scrapy-redis(调度器Scheduler源码分析)

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