Python:报纸模块--有什么方法可以直接从URL获取文章吗？

Question

我正在为python 这里使用报纸模块。

在教程中，它描述了如何汇集不同报纸的建设。它同时产生它们。(请参阅上面链接中的“多线程文章下载”)

有什么方法可以直接从urls列表中提取文章吗？也就是说，我是否可以将多个urls插入到下面的设置中，并让它同时下载和解析它们？

from newspaper import Article
url = 'http://www.bbc.co.uk/zhongwen/simp/chinese_news/2012/12/121210_hongkong_politics.shtml'
a = Article(url, language='zh') # Chinese
a.download()
a.parse()
print(a.text[:150])

Answer 1

我能够通过为每个文章URL创建一个Source来做到这一点。(免责声明:不是python开发人员)

import newspaper

urls = [
  'http://www.baltimorenews.net/index.php/sid/234363921',
  'http://www.baltimorenews.net/index.php/sid/234323971',
  'http://www.atlantanews.net/index.php/sid/234323891',
  'http://www.wpbf.com/news/funeral-held-for-gabby-desouza/33874572',  
]

class SingleSource(newspaper.Source):
    def __init__(self, articleURL):
        super(StubSource, self).__init__("http://localhost")
        self.articles = [newspaper.Article(url=url)]

sources = [SingleSource(articleURL=u) for u in urls]

newspaper.news_pool.set(sources)
newspaper.news_pool.join()

for s in sources:
  print s.articles[0].html

Answer 2

我知道这个问题确实很古老，但这是我在谷歌上搜索如何获取多线程报纸时最先出现的链接之一。虽然Kyles的答案很有帮助，但它并不完整，我认为它有一些排印.

import newspaper

urls = [
'http://www.baltimorenews.net/index.php/sid/234363921',
'http://www.baltimorenews.net/index.php/sid/234323971',
'http://www.atlantanews.net/index.php/sid/234323891',
'http://www.wpbf.com/news/funeral-held-for-gabby-desouza/33874572',  
]

class SingleSource(newspaper.Source):
def __init__(self, articleURL):
    super(SingleSource, self).__init__("http://localhost")
    self.articles = [newspaper.Article(url=articleURL)]

sources = [SingleSource(articleURL=u) for u in urls]

newspaper.news_pool.set(sources)
newspaper.news_pool.join()

我将Stubsource更改为Singlesource，将其中一个urls更改为articleURL。当然，这只是下载网页，你仍然需要解析它们才能得到文本。

multi=[]
i=0
for s in sources:
    i+=1
    try:
        (s.articles[0]).parse()
        txt = (s.articles[0]).text
        multi.append(txt)
    except:
        pass

在我的100个url示例中，与仅按顺序处理每个url相比，这花费了一半的时间。(编辑:在将样本数量增加到2000年之后，大约减少了四分之一。)

(编辑:让整个工作与多线程！)我对我的实现使用了非常好的这解释。当样本大小为100个urls时，使用4个线程所需的时间与上面的代码相当，但是将线程数量增加到10会进一步减少大约一半。更大的样本大小需要更多的线程来提供一个可比较的差异。

import newspaper
from multiprocessing.dummy import Pool as ThreadPool

def getTxt(url):
    article = Article(url)
    article.download()
    try:
        article.parse()
        txt=article.text
        return txt
    except:
        return ""

pool = ThreadPool(10)

# open the urls in their own threads
# and return the results
results = pool.map(getTxt, urls)

# close the pool and wait for the work to finish 
pool.close() 
pool.join()

Answer 3

以约瑟夫的回答为基础。我假设最初的海报想要使用多线程来提取一堆数据，并将其正确地存储在某个地方。经过多次尝试，我认为我已经找到了一个解决方案，它可能不是最有效的，但它是有效的，我试着使它更好，然而，我认为newspaper3k插件可能有点错误。但是，这在将所需的元素提取到DataFrame中时是有效的。

import newspaper
from newspaper import Article
from newspaper import Source
import pandas as pd

gamespot_paper = newspaper.build('https://www.gamespot.com/news/', memoize_articles=False)
bbc_paper = newspaper.build("https://www.bbc.com/news", memoize_articles=False)
papers = [gamespot_paper, bbc_paper]
news_pool.set(papers, threads_per_source=4) 
news_pool.join()

#Create our final dataframe
df_articles = pd.DataFrame()

#Create a download limit per sources
limit = 100

for source in papers:
    #tempoary lists to store each element we want to extract
    list_title = []
    list_text = []
    list_source =[]

    count = 0

    for article_extract in source.articles:
        article_extract.parse()

        if count > limit:
            break

        #appending the elements we want to extract
        list_title.append(article_extract.title)
        list_text.append(article_extract.text)
        list_source.append(article_extract.source_url)

        #Update count
        count +=1


    df_temp = pd.DataFrame({'Title': list_title, 'Text': list_text, 'Source': list_source})
    #Append to the final DataFrame
    df_articles = df_articles.append(df_temp, ignore_index = True)
    print('source extracted')

请建议任何改进！