Ewen Gallet

Web Scraper

The Web Scraper is a data extraction tool built using the Spring Batch framework. It automates the process of fetching and parsing data from websites, enabling efficient and scalable scraping operations.

Key Components:

• Job Configuration: The scraper utilizes Spring Batch's job configuration to define the steps involved in the scraping process. It specifies the data source, data processing logic, and data storage.
• ItemReader: The ItemReader component reads data from the web sources. It fetches the HTML content from target websites using HTTP requests and converts it into a format suitable for processing.
• ItemProcessor: The ItemProcessor performs the necessary data transformations and validations. It applies parsing rules and filters to extract relevant information from the fetched HTML content.
• ItemWriter: The ItemWriter persists the scraped data into the desired storage system. It can store the data in a database, write it to files, or publish it to external APIs.
• JobLauncher: The JobLauncher triggers the execution of the scraping job. It coordinates the execution flow and manages job scheduling, allowing the scraper to be run at predefined intervals.

Workflow:

The scraper follows a well-defined workflow that consists of the following steps:

1. Data Source Identification: Determine the target websites or web pages from which data needs to be scraped.
2. Job Configuration: Configure the scraping job by defining the necessary components, such as the ItemReader, ItemProcessor, and ItemWriter.
3. Data Fetching: The ItemReader fetches the HTML content from the identified web sources using HTTP requests.
4. Data Processing: The ItemProcessor applies parsing rules and filters to the fetched HTML content to extract the desired information.
5. Data Storage: The ItemWriter persists the extracted data into the designated storage system.
6. Execution: Trigger the scraping job using the JobLauncher. The job can be scheduled to run periodically to keep the data up to date.

Benefits:

The web scraper implemented using Spring Batch offers several benefits, including:

• Scalability: Spring Batch's built-in scalability features allow the scraper to handle large volumes of data efficiently.
• Error Handling: Spring Batch provides robust error handling and retry mechanisms, ensuring the reliability of the scraping process.
• Monitoring and Logging: The scraper can leverage Spring Batch's monitoring and logging capabilities to track job progress, identify issues, and collect performance metrics.
• Integration: Spring Batch seamlessly integrates with other Spring frameworks and third-party tools, enabling easy integration with existing systems.

Overall, the Web Scraper with Spring Batch provides a reliable and scalable solution for automating data extraction from websites, facilitating efficient data processing and storage.

Technologies:

Spring Batch, Java, HTML, HTTP, Postgres, Maven, Git, IntelliJ, JUnit, REST API, CSS, JavaScript, Docker.