class Engine(object):
def __init__(self):
self.spider = Spider()
self.scheduler = Scheduler()
self.pipeline = Pipeline()
self.downloader = Downloader()
def start(self):
"""启动整个引擎,主要调用逻辑代码写在_start_engine中"""
self._start_engine()
def _start_engine(self):
'''实现个业务之间对接'''
# 爬虫模块发出初始化请求
start_request = self.spider.start_request()
# 把初始化请求添加给调度器
self.scheduler.add_request(start_request)
# 从调度器获取请求对象
request = self.scheduler.get_request()
# 调用下载器发送请求
response = self.downloader.get_response(request)
# 调用爬虫处理响应方法,处理响应,得到结果
result = self.spider.parse(response)
if isinstance(result, Request):
self.scheduler.add_request(result)
else:
self.pipeline.process_item(result)
def __init__(self):
self.spider = Spider()
self.scheduler = Scheduler()
self.pipeline = Pipeline()
self.downloader = Downloader()
self.spider_mid = SpiderMiddleware() # 初始化爬虫中间件对象
self.downloader_mid = DownloaderMiddleware() # 初始化下载器中间件对象
class Engine():
def __init__(self):
self.spider = Spider()
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipeline = Pipeline()
self.spider_mid = SpiderMiddleware()
self.downloader_mid = DownloaderMiddleware()
def start(self):
# 被调用执行引擎逻辑的入口函数
self._start_engine()
def _start_engine(self):
# 框架运行的逻辑
# 1. 爬虫模块发出初始请求
start_request = self.spider.start_request()
# 利用爬虫中间件预处理请求对象
start_request = self.spider_mid.process_request(start_request)
# 2. 把初始请求添加给调度器
self.scheduler.add_request(start_request)
# 3. 从调度器获取请求对象
request = self.scheduler.get_request()
# 利用下载器中间件预处理请求对象
request = self.downloader_mid.process_request(request)
# 4. 利用下载器发起请求
response = self.downloader.get_response(request)
# 利用下载器中间件预处理响应对象
response = self.downloader_mid.process_response(response)
# 利用爬虫中间件预处理响应对象
response = self.spider_mid.process_response(response)
# 5. 利用爬虫的解析响应的方法，处理响应，得到结果
result = self.spider.parse(response)
# 6. 判断结果对象
if isinstance(result, Request):
# 利用爬虫中间件预处理请求对象
result = self.spider_mid.process_request(result)
# 6.1 如果是请求对象，那么就再交给调度器
self.scheduler.add_request(result)
else:
# 6.2 否则，就交给管道处理
self.pipeline.process_item(result)
def __init__(self):
self.spiders = self._auto_import_instances(path=SPIDERS, isspider=True)
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipelines = self._auto_import_instances(path=PIPELINES)
self.spider_mids = self._auto_import_instances(path=SPIDER_MIDDLEWARES)
self.downloader_mids = self._auto_import_instances(
path=DOWNLOADER_MIDDLEWARES)
self.total_response_nums = 0
self.total_request_nums = 0
def __init__(self, spiders):
self.spiders = spiders
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipeline = Pipeline()
self.spider_mid = SpiderMiddleware()
self.downloader_mid = DownloaderMiddleware()
self.total_response_nums = 0
self.total_request_nums = 0
def __init__(self):
self.spiders = self._auto_import_ret(path=SPIDERS, isspider=True)
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipelines = self._auto_import_ret(path=PIPELINES)
self.spider_mids = self._auto_import_ret(path=SPIDER_MIDDLEWARES)
self.downloader_mids = self._auto_import_ret(
path=DOWNLOADER_MIDDLEWARES)
self.total_request_nums = 0
self.total_response_nums = 0
self.pool = Pool(MAX_REQUEST_NUMS)
self.is_running = True
def __init__(self):
self.spiders = self.__auto_import(
settings.SPIDERS, is_spider=True) # 这里传递过来的是一个字典{爬虫名：爬虫对象}
# 创建统计器对象
self.stats_collector = StatsCollector()
# 把统计器对象传递给调度器
self.scheduler = Scheduler(self.stats_collector)
self.downloader = Downloader()
self.pipelines = self.__auto_import(settings.PIPELINES)
self.spider_middlewares = self.__auto_import(
settings.SPIDER_MIDDLEWARES)
self.downloader_middlewares = self.__auto_import(
settings.DOWNLOADER_MIDDLEWARES)
self.pool = Pool() # 创建线程池对象
# 定义变量，用于记录起始请求完成的爬虫数量
self.start_request_finished_spider_count = 0
def __init__(self):
self.spiders = self._auto_import_instances(path=SPIDERS,
isspider=True) # 爬虫字典
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipelines = self._auto_import_instances(path=PIPELINES)
self.spider_mids = self._auto_import_instances(path=SPIDER_MIDDLEWARES)
self.downloader_mids = self._auto_import_instances(
path=DOWNLOADER_MIDDLEWARES)
self.total_response_nums = 0
self.total_request_nums = 0
self.pool = Pool(5) # os.cpu_count() or 1
self.is_running = True
def __init__(self):
self.spiders = self._auto_import_instances(path=SPIDERS, isspider=True) # 爬虫字典
self.pipelines = self._auto_import_instances(path=PIPELINES)
self.spider_mids = self._auto_import_instances(path=SPIDER_MIDDLEWARES)
self.downloader_mids = self._auto_import_instances(path=DOWNLOADER_MIDDLEWARES)
if SCHEDULER_PERSIST:
self.collector = ReidsStatsCollector()
else:
self.collector = NormalStatsCollector()
# self.total_response_nums = 0
# self.total_request_nums = 0
self.scheduler = Scheduler(self.collector)
self.downloader = Downloader()
self.pool = Pool(5) # os.cpu_count() or 1
self.is_running = True
class Engine(object):
def __init__(self):
self.spider = Spider()
self.scheduler = Scheduler()
self.pipeline = Pipeline()
self.downloader = Downloader()
self.spider_mid = SpiderMiddleware() # 初始化爬虫中间件对象
self.downloader_mid = DownloaderMiddleware() # 初始化下载器中间件对象
def start(self):
"""启动整个引擎,主要调用逻辑代码写在_start_engine中"""
start = datetime.now() # 获取当前时间
logger.info('开始运行时间:%s' % start)
self._start_engine()
stop = datetime.now()
logger.info('运行结束时间:%s' % stop)
# 运行总耗时时间
logger.info('耗时: %.2f' % (stop - start).total_seconds())
def _start_engine(self):
'''实现个业务之间对接'''
# 爬虫模块发出初始化请求
start_request = self.spider.start_request()
# 爬虫中间件
start_request = self.spider_mid.process_request(start_request)
# 把初始化请求添加给调度器
self.scheduler.add_request(start_request)
# 从调度器获取请求对象
request = self.scheduler.get_request()
# 利用下载中间件预处理请求对象
request = self.downloader_mid.process_request(request)
# 调用下载器发送请求
response = self.downloader.get_response(request)
# 下载中间件预处理对象
response = self.downloader_mid.process_response(response)
# 调用爬虫处理响应方法,处理响应,得到结果
result = self.spider.parse(response)
if isinstance(result, Request):
result = self.spider_mid.process_request(result)
self.scheduler.add_request(result)
else:
self.pipeline.process_item(result)
class Engine():
def __init__(self):
self.spider = Spider()
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipeline = Pipeline()
self.spider_mid = SpiderMiddleware()
self.downloader_mid = DownloaderMiddleware()
def start(self):
# 被调用执行引擎逻辑的入口函数
start = datetime.now() # 起始时间
logger.info("开始运行时间：%s" % start) # 使用日志记录起始运行时间
self._start_engine()
stop = datetime.now() # 结束时间
logger.info("结束运行时间：%s" % stop) # 使用日志记录结束运行时间
logger.info("耗时：%.2f" % (stop - start).total_seconds()) # 使用日志记录运行耗时
def _start_engine(self):
# 框架运行的逻辑
# 1. 爬虫模块发出初始请求
start_request = self.spider.start_request()
# 利用爬虫中间件预处理请求对象
start_request = self.spider_mid.process_request(start_request)
# 2. 把初始请求添加给调度器
self.scheduler.add_request(start_request)
# 3. 从调度器获取请求对象
request = self.scheduler.get_request()
# 利用下载器中间件预处理请求对象
request = self.downloader_mid.process_request(request)
# 4. 利用下载器发起请求
response = self.downloader.get_response(request)
# 利用下载器中间件预处理响应对象
response = self.downloader_mid.process_response(response)
# 利用爬虫中间件预处理响应对象
response = self.spider_mid.process_response(response)
# 5. 利用爬虫的解析响应的方法，处理响应，得到结果
result = self.spider.parse(response)
# 6. 判断结果对象
if isinstance(result, Request):
# 利用爬虫中间件预处理请求对象
result = self.spider_mid.process_request(result)
# 6.1 如果是请求对象，那么就再交给调度器
self.scheduler.add_request(result)
else:
# 6.2 否则，就交给管道处理
self.pipeline.process_item(result)
class Engine():
def __init__(self):
self.spiders = self._auto_import_instances(path=SPIDERS,
isspider=True) # 爬虫字典
self.pipelines = self._auto_import_instances(path=PIPELINES)
self.spider_mids = self._auto_import_instances(path=SPIDER_MIDDLEWARES)
self.downloader_mids = self._auto_import_instances(
path=DOWNLOADER_MIDDLEWARES)
if SCHEDULER_PERSIST:
self.collector = ReidsStatsCollector()
else:
self.collector = NormalStatsCollector()
# self.total_response_nums = 0
# self.total_request_nums = 0
self.scheduler = Scheduler(self.collector)
self.downloader = Downloader()
self.pool = Pool(5) # os.cpu_count() or 1
self.is_running = True
def _auto_import_instances(self, path=[], isspider=False):
"""传入项目配置中爬虫,管道,中间件配置变量(list),返回爬虫字段 或 包含管道类中间件对象的list"""
results = {} if isspider else []
for p in path: # p == 'spiders.baidu.BaiduSpider' or 'pipelines.BaiduPipeline'
py_name_str = p.rsplit('.', 1)[0] # 'spiders.baidu' or 'pipelines'
cls_name_str = p.rsplit('.',
1)[1] # 'BaiduSpider' or 'BaiduPipeline'
# 动态导入py文件模块对象
# importlib.import_module(模块/py文件名字的字符串) == 模块/py文件对象
py_obj = importlib.import_module(py_name_str)
# getattr(模块/py文件对象, 类名称字符串) == 类对象 # 还没有实例化
cls_obj = getattr(py_obj, cls_name_str)
if isspider:
results[cls_obj.name] = cls_obj()
else:
results.append(cls_obj())
return results
def start(self):
# 框架启动的入口函数
start = datetime.now() # 起始时间
logger.info("开始运行时间：%s" % start) # 使用日志记录起始运行时间
self._start_engine()
stop = datetime.now() # 结束时间
logger.info("结束运行时间：%s" % stop) # 使用日志记录结束运行时间
logger.info("耗时：%.2f" % (stop - start).total_seconds()) # 使用日志记录运行耗时
logger.info("总的请求数量:{}".format(self.collector.request_nums))
logger.info("总的响应数量:{}".format(self.collector.response_nums))
logger.info("重复请求数量:{}".format(self.collector.repeat_request_nums))
self.collector.clear() # 清除计数统计!
def _start_requests(self):
"""专门处理所有爬虫起始url:构造request,加入队列"""
def func(spider_name, spider):
"""对一个爬虫的所有起始url构造request,并入队"""
# 1. 爬虫模块发出初始请求
for start_request in spider.start_requests():
# 给request添加spider_name属性
start_request.spider_name = spider_name
# 利用爬虫中间件预处理请求对象
for spider_mid in self.spider_mids:
start_request = spider_mid.process_request(
start_request, spider)
# 2. 把初始请求添加给调度器
self.scheduler.add_request(start_request)
# 总请求数 +1
# self.total_request_nums += 1
self.collector.incr(self.collector.request_nums_key)
for spider_name, spider in self.spiders.items():
# 异步的让每个爬虫的起始request入队
self.pool.apply_async(func, args=(spider_name, spider))
def _execute_request_response_item(self):
"""只处理一个请求对象:从队列取出一个request->response->item进管道/request入队"""
# 3. 从调度器获取请求对象，交给下载器发起请求，获取一个响应对象
request = self.scheduler.get_request()
if request is None: # 此时队列取空了
return # 提前终止函数
# 根据爬虫的名字来获取爬虫类对象 # 爬虫名字在请求对象进入队列之前已经赋值了!
spider = self.spiders[request.spider_name]
# 利用下载器中间件预处理请求对象
for downloader_mid in self.downloader_mids:
request = downloader_mid.process_request(request, spider)
# 4. 利用下载器发起请求
response = self.downloader.get_response(request)
# meta属性的传递!!!
response.meta = request.meta
# 利用下载器中间件预处理响应对象
for downloader_mid in self.downloader_mids:
response = downloader_mid.process_response(request, response,
spider)
# 利用爬虫中间件预处理响应对象
for spider_mid in self.spider_mids:
response = spider_mid.process_response(request, response, spider)
# 5. 利用爬虫的解析响应的方法，处理响应，得到结果
# 利用getattr函数和爬虫类中构造的request指定的解析函数名称字符串 获取指定解析函数对象
# func = getattr(类, 类中函数的字符串) # func还没有执行被调用
parse_func = getattr(spider, request.parse)
# 调用request.parse指定的解析函数
if request.parse == 'start_requests': # 防止爬虫中request.parse指定为start_requests函数
results = parse_func()
else:
results = parse_func(response) # 解析函数有可能返回可迭代对象或None
if results is None: # 如果解析函数返回None就提前return
# 总响应数 +1
# self.total_response_nums += 1
self.collector.incr(self.collector.response_nums_key)
return
for result in results:
# 6. 判断结果对象
if isinstance(result, Request):
# 给request添加spider_name属性
result.spider_name = request.spider_name
# 利用爬虫中间件预处理请求对象
for spider_mid in self.spider_mids:
result = spider_mid.process_request(result, spider)
# 6.1 如果是请求对象，那么就再交给调度器
self.scheduler.add_request(result)
# 总请求数 +1
# self.total_request_nums += 1
self.collector.incr(self.collector.request_nums_key)
else:
# 6.2 否则，就交给管道处理
for pipeline in self.pipelines:
result = pipeline.process_item(result, spider)
# 总响应数 +1
# self.total_response_nums += 1
self.collector.incr(self.collector.response_nums_key)
def _error_callback(self, exception):
try:
raise exception # 抛出异常后，才能被日志进行完整记录下来
except Exception as e:
logger.exception(e)
def _callback(self, xxx):
if self.is_running:
# print(self.total_response_nums, self.total_request_nums, self.scheduler.total_repeat_nums)
self.pool.apply_async(self._execute_request_response_item,
callback=self._callback,
error_callback=self._error_callback)
def _start_engine(self):
"""引擎执行的逻辑"""
self._start_requests() # 把所有起始url构造request入队
for i in range(MAX_ASYNC_THREAD_NUMBER):
# 不断 处理一个请求对象,直到该request处理完毕
self.pool.apply_async(self._execute_request_response_item,
callback=self._callback,
error_callback=self._error_callback)
while True: # 退出条件
time.sleep(0.01)
# 总响应数 + 重复的请求数 == 总请求数
if self.collector.response_nums + self.collector.repeat_request_nums == self.collector.request_nums:
self.is_running = False
# print(self.total_response_nums, self.total_request_nums, self.scheduler.total_repeat_nums)
break
class Engine():
def __init__(self):
self.spiders = self._auto_import_ret(path=SPIDERS, isspider=True)
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipelines = self._auto_import_ret(path=PIPELINES)
self.spider_mids = self._auto_import_ret(path=SPIDER_MIDDLEWARES)
self.downloader_mids = self._auto_import_ret(
path=DOWNLOADER_MIDDLEWARES)
self.total_request_nums = 0
self.total_response_nums = 0
self.pool = Pool(MAX_REQUEST_NUMS)
self.is_running = True
def _auto_import_ret(self, path=[], isspider=False):
"""利用动态导包的方式，自动根据配置获取爬虫字典或管道、中间件列表"""
ret = {} if isspider else []
for p in path: # 'spiders.baidu.BaiduSpider'
py_name_str = p.rsplit('.', 1)[0] # 'spiders.baidu'
cls_name_str = p.rsplit('.', 1)[1] # 'BaiduSpider'
# 利用importlib.import_module函数来根据执行位置.模块名字符串来获取模块对象
py_obj = importlib.import_module(py_name_str)
cls = getattr(py_obj, cls_name_str) #此时返回的是没有实例化的类对象！
if isspider:
ret[cls.name] = cls()
else:
ret.append(cls())
return ret
def start(self):
# 入口函数
start_time = datetime.datetime.now()
logger.info('开始的时间：{}'.format(start_time))
self._start_engine()
end_time = datetime.datetime.now()
logger.info('结束的时间：{}'.format(end_time))
logger.info('耗时：{}'.format(end_time - start_time))
logger.info('总请求数：{}'.format(self.total_request_nums))
logger.info('总响应数：{}'.format(self.total_response_nums))
logger.info('重复的请求数：{}'.format(self.scheduler.repeat_request_nums))
def _start_requests(self):
"""把爬虫的所有起始url全部构造成request，放入队列"""
# 1. 爬虫模块发出初始请求
for spider_name, spider in self.spiders.items():
for start_request in spider.start_requests():
# 给request添加爬虫名的属性
start_request.spider_name = spider_name
# 利用爬虫中间件预处理请求对象
for spider_mid in self.spider_mids:
start_request = spider_mid.process_request(
start_request, spider)
# 2. 把初始请求添加给调度器
self.scheduler.add_request(start_request)
# 总请求数 + 1
self.total_request_nums += 1
def execute_request_response_item(self):
"""把队列中取出的一个request进行处理，直到不再需要该request"""
# 3. 从调度器获取请求对象
request = self.scheduler.get_request()
if request is None:
return # 此时请求队列被取空
# 通过request携带的spider_name来按键取出爬虫类对象
spider = self.spiders[request.spider_name]
# 利用下载器中间件预处理请求对象
for downloader_mid in self.downloader_mids:
request = downloader_mid.process_request(request, spider)
# 4. 利用下载器发起请求
response = self.downloader.get_response(request)
# 传递meta!!!
response.meta = request.meta
# 利用下载器中间件预处理响应对象
for downloader_mid in self.downloader_mids:
response = downloader_mid.process_response(response, spider)
# 利用爬虫中间件预处理响应对象
for spider_mid in self.spider_mids:
response = spider_mid.process_response(response, spider)
# request.parse == 解析函数名字符串
# 函数 = getattr(类对象, 类的函数名字符串)
# 获取request在构造时指定的解析函数
parse_func = getattr(spider, request.parse)
# 5. 利用爬虫的解析响应的方法，处理响应，得到结果
results = parse_func(response)
for result in results:
# 6. 判断结果对象
if isinstance(result, Request):
# 给request添加爬虫名的属性
result.spider_name = request.spider_name
# result.spider_name = spider.name # 结果同上一行
# 利用爬虫中间件预处理请求对象
for spider_mid in self.spider_mids:
result = spider_mid.process_request(result, spider)
# 6.1 如果是请求对象，那么就再交给调度器
self.scheduler.add_request(result)
# 总请求数 + 1
self.total_request_nums += 1
else:
# 6.2 否则，就交给管道处理
for pipeline in self.pipelines:
result = pipeline.process_item(result, spider)
# 总响应数 + 1
self.total_response_nums += 1
def _callback(self, temp):
if self.is_running:
self.pool.apply_async(func=self.execute_request_response_item,
callback=self._callback)
def _start_engine(self):
# 调用其他组件的属性或函数来组织运行的逻辑
self._start_requests()
for i in range(MAX_REQUEST_NUMS): # 通过配置来控制并发规模
self.pool.apply_async(func=self.execute_request_response_item,
callback=self._callback)
while True:
# 程序退出的条件：总响应数 + 重复请求数 == 总请求数
if self.total_response_nums + self.scheduler.repeat_request_nums == self.total_request_nums:
self.is_running = False
break
class Engine():
def __init__(self):
self.spiders = self._auto_import_instances(path=SPIDERS, isspider=True)
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipelines = self._auto_import_instances(path=PIPELINES)
self.spider_mids = self._auto_import_instances(path=SPIDER_MIDDLEWARES)
self.downloader_mids = self._auto_import_instances(
path=DOWNLOADER_MIDDLEWARES)
self.total_response_nums = 0
self.total_request_nums = 0
def _auto_import_instances(self, path=[], isspider=False):
"""根据项目配置动态返回爬虫字典 或管道中间件列表"""
instances = {} if isspider else []
for p in path: # p = 'pipelines.BaiduPipeline'
py_name_str = p.rsplit('.', 1)[0] # 'spipelines'
cls_name_str = p.rsplit('.', 1)[1] # 'BaiduPipeline'
py_obj = importlib.import_module(py_name_str) # 获取py文件对象
cls_obj = getattr(py_obj, cls_name_str) # 获取py文件中的类对象,此时没有实例化!
if isspider:
instances[cls_obj.name] = cls_obj()
else:
instances.append(cls_obj())
return instances
def start(self):
# 被调用执行引擎逻辑的入口函数
start = datetime.now() # 起始时间
logger.info("开始运行时间：%s" % start) # 使用日志记录起始运行时间
self._start_engine()
stop = datetime.now() # 结束时间
logger.info("结束运行时间：%s" % stop) # 使用日志记录结束运行时间
logger.info("耗时：%.2f" % (stop - start).total_seconds()) # 使用日志记录运行耗时
logger.info("总的请求数量:{}".format(self.total_request_nums))
logger.info("总的响应数量:{}".format(self.total_response_nums))
def _start_requests(self):
"""把爬虫中所有起始的url构造request并添加到请求队列中"""
for spider_name, spider in self.spiders.items():
for start_request in spider.start_requests():
# 1. 爬虫模块发出初始请求
# 利用爬虫中间件预处理请求对象
for spider_mid in self.spider_mids:
start_request = spider_mid.process_request(
start_request, spider)
# 给request对象增加spider_name的属性
start_request.spider_name = spider_name
# 2. 把初始请求添加给调度器
self.scheduler.add_request(start_request)
# 总请求数 + 1
self.total_request_nums += 1
def _execute_request_response_item(self):
"""队列中取出一个request,直到处理完毕"""
# 3. 从调度器获取请求对象
request = self.scheduler.get_request()
# 判断队列是否取空
if request is None:
return # 提前终止
# 根据爬虫名获取爬虫类对象
spider = self.spiders[request.spider_name]
# 利用下载器中间件预处理请求对象
for downloader_mid in self.downloader_mids:
request = downloader_mid.process_request(request, spider)
# 4. 利用下载器发起请求
response = self.downloader.get_response(request)
# 传递meta
response.meta = request.meta
# 利用下载器中间件预处理响应对象
for downloader_mid in self.downloader_mids:
response = downloader_mid.process_response(request, response,
spider)
# 利用爬虫中间件预处理响应对象
for spider_mid in self.spider_mids:
response = spider_mid.process_response(request, response, spider)
# 5. 利用爬虫的解析响应的方法，处理响应，得到结果
# request.parse指定的解析函数 = getattr(爬虫类对象, 指定的解析函数的字符串)
parse_func = getattr(spider, request.parse)
results = parse_func(response)
for result in results:
# 6. 判断结果对象
if isinstance(result, Request):
# 利用爬虫中间件预处理请求对象
for spider_mid in self.spider_mids:
result = spider_mid.process_request(result, spider)
# 给request对象增加spider_name的属性
result.spider_name = request.spider_name
# 6.1 如果是请求对象，那么就再交给调度器
self.scheduler.add_request(result)
# 总请求数 + 1
self.total_request_nums += 1
else:
# 6.2 否则，就交给管道处理
for pipeline in self.pipelines:
result = pipeline.process_item(result, spider)
# 总响应数 +1
self.total_response_nums += 1
def _start_engine(self):
# 框架运行的逻辑
self._start_requests() # 把所有初始request放入队列
while True:
time.sleep(0.1)
self._execute_request_response_item() # 处理一个从队列中取出的request
# 程序退出的条件
if self.scheduler.q.empty():
break # 判断队列为空
class Engine():
def __init__(self, spiders):
self.spiders = spiders
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipeline = Pipeline()
self.spider_mid = SpiderMiddleware()
self.downloader_mid = DownloaderMiddleware()
self.total_response_nums = 0
self.total_request_nums = 0
def start(self):
# 被调用执行引擎逻辑的入口函数
start = datetime.now() # 起始时间
logger.info("开始运行时间：%s" % start) # 使用日志记录起始运行时间
self._start_engine()
stop = datetime.now() # 结束时间
logger.info("结束运行时间：%s" % stop) # 使用日志记录结束运行时间
logger.info("耗时：%.2f" % (stop - start).total_seconds()) # 使用日志记录运行耗时
logger.info("总的请求数量:{}".format(self.total_request_nums))
logger.info("总的响应数量:{}".format(self.total_response_nums))
def _start_requests(self):
"""把爬虫中所有起始的url构造request并添加到请求队列中"""
for spider_name, spider in self.spiders.items():
for start_request in spider.start_requests():
# 1. 爬虫模块发出初始请求
# 利用爬虫中间件预处理请求对象
start_request = self.spider_mid.process_request(start_request)
# 给request对象增加spider_name的属性
start_request.spider_name = spider_name
# 2. 把初始请求添加给调度器
self.scheduler.add_request(start_request)
# 总请求数 + 1
self.total_request_nums += 1
def _execute_request_response_item(self):
"""队列中取出一个request,直到处理完毕"""
# 3. 从调度器获取请求对象
request = self.scheduler.get_request()
# 判断队列是否取空
if request is None:
return # 提前终止
# 利用下载器中间件预处理请求对象
request = self.downloader_mid.process_request(request)
# 4. 利用下载器发起请求
response = self.downloader.get_response(request)
# 传递meta
response.meta = request.meta
# 利用下载器中间件预处理响应对象
response = self.downloader_mid.process_response(response)
# 利用爬虫中间件预处理响应对象
response = self.spider_mid.process_response(response)
# 根据爬虫名获取爬虫类对象
spider = self.spiders[request.spider_name]
# 5. 利用爬虫的解析响应的方法，处理响应，得到结果
# request.parse指定的解析函数 = getattr(爬虫类对象, 指定的解析函数的字符串)
parse_func = getattr(spider, request.parse)
results = parse_func(response)
for result in results:
# 6. 判断结果对象
if isinstance(result, Request):
# 利用爬虫中间件预处理请求对象
result = self.spider_mid.process_request(result)
# 给request对象增加spider_name的属性
result.spider_name = request.spider_name
# 6.1 如果是请求对象，那么就再交给调度器
self.scheduler.add_request(result)
# 总请求数 + 1
self.total_request_nums += 1
else:
# 6.2 否则，就交给管道处理
self.pipeline.process_item(result)
# 总响应数 +1
self.total_response_nums += 1
def _start_engine(self):
# 框架运行的逻辑
self._start_requests() # 把所有初始request放入队列
while True:
time.sleep(0.1)
self._execute_request_response_item() # 处理一个从队列中取出的request
# 程序退出的条件
if self.scheduler.q.empty():
break # 判断队列为空
def __init__(self):
self.spider = Spider()
self.scheduler = Scheduler()
self.downloader = Downloader()
self.pipeline = Pipeline()
class Engine(object):
"""
1.对其他模块进行初始化
2.启动引擎（实现引擎调用核心逻辑）
"""
def __init__(self):
self.spiders = self.__auto_import(
settings.SPIDERS, is_spider=True) # 这里传递过来的是一个字典{爬虫名：爬虫对象}
# 创建统计器对象
self.stats_collector = StatsCollector()
# 把统计器对象传递给调度器
self.scheduler = Scheduler(self.stats_collector)
self.downloader = Downloader()
self.pipelines = self.__auto_import(settings.PIPELINES)
self.spider_middlewares = self.__auto_import(
settings.SPIDER_MIDDLEWARES)
self.downloader_middlewares = self.__auto_import(
settings.DOWNLOADER_MIDDLEWARES)
self.pool = Pool() # 创建线程池对象
# 定义变量，用于记录起始请求完成的爬虫数量
self.start_request_finished_spider_count = 0
@staticmethod
def __auto_import(full_names, is_spider=False):
"""
动态导入:根据配置信息自动创建对象,封装成需要的格式返回
:param full_names: 配置全类名(路径)列表
:param is_spider: 判断是不是爬虫对象
:return: 配置类的对象列表或者字典
"""
# 如果是爬虫就是字典,否则是列表
instances = {} if is_spider else []
for full_name in full_names:
result = full_name.rsplit('.', maxsplit=1)
# 模块名
module_name = result[0]
# 类名
class_name = result[1]
# 根据模块名,导入模块,获取模块对象
module = importlib.import_module(module_name)
# 根据类名,从模块对象中获取类对象
cls = getattr(module, class_name)
# 使用类对象,创建实例对象
instance = cls()
# 如果是爬虫,存储到字典中,否则存到列表里
if is_spider:
instances[instance.name] = instance
else:
instances.append(instance)
return instances
def start(self):
"""启动引擎，对外提供接口"""
start = datetime.now()
logger.info("开始运行时间：%s" % start)
self.__start()
stop = datetime.now()
logger.info("运行结束时间：%s" % stop)
logger.info("耗时：%.2f秒" % (stop - start).total_seconds())
# 总起始请求数量
logger.info('总起始请求数量:%s' % self.stats_collector.start_request_nums)
# 记录总请求数量
logger.info('总请求数量：%s' % self.stats_collector.request_nums)
# 总过滤请求数量
logger.info('过滤掉的请求数量:%s' % self.stats_collector.repeat_request_nums)
# 总响应数量
logger.info('总响应处理数量：%s' % self.stats_collector.response_nums)
# 如果启用分布式，当前程序结束的时候，清空统计信息
if settings.SCHEDULER_PERSIST:
self.stats_collector.clear()
if not settings.FP_PERSIST:
# 如果不开启断点续爬，清空指纹和请求队列数据
self.scheduler.clear()
@staticmethod
def __error_callback(e):
"""错误回调函数"""
try:
raise e
except Exception as e:
logger.exception(e)
def __callback_execute(self, temp):
"""异步线程池回调函数"""
self.pool.apply_async(self.__execute_request_response_item,
callback=self.__callback_execute,
error_callback=self.__error_callback)
def __start(self):
"""私有启动引擎的方法，实现核心代码"""
# 添加起始请求到调度器中
# 异步执行__add_start_requests任务
self.pool.apply_async(self.__add_start_requests,
error_callback=self.__error_callback)
# 配置多少个异步任务，这个异步调用就执行多少次
for i in range(settings.ASYNC_COUNT):
# 异步执行__execute_request_response_item任务
self.pool.apply_async(self.__execute_request_response_item,
callback=self.__callback_execute,
error_callback=self.__error_callback)
# 让主线程等待一下，让上面的异步任务启动起来
time.sleep(1)
while True:
# 死循环进行轮询，非常消耗cpu性能，稍睡一下，降低消耗
time.sleep(0.1)
# 当所有爬虫的起始请求都执行完了才结束
if self.start_request_finished_spider_count >= len(self.spiders):
# 当所有请求都处理完成，要结束循环
if self.stats_collector.response_nums >= self.stats_collector.request_nums:
# 没有请求了，退出循环
break
def __execute_request_response_item(self):
"""处理请求、响应和数据方法"""
# 从调度器获取请求对象，交给下载器发起请求，获取一个响应对象
request = self.scheduler.get_request()
# 取出该请求对应爬虫对象，根据爬虫名去爬虫字典中取出爬虫对象
spider = self.spiders[request.spider_name]
# 遍历下载器中间件列表,获取每一个下载器中间件
for downloader_middleware in self.downloader_middlewares:
# 利用下载器中间件预处理请求对象
request = downloader_middleware.process_request(request)
# 利用下载器发起请求
response = self.downloader.get_response(request)
# 把请求的meta数据传递给response
response.meta = request.meta
# 利用下载器中间件预处理响应对象
# 遍历下载器中间件列表,获取每个下载器中间件
for downloader_middleware in self.downloader_middlewares:
response = downloader_middleware.process_response(response)
# 遍历爬虫中间件列表,获取每一个爬虫中间件
for spider_middleware in self.spider_middlewares:
# 调用爬虫中间件的process_response方法，处理响应
response = spider_middleware.process_response(response)
# 如果有该请求有对应解析函数callback，就使用callback来解析数据
if request.callback:
# 接收解析函数，处理结果
results = request.callback(response)
else:
# 如果没有callback就使用parse函数来解析数据
results = spider.parse(response)
# 判断results是不是可迭代对象，如果不可迭代，变为可迭代的
if not isinstance(results, Iterable):
results = [results]
for result in results:
# 判断结果对象
if isinstance(result, Request):
# 如果是请求对象，就再交给调度器
# 遍历爬虫中间件列表,获取每个爬虫中间件
for spider_middleware in self.spider_middlewares:
# 利用爬虫中间件预处理请求对象
result = spider_middleware.process_request(result)
# 设置请求对象对应的爬虫名
result.spider_name = spider.name
self.scheduler.add_request(result)
else:
# 否则，交给管道处理
for pipeline in self.pipelines:
result = pipeline.process_item(result, spider)
# 统计总的响应数量，每次递增1
self.stats_collector.incr(self.stats_collector.response_nums_key)
def __add_start_requests(self):
# 遍历爬虫字典，取出爬虫对象
for spider_name, spider in self.spiders.items():
# 异步执行起始请求任务，防止有增量爬虫启动后不停止而后面的爬虫不执行的问题
self.pool.apply_async(
self.__add_one_spider_start_requests,
args=(spider, spider_name),
error_callback=self.__error_callback,
callback=self.__add_one_spider_start_requests_callback)
def __add_one_spider_start_requests_callback(self, temp):
"""每调用一次，起始请求完成数+1"""
self.start_request_finished_spider_count += 1
def __add_one_spider_start_requests(self, spider, spider_name):
# 调用爬虫start_request方法，获取请求对象
for request in spider.start_request():
# 设置该请求对应的爬虫名
request.spider_name = spider_name
# 统计起始请求数量
self.stats_collector.incr(
self.stats_collector.start_request_nums_key)
# 利用爬虫中间件预处理请求对象
# 遍历爬虫中间件列表,获取每个爬虫中间件
for spider_middleware in self.spider_middlewares:
request = spider_middleware.process_request(request)
# 调用调度器的add_request把请求添加到调度器中
self.scheduler.add_request(request)
