katanavsdataflowkit
Katana is a next-generation web crawling and spidering framework written in Go by ProjectDiscovery. It is designed for fast, comprehensive endpoint and asset discovery and is widely used in the security research and bug bounty communities.
Katana offers multiple crawling modes:
- Standard mode Fast HTTP-based crawling without a browser. Parses HTML, JavaScript files, and other resources to discover endpoints and links.
- Headless mode Uses a headless Chrome browser for crawling JavaScript-rendered pages and single-page applications (SPAs).
- Passive mode Discovers URLs from external sources (Wayback Machine, CommonCrawl, etc.) without actively visiting the target.
Key features include:
- Scope control Configurable crawl scope with regex patterns for including/excluding URLs, domains, and file extensions.
- JavaScript parsing Extracts endpoints from JavaScript files, inline scripts, and AJAX requests even in standard (non-headless) mode.
- Customizable output Filter and format output with field selection, JSON output, and custom templates.
- Rate limiting Built-in rate limiting and concurrency control to avoid overwhelming targets.
- Proxy support HTTP and SOCKS5 proxy support with rotation.
- Form filling Can detect and auto-fill forms to discover endpoints behind form submissions.
While Katana was designed for security research and reconnaissance, its fast crawling capabilities and JavaScript parsing make it equally useful for web scraping discovery and sitemap generation.
Dataflow kit ("DFK") is a Web Scraping framework for Gophers. It extracts data from web pages, following the specified CSS Selectors. You can use it in many ways for data mining, data processing or archiving.
Web-scraping pipeline consists of 3 general components:
- Downloading an HTML web-page. (Fetch Service)
- Parsing an HTML page and retrieving data we're interested in (Parse Service)
- Encoding parsed data to CSV, MS Excel, JSON, JSON Lines or XML format.
For fetching dataflowkit has several types of page fetchers:
- Base fetcher uses standard golang http client to fetch pages as is. It works faster than Chrome fetcher. But Base fetcher cannot render dynamic javascript driven web pages.
- Chrome fetcher is intended for rendering dynamic javascript based content. It sends requests to Chrome running in headless mode.
For parsing dataflowkit extracts data from downloaded web page following the rules listed in configuration JSON file. Extracted data is returned in CSV, MS Excel, JSON or XML format.
Some dataflowkit features:
- Scraping of JavaScript generated pages;
- Data extraction from paginated websites;
- Processing infinite scrolled pages.
- Sсraping of websites behind login form;
- Cookies and sessions handling;
- Following links and detailed pages processing;
- Managing delays between requests per domain;
- Following robots.txt directives;
- Saving intermediate data in Diskv or Mongodb. Storage interface is flexible enough to add more storage types easily;
- Encode results to CSV, MS Excel, JSON(Lines), XML formats;
- Dataflow kit is fast. It takes about 4-6 seconds to fetch and then parse 50 pages.
- Dataflow kit is suitable to process quite large volumes of data. Our tests show the time needed to parse appr. 4 millions of pages is about 7 hours.
Highlights
fastpopularlarge-scale
Example Use
```go
package main
import (
"context"
"math"
"github.com/projectdiscovery/katana/pkg/engine/standard"
"github.com/projectdiscovery/katana/pkg/output"
"github.com/projectdiscovery/katana/pkg/types"
)
func main() {
// Configure crawl options
options := &types.Options{
MaxDepth: 3,
FieldScope: "rdn", // restrict to root domain
BodyReadSize: math.MaxInt,
Timeout: 10,
Concurrency: 10,
Parallelism: 10,
Delay: 0,
RateLimit: 150,
Strategy: "depth-first",
OnResult: func(result output.Result) {
// Process each discovered URL
println(result.Request.URL)
},
}
// Create and run the crawler
crawlerOptions, _ := types.NewCrawlerOptions(options)
defer crawlerOptions.Close()
crawler, _ := standard.New(crawlerOptions)
defer crawler.Close()
// Start crawling
_ = crawler.Crawl("https://example.com")
}
```
Dataflowkit uses JSON configuration like:
```json
{
"name": "collection",
"request": {
"url": "https://example.com"
},
"fields": [
{
"name": "Title",
"selector": ".product-container a",
"extractor": {
"types": [
"text",
"href"
],
"filters": [
"trim",
"lowerCase"
],
"params": {
"includeIfEmpty": false
}
}
},
{
"name": "Image",
"selector": "#product-container img",
"extractor": {
"types": [
"alt",
"src",
"width",
"height"
],
"filters": [
"trim",
"upperCase"
]
}
},
{
"name": "Buyinfo",
"selector": ".buy-info",
"extractor": {
"types": [
"text"
],
"params": {
"includeIfEmpty": false
}
}
}
],
"paginator": {
"selector": ".next",
"attr": "href",
"maxPages": 3
},
"format": "json",
"fetcherType": "chrome",
"paginateResults": false
}
```
which is then ingested through CLI command.
Alternatives / Similar
crawl4ai
new
scrapling
new
crawlee
new
mechanize
new
scrapegraphai
new
botasaurus
new
goutte
new
kimurai
new
firecrawl
new
katana
new
crawl4ai
new
scrapling
new
crawlee
new
mechanize
new
scrapegraphai
new
botasaurus
new
goutte
new
kimurai
new
firecrawl
new