Python 如何从PDF文件中提取文本？
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How to extract text from a PDF file?
提问by Simplicity
I'm trying to extract the text included in thisPDF file using Python.
我试图提取包含在文本此使用PDF文件Python。
I'm using the PyPDF2module, and have the following script:
我正在使用PyPDF2模块，并有以下脚本：
import PyPDF2
pdf_file = open('sample.pdf')
read_pdf = PyPDF2.PdfFileReader(pdf_file)
number_of_pages = read_pdf.getNumPages()
page = read_pdf.getPage(0)
page_content = page.extractText()
print page_content
When I run the code, I get the following output which is different from that included in the PDF document:
当我运行代码时，我得到以下输出，它与 PDF 文档中包含的输出不同：
!"#$%#$%&%$&'()*%+,-%./01'*23%4
5'%1$#26%3/%7/))/8%&)/26%8#3"%3"*%313/9#&)
%
How can I extract the text as is in the PDF document?
如何按原样提取 PDF 文档中的文本？
回答by Eugene
You may want to use time proved xPDFand derived tools to extract text instead as pyPDF2 seems to have various issueswith the text extraction still.
您可能希望使用经过时间验证的 xPDF和派生工具来提取文本，因为 pyPDF2 似乎在文本提取方面仍然存在各种问题。
The long answer is that there are lot of variations how a text is encoded inside PDF and that it may require to decoded PDF string itself, then may need to map with CMAP, then may need to analyze distance between words and letters etc.
长的答案是，文本在 PDF 中的编码方式有很多变化，并且可能需要解码 PDF 字符串本身，然后可能需要使用 CMAP 进行映射，然后可能需要分析单词和字母之间的距离等。
In case the PDF is damaged (i.e. displaying the correct text but when copying it gives garbage) and you really need to extract text, then you may want to consider converting PDF into image (using ImageMagik) and then use Tesseractto get text from image using OCR.
如果 PDF 损坏（即显示正确的文本，但在复制时会产生垃圾）并且您确实需要提取文本，那么您可能需要考虑将 PDF 转换为图像（使用ImageMagik），然后使用Tesseract从图像中获取文本使用 OCR。
回答by Quinn
Look at this code:
看看这段代码：
import PyPDF2
pdf_file = open('sample.pdf', 'rb')
read_pdf = PyPDF2.PdfFileReader(pdf_file)
number_of_pages = read_pdf.getNumPages()
page = read_pdf.getPage(0)
page_content = page.extractText()
print page_content.encode('utf-8')
The output is:
输出是：
!"#$%#$%&%$&'()*%+,-%./01'*23%4
5'%1$#26%3/%7/))/8%&)/26%8#3"%3"*%313/9#&)
%
Using the same code to read a pdf from 201308FCR.pdf.The output is normal.
用同样的代码从201308FCR.pdf读取pdf， 输出正常。
Its documentationexplains why:
其文档解释了原因：
def extractText(self):
"""
Locate all text drawing commands, in the order they are provided in the
content stream, and extract the text. This works well for some PDF
files, but poorly for others, depending on the generator used. This will
be refined in the future. Do not rely on the order of text coming out of
this function, as it will change if this function is made more
sophisticated.
:return: a unicode string object.
"""
回答by Jakobovski
Use textract.
使用文本。
It supports many types of files including PDFs
它支持多种类型的文件，包括 PDF
import textract
text = textract.process("path/to/file.extension")
回答by Máxima Alekz
You can use PDFtoText https://github.com/jalan/pdftotext
您可以使用 PDFtoText https://github.com/jalan/pdftotext
PDF to text keeps text format indentation, doesn't matter if you have tables.
PDF to text 保持文本格式缩进，如果你有表格也没关系。
回答by DJK
Was looking for a simple solution to use for python 3.x and windows. There doesn't seem to be support from textract, which is unfortunate, but if you are looking for a simple solution for windows/python 3 checkout the tikapackage, really straight forward for reading pdfs.
正在寻找用于 python 3.x 和 windows 的简单解决方案。似乎没有textract 的支持，这很不幸，但如果您正在寻找 Windows/python 3 的简单解决方案，请查看tika包，阅读 pdf 非常直接。
Tika-Python is a Python binding to the Apache Tika? REST services allowing Tika to be called natively in the Python community.
Tika-Python 是一个 Python 绑定到 Apache Tika？REST 服务允许在 Python 社区中本地调用 Tika。
from tika import parser
raw = parser.from_file('sample.pdf')
print(raw['content'])
回答by Ritesh Shanker
I am adding code to accomplish this: It is working fine for me:
我正在添加代码来实现这一点：它对我来说很好用：
# This works in python 3
# required python packages
# tabula-py==1.0.0
# PyPDF2==1.26.0
# Pillow==4.0.0
# pdfminer.six==20170720
import os
import shutil
import warnings
from io import StringIO
import requests
import tabula
from PIL import Image
from PyPDF2 import PdfFileWriter, PdfFileReader
from pdfminer.converter import TextConverter
from pdfminer.layout import LAParams
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.pdfpage import PDFPage
warnings.filterwarnings("ignore")
def download_file(url):
local_filename = url.split('/')[-1]
local_filename = local_filename.replace("%20", "_")
r = requests.get(url, stream=True)
print(r)
with open(local_filename, 'wb') as f:
shutil.copyfileobj(r.raw, f)
return local_filename
class PDFExtractor():
def __init__(self, url):
self.url = url
# Downloading File in local
def break_pdf(self, filename, start_page=-1, end_page=-1):
pdf_reader = PdfFileReader(open(filename, "rb"))
# Reading each pdf one by one
total_pages = pdf_reader.numPages
if start_page == -1:
start_page = 0
elif start_page < 1 or start_page > total_pages:
return "Start Page Selection Is Wrong"
else:
start_page = start_page - 1
if end_page == -1:
end_page = total_pages
elif end_page < 1 or end_page > total_pages - 1:
return "End Page Selection Is Wrong"
else:
end_page = end_page
for i in range(start_page, end_page):
output = PdfFileWriter()
output.addPage(pdf_reader.getPage(i))
with open(str(i + 1) + "_" + filename, "wb") as outputStream:
output.write(outputStream)
def extract_text_algo_1(self, file):
pdf_reader = PdfFileReader(open(file, 'rb'))
# creating a page object
pageObj = pdf_reader.getPage(0)
# extracting extract_text from page
text = pageObj.extractText()
text = text.replace("\n", "").replace("\t", "")
return text
def extract_text_algo_2(self, file):
pdfResourceManager = PDFResourceManager()
retstr = StringIO()
la_params = LAParams()
device = TextConverter(pdfResourceManager, retstr, codec='utf-8', laparams=la_params)
fp = open(file, 'rb')
interpreter = PDFPageInterpreter(pdfResourceManager, device)
password = ""
max_pages = 0
caching = True
page_num = set()
for page in PDFPage.get_pages(fp, page_num, maxpages=max_pages, password=password, caching=caching,
check_extractable=True):
interpreter.process_page(page)
text = retstr.getvalue()
text = text.replace("\t", "").replace("\n", "")
fp.close()
device.close()
retstr.close()
return text
def extract_text(self, file):
text1 = self.extract_text_algo_1(file)
text2 = self.extract_text_algo_2(file)
if len(text2) > len(str(text1)):
return text2
else:
return text1
def extarct_table(self, file):
# Read pdf into DataFrame
try:
df = tabula.read_pdf(file, output_format="csv")
except:
print("Error Reading Table")
return
print("\nPrinting Table Content: \n", df)
print("\nDone Printing Table Content\n")
def tiff_header_for_CCITT(self, width, height, img_size, CCITT_group=4):
tiff_header_struct = '<' + '2s' + 'h' + 'l' + 'h' + 'hhll' * 8 + 'h'
return struct.pack(tiff_header_struct,
b'II', # Byte order indication: Little indian
42, # Version number (always 42)
8, # Offset to first IFD
8, # Number of tags in IFD
256, 4, 1, width, # ImageWidth, LONG, 1, width
257, 4, 1, height, # ImageLength, LONG, 1, lenght
258, 3, 1, 1, # BitsPerSample, SHORT, 1, 1
259, 3, 1, CCITT_group, # Compression, SHORT, 1, 4 = CCITT Group 4 fax encoding
262, 3, 1, 0, # Threshholding, SHORT, 1, 0 = WhiteIsZero
273, 4, 1, struct.calcsize(tiff_header_struct), # StripOffsets, LONG, 1, len of header
278, 4, 1, height, # RowsPerStrip, LONG, 1, lenght
279, 4, 1, img_size, # StripByteCounts, LONG, 1, size of extract_image
0 # last IFD
)
def extract_image(self, filename):
number = 1
pdf_reader = PdfFileReader(open(filename, 'rb'))
for i in range(0, pdf_reader.numPages):
page = pdf_reader.getPage(i)
try:
xObject = page['/Resources']['/XObject'].getObject()
except:
print("No XObject Found")
return
for obj in xObject:
try:
if xObject[obj]['/Subtype'] == '/Image':
size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
data = xObject[obj]._data
if xObject[obj]['/ColorSpace'] == '/DeviceRGB':
mode = "RGB"
else:
mode = "P"
image_name = filename.split(".")[0] + str(number)
print(xObject[obj]['/Filter'])
if xObject[obj]['/Filter'] == '/FlateDecode':
data = xObject[obj].getData()
img = Image.frombytes(mode, size, data)
img.save(image_name + "_Flate.png")
# save_to_s3(imagename + "_Flate.png")
print("Image_Saved")
number += 1
elif xObject[obj]['/Filter'] == '/DCTDecode':
img = open(image_name + "_DCT.jpg", "wb")
img.write(data)
# save_to_s3(imagename + "_DCT.jpg")
img.close()
number += 1
elif xObject[obj]['/Filter'] == '/JPXDecode':
img = open(image_name + "_JPX.jp2", "wb")
img.write(data)
# save_to_s3(imagename + "_JPX.jp2")
img.close()
number += 1
elif xObject[obj]['/Filter'] == '/CCITTFaxDecode':
if xObject[obj]['/DecodeParms']['/K'] == -1:
CCITT_group = 4
else:
CCITT_group = 3
width = xObject[obj]['/Width']
height = xObject[obj]['/Height']
data = xObject[obj]._data # sorry, getData() does not work for CCITTFaxDecode
img_size = len(data)
tiff_header = self.tiff_header_for_CCITT(width, height, img_size, CCITT_group)
img_name = image_name + '_CCITT.tiff'
with open(img_name, 'wb') as img_file:
img_file.write(tiff_header + data)
# save_to_s3(img_name)
number += 1
except:
continue
return number
def read_pages(self, start_page=-1, end_page=-1):
# Downloading file locally
downloaded_file = download_file(self.url)
print(downloaded_file)
# breaking PDF into number of pages in diff pdf files
self.break_pdf(downloaded_file, start_page, end_page)
# creating a pdf reader object
pdf_reader = PdfFileReader(open(downloaded_file, 'rb'))
# Reading each pdf one by one
total_pages = pdf_reader.numPages
if start_page == -1:
start_page = 0
elif start_page < 1 or start_page > total_pages:
return "Start Page Selection Is Wrong"
else:
start_page = start_page - 1
if end_page == -1:
end_page = total_pages
elif end_page < 1 or end_page > total_pages - 1:
return "End Page Selection Is Wrong"
else:
end_page = end_page
for i in range(start_page, end_page):
# creating a page based filename
file = str(i + 1) + "_" + downloaded_file
print("\nStarting to Read Page: ", i + 1, "\n -----------===-------------")
file_text = self.extract_text(file)
print(file_text)
self.extract_image(file)
self.extarct_table(file)
os.remove(file)
print("Stopped Reading Page: ", i + 1, "\n -----------===-------------")
os.remove(downloaded_file)
# I have tested on these 3 pdf files
# url = "http://s3.amazonaws.com/NLP_Project/Original_Documents/Healthcare-January-2017.pdf"
url = "http://s3.amazonaws.com/NLP_Project/Original_Documents/Sample_Test.pdf"
# url = "http://s3.amazonaws.com/NLP_Project/Original_Documents/Sazerac_FS_2017_06_30%20Annual.pdf"
# creating the instance of class
pdf_extractor = PDFExtractor(url)
# Getting desired data out
pdf_extractor.read_pages(15, 23)
回答by hansaplast
After trying textract (which seemed to have too many dependencies) and pypdf2 (which could not extract text from the pdfs I tested with) and tika (which was too slow) I ended up using pdftotextfrom xpdf (as already suggested in another answer) and just called the binary from python directly (you may need to adapt the path to pdftotext):
在尝试了 textract（似乎有太多依赖项）和 pypdf2（无法从我测试的 pdf 中提取文本）和 tika（太慢）之后，我最终使用pdftotext了 xpdf（如另一个答案中已经建议的那样）和只是直接从 python 调用二进制文件（您可能需要将路径调整为 pdftotext）：
import os, subprocess
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
args = ["/usr/local/bin/pdftotext",
'-enc',
'UTF-8',
"{}/my-pdf.pdf".format(SCRIPT_DIR),
'-']
res = subprocess.run(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
output = res.stdout.decode('utf-8')
There is pdftotextwhich does basically the same but this assumes pdftotext in /usr/local/bin whereas I am using this in AWS lambda and wanted to use it from the current directory.
有pdftotext这确实基本上是相同的，但是这个，而我在AWS拉姆达使用这个，想从当前目录使用它假定pdftotext在/ usr / local / bin目录。
Btw: For using this on lambda you need to put the binary and the dependency to libstdc++.sointo your lambda function. I personally needed to compile xpdf. As instructions for this would blow up this answer I put them on my personal blog.
顺便说一句：要在 lambda 上使用它，您需要将二进制文件和依赖项libstdc++.so放入 lambda 函数中。我个人需要编译xpdf。由于这方面的说明会破坏这个答案，我将它们放在我的个人博客上。
回答by Steffi Keran Rani J
The below code is a solution to the question in Python 3. Before running the code, make sure you have installed the PyPDF2library in your environment. If not installed, open the command prompt and run the following command:
下面的代码是Python 3 中问题的解决方案。在运行代码之前，请确保您已PyPDF2在您的环境中安装了该库。如果未安装，请打开命令提示符并运行以下命令：
pip3 install PyPDF2
Solution Code:
解决方案代码：
import PyPDF2
pdfFileObject = open('sample.pdf', 'rb')
pdfReader = PyPDF2.PdfFileReader(pdfFileObject)
count = pdfReader.numPages
for i in range(count):
page = pdfReader.getPage(i)
print(page.extractText())
回答by Infinity
Here is the simplest code for extracting text
这是提取文本的最简单代码
code:
代码：
# importing required modules
import PyPDF2
# creating a pdf file object
pdfFileObj = open('filename.pdf', 'rb')
# creating a pdf reader object
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
# printing number of pages in pdf file
print(pdfReader.numPages)
# creating a page object
pageObj = pdfReader.getPage(5)
# extracting text from page
print(pageObj.extractText())
# closing the pdf file object
pdfFileObj.close()
回答by Yogi
Multi - page pdf can be extracted as text at single stretch instead of giving individual page number as argument using below code
多页 pdf 可以在一次拉伸中提取为文本，而不是使用以下代码将单个页码作为参数
import PyPDF2
import collections
pdf_file = open('samples.pdf', 'rb')
read_pdf = PyPDF2.PdfFileReader(pdf_file)
number_of_pages = read_pdf.getNumPages()
c = collections.Counter(range(number_of_pages))
for i in c:
page = read_pdf.getPage(i)
page_content = page.extractText()
print page_content.encode('utf-8')
