How does a web scraper work?

#datascience #python #analytics #learning

Recently I made a web scraper for my EEG attention classification project, here's how a web scraper works.

1. Request:

The web scraper starts by receiving a request from the user specifying the target website and desired data.
The request may also include specific instructions for filtering or parsing the extracted information.

2. Fetching Data:

The scraper initiates a web request to the target website, mimicking a regular browser visit.
This request retrieves the website's HTML code, which contains all the content and structure information.

3. Parsing the HTML:

The scraper then parses the downloaded HTML code using various techniques like regular expressions or dedicated libraries.
This process identifies and extracts the desired data based on the provided instructions.

4. Data Extraction:

The extracted data can be targeted specific elements like text within specific HTML tags or attributes.
Alternatively, the scraper can extract entire sections or tables based on their structure and position.

5. Handling Dynamic Content:

Some websites use dynamic content generated by JavaScript or other scripting languages.
Web scrapers often utilise headless browsers or dedicated libraries to handle such dynamic content and extract the relevant data.

6. Data Processing:

Once extracted, the data can be cleaned, formatted, and converted to the desired format (e.g., CSV, JSON).
This may involve removing unwanted elements, handling inconsistencies, and structuring the data for further use.

7. Storage and Output:

Finally, the processed data is stored in a chosen location (e.g., local file, database) or delivered to the user.
The output format and delivery method depend on the specific application and user needs.

Additional Points:

Web scrapers can be automated to run periodically and collect updated data over time.
Advanced scrapers can handle complex website structures and utilise various techniques to avoid detection and bypass anti-scraping measures.
Ethical web scraping practices involve respecting robots.txt guidelines and using responsible scraping techniques.