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Learn Python Coding

Learn Python Coding

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Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Analytical overview of Telegram channel Learn Python Coding

Channel Learn Python Coding (@pythonre) in the English language segment is an active participant. Currently, the community unites 40 879 subscribers, ranking 3 292 in the Technologies & Applications category and 9 353 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 879 subscribers.

According to the latest data from 27 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 395 over the last 30 days and by -12 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 3.98%. Within the first 24 hours after publication, content typically collects 1.48% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 628 views. Within the first day, a publication typically gains 604 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
  • Thematic interests: Content is focused on key topics such as math, harvard, oxford, supervision, waybienad.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 28 October, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

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Posts Archive
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📂 Reminder about Python map()! map() — a built-in function that applies the specified function to each element of an iterabl
📂 Reminder about Python map()! map() — a built-in function that applies the specified function to each element of an iterable object (list, tuple, set, etc.). The picture shows the basic syntax, an example of use with lambda, and a typical case — data transformation without a manual for loop. Save it to quickly remember the syntax! 🐍💻🗺️ #Python #Coding #Programming #LearnToCode #DevTips #Tech

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"Open Data Structures" is another very useful free resource for anyone studying data structures and algorithms. 📚✨ The book
"Open Data Structures" is another very useful free resource for anyone studying data structures and algorithms. 📚✨ The book discusses the implementation and analysis of basic structures: array-based lists, linked lists, hash tables, binary trees, red-black trees, heaps, sorting algorithms, graphs, and data structures for working with integers. 🔍🧮 This is a full-fledged open textbook for studying one of the fundamental topics of computer science and a good reference that's worth keeping on hand. 💻🌟 https://opendatastructures.org/ods-python.pdf 📄 👉 @PythonRe #DataStructures #Algorithms #Python #ComputerScience #OpenSource #Learning

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Do you know that Python can shift sequences without slicing and creating new lists? 🤔 When you need to cyclically shift data, many use slicing:
data = data[-1:] + data[:-1]
But deque.rotate() does this at the level of the data structure and usually works more efficiently for cyclical operations. 🚀
q.rotate(1)
A negative value rotates the queue in the other direction. ⬅️
q.rotate(-2)
This is useful for ring buffers, task schedulers, cyclical queues, and round-robin algorithms. 🔄
workers.rotate(-1)
🔥 deque.rotate() allows you to implement cyclical data structures without manual index logic and without creating new lists. 💡 #Python #Programming #Deque #CodingTips #Tech #DevCommunity

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The Python library itertools contains many useful functions. 🐍✨ One of them is compress(), which returns an iterator over th
The Python library itertools contains many useful functions. 🐍✨ One of them is compress(), which returns an iterator over the elements from data, for which the corresponding element in selectors is equal to True. 🔍💻 Here's an example: 📝👇 #Python #Programming #Itertools #Coding #Tech #DataScience

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Many applications require mapping strings to integers. In Python, this usually looks like: d = {"apple": 100, "banana": 200,
Many applications require mapping strings to integers. In Python, this usually looks like:
d = {"apple": 100, "banana": 200, "cherry": 300}
If there are 1 million keys, this can consume a lot of memory — more than 100 bytes per key. Our elephant has published a new library that uses about 9 bytes per key. Yes, only 9 bytes. Usage looks like this:
from fastconstmap import ConstMap

d = {"apple": 100, "banana": 200, "cherry": 300}
m = ConstMap(d)

m["apple"]                  # -> 100
m.get_many(["banana", "cherry"])  # -> [200, 300]
It can be significantly faster (for example, up to 2 times in some cases) than the standard dictionary. It can also be serialized and deserialized to disk or network for convenient reuse. https://pypi.org/project/fastconstmap/ github: https://github.com/lemire/fastconstmap 👉 @PythonRe

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Python Basics Notes 🐍📚 https://t.me/pythonRe 🔗 #Python #Coding #Programming #LearnPython #Tech #DevCommunity

🙏💸 500$ FOR THE FIRST 500 WHO JOIN THE CHANNEL! 🙏💸 Join our channel today for free! Tomorrow it will cost 500$! https://t
🙏💸 500$ FOR THE FIRST 500 WHO JOIN THE CHANNEL! 🙏💸 Join our channel today for free! Tomorrow it will cost 500$! https://t.me/+-WZeIeP8YI8wM2E6 You can join at this link! 👆👇 https://t.me/+-WZeIeP8YI8wM2E6

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𝗣𝘆𝘁𝗵𝗼𝗻 𝗶𝘀 𝘁𝗵𝗲 𝗡𝗲𝘄 𝗘𝗻𝗴𝗹𝗶𝘀𝗵. 𝗦𝗽𝗲𝗮𝗸 𝗜𝘁 𝗙𝗹𝘂𝗲𝗻𝘁𝗹𝘆! Here’s Your Ultimate Guide!
𝗜𝗻𝗽𝘂𝘁/𝗢𝘂𝘁𝗽𝘂𝘁 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀
- print() 
- input() 
- format()

𝗗𝗮𝘁𝗮 𝗧𝘆𝗽𝗲 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀  
- int() 
- float()  
- str() 
- bool() 
- complex()  
- list() 
- tuple()
- set() 
- dict()
- frozenset()  
- bytes()
- bytearray()  
- memoryview()  

𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀
- abs()
- pow()  
- round()
- divmod()  
- sum()  
- min()  
- max()  

𝗦𝗲𝗾𝘂𝗲𝗻𝗰𝗲 & 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀  
- len()  
- sorted() 
- range() 
- zip() 
- enumerate()
- reversed() 
- all()  
- any() 

𝗧𝘆𝗽𝗲 & 𝗢𝗯𝗷𝗲𝗰𝘁 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀
- type()
- id()
- isinstance()  
- issubclass()

𝗙𝗶𝗹𝗲 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀
- open()
- close()  
- read()
- write()  
- seek()
- tell()

𝗦𝘁𝗿𝗶𝗻𝗴 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀
- ord()
- chr()
- ascii()
- repr()

𝗨𝘁𝗶𝗹𝗶𝘁𝘆 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 
- help() 
- dir()
- eval()  
- exec() 
- hash()

𝗟𝗼𝗴𝗶𝗰𝗮𝗹 & 𝗕𝗼𝗼𝗹𝗲𝗮𝗻 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀
- bin()
- oct() 
- hex()
- bool()

𝗠𝗲𝗺𝗼𝗿𝘆 & 𝗢𝗯𝗷𝗲𝗰𝘁 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀
- memoryview()
- object()
- callable()