settings里面的配置：
'''当下面配置了这个（scrapy-redis）时候，下面的调度器已经配置在scrapy-redis里面了'''
##########连接配置########
REDIS_HOST = '127.0.0.1'
REDIS_PORT = 6379
# REDIS_PARAMS = {'password':'xxxx'} #Redis连接参数，默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
REDIS_ENCODING = "utf-8"
# REDIS_URL = 'redis://user:pass@hostname:6379' #连接URL（优先于以上配置）
###########调度器##########
# from scrapy_pro1.scheduler_test import Self_Scheduler
#SCHEDULER='scrapy_pro1.scheduler_test.Self_Scheduler'##可以使用自己定制的调度器
SCHEDULER='scrapy_redis.scheduler.Scheduler'#自带的调度器
##有scrapy_redis里面的调度器，也就是调度器》》scrapy-redis里面的调度器
SCHEDULER_QUEUE_KEY = '%(spider)s:requests' # 调度器中请求存放在redis中的key
#每一个爬虫都有自己自己的历史记录
'''
{
里面是全部的爬虫（里面有相对应的爬虫记录）
chouti:requets(封装了>>url:'',callback=''):'xx结果'
由于redis不能存放request对象，所以需要序列化一下，生成字符串然后保存在redis里面,作为key存在
pickle.dumps(chouti:requets,requets里面封装了要访问url和回调函数，chouti:requets就是key，要去这里面的数据的时候应该也是conn.smembers('chouti:requets')
}
'''
SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat" # 对保存到redis中的数据进行序列化，默认使用pickle
##将requets对象进行序列化处理，作为key保存
SCHEDULER_PERSIST = False # 是否在关闭时候保留原来的调度器和去重记录，True=保留，False=清空
##是否在关闭的时候保留数据REDIS_PARAMS
SCHEDULER_FLUSH_ON_START = True # 是否在开始之前清空 调度器和去重记录，True=清空，False=不清空
##在爬虫启动的时候清空或者是不清空
# SCHEDULER_IDLE_BEFORE_CLOSE = 10 # 去调度器中获取数据时，如果为空，最多等待时间（最后没数据，未获取到）。
#当没有数据的时候，最多等待的时间
SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter' # 去重规则，在redis中保存时对应的key》》chouti:dupefilter
##爬虫相对应的记录，对应的键
SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter' # 去重规则对应处理的类
START_URLS_KEY = '%(name)s:start_urls'
##你要保存去重规则的键
REDIS_START_URLS_AS_SET = False
在scray-redis调度器scheduler里面：
实例化调度器对象：scrapy crawl baidu --nolog
最开始执行from_crawler:
@classmethod
def from_crawler(cls, crawler):##当你执行调度器scrapy-redis的时候，就会传入settigs进来，配置信息是在crawler.settings
instance = cls.from_settings(crawler.settings)##crawlwe.settinsg拿到的是setting对象<scrapy.settings.Settings object at 0x00000265B2E41940>
'''可以调用里面的方法，通过crawler.settings.get("host")'''
# FIXME: for now, stats are only supported from this constructor
instance.stats = crawler.stats
return instance##执行from_settings，传入参数settings
执行from_settings（传入参数settings，配置信息）：
作用：读取配置信息
@classmethod
def from_settings(cls, settings):##settings是传过来的配置文件信息
kwargs = {
'persist': settings.getbool('SCHEDULER_PERSIST'),
'flush_on_start': settings.getbool('SCHEDULER_FLUSH_ON_START'),
'idle_before_close': settings.getint('SCHEDULER_IDLE_BEFORE_CLOSE'),
}
# If these values are missing, it means we want to use the defaults.
optional = {
# TODO: Use custom prefixes for this settings to note that are
# specific to scrapy-redis.
'queue_key': 'SCHEDULER_QUEUE_KEY',
'queue_cls': 'SCHEDULER_QUEUE_CLASS',
'dupefilter_key': 'SCHEDULER_DUPEFILTER_KEY',
# We use the default setting name to keep compatibility.
'dupefilter_cls': 'DUPEFILTER_CLASS',
'serializer': 'SCHEDULER_SERIALIZER',
}
##读取上面的配置文件，取settings里面找到相对应的值，拿到settings后面的结果
for name, setting_name in optional.items():
val = settings.get(setting_name)##匹配settings对应的值出来（自己配置的）
if val:
kwargs[name] = val
'''
val = settings.get(setting_name)取配置文件settings里面拿到相对应的值出来，settings里面的键是在这里面循环拿到的(optional),也就是optional后面的值，对应settinsg里面的键
kwargs[name] = val#存进去
'''
# Support serializer as a path to a module.
##序列化操作,爬虫key序列化
if isinstance(kwargs.get('serializer'), six.string_types):
kwargs['serializer'] = importlib.import_module(kwargs['serializer'])
##取settings里面拿到相对应的配置信息，连接上redis，在settings里面的配置信息就是：
'''
REDIS_HOST = '127.0.0.1'
REDIS_PORT = 6379
# REDIS_PARAMS = {'password':'xxxx'} #Redis连接参数，默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
REDIS_ENCODING = "utf-8"
# REDIS_URL = 'redis://user:pass@hostname:6379' #连接URL（优先于以上配置）
'''
server = connection.from_settings(settings)##取配置文件里面读取自己配置的连接相关的配置文件，连接redis操作
# Ensure the connection is working.
server.ping()##可以测试有没有连接成功
return cls(server=server, **kwargs)
##开始实例化scheduler对象，执行爬虫，cls是当前的类
连接redis操作：from_settings
from_settings = get_redis_from_settings
def get_redis_from_settings(settings):
params = defaults.REDIS_PARAMS.copy()
##拿到默认的配置参数：
'''
REDIS_PARAMS = {
'socket_timeout': 30,
'socket_connect_timeout': 30,
'retry_on_timeout': True,
'encoding': REDIS_ENCODING,
}
'''
params.update(settings.getdict('REDIS_PARAMS'))##取settings里面读取相对应的连接的配合信息,字典扩展一下，后面是settings配置的值，加进去
##把配置settings里面的信息加进来
# XXX: Deprecate REDIS_* settings.
for source, dest in SETTINGS_PARAMS_MAP.items():
val = settings.get(source)##settings.get这个是settings里面的字典名称，DNA在settings里面没有配置名称，所以自己是取模块文件取静态方法，直接后面是模块名字
'''
这个操作是去到这里的键
然后在settigs里面拿到拿到相对应的值出来
'''
if val:
params[dest] = val
# Allow ``redis_cls`` to be a path to a class.
if isinstance(params.get('redis_cls'), six.string_types):
params['redis_cls'] = load_object(params['redis_cls'])
return get_redis(**params)
getdict方法:
def getdict(self, name, default=None):
value = self.get(name, default or {})
if isinstance(value, six.string_types):
value = json.loads(value)
return dict(value)
实例化scheduler对象的时候，开始执行爬虫：
##开始真正执行下面的爬虫部分了，上面的只是取读取配置信息
def enqueue_request(self, request):
if not request.dont_filter and self.df.request_seen(request):
#判断requets里面是否封装了dont_filter
##判断之前是否已经存在此爬虫
self.df.log(request, self.spider)
return False
##已经访问过不用在访问了,返回false
if self.stats:
##如果已经访问过的话
self.stats.inc_value('scheduler/enqueued/redis', spider=self.spider)
##如果未访问过的话，将这个requets对象，加进调度器里面，以便下载器调度使用
self.queue.push(request)##放进队列里面，可能是先进先出，优先级队列，取决于你在settings里面的配置
##其请求的调度其里面
return True##没有访问过的url，将他添加进调度器里面
下载器去队列里面获取数据：queue
def next_request(self):
block_pop_timeout = self.idle_before_close
request = self.queue.pop(block_pop_timeout)##每pop一次的时候，可以拿出当前取出的requets对象
if request and self.stats:
self.stats.inc_value('scheduler/dequeued/redis', spider=self.spider)
return request
scrapy-redis调度器源码：
from scrapy_redis.scheduler import Scheduler
import importlib
import six##判断类型，six.xxtype
from scrapy.utils.misc import load_object
from . import connection, defaults
# TODO: add SCRAPY_JOB support.
class Scheduler(object):
"""Redis-based scheduler
Settings
--------
SCHEDULER_PERSIST : bool (default: False)
Whether to persist or clear redis queue.
SCHEDULER_FLUSH_ON_START : bool (default: False)
Whether to flush redis queue on start.
SCHEDULER_IDLE_BEFORE_CLOSE : int (default: 0)
How many seconds to wait before closing if no message is received.
SCHEDULER_QUEUE_KEY : str
Scheduler redis key.
SCHEDULER_QUEUE_CLASS : str
Scheduler queue class.
SCHEDULER_DUPEFILTER_KEY : str
Scheduler dupefilter redis key.
SCHEDULER_DUPEFILTER_CLASS : str
Scheduler dupefilter class.
SCHEDULER_SERIALIZER : str
Scheduler serializer.
"""
def __init__(self, server,
persist=False,
flush_on_start=False,
queue_key=defaults.SCHEDULER_QUEUE_KEY,
queue_cls=defaults.SCHEDULER_QUEUE_CLASS,
dupefilter_key=defaults.SCHEDULER_DUPEFILTER_KEY,
dupefilter_cls=defaults.SCHEDULER_DUPEFILTER_CLASS,
idle_before_close=0,
serializer=None):
"""Initialize scheduler.
Parameters
----------
server : Redis
The redis server instance.
persist : bool
Whether to flush requests when closing. Default is False.
flush_on_start : bool
Whether to flush requests on start. Default is False.
queue_key : str
Requests queue key.
queue_cls : str
Importable path to the queue class.
dupefilter_key : str
Duplicates filter key.
dupefilter_cls : str
Importable path to the dupefilter class.
idle_before_close : int
Timeout before giving up.
"""
if idle_before_close < 0:
raise TypeError("idle_before_close cannot be negative")
self.server = server
self.persist = persist
self.flush_on_start = flush_on_start
self.queue_key = queue_key
self.queue_cls = queue_cls
self.dupefilter_cls = dupefilter_cls
self.dupefilter_key = dupefilter_key
self.idle_before_close = idle_before_close
self.serializer = serializer
self.stats = None
def __len__(self):
return len(self.queue)
@classmethod
def from_settings(cls, settings):##settings是传过来的配置文件信息
kwargs = {
'persist': settings.getbool('SCHEDULER_PERSIST'),
'flush_on_start': settings.getbool('SCHEDULER_FLUSH_ON_START'),
'idle_before_close': settings.getint('SCHEDULER_IDLE_BEFORE_CLOSE'),
}
# If these values are missing, it means we want to use the defaults.
optional = {
# TODO: Use custom prefixes for this settings to note that are
# specific to scrapy-redis.
'queue_key': 'SCHEDULER_QUEUE_KEY',
'queue_cls': 'SCHEDULER_QUEUE_CLASS',
'dupefilter_key': 'SCHEDULER_DUPEFILTER_KEY',
# We use the default setting name to keep compatibility.
'dupefilter_cls': 'DUPEFILTER_CLASS',
'serializer': 'SCHEDULER_SERIALIZER',
}
##读取上面的配置文件，取settings里面找到相对应的值，拿到settings后面的结果
for name, setting_name in optional.items():
val = settings.get(setting_name)##匹配settings对应的值出来（自己配置的）
if val:
kwargs[name] = val
# Support serializer as a path to a module.
if isinstance(kwargs.get('serializer'), six.string_types):
kwargs['serializer'] = importlib.import_module(kwargs['serializer'])
server = connection.from_settings(settings)##取配置文件里面读取自己配置的连接相关的配置文件
# Ensure the connection is working.
server.ping()
return cls(server=server, **kwargs)##这里开始实例化scheduler对象，开始正式执行爬虫，cls就是当前的类
@classmethod
def from_crawler(cls, crawler):##当你执行调度器scrapy-redis的时候，就会传入settigs进来，配置信息是在crawler.settings
instance = cls.from_settings(crawler.settings)##crawlwe.settinsg拿到的是setting对象<scrapy.settings.Settings object at 0x00000265B2E41940>
'''可以调用里面的方法，通过crawler.settings.get("host")'''
# FIXME: for now, stats are only supported from this constructor
instance.stats = crawler.stats
return instance
def open(self, spider):
self.spider = spider
try:
self.queue = load_object(self.queue_cls)(
server=self.server,
spider=spider,
key=self.queue_key % {'spider': spider.name},
serializer=self.serializer,
)
except TypeError as e:
raise ValueError("Failed to instantiate queue class '%s': %s",
self.queue_cls, e)
try:
self.df = load_object(self.dupefilter_cls)(
server=self.server,
key=self.dupefilter_key % {'spider': spider.name},
debug=spider.settings.getbool('DUPEFILTER_DEBUG'),
)
except TypeError as e:
raise ValueError("Failed to instantiate dupefilter class '%s': %s",
self.dupefilter_cls, e)
if self.flush_on_start:
self.flush()
# notice if there are requests already in the queue to resume the crawl
if len(self.queue):
spider.log("Resuming crawl (%d requests scheduled)" % len(self.queue))
def close(self, reason):
if not self.persist:
self.flush()
def flush(self):
self.df.clear()
self.queue.clear()
##开始真正执行下面的爬虫部分了，上面的只是取读取配置信息
def enqueue_request(self, request):
if not request.dont_filter and self.df.request_seen(request):
#判断requets里面是否封装了dont_filter
##判断之前是否已经存在此爬虫
self.df.log(request, self.spider)
return False
##已经访问过不用在访问了,返回false
if self.stats:
##如果已经访问过的话
self.stats.inc_value('scheduler/enqueued/redis', spider=self.spider)
##如果未访问过的话，将这个requets对象，加进调度器里面，以便下载器调度使用
self.queue.push(request)
##其请求的调度其里面
return True##没有访问过的url，将他添加进调度器里面
def next_request(self):
block_pop_timeout = self.idle_before_close
request = self.queue.pop(block_pop_timeout)
if request and self.stats:
self.stats.inc_value('scheduler/dequeued/redis', spider=self.spider)
return request
def has_pending_requests(self):
return len(self) > 0
