Code With Python – Telegram
Code With Python
39K subscribers
841 photos
24 videos
22 files
746 links
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills.
Admin: @HusseinSheikho || @Hussein_Sheikho
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Quiz: Python Skill Test

📖 Test your Python knowledge in a skill quiz with basic to advanced questions. Are you a Novice, Intermediate, Proficient, or Expert?

🏷️ #python
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How to Drop Null Values in pandas

📖 Learn how to use .dropna() to drop null values from pandas DataFrames so you can clean missing data and keep your Python analysis accurate.

🏷️ #basics #datascience #python
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Code With Python pinned «🔍 Searching for fast, reliable proxies for your data science and machine learning projects? Thordata provides the perfect solution for all your data scraping needs! 👍 https://www.thordata.com/?ls=DhthVzyG&lk=Data Why Choose Thordata? Rotating & Sticky…»
Claude Code | AI Coding Tools

📖 An AI‑powered command‑line coding assistant.

🏷️ #Python
ChatGPT | AI Coding Tools

📖 An AI chatbot that understands and generates natural language and Python code.

🏷️ #Python
Quiz: Python Annotations

📖 Test your knowledge of annotations and type hints, including how different Python versions evaluate them at runtime.

🏷️ #intermediate #python
Reference: AI Coding Tools

📖 Explore today’s leading AI coding tools and their growing impact on modern software development workflows.

🏷️ #terms
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Cursor | AI Coding Tools

📖 An AI-powered integrated development environment (IDE) based on Visual Studio Code.

🏷️ #Python
Windsurf | AI Coding Tools

📖 An AI‑native integrated development environment (IDE) and coding assistant

🏷️ #Python
GitHub Copilot Chat | AI Coding Tools

📖 An AI coding tool that integrates with supported code editors, enabling developers to conversationally interact with an AI assistant directly within their IDE.

🏷️ #Python
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Quiz: Working With Python's .__dict__ Attribute

📖 Practice how Python's .__dict__ attribute works for classes, instances, and functions, and when mappingproxy and __slots__ come into play.

🏷️ #advanced #python
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Quiz: Exploring Python T-Strings

📖 Explore Python's t-strings, including their syntax, use cases, and differences from f-strings and older approaches.

🏷️ #intermediate #python
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Quiz: Profiling Performance in Python

📖 Test your knowledge of Python profiling and performance tools. Practice identifying bottlenecks and using profilers like cProfile and timeit.

🏷️ #intermediate #tools
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What Does -> Mean in Python Function Definitions?

📖 Wondering what the arrow notation means in Python? Discover how -> is used in type hints, functions, and more with simple explanations and examples.

🏷️ #basics #python
Codex CLI | AI Coding Tools

📖 A command-line interface for interacting with the OpenAI Codex tool.

🏷️ #Python
Quiz: Exploring Python Closures: Examples and Use Cases

📖 In this quiz, you'll test your understanding of Python closures. Closures are a common feature in functional programming languages and are particularly popular in Python because they allow you to create function-based decorators.

🏷️ #intermediate #python
Quiz: Deep vs Shallow Copies in Python

📖 Test your understanding of deep and shallow copying in Python. Review assignment, identity, and how to copy complex objects correctly.

🏷️ #advanced #python
How to work with Microsoft SQL Server in Python?

You can connect, read, and insert data into an SQL database with just a few lines of Python code.

Microsoft SQL with Python:

pip install mssql-python


Code to connect to SQL Server:

import mssql_python

# Establish connection
# Specify connection string
connection_string = "YOUR_CONNECTION_STRING"
connection = mssql_python.connect(connection_string)

# Execute query
cursor = connection.cursor()
cursor.execute("SELECT * from customer")
rows = cursor.fetchall()

for row in rows:
    print(row)

# Close connection
connection.close()


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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

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