Real Python’s Post

🐍📈 Become a Python Web Developer This learning path will provide you with the foundational skills you need to become a Python web developer. You’ll cover the most popular Python web development frameworks & working with databases. #python #learnpython

Start your programming journey with Python — the most beginner-friendly language in the world. Learn what Python is, why it’s powerful, and write your first program step by step. https://lnkd.in/gfCUWc6G

I wrote a short guide on using `uv` for Python dependency management. It’s helped clean up my local environments a bit, so I thought I’d share it in case it’s useful to anyone else. https://lnkd.in/dwqduhp9 #Python #uv

🐍📰 Data Version Control With Python and DVC In this tutorial, you'll find out how data version control helps you to track your data, share development machines with your team, and create easily reproducible experiments #python

Stop writing Python like Java/C++! Building scalable applications in Python means embracing its unique strengths, not fighting them. A truly "clean" API in Python isn't just about naming conventions; it's about thinking in terms of Python's object model, its dynamic nature, and its emphasis on readability. Let's look at how we handle optional parameters. Okay: class Service: def process(self, data, config=None): if config is None: config = {} # Boilerplate to handle None # ... process with data and config Best (Pythonic): class Service: def process(self, data, config=None): config = config or {} # Concise and idiomatic # ... process with data and config The "Best" version uses Python's truthiness. None evaluates to False, so config or {} will assign an empty dictionary if config is None, otherwise it uses the provided config. It's shorter, clearer, and less prone to errors. Takeaway: Design APIs that leverage Python's expressiveness for clarity and conciseness. #Python #CodingTips

7 Python Mistakes That Make Your Code Slow 🐍 👉 Bad coding practices make Python slow — not Python itself. When written correctly, Python powers some of the world’s biggest platforms like Google, Netflix, and Instagram. The difference between average Python code and professional Python code is usually these small mistakes. Here are some serious Python mistakes developers often make 👇 ❌ Writing nested loops for heavy operations ❌ Ignoring list comprehensions ❌ Not using virtual environments ❌ Poor error handling ❌ Writing everything in one huge script ❌ Not using built-in libraries ❌ Inefficient database queries Professional Python developers do this instead 👇 ✅ Use list comprehensions & generators ✅ Split code into modular functions and classes ✅ Use virtual environments for dependencies ✅ Implement proper exception handling ✅ Use built-in optimized libraries ✅ Optimize database queries ✅ Write clean and maintainable code When used properly, **Python can handle large-scale applications, AI systems, and data platforms efficiently. Which Python mistake do you see most often? #python #pythondeveloper #programmingtips #softwaredeveloper #codinglife #webdevelopment #backenddeveloper #developercommunity #learnpython #programming

Organizing your Python code with modules and packages makes it easier to reuse, maintain, and scale projects. Just split functionality into .py files (modules) and group related ones into packages with __init__.py. It’s one of the best ways to keep your codebase clean and professional! 🐍 Read More: https://lnkd.in/daWhU88Q #Python #CodeQuality #SoftwareEngineering #DevTips

I built a project using Python & Django 🚀 Here’s what it does: 🔹 Handles real-time requests 🔹 Built REST APIs 🔹 Optimized database queries Biggest learning: 👉 Writing code is easy 👉 Writing efficient code is HARD Always optimize. Always improve. #Projects #DjangoDeveloper #PythonProjects #BuildInPublic #Python #Django #BackendDeveloper #TechCareers #hiring #hire #developer #dailypost

The latest Qt for Python 6.11 release focuses on Qt Bridges, simplifying Python-Qt integration, and continues alignment with Qt/C++ updates to keep Qt for Python up to date with upstream improvements. See what is new and what is still in progress in the release blog:

The latest Qt for Python 6.11 release focuses on Qt Bridges, simplifying Python-Qt integration, and continues alignment with Qt/C++ updates to keep Qt for Python up to date with upstream improvements. See what is new and what is still in progress in the release blog: