The most used accounts for 99.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 149 | 99.3% | |
| 👍 | 1 | 0.667% |
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 115 of the 124 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 150 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 124 most recent posts we hold, published 5 August 2026 to 29 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.
Python Tips: 🚀 DAY 105/150 – Number guessing game Code: https://www.clcoding.com/2026/08/day-105150-number-guessing-game.html
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🚀 CLCODING SEPTEMBER BOOTCAMP 2026 🐍📊 Python Beginner to Data Science Want to learn Python from the basics and gradually move toward Data Science? Join the CLCODING September BootCamp and follow a structured learning journey from Python fundamentals to Data Science concepts and practical applications. Register Now: https://forms.gle/5GxJ7Gsmmb3PgKTbA
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Understanding Machine Learning: From Theory to Algorithms — Free PDF 📘 Understanding Machine Learning: From Theory to Algorithms Authors: Shai Shalev-Shwartz & Shai Ben-David Publisher: Cambridge University Press Pages: 449 This is a rigorous textbook covering machine learning theory, PAC learning, generalization, optimization, SGD, regularization, kernel methods, SVMs, neural networks, computational learning…
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Python Quiz of the Day Python Coding Challenge - Question with Answer (ID 280826) Answer with Explanation: https://www.clcoding.com/2026/08/python-coding-challenge-id-280826.html
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Statistical Divergences between Densities of Truncated Exponential Families with Nested Supports: Duo Bregman and Duo Jensen Divergences (Free PDF) Download the Free PDF: https://www.clcoding.com/2026/08/statistical-divergences-between.html
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🐍 Daily Python Coding Challenge — Day 1130 Can you predict the output of this Python code? 🤔 This challenge tests your understanding of: • @ classmethod • @ staticmethod • Class attributes • Method binding in Python 💡 Take a moment and think carefully before checking the answer! What do you think the correct option is? A: 10 10 B: Error C: None None D: 10 Error Drop your answer in the comments 👇 The answer an…
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🐍 7 Essential Python Libraries for Data Professionals 📊 Want to build a career in Data Analytics, Data Science, or Machine Learning? Learning Python is only the beginning. You also need to know the right libraries to work with real-world data. 🚀 Here are 7 essential Python libraries worth learning: 1️⃣ Pandas — Clean, transform, and analyze datasets 2️⃣ NumPy — Numerical computing and multidimensional arrays 3️⃣ …
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Python quiz of the Day Python Coding Challenge - Question with Answer (ID 270826) Answer with Explanation: https://www.clcoding.com/2026/08/python-coding-challenge-id-270826.html
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Python Tips: 🚀 Day 104/150 – OTP Generator in Python Code: https://www.clcoding.com/2026/08/day-104150-otp-generator-in-python.html
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Generalized Bhattacharyya and Chernoff Upper Bounds on Bayes Error Using Quasi-Arithmetic Means The paper covers: Bayesian classification and Bayes error Bhattacharyya upper bounds Chernoff information Quasi-arithmetic means Statistical divergences and affinity coefficients Applications to Cauchy and multivariate t-distributions 👉 Download / Read the Free PDF: https://www.clcoding.com/2026/08/generalized-bhattach…
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Python Quiz of the Day! Python Coding Challenge - Question with Answer (ID 260826) Answer with Explanation: https://www.clcoding.com/2026/08/python-coding-challenge-id-260826.html
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Machine Learning Projects — Free PDF 📘 Machine Learning Projects (Free PDF) Looking for practical machine learning projects to strengthen your skills? This 135-page free PDF is a useful resource for students, beginners, and aspiring machine learning developers who want to learn by working on real-world project ideas. 🚀 What you’ll find: Machine Learning project ideas Python-based ML projects Practical implemen…
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Showing the 12 most recent of 124 posts we hold for @pythonclcoding. 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.
Citation-graph rank — 357,565 of 1,629,571 entries 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.
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.
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 2 September 2026 — this entry's latest reading, not the date you are reading this.
“Python Coding (CLCODING)” (@pythonclcoding), 9,613 subscribers as measured 2 September 2026. Telegram Register, tgregister.com/channel/pythonclcoding.
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.