15个超实用Python文本处理案例分享，快点码住！_python关于文件经典例子

Python 处理文本是一项非常常见的功能，本文整理了多种文本提取及NLP相关的案例，还是非常用心的

文章很长，高低要忍一下，如果忍不了，那就收藏吧，总会用到的！

 1.提取 PDF 内容

# pip install PyPDF2  安装 PyPDF2
import PyPDF2
from PyPDF2 import PdfFileReader
 
# Creating a pdf file object.
pdf = open("test.pdf", "rb")
 
# Creating pdf reader object.
pdf_reader = PyPDF2.PdfFileReader(pdf)
 
# Checking total number of pages in a pdf file.
print("Total number of Pages:", pdf_reader.numPages)
 
# Creating a page object.
page = pdf_reader.getPage(200)
 
# Extract data from a specific page number.
print(page.extractText())
 
# Closing the object.
pdf.close()

2.提取 Word 内容

# pip install python-docx  安装 python-docx
 
 
import docx
 
 
def main():
    try:
        doc = docx.Document('test.docx')  # Creating word reader object.
        data = ""
        fullText = []
        for para in doc.paragraphs:
            fullText.append(para.text)
            data = '\n'.join(fullText)
 
        print(data)
 
    except IOError:
        print('There was an error opening the file!')
        return
 
 
if __name__ == '__main__':
    main()

3.提取 Web 网页内容

# pip install bs4  安装 bs4
 
from urllib.request import Request, urlopen
from bs4 import BeautifulSoup
 
req = Request('http://www.cmegroup.com/trading/products/#sortField=oi&sortAsc=false&venues=3&page=1&cleared=1&group=1',
              headers={'User-Agent': 'Mozilla/5.0'})
 
webpage = urlopen(req).read()
 
# Parsing
soup = BeautifulSoup(webpage, 'html.parser')
 
# Formating the parsed html file
strhtm = soup.prettify()
 
# Print first 500 lines
print(strhtm[:500])
 
# Extract meta tag value
print(soup.title.string)
print(soup.find('meta', attrs={'property':'og:description'}))
 
# Extract anchor tag value
for x in soup.find_all('a'):
    print(x.string)
 
# Extract Paragraph tag value    
for x in soup.find_all('p'):
    print(x.text)

4.读取 Json 数据

import requests
import json
 
r = requests.get("https://support.oneskyapp.com/hc/en-us/article_attachments/202761727/example_2.json")
res = r.json()
 
# Extract spec