Python Web Scraping Fundamentals

🚀 Python List Methods — Explained Visually 🐍 > If you’re learning Python, this is something you must understand 👇 Lists are used everywhere — from basic scripts to: 📊 Data Analytics 🤖 Machine Learning 🌐 Web Development >This visual covers the most important list methods: • append() • insert() • pop() • remove() • count() • index() • reverse() 👉 Mastering fundamentals = Faster growth in Python 📌 Save this post for revision 🤝 Follow me for more beginner-friendly Python & Data insights #Python #LearnPython #PythonBasics #DataAnalytics #MachineLearning #Coding #Programming #Developer #LearningInPublic

Worked on comprehensions in Python, covering list, dictionary, and set comprehensions to write concise, readable, and efficient data transformations 🐍 Practiced generating derived data structures, applying conditional filters, creating nested lists, and extracting unique values from text. This approach highlights how Python enables expressive logic without sacrificing clarity. Key takeaways: Using list comprehensions for clean data generation and filtering 🔁 Building nested lists for structured outputs Applying dictionary comprehensions to transform and filter key–value data Leveraging set comprehensions to extract unique elements from text Writing compact logic without compromising readability ✨ #Python #Comprehensions #DataStructures #ProgrammingFundamentals #SoftwareDevelopment #CleanCode

Google has open-sourced the LangExtract Python library. It turns unstructured documents into structured data, with clear source references for each result. 100% open-source.

✅ Python Basic Certificate – Key Points #Learned Python fundamentals (syntax, keywords, indentation) #Worked with data types: int, float, string, list, tuple, set, dictionary #Used operators and expressions #Implemented conditional statements (if, if-else, elif) #Practiced loops (for loop, while loop) #Learned functions and parameter passing #Understood user input and output #Basic knowledge of file handling #Handled errors using try-except #Wrote simple Python programs and mini projects #Developed problem-solving and logical thinking skills

🚀 Project Showcase: Web Scraping with Python! 🐍 I recently built a web scraper using Python, BeautifulSoup, and Pandas to extract book data from Books to Scrape 📌 Key Highlights: Scraped book titles, prices, availability, and ratings across multiple pages Used requests and BeautifulSoup for data extraction Stored the data in a CSV file for easy analysis 💡 This project helped me practice data extraction, web automation, and data cleaning—skills essential for Data Analysis and Python development. Check out the CSV output and explore how you can turn web data into actionable insights! Project Link : https://lnkd.in/gqRcbYdb #Python #WebScraping #DataAnalysis #BeautifulSoup #Pandas #DataScience #LearningByDoing

Python script helps users track their daily internet usage against a predefined data bundle. It calculates whether the user has consumed more or less than the expected daily allowance and provides feedback accordingly. https://lnkd.in/d3uv65Rr

Today’s Python focus was 𝗠𝗼𝗱𝘂𝗹𝗲𝘀. I worked on understanding how Python lets you organize code into reusable files instead of writing everything in one script. 𝗪𝗵𝗮𝘁 𝗜 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝗱 𝘁𝗼𝗱𝗮𝘆: • Importing built in modules like math and calendar • Using functions from the math module such as sqrt() and ceil() • Working with the calendar module to generate month level calendars • Creating a custom module to store reusable functions • Importing and using functions from a user defined module • Separating logic into different files for better structure and readability 𝗞𝗲𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀: • Modules help break large programs into smaller, manageable pieces • Built in modules save time and prevent rewriting common logic • Custom modules make code reusable across multiple scripts • Organizing functions into modules improves maintainability Working with modules made it clear how real Python projects are structured. Code is written once, organized properly, and reused when needed. If you are learning Python, are you already using modules in your practice or still keeping everything in a single file? #Python #PythonLearning #PythonModules #ProgrammingBasics #LearningInPublic #DataAnalytics #Upskilling

🚀 Learning Python: Using enumerate() in Loops! 🐍 Today, I explored a simple yet powerful Python feature — enumerate(). It makes looping through sequences cleaner and more readable, especially when you need both the index and the value. 🔍 What I learned: • What enumerate() is and why it’s useful • Looping with both index and value at the same time • Replacing manual counters with cleaner code • How enumerate() improves readability and reduces errors • Using start= to customize index values 💡 Why it matters: Using enumerate() helps write cleaner, more Pythonic code — which is especially useful in data analysis, automation, and everyday scripting. 📚 Next Goal: Continue practicing Python loops and explore more built-in functions to write efficient code. If you have any tips or practice ideas for mastering Python loops, feel free to share below 👇 #Python #LearningJourney #Programming #DataAnalysis #PythonTips #Enumerate #CodingJourney

🐍 90 Days of Python – Day 21 Sets in Python Today, I learned about sets in Python, a data structure used to store unique and unordered elements. Sets are especially useful when working with data that should not contain duplicates and when checking membership efficiently. 🔹 Key concepts I explored today: • Creating sets using set() • Understanding how sets handle unique values • Adding and removing elements • Using sets for membership testing and data cleaning Sets are commonly used in data preprocessing, analytics, and performance-critical operations where uniqueness matters. I’m practicing these concepts to better understand how Python handles collections efficiently. 📌 Day 21 completed. Managing unique data with sets. 👉 In which scenario do you think sets are more useful than lists? #90DaysOfPython #PythonLearning #LearningInPublic #PythonSets #PythonDeveloper #BTechCSE

Proof of Work | Python Mini Project 🚀 As part of my Python learning journey, I recently built a custom Email Validation Program using core Python concepts. 🔍 What the project does The script validates an email ID by checking: Minimum length requirements Whether the email starts with an alphabet Presence of exactly one @ symbol Correct placement of . (dot) Absence of spaces and uppercase characters Allowance of valid characters like digits, _, @, and . Based on these checks, the program clearly identifies whether an email is valid or highlights the exact issue. 🧠 What I learned String indexing and traversal Built-in string methods like isalpha(), isdigit(), isspace() Conditional logic and control flow Importance of handling edge cases Writing readable and logical validation code This project may be small, but it helped me strengthen my fundamentals and build confidence to move toward more complex Python applications. Next goal: improving this validator using functions and exploring regex-based validation. #proofofwork #pythonlearning #programmingbasics #learningbydoing #techjourney #computerscience