I have the following sample code where I download a pdf from the European Parliament website on a given legislative proposal:
EDIT: I ended up just getting the link and feeding it to adobes online conversion tool (see the code below):
import mechanize
import urllib2
import re
from BeautifulSoup import *
adobe = "http://www.adobe.com/products/acrobat/access_onlinetools.html"
url = "http://www.europarl.europa.eu/oeil/search_reference_procedure.jsp"
def get_pdf(soup2):
link = soup2.findAll("a", "com_acronym")
new_link = []
amendments = []
for i in link:
if "REPORT" in i["href"]:
new_link.append(i["href"])
if new_link == None:
print "No A number"
else:
for i in new_link:
page = br.open(str(i)).read()
bs = BeautifulSoup(page)
text = bs.findAll("a")
for i in text:
if re.search("PDF", str(i)) != None:
pdf_link = "http://www.europarl.europa.eu/" + i["href"]
pdf = urllib2.urlopen(pdf_link)
name_pdf = "%s_%s.pdf" % (y,p)
localfile = open(name_pdf, "w")
localfile.write(pdf.read())
localfile.close()
br.open(adobe)
br.select_form(name = "convertFrm")
br.form["srcPdfUrl"] = str(pdf_link)
br["convertTo"] = ["html"]
br["visuallyImpaired"] = ["notcompatible"]
br.form["platform"] =["Macintosh"]
pdf_html = br.submit()
soup = BeautifulSoup(pdf_html)
page = range(1,2) #can be set to 400 to get every document for a given year
year = range(1999,2000) #can be set to 2011 to get documents from all years
for y in year:
for p in page:
br = mechanize.Browser()
br.open(url)
br.select_form(name = "byReferenceForm")
br.form["year"] = str(y)
br.form["sequence"] = str(p)
response = br.submit()
soup1 = BeautifulSoup(response)
test = soup1.find(text="No search result")
if test != None:
print "%s %s No page skipping..." % (y,p)
else:
print "%s %s Writing dossier..." % (y,p)
for i in br.links(url_regex="file.jsp"):
link = i
response2 = br.follow_link(link).read()
soup2 = BeautifulSoup(response2)
get_pdf(soup2)
In the get_pdf() function I would like to convert the pdf file to text in python so I can parse the text for information about the legislative procedure. can anyone explaon me how this can be done?
Thomas
It has an extensible PDF parser that can be used for other purposes than text analysis. PyPDF2 is a pure-python PDF library capable of splitting, merging together, cropping, and transforming the pages of PDF files. It can also add custom data, viewing options, and passwords to PDF files.
Sounds like you found a solution, but if you ever want to do it without a web service, or you need to scrape data based on its precise location on the PDF page, can I suggest my library, pdfquery? It basically turns the PDF into an lxml tree that can be spit out as XML, or parsed with XPath, PyQuery, or whatever else you want to use.
To use it, once you had the file saved to disk you would return pdf = pdfquery.PDFQuery(name_pdf)
, or pass in a urllib file object directly if you didn't need to save it. To get XML out to parse with BeautifulSoup, you could do pdf.tree.tostring()
.
If you don't mind using JQuery-style selectors, there's a PyQuery interface with positional extensions, which can be pretty handy. For example:
balance = pdf.pq(':contains("Your balance is")').text()
strings_near_the_bottom_of_page_23 = [el.text for el in pdf.pq('LTPage[page_label=23] :in_bbox(0, 0, 600, 200)')]
It's not exactly magic. I suggest
For text extraction command-line utilities you have a number of possibilities and there may be others not mentioned in the link (perhaps Java-based). Try them first to see if they fit your needs. That is, try each step separately (finding the links, downloading the files, extracting the text) and then piece them together. For calling out, use subprocess.Popen
or subprocess.call()
.
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