How to Use range() in Python Loops

💡 Python Tip of the Day 🔑 Using get() to Avoid Key Errors Stop your code from breaking when a key doesn’t exist! ✅ get() gives a safe way to fetch values! #PythonTips #Dictionaries #ErrorHandling #PythonForBeginners

Day 55 – Using finally to Clean Up Some actions should happen no matter what — like closing files or releasing resources. Use finally for that 👇 try: file = open("data.txt", "r") print(file.read()) except FileNotFoundError: print("File not found!") finally: print("Closing file...") file.close() ✅ finally always executes ✅ Essential for clean resource handling 🚨 Forgetting to close files or connections = potential memory leaks! 👉 Ever used finally in your code? #Python #ErrorHandling #BestPractices #100DaysOfCode

💡 Python Tip of the Day ⚡ Loop with break and continue Control Your Loop Flow Use break() to stop the loop, and continue() to skip an iteration. ✅ Skip or stop loops dynamically! #PythonTips #BreakContinue #PythonLoops #CodingSmart

💡 Python Tip of the Day 🧠 Remove Duplicates Using Sets Simplify your list instantly! ✅ Sets automatically remove duplicates — quick & clean! #PythonTips #SetTricks #DataCleaning #LearnPython #ProgrammingTips

⚡ Day 92 of #100DaysOfDSA – Single Number III 🔍 📌 Problem. no 260: Given an array where every element appears twice except for two unique numbers, find both unique elements that appear only once. 🚀 Runtime: 0 ms – Beats ⚡100.00% of Python submissions 💾 Memory: 13.23 MB – Beats 65.94% 💻 Language: Python ✅ Result: Accepted – 35 / 35 test cases passed flawlessly This problem pushed me to dive deeper into bit manipulation and understand how XOR can efficiently isolate unique numbers without using extra space. 🔑 Key Learnings ✔️ XOR helps cancel out repeating elements effectively ✔️ Smart bit-level logic simplifies complex comparisons ✔️ Achieved O(n) time and O(1) space – clean and optimal 🎯 Day 92 — Every bit counts when it comes to optimization! ⚙️🔥 #100DaysOfCode #100DaysOfDSA #LeetCode #PythonProgramming #DataStructures #AlgorithmPractice #CodeNewbie #DailyCoding #ProblemSolving #TechJourney #WomenWhoCode #CodeLife #CodingChallenge #DSAChallenge #DeveloperLife #PythonDeveloper #LearnToCode #CodingCommunity #CodeEveryday #SoftwareEngineering #KathirCollegeOfEngineering #KathirCollege #BTechLife #AIDS #FutureEngineer #CodingMotivation #ProgrammingSkills

🚀 LeetCode Daily — Problem #350: Intersection of Two Arrays II Today I solved another interesting array problem that focuses on finding the intersection between two integer arrays — including duplicates. 💡 Problem Statement: Given two arrays, return an array of their intersection. Each element in the result must appear as many times as it shows in both arrays. 🧠 My Approach: I used the two-pointer technique after sorting both arrays: Sort both nums1 and nums2. Use two pointers i and j to traverse both arrays. Compare elements: If equal → add to result and move both pointers. If smaller → move the smaller pointer. Continue until one array ends. 🧩 Time Complexity: Sorting: O(n log n + m log m) Traversal: O(n + m) ✅ Overall: Efficient and clean solution 🏆 Result: ⏱ Runtime: 3 ms (Beats 40.41%) 💾 Memory: 17.75 MB (Beats 93.43%) Each problem like this strengthens my understanding of two-pointer patterns and efficient array traversal in Python. #LeetCode #Python #DSA #CodingJourney #ProblemSolving #Arrays #TwoPointers #Programming

𝐓𝐡𝐞 𝐭𝐡𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐉𝐮𝐩𝐲𝐭𝐞𝐫 𝐧𝐨𝐭𝐞𝐛𝐨𝐨𝐤𝐬... In the beginning, everything is easy: testing code, visualizing data, implementing ideas immediately. But with every new feature, the complexity grows. At some point, #Jupyter notebooks reach their limits. Our data engineer Bianca Leßmann shares her experiences in the blog and explains when classic #Python scripts are the better choice: https://lnkd.in/gJsBfQyC #DataEngineering #JupyterNotebooks #DataScience #DigitalizationbyMM

Sometimes it's helpful to visualize your network traffic in real-time. So here, Chaitanya helps you build a network traffic dashboard with Python and Streamlit. You'll learn how to capture raw network packets from the NIC, process the data, and create visualizations that update in real time. https://lnkd.in/gCvipPUB

Today I solved LeetCode 3321 - Find X-Sum of All K-Long Subarrays II (Hard) #day14 of #1001DaysOfCode The challenge is to compute the “x-sum” for every subarray of length k. Instead of simply summing values, we first: Count occurrences of each number in the subarray Select the top x most frequent elements (breaking ties by choosing the larger value) Then sum only those selected elements with all their occurrences A direct recalculation for every sliding window would be too slow, so the key idea was to maintain frequency counts incrementally and keep the top-x elements efficiently balanced using two heaps. To solve it, I used: A sliding window to move across the array efficiently A frequency map to track counts Two heaps (in for top-x elements, out for remaining elements) A dynamic rebalancing step to ensure correctness as counts change Detailed explanation + code here: https://lnkd.in/dD4e5WNh #LeetCode #Python #DataStructures #Heaps #Algorithms #CodingChallenge #SoftwareEngineering #CompetitiveProgramming

#LearnPythonWithMe With the guidance of Dev BhushanSir Today, I practiced two key Python concepts — dictionary creation and pair sum logic. Topics Covered: Creating dictionaries dynamically using input() Mapping multiple values using split() and map() Nested loops for finding number pairs that match a target sum Applying logic to check conditions and append pairs to a list This session strengthened my understanding of how loops and data structures, such as lists and dictionaries, can interact dynamically in real-world scenarios. #PythonLearning #ProblemSolving #CodingJourney