Python Crawl Pictures of Girls and Save Them Locally

Python Crawl Pictures of Girls and Save Them Locally

As an introductory tutorial for Python crawlers, I think it is necessary to come to a crawler program to crawl, take pictures of sexy beauties, and save them to your computer. Cool and crooked ~

As an introductory tutorial for Python crawlers, I think it is necessary to come to a crawler program to crawl, take pictures of sexy beauties, and save them to your computer. Cool and crooked ~

First look at the effect, this is the folder where I automatically stored the crawled pictures:

The crawler has three steps: crawl , analyze , and store .

1. Crawl

First of all, we have to have a goal, right. If we want to capture photos of beautiful women, we will look for the website where there are many papers, so let's start from there.

I found that the girl paper map of this website http://www.meizitu.com is pretty good, what are you waiting for, grabbing chant.

There is a module called requests in python, which can be directly pip install, and then visit this URL to get the corresponding source code:

response = requests.get(url)
return response

For example, I want to get the source code of sexy beauties, then my url is https://www.meizitu.com/a/sexy_1.html. We can get the returned response body through the get request, and we can use response.text Or source code.

2. Analysis

After crawling, we have to analyze the content we are interested in. At this time, it involves "regular expressions". According to some rules we define, we get the content we want.

Of course, we are now interested in returning the beauty pictures in the source code. You can see from the returned source code that the beauty pictures are wrapped in the img tag.

Then we can use the re module to match and get the image link we want:

p = r'<img src="([^"]+\.jpg)"'

img_addrs = re.findall(p, html)
3. Storage

Now that the image link is obtained, it can be stored next. Here, temporarily store it on your local computer:

with open(filename,'wb') as f:
    img = url_open(each).content
    f.write(img)

Ok, that's it, isn't it easy? Of course, the reptile is simple and simple, and complex and complicated. The key is to see what you want to do. If you find out from this example that you have a little more interest in python, you may wish to pay more attention to it. Some python crawlers need knowledge points, such as other crawler modules such as Scrapy, some form request parameters, anti-crawlers, cookies, multi-process crawling and so on.

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