Scrapy-Distributed 2023.4.23

A series distributed components for Scrapy framework

Scrapy-Distributed

Scrapy-Distributed is a series of components for you to develop a distributed crawler base on Scrapy in an easy way.

Now! Scrapy-Distributed has supported RabbitMQ Scheduler, Kafka Scheduler and RedisBloom DupeFilter. You can use either of those in your Scrapy's project very easily.

Features

• RabbitMQ Scheduler
  • Support custom declare a RabbitMQ's Queue. Such as passive, durable, exclusive, auto_delete, and all other options.
• RabbitMQ Pipeline
  • Support custom declare a RabbitMQ's Queue for the items of spider. Such as passive, durable, exclusive, auto_delete, and all other options.
• Kafaka Scheduler
  • Support custom declare a Kafka's Topic. Such as num_partitions, replication_factor and will support other options.
• RedisBloom DupeFilter
  • Support custom the key, errorRate, capacity, expansion and auto-scaling(noScale) of a bloom filter.

Requirements

• Python >= 3.6
• Scrapy >= 1.8.0
• Pika >= 1.0.0
• RedisBloom >= 0.2.0
• Redis >= 3.0.1
• kafka-python >= 1.4.7

TODO

• RabbitMQ Item Pipeline
• Support Delayed Message in RabbitMQ Scheduler
• Support Scheduler Serializer
• Custom Interface for DupeFilter
• RocketMQ Scheduler
• RocketMQ Item Pipeline
• SQLAlchemy Item Pipeline
• Mongodb Item Pipeline
• Kafka Scheduler
• Kafka Item Pipeline

Usage

Step 0:

pip install scrapy-distributed

OR

git clone https://github.com/Insutanto/scrapy-distributed.git && cd scrapy-distributed
&& python setup.py install

There is a simple demo in examples/simple_example. Here is the fast way to use Scrapy-Distributed.

Examples of RabbitMQ

If you don't have the required environment for tests:

# pull and run a RabbitMQ container.
docker run -d --name rabbitmq -p 0.0.0.0:15672:15672 -p 0.0.0.0:5672:5672 rabbitmq:3-management

# pull and run a RedisBloom container.
docker run -d --name redisbloom -p 6379:6379 redis/redis-stack

cd examples/rabbitmq_example
python run_simple_example.py

Or you can use docker compose:

docker compose -f ./docker-compose.dev.yaml up -d
cd examples/rabbitmq_example
python run_simple_example.py

Examples of Kafka

If you don't have the required environment for tests:

# make sure you have a Kafka running on localhost:9092
# pull and run a RedisBloom container.
docker run -d --name redisbloom -p 6379:6379 redis/redis-stack

cd examples/kafka_example
python run_simple_example.py

Or you can use docker compose:

docker compose -f ./docker-compose.dev.yaml up -d
cd examples/kafka_example
python run_simple_example.py

RabbitMQ Support

If you don't have the required environment for tests:

# pull and run a RabbitMQ container.
docker run -d --name rabbitmq -p 0.0.0.0:15672:15672 -p 0.0.0.0:5672:5672 rabbitmq:3-management

# pull and run a RedisBloom container.
docker run -d --name redisbloom -p 6379:6379 redis/redis-stack

Or you can use docker compose:

docker compose -f ./docker-compose.dev.yaml up -d

Step 1:

Only by change SCHEDULER, DUPEFILTER_CLASS and add some configs, you can get a distributed crawler in a moment.

SCHEDULER = "scrapy_distributed.schedulers.DistributedScheduler"
SCHEDULER_QUEUE_CLASS = "scrapy_distributed.queues.amqp.RabbitQueue"
RABBITMQ_CONNECTION_PARAMETERS = "amqp://guest:guest@localhost:5672/example/?heartbeat=0"
DUPEFILTER_CLASS = "scrapy_distributed.dupefilters.redis_bloom.RedisBloomDupeFilter"
BLOOM_DUPEFILTER_REDIS_URL = "redis://:@localhost:6379/0"
BLOOM_DUPEFILTER_REDIS_HOST = "localhost"
BLOOM_DUPEFILTER_REDIS_PORT = 6379
REDIS_BLOOM_PARAMS = {
    "redis_cls": "redisbloom.client.Client"
}
BLOOM_DUPEFILTER_ERROR_RATE = 0.001
BLOOM_DUPEFILTER_CAPACITY = 100_0000

# disable the RedirectMiddleware, because the RabbitMiddleware can handle those redirect request.
DOWNLOADER_MIDDLEWARES = {
    ...
    "scrapy.downloadermiddlewares.redirect.RedirectMiddleware": None,
    "scrapy_distributed.middlewares.amqp.RabbitMiddleware": 542
}

# add RabbitPipeline, it will push your items to rabbitmq's queue. 
ITEM_PIPELINES = {
    ...
   'scrapy_distributed.pipelines.amqp.RabbitPipeline': 301,
}

Step 2:

scrapy crawl <your_spider>

Kafka Support

Step 1:

SCHEDULER = "scrapy_distributed.schedulers.DistributedScheduler"
SCHEDULER_QUEUE_CLASS = "scrapy_distributed.queues.kafka.KafkaQueue"
KAFKA_CONNECTION_PARAMETERS = "localhost:9092"
DUPEFILTER_CLASS = "scrapy_distributed.dupefilters.redis_bloom.RedisBloomDupeFilter"
BLOOM_DUPEFILTER_REDIS_URL = "redis://:@localhost:6379/0"
BLOOM_DUPEFILTER_REDIS_HOST = "localhost"
BLOOM_DUPEFILTER_REDIS_PORT = 6379
REDIS_BLOOM_PARAMS = {
    "redis_cls": "redisbloom.client.Client"
}
BLOOM_DUPEFILTER_ERROR_RATE = 0.001
BLOOM_DUPEFILTER_CAPACITY = 100_0000

DOWNLOADER_MIDDLEWARES = {
    ...
   "scrapy_distributed.middlewares.kafka.KafkaMiddleware": 542
}

Step 2:

scrapy crawl <your_spider>

Reference Project

scrapy-rabbitmq-link(scrapy-rabbitmq-link)

scrapy-redis(scrapy-redis)