(2/2) Virtual Env workflow 📌 Save dependencies: pip freeze > requirements.txt 📌 Exit venv: deactivate Each project = its own sandbox 🏖️ → no conflicts, reproducible installs 🚀 #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

counter = it.count(3, 10) next(counter) # 3 → 13 → 23 ... Efficient looping tools in one place 🚀 #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Python number bases 🧮 bin(10) # '0b1010' → binary oct(10) # '0o12' → octal hex(255) # '0xff' → hexadecimal int('1010', 2) # binary → int int('12', 8) # octal → int int('ff', 16) # hex → int #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Python numbers & bases 🔢 int('35') str(35) int('35', 8) 2 ** 10 pow(2, 10) pow(2, 10, 100) # with mod abs(-4) round(3.14) Handy tricks for everyday math! #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Python web frameworks 🌐 Flask Django FastAPI 🚀 from flask import Flask app = Flask(__name__) @app.route("/") def home(): return "Hello, World!" app.run() #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Call an API with Python 🚀 import requests api_url = "api.open-notify.org/astros.json" response = requests.get(api_url) print(response.status_code) # 200 = OK data = response.json() print(data["number"]) 👉 requests.get() 👉 .json() #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Working with API & JSON in Python: import json data = {"name": "alireza", "age": 34} json_str = json.dumps(data) new_data = json.loads(json_str) print(new_data["age"]) # 34 dumps = dict → JSON string loads = JSON string → dict #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

👉 You can also create & edit Excel files: from openpyxl import Workbook import datetime new_wb = Workbook() ws = new_wb.active ws["A1"] = "jadi" ws.append([1, 2, 3, 4]) ws["A2"] = datetime.datetime.now() new_wb.save("funny.xlsx") #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Working with PDFs in Python 📑 import PyPDF2 my_pdf = PyPDF2.PdfReader("file.pdf") pages = my_pdf.pages print(len(pages)) first_page = pages[0] print(first_page.extract_text()) Super handy for reading & extracting text from PDFs! #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

# Write with open("mycsv.csv", "w", newline="") as f: writer = csv.writer(f, delimiter="|") writer.writerow([1, 2, 3]) writer.writerow(["jadi", "madi", "padi"]) 👉 Also: csv.DictReader for dict-style access. #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Working with CSV in Python 📊 CSV = Comma Separated Values Common libs: csv, pandas import csv # Read with open("data.csv", encoding="utf-8") as f: reader = csv.reader(f) rows = list(reader) #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

Working with images in Python 🎨🖼️ 📦 pip install Pillow from PIL import Image Useful methods: .show() .crop() .paste() .rotate() .resize() .save() .putpixel() .putalpha() ✨ Also: ASCII fun with ord('J') → 74 and chr(74) → 'J' #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

1/3 Perfect when JS-heavy pages block requests/BS4 😉 #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

1/1 - Selectors & Selenium 🔹 CSS Selectors Use browser Inspector → pick element → copy selector. 👉 Helps you grab exact HTML elements. #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

1/3 Selectors: #id 👉 select by id .class 👉 select by class p span 👉 nested elements div > span 👉 direct child Powerful combo for parsing HTML! ⚡ #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

1/2 🔹 BeautifulSoup import bs4 data = r.text soup = bs4.BeautifulSoup(data, "html.parser") title = soup.select("title") print(title[0], type(title[0])) Quick & powerful combo for extracting web data! ⚡ #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

1/1 - Web Scraping with Python 🔹 Requests import requests r = requests.get("http.cat") #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

⚡ Web Scraping – Networking Basics Sometimes you don’t need heavy tools… Python has built-ins like: 🔹 socket 🔹 urllib And when your request fails? 👉 Study HTTP response codes with style: http.cat 🐱 #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

📌 (2/2) Web Scraping — Setup Install some essentials: pip install requests pip install bs4 pip install lxml Pro tip: Learn HTML + CSS + JS → “View Page Source” is your best friend. #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣

📌 (1/2) Web Scraping — Quick Notes 🔹 Websites are always human-readable, but not always machine-readable. That’s why we use scraping tools 👇 🛠️ Popular Python libraries: BeautifulSoup Requests Scrapy Selenium lxml Playwright #MyDevJourney #JadiWay #TechNotes 🐍🖥️👣