Learn Python Web Development with Frameworks and Databases

Why I like working with Python 🐍 Python is one of the most practical and beginner-friendly programming languages. Its simple syntax makes it easy to learn, but it is also powerful enough to build real applications. I’ve been learning and building projects with Python, especially using Django for web development. Python allows developers to create web applications, automate tasks, work with data, and build scalable backend systems. Every project I build helps me improve my problem-solving skills and understand how real applications work. Looking forward to learning more and building better projects with Python. #Python #PythonDeveloper #Programming #BackendDevelopment #Django#open to work

🐍🕸 Python Web Development Tutorials — In this section cover techniques used in the development of Python Web applications and focus on how to program real-world solutions to problems that ordinary people actually want to solve https://lnkd.in/g8Jc8fT

Python for PHP Devs — 7-Day Quick Plan If you are at all like me, you started your development path somewhere else, but now are working in Python more and more. Here's a quick 7 day started plan to boost your familiarity with Python. https://lnkd.in/gVugsHdV

🚀 Day 15/50 – Convert Python (.py) to Executable (.exe) ⚙️ Today I learned how to convert a Python script into a standalone executable file (.exe). This allows Python programs to run on systems without requiring Python installation, making it easier to distribute applications to users. For this, I used PyInstaller, a popular tool that bundles Python scripts and dependencies into a single executable file. 🛠 How It Works The tool packages your Python script along with all required libraries into a single .exe file. This means: No need to install Python on another system Easy distribution of applications Works like a normal software program ⚙ Technologies Used Python PyInstaller 📚 Key Learnings ✔ Converting Python scripts into executable files ✔ Packaging dependencies with applications ✔ Creating distributable Python software ✔ Understanding basic software deployment 📂 Project Available on GitHub You can explore the full project here: 👉 https://lnkd.in/g4kVDpG4 #Python #PythonProjects #50DaysOfCode #LearningInPublic #Programming #Developers #CodingJourney #PythonDeveloper #BuildInPublic #Automation

As a Python Django developer, I believe strong fundamentals are everything. Revisiting Python list methods like append(), insert(), pop(), and reverse()—simple tools that play a big role in writing clean and efficient backend logic. #Python #Django #BackendDevelopment #WebDevelopment #Coding #Developers

Most developers learn Python. Very few learn how to think in Python. Here’s what I mean 👇 Many beginners write Python like this: • Overcomplicated loops • Unnecessary classes • Long functions doing multiple things • Code that works… but is hard to read But Python was designed for clarity and simplicity. Good Python code should feel almost like reading English. Instead of writing clever code, experienced developers focus on: ✔ Readability ✔ Simple logic ✔ Small reusable functions ✔ Using built-in Python features properly The best Python developers I’ve seen don’t write the most complex code. They write the clearest code. And that’s what makes systems easier to scale and maintain. What’s one Python habit that improved your coding style? #Python #Programming #Developers #SoftwareEngineering #Coding #BackendDevelopment

🐍📈 Flask by Example — You're going to start building a Flask app that calculates word-frequency pairs based on the text from a given URL. This is a full-stack tutorial covering a number of web development techniques #python #learnpython

The best Python setup is not the one with the most extensions. It’s the one with the fewest surprises. I shared a practical Medium post on the best VS Code extensions for Python development and how to avoid editor overload. Read here: https://lnkd.in/dVgDwEHG

🚀 Visualizing Python Code Execution with Open Source As a backend Python developer, I always try to understand not just *what code does*, but **how it actually runs internally**. Recently, I explored an amazing open-source tool: **PyVisualizer**. It allows you to visually track how Python code executes step-by-step — variables, memory changes, and logic flow. I created a short demo video showing how a Python program evolves during execution. Why this matters for developers 👇 🔹 **Debugging becomes clearer** – You see exactly how variables change in memory. 🔹 **Better algorithm understanding** – Especially useful for data structures and problem solving. 🔹 **Great for teaching & learning** – Makes complex logic visually simple. 🔹 **Open source power** – Tools like this remind us how powerful the developer community is. For Python and backend developers, tools like this help strengthen the **mental model of how code actually behaves at runtime**. My takeaway: Good developers don’t just write code — they **visualize and understand the execution behind it**. If you are learning Python or preparing for coding interviews, try visualizing your code execution at least once. It can completely change how you debug and design logic. 🎥 Demo video attached. #Python #BackendDevelopment #OpenSource #SoftwareEngineering #Debugging #LearningInPublic

Converting Python Dictionaries to JSON: A Simple Guide Working with JSON in Python is crucial, especially when integrating with web APIs or handling configuration files. JSON (JavaScript Object Notation) is a lightweight data interchange format that is both human-readable and machine-readable. In the example, we start by importing the JSON module, which is part of Python’s standard library. Next, we define a simple Python dictionary. This data structure is versatile and easy to manipulate, making it a perfect candidate for JSON conversion. The function `json.dumps()` is then used to convert the dictionary into a JSON string. This serialization process transforms the dictionary into a format that can be easily transmitted or stored. When printed, the JSON string appears as expected, structured to facilitate data exchange. To convert the JSON string back into a Python dictionary, we use `json.loads()`, which deserializes the JSON, allowing us to manipulate the data in its original form. JSON's simplicity and flexibility make it an essential tool for data exchange in web development, where compatibility and efficiency are critical. Understanding its serialization and deserialization processes opens doors to various applications, from handling API responses to saving configurations. Quick challenge: How would you modify the code to handle a nested dictionary for JSON conversion? #WhatImReadingToday #Python #PythonProgramming #JSON #WebDevelopment #Programming