Advanced Exception Handling in Python

✅ Day 90 of 100 Days LeetCode Challenge Problem: 🔹 #476 – Number Complement 🔗 https://lnkd.in/gzE6gM7d Learning Journey: 🔹 Today’s problem focused on finding the complement of a number by flipping its binary bits. 🔹 I first converted the integer to its binary representation using bin(num)[2:]. 🔹 Then, I created a helper function to flip each bit: • '0' → '1' • '1' → '0' 🔹 After generating the flipped binary string, I converted it back to an integer using int(..., 2). 🔹 Returned the final complemented value. Concepts Used: 🔹 Binary Representation 🔹 Bit Manipulation 🔹 String Traversal 🔹 Base Conversion Key Insight: 🔹 The complement operation is essentially a bitwise NOT, but only within the significant bits of the number (ignoring leading zeros). 🔹 Converting to binary simplifies the flipping logic for beginners. Complexity: 🔹 Time: O(log n) 🔹 Space: O(log n) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #Python #ProblemSolving #LearningInPublic #TechCareers

🚀 Day 6 of My 30-Day Python Journey Today’s focus was on handling collections of data using lists and tuples a key step toward writing more practical and scalable programs. 🔹 What I covered today: • Working with lists to store and manage multiple values • Performing operations like adding, removing, and sorting items • Iterating through lists using loops • Understanding tuples and their immutable nature • Comparing when to use lists vs tuples 💡 Key Takeaway: Choosing the right data structure is crucial. Lists provide flexibility for dynamic data, while tuples ensure stability when data should remain unchanged. 🧪 Practice Focus: Worked on tasks like finding maximum values, summing list elements, removing duplicates, and tuple unpacking. 📌 Next Step: Exploring dictionaries and sets to handle structured and unique data more efficiently. Step by step, building stronger logic and data handling skills. 💻 #Python #CodingJourney #LearnToCode #Developers #Programming #TechGrowth #100DaysOfCode

Just solved “Second Largest Digit in a String” on LeetCode — and here’s the simple approach I followed 👇 Instead of overcomplicating it, I focused on clean thinking + Python basics: 🔹 Converted the string into a set → removes duplicates instantly 🔹 Filtered only digits using isdigit() 🔹 Stored them as integers in a list 🔹 Sorted the list → easy access to largest & second largest 🔹 Edge case check: if less than 2 digits → return -1 💡 Key takeaway: Sometimes the most optimal solution isn’t about complex algorithms — it’s about using the right built-in tools smartly. 🚀 What I’m improving with each problem: • Writing cleaner logic • Thinking in steps instead of rushing • Handling edge cases early Consistency > Complexity. #LeetCode #DSA #Python #ProblemSolving #CodingJourney #100DaysOfCode

LeetCode 1647. Minimum Deletions to Make Character Frequencies Unique: "A string s is called good if there are no two different characters in s that have the same frequency. Given a string s, return the minimum number of characters you need to delete to make s good. The frequency of a character in a string is the number of times it appears in the string. For example, in the string "aab", the frequency of 'a' is 2, while the frequency of 'b' is 1." Approach: Maintain two data structures one hash_table to store the frequencies of characters and other a set that stores the accepted frequency of characters. Iterate through the hash_table and for each value check if it is present or not in set, if not add it to the set, else decrease the value until you get a unique frequency or zero, mean while keep increment a count variable on each delete. #LeetCode #Python #DSA #DataStructures #CompetitiveProgramming #Coding #Algorithms #Strings #HashMap #Sets #InterviewPrep

🚀 Day 65 of My Python & DSA Journey Today’s problem was Word Pattern (290) — a great exercise in understanding mapping and relationships between data. 🔍 Problem Solved: Given a pattern and a string, determine if the string follows the same pattern with a one-to-one mapping (bijection) between characters and words. 💡 Approach Used: • Split the string into words • Use two hashmaps (dictionaries): • One for character → word • One for word → character • Ensure consistency in both mappings while iterating ⚡ Key Learnings: • Concept of bijection (one-to-one mapping) • Using hashmaps for efficient lookups • Handling edge cases like unequal lengths • Writing clean validation logic 📊 Complexity Analysis: ✅ Time Complexity: O(n) We traverse the pattern and words once ✅ Space Complexity: O(n) For storing mappings 🎯 Why This Works? Using two dictionaries ensures no duplicates or conflicts, maintaining a strict one-to-one relationship. Another step closer to mastering problem-solving patterns! Under the Guidance of: Rudra Sravan kumar and Manoj Kumar Reddy Parlapalli #Day65 #Python #LeetCode #DSA #Algorithms #CodingJourney #100DaysOfCode #10000Coders 🚀

Day 6 of my Python learning journey: Focusing on writing code that's not just functional, but also dependable. Highlights from today: - Warmed up by practicing iterators and generators. - Solved the "First Non-Repeating Character" problem using a clean two-pass frequency approach with O(n) complexity. - Merged two sorted arrays efficiently through the two-pointer technique (O(n + m))—avoiding any redundant sorting. - Developed a FastAPI endpoint for the above problem, complete with schema validation. Observations: Initially, I attempted a one-pass solution for the non-repeating character problem, but it ended up feeling convoluted. Switching to a two-pass strategy made the solution much more straightforward and maintainable. Current focus areas: - Maintaining input order integrity. - Performing input validation early on. - Keeping logic as simple as possible. - Thoroughly testing edge cases beforehand. Major takeaway: Define inputs/outputs upfront → validate data early → then prioritize optimization. Starting to grasp how even minor design decisions can significantly impact code quality. GitHub link: https://lnkd.in/gGPw8_js #Python #FastAPI #ProblemSolving #SoftwareEngineering #CleanCode #LearningInPublic #OOP #Testing

🚀 Day 19/60 – Iterators (Understand How Python Loops Work Internally ⚡) Yesterday you learned Decorators. Today, let’s go deeper into how Python actually loops 👇 🧠 What is an Iterator? An iterator is an object that lets you loop through data one item at a time. 👉 Implements __iter__() and __next__() 👉 Used behind every for loop 🔄 How for loop works internally numbers = [1, 2, 3] iterator = iter(numbers) print(next(iterator)) # 1 print(next(iterator)) # 2 print(next(iterator)) # 3 👉 StopIteration is raised at the end ⚡ Custom Iterator class CountUp: def __init__(self, max): self.max = max self.current = 1 def __iter__(self): return self def __next__(self): if self.current > self.max: raise StopIteration val = self.current self.current += 1 return val for num in CountUp(5): print(num) 🔍 Iterator vs Iterable 👉 Iterable → Object you can loop over (list, tuple, string) 👉 Iterator → Object that actually produces values 🔥 Why Iterators Matter? ✅ Memory efficient ✅ Lazy evaluation ✅ Core of generators ❌ Common Mistake Confusing iterable with iterator ❌ 👉 Not every iterable is an iterator 🔥 Pro Tip 👉 Use iter() to convert iterable → iterator 👉 Use next() to manually fetch values 🔥 Challenge for today 👉 Create a custom iterator 👉 That returns numbers from 1 to 3 👉 Use next() manually Comment “DONE” when finished ✅ Follow Adeel Sajjad to stay consistent for 60 days 🚀 #Python #PythonProgramming #LearnPython #Coding #Programming #Developer

2025 was a year of: 🧵 Making Python thread-safe 📦 Revolutionizing packaging ♿ Building accessible tools 🚀 Accelerating sparse computation 🦄 Launching Narwhals ecosystem-wide Our Annual Report tells these community stories. Read it here: https://lnkd.in/dSaTH7wy

👉 Your code doesn’t become smart… until it learns how to make decisions. 💡 That’s where conditional logic comes in. In Python, we use "if", "elif", and "else" to control what should happen next. age = 18 if age >= 18: print("You can vote") else: print("You cannot vote") Simple, right? But this is powerful. Because now your program is not just running… 👉 It’s thinking based on conditions You can add more situations: marks = 75 if marks >= 80: print("Grade A") elif marks >= 60: print("Grade B") else: print("Grade C") 💡 This is how programs: • Make decisions • Handle different situations • React to user input And honestly… We use conditional logic in real life every day: 👉 If it rains → take an umbrella 👉 If you’re tired → take rest 👉 Else → keep working 💡 That’s the real idea: Conditional logic = decision making Are you just writing code… or teaching it how to think? #Python #LearnPython #CodingBasics #ConditionalLogic #ProgrammingConcepts #Ifelse #CodingForBeginners #TechEducation #LearnWithMe

🚀 Just solved the “Valid Number” problem on LeetCode! This problem looks simple at first glance—but handling edge cases like decimals, signs, and exponents makes it a great test of attention to detail and logical thinking. ✅ Key takeaways: Careful handling of edge cases is crucial Validating input step-by-step can simplify complex parsing problems Writing clean, readable logic beats overcomplicated solutions 💡 Performance: ⚡ Runtime: 3 ms 🧠 Efficient space usage ✅ All test cases passed Problems like this remind me that consistency in practice is what builds strong problem-solving skills. On to the next one! 🔥 #LeetCode #Coding #Python #ProblemSolving #SoftwareEngineering #AIEngineerJourney link of #Solution :- https://lnkd.in/ga9b5pVb