Mohshin Mansuri’s Post

This week, I learned something really interesting, Python already comes with SQLite built-in! That means I can create, modify, and manage databases directly from Python without needing to install any extra tools. Using the sqlite3 module, I practiced how to: - Create a database and connect to it from Python - Create, alter, and drop tables through SQL commands - Execute queries and view results right from my script It’s been exciting to see how seamlessly Python bridges programming and data management. Understanding how to handle data at the database level feels like a big step forward in my data analytics journey. Next up: exploring how to integrate SQLite with pandas for real data analysis workflows! #Python #DataAnalytics #SQLite #LearningJourney #DataScience #PythonForData

💼 Learning Update: Python Batteries & Integrations Today I learnt how Python uses batteries (modules) to connect with different systems. Python can interact with Oracle, SQL Server, and MySQL using third-party modules like cx-Oracle, pyodbc, and mysql-connector. I also explored modules used for real projects — CherryPy for web apps, Boto for AWS, PIL/OpenCV for image processing, and Matplotlib + Pandas for data visualization. I revised variables, arrays, and how input is handled in Python using input() and argparse. A very useful session on how Python connects with the outside world. #Python #LearningJourney #TechSkills

💻 Bringing Data and Code Together with Python + SQLite I recently deepened my understanding of databases by integrating SQLite with Python — combining the power of SQL with the flexibility of programming. This hands-on practice helped me:  ✅ Build and manage database tables  ✅ Perform CRUD operations (Create, Read, Update, Delete)  ✅ Understand how data flows between Python and SQL What I love most is how effortlessly Python bridges the gap between data storage and real-world applications. “Databases store data; Python gives it purpose.” #Python #SQLite #SQL #DatabaseManagement #DataEngineering #PythonProjects #TechLearning

Complete Roadmap to learn Python 🚀 1. Basics 🌱 - Learn programming fundamentals and Python syntax. 2. Core Python 🧠 - Master data structures, functions, and OOP. 3. Advanced Python 📈 - Explore modules, file handling, and exceptions. 4. Web Development 🌐 - Use Django or Flask; build REST APIs. 5. Data Science 📊 - Learn NumPy, pandas, and Matplotlib. 6. Projects & Practice💡 - Build projects, contribute to open-source, join communities. [Explore More In The Post] Follow Future Tech Skills for more such information and don’t forget to save this post for later #SQL #SQLServer #DatabaseManagement #TSQL #MySQL #PostgreSQL #SQLProgramming #SQLQueries #SQLLearning #CodingLife #DataScience #DatabaseDevelopment #DatabaseDesign #SQLDeveloper #SQLCode #DatabaseCareer #SQLTraining #ProgrammingSkills #DeveloperHumor #ProgrammerLife #GeekLife #sqlcommunity

✨ Master File Handling in Python! ✨ Most beginners skip this topic… But file handling is the backbone of automation, logging, and data storage in Python. 🐍💾 Once you understand how to open, read, and write files — you unlock real power for data projects and backend scripts. ⚡ 💡 What You’ll Learn: ✅ Open & close files safely using with open() ✅ 4 key modes you must know: r → Read w → Write (overwrites) a → Append (adds content) x → Exclusive creation (error if file exists) ✅ Read data line-by-line or all-at-once ✅ Write & append cleanly ✅ Handle errors like a pro with try-except 🧠 Pro Tip: Always use the with statement — it auto-closes files even if an error occurs. That’s clean, efficient, and Pythonic. ✅ 🚀 Why It Matters: Once you master this, you can build: Automated report generators 📊 Log and audit systems 🧾 Data extraction pipelines ⚙️ Configuration file handlers ⚡ It’s a small concept… but it makes you think like a real developer. 👨💻 💬 Save this post for your next Python practice! #Python #PythonProgramming #LearnPython #PythonForBeginners #FileHandling #PythonProjects #PythonTips #CodeWithPython #PythonSkills #AutomationWithPython #CodingCommunity #TechLearning

𝐍𝐞𝐯𝐞𝐫 𝐬𝐚𝐯𝐞 𝐭𝐨 𝐲𝐨𝐮𝐫 𝐃𝐁 𝐢𝐧𝐬𝐢𝐝𝐞 𝐚 𝐟𝐨𝐫 𝐥𝐨𝐨𝐩 😬 I’ve been working on improving my Python project’s performance, and here’s what I learned. Before, I was saving data to the database 𝐨𝐧𝐞 𝐢𝐭𝐞𝐦 𝐚𝐭 𝐚 𝐭𝐢𝐦𝐞 𝐢𝐧𝐬𝐢𝐝𝐞 𝐚 𝐥𝐨𝐨𝐩. Just saving 300 items took around 𝟑𝟎𝟎 𝐬𝐞𝐜𝐨𝐧𝐝𝐬 — roughly 1 second per item. Way too slow! 😬 So I decided to fix it. The solution? 👉 𝐁𝐮𝐥𝐤 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬. Instead of “talking” to the database 300 separate times, I changed the code to 𝐬𝐚𝐯𝐞 𝐚𝐥𝐥 𝟑𝟎𝟎 𝐢𝐭𝐞𝐦𝐬 𝐢𝐧 𝐨𝐧𝐞 𝐠𝐨. And guess what? The same 300 items now get saved in just 𝟏–𝟐 𝐬𝐞𝐜𝐨𝐧𝐝𝐬.⚡ This little change taught me a few big lessons: 1) The 𝐍+𝟏 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 (doing DB operations in loops) is a real performance killer. 2) Letting the 𝐝𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐝𝐨 𝐭𝐡𝐞 𝐡𝐞𝐚𝐯𝐲 𝐥𝐢𝐟𝐭𝐢𝐧𝐠 (via bulk writes, aggregations, etc.) can make a huge difference. 3) Sometimes, a single small refactor can make your app feel 100x faster. Have you ever had a “wow” moment like this with database performance? Would love to hear your stories or tips below! 👇 #Python #Database #PerformanceOptimization #MongoDB #SoftwareDevelopment #TechTips #BulkOperations #CodeRefactoring"

Was going through some SQL practice today and stumbled on one of those tiny things that can trip you up for no reason 😅 I kept thinking the "not equal"operator in SQL works the same as Python, but nope. In SQL, it's actually: <> (the classic one) != (also works in many SQL databases) Meanwhile in Python we only use !=. Such a small difference, but it's so easy to mix up when you switch between languages. Caught myself doing it and had to laugh, the debugging wasn't fun though 😅 Anyway, just sharing in case someone else has the same habit. Little things like this really make you appreciate the basics. #DataAnalysis #DataAnalytics #SQL #Python #AnalyticsJourney #DataLearning #DataSkills #AnalystLife #BusinessIntelligence #DataCommunity #LearnSQL #DataCleaning #TechLearning #DataBeginners #UpskillJourney #ProgrammingTips

🚀 🐍 Day 20 — Advanced Python Modules, Packages & File Handling Today’s deep dive took my Python journey to a whole new level 💻✨ Understanding how large-scale Python projects are structured and managed makes all the difference between just writing code and writing scalable, production-ready software! Here’s what I explored today 👇 🔹 Modules — Reusable building blocks of Python projects. 🔹 Packages — Organizing modules with __init__.py for clean, scalable architecture. 🔹 File Handling — Managing large files efficiently using streaming and binary modes. 🔹 JSON & CSV Handling — Working with structured data formats for automation & data analysis. 🔹 Pickle — Serializing Python objects for quick storage and retrieval. 🔹 Best Practices — - ✅ Keep modules single-purpose ✅ Use with open() for safe file handling ✅ Store configs in JSON or .env files ✅ Leverage relative imports for cleaner packages Each concept taught me how modularity, structure, and safety make a huge impact in real-world applications. - 💡 Next goal: Implement these concepts in my upcoming Python automation project to build faster and cleaner scripts. - - #Python #AdvancedPython #PythonModules #PythonPackages #PythonFileHandling #PythonJSON #PythonCSV #PythonPickle #PythonBestPractices #PythonProgramming #PythonDeveloper #PythonLearning #PythonProjects #CodeWithPython #LearnPython #Day20PythonSeries #PythonAutomation - SAI PRASANNA SIRISHA KALISETTI Vamsi Enduri 10000 Coders -

💻 Exploring the Basics of DataFrame in Python (Pandas) I recently learned and practiced the fundamentals of DataFrames — one of the most powerful tools in Python for data analysis. This exercise helped me understand how to: 🔹 Create and manipulate DataFrames 🔹 Access, modify, and clean data 🔹 Perform basic operations and analysis efficiently It was a great step toward building a strong foundation in data handling and preprocessing using Pandas! Guided by : Ashish Sawant sir GitHub: https://lnkd.in/eu875cP5 LinkedIn: https://lnkd.in/epsdwKQu Google drive: https://lnkd.in/es63Cp9p #Python #Pandas #DataFrame #DataScience #DataAnalysis #LearningJourney

PyMSSQL Just Updated to Support Python 3.14 For those that might have been holding out on upgrading to Python 3.14 due to SQL Server integration support, the PyMSSQL package has been updated to support the latest Python version. Find details below. https://lnkd.in/eYpM-Gs3 https://lnkd.in/etKEgHB3 #pymssql #python #python314 #sqlserver