Scrapy使用和学习笔记

前言

Scrapy是非常优秀的一个爬虫框架，基于twisted异步编程框架。yield的使用如此美妙。基于调度器，下载器可以对scrapy扩展编程。插件也是非常丰富，和Selenium，PlayWright集成也比较轻松。

当然，对网页中的ajax请求它是无能无力的，但结合mitmproxy几乎无所不能：Scrapy + PlayWright模拟用户点击，mitmproxy则在后台抓包取数据，登录一次，运行一天。

最终，我通过asyncio把这几个工具整合到了一起，基本达成了自动化无人值守的稳定运行，一篇篇的文章送入我的ElasticSearch集群，经过知识工厂流水线，变成知识商品。

”爬虫+数据，算法+智能“，这是一个技术人的理想。

配置与运行

安装:

pip install scrapy

当前目录下有scrapy.cfg和settings.py，即可运行scrapy

命令行运行：

scrapy crawl ArticleSpider

在程序中运行有三种写法：

from scrapy.cmdline import execute

execute('scrapy crawl ArticleSpider'.split())

采用CrawlerRunner:

# 采用CrawlerRunn服务器托管网er
from twisted.internet.asyncioreactor import AsyncioSelectorReactor
reactor = AsyncioSelectorReactor()

runner = CrawlerRunner(settings)
runner.crawl(ArticleSpider)
reactor.run()

采用CrawlerProcess

# 采用CrawlerProcess
process = CrawlerProcess(settings)
process.crawl(ArticleSpider)
process.start()

和PlayWright的集成

使用PlayWright的一大好处就是用headless browser做自动化数据采集。A headless browser 是一种特殊的Web浏览器，它为自动化提供API。通过安装 asyncio reactor ，则可以集成 asyncio 基础库，用于处理无头浏览器。

import scrapy
from playwright.async_api import async_playwright

class PlaywrightSpider(scrapy.Spider):
    name = "playwright"
    start_urls = ["data:,"]  # avoid using the default Scrapy downloader

    async def parse(self, response):
        async with async_playwright() as pw:
            browser = await pw.chromium.launch()
            page = await browser.new_page()
            await page.goto("https:/example.org")
            title = await page.title()
            return {"title": title}

使用 playwright-python 与上面的示例一样，直接绕过了大多数scrapy组件(中间件、dupefilter等)。建议使用 scrapy-playwright 进行整合。

安装

pip install scrapy-playwright
playwright install
playwright install firefox chromium

settings.py配置

BOT_NAME = 'ispider'

SPIDER_MODULES = ['ispider.spider']

TWISTED_REACTOR = 'twisted.internet.asyncioreactor.AsyncioSelectorReactor'
DOWNLOAD_HANDLERS = {
    "https": "scrapy_playwright.handler.ScrapyPlaywrightDownloadHandler",
    "http": "scrapy_playwright.handler.ScrapyPlaywrightDownloadHandler",
}

CONCURRENT_REQUESTS = 32
PLAYWRIGHT_MAX_PAGES_PER_CONTEXT = 4
CLOSESPIDER_ITEMCOUNT = 100

PLAYWRIGHT_CDP_URL = "http://localhost:9900"

爬虫定义

class ArticleSpider(Spider):

    name = "ArticleSpider"
    custom_settings = {
        # "TWISTED_REACTOR": "twisted.internet.asyncioreactor.AsyncioSelectorReactor",
        # "DOWNLOAD_HANDLERS": {
        #     "https": "scrapy_playwright.handler.ScrapyPlaywrightDownloadHandler",
        #     "http": "scrapy_playwright.handler.ScrapyPlaywrightDownloadHandler",
        # },
        # "CONCURRENT_REQUESTS": 32,
        # "PLAYWRIGHT_MAX_PAGES_PER_CONTEXT": 4,
        # "CLOSESPIDER_ITEMCOUNT": 100,

    }
    start_urls = ["https://blog.csdn.net/nav/lang/javascript"]

    def __init__(self, name=None, **kwargs):
        super().__init__(name, **kwargs)
        logger.debug('ArticleSpider initialized.')

    def start_requests(self):
        for url in self.start_urls:
            yield Request(
                url,
                meta={
                    "playwright": True,
                    "playwright_context": "first",
                    "playwright_include_page": True,
                    "playwright_page_goto_kwargs": {
                        "wait_until": "domcontentloaded",
                    },
                },
            )


    async def parse(self, response: Response, current_page: Optional[int] = None) -> Generator:
        content = response.text
        p服务器托管网age = response.meta["playwright_page"]
        context = page.context
        title = await page.title()
        while True:
            ## 垂直滚动下拉，不断刷新数据
            page.mouse.wheel(delta_x=0, delta_y=200)
            time.sleep(3)

        pass

参考链接

• scrapy文档
• 官方scrapy-playwright插件
• 崔庆才丨静觅写的插件GerapyPlaywright

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