Flask Debugging: Fixing Form Handling & Route Logic Issues

 Debugging is just high-stakes problem solving. They say code is 10% writing and 90% debugging. But the best debugging doesn't just fix a "bug"—it uncovers a better way to think about the problem. 💡 When I started this LeetCode challenge, I looked for the most obvious path. But after a few rounds of testing and refinement, I realized that the "cleanest" code is the one where bugs have nowhere to hide. By moving from complex loops to Bit Manipulation, I reduced the surface area for errors and achieved a perfect 0ms runtime. 🚀 Debugging isn't a chore; it's the process of distilling logic until only the truth (and a 100% beat rate) remains. #Debugging #SoftwareEngineering #ProblemSolving #Python #LeetCode #CleanCode #DeveloperJourney #snsinstitutions #snsdesignthinkers #snsdesignthinking

Day 24 Learning | Python Polymorphism & OOP Concepts 🚀 Today, I explored the concept of Polymorphism in Python, another fundamental pillar of Object-Oriented Programming. I focused on how polymorphism allows the same interface or method name to behave differently based on the object or context. I studied and practiced key forms of polymorphism, including: Method Overriding Method Overloading (using default arguments) Operator Overloading Through hands-on coding examples, I understood how different classes can implement the same method name with different behaviour, enabling flexible and scalable program design. This learning strengthened my understanding of dynamic behaviour in OOP, abstraction, and designing adaptable software components in Python. 🔗 GitHub Repository: https://lnkd.in/g3CrHbUt Consistent learning and implementation are key steps toward becoming a better developer. #Python #PythonLearning #OOP #Polymorphism #HandsOnLearning #CodingPractice #ProgrammingJourney #LearningByDoing #Consistency

🚀 Coding Practice — Prime Number of Set Bits (Bit Manipulation) Today I solved an interesting bit manipulation problem: 👉 Given two integers left and right, count how many numbers in the range [left, right] have a prime number of set bits in their binary representation. 🧠 Problem Understanding A set bit means a 1 in binary representation. Example: 21 → 10101 → 3 set bits We must: Convert each number in range [left, right] to binary Count number of 1s Check if that count is prime Return total count 🔍 Key Insight (Optimization Trick) Given constraint: 1 ≤ left ≤ right ≤ 10^6 0 ≤ right - left ≤ 10^4 Maximum number of bits required for 10^6: log₂(10^6) ≈ 20 So maximum possible set bits = 20 That means we only need to check primes up to 20: {2, 3, 5, 7, 11, 13, 17, 19} ⚡ Instead of checking prime every time, we store these in a set for O(1) lookup. ✅ Optimized Python Solution class Solution: def countPrimeSetBits(self, left: int, right: int) -> int: # Prime numbers up to 20 (maximum possible set bits) primes = {2, 3, 5, 7, 11, 13, 17, 19} count = 0 for num in range(left, right + 1): set_bits = num.bit_count() # Fast built-in method if set_bits in primes: count += 1 return count 🔎 Example 1 Input: left = 6, right = 10 NumberBinarySet BitsPrime?61102✅71113✅810001❌910012✅1010102✅ ✔ Output = 4 ⏱ Complexity Analysis Time Complexity: O(N) where N = right - left (max 10^4) Space Complexity: O(1) Very efficient and well within constraints. #Python #CodingPractice #BitManipulation #ProblemSolving #DataStructures #InterviewPreparation #LeetCode

𝑴𝒚 𝒊𝒏𝒔𝒊𝒈𝒉𝒕𝒔 𝒘𝒉𝒊𝒍𝒆 𝒄𝒐𝒎𝒑𝒂𝒓𝒊𝒏𝒈 '𝑴𝒚 𝒄𝒐𝒅𝒆' 𝒕𝒐 𝒕𝒉𝒆 '𝑺𝒐𝒍𝒖𝒕𝒊𝒐𝒏 𝑪𝒐𝒅𝒆' 🙄 To be honest, I've only recently started using functions and using comments in my code... since I didn't know that they were so handy 😅 But when I look at the solution, it feels like: "Wow! You just have to look once to get what's happening in there 😮" And hence, I started using 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 and 𝐂𝐨𝐦𝐦𝐞𝐧𝐭𝐬 in my code which made it look less messy and more understandable 😁 I guess, just 'making the code work and give the desired solution' is not the only step, but making it more READABLE and UNDERSTANDABLE is what makes the code more awesome 😆 (It helps to solve bugs easily too 👍) Suggestions and Insights are appreciated 🙌✨ #Python #Programming #CSE #StudentDeveloper #LearningWhileCoding

🛠️ Debugging 101: How Variable Scope Mistakes Can Break Your Program (And How to Fix Them) Ever run into an "UnboundLocalError" in Python and wondered why? Let's break it down simply: 🔍 Why this happens: When you create a variable inside a function, Python treats it as "local" to that function — "even if" there's a global variable with the same name outside. Example: x = 10 # global variable def my_func(): x = x + 5 # ❌ UnboundLocalError! print(x) Here, 'x' inside 'my_func()' is considered local, so when we try to use 'x' on the right side of '=', Python says: "𝙒𝙖𝙞𝙩, 𝙩𝙝𝙞𝙨 𝙡𝙤𝙘𝙖𝙡 'x' 𝙝𝙖𝙨𝙣'𝙩 𝙗𝙚𝙚𝙣 𝙙𝙚𝙛𝙞𝙣𝙚𝙙 𝙮𝙚𝙩! " ✅ How to fix it: 1. Use the 'global' keyword to tell Python you’re referring to the global variable: x = 10 def my_func(): global x x = x + 5 # ✅ Now it works! print(x) 2. Avoid reusing variable names across scopes to prevent confusion. 🔧 Pro tip: Always pause and ask: "Is this variable 'local' or global?" before writing or modifying it inside a function. Understanding scope is more than just syntax — it’s about writing clean, predictable, and bug-free code. 🧠💻 Have you faced scope-related bugs before? How did you solve them? 👇 #Python #Debugging #Programming #Coding #DeveloperTips #LearnToCode #SoftwareEngineering #Tech #BeginnerFriendly #PythonTips #Day29

Exploring Desktop Automation using PyAutoGUI in Python I recently built a simple automation script using pyautogui that simulates real keyboard typing on my system. The program waits for a few seconds so I can switch to Notepad, and then it automatically types my introduction and presses Enter — just like a human would. It’s a small script, but it clearly shows how powerful automation can be. Instead of manually typing repetitive text, Python can handle it in seconds. Through this hands-on experiment, I learned: • How pyautogui controls keyboard actions • How execution delays help manage task timing • How automation scripts mimic real user behavior • The foundation behind bots and GUI testing tools This concept can be extended to automate form filling, repetitive data entry, testing applications, and other productivity tasks. Sometimes the simplest projects teach the most practical lessons. Excited to keep exploring automation and real-world scripting with Python #Python #PyAutoGUI #Automation #LearningByDoing

Day 47/100 – #100DaysOfLeetCode 🚀 🧩 Problem: LeetCode 191 - Number of 1 Bits (Easy) 🧠 Approach 1: Using Brian Kernighan’s Algorithm. 💻 Solution: class Solution:   def hammingWeight(self, n: int) -> int:     count = 0     while n:       n &= (n - 1)        count += 1     return count ⏱ Time | Space: O(k) | O(1) 📌 Key Takeaway: Using n & (n - 1) efficiently removes one set bit at a time, making it faster than checking every bit individually. 🧠 Approach 2: Python’s built-in binary conversion makes counting set bits simple 💻 Solution: class Solution:   def hammingWeight(self, n: int) -> int:     return bin(n).count('1') #leetcode #dsa #development #problemSolving #CodingChallenge

🧠 Python Feature That Makes Error Handling Elegant: contextlib.suppress 💫 No noisy try/except. 💫 No empty except: pass. 💫 Just clean intent ❌ Old Way try: os.remove("temp.txt") except FileNotFoundError: pass Works… but feels messy 😬 ✅ Pythonic Way from contextlib import suppress with suppress(FileNotFoundError): os.remove("temp.txt") Readable. Explicit. Clean. 🧒 Simple Explanation Imagine wearing noise-canceling headphones 🎧 You choose which noise to ignore. Python ignores only that error — nothing else. 💡 Why This Is Powerful ✔ Cleaner error handling ✔ Avoids swallowing real bugs ✔ Very expressive code ✔ Used in production-grade code ⚠️ Important Rule Only suppress errors you truly expect (never hide bugs blindly ❌) 💻 Clean code isn’t about removing errors. 💻 It’s about handling them intentionally 🐍✨ 💻 contextlib.suppress is Python being elegant again. #Python #PythonTips #PythonTricks #AdvancedPython #CleanCode #LearnPython #Programming #DeveloperLife #DailyCoding #100DaysOfCode

🏎️ Day 12 of The Product-Engineer-Max Challenge After mastering the Bun runtime, I’ve now shifted gears into Python, alongside Rus, focusing on fundamentals, clarity, and how languages actually teach you to think. This phase is less about frameworks and more about first principles: how code runs, how bugs happen, and how developers debug in the real world. Repo: https://lnkd.in/eiUTGx8V Reflections & Learnings: - Started Python from absolute scratch, assuming zero prior knowledge - Revisited Hello World as a runtime + tooling check, not just a ritual - Learned how Python executes via the terminal and why print() is your window into execution - Understood what a bug really is: code that runs but behaves incorrectly - Practiced debugging by reading output before touching code - Differentiated logic bugs vs syntax errors - Learned how Python reports syntax errors clearly and why that matters - Understood what the console/terminal actually is: a text-only conversation with the machine - Clarified backend vs frontend thinking early - Revisited source code vs machine code fundamentals - Reinforced that code executes top-to-bottom, instruction by instruction - Compared syntax across languages (Python vs Go vs Fortran) - Realized Python isn’t just easy — it’s deliberately readable and expressive Overall takeaway: After systems-level tooling with Bun, Python feels like learning to explain ideas clearly to a computer. Pairing it with Rust keeps me grounded between simplicity and correctness. One tool teaches speed. Another teaches discipline. Together, they teach engineering. Coding_is_meditation #ProductEngineer #Python #Rust #BackendEngineering #ComputerScience #LearnBuildShip #SoftwareEngineering #ProgrammingFundamentals

“𝗔 𝗴𝗼𝗼𝗱 𝗔𝗣𝗜 𝗺𝗲𝗮𝗻𝘀 𝗻𝗼𝘁𝗵𝗶𝗻𝗴 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗴𝗼𝗼𝗱 𝗲𝘅𝗮𝗺𝗽𝗹𝗲𝘀.” When we asked Jonathan Mercier-Ganady why PyO3 stood out to him, this was the real takeaway 👇 It wasn’t just about performance. Or even Rust ↔ Python interoperability. 𝗜𝘁 𝘄𝗮𝘀 𝗮𝗯𝗼𝘂𝘁 𝗱𝗲𝘀𝗶𝗴𝗻 𝗮𝗻𝗱 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗱𝗼𝗻𝗲 𝗿𝗶𝗴𝗵𝘁. He’d worked on a project where most of the core logic lived in Rust, but some pieces still needed to run in Python. PyO3 was the bridge, and unlike many “glue” tools between languages, it didn’t fight back. What made the difference? 👉 A clean, well-thought-out API 👉 Clear documentation 👉 And crucially: real examples that make learning fast Because even the best-designed API slows you down if you’re left guessing how to use it in practice. Mixing languages is rarely trivial, especially when you’re dealing with Python’s garbage collection alongside Rust’s ownership model. Tools like PyO3 matter because they smooth over those sharp edges and let engineers focus on shipping, not wrestling abstractions. It’s a good reminder that developer experience isn’t a “nice to have”. It’s the difference between: 👉 “This looks powerful” and 👉 “I can actually use this tomorrow.” You can watch the full interview here: https://lnkd.in/e4ab5Sgx If you’ve worked across languages, what’s the best integration tooling you’ve used? #RustLang #Python #PyO3 #OpenSource #DevExperience #EngineeringCulture