问题:使用Python进行网页抓取[关闭]

我想从网站上获取每天的日出/日落时间。是否可以使用Python抓取Web内容?使用什么模块?有没有可用的教程?

I’d like to grab daily sunrise/sunset times from a web site. Is it possible to scrape web content with Python? what are the modules used? Is there any tutorial available?


回答 0

结合使用urllib2和出色的BeautifulSoup库:

import urllib2
from BeautifulSoup import BeautifulSoup
# or if you're using BeautifulSoup4:
# from bs4 import BeautifulSoup

soup = BeautifulSoup(urllib2.urlopen('http://example.com').read())

for row in soup('table', {'class': 'spad'})[0].tbody('tr'):
    tds = row('td')
    print tds[0].string, tds[1].string
    # will print date and sunrise

Use urllib2 in combination with the brilliant BeautifulSoup library:

import urllib2
from BeautifulSoup import BeautifulSoup
# or if you're using BeautifulSoup4:
# from bs4 import BeautifulSoup

soup = BeautifulSoup(urllib2.urlopen('http://example.com').read())

for row in soup('table', {'class': 'spad'})[0].tbody('tr'):
    tds = row('td')
    print tds[0].string, tds[1].string
    # will print date and sunrise

回答 1

我真的会推荐Scrapy。

引用删除的答案:

  • Scrapy爬行比机械化最快,因为它使用异步操作(在Twisted之上)。
  • Scrapy在libxml2之上对解析(x)html提供了更好,最快的支持。
  • Scrapy是具有完整unicode的成熟框架,可处理重定向,gzip压缩响应,奇数编码,集成的http缓存等。
  • 一旦进入Scrapy,您可以在不到5分钟的时间内编写蜘蛛,下载图像,创建缩略图并将提取的数据直接导出到csv或json。

I’d really recommend Scrapy.

Quote from a deleted answer:

  • Scrapy crawling is fastest than mechanize because uses asynchronous operations (on top of Twisted).
  • Scrapy has better and fastest support for parsing (x)html on top of libxml2.
  • Scrapy is a mature framework with full unicode, handles redirections, gzipped responses, odd encodings, integrated http cache, etc.
  • Once you are into Scrapy, you can write a spider in less than 5 minutes that download images, creates thumbnails and export the extracted data directly to csv or json.

回答 2

我将网络抓取工作中的脚本收集到了这个位桶库中

针对您的案例的示例脚本:

from webscraping import download, xpath
D = download.Download()

html = D.get('http://example.com')
for row in xpath.search(html, '//table[@class="spad"]/tbody/tr'):
    cols = xpath.search(row, '/td')
    print 'Sunrise: %s, Sunset: %s' % (cols[1], cols[2])

输出:

Sunrise: 08:39, Sunset: 16:08
Sunrise: 08:39, Sunset: 16:09
Sunrise: 08:39, Sunset: 16:10
Sunrise: 08:40, Sunset: 16:10
Sunrise: 08:40, Sunset: 16:11
Sunrise: 08:40, Sunset: 16:12
Sunrise: 08:40, Sunset: 16:13

I collected together scripts from my web scraping work into this bit-bucket library.

Example script for your case:

from webscraping import download, xpath
D = download.Download()

html = D.get('http://example.com')
for row in xpath.search(html, '//table[@class="spad"]/tbody/tr'):
    cols = xpath.search(row, '/td')
    print 'Sunrise: %s, Sunset: %s' % (cols[1], cols[2])

Output:

Sunrise: 08:39, Sunset: 16:08
Sunrise: 08:39, Sunset: 16:09
Sunrise: 08:39, Sunset: 16:10
Sunrise: 08:40, Sunset: 16:10
Sunrise: 08:40, Sunset: 16:11
Sunrise: 08:40, Sunset: 16:12
Sunrise: 08:40, Sunset: 16:13

回答 3

我强烈建议您检查pyquery。它使用类似jquery(又称css)的语法,这对于那些来自该背景的人来说确实很容易。

对于您的情况,它将类似于:

from pyquery import *

html = PyQuery(url='http://www.example.com/')
trs = html('table.spad tbody tr')

for tr in trs:
  tds = tr.getchildren()
  print tds[1].text, tds[2].text

输出:

5:16 AM 9:28 PM
5:15 AM 9:30 PM
5:13 AM 9:31 PM
5:12 AM 9:33 PM
5:11 AM 9:34 PM
5:10 AM 9:35 PM
5:09 AM 9:37 PM

I would strongly suggest checking out pyquery. It uses jquery-like (aka css-like) syntax which makes things really easy for those coming from that background.

For your case, it would be something like:

from pyquery import *

html = PyQuery(url='http://www.example.com/')
trs = html('table.spad tbody tr')

for tr in trs:
  tds = tr.getchildren()
  print tds[1].text, tds[2].text

Output:

5:16 AM 9:28 PM
5:15 AM 9:30 PM
5:13 AM 9:31 PM
5:12 AM 9:33 PM
5:11 AM 9:34 PM
5:10 AM 9:35 PM
5:09 AM 9:37 PM

回答 4

您可以使用urllib2发出HTTP请求,然后获得Web内容。

您可以这样获得:

import urllib2
response = urllib2.urlopen('http://example.com')
html = response.read()

Beautiful Soup是一个Python HTML解析器,应该适合于屏幕抓取。

特别是,是他们的解析HTML文档的教程。

祝好运!

You can use urllib2 to make the HTTP requests, and then you’ll have web content.

You can get it like this:

import urllib2
response = urllib2.urlopen('http://example.com')
html = response.read()

Beautiful Soup is a python HTML parser that is supposed to be good for screen scraping.

In particular, here is their tutorial on parsing an HTML document.

Good luck!


回答 5

我将Scrapemark(查找网址-py2)和httlib2(下载图像-py2 + 3)结合使用。scrapemark.py有500行代码,但是使用正则表达式,因此它可能没有那么快,没有进行测试。

抓取网站的示例:

import sys
from pprint import pprint
from scrapemark import scrape

pprint(scrape("""
    <table class="spad">
        <tbody>
            {*
                <tr>
                    <td>{{[].day}}</td>
                    <td>{{[].sunrise}}</td>
                    <td>{{[].sunset}}</td>
                    {# ... #}
                </tr>
            *}
        </tbody>
    </table>
""", url=sys.argv[1] ))

用法:

python2 sunscraper.py http://www.example.com/

结果:

[{'day': u'1. Dez 2012', 'sunrise': u'08:18', 'sunset': u'16:10'},
 {'day': u'2. Dez 2012', 'sunrise': u'08:19', 'sunset': u'16:10'},
 {'day': u'3. Dez 2012', 'sunrise': u'08:21', 'sunset': u'16:09'},
 {'day': u'4. Dez 2012', 'sunrise': u'08:22', 'sunset': u'16:09'},
 {'day': u'5. Dez 2012', 'sunrise': u'08:23', 'sunset': u'16:08'},
 {'day': u'6. Dez 2012', 'sunrise': u'08:25', 'sunset': u'16:08'},
 {'day': u'7. Dez 2012', 'sunrise': u'08:26', 'sunset': u'16:07'}]

I use a combination of Scrapemark (finding urls – py2) and httlib2 (downloading images – py2+3). The scrapemark.py has 500 lines of code, but uses regular expressions, so it may be not so fast, did not test.

Example for scraping your website:

import sys
from pprint import pprint
from scrapemark import scrape

pprint(scrape("""
    <table class="spad">
        <tbody>
            {*
                <tr>
                    <td>{{[].day}}</td>
                    <td>{{[].sunrise}}</td>
                    <td>{{[].sunset}}</td>
                    {# ... #}
                </tr>
            *}
        </tbody>
    </table>
""", url=sys.argv[1] ))

Usage:

python2 sunscraper.py http://www.example.com/

Result:

[{'day': u'1. Dez 2012', 'sunrise': u'08:18', 'sunset': u'16:10'},
 {'day': u'2. Dez 2012', 'sunrise': u'08:19', 'sunset': u'16:10'},
 {'day': u'3. Dez 2012', 'sunrise': u'08:21', 'sunset': u'16:09'},
 {'day': u'4. Dez 2012', 'sunrise': u'08:22', 'sunset': u'16:09'},
 {'day': u'5. Dez 2012', 'sunrise': u'08:23', 'sunset': u'16:08'},
 {'day': u'6. Dez 2012', 'sunrise': u'08:25', 'sunset': u'16:08'},
 {'day': u'7. Dez 2012', 'sunrise': u'08:26', 'sunset': u'16:07'}]

回答 6

通过使用使您的生活更轻松 CSS Selectors

我知道我来晚了,但是我对你有很好的建议。

使用BeautifulSoup已经有人建议我宁愿用CSS Selectors刮里面的数据HTML

import urllib2
from bs4 import BeautifulSoup

main_url = "http://www.example.com"

main_page_html  = tryAgain(main_url)
main_page_soup = BeautifulSoup(main_page_html)

# Scrape all TDs from TRs inside Table
for tr in main_page_soup.select("table.class_of_table"):
   for td in tr.select("td#id"):
       print(td.text)
       # For acnhors inside TD
       print(td.select("a")[0].text)
       # Value of Href attribute
       print(td.select("a")[0]["href"])

# This is method that scrape URL and if it doesnt get scraped, waits for 20 seconds and then tries again. (I use it because my internet connection sometimes get disconnects)
def tryAgain(passed_url):
    try:
        page  = requests.get(passed_url,headers = random.choice(header), timeout = timeout_time).text
        return page
    except Exception:
        while 1:
            print("Trying again the URL:")
            print(passed_url)
            try:
                page  = requests.get(passed_url,headers = random.choice(header), timeout = timeout_time).text
                print("-------------------------------------")
                print("---- URL was successfully scraped ---")
                print("-------------------------------------")
                return page
            except Exception:
                time.sleep(20)
                continue 

Make your life easier by using CSS Selectors

I know I have come late to party but I have a nice suggestion for you.

Using BeautifulSoup is already been suggested I would rather prefer using CSS Selectors to scrape data inside HTML

import urllib2
from bs4 import BeautifulSoup

main_url = "http://www.example.com"

main_page_html  = tryAgain(main_url)
main_page_soup = BeautifulSoup(main_page_html)

# Scrape all TDs from TRs inside Table
for tr in main_page_soup.select("table.class_of_table"):
   for td in tr.select("td#id"):
       print(td.text)
       # For acnhors inside TD
       print(td.select("a")[0].text)
       # Value of Href attribute
       print(td.select("a")[0]["href"])

# This is method that scrape URL and if it doesnt get scraped, waits for 20 seconds and then tries again. (I use it because my internet connection sometimes get disconnects)
def tryAgain(passed_url):
    try:
        page  = requests.get(passed_url,headers = random.choice(header), timeout = timeout_time).text
        return page
    except Exception:
        while 1:
            print("Trying again the URL:")
            print(passed_url)
            try:
                page  = requests.get(passed_url,headers = random.choice(header), timeout = timeout_time).text
                print("-------------------------------------")
                print("---- URL was successfully scraped ---")
                print("-------------------------------------")
                return page
            except Exception:
                time.sleep(20)
                continue 

回答 7

如果我们想从任何特定类别中获取商品名称,则可以通过使用CSS选择器指定该类别的类别名称来实现:

import requests ; from bs4 import BeautifulSoup

soup = BeautifulSoup(requests.get('https://www.flipkart.com/').text, "lxml")
for link in soup.select('div._2kSfQ4'):
    print(link.text)

这是部分搜索结果:

Puma, USPA, Adidas & moreUp to 70% OffMen's Shoes
Shirts, T-Shirts...Under ₹599For Men
Nike, UCB, Adidas & moreUnder ₹999Men's Sandals, Slippers
Philips & moreStarting 99LED Bulbs & Emergency Lights

If we think of getting name of items from any specific category then we can do that by specifying the class name of that category using css selector:

import requests ; from bs4 import BeautifulSoup

soup = BeautifulSoup(requests.get('https://www.flipkart.com/').text, "lxml")
for link in soup.select('div._2kSfQ4'):
    print(link.text)

This is the partial search results:

Puma, USPA, Adidas & moreUp to 70% OffMen's Shoes
Shirts, T-Shirts...Under ₹599For Men
Nike, UCB, Adidas & moreUnder ₹999Men's Sandals, Slippers
Philips & moreStarting ₹99LED Bulbs & Emergency Lights

回答 8

这是一个简单的Web搜寻器,我使用BeautifulSoup,我们将搜索所有类名称为_3NFO0d的链接(锚)。我使用了Flipkar.com,它是一家在线零售商店。

import requests
from bs4 import BeautifulSoup
def crawl_flipkart():
    url = 'https://www.flipkart.com/'
    source_code = requests.get(url)
    plain_text = source_code.text
    soup = BeautifulSoup(plain_text, "lxml")
    for link in soup.findAll('a', {'class': '_3NFO0d'}):
        href = link.get('href')
        print(href)

crawl_flipkart()

Here is a simple web crawler, i used BeautifulSoup and we will search for all the links(anchors) who’s class name is _3NFO0d. I used Flipkar.com, it is an online retailing store.

import requests
from bs4 import BeautifulSoup
def crawl_flipkart():
    url = 'https://www.flipkart.com/'
    source_code = requests.get(url)
    plain_text = source_code.text
    soup = BeautifulSoup(plain_text, "lxml")
    for link in soup.findAll('a', {'class': '_3NFO0d'}):
        href = link.get('href')
        print(href)

crawl_flipkart()

回答 9

Python有很好的选择来抓取网络。具有框架的最好的框架是令人毛骨悚然的。对于初学者来说可能有些棘手,所以这里有一些帮助。
1.在3.5以上安装python(直到2.7才可用)。
2.在conda中创建一个环境(我这样做了)。
3.将scrapy安装在某个位置,然后从那里运行。
4. Scrapy shell将为您提供一个交互式界面来测试您的代码。
5. Scrapy startproject projectname将创建一个框架。
6. Scrapy genspider spidername会制造蜘蛛。您可以根据需要创建任意数量的蜘蛛。在执行此操作时,请确保您位于项目目录中。


较容易的是使用要求漂亮的汤。在开始花一小时时间阅读文档之前,它将解决您的大部分疑问。BS4提供了广泛的解析器供您选择。使用user-agentsleep使刮擦更容易。BS4返回bs.tag,请使用variable[0]。如果正在运行js,您将无法直接使用request和bs4进行抓取。您可以获取api链接,然后解析JSON以获取所需的信息或尝试进行操作selenium

Python has good options to scrape the web. The best one with a framework is scrapy. It can be a little tricky for beginners, so here is a little help.
1. Install python above 3.5 (lower ones till 2.7 will work).
2. Create a environment in conda ( I did this).
3. Install scrapy at a location and run in from there.
4. Scrapy shell will give you an interactive interface to test you code.
5. Scrapy startproject projectname will create a framework.
6. Scrapy genspider spidername will create a spider. You can create as many spiders as you want. While doing this make sure you are inside the project directory.


The easier one is to use requests and beautiful soup. Before starting give one hour of time to go through the documentation, it will solve most of your doubts. BS4 offer wide range of parsers that you can opt for. Use user-agent and sleep to make scraping easier. BS4 returns a bs.tag so use variable[0]. If there is js running, you wont be able to scrape using requests and bs4 directly. You could get the api link then parse the JSON to get the information you need or try selenium.


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