new

scraper.py

@@ -0,0 +1,41 @@
+import requests
+from bs4 import BeautifulSoup
+import pandas as pd
+
+def scrape_courses():
+    url = "https://courses.analyticsvidhya.com/pages/all-free-courses"  # Use the actual URL where the courses are listed
+    response = requests.get(url)
+    soup = BeautifulSoup(response.text, 'html.parser')
+    
+    courses = []
+    for course_card in soup.find_all("a", class_="card-link"):
+        # Extract title
+        title = course_card.find("h2", class_="card-text").get_text(strip=True)
+        
+        # Extract duration and lessons (if available)
+        duration_lessons = course_card.find("p", class_="fs-14").get_text(strip=True)
+        duration, lessons = duration_lessons.split(" Hours")[0] + " Hours", duration_lessons.split(" Hours")[1].strip()
+        
+        # Extract review rating (if available)
+        rating = course_card.find("span", class_="rating")  # Assuming rating is in a span with class "rating"
+        rating = rating.get_text(strip=True) if rating else "No rating"
+        
+        # Extract price (if available)
+        price = course_card.find("span", class_="price")  # Assuming price is in a span with class "price"
+        price = price.get_text(strip=True) if price else "Free"  # Assuming courses without price are free
+        
+        courses.append({
+            'title': title,
+            'duration': duration,
+            'lessons': lessons,
+            'rating': rating,
+            'price': price
+        })
+
+    return pd.DataFrame(courses)
+
+# Run the scraper and save the data to a CSV
+if __name__ == "__main__":
+    courses_df = scrape_courses()
+    print(courses_df)  # Preview the scraped data
+    courses_df.to_csv("courses_data.csv", index=False)