Checking for Consecutive Duplicates in a Python List

Ever tried to sort a list and ended up with None? The logic looks correct: nums = [3, 1, 2] sorted_nums = nums.sort() print(sorted_nums) 👉 Output: None Why did it fail? In Python, there is a big difference between a Method that modifies an object and a Function that returns a new one. 1️⃣ .sort() is a Method: It modifies the original list "in-place." It doesn't need to return anything because the work is done directly on the original variable. 2️⃣ sorted() is a Function: It creates a brand-new list and leaves the original one exactly as it was. Use .sort() when you want to save memory and don't need the original order anymore. Use sorted() when you need to keep your original data safe and want a new sorted version. #Python #30DaysOfCode #BCA #LearningInPublic #Day22 #JECRC

Writing clean, predictable code is just as important as the analysis itself. In Python, understanding memory references is the "hidden" skill that separates scripts that work from scripts that scale. I see many developers struggle with unexpected mutations when handling nested data structures. A simple new_list = old_list doesn't just copy the data; it copies the problem. I just published a deep dive into "Why Your Python List Copies Keep Betraying You." It’s a guide to mastering the copy module so you can stop debugging "impossible" errors and start building more resilient data pipelines. #PythonProgramming #DataAnalytics #TechWriting #CleanCode #MachineLearnin

Python Clarity Series – Episode 23 Topic: Floating Point Precision Issue 🤯 Why does this happen? print(0.1 + 0.2) Output: 0.30000000000000004 ❗ 👉 This is NOT a Python bug. It’s due to how floating-point numbers are stored in binary. 💡 Fix (when needed): round(0.1 + 0.2, 1) Output: 0.3 💡 Concept: Computers approximate decimal values internally. Important in: ✔ Financial calculations ✔ Data Science Don’t ignore this. #PythonConcepts #FloatingPoint #RealWorldCoding #python #clarity

You subclass a data processor, override one method, tests pass… then you swap it in and something upstream breaks ⚠️ That’s usually not “bad luck,” it’s a Liskov Substitution Principle violation 🧠 The subclass technically works, but it quietly changed the contract: stricter preconditions, different return guarantees, or new exceptions the parent never had 💥 If callers need to check which subclass they’re dealing with, the abstraction already failed. I broke this down with concrete Python examples 🐍 and when inheritance is just the wrong tool entirely 👉 https://lnkd.in/ewG9ugCc What’s the sneakiest contract violation you’ve shipped without noticing? 💬 #Python #SoftwareEngineering #SOLID #CleanCode #DataScience

🚀 Day 6/30 of My LeetCode Journey (Python + SQL) Consistency is slowly turning into confidence 💪📈 🔹 **Python Problem of the Day** 👉 *Plus One* Given an integer represented as an array of digits, increment the number by one and return the resulting array. 💡 *Key Concept:* Handling carry from the last digit (especially edge cases like 9 → 10). 🔹 **SQL Problem of the Day** 👉 *Game Play Analysis I* Given a table of player activity, write a query to find the first login date for each player. 💡 *Key Concept:* GROUP BY with MIN() to extract earliest dates. Every day learning something new, refining logic, and improving speed ⚡ Day 6 done ✅ #LeetCode #30DaysChallenge #Python #SQL #CodingJourney #Consistency #ProblemSolving #Learning

Most implementations of the State pattern in Python look very “clean”. Lots of small classes. A base interface. One class per state. But if you’ve ever worked with one in a real project, you know the downside: transitions are scattered, behaviour is hard to see in one place, and adding new states often means touching multiple files. In today’s video, I rebuild the State pattern in a very different way. Instead of relying on inheritance, I make the state machine explicit as data and use decorators to define transitions. The result is a small, reusable engine where the entire flow becomes visible at a glance. If you’re interested in writing Python that’s easier to reason about and extend, this is a pattern worth understanding. 👉 Watch here: https://lnkd.in/e9Y3xGNF. #python #softwaredesign #designpatterns #statemachine #cleancode

Learn how to build a predictive model with Python and Scikit-Learn, including data preparation, model selection, and evaluation techniques, with expert tips and real-world examples https://lnkd.in/ge-CSTzq #PredictiveModelWithPython Read the full article https://lnkd.in/ge-CSTzq

Learn how to build a predictive model with Python and Scikit-Learn, including data preparation, model selection, and evaluation techniques, with expert tips and real-world examples https://lnkd.in/ge-CSTzq #PredictiveModelWithPython Read the full article https://lnkd.in/ge-CSTzq

Learn how to build a predictive model with Python and Scikit-Learn, including data preparation, model selection, and evaluation techniques, with expert tips and real-world examples https://lnkd.in/ge-CSTzq #PredictiveModelWithPython Read the full article https://lnkd.in/ge-CSTzq

🚀 Day 12/30 of My LeetCode Journey (Python + SQL) Consistency continues… and the concepts are getting sharper! 💻🔥 🔹 **SQL Problem of the Day** 👉 *Invalid Tweets* Given a `Tweets` table, write a query to find tweet IDs where the content length is strictly greater than 15 characters. 💡 *Key Concept:* String functions like `LENGTH()` for validation. 🔹 **Python Problem of the Day** 👉 *Single Number* Given an array where every element appears twice except one, find that single element. 💡 *Key Concept:* Bit manipulation using XOR for optimal O(n) time and O(1) space. Loving how problem-solving is becoming more intuitive day by day ⚡ Day 12 done ✅ #LeetCode #30DaysChallenge #Python #SQL #CodingJourney #Consistency #ProblemSolving #Learning #BitManipulation