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

Network:Machine Learning with Python India9 700 Technologies & Applications3 238...

📈 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 40 060 subscribers, ranking 3 238 in the Technologies & Applications category and 9 700 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 060 subscribers.

According to the latest data from 26 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 182 over the last 30 days and by -10 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 2.93%. Within the first 24 hours after publication, content typically collects 1.12% reactions from the total number of subscribers.
Post reach: On average, each post receives 1 172 views. Within the first day, a publication typically gains 447 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
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 August, 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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40 060

Subscribers

-1024 hours

-397 days

+18230 days

1 172

Post views

~ 44724 hours

~ 63948 hours

2.93%

Engagement rate

~ 2

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Top 10 Python One Liners! 1️⃣ Reverse a string:

reversed_string = "Hello World"[::-1]

2️⃣ Check if a number is even:

is_even = lambda x: x % 2 == 0

3️⃣ Find the factorial of a number:

factorial = lambda x: 1 if x == 0 else x * factorial(x - 1)

4️⃣ Read a file and print its contents:

[print(line.strip()) for line in open('file.txt')]

5️⃣ Create a list of squares:

squares = [x**2 for x in range(10)]

6️⃣ Flatten a list of lists:

flat_list = [item for sublist in [[1, 2], [3, 4], [5, 6]] for item in sublist]

7️⃣ Find the length of a list:

length = len([1, 2, 3, 4])

8️⃣ Create a dictionary from two lists:

keys = ['a', 'b', 'c']; values = [1, 2, 3]; dictionary = dict(zip(keys, values))

9️⃣ Generate a list of random numbers:

import random; random_numbers = [random.randint(0, 100) for _ in range(10)]

🔟 Check if a string is a palindrome:

is_palindrome = lambda s: s == s[::-1]

Mastering these one-liners can significantly improve your coding efficiency and make your code more concise. https://t.me/pythonRe ✉️

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What is a Lambda Function? A lambda function is a small anonymous function defined using the lambda keyword. It's often used for short, throwaway functions that are only needed temporarily. Basic Syntax- The syntax of a lambda function is: "lambda arguments: expression" -arguments: A comma-separated list of parameters. -expression: An expression that is evaluated and returned. Examples 1️⃣ Basic Lambda Function: "add = lambda x, y: x + y print(add(2, 3)) # Output: 5 " Here, lambda x, y: x + y is a lambda function that adds two numbers. 2️⃣ Lambda with map(): "numbers = [1, 2, 3, 4, 5] squared = list(map(lambda x: x ** 2, numbers)) print(squared) # Output: [1, 4, 9, 16, 25] " map() applies the lambda function to each item in the numbers list. 3️⃣ Lambda with filter(): "numbers = [1, 2, 3, 4, 5] even = list(filter(lambda x: x % 2 == 0, numbers)) print(even) # Output: [2, 4] " filter() uses the lambda function to filter out only the even numbers. 4️⃣ Lambda with reduce(): "from functools import reduce numbers = [1, 2, 3, 4, 5] product = reduce(lambda x, y: x * y, numbers) print(product) # Output: 120 " reduce() applies the lambda function cumulatively to the items in the list. Pros and Cons- Pros: -> Concise and readable. -> Useful for small, simple functions. -> Handy for functional programming (e.g., map, filter, reduce). Cons: -> Limited to single expressions. -> Can be less readable if overused. -> Lack of function name can make debugging harder. Lambda functions are an excellent tool for any Python developer to have in their toolkit. They can help streamline your code and make your functions more elegant and efficient.

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✨ Quiz: The Factory Method Pattern and Its Implementation in Python ✨ 📖 Check your grasp of the Factory Method pattern in Python: when to use it, the roles involved, and how to implement a flexible object factory. 🏷️ #intermediate #best-practices

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✨ netrc | Python Standard Library ✨ 📖 Provides tools for parsing .netrc credentials files and looking up logins, accounts, and passwords by host. 🏷️ #Python

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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

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Repost from Machine Learning with Python

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✨ How to Use OpenCode for AI-Assisted Python Coding ✨ 📖 Learn how to use OpenCode, an open-source AI coding assistant, with a free Gemini API key to analyze and refactor Python code in your terminal. 🏷️ #intermediate #ai #python #tools

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✨ Quiz: Using Python for Data Analysis ✨ 📖 Test your understanding of a data analysis workflow in Python, from cleansing raw data with pandas to spotting insights with regression. 🏷️ #intermediate #best-practices #data-science #python

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✨ getopt | Python Standard Library ✨ 📖 Provides tools for parsing command line options from sys.argv following Unix getopt() conventions, with support for both short and long option styles. 🏷️ #Python

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✨ A New Python Packaging Council and Other News for May 2026 ✨ 📖 A new Python Packaging Council, PEP 803 stabilizes the free-threaded ABI, the incremental GC gets reverted, and Astral changes hands. 🏷️ #community #news

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✨ Quiz: ChatterBot: Build a Chatbot With Python ✨ 📖 Test your understanding of the ChatterBot Python library, from training a basic bot with ListTrainer to wiring in a local LLM through Ollama. 🏷️ #intermediate #data-science #projects

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✨ Quiz: Python 3.13: A Modern REPL ✨ 📖 Test your understanding of the redesigned Python 3.13 REPL with color support, multiline editing, paste mode, and history browsing. 🏷️ #basics #python

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