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.

Links

• Code
• My GitHub