Channel
@python_bds
On this record: Topic · Growth · Engagement · Reactions · Posts · Polls · Citations · Telegram's recommendations · Cite this entry
5,759subscribers
-80 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001718432323 |
|---|---|
| Type | Channel |
| Username | @python_bds |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 15 September 2026 |
| Measurements held | 13 |
| Confirmed unchanged | 2 times, most recently 15 September 2026 |
| On Telegram | t.me/python_bds |
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 12 September 2026 and assigned it the closest of 31 fixed categories, at 67% 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 why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Sept 2026, 17:37 | 5,759 | -15 |
| 7 Sept 2026, 09:59 | 5,774 | -9 |
| 3 Sept 2026, 00:48 | 5,783 | -9 |
| 30 Aug 2026, 15:47 | 5,792 | +3 |
| 27 Aug 2026, 09:26 | 5,789 | -12 |
| 24 Aug 2026, 00:05 | 5,801 | -21 |
| 20 Aug 2026, 04:43 | 5,822 | -12 |
| 16 Aug 2026, 21:33 | 5,834 | -5 |
| 13 Aug 2026, 17:57 | 5,839 | -5 |
| 10 Aug 2026, 19:25 | 5,844 | +4 |
| 7 Aug 2026, 23:44 | 5,840 | +1 |
| 7 Aug 2026, 10:00 | 5,839 | no change |
| 7 Aug 2026, 09:53 | 5,839 | first reading |
22 posts held, back to 12 July 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 9 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 22 posts for this entry, the most recent from 10 August 2026. An engagement rate over an empty window would be a number about nothing.
66 reactions across 20 posts, in 4 distinct kinds. The most used accounts for 75.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 50 | 75.8% | |
| 🔥 | 9 | 13.6% | |
| 👍 | 4 | 6.06% | |
| 🥰 | 3 | 4.55% |
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 22 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 66 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 12 July 2026 to 10 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 Time Complexity Cheat Sheet ✅ List • Access by index → O(1) • Append → O(1) • Insert at beginning → O(n) • Delete from middle → O(n) • Search (in) → O(n) Best for: Ordered collections where fast indexing matters. ✅ Dictionary (dict) • Lookup → O(1) • Insert → O(1) • Update → O(1) • Delete → O(1) Best for: Fast lookups using keys. ✅ Set • Add → O(1) • Remove → O(1) • Membership test → O(1) Best for: Removi…
❤2
📖 Reading Python Error Messages Suppose you see this. TypeError: 'NoneType' object is not iterable Instead of guessing, break it down. TypeError → You're performing an operation on an incompatible type. NoneType → The value is None. not iterable → Python expected something it could loop over, like a list or tuple. A common cause: def get_users(): print("Loading users...") for user in get_users(): print(us…
❤3
🐍 15 Python Built-in Functions Every Developer Should Know You don't always need another library. Python already ships with powerful built-in functions that can make your code cleaner, shorter, and faster. 1. enumerate() - Loop through items while automatically keeping track of their index. 2. zip() - Combine multiple lists together element by element. 3. map() - Apply the same function to every item in an itera…
❤3
What is the biggest advantage of using a set instead of a list when checking whether an item exists?
Shares as published. No per-option vote count is published by Telegram, so none is shown.
A Japanese AI company called Preferred Networks has a mature open-source library for NumPy/SciPy calculations on GPUs. It's called CuPy 🚀. For massive datasets, it is often enough to replace a single line: import cupy as cp The same array operations can run on CUDA up to 100 times faster. What it can do: 🛠 Highly compatible with existing NumPy and SciPy code 📝 Dramatically reduces the need to rewrite code or learn…
❤3
File, posted without a caption
❤2🔥1
📘 Biopython: Tutorial and Cookbook ✍️ Authors: Jeff Chang, Brad Chapman, Iddo Friedberg, Thomas Hamelryck, Michiel de Hoon, Peter Cock, Tiago Antao, Eric Talevich, Bartek Wilczyński 🔗 Read Online #Python ──────────────────── 👉 @free_programming_books_bds 👈
❤4
The Unofficial Python Graph Gallery If you work with data, you already know the pain of making charts look decent in Python. You spend 5 minutes writing the logic to process your data, and then 45 minutes wrestling with matplotlib or seaborn trying to figure out why your labels are overlapping, how to change a specific hex color, or how to remove those ugly default borders. This repository completely solves that. I…
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File, posted without a caption
🔥3❤1
Python List Exercises Guide
❤4👍2
Python Web Scraping This learning path you’ll learn the core Python technologies and skills you need to build your own web scraper. Web scraping is about downloading structured data from the web and processing selected data. 👉 You should already be comfortable writing Python scripts 🔗 Learn Here
❤3
📦 The Difference Between a Package and a Module These terms get mixed up a lot. 📗A module is a single Python file. math.py 📚A package is a folder containing multiple modules. utils/ helpers.py parser.py formatter.py Think of it like this: 📖 Module = One book 📚 Package = An entire bookshelf
👍2
Showing the 12 most recent of 22 posts we hold for @python_bds. 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.
The 2 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
What is the biggest advantage of using a set instead of a list when checking whether an item exists?
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Which statement about Python tuples is true?
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 22 most recent posts we hold, published 12 July 2026 to 10 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
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 27 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 September 2026 — this entry's latest reading, not the date you are reading this.
“Python Learning” (@python_bds), 5,759 subscribers as measured 11 September 2026. Telegram Register, tgregister.com/channel/python_bds.
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.