Python Interviews

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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

Red:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert India15 162 Tecnologías y Aplicaciones4 796...

📈 Análisis del canal de Telegram Python Interviews

El canal Python Interviews (@pythoninterviews) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 28 762 suscriptores, ocupando la posición 4 796 en la categoría Tecnologías y Aplicaciones y el puesto 15 162 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 28 762 suscriptores.

Según los últimos datos del 08 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 59, y en las últimas 24 horas de -11, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 0.57%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.81% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 163 visualizaciones. En el primer día suele acumular 234 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 1.
Intereses temáticos: El contenido se centra en temas clave como |--, link:-, learning, sql, analytic.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 09 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

28 762

Suscriptores

-1124 horas

+217 días

+5930 días

163

Visitas de la publicación

~ 23424 horas

~ 30148 horas

0.57%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

beta

Archivo de publicaciones

28 762

17_Day_17_Intermediate_The_Quiz_Project_&_the_Benefits_of_OOP.zip362.42 MB

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16_Day_16_Intermediate_Object_Oriented_Programming_OOP.zip390.59 MB

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15_Day_15_Intermediate_Local_Development_Environment_Setup_&_the.zip442.32 MB

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

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13_Day_13_Beginner_Debugging_How_to_Find_and_Fix_Errors_in_your.zip247.13 MB

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

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

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

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9_Day_9_Beginner_Dictionaries,_Nesting_and_the_Secret_Auction.zip399.25 MB

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8_Day_8_Beginner_Function_Parameters_&_Caesar_Cipher.zip617.60 MB

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

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

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@programming_guide

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100 Days of Code: Python Bootcamp

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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

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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)

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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)

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

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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

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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