Nupur Pathak’s Post

The "Quick Fix" That Wasn't: A Lesson in Humility (and Python) 🤦♂️💻 You might have seen my recent post about the automation and data project I’ve been building. I’m incredibly proud of it, but let’s be real—the road to "fully automated" is rarely a straight line! 📈 Funnily enough, everything passed testing. It even worked perfectly on Day 1 of deployment. 🚀 But then? I decided to give the code a "quick once-over." I spotted a potential minor issue and implemented a "fix." Plot twist: That fix actually broke the system. 😅 The database was fine and I still delivered the report on time, but it was a classic reminder: sometimes we are our own biggest bugs. 🐞 The culprit? Reusing global variable names as local variables. A total rookie mistake! 🤦♂️ The Silver Lining: ✅ Issue identified and resolved. ✅ This morning, the report was exactly where it should be. ✅ Fully automated and packed with the insights leadership needs. In tech, you never stop learning. Whether it’s a massive architecture shift or a simple variable name, there’s always a lesson in the code. 🛠️ Has a "quick fix" ever come back to haunt you? Let's swap horror stories in the comments! 👇 #SoftwareEngineering #DataAutomation #Python #LearningEveryday #TechLife #GrowthMindset #CleanCode

Day 10/60 Continuing Chapter 2: Flow Control Continuing Topic l - Making Decisions 2. Code blocks i⁠f⁠ statements don't decide on skipping or running the entire code. They only make decisions about a code block. We use an indentation of two spaces to highlight code blocks, like indenting this display statement. Indentation refers to the space between the code and the code editor's margin. A code block can be more than a one-liner. All lines with the same indentation belong to the same code block. We can see it here when we use  p⁠r⁠i⁠n⁠t⁠(⁠)⁠ to add one more line at the beginning. 🧩Code if True: print ("Look at me!") print("I'm a code block") 🖥️Output Look at me! I'm a code block If the indentation is incorrect, the computer can't understand your code. This leads to an  I⁠n⁠d⁠e⁠n⁠t⁠a⁠t⁠i⁠o⁠n⁠E⁠r⁠r⁠o⁠r⁠ showing up in the console. Instead of using the boolean  T⁠r⁠u⁠e⁠ , we can save it in a variable like  g⁠r⁠e⁠e⁠t⁠ and use it as the condition. 🧩Code greet = True if greet: print("Hello!") 🖥️Output Hello! Using a variable like  g⁠r⁠e⁠e⁠t⁠ set to  F⁠a⁠l⁠s⁠e⁠ allows us to skip code like the display statement. 🧩Code greet = False if greet: print("Hello!") 🖥️Output is empty 🧠Challenge of the day What is the output of this code? 🧩Code if True: print ("Look at me!") print("I'm a code block") #python #ai #programming #bigtech

Mistakes are part of the process Day 7 – #100DaysOfCode ⏰ Time Spent: 2 hours ⚒️ What I Did: * Yesterday I have learned one way to read scatter plots , today I Practiced that . * Modified my function to make it reusable * Plotted relationships between complaints and aggregated features I observed only these two trends: * log(x) vs y → logarithmic trend [ y = a · log(x) + b ] * log(x) vs log(y) → power law [ y = k · xᵃ ] But then I realized something important… I was plotting a sum on the x-axis, which naturally increases the values which created misleading patterns. So I switched to mean,but the trends disappeared. Which implies no relation but I'll experiment with few other transformations before I conclude that --- 🚪 Links: * Repo: [https://lnkd.in/g7zsMygp) --- 🧠 Learning: Bad feature choice can create fake patterns. 📌 Closing: Should try to work on these things when I am not tired ( Mornings / After a nap ) #DataScience #DataAnalytics #Python #CodingJourney

Day 116 🚀 Today was all about going deeper into my trading bot project using Python — and honestly, it was one of those “messy but meaningful” days. I focused heavily on improving how my bot handles market data. Earlier, my candle-fetching logic was inconsistent and sometimes broke due to API issues. So I reworked the entire flow: • Built a cleaner function to fetch OHLC candle data • Handled API errors like timeouts and incomplete responses • Added retry logic to make the bot more reliable • Structured the data properly for further analysis A big chunk of time went into debugging. At one point, I was getting unexpected errors from the data provider, which forced me to rethink how I validate incoming data before using it. This made me realize — a trading bot is not just about strategy, it's about robust systems. I also started refining the internal structure: • Separating data fetching, processing, and execution logic • Making the code more modular and easier to scale • Preparing the base for plugging in different strategies Key learning today: A bot that fails silently is more dangerous than one that crashes loudly. Logging, validation, and error handling are not optional — they are core features. Next steps: • Implement strategy logic (entry/exit conditions) • Add backtesting to evaluate performance • Start tracking trades and metrics Still early, still learning — but moving forward every day 📈 #BuildInPublic #Python #TradingBot #LearningJourney #Consistency

M𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘄𝗿𝗶𝘁𝗲 𝗣𝘆𝘁𝗵𝗼𝗻. 𝗩𝗲𝗿𝘆 𝗳𝗲𝘄 𝘄𝗿𝗶𝘁𝗲 𝗶𝘁 𝘄𝗲𝗹𝗹. That’s the difference between getting things done… and standing out. You don’t need more tutorials. 𝗬𝗼𝘂 𝗻𝗲𝗲𝗱 𝗯𝗲𝘁𝘁𝗲𝗿 𝗵𝗮𝗯𝗶𝘁𝘀. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝟭𝟬 𝗣𝘆𝘁𝗵𝗼𝗻 𝘁𝗿𝗶𝗰𝗸𝘀 𝘁𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗺𝗮𝗸𝗲 𝗮 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲: 1. 𝗟𝗶𝘀𝘁 𝗖𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝗼𝗻𝘀   Write less. Do more. 2. 𝗦𝘄𝗮𝗽 𝗩𝗮𝗿𝗶𝗮𝗯𝗹𝗲𝘀   No temp variable. Cleaner logic. 3. 𝗲𝗻𝘂𝗺𝗲𝗿𝗮𝘁𝗲()   Stop managing indexes manually. 4. 𝘇𝗶𝗽()   Handle multiple lists effortlessly. 5. 𝘀𝗲𝘁()   Remove duplicates in one line. 6. 𝗱𝗶𝗰𝘁.𝗴𝗲𝘁()   Avoid crashes. Use defaults. 7. 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗼𝗿𝘀   Handle large data without memory issues. 8. 𝗰𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀   Smarter data handling (Counter, defaultdict, deque) 9. 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀   Keep your projects clean. 10. 𝗕𝘂𝗶𝗹𝘁-𝗶𝗻 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀   Let Python do the heavy lifting. 𝗕𝘂𝘁 𝗵𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗴𝗮𝗺𝗲: Readable code > clever code Consistency > shortcuts Projects > theory 𝗞𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁: Python doesn’t reward complexity. 𝗜𝘁 𝗿𝗲𝘄𝗮𝗿𝗱𝘀 𝗰𝗹𝗮𝗿𝗶𝘁𝘆. 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝘄𝗶𝘁𝗵 𝗺𝗲 𝗖𝗼𝗺𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝗜’𝗹𝗹 𝘀𝗵𝗮𝗿𝗲 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝘁𝗶𝗽𝘀 #Python #PythonTips #Programming #Coding #SoftwareDevelopment #Developers #TechCareers

Leveling Up with Functions Focus: Functions, Scope, and Efficiency Day 8(04-04-2026): Today was the day I stopped repeating myself! I dove into Functions, and it’s a total game-changer for writing clean code. Instead of writing the same logic over and over, I can now "wrap" it into a function and call it whenever I need it. It’s all about working smarter, not harder. Key concepts I tackled: Parameters vs. Arguments: Understanding the difference between what a function expects and what I actually give it. The Return Statement: Learning how to get a result back from a function so I can use it elsewhere. Variable Scope: This one was tricky! Understanding why a variable created inside a function "disappears" once the function is done (Global vs. Local). In-built Libraries: Starting to explore the massive world of pre-written tools Python offers. It feels like I’m finally moving from writing "scripts" to building "systems." 🏗️ #PythonFunctions #CleanCode #Day8 #TechSkills #CodingLogic

If you've ever spent hours manually renaming hundreds of files or updating dizzying amounts of spreadsheet cells, you know exactly how draining it can be. That's why I decided to dive deep into the world of Python Automation to unlock the ultimate game-changer in productivity. I recently completed an intensive course that completely transformed how I approach these challenges. It taught me that writing code isn't just about solving basic problems; it's about crafting true digital artistry. 🎨 Here are some of the key skills I’ve added to my toolkit: 📂 Mastering File Handling: Automating local storage and data organization. 🕸️ Advanced Web Scraping: Extracting data efficiently using Beautiful Soup and Selenium. ⚙️ Robust Scripting: Learning the art of parsing, weaving through command lines, and implementing solid error handling. 🔗 API Integration: Seamlessly connecting different software pieces for robust, automated solutions. I’m incredibly excited to apply these time-saving skills to future projects and build systems that work smarter, not harder. What was the first tedious task you ever automated? Let me know in the comments! 👇 #Python #Automation #Coding #WebScraping #Productivity #TechSkills #ContinuousLearning #PythonDeveloper #processautomation #python.

🚀 From Confusion → Clarity: My Approach to “Sort the People” (LeetCode) Today I solved the Sort the People problem, and instead of jumping straight into sorting tricks, I focused on building clarity step by step 👇 🔍 My Thought Process: First, I paired each name with its corresponding height using a list (like a mini mapping). Then, I sorted this list based on height. Since the problem required descending order, I simply reversed the sorted list. Finally, I extracted only the names in the correct order. 💡 Key Learning: Sometimes, the simplest approach is the best one. Instead of overcomplicating with advanced data structures, breaking the problem into smaller transformations made it super manageable. 🧠 What this improved for me: Understanding how to use lambda for sorting Confidence in handling paired data (name + value problems) Thinking in steps rather than jumping to optimization ⚡ Code Strategy in One Line: Pair → Sort → Reverse → Extract Consistency > Speed. One problem at a time. 💪 📈 If you're also grinding DSA, keep going — progress compounds! #DSA #LeetCode #CodingJourney #Python #ProblemSolving #Consistency #TechGrowth #100DaysOfCode #WomenInTech #FutureEngineer

🚀✨ **𝗗𝗮𝘆 𝟯 𝗼𝗳 𝗠𝘆 𝗣𝘆𝘁𝗵𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗝𝗼𝘂𝗿𝗻𝗲𝘆** 🐍💻 Consistency check ✅ — showing up again and learning step by step 💪 ━━━━━━━━━━━━━━━━━━━━━━━ 🔹 **📚 𝗪𝗵𝗮𝘁 𝗜 𝗦𝘁𝘂𝗱𝗶𝗲𝗱 𝗧𝗼𝗱𝗮𝘆 (Loops):** ✔️ **for loop** – iterates over a sequence ✔️ **while loop** – runs while condition is true ✔️ **range()** – generates number sequence ✔️ **break** – exits the loop ✔️ **continue** – skips one iteration ✔️ **pass** – placeholder (does nothing) ━━━━━━━━━━━━━━━━━━━━━━━ 🔹 **💻 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲:** 🔥 Found square of numbers in a list 🔥 Printed table of a number *(using both for & while loop)* 🔥 Solved pattern-based questions 🔥 Practiced loop-based logic problems ━━━━━━━━━━━━━━━━━━━━━━━ 🔹 **🧩 𝗠𝗶𝗻𝗶 𝗣𝗿𝗼𝗷𝗲𝗰𝘁:** ⏳ **Countdown Timer (1-second gap)** 💡 Learned how to use the **time module** to control execution speed and make programs interactive ━━━━━━━━━━━━━━━━━━━━━━━ 🔹 **✨ 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀:** ✔️ Loops help automate repetitive tasks ✔️ Control statements make logic flexible ✔️ Small logic mistakes can change entire output ✔️ Hands-on practice makes concepts clear ━━━━━━━━━━━━━━━━━━━━━━━ 🎯 **𝗠𝘆 𝗚𝗼𝗮𝗹:** Improve my logic building and get more comfortable with loops and problem-solving. 💬 **𝗟𝗲𝘁’𝘀 𝗲𝗻𝗴𝗮𝗴𝗲:** 👉 What’s your favorite loop-based problem? 👉 Any tips to master loops faster? 🔥 **𝗗𝗮𝘆 𝟯 — 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗯𝘆 𝗗𝗼𝗶𝗻𝗴!** #Python #LearningJourney #Day3 #Coding #Programming #Consistency 🚀 Saumya Singh

Hello dudes and dudettes!! 🚀 Day 19/150 — Solved LeetCode 58: Length of Last Word Today’s problem looked super simple at first… but taught me a great lesson about handling edge cases carefully 😄 🧠 What’s the Problem About? You’re given a string that contains words separated by spaces. Your task is to find the length of the last word. Sounds easy, right? Well… not always 👇 💡 The Catch The string might contain: Extra spaces at the beginning Extra spaces at the end Multiple spaces between words So it’s not just about “finding the last word” — it’s about finding the last valid word. 🔥 Example Input: " hello world " At first glance, it looks messy 😵 But the actual last word is: 👉 "world" 👉 Length = 5 🧠 The Thought Process Instead of trying to split everything immediately, I started thinking: Why not scan from the end? Because: The last word is always near the end We can skip spaces quickly Then just count characters until we hit a space ⚙️ Approach That Worked Ignore trailing spaces Start from the end of the string Count characters until a space appears That count is your answer Simple, efficient, and clean. 😎 Why This Problem Is Interesting It’s not about complexity — it’s about precision It shows how small edge cases can break simple logic It encourages thinking in reverse (which is surprisingly powerful) 💡 What I Learned Always consider edge cases like extra spaces Sometimes scanning backward is smarter than forward Even easy problems can sharpen your attention to detail 🎯 Key Takeaway “Simple problems aren’t always trivial — they test how carefully you think.” 🔥 Another step forward — improving not just coding skills, but problem-solving mindset. #LeetCode #Algorithms #ProblemSolving #CodingJourney #100DaysOfCode #Python #LearningInPublic