APIs & Data Collection in Python 🐍 In today’s data-driven world, the ability to collect and work with data from external sources is an essential skill for developers. One of the most common ways to access external data is through APIs (Application Programming Interfaces). APIs allow applications to communicate with other services and retrieve structured data such as weather information, financial data, user details, and much more. With Python, developers can easily connect to APIs, send requests, and process the returned data. Libraries like requests make it simple to interact with web services and retrieve information in formats such as JSON. This capability makes Python incredibly powerful for tasks like: • Data collection and automation • Building data-driven applications • Integrating third-party services • Creating dashboards and analytics tools Created by Guido van Rossum, Python continues to be a popular choice for developers because of its simplicity and its strong ecosystem for working with data. Understanding how to collect and work with data through APIs opens the door to building smarter and more connected applications. 💬 What APIs have you worked with in your Python projects? #Python #APIs #DataCollection #Programming #SoftwareDevelopment #Tech

🚀 Personal Expense Tracker | Python Project Managing daily expenses becomes simple and smart with my Personal Expense Tracker project. This application helps users record, categorize, and analyze their expenses efficiently, making budgeting easier and more organized. 🔹 Key Features: Add and track daily expenses Categorize spending (Food, Travel, Shopping, etc.) View total expenses clearly Simple and user-friendly logic Helps in better financial planning 🔹 Tech Stack Used: Python Basic concepts of lists, functions, and conditionals 📌 This project strengthened my understanding of Python fundamentals and logical problem-solving while working on a real-life use case. 💡 Looking forward to improving it further by adding file handling, data visualization, and GUI features. #Python #MiniProject #ExpenseTracker #LearningByDoing #BTech #Programming #pythonproject

📈 Python Automation Project – Stock Price Alert System I recently built a small Python automation tool that monitors stock prices and sends an email notification when a stock reaches a target price. Instead of manually checking stock prices throughout the day, I wanted a script that could track them and alert me automatically. This project helped me practice combining several concepts into one working tool: 🔹 Retrieving live stock data using the Yahoo Finance API 🔹 Automating email alerts using SMTP 🔹 Automating the script using Windows Task Scheduler Building projects like this has been a great way to strengthen my Python skills and better understand how automation can solve everyday problems. As I continue transitioning into tech, I'm focused on building projects around Python, data analysis, and automation. You can check out the project here: 🔗 https://lnkd.in/gyZS9AnA For those working with Python or automation tools — what projects helped you the most when you were learning? #Python #Automation #APIs #DataAnalytics #TechProjects #LearningInPublic #CareerTransition

🚀 Python Project: Expense Tracker I’m happy to share my Python project “Expense Tracker”, which I created to track expenses for my friend’s birthday celebration. This program helps manage spending and compare it with the monthly pocket money budget. 🔹 Project Features: • Add expenses with date, category, and amount • View all recorded expenses • Calculate total expenses and percentage of monthly budget used • Display total expenses by category • Search expenses by date • High expense alert when a single expense exceeds 50% of the monthly budget This project helped me practice important Python concepts I’m continuously learning and improving my programming skills by building practical projects. GitHub URL-https://lnkd.in/g2Hbz_Kt #Python #PythonProject #ExpenseTracker #Programming

Committed to upskilling to allow myself to compete in global job markets. I recently built small Python scripts to automate repetitive tasks like organizing folders, renaming files, backing up documents, and cleaning messy Downloads directories. Naturally, I also used Python to automate parts of creating this portfolio. One thing I’ve learned so far is that every new concept feels confusing at first, sometimes completely impossible… but with enough persistence, things eventually start making sense. Current scripts can: • organize files by type • detect duplicate filenames • rename files automatically • delete large files • create backup copies Small steps, but each project makes the next concept a little easier to understand. GitHub: https://lnkd.in/dykD_GH9 Also want to thank Keron Rose for consistently sharing insights about building skills that can compete in global job markets — your content has been a strong motivator as I continue learning.

🚀 Built a Series Completion System in Python I recently worked on a Python-based solution that can intelligently identify patterns in a number series and find the missing value. Instead of hardcoding logic, I focused on building a structured approach using core programming concepts. 🔍 What this system does: • Takes a series input (with a missing value represented by “?”) • Cleans and processes data using lambda functions • Stores and reads data using file handling • Identifies patterns using difference logic • Calculates and predicts the missing number 🧠 Concepts used: • Functions • While loops • Conditional statements • File handling (read/write) • Lambda functions • Exception handling 💡 Example: Input: 1, 6, 15, ?, 45 Output: 28 This project helped me understand how fundamental programming concepts can be combined to solve logical problems efficiently. 📌 Key Learning: Strong basics in programming can be applied to build intelligent systems, even without complex libraries. Looking forward to enhancing this further by: • Supporting multiple pattern types (multiplication, alternating patterns) • Adding a GUI interface • Exploring AI-based pattern detection Would love your feedback and suggestions! 🚀 #Python #Programming #DSA #Coding #SoftwareDevelopment #ProblemSolving #LearningInPublic #TechJourney

#UnderstandingEncapsulationObjectOrientedProgramming (Python) #Encapsulation is one of the core principles of OOP. It focuses on protecting data and controlling how it is accessed or modified within a class. In simple terms, encapsulation means: ➡️ Keeping data (attributes) private inside a class ➡️ Allowing access through controlled methods like getters and setters For example, in a BankAccount class: The balance can be stored as a private variable (__balance) A getter method allows safe access to read the balance A setter method ensures the balance is updated only after validation This approach helps to: ✔️ Protect sensitive data ✔️ Prevent invalid updates ✔️ Maintain clean and reliable code Encapsulation ensures that the internal state of an object cannot be changed arbitrarily, but only through defined methods that enforce rules. In Python, this can be implemented using: Private attributes (__variable) Getter and setter methods @property and @setter decorators for cleaner access 📌 Key takeaway: Encapsulation is not just about hiding data — it's about maintaining control and ensuring data integrity inside your class design. #Python #OOP #Encapsulation #Programming #SoftwareDevelopment #Coding

🐍 Python Basics – Quick Learning Notes Python is one of the most popular programming languages today, known for its simplicity and versatility. Here are some key fundamentals: 🔹 Interpreted Language Python executes code line by line using an interpreter, making debugging easier and faster. 🔹 Dynamically Typed No need to declare data types explicitly – Python handles it automatically. 🔹 Scripting Language Widely used for automation, data processing, and rapid development. 🔹 Case Sensitive Variables like data and Data are treated differently. 🔹 Memory Management (Private Heap) Python manages memory internally using a private heap, ensuring efficient storage of objects. 🔹 Simple & Readable Syntax Easy to learn and write, making it beginner-friendly. 🔹 Supports Structured Programming Although flexible by default, Python supports structured programming through functions, classes, and OOPS concepts. 💡 Python is not just a language, it's a powerful tool to solve real-world problems efficiently. #Python #Programming #Coding #SoftwareDevelopment #DataScience #Learning #Beginners #Tech

🚀 Day 2 of My Python Full Stack Development Journey Continuing my learning at Global Quest Technologies, Yelahanka. Today’s session focused on understanding how programming languages work and getting introduced to Python. 📌 Concepts Covered Today 🔹 What is an Interpreter? An interpreter is a program that executes code line by line and converts it into machine-understandable instructions. Example: Python uses an interpreter, which allows developers to run code directly without compiling it first. 🔹 How an Interpreter Works Reads the source code written by the programmer Translates each line into machine-level instructions Executes the instructions immediately 🔹 Introduction to Python Python is a high-level, interpreted programming language known for its simplicity and readability. It is widely used for building applications, automation, and data analysis. 🔹 Founder of Python Python was created by Guido van Rossum and first released in 1991. 🔹 Key Features of Python • Easy to learn and readable syntax • Interpreted language • Object-oriented programming support • Large standard library • Cross-platform compatibility 🔹 Fields Where Python is Used • Web Development • Data Science and Machine Learning • Artificial Intelligence • Automation and Scripting • Cybersecurity • Software Development Every day is helping me understand how programming languages work and why Python is one of the most popular languages today. Looking forward to learning more tomorrow! 💻 #Python #LearningJourney #FullStackDevelopment #GlobalGlobal Quest Technologies #Programming #GG.R NARENDRA REDDY Global Quest Technologies

🚀 Day 12/50 – Take a Break Desktop Notification System ⏰💻 Today I built a Take a Break Desktop Notification System using Python. When we work continuously on a computer, it’s easy to lose track of time and forget to take breaks. This small automation tool helps solve that problem by sending periodic desktop notifications reminding the user to take a break. The program runs in the background and triggers notifications after a fixed time interval to encourage healthier work habits. 🛠 How It Works The program uses a Python notification library to send desktop alerts after a specific amount of time. Once the timer completes, a notification pops up reminding the user to step away from the screen and take a short break. This kind of automation can be very helpful for developers, students, or anyone who spends long hours working on a computer. ⚙ Technologies Used Python plyer (Desktop Notification Library) time module 📚 Key Learnings Through this project I learned: ✔ How to create desktop notifications using Python ✔ How to automate reminders using time intervals ✔ How small automation tools can improve productivity ✔ How Python can interact with the operating system 📂 Project Available on GitHub You can explore the full project here: 👉 https://lnkd.in/g4kVDpG4 #Python #PythonProjects #50DaysOfCode #LearningInPublic #Programming #Developers #CodingJourney #PythonDeveloper #BuildInPublic #TechLearning