Web crawling is a process of visiting websites and extracting data automatically. It’s also known as web scraping, web harvesting, or web data mining.
Web crawlers are mainly used to collect data from websites. They can be used for a variety of purposes, such as indexing a search engine, monitoring a website, or downloading content for offline processing.
A common use case is to monitor competitor prices on e-commerce websites and update your own price accordingly. You can check RemoteDBA for more information.
There are two main types of web crawlers:
1. General purpose crawlers:
These crawlers visit any website they come across on the internet. Examples include Googlebot (Google’s web crawler) and Bingbot (Bing’s web crawler).
2. Custom web crawlers:
These are created to visit specific websites and collect specific data. They are also known as spiders or bots. Examples include AhrefsBot (Ahrefs’ web crawler) and SemrushBot (Semrush’s web crawler).
How does a web crawler work?
A web crawler starts with a list of URLs to visit, called the seed list. It then fetches the HTML code for each URL on the seed list. Once it has the HTML code, it extracts all the links from the code and adds them to its queue of URLs to crawl. It then visits each URL in the queue and repeats the process.
The main components of a web crawler are:
1. The scheduler:
This is responsible for maintaining the list of URLs to be crawled. It can be either push-based or pull-based.
2. The downloader:
This component is responsible for fetching the HTML code for a given URL.
3. The parser:
This component is responsible for extracting links from the HTML code and adding them to the scheduler’s queue of URLs to crawl.
4. The link filter:
This component is responsible for filtering out irrelevant or malicious URLs.
5. The data store:
This is where all the extracted data is stored. It can be either a database or a file system.
Web crawling can be divided into two main types:
1. Depth-first search:
This is the most common type of web crawler. It starts with the seed list of URLs and visits them one by one. For each URL, it fetches the HTML code and extracts all the links from the code. It then adds these links to its queue of URLs to crawl and visits them one by one.
2. Breadth-first search:
This is less common than depth-first search but it’s more efficient in some cases. It starts with the seed list of URLs and adds them to its queue of URLs to crawl. It then visits the URLs in the queue one by one. For each URL, it fetches the HTML code and extracts all the links from the code. It then adds these links to its queue of URLs to crawl and visits them one by one.
There are a few things to keep in mind when designing a web crawler:
1. Crawling frequency:
You need to decide how often you want your web crawler to visit a website. This will depend on how often the data on the website changes.
2. Parallelism:
You need to decide how many threads or processes you want your web crawler to use. This will depend on the number of CPUs you have and the speed of your internet connection.
3. Timeouts:
You need to decide how long you want your web crawler to wait for a response from a website before timing out. This will depend on the speed of the website and the resources you have available.
4. Error handling:
You need to decide how you want your web crawler to handle errors. This will depend on the type of data you are crawling and the format in which you want it.
5. Proxy servers:
You need to decide whether or not you want to use proxy servers. This will depend on the number of IP addresses you have and the country in which you are crawling.
Conclusion:
Web crawling is a process of visiting websites and extracting data automatically. The main components of a web crawler are the scheduler, the downloader, the parser, the link filter, and the data store. There are two main types of web crawlers: depth-first search and breadth-first search. When designing a web crawler, you need to keep in mind crawling frequency, parallelism, timeouts, error handling, and proxy servers.
