[Python知识库]数据采集---高清壁纸

这个链接里面有很多热心网友贡献的链接,有哪些无版权、免费、高清图片素材网站？ - 知乎 需要素材就随便点开一个网站去找很方便，今天想用爬虫方式来抓取一下这些图片

确定目标网站：Fireworks Celebration Free Stock CC0 Photo - StockSnap.io

打开界面可以发现，在界面上有个下载按钮，直接点击下载就可以了，但是在很多网站上是没有下载按钮的，这个时候就需要我们另想办法了：

方案一：野生的request

右键检查会发现里边有个url，但是里边并不是高清大图的url地址，

通过抓包工具点击download按钮，会发现有个download的文件，在network工具中查看本次请求的url为Free Stock Photos and Images - StockSnap.io

首先直接用url去请求，试图获取网页源代码

import requests

def download_pic(url):
    resp = requests.post(url)
    print("状态码:", resp)

if __name__ == '__main__':
    url = r'https://stocksnap.io/photo/download'
    download_pic(url)

输出：

状态码: <Response [403]>

403状态码代表的含义：

状态码 403 Forbidden 代表客户端错误，指的是服务器端有能力处理该请求，但是拒绝授权访问。. 这个状态类似于 401 ，但进入该状态后不能再继续进行验证。. 该访问是长期禁止的，并且与应用逻辑密切相关（例如不正确的密码）。

显然不正确

于是尝试加上请求头

还是会返回403

再加上请求信息试试

依然会返回403

再加上cookie试试

import requests

def download_pic(url):
    headers = {
        "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36",
        "Cookie": "_csrf=pfQRFAJQyujrBcvmEYV-m918; _ga=GA1.2.1764522094.1637402941; _gid=GA1.2.1840794345.1637402941; _hjSessionUser_2571802=eyJpZCI6IjNlNzM2NDUyLTVkMGMtNTZjNC1iMDM4LWJmZjRjMDg3MmQyMSIsImNyZWF0ZWQiOjE2Mzc0MDI5NjAxOTgsImV4aXN0aW5nIjp0cnVlfQ==; photoViews=KB3VPMZBOX,LTYITHITMX; photoDownloads=KB3VPMZBOX,LTYITHITMX"
            }

    data = {
        "_csrf": "STITz8bf-5-SrqMqkg9jyJen_UkbW-zFznmg",
        "photoId": "LTYITHITMX"
    }

    resp = requests.post(url,headers=headers, data=data)
    print("状态码:", resp)


if __name__ == '__main__':
    url = r'https://stocksnap.io/photo/download'
    download_pic(url)

输出：这下OK了

状态码: <Response [200]>

接下来就是对图片内容的保存了

import requests

def download_pic(url):
    headers = {
        "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36",
        "Cookie": "_csrf=pfQRFAJQyujrBcvmEYV-m918; _ga=GA1.2.1764522094.1637402941; _gid=GA1.2.1840794345.1637402941; _hjSessionUser_2571802=eyJpZCI6IjNlNzM2NDUyLTVkMGMtNTZjNC1iMDM4LWJmZjRjMDg3MmQyMSIsImNyZWF0ZWQiOjE2Mzc0MDI5NjAxOTgsImV4aXN0aW5nIjp0cnVlfQ==; photoViews=KB3VPMZBOX,LTYITHITMX; photoDownloads=KB3VPMZBOX,LTYITHITMX"
            }

    data = {
        "_csrf": "STITz8bf-5-SrqMqkg9jyJen_UkbW-zFznmg",
        "photoId": "LTYITHITMX"
    }

    resp = requests.post(url,headers=headers, data=data)
    print("状态码:", resp)
    
    with open('1.jpg', mode='wb') as f:
        f.write(resp.content)


if __name__ == '__main__':
    url = r'https://stocksnap.io/photo/download'
    download_pic(url)

运行完成打开图片看看，确实是高清大图

在每次请求一个图片的时候都要进行cookie配置，会很麻烦，下面将用管理session的方式处理

方案二：进阶的request

在主页面刷新network工具查看请求的方式为get，于是通过get方式发送请求

import requests

def download_pic(url):

    headers = {
        "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36",
    }

    # data = {
    #     "_csrf": "STITz8bf-5-SrqMqkg9jyJen_UkbW-zFznmg",
    #     "photoId": "LTYITHITMX"
    # }
    session = requests.session()
    resp = session.get(url, headers=headers)
    print(resp)
    resp.encoding = "utf-8"
    print(resp.text)



if __name__ == '__main__':
    url = r'https://stocksnap.io/'

    download_pic(url)

输出内容太长

拿到网页源代码之后进行解析获取图片的url

获取到子页面后在子页面中寻找两个请求的参数

拿到两个请求参数就可以发起请求了

import requests
from lxml import etree
from urllib.parse import urljoin


def download_pic(url):

    headers = {
        "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36",
    }

    session = requests.session()
    resp = session.get(url, headers=headers)  # 获取主页面

    resp.encoding = "utf-8"
    source_page = resp.text
    tree = etree.HTML(source_page)
    hrefs = tree.xpath('//div[@id="main"]/div/a/@href')[1:]
    for href in hrefs[0:len(hrefs)-1]:
        # print(href)
        child_url = urljoin(url, href)
        child_resp = session.get(child_url)  # 获取到子页面的url
        child_resp.encoding = 'utf-8'

        child_page = child_resp.text   # 拿到子页面
        child_tree = etree.HTML(child_page)

        # 获取两个请求参数
        _csrf = child_tree.xpath('//form[@action="/photo/download"]/input[1]/@value')[0]
        photoId = child_tree.xpath('//form[@action="/photo/download"]/input[2]/@value')[0]

        # 图片名在保存图片的时候使用
        img_name = child_tree.xpath('//img[@itemprop="url"]/@src')[0].split('/')[-1]
        print(img_name)

        data = {
            "_csrf":_csrf,
            "photoId":photoId
        }


        download_url = r'https://stocksnap.io/photo/download'
        dwon_resp = session.post(download_url, data=data)     # 请求图片的地址
        
        with open(img_name, mode='wb') as f:
            f.write(dwon_resp.content)


if __name__ == '__main__':
    url = r'https://stocksnap.io/'

    download_pic(url)

运行之后会获得一批高清图片

这样就下载下来了，但是下载速度有点慢， 改进一下，使用异步协程进行下载

import aiohttp
import asyncio
import aiofiles
import requests
from lxml import etree
from urllib.parse import urljoin
import os

# 本地写入
async def save_one(name,data, href,session):
    # async with aiohttp.ClientSession() as session:
    async with session.post(href,data=data) as resp:
        img = await resp.read()
        async with aiofiles.open(os.path.join('save',name),mode='wb') as f:
            await f.write(img)



# 请求单个子页面，从子页面中 ，获取图片的请求数据
async def get_one_data(url):
    headers = {
        "user-agent": "Mozilla/5.0 (Windows; U; Windows NT 6.1; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
    }
    async with aiohttp.ClientSession() as session:
        async with session.get(url,headers=headers) as child_resp:
            child_page = await child_resp.text(encoding='utf-8', errors='ignore')
            child_tree = etree.HTML(child_page)

            # 获取两个请求参数
            _csrf = child_tree.xpath('//form[@action="/photo/download"]/input[1]/@value')[0]
            photoId = child_tree.xpath('//form[@action="/photo/download"]/input[2]/@value')[0]

            # 图片名在保存图片的时候使用
            img_name = child_tree.xpath('//img[@itemprop="url"]/@src')[0].split('/')[-1]
            print(img_name)

            data = {
                "_csrf": _csrf,
                "photoId": photoId
            }

            href = r"https://stocksnap.io/photo/download"
            await asyncio.create_task(save_one(img_name, data,href ,session))




# 从主页面中获取所有的子页面url
def get_urls(main_url):
    headers = {
        "user-agent": "Mozilla/5.0 (Windows; U; Windows NT 6.1; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
    }

    session = requests.session()
    resp = session.get(main_url, headers=headers)  # 获取主页面

    resp.encoding = "utf-8"
    source_page = resp.text
    tree = etree.HTML(source_page)
    hrefs = tree.xpath('//div[@id="main"]/div/a/@href')[1:]
    child_urls = []
    for href in hrefs[0:len(hrefs) - 1]:
        print(href)
        child_url = urljoin(main_url, href)

        child_urls.append(child_url)
    return child_urls



async def get_all_content_url(all_urls):
    tasks = []
    for url in all_urls:
        task = asyncio.create_task(get_one_data(url))
        tasks.append(task)
    await asyncio.wait(tasks)


if __name__ == '__main__':
    main_url = r'https://stocksnap.io/'
    all_urls = get_urls(main_url)
    asyncio.run(get_all_content_url(all_urls))

方案三：scrapy

在终端运行

scrapy startproject pic
cd pic
scrapy genspider imgs stocksnap.io

将img.py中pase中的参数加入**kwargs可以使pycharm不报黄色警告

将settings.py中设置警告类型为LOG_LEVEL = "WARNING",并将robots协议设置为False

修改imgs.py并在终端运行scrapy crawl imgs运行以查看能够成功请求到数据

返回

<200 https://stocksnap.io/>

说明可以获取到网页源代码,接下来就是对网页源代码进行解析了

解析部分正在imgs.py中,其中pase函数是对主页面进行解析，返回一个request对象给子页面，子页面得到后通过parse_child函数进行解析，获取图片的高清大图地址，图片名，请求参数等信息

img.py

import scrapy
from scrapy.http import HtmlResponse

from pic.items import PicItem
class ImgsSpider(scrapy.Spider):
    name = 'imgs'
    allowed_domains = ['stocksnap.io']
    start_urls = ['http://stocksnap.io']

    def parse(self, response:HtmlResponse, **kwargs):

        hrefs = response.xpath('//div[@id="main"]/div/a/@href').extract()

        for href in hrefs[0:len(hrefs) - 1]:

            child_url = response.urljoin(href)
            print(child_url)

            yield scrapy.Request(
                url=child_url,
                method = 'get',
                callback=self.parse_child,
            )
            # break


    def parse_child(self, resp, **kwargs):
        # print('子页面：', resp)

        _csrf = resp.xpath('//form[@action="/photo/download"]/input[1]/@value').extract_first()
        photoId = resp.xpath('//form[@action="/photo/download"]/input[2]/@value').extract_first()
        # print("_csrf", _csrf)
        # print("photoId", photoId)
        # 图片名在保存图片的时候使用
        img_name = resp.xpath('//img[@itemprop="url"]/@src').extract_first().split('/')[-1]
        # print('img_name:',img_name)
        download_url = r'https://stocksnap.io/photo/download'

        item = PicItem()
        item['_csrf']= _csrf
        item["photoId"] = photoId
        item["img_name"]= img_name
        item['src'] = download_url

        yield item

因为在返回中指定了标准格式的字典，因此在items.py中需要设置与之对应的Field

items.py

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

import scrapy


class PicItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    _csrf = scrapy.Field()
    photoId = scrapy.Field()
    img_name = scrapy.Field()
    src = scrapy.Field()

两个文件是相互对应的

配置好img.py后，进到pipelines.py中进行配置,配置如下，其中get_media_requests函数指定一个请求对象，file_path函数指定图片的保存路径

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
from scrapy.pipelines.images import ImagesPipeline
from pic import settings
import scrapy
import json
import os

class PicPipeline(ImagesPipeline):

    def get_media_requests(self, item, info):
        src = item['src']
        data = {
            "_csrf":item["_csrf"],
            "photoId":item["photoId"]
        }

        yield scrapy.FormRequest(url=src, formdata=data,meta={"item": item})
    def file_path(self, request, response=None, info=None, *, item=None):
        item = request.meta['item']
        img_name = item['img_name']
        return os.path.join('save1',img_name)

接下来是队settings.py的设置，其中ITEM_PIPELINES会指定管道的执行顺序

# Scrapy settings for pic 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

BOT_NAME = 'pic'

SPIDER_MODULES = ['pic.spiders']
NEWSPIDER_MODULE = 'pic.spiders'

LOG_LEVEL = "WARNING"
# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'pic (+http://www.yourdomain.com)'

# Obey robots.txt rules
ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
#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
#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)
#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',
#}

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

# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'pic.middlewares.PicDownloaderMiddleware': 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 = {
   'pic.pipelines.PicPipeline': 300,
}

# 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'

IMAGES_STORE = './down_imgs'

所有文件都配置完成之后就可以下载了,终端运行

scrapy crawl imgs

图片很快就下载完成了

?