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