kk-scrapy-redis 0.0.1

Redis-based components for Scrapy.

Redis-based components for Scrapy.

• Usage: https://github.com/rmax/scrapy-redis/wiki/Usage

• Documentation: https://github.com/rmax/scrapy-redis/wiki.

• Release: https://github.com/rmax/scrapy-redis/wiki/History

• Contribution: https://github.com/rmax/scrapy-redis/wiki/Getting-Started

• LICENSE: MIT license

Features

• Distributed crawling/scraping

  You can start multiple spider instances that share a single redis queue. Best suitable for broad multi-domain crawls.

• Distributed post-processing

  Scraped items gets pushed into a redis queued meaning that you can start as many as needed post-processing processes sharing the items queue.

• Scrapy plug-and-play components

  Scheduler + Duplication Filter, Item Pipeline, Base Spiders.

• In this forked version: added json supported data in Redis

  data contains url, `meta` and other optional parameters. meta is a nested json which contains sub-data. this function extract this data and send another FormRequest with url, meta and addition formdata.

  For example:

  { "url": "https://exaple.com", "meta": {"job-id":"123xsd", "start-date":"dd/mm/yy"}, "url_cookie_key":"fertxsas" }

  this data can be accessed in scrapy spider through response. like: request.url, request.meta, request.cookies

Note

This features cover the basic case of distributing the workload across multiple workers. If you need more features like URL expiration, advanced URL prioritization, etc., we suggest you to take a look at the Frontera project.

Requirements

• Python 3.7+

• Redis >= 5.0

• Scrapy >= 2.0

• redis-py >= 4.0

Installation

From pip

pip install scrapy-redis

From GitHub

git clone https://github.com/darkrho/scrapy-redis.git
cd scrapy-redis
python setup.py install

Note

For using this json supported data feature, please make sure you have not installed the scrapy-redis through pip. If you already did it, you first uninstall that one.

pip uninstall scrapy-redis

Alternative Choice

Frontera is a web crawling framework consisting of crawl frontier, and distribution/scaling primitives, allowing to build a large scale online web crawler.

History