✨ Get Started With FastAPI ✨
📖 FastAPI is the first choice when creating APIs in Python. Explore FastAPI code examples and get the most frequent questions about FastAPI answered.
🏷️ #intermediate #api #frontend #webdev
📖 FastAPI is the first choice when creating APIs in Python. Explore FastAPI code examples and get the most frequent questions about FastAPI answered.
🏷️ #intermediate #api #frontend #webdev
📌 Python Cheatsheet + Free Courses to Kickstart Your Journey in 2025
Learning Python is one of the best investments you can make for your career in tech.
This cheatsheet makes it easier to get started with the fundamentals, advanced concepts, and practical tools.
To go further, here are some free courses you should not miss this year:
→ Introduction to Programming with Python
https://lnkd.in/d2Zvwgix
→ Python Courses
https://lnkd.in/dRkaqW_p
https://lnkd.in/dFvKvbNw
https://t.me/DataScience4 🩵
Learning Python is one of the best investments you can make for your career in tech.
This cheatsheet makes it easier to get started with the fundamentals, advanced concepts, and practical tools.
To go further, here are some free courses you should not miss this year:
→ Introduction to Programming with Python
https://lnkd.in/d2Zvwgix
→ Python Courses
https://lnkd.in/dRkaqW_p
https://lnkd.in/dFvKvbNw
https://t.me/DataScience4 🩵
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Forwarded from Machine Learning
📌 Data Engineering – ORM and ODM with Python
🗂 Category: DATA ENGINEERING
🕒 Date: 2025-01-02 | ⏱️ Read time: 7 min read
Manipulate database data leveraging an object-oriented programming paradigm
🗂 Category: DATA ENGINEERING
🕒 Date: 2025-01-02 | ⏱️ Read time: 7 min read
Manipulate database data leveraging an object-oriented programming paradigm
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✨ Quiz: Python Project Management With uv ✨
📖 Test your skills with uv, the fast Python project manager. Practice setup, package installs, and key files created by uv.
🏷️ #intermediate #tools
📖 Test your skills with uv, the fast Python project manager. Practice setup, package installs, and key files created by uv.
🏷️ #intermediate #tools
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✨ Visual Studio IntelliCode | AI Coding Tools ✨
📖 An AI-assisted coding feature that augments IntelliSense.
🏷️ #Python
📖 An AI-assisted coding feature that augments IntelliSense.
🏷️ #Python
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Cheat sheet for f-strings in Python
f-strings are one of the simplest and fastest ways to format texts in Python.
Save this cheat sheet to always have it handy⌨️
Extended version here
https://fstring.help/cheat/
https://t.me/DataScience4🔰
f-strings are one of the simplest and fastest ways to format texts in Python.
Save this cheat sheet to always have it handy
Extended version here
https://fstring.help/cheat/
https://t.me/DataScience4
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fstring.help
Python f-string cheat sheet
Get quick help with Python's f-string syntax
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✨ Python MCP: Connect Your LLM With the World ✨
📖 Learn how to build a Model Context Protocol (MCP) server in Python. Connect tools, prompts, and data to AI agents like Cursor for smarter assistants.
🏷️ #intermediate
📖 Learn how to build a Model Context Protocol (MCP) server in Python. Connect tools, prompts, and data to AI agents like Cursor for smarter assistants.
🏷️ #intermediate
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✨ Gemini Code Assist | AI Coding Tools ✨
📖 An AI coding assistant for integrated development environments (IDEs) and Google Cloud.
🏷️ #Python
📖 An AI coding assistant for integrated development environments (IDEs) and Google Cloud.
🏷️ #Python
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RapidProxy provides developers with a reliable proxy network built for scale.
🌐 https://www.rapidproxy.io/?ref=tst
Why Developers Choose RapidProxy
No monthly lock-in. Pay once, use when you need—perfect for long-term projects.
Evaluate performance before committing. Ideal for experimenting with your Python workflows.
90M+ clean residential IPs across 200+ countries and cities. Great for bypassing restrictions, collecting data, or managing accounts.
HTTP(S) & SOCKS5 compatibility ensures smooth integration with tools like requests, Scrapy, or Selenium.
Residential Proxy: from $0.65/GB, traffic never expires.
Static (ISP) Residential Proxy: $5/IP, unlimited traffic for 30 days (easy renewal).
Get started in minutes:
1️⃣ Sign up at RapidProxy.io
2️⃣ Claim your free trial traffic
3️⃣ Scale your scraping, automation, or research projects with confidence
☑️99.9% uptime guarantee
☑️Ultra-low 0.38s average response time
☑️Unlimited concurrent sessions for high-volume tasks
RapidProxy — Fast · Reliable · Developer-Friendly
Your trusted partner for Python scraping and global online operations.
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✨ Code Llama | AI Coding Tools ✨
📖 A family of code-specialized large language models (LLMs) for generating, completing, and explaining source code.
🏷️ #Python
📖 A family of code-specialized large language models (LLMs) for generating, completing, and explaining source code.
🏷️ #Python
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✨ Astral's ty: A New Blazing-Fast Type Checker for Python ✨
📖 Learn to use ty, an ultra-fast Python type checker written in Rust. Get setup instructions, run type checks, and fine-tune custom rules in personal projects.
🏷️ #intermediate #tools
📖 Learn to use ty, an ultra-fast Python type checker written in Rust. Get setup instructions, run type checks, and fine-tune custom rules in personal projects.
🏷️ #intermediate #tools
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4 ways to copy a list in Python
In Python, there are several ways to make a copy of a list. But it is important to understand the difference between a shallow copy and a deep copy.
Now let's check the difference between shallow and deep copy:
👉 https://t.me/DataScience4
In Python, there are several ways to make a copy of a list. But it is important to understand the difference between a shallow copy and a deep copy.
original = [1, 2, [3, 4]]
# 1. Slice (shallow copy)
copy1 = original[:]
# 2. .copy() method (shallow copy)
copy2 = original.copy()
# 3. Using list() (shallow copy)
copy3 = list(original)
# 4. deepcopy (deep copy)
import copy
copy4 = copy.deepcopy(original)
Now let's check the difference between shallow and deep copy:
original[2].append(5)
print(copy1)
# [1, 2, [3, 4, 5]] — nested list changed!
print(copy4)
# [1, 2, [3, 4]] — unchanged
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