Python.Scrapy.11-scrapy-source-code-analysis-part-1
Scrapy 源代码分析系列-1 spider, spidermanager, crawler, cmdline, command
分析的源代码版本是0.24.6, url: https://github.com/DiamondStudio/scrapy/blob/0.24.6
如github 中Scrapy 源码树所示,包含的子包有:
commands, contracts, contrib, contrib_exp, core, http, selector, settings, templates, tests, utils, xlib
包含的模块有:
_monkeypatches.py, cmdline.py, conf.py, conftest.py, crawler.py, dupefilter.py, exceptions.py,
extension.py, interface.py, item.py, link.py, linkextractor.py, log.py, logformatter.py, mail.py,
middleware.py, project.py, resolver.py, responsetypes.py, shell.py, signalmanager.py, signals.py,
spider.py, spidermanager.py, squeue.py, stats.py, statscol.py, telnet.py, webservice.py
先从重要的模块进行分析。
0. scrapy依赖的第三方库或者框架
twisted
1. 模块: spider, spidermanager, crawler, cmdline, command
1.1 spider.py spidermanager.py crawler.py
spider.py定义了spider的基类: BaseSpider. 每个spider实例只能有一个crawler属性。那么crawler具备哪些功能呢?
crawler.py定义了类Crawler,CrawlerProcess。
类Crawler依赖: SignalManager, ExtensionManager, ExecutionEngine, 以及设置项STATS_CLASS、SPIDER_MANAGER_CLASS
、LOG_FORMATTER
类CrawlerProcess: 顺序地在一个进程中运行多个Crawler。依赖: twisted.internet.reactor、twisted.internet.defer。
启动爬行(Crawlering)。该类在1.2中cmdline.py会涉及。
spidermanager.py定义类SpiderManager, 类SpiderManager用来创建和管理所有website-specific的spider。
class SpiderManager(object): implements(ISpiderManager) def __init__(self, spider_modules):
self.spider_modules = spider_modules
self._spiders = {}
for name in self.spider_modules:
for module in walk_modules(name):
self._load_spiders(module) def _load_spiders(self, module):
for spcls in iter_spider_classes(module):
self._spiders[spcls.name] = spcls
1.2 cmdline.py command.py
cmdline.py定义了公有函数: execute(argv=None, settings=None)。
函数execute是工具scrapy的入口方法(entry method),如下所示:
XiaoKL$ cat `which scrapy`
#!/usr/bin/python # -*- coding: utf-8 -*-
import re
import sys from scrapy.cmdline import execute if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
sys.exit(execute())
所以可以根据这个点为切入点进行scrapy源码的分析。下面是execute()函数:
def execute(argv=None, settings=None):
if argv is None:
argv = sys.argv # --- backwards compatibility for scrapy.conf.settings singleton ---
if settings is None and 'scrapy.conf' in sys.modules:
from scrapy import conf
if hasattr(conf, 'settings'):
settings = conf.settings
# ------------------------------------------------------------------ if settings is None:
settings = get_project_settings()
check_deprecated_settings(settings) # --- backwards compatibility for scrapy.conf.settings singleton ---
import warnings
from scrapy.exceptions import ScrapyDeprecationWarning
with warnings.catch_warnings():
warnings.simplefilter("ignore", ScrapyDeprecationWarning)
from scrapy import conf
conf.settings = settings
# ------------------------------------------------------------------ inproject = inside_project()
cmds = _get_commands_dict(settings, inproject)
cmdname = _pop_command_name(argv)
parser = optparse.OptionParser(formatter=optparse.TitledHelpFormatter(), \
conflict_handler='resolve')
if not cmdname:
_print_commands(settings, inproject)
sys.exit(0)
elif cmdname not in cmds:
_print_unknown_command(settings, cmdname, inproject)
sys.exit(2) cmd = cmds[cmdname]
parser.usage = "scrapy %s %s" % (cmdname, cmd.syntax())
parser.description = cmd.long_desc()
settings.setdict(cmd.default_settings, priority='command')
cmd.settings = settings
cmd.add_options(parser)
opts, args = parser.parse_args(args=argv[1:])
_run_print_help(parser, cmd.process_options, args, opts) cmd.crawler_process = CrawlerProcess(settings)
_run_print_help(parser, _run_command, cmd, args, opts)
sys.exit(cmd.exitcode)
execute()函数主要做: 对命令行进行解析并对scrapy命令模块进行加载;解析命令行参数;获取设置信息;创建CrawlerProcess对象。
CrawlerProcess对象、设置信息、命令行参数都赋值给ScrapyCommand(或其子类)的对象。
自然我们需要来查看定义类ScrapyCommand的模块: command.py。
ScrapyCommand的子类在子包scrapy.commands中进行定义。
_run_print_help() 函数最终调用cmd.run(),来执行该命令。如下:
def _run_print_help(parser, func, *a, **kw):
try:
func(*a, **kw)
except UsageError as e:
if str(e):
parser.error(str(e))
if e.print_help:
parser.print_help()
sys.exit(2)
func是参数_run_command,该函数的实现主要就是调用cmd.run()方法:
def _run_command(cmd, args, opts):
if opts.profile or opts.lsprof:
_run_command_profiled(cmd, args, opts)
else:
cmd.run(args, opts)
我们在进行设计时可以参考这个cmdline/commands无关的设计。
command.py: 定义类ScrapyCommand,该类作为Scrapy Commands的基类。来简单看一下类ScrapyCommand提供的接口/方法:
class ScrapyCommand(object): requires_project = False
crawler_process = None # default settings to be used for this command instead of global defaults
default_settings = {} exitcode = 0 def __init__(self):
self.settings = None # set in scrapy.cmdline def set_crawler(self, crawler):
assert not hasattr(self, '_crawler'), "crawler already set"
self._crawler = crawler @property
def crawler(self):
warnings.warn("Command's default `crawler` is deprecated and will be removed. "
"Use `create_crawler` method to instatiate crawlers.",
ScrapyDeprecationWarning) if not hasattr(self, '_crawler'):
crawler = self.crawler_process.create_crawler() old_start = crawler.start
self.crawler_process.started = False def wrapped_start():
if self.crawler_process.started:
old_start()
else:
self.crawler_process.started = True
self.crawler_process.start() crawler.start = wrapped_start self.set_crawler(crawler) return self._crawler def syntax(self): def short_desc(self): def long_desc(self): def help(self): def add_options(self, parser): def process_options(self, args, opts): def run(self, args, opts):
类ScrapyCommand的类属性:
requires_project: 是否需要在Scrapy project中运行
crawler_process:CrawlerProcess对象。在cmdline.py的execute()函数中进行设置。
类ScrapyCommand的方法,重点关注:
def crawler(self): 延迟创建Crawler对象。
def run(self, args, opts): 需要子类进行覆盖实现。
那么我们来具体看一个ScrapyCommand的子类(参考 Python.Scrapy.14-scrapy-source-code-analysis-part-4)。
To Be Continued:
接下来分析模块: signals.py signalmanager.py project.py conf.py Python.Scrapy.12-scrapy-source-code-analysis-part-2
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