Saving Scraped Data

Scraping is useless if you don’t save data. Your goal is not just to print results, but to: - store them - reuse later - analyze - share ## Why saving matters If you scrape: - today: 100 products - tomorrow: prices change You want history. ## Common formats - CSV: simple tables (Excel friendly) - JSON: structured/nested data (APIs, configs) --- ## Save to CSV CSV = comma separated values. ```python import csv data = [ ["Name", "Price"], ["Apple", 120], ["Banana", 80], ] with open("products.csv", "w", newline="", encoding="utf-8") as f: writer = csv.writer(f) writer.writerows(data) ``` You can open this file in Excel. --- ## Save scraped data to CSV ```python import requests, csv from bs4 import BeautifulSoup res = requests.get("https://example.com") soup = BeautifulSoup(res.text, "html.parser") rows = [] rows.append(["Text", "Link"]) for a in soup.find_all("a"): rows.append([a.text.strip(), a.get("href")]) with open("links.csv", "w", newline="", encoding="utf-8") as f: writer = csv.writer(f) writer.writerows(rows) ``` --- ## Save to JSON JSON is great for nested data. ```python import json data = [ {"name": "Apple", "price": 120}, {"name": "Banana", "price": 80} ] with open("products.json", "w", encoding="utf-8") as f: json.dump(data, f, indent=2) ``` --- ## Graph: scraping to storage ```mermaid flowchart LR A[Scraper] --> B[Extracted Data] B --> C[CSV File] B --> D[JSON File] ``` ## Remember - Always save data, not just print - CSV for tables - JSON for structured data - Use utf-8 encoding