We are a fictitious music streaming service without real data - use us to learn collecting data with web scraping and APIs.

Learn how to scrape

Hey there, curious coder! 🚀 Are you ready to start with web scraping? Imagine being able to extract any information from websites, and store it for use in a research project!

Why Web Scraping is Super Cool

Web scraping is your key to unlocking data and insights on the internet. Think of the internet as a public library: web scraping allows you to pick some of the books, and copy selected information for later use. Whether you're looking for public data to use in a research project, or simply want to satisfy your curiosity, web scraping lets you gather and organize information from websites without manual copying and pasting.

Install Python or R

One way to get started is by using Python or R. If you're new to Python or R, then install one of these packages first (click here for R or Python). Unsure which one to use? We'd recommend R if you're already using it, e.g., in a research project. It works well for simple applications. Looking to engage in some more advanced projects? Then go with Python.

Let's Get Our Hands Dirty

Let's start by extracting some data from this website, using your programming language of choice. Are you ready to roll? Open R or Python and paste the code snippets below. Let's go!

# Load the necessary libraries

# Specify the URL of the website
url <- "https://music-to-scrape.org"

# Read the webpage into R
page <- read_html(url)

# Extract the desired information using CSS selectors (here, songs from the weekly top 15)
songs <- page %>%
  html_nodes("section[name='weekly_15']") %>% html_elements('a') %>% html_element('p') %>% html_text()

# Print out the scraped data

# Import the required libraries
import requests
from bs4 import BeautifulSoup

# Specify the URL of the website
url = "https://music-to-scrape.org"

# Send an HTTP GET request and get the webpage content
response = requests.get(url)
content = response.content

# Parse the HTML content with BeautifulSoup
soup = BeautifulSoup(content, 'html.parser')

# Extract the desired information using CSS selectors (here, items from the weekly top 15)
items = soup.find(attrs={'name':'weekly_15'}).find_all('p')

# Print out the scraped items
for item in items:

Good job!

You've just scraped data from our website! Make sure to also check out how our API works. Keep it up & happy coding!