Mastering Python Range Function

Some scripts run. Some scale. That difference hit home while reading this 👇 🧠 “Professional code isn’t about cleverness. It’s about predictability.” For a long time, my Python scripts worked… but felt fragile. The shift wasn’t more syntax — it was better libraries and better thinking. 🔧 Tools like: pathlib → clean, cross-platform file handling loguru → real logging beyond print() A mindset of structure first, failures second, scale always Small choices. Big upgrade. From “it runs on my machine” to “this could ship.” 🚀 If you’re automating with Python, boring + predictable beats clever every time. #Python #Automation #SoftwareEngineering #CleanCode #DeveloperGrowth #LearningEveryday

🚀 Day 4/30 | LeetCode Problem: Running Sum of 1D Array (1480) Problem: Given an array nums, return the running sum, where each element at index i is the sum of elements from index 0 to i. Approach: Initialize a variable to store the cumulative sum Traverse the array one by one Add each element to the cumulative sum Store the result in a new list This is a simple single-pass solution. Time Complexity: O(n) Space Complexity: O(n) Python Code: class Solution: def runningSum(self, nums): a = 0 b = [] for i in nums: a = a + i b.append(a) return b Example: Input: [1, 2, 3, 4] Output: [1, 3, 6, 10] Takeaway: Running sum is a basic form of prefix sum, which is very useful in many array problems. 📌 Accepted ✅ | All test cases passed 🔖 Hashtags #LeetCode #30DaysOfLeetCode #Day4 #Python #DSA #Algorithms #ProblemSolving #CodingJourney #SoftwareEngineering #TechCommunity

🚀 Day 55 of #100DaysOfCode — Counting Characters & Pythonic Efficiency Hey everyone! 👋 Today was all about String Manipulation. The task was to write a function that returns the total number of characters in a given string. While it’s a simple concept, it’s a great exercise to visualize how data is traversed in memory. 👨💻 What I practiced today: ✅ String Iteration: Using a for loop to step through a string character by character. ✅ Counter Logic: Manually incrementing a variable to track the sequence length. ✅ Edge Case Handling: Ensuring the function correctly returns 0 for an empty string "". 📌 Today’s Task: ✔ Given a string s. ✔ Traverse the string and count every character. ✔ Return the final count. 🧠 Key Insight: In my solution today, I manually built a counter (O(n) time). However, in Python, the len() function is the most efficient way to do this. Unlike a manual loop, len() is O(1) (constant time) because Python stores the length of the string as an attribute in memory! ✨ Key Takeaway: Learning the manual logic behind basic tasks is essential for mastering algorithms, but knowing when to use built-in functions like len() is what makes your code professional and performant. #100DaysOfCode #Day55 #Python #CodingJourney #DSA #Strings #CleanCode #LogicBuilding #SoftwareEngineering #Programming

#Day02 of 50 Days of Learning hashtag#Python through hashtag#Automation On Day 02, I moved from basics to a real-world automation task 📸 Today, I learned how to automatically resize multiple images using Python and the Pillow (PIL) library. What I covered: • What Pillow (PIL) is and why it’s needed • How to install external libraries using pip • Looping through folders to process files automatically • Resizing images while maintaining aspect ratio • Using Python for bulk image automation This script can resize hundreds of images in seconds — useful for: ✔ Websites ✔ Applications ✔ Automation workflows Read the full blog here 👇 https://lnkd.in/gSFXiAjW

Headline: Stop writing loops to clean your data. 🛑 One of the most common tasks in Python is handling duplicate entries. While you could write a for-loop with a conditional check, there’s a much faster, more "Pythonic" way to do it: Sets. Sets are unordered collections of unique elements. By casting your list to a set, Python handles the heavy lifting of deduplication instantly. Why use this? ✅ Cleaner, more readable code. ✅ Better performance for large datasets. ✅ Built-in membership testing (O(1) complexity). How are you using Sets in your current workflow? Let’s discuss below! 👇 #PythonProgramming #Pyspiders #CodingTips #SoftwareDevelopment

Flagging outliers in time series is tricky. You need to decompose the series, calculate the residuals, choose a threshold, and then check if the results make sense. That's a lot of manual steps. And a lot of room for error. TimeCopilot handles it differently. You pass your data to detect_anomalies() and get: • Prediction intervals built with conformal methods • Anomalies flagged based on the confidence level you choose • Visualization with forecasts and anomalies together No separate tools. No manual calculations. 🚀Full tutorial: https://lnkd.in/ePEjshey #TimeSeries #AnomalyDetection #Python #DataScience

Problem: Print Elements of a Linked List Concepts: Linked List Traversal | Pointers | Iteration Difficulty: Easy Problem Summary: Given the head of a singly linked list, traverse the list and print the data of each node line by line. If the head is NULL, nothing should be printed. This problem focuses on understanding how to move through nodes using pointers and access data stored in each node. Key Learnings: A linked list is traversed using a temporary pointer that starts at the head Each node stores both data and a next pointer Traversal continues until the pointer becomes NULL Proper pointer movement is essential to avoid infinite loops GitHub Link:https://lnkd.in/dfxDCKdq #Day40 #DSA #LinkedList #ProblemSolving #DataStructures #Coding #Python #Cplusplus #LearningInPublic #50DaysChallenge #TechJourney 

🌙 Day 28/100 | #100DaysOfCode 🚀 Today was all about File Handling in Python — and it felt really powerful! 🐍📁 Here’s what I learned today: 🔹 File Modes "r" → Read file "w" → Write file (overwrite) "a" → Append data "rb" / "wb" → For binary files like images & PDFs Understanding file modes helped me control how data is read and written in files. 🔹 with Statement I learned how with automatically handles opening and closing files, which makes the code cleaner and safer. No need to manually close files ✅ 🔹 Built a Simple File Copier Using file modes + with statement, I created a program that copies data from one file to another — even works for images and PDFs in binary mode! 😄 Small steps, but learning things that are actually used in real projects 💪 Consistency over perfection — moving forward every day. 👉 Tomorrow: more practice + deeper concepts! #Python #FileHandling #100DaysOfCode #LearningInPublic #PythonBeginner #DeveloperJourney #Consistency #TechSkills #DailyLearning

Today was all about going deeper into Python fundamentals 🐍💡 📌 What I covered today: 🔹 Scope (LEGB Rule) Understood how Python searches for variables and why scope matters for clean and predictable code. 🔹 Closures Learned how inner functions can remember variables from their enclosing scope even after the outer function has finished execution — powerful concept for state management and decorators. 🔹 OOPS – Class & Object Explored why classes are used over only functions: - Classes act as blueprints - Objects are real instances - Better structure, data protection, scalability, and real-world modeling - Also clarified how __init__ works and how each object maintains its own state. 👉 Revisiting fundamentals really changes how you think about writing better, cleaner code. Learning step by step, one concept at a time 🚀 #Python #LearningInPublic #PythonBasics #OOPS #Closures #Scope #Programming #DeveloperJourney

I kept reaching for Great Expectations for very small pandas checks, but it often felt heavier than what I needed. So I built a tiny, code-first alternative focused on fast sanity checks for pandas DataFrames. `pip install mini-expectations` It’s meant for notebooks and small pipelines where YAML/config overhead feels like overkill. Would genuinely love feedback from folks doing pandas-based data validation or lightweight data pipelines. #Python #DataEngineering #DataQuality #OpenSourceSoftware