Python List Management: Extend vs Append

I’ve written several blogs on the topics of Python, but I recently realized something important — many beginners struggle before they even start coding. So, I’ve added a new blog focused on Installation and Basics of Python. This post is aimed especially at beginners, students, and career-switchers who often get stuck during installation and setup. If you’re starting your Python journey — this might be helpful. Read here: https://lnkd.in/e3a_Cxat Feedback and suggestions are always welcome! #Python #Programming #DataScience #BeginnerFriendly #LearningPython #CareerGrowth #RinaMondal

I've been messing around with Python lately and put together a very simple port scanner as a learning exercise. Nothing new or original here at all - I'm very aware this has been built a million times before. But rebuilding well-known things from scratch has been a great way for me to actually understand how they work. In short, the script: - Takes a host (IP or domain) and a port range - Tries to open a TCP connection to each port - Marks a port as open if the connection succeeds - Uses a timeout so it doesn't get stuck - Prints a small summary at the end Under the hood it's just: - Python's socket module - A basic loop (no threading, no optimizations) - argparse to make it usable from the CLI This little exercise helped me better understand: - What “open ports” really mean - DNS resolution vs IPs - Why network code needs timeouts - How to structure a small command-line tool As usual, this is purely for learning and meant to be used only on systems you own or have permission to test. Sharing because even if something already exists, rebuilding it yourself can be a really good way to learn. Feedback welcome 🙂 https://lnkd.in/ehNPBhKg #Python #LearningByDoing #NetworkingBasics #SideProjects #LearningInPublic

Python Full Stack Development – Day 4 🚀 📌 Topic: Control Statements / Conditional Statements (with Flowchart) On Day 4 of my Python Full Stack learning journey, I explored how Python programs make decisions using control (conditional) statements. 🔹 What are Control / Conditional Statements? Control statements decide the flow of execution in a program based on conditions (True or False). They help a program choose which block of code should run. 🔹 Types of Conditional Statements in Python ✔ if ✔ if – else ✔ if – elif – else ✔ Nested if 🔹 Working Concept (Flowchart Explanation) Program starts A condition is checked If the condition is True, a specific block executes If False, another block (or next condition) executes Program ends

Why does Python sometimes need an __init__.py file (even when it’s empty)❔ __init__.py tells Python: “This folder is a package.” Before Python 3.3, imports failed without it. Even today, it’s useful for: 1. Explicit package boundaries 2. Package-level initialization 3. Clean public APIs 4. Better tool & framework compatibility Example: ➡️ Folder structure utils/  ├── __init__.py  └── helpers.py ➡️ helpers.py file def greet():   return "Hello Ansh!" Now, ➡️ from utils.helpers import greet (this works because "utils" is a package) Rule of thumb: If you want clarity, control, and fewer surprises 😊 keep __init__.py. Visit: https://lnkd.in/dknCdk6i Thankyou. #Python #Programming #SoftwareEngineering #Backend #Learning

Why pop(0) can bring a Python service to halt, literally! If we need to manage a queue of tasks, first instinct is likely tasks = []. It works perfectly in testing with 100 items. But it would be disaster for 100000 items. Python lists are dynamic arrays. All items live in a single, contiguous block of memory. 1. append() → fast (O(1)) 2. pop(0) → very slow (O(n)) Why? Removing the first element means every remaining item must be shifted one slot to the left in memory. The solution is using Queues, specifically Double-Ended Queue (deque). Internally, a deque is implemented as a Doubly Linked List. - To remove the first item, Python just updates a pointer. No items are moved. - The cost is always Constant Time (O(1)), regardless of data size. Takeaway - Choose your collection based on the Access Pattern and not habits. 1. Need Random Access? Use a List. 2. Need a Queue? Use a Deque. I’m deep-diving into Python internals and performance. Do follow along and tell your experiences in comments. #Python #PythonInternals #SoftwareEngineering #BackendDevelopment

🧠 Python Feature That Makes Code Faster: functools.lru_cache Sometimes Python isn’t slow… it’s just repeating work 😴 ❌ Without Caching def fib(n): if n <= 1: return n return fib(n-1) + fib(n-2) This recalculates the same values again and again 🐌 ✅ Pythonic Way (Cache the result) from functools import lru_cache @lru_cache def fib(n): if n <= 1: return n return fib(n-1) + fib(n-2) Same code. ⚡ Massive speed boost. 🧒 Simple Explanation Imagine doing homework 📚 If you already solved a question once, why solve it again? Python remembers the answer 🧠✨ 💡 Why This Is Powerful ✔ Faster programs ✔ Less CPU usage ✔ One-line optimization ✔ Used in real systems ⚡ Bonus Tip Limit memory usage: @lru_cache(maxsize=100) Before optimizing your code… check if you’re repeating work. Sometimes performance is just memory 🐍⚡ #Python #PythonTips #AdvancedPython #CleanCode #Programming #SoftwareDevelopment #PerformanceOptimization #Caching #DeveloperLife #LearnPython

A quick guide to some of the most important Python List methods for anyone starting their Python journey or revising the basics: 🔹 append(x) – Adds an element x to the end of the list. Commonly used when collecting or storing data dynamically. 🔹 insert(i, x) – Inserts an element at a specific index without removing existing elements. 🔹 count(x) – Returns how many times an element appears in the list. Useful for analyzing frequency. 🔹 index(x) – Returns the position of the first occurrence of an element in the list. 🔹 copy() – Creates a shallow copy of a list so changes to the new list do not affect the original one. 🔹 reverse() – Reverses the order of elements in the list in place. 🔹 pop() / pop(i) – Removes and returns the last element or the element at a given index. Helpful for stack and queue operations. 🔹 clear() – Removes all elements from the list and makes it empty. Understanding these methods helps improve problem-solving skills and makes code more efficient and readable. Visual examples are a great way to clearly see how each method transforms a list step by step. This guide is useful for students, beginners, and anyone revising Python fundamentals before moving on to advanced topics like data structures and algorithms. #Python #PythonProgramming #ListMethods #BeginnerGuide #CodingBasics #Programming #LearningPython #TechEducation #DeveloperCommunity #DataStructures

Python Class Update 🚀 In my last class, we went deeper into Python fundamentals and this is where things start getting powerful. We covered: 🔹 Loops We learned how to use for loops (when you know how many times you want to repeat something) and while loops (when you want something to keep running until a condition changes). Loops are important because automation is everything in tech. If you’re still repeating tasks manually, you’re not thinking like a programmer yet. Then we moved to: 🔹 Functions This is where students start feeling like real developers. A function allows you to write a block of reusable code that performs a specific task. Instead of rewriting the same logic again and again, you define it once and call it whenever you need it. The highlight of the class; We built a function that checks whether a password is strong or not. The function checked for: 🔹Minimum length 🔹Uppercase letters 🔹Lowercase letters 🔹Numbers 🔹Special characters This simple exercise helped students understand: 🔹 Conditional statements 🔹 Loops 🔹 Logical operators 🔹 And how to structure clean, reusable code This is how confidence is built, by practicing real-world scenarios, not just theory. We’re not just learning Python, We’re learning how to think logically and solve problems. If you're learning Python, master loops and functions early. Everything else builds on them. #Python #TechEducation #WomenInTech #DataAnalytics #Programming

✅ Day 24 of 100 — Working with Files, Directories & Paths 📂 A new skill unlocked today: file handling in Python. In this mini-project, I learned how to: - Read from and write to .txt files - Use .strip(), .replace(), and .readlines() to process content - Automate personalized letter creation The task was to take a list of names from one file and merge each into a starting_letter.txt, replacing [name] with the actual person's name—turning one template into many personalized letters in seconds. It's exciting to move beyond pure programming logic and start automating real-world tasks like mail merging. Each new concept opens another door. 🚪👨💻 #python #100DaysOfCode