Python Access Specifiers: Understanding the Philosophy

🐍 asyncio.gather() might be the new goto of async Python. For years we used: asyncio.create_task() asyncio.gather() And accidentally created zombie tasks, coroutines still running long after the request finished. Python 3.11 introduced a different model: ⚙️ Structured Concurrency with asyncio.TaskGroup. Clear task lifecycles. Deterministic cancellation. No background chaos. I break down why this is one of the biggest shifts in Python async programming. 👉 https://lnkd.in/eBF_AkNe #python #asyncio #backend #softwaredevelopment #engineering

𝗘𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 𝗜𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 In Python, errors are inevitable. Your program must handle them to avoid crashing. You can use exception handling to catch and manage errors. This allows your program to respond to errors without stopping. Here's how it works: - Try: You put risky code here. - Except: You handle errors here. Example: You try to divide a number by zero. Without exception handling, your program stops. With exception handling, you can print an error message and continue. Tips: - Always catch specific exceptions. - Use the finally block to execute code after try and except. - You can manually trigger exceptions using raise. - Create custom exceptions for structured error handling. Exception handling is critical in APIs, backend services, and data processing. It ensures your system behaves predictably even during failures. Mastering exception handling makes your code professional, stable, and production-ready. Source: https://lnkd.in/gHrRR22g

🚀Python Practice Update Today I solved the “String Validators”problem on HackerRank. Key learnings: • Practiced Python string validation methods 🔤 • Used functions like `isalnum()`, `isalpha()`, `isdigit()`, `islower()`, and `isupper()` ✅ • Learned how to check different character types in a string 🔍 • Improved logic-building with loops and conditions 💡 Each challenge is helping me get stronger in Python basics. 🚀 🔗Link: https://lnkd.in/dA4XRHmS #Python #HackerRank #StringValidators #CodingPractice #ProblemSolving #100DaysOfCode #LearningPython #Codegnan #Programming

𝗦𝗲𝗹𝗳 𝗜𝗺𝗽𝗿𝗼𝘃𝗶𝗻𝗴 𝗣𝘆𝘁𝗵𝗼𝗻 𝗦𝗰𝗿𝗶𝗽𝘁𝘀 𝗪𝗶𝘁𝗵 𝗟𝗟𝗠𝘀 I wanted code to fix itself. I used LLMs to make Python scripts improve their own logic. Here is the setup: - Python 3.8 or later - llm_groq - transformers The workflow is simple. The LLM writes a piece of code. A script runs the code to check for errors. If the code fails, the LLM receives the error. The LLM rewrites the code to fix the mistake. I faced problems. LLMs write wrong code sometimes. I built a strict evaluation function to catch these errors. I tested prompts to get better results. Self-improving code changes how you build software. Start building your own scripts. Source: https://lnkd.in/gcyzxwXz Optional learning community: https://t.me/GyaanSetuAi

Python List Methods Tip: append() and extend() Most Python Beginners Don’t Realize This List Mistake, append() and extend() look almost the same… But using the wrong one silently changes your data structure. Here’s the real difference: - append() adds the entire object as ONE element. - extend() adds each element individually. That means this: - append() → Creates nested lists - extend() → Keeps list flat Why This Matters: - This small mistake often causes unexpected bugs while looping, filtering, or processing data. - Many developers only notice it when their logic suddenly stops working. Simple Rule To Remember: - If you want to add one item → append() - If you want to merge items → extend() Small concepts like this make your Python code cleaner and easier to debug. Have you ever accidentally created a nested list using append()? #Python #LearnPython #PythonTips #Programming #Coding #SoftwareEngineering #PythonDeveloper

Handling Files in Python: Best Practices for Opening Opening files in Python is a foundational skill for data manipulation and processing. The code above demonstrates how to open a file safely using a context manager, represented by the `with` statement. This approach ensures that the file is properly closed after its block of code is executed, even if an error occurs. Without the context manager, you might leave the file open after reading it, leading to potential memory leaks or file corruption. By using `with`, Python takes care of closing the file automatically, making your code cleaner and safer. It also helps handle exceptions gracefully. For instance, if the specified file is not found, a `FileNotFoundError` will trigger the exception block, allowing you to inform the user without crashing the program. This becomes critical when working on projects that involve multiple files or external resources. The need for efficient resource management cannot be overstated, especially in larger applications where multiple files may be opened. Quick challenge: How would you modify this code to open a file for writing, ensuring that it creates the file if it doesn't exist? #WhatImReadingToday #Python #PythonProgramming #FileHandling #LearnPython #Programming

Understanding Python Encapsulation Encapsulation is a fundamental concept in object-oriented programming that restricts direct access to certain attributes or methods. In Python, this is achieved using private attributes, which are designated by a preceding double underscore (e.g., `__balance`). This convention indicates that the attribute should not be accessible outside the class, promoting data hiding and ensuring better control over how the data can be modified. In the provided code, the `BankAccount` class demonstrates encapsulation. The `__balance` attribute is a private variable, ensuring that it cannot be accessed directly from outside the class. Instead, public methods like `get_balance()`, `deposit()`, and `withdraw()` are provided to interact with this private variable safely. This structure helps to validate inputs and maintain integrity, as any changes to the balance must go through these methods, which can enforce rules like not allowing negative deposits or withdrawals exceeding the current balance. This becomes critical when managing sensitive data, such as financial information in the example. By masking the underlying implementation details, encapsulation allows you to change the internal workings of a class without affecting code that uses the class. This flexibility adds to the robustness and maintainability of your code. Quick challenge: How would you modify the `BankAccount` class to include a method that prevents the balance from going below zero? #WhatImReadingToday #Python #PythonProgramming #OOP #Encapsulation #Programming

📅 Day 4 – Python Sets 🐍 Today I learned one of the most useful concepts in Python – Sets and practiced different operations on them 👇 🧠 What is a Set? A set is a collection of unique elements stored in a single variable. It does not allow duplicates and does not follow any specific order. 📚 What I learned: • Sets are unordered and mutable • Duplicate values are automatically removed • Useful for storing unique data • Fast operations compared to lists 🔄 Operations I practiced: • Union → combine sets • Intersection → common elements • Difference → unique elements from one set • Symmetric Difference → uncommon elements 📸 I practiced these operations with small programs (screenshots attached 👇) Sets are very helpful when working with unique values and performing mathematical operations efficiently. Consistent daily practice is helping me improve step by step 💪 #Python #100DaysOfCode #CodingJourney #LearningPython #Developers

👩🍳 "Python isn't programming. It's writing recipes that the computer follows. Exactly. Every time." That's what TryHackMe's Python: Simple Demo room showed me. The recipe structure: 📝 Variables → Ingredients. name = "Alice", age = 25, is_hacker = True 🥣 Functions → Steps in the recipe. def greet_user(): then print("Hello") 🔁 Loops → Repeat a step. for i in range(5): → do something 5 times ⚡ Conditionals → If this, do that. if temperature > 100: print("Too hot!") What I built in this room: python name = input("What is your name? ") print(f"Hello, {name}!") First program. Input. Output. It worked. Felt like magic. Why this matters for security: 🔐 Automate log analysis (read 10,000 lines in 1 second) 🔐 Build your own port scanner 🔐 Decode encoded data (Base64, hex, binary) 🔐 Reverse engineer simple malware The big takeaway: You don't need to be a developer. You need to be someone who can tell the computer what to do. Python is how you talk. Recipe written. Computer followed. Room complete. 🐍 #PythonSimpleDemo #TryHackMe #Python #CodingForSecurity #Automation #CyberSecurity #Infosec