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Python Interviews

Python Interviews

رفتن به کانال در 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

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📈 تحلیل کانال تلگرام Python Interviews

کانال Python Interviews (@pythoninterviews) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 28 854 مشترک است و جایگاه 4 620 را در دسته فناوری و برنامه‌ها و رتبه 14 448 را در منطقه الهند دارد.

📊 شاخص‌های مخاطب و پویایی

از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 28 854 مشترک جذب کرده است.

بر اساس آخرین داده‌ها در تاریخ 30 ژوئیه, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 102 و در ۲۴ ساعت گذشته برابر 2 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.

  • وضعیت تأیید: تأیید نشده
  • نرخ تعامل (ER): میانگین تعامل مخاطب 2.55% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.66% واکنش نسبت به کل مشترکان کسب می‌کند.
  • دسترسی پست‌ها: هر پست به طور میانگین 735 بازدید دریافت می‌کند. در اولین روز معمولاً 191 بازدید جمع‌آوری می‌شود.
  • واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 2 است.
  • علایق موضوعی: محتوا بر موضوعات کلیدی مانند |--, link:-, learning, sql, analytic تمرکز دارد.

📝 توضیح و سیاست محتوایی

نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
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

به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 31 ژوئیه, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامه‌ها تبدیل کرده‌اند.

28 854
مشترکین
+224 ساعت
+367 روز
+10230 روز
آرشیو پست ها
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

HTTP Requests 🔸Requests is an elegant and simple HTTP library for Python. It allows you to send HTTP/1.1 requests extremely easy, so you can focus on interacting with services and consuming data in your application. ⚙️Installation pip install requests The most-commonly-used HTTP methods are GET and POST: requests.get(url) requests.post(url, data=somedictdata) Each of there functions returns a Response. It's a really powerful object for inspecting the results of the request. We can get all the information we need from this object like text, status code or encoding. 🔗Docs 🔗Python’s Requests Library (Guide) #requests

What are Python Modules? Python modules are files containing Python code. A module can define functions, classes and variables. A module can also include runnable code. Grouping related code into a module makes the code easier to understand and use.

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