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Python Interviews

Python Interviews

الذهاب إلى القناة على Telegram

Join this channel to learn python for web development, data science, artificial intelligence and machine learning with quizzes, projects and amazing resources for free For collaborations: @coderfun

إظهار المزيد

📈 نظرة تحليلية على قناة تيليجرام Python Interviews

تُعد قناة Python Interviews (@pythoninterviews) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 28 762 مشتركاً، محتلاً المرتبة 4 796 في فئة التكنولوجيات والتطبيقات والمرتبة 15 162 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 28 762 مشتركاً.

بحسب آخر البيانات بتاريخ 08 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 59، وفي آخر 24 ساعة بمقدار -11، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 0.57‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 0.81‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 163 مشاهدة. وخلال اليوم الأول يجمع عادةً 234 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 1.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل |--, link:-, learning, sql, analytic.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
Join this channel to learn python for web development, data science, artificial intelligence and machine learning with quizzes, projects and amazing resources for free For collaborations: @coderfun

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 09 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

28 762
المشتركون
-1124 ساعات
+217 أيام
+5930 أيام
أرشيف المشاركات
17_Day_17_Intermediate_The_Quiz_Project_&_the_Benefits_of_OOP.zip362.42 MB

16_Day_16_Intermediate_Object_Oriented_Programming_OOP.zip390.59 MB

15_Day_15_Intermediate_Local_Development_Environment_Setup_&_the.zip442.32 MB

14. Day 14 - Beginner - Higher Lower Game Project.zip293.62 MB

13_Day_13_Beginner_Debugging_How_to_Find_and_Fix_Errors_in_your.zip247.13 MB

12. Day 12 - Beginner - Scope & Number Guessing Game.zip264.40 MB

11. Day 11 - Beginner - The Blackjack Capstone Project.zip401.83 MB

10. Day 10 - Beginner - Functions with Outputs.zip372.14 MB

9_Day_9_Beginner_Dictionaries,_Nesting_and_the_Secret_Auction.zip399.25 MB

8_Day_8_Beginner_Function_Parameters_&_Caesar_Cipher.zip617.60 MB

4. Day 4 - Beginner - Randomisation and Python Lists.zip539.31 MB

3. Day 3 - Beginner - Control Flow and Logical Operators.zip582.76 MB

100 Days of Code: Python Bootcamp

Why should you learn Python? - simple yet powerful - versatile - clean - beginner friendly - tremendous job opportunities - high demand - readability - awesome community - awesome ecosystem - web development - machine learning

ChatGPT can write code faster and seemingly better than many programmers. So will it replace software engineers anytime soon? The answer is No. Here are 4 reasons why: 👇 1) Currently, when doing programming tasks, ChatGPT outputs code. And is everybody able to grok, manipulate, and use code? No—only software engineers are. ChatGPT's current coding-related outputs are useless to the general population and need to be handled by SWEs. 2) ChatGPT has been proven to sometimes give incorrect answers, including buggy code. No sound business will risk getting rid of their SWEs in favor of an AI that can provably write buggy software. 3) ChatGPT currently struggles to successfully debug buggy code, even in simple, self-contained code blocks. We can imagine that this will remain especially true in large, complex codebases. You can't get rid of SWEs if you need them to debug your AI's code. 4) To build complex applications with ChatGPT, you need to give it complex prompts that inherently require some technical knowledge as well as "prompt engineering" prowess. Right now, SWEs are the best-equipped people to write these prompts. Instead of replacing software engineers, ChatGPT will serve as an amazing quality-of-life-improvement tool for them, helping them perform certain programming tasks much faster. If you're a SWE, you don't need to worry about ChatGPT—for now. (Credits: Unknown)

Data types are foundational in computing, and it's essential to understand them to work effectively in any programming environment. Let's take a dive into the top ten commonly used data types: 1. Integer (int): - Represents whole numbers. - Examples: -2, -1, 0, 1, 2, 3 2. Floating Point (float/double): - Represents numbers with decimals. - Examples: -2.5, 0.0, 3.14 3. Character (char): - Represents single characters. - Examples: 'A', 'b', '1', '%' 4. String: - Represents sequences of characters, basically text. - Examples: "Hello", "ChatGPT", "1234" 5. Boolean (bool): - Represents true or false values. - Examples: True, False 6. Array: - Represents a collection of elements, often of the same type. - Examples: [1, 2, 3], ["apple", "banana", "cherry"] 7. Object: - Used in object-oriented programming, represents a combination of data and methods to manipulate the data. - Examples: A Car object might have data like color and speed and methods like drive() and park(). 8. Date & Time: - Represents date and time values. - Examples: 23-10-2023, 12:30:45 9. Byte & Binary: - Represents raw binary data. - Examples: 01010101 (Byte), 101000111011 (Binary) 10. Enum: - Represents a set of named constants. - Examples: Days of the week (Monday, Tuesday...), Colors (Red, Blue, Green)

6 Websites To Practice Faster Typing Online... ⌨️ monkeytype.com ⌨️ keybr.com ⌨️ typings.gg ⌨️ farzher.com ⌨️ typingbolt.com
6 Websites To Practice Faster Typing Online... ⌨️ monkeytype.com ⌨️ keybr.com ⌨️ typings.gg ⌨️ farzher.com ⌨️ typingbolt.com ⌨️ typrx.com

Web Scraping in Python 🔸Scrapy is an open source and collaborative framework for extracting the data you need from websites. It gives you all the tools you need to efficiently extract data from websites, process them as you want, and store them in your preferred structure and format. Unlike BeautifulSoup, which you may have heard of, Scrapy is a tool specifically created for downloading, cleaning and saving data from the web and will help you end-to-end; whereas BeautifulSoup is a smaller package which will only help you get information out of webpages. ⚙️Installation pip install scrapy 🔗Homepage 🔗GitHub 🔗[Tutorial] Making Web Crawlers Using Scrapy for Python #scrapy #web

Visualize code execution Have you ever had a hard time understanding what is going on in your code? Python Tutor's online coding environment allows you to write code and visualize frame-by-frame how it gets executed by the computer. Besides Python, It's also supports Java, C/C++, JavaScript and Ruby. Just pick a language, write some code, press the "Visualize Execution" button and you’ll be redirected to a page, where all the magic happens. 💫 🔗Python Tutor's homepage #tools