I need to process some PDF files and add their form field contents in a database.
This document has not Security Method set, as I can see in the PDF Viewer document properties.
I tried the suggestions I found here.
When I test using pdfminer (or pdfminer.six), I didn't get an error message, but it didn't retrieve any field.
Using PyPDF2, I get the error message: "file has not been decrypted."
This is the pdfminer code:
import sys
from pdfminer.pdfparser import PDFParser
from pdfminer.pdfdocument import PDFDocument
from pdfminer.pdftypes import resolve1
fname=r'D:\Atrium\Projects\CTFC\psgf\database\19022021\formulari-dinamic-redaccio-plans-simples-gestio-forestal_Filled.pdf'
fp = open(fname, 'rb')
parser = PDFParser(fp)
doc = PDFDocument(parser)
fields = resolve1(doc.catalog['AcroForm'])['Fields']
for i in fields:
field = resolve1(i)
name, value = field.get('T'), field.get('V')
print('{0}: {1}'.format(name, value))
print('Done!')
A sample file can be download here.
How can I do to obtain field names and content?
As mkl explained, my PDF files store form data in XFA form, a deprecated format. The XFA is an array of XML docs and I have to procure field names in each one of these docs.
I used PyPDF2 library to do that:
import PyPDF2 as pypdf
import xml.etree.ElementTree as ET
fname=r'form.pdf'
def findInDict(needle, haystack):
xlas = []
for key in haystack.keys():
try:
value=haystack[key]
except:
continue
if key==needle:
return value
if isinstance(value,dict):
x=findInDict(needle,value)
if x is not None:
return x
pdfobject=open(fname,'rb')
pdf=pypdf.PdfFileReader(pdfobject)
xfaparts=findInDict('/XFA',pdf.resolvedObjects)
for xfa in xfaparts:
if isinstance(xfa,pypdf.generic.IndirectObject):
xml = str(xfa.getObject().getData())
## Then process XML to find form tags
So I've just played around with PDFMiner and can now extract text from a PDF and throw it into an html or textfile.
pdf2txt.py -o outputfile.txt -t txt inputfile.pdf
I have then written a simple script to extract all certain strings:
with open('output.txt', 'r') as searchfile:
for line in searchfile:
if 'HELLO' in line:
print(line)
And now I can use all these strings containing the word HELLO to add to my databse if that is what I wanted.
My questions is:
Is the only way or can PDFinder grab conditional stuff before even spitting it out to the txt, html or even straight into the database?
Well, yes, you can: PDFMiner has API.
The basic example sais
from pdfminer.pdfparser import PDFParser
from pdfminer.pdfdocument import PDFDocument
from pdfminer.pdfpage import PDFPage
from pdfminer.pdfpage import PDFTextExtractionNotAllowed
from pdfminer.pdfinterp import PDFResourceManager
from pdfminer.pdfinterp import PDFPageInterpreter
from pdfminer.pdfdevice import PDFDevice
# Open a PDF file.
fp = open('mypdf.pdf', 'rb')
# Create a PDF parser object associated with the file object.
parser = PDFParser(fp)
# Create a PDF document object that stores the document structure.
# Supply the password for initialization.
document = PDFDocument(parser, password)
# Check if the document allows text extraction. If not, abort.
if not document.is_extractable:
raise PDFTextExtractionNotAllowed
# Create a PDF resource manager object that stores shared resources.
rsrcmgr = PDFResourceManager()
# Create a PDF device object.
device = PDFDevice(rsrcmgr)
# Create a PDF interpreter object.
interpreter = PDFPageInterpreter(rsrcmgr, device)
# Process each page contained in the document.
for page in PDFPage.create_pages(document):
interpreter.process_page(page)
# do stuff with the page here
and in the loop you should go with
# receive the LTPage object for the page.
layout = device.get_result()
and then use LTTextBox object. You have to analyse that. There's no full example in the docs, but you may check out the pdf2txt.py source which will help you to find missing pieces (although it does much more since it parses options and applies them).
And once you have the code that extracts the text, you can do what you want before saving a file. Including searching for certain parts of text.
PS looks like this was, in a way, asked before: How do I use pdfminer as a library which should be helpful, too.
I am currently using the class provided in the answer here:
How to extract text and text coordinates from a pdf file?
The class provided is very helpful in that I can get the position of every text box in a PDF. The class given also inserts a '_' every time there is a new line within the textbox.
I was wondering whether there was some way to get the position of each line of text within the textbox as well?
Found it: The solution is to recurse even when there is a TextBox, until a textline is found. The class below should provide the x and y coordinates of every line of text on a pdf when the parsepdf method is called.
from pdfminer.pdfparser import PDFParser
from pdfminer.pdfdocument import PDFDocument
from pdfminer.pdfpage import PDFPage
from pdfminer.pdfpage import PDFTextExtractionNotAllowed
from pdfminer.pdfinterp import PDFResourceManager
from pdfminer.pdfinterp import PDFPageInterpreter
from pdfminer.pdfdevice import PDFDevice
from pdfminer.layout import LAParams
from pdfminer.converter import PDFPageAggregator
import pdfminer
class pdfPositionHandling:
def parse_obj(self, lt_objs):
# loop over the object list
for obj in lt_objs:
if isinstance(obj, pdfminer.layout.LTTextLine):
print "%6d, %6d, %s" % (obj.bbox[0], obj.bbox[1], obj.get_text().replace('\n', '_'))
# if it's a textbox, also recurse
if isinstance(obj, pdfminer.layout.LTTextBoxHorizontal):
self.parse_obj(obj._objs)
# if it's a container, recurse
elif isinstance(obj, pdfminer.layout.LTFigure):
self.parse_obj(obj._objs)
def parsepdf(self, filename, startpage, endpage):
# Open a PDF file.
fp = open(filename, 'rb')
# Create a PDF parser object associated with the file object.
parser = PDFParser(fp)
# Create a PDF document object that stores the document structure.
# Password for initialization as 2nd parameter
document = PDFDocument(parser)
# Check if the document allows text extraction. If not, abort.
if not document.is_extractable:
raise PDFTextExtractionNotAllowed
# Create a PDF resource manager object that stores shared resources.
rsrcmgr = PDFResourceManager()
# Create a PDF device object.
device = PDFDevice(rsrcmgr)
# BEGIN LAYOUT ANALYSIS
# Set parameters for analysis.
laparams = LAParams()
# Create a PDF page aggregator object.
device = PDFPageAggregator(rsrcmgr, laparams=laparams)
# Create a PDF interpreter object.
interpreter = PDFPageInterpreter(rsrcmgr, device)
i = 0
# loop over all pages in the document
for page in PDFPage.create_pages(document):
if i >= startpage and i <= endpage:
# read the page into a layout object
interpreter.process_page(page)
layout = device.get_result()
# extract text from this object
self.parse_obj(layout._objs)
i += 1
Below code is not working if XMLNS tag is present in the xml file. How can I remove XMLNS tag, so that I can read the xml and update the value in xml w.o affecting XML format. If I won't remove XMLNS tag it is corrupting my xml file by adding namespace.
import os
import re
import sys
import math
import shutil
import string
import subprocess
from xml.dom import minidom
from xml.etree import ElementTree as et
from optparse import OptionParser
from array import *
with open("file1.txt") as input_file:
for line in input_file:
line = line.strip()
for number in line.split():
#int(data[0])
data=(float(number))
data=int(math.ceil(data))
data=(data*1024*1024)
data=hex(data)[2:]
tree = et.parse("..\FFUPackages\MemoryReservation.pkg.xml")
root = tree.getroot()
#del root.attrib["xmlns"]
#root[0][0][0][0].set("text","tony")
labels = tree.findall("Components/OSComponent/RegKeys/RegKey/RegValue")
#print labels
for label in labels:
#lineNum = lineNum + 1
#print label.find("Name")
if (label.get("Name")=="MemoryReservation"):
print label.get("Name")
#print label.set("int", data)
#self.logger.info("\t>Updating QCLabel.xml")
label.set("Value", str(data))
root.set("xmlns","urn:Microsoft.WindowsPhone/PackageSchema.v8.00")
tree.write("..\FFUPackages\MemoryReservation.pkg.xml")
I am trying to parse the pdf file text using pdfMiner, but the extracted text gets merged. I am using the pdf file from the following link [edit: link was broken / pointed to potential malware]
I am good with any type of output (file/string). Here is the code which returns the extracted text as string for me but for some reason, columns are merged.
from pdfminer.converter import TextConverter
from pdfminer.layout import LAParams
from pdfminer.pdfinterp import PDFResourceManager, process_pdf
import StringIO
def convert_pdf(filename):
rsrcmgr = PDFResourceManager()
retstr = StringIO()
codec = 'utf-8'
laparams = LAParams()
device = TextConverter(rsrcmgr, retstr, codec=codec)
fp = file(filename, 'rb')
process_pdf(rsrcmgr, device, fp)
fp.close()
device.close()
str = retstr.getvalue()
retstr.close()
return str
I have also tried PyPdf2, but faced the same issue. Here is the sample code for PyPDF2
from PyPDF2 import PdfReader
import StringIO
def get_data_using_pypdf2(filename):
reader = PdfReader(filename)
content = ""
for page in reader.pages:
extracted_text = page.extract_text()
content += extracted_text + "\n"
content = " ".join(content.replace("\xa0", " ").strip().split())
return content.encode("ascii", "ignore")
I have also tried pdf2txt.py but unable to get the formatted output.
I recently struggled with a similar problem, although my pdf had slightly simpler structure.
PDFMiner uses classes called "devices" to parse the pages in a pdf fil. The basic device class is the PDFPageAggregator class, which simply parses the text boxes in the file. The converter classes , e.g. TextConverter, XMLConverter, and HTMLConverter also output the result in a file (or in a string stream as in your example) and do some more elaborate parsing for the contents.
The problem with TextConverter (and PDFPageAggregator) is that they don't recurse deep enough to the structure of the document to properly extract the different columns. The two other converters require some information about the structure of the document for display purposes, so they gather more detailed data. In your example pdf both of the simplistic devices only parse (roughly) the entire text box containing the columns, which makes it impossible (or at least very difficult) to correctly separate the different rows. The solution to this that I found works pretty well, is to either
Create a new class that inherits from PDFPageAggregator, or
Use XMLConverter and parse the resulting XML document using e.g. Beautifulsoup
In both cases you would have to combine the different text segments to rows using their bounding box y-coordinates.
In the case of a new device class ('tis more eloquent, I think) you would have to override the method receive_layout that get's called for each page during the rendering process. This method then recursively parses the elements in each page. For example, something like this might get you started:
from pdfminer.pdfdocument import PDFDocument, PDFNoOutlines
from pdfminer.pdfparser import PDFParser
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.converter import PDFPageAggregator
from pdfminer.layout import LTPage, LTChar, LTAnno, LAParams, LTTextBox, LTTextLine
class PDFPageDetailedAggregator(PDFPageAggregator):
def __init__(self, rsrcmgr, pageno=1, laparams=None):
PDFPageAggregator.__init__(self, rsrcmgr, pageno=pageno, laparams=laparams)
self.rows = []
self.page_number = 0
def receive_layout(self, ltpage):
def render(item, page_number):
if isinstance(item, LTPage) or isinstance(item, LTTextBox):
for child in item:
render(child, page_number)
elif isinstance(item, LTTextLine):
child_str = ''
for child in item:
if isinstance(child, (LTChar, LTAnno)):
child_str += child.get_text()
child_str = ' '.join(child_str.split()).strip()
if child_str:
row = (page_number, item.bbox[0], item.bbox[1], item.bbox[2], item.bbox[3], child_str) # bbox == (x1, y1, x2, y2)
self.rows.append(row)
for child in item:
render(child, page_number)
return
render(ltpage, self.page_number)
self.page_number += 1
self.rows = sorted(self.rows, key = lambda x: (x[0], -x[2]))
self.result = ltpage
In the code above, each found LTTextLine element is stored in an ordered list of tuples containing the page number, coordinates of the bounding box, and the text contained in that particular element. You would then do something similar to this:
from pprint import pprint
from pdfminer.pdfparser import PDFParser
from pdfminer.pdfdocument import PDFDocument
from pdfminer.pdfpage import PDFPage
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.layout import LAParams
fp = open('pdf_doc.pdf', 'rb')
parser = PDFParser(fp)
doc = PDFDocument(parser)
doc.initialize('password') # leave empty for no password
rsrcmgr = PDFResourceManager()
laparams = LAParams()
device = PDFPageDetailedAggregator(rsrcmgr, laparams=laparams)
interpreter = PDFPageInterpreter(rsrcmgr, device)
for page in PDFPage.create_pages(doc):
interpreter.process_page(page)
# receive the LTPage object for this page
device.get_result()
pprint(device.rows)
The variable device.rows contains the ordered list with all the text lines arranged using their page number and y-coordinates. You can loop over the text lines and group lines with the same y-coordinates to form the rows, store the column data etc.
I tried to parse your pdf using the above code and the columns are mostly parsed correctly. However, some of the columns are so close together that the default PDFMiner heuristics fail to separate them into their own elements. You can probably get around this by tweaking the word margin parameter (the -W flag in the command line tool pdf2text.py). In any case, you might want to read through the (poorly documented) PDFMiner API as well as browse through the source code of PDFMiner, which you can obtain from github. (Alas, I cannot paste the link because I do not have sufficient rep points :'<, but you can hopefully google the correct repo)
I tried your first block of code and got a bunch of results that look like this:
MULTIPLE DWELLING AGARDEN COMPLEX 14945010314370 TO 372WILLOWRD W MULTIPLE DWELLING AGARDEN COMPLEX 14945010314380 TO 384WILLOWRD W MULTIPLE DWELLING AGARDEN COMPLEX 149450103141000 TO 1020WILLOWBROOKRD MULTIPLE DWELLING AROOMING HOUSE 198787
I am guessing you are in a similar position as this answer and that all the whitespace is used to position the words in the proper place, not as actual printable space characters. The fact that you have tried with with other pdf libraries makes me think that this might be an issue that is difficult for any pdf library to parse.
Solution provided by #hlindblo gave pretty good results. To further group the extracted text chunks by page and paragraph, here are the simple commands I used.
from collections import OrderedDict
grouped_text = OrderedDict()
for p in range(1000): # max page nb is 1000
grouped_text[p] = {}
for (page_nb, x_min, y_min, x_max, y_max, text) in device.rows:
x_min = round(x_min)//10 # manipulate the level of aggregation --> x_min might be slitghly different
try:
grouped_text[page_nb][x_min]+= " " + text
except:
grouped_text[page_nb][x_min] = text