Disclaimer: This project is intended to study the Scrapy Spider Framework and the MongoDB database, it cannot be used for commercial or other personal intentions. If used improperly, it will be the individuals bear.
- The project is mainly used for crawling a Website, the largest site in the world. In doing so it retrieves video titles, duration, mp4 link, cover url and direct Website`s url.
- This project crawls PornHub.com quickly, but with a simple structure.
- This project can crawl up to 5 millon Website`s videos per day, depending on your personal network. Because of my slow bandwith my results are relatively slow.
- The crawler requests 10 threads at a time, and because of this can achieve the speed mentioned above. If your network is more performant you can request more threads and crawl a larger amount of videos per day. For the specific configuration see [pre-boot configuration]
Environment, Architecture
Language: Python2.7
Environment: MacOS, 4G RAM
Database: MongoDB
- Mainly uses the scrapy reptile framework.
- Join to the Spider randomly by extracted from the Cookie pool and UA pool.
- Start_requests start five Request based on Website`s classification, and crawl the five categories at the same time.
- Support paging crawl data, and join to the queue.
Instructions for use
Pre-boot configuration
- Install MongoDB and start without configuration
- Install Python dependent modules：Scrapy, pymongo, requests or
pip install -r requirements.txt
- Modify the configuration by needed, such as the interval time, the number of threads, etc.
Start up
- cd WebHub
- python quickstart.py
Run screenshots
Database description
The table in the database that holds the data is PhRes. The following is a field description:
PhRes table：
video_title: The title of the video, and as a unique.
link_url: Video jump to Website`s link
image_url: Video cover link
video_duration: The length of the video, in seconds
quality_480p: Video 480p mp4 download address
For Chinese
