There are several popular web scraping frameworks of varying complexity and whether to use a framework or not depends on a few key factors:
- Frameworks come with many batteries-included like automatically configuring request headers, rate limiting, proxy switching etc.
- Community plugins and documentation helps to solve popular problems.
- Easy to scale up.
- Learning curve.
- Frameworks are often very opaque making it harder to debug and understand the scraping process.
- Hard to patch weak points for avoiding blocking.
In summary, frameworks are best for medium-sized average web scrapers. Here's a list of popular web scraping frameworks:
|Python||scrapy||most popular web scraping framework, big community, feature rich|
|autoscraper||automatic parsing via fuzzy matching|
|Go||colly||simple, aimed at crawling|
|gospider||similar to colly|
|dataflowkit||integrated browser automation|
|ferret||custom DSL, integrated browser automation (Chrome)|
|PHP||panther||integrated browser automation|
|Ruby||spidr||simple, aimed at crawling|
|NodeJS||ayakashi||custom DSL, extendible|