PyCharm搭建Scrapy环境

1、Scrapy概述

Scrapy是一个由Python语言开发的适用爬取网站数据、提取结构性数据的Web应用程序框架。主要用于数据挖掘、信息处理、数据存储和自动化测试等。通过Scrapy框架实现一个爬虫，只需要少量的代码，就能够快速的网络抓取

Scrapy框架5大组件（架构）：

• Scrapy引擎(Scrapy Engine)：Scrapy引擎是整个框架的核心，负责Spider、ItemPipeline、Downloader、Scheduler间的通讯、数据传递等
• 调度器(Scheduler)：网页URL的优先队列，主要负责处理引擎发送的请求，并按一定方式排列调度，当引擎需要时，交还给引擎
• 下载器(Downloader)：负责下载引擎发送的所有Requests请求资源，并将其获取到的Responses交还给引擎，由引擎交给Spider来处理
• 爬虫(Spider)：用户定制的爬虫，用于从特定网页中提取信息(实体Item)，负责处理所有Responses，从中提取数据，并将需要跟进的URL提交给引擎，再次进入调度器
• 实体管道(Item Pipeline)：用于处理Spider中获取的实体，并进行后期处理（详细分析、过滤、持久化存储等）

其他组件：

• 下载中间件(Downloader Middlewares)：一个可以自定义扩展下载功能的组件
• Spider中间件(Spider Middlewares)：一个可以自定扩展和操作引擎和Spider间通信的组件

官方文档：https://docs.scrapy.org

入门文档：https://doc.scrapy.org/en/latest/intro/tutorial.html

2、PyCharm搭建Scrapy环境

1）新建一个爬虫项目ScrapyDemo

2）在Terminal终端安装所需模块

Scrapy基于Twisted，Twisted是一个异步网络框架，主要用于提高爬虫的下载速度

pip install scrapy
pip install twisted

如果报错：

ERROR: Failed building wheel for twisted
error: Microsoft Visual C++ 14.0 or greater is required

则需要下载对应的whl文件安装：

Python扩展包whl文件下载：https://www.lfd.uci.edu/~gohlke/pythonlibs/#

ctrl+f查找需要的whl文件，点击下载对应版本

安装：

pip install whl文件绝对路径

例如：

pip install F:\PyWhl\Twisted-20.3.0-cp38-cp38m-win_amd64.whl

3）在Terminal终端创建爬虫项目ScrapyDemo

scrapy startproject ScrapyDemo

生成项目目录结构

4）在spiders文件夹下创建核心爬虫文件SpiderDemo.py

最终项目结构及说明：

ScrapyDemo/                              爬虫项目
    ├── ScrapyDemo/                      爬虫项目目录    
    │      ├── spiders/                  爬虫文件
    │      │      ├── __init__.py   
    │      │      └── SpiderDemo.py      自定义核心功能文件
    │      ├── __init__.py   
    │      ├── items.py                  爬虫目标数据
    │      ├── middlewares.py            中间件、代理  
    │      ├── pipelines.py              管道，用于处理爬取的数据    
    │      └── settings.py               爬虫配置文件
    └── scrapy.cfg                       项目配置文件

3、Scrapy使用四部曲

1）明确目标

明确爬虫的目标网站

明确需要爬取实体（属性）：items.py

定义：属性名 = scrapy.Field()

2）制作爬虫

自定义爬虫核心功能文件：spiders/SpiderDemo.py

3）存储数据

设计管道存储爬取内容：settings.py、pipelines.py

4）运行爬虫

方式1：在Terminal终端执行（cmd执行需要切到项目根目录下）

scrapy crawl dangdang(爬虫名)

cmd切换操作：

切盘：F:
切换目录：cd A/B/...

方式2：在PyCharm执行文件

在爬虫项目目录下创建运行文件run.py，右键运行

4、Scrapy入门案例

4.1、明确目标

1）爬取当当网手机信息：https://category.dangdang.com/cid4004279.html

2）明确需要爬取实体属性：items.py

# Define here the models for your scraped items
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/items.html

import scrapy

# 1）明确目标
# 1.2）明确需要爬取实体属性
class ScrapyDemoItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    # 名称
    name = scrapy.Field()
    # 价格
    price = scrapy.Field()

4.2、制作爬虫

SpiderDemo.py

# 入门案例

# 1）明确目标
# 1.1）爬取当当网手机信息：https://category.dangdang.com/cid4004279.html

# 2）制作爬虫
import scrapy
from scrapy.http import Response
from ..items import ScrapyDemoItem

class SpiderDemo(scrapy.Spider):
    # 爬虫名称，运行爬虫时使用的值
    name = "dangdang"
    # 爬虫域，允许访问的域名
    allowed_domains = ['category.dangdang.com']
    # 爬虫地址：起始URL：第一次访问是域名
    start_urls = ['https://category.dangdang.com/cid4004279.html']
    # 翻页分析
    # 第1页：https://category.dangdang.com/cid4004279.html
    # 第2页：https://category.dangdang.com/pg2-cid4004279.html
    # 第3页：https://category.dangdang.com/pg3-cid4004279.html
    # ......
    page = 1

    # 请求响应处理
    def parse(self, response: Response):
        li_list = response.xpath('//ul[@id="component_47"]/li')
        for li in li_list:
            # 商品名称
            name = li.xpath('.//img/@alt').extract_first()
            print(name)
            # 商品价格
            price = li.xpath('.//p[@class="price"]/span[1]/text()').extract_first()
            print(price)
            # 获取一个实体对象就交给管道pipelines
            demo = ScrapyDemoItem(name=name, price=price)
            # 封装item数据后，调用yield将控制权给管道，管道拿到item后返回该程序
            yield demo
        # 每一页爬取逻辑相同，只需要将执行下一页的请求再次调用parse()方法即可
        if self.page <= 10:
            self.page += 1
            url = rf"https://category.dangdang.com/pg{str(self.page)}-cid4004279.html"
            # scrapy.Request为scrapy的请求
            # yield中断
            yield scrapy.Request(url=url, callback=self.parse)

补充：Response对象的属性和方法

'''
1）获取响应的字符串
response.text
2）获取响应的二进制数据
response.body
3）解析响应内容
response.xpath()
'''

4.3、存储数据

settings.py

# Scrapy settings for ScrapyDemo project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     https://docs.scrapy.org/en/latest/topics/settings.html
#     https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#     https://docs.scrapy.org/en/latest/topics/spider-middleware.html

# 3）存储数据
# 3.1）爬虫配置、打开通道和添加通道

# 爬虫项目名
BOT_NAME = "ScrapyDemo"

SPIDER_MODULES = ["ScrapyDemo.spiders"]
NEWSPIDER_MODULE = "ScrapyDemo.spiders"

# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = "ScrapyDemo (+http://www.yourdomain.com)"
# User-Agent配置
USER_AGENT = 'Mozilla/5.0'

# Obey robots.txt rules
# 是否遵循机器人协议（默认True），为了避免一些爬取限制需要改为False
ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 最大并发数
#CONCURRENT_REQUESTS = 32

# Configure a delay for requests for the same website (default: 0)
# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# 下载延迟（单位：s），用于控制爬取的频率
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16

# Disable cookies (enabled by default)
# 是否保存Cookies（默认False）
#COOKIES_ENABLED = False

# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False

# Override the default request headers:
#DEFAULT_REQUEST_HEADERS = {
#    "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
#    "Accept-Language": "en",
#}
# 请求头
DEFAULT_REQUEST_HEADERS = {
   "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
   "Accept-Language": "en",
}

# Enable or disable spider middlewares
# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
#    "ScrapyDemo.middlewares.ScrapydemoSpiderMiddleware": 543,
#}

# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    "ScrapyDemo.middlewares.ScrapydemoDownloaderMiddleware": 543,
#}

# Enable or disable extensions
# See https://docs.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    "scrapy.extensions.telnet.TelnetConsole": None,
#}

# Configure item pipelines
# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
#ITEM_PIPELINES = {
#    "ScrapyDemo.pipelines.ScrapydemoPipeline": 300,
#}

# 项目管道
ITEM_PIPELINES = {
    # 管道可以有多个，后面的数字是优先级（范围：1-1000），值越小优先级越高
    # 爬取网页
    'scrapy_dangdang.pipelines.ScrapyDemoPipeline': 300,
    # 保存数据
    'scrapy_dangdang.pipelines.ScrapyDemoSinkPiepline': 301,
}

# Enable and configure the AutoThrottle extension (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False

# Enable and configure HTTP caching (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = "httpcache"
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = "scrapy.extensions.httpcache.FilesystemCacheStorage"

# Set settings whose default value is deprecated to a future-proof value
REQUEST_FINGERPRINTER_IMPLEMENTATION = "2.7"
TWISTED_REACTOR = "twisted.internet.asyncioreactor.AsyncioSelectorReactor"
FEED_EXPORT_ENCODING = "utf-8"

# 设置日志输出等级（默认DEBUG）与日志存放的路径
LOG_LEVEL = 'INFO'
# LOG_FILE = "spider.log"

pipelines.py

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html

# useful for handling different item types with a single interface
from itemadapter import ItemAdapter

# 3）存储数据
# 3.2）使用管道存储数据
# 若使用管道，则必须在settings.py中开启管道

import os
import csv

# 爬取网页
class ScrapyDemoPipeline:

    # 数据item交给管道输出
    def process_item(self, item, spider):
        print(item)
        return item

# 保存数据
class ScrapyDemoSinkPiepline:

    # item为yield后面的ScrapyDemoItem对象，字典类型
    def process_item(self, item, spider):
        with open(r'C:\Users\cc\Desktop\scrapy_test.csv', 'a', newline='', encoding='utf-8') as csvfile:
            # 定义表头
            fields = ['name', 'price']
            writer = csv.DictWriter(csvfile, fieldnames=fields)
            writer.writeheader()
            # 写入数据
            writer.writerow(item)

4.4、运行爬虫

run.py

# 4）运行爬虫

from scrapy import cmdline

cmdline.execute('scrapy crawl dangdang'.split())

其他文件不动，本案例运行会报错：

ERROR: Twisted-20.3.0-cp38-cp38m-win_amd64.whl is not a supported wheel on this platform
builtins.ModuleNotFoundError: No module named 'scrapy_dangdang'

原因大概是Twisted版本兼容问题，暂未解决，后续补充