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All of you must be familiar with what PDFs are. In fact, they are one of the most important and widely used digital media. PDF stands for Portable Document Format. It uses .pdf extension. It is used to present and exchange documents reliably, independent of software, hardware, or operating system.
Extracting Text from PDF File
Python package PyPDF can be used to achieve what we want [text extraction], although it can do more than what we need. This package can also be used to generate, decrypting and merging PDF files.
Note: For more information, refer to Working with PDF files in Python
Installation
To install this package type the below command in the terminal.
pip install PyPDF2
Example:
Input PDF:
import PyPDF2
pdfFileObj = open['example.pdf', 'rb']
pdfReader = PyPDF2.PdfFileReader[pdfFileObj]
print[pdfReader.numPages]
pageObj = pdfReader.getPage[0]
print[pageObj.extractText[]]
pdfFileObj.close[]
Output:
Let us try to understand the above code in chunks:
pdfFileObj = open['example.pdf', 'rb']
We opened the example.pdf in binary mode. and saved the file object as pdfFileObj.
pdfReader = PyPDF2.PdfFileReader[pdfFileObj]
Here, we create an object of PdfFileReader class of PyPDF2 module and pass the pdf file object & get a pdf reader object.
print[pdfReader.numPages]
numPages property gives the number of pages in the pdf file. For example, in our case, it is 20 [see first line of output].
pageObj = pdfReader.getPage[0]
Now, we create an object of PageObject class of PyPDF2 module. pdf reader object has function getPage[] which takes page number [starting form index 0] as argument and returns the page object.
print[pageObj.extractText[]]
Page object has function extractText[] to extract text from the pdf page.
pdfFileObj.close[]
At last, we close the pdf file object.
I am adding code to accomplish this: It is working fine for me:
# 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 = '