Web scraping with python how to handle pagination

web scraping is the process of extracting data from websites. python, with its rich ecosystem of libraries, makes it an excellent choice for web scraping tasks. this tutorial will guide you through the basics of web scraping using python, with a focus on handling pagination.

### prerequisites

before you start, make sure you have the following installed:

- python (3.x)
- libraries: `requests`, `beautifulsoup`, and optionally `pandas` for data handling.

you can install the required libraries using pip:

### basic web scraping

here’s a simple example of scraping data from a website:

1. **import libraries**:

2. **send a request to the website**:

3. **parse the html content**:

4. **extract data**:

### handling pagination

many websites display their data across multiple pages. to scrape data from multiple pages, you need to identify the url structure of the pagination and loop through the pages.

#### example: scraping with pagination

here’s how you can handle pagination:

1. **define the base url**:

2. **loop through the pages**:

3. **store the data in a dataframe**:

### complete example

here’s the complete code for scraping articles with pagination:

### best practices

- **user-agent**: set a user-agent in your requests to mimic a browser and avoid being blocked.
- **error handling**: always handle errors and exceptions to make your scraper robust.

### conclusion

this tutorial covered the basics of web scraping with python, including how to handle pagination. with this knowledge, you can start scraping your ...

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