How to extract text from embedded document in Python
0
I want to extract text from some URLS using Python, but I wasn't able to get anything from BeautifulSoup as the documents' HTML only includes an imbedded ID. Here is an example of a file that I would like to extract the text from: Example
Any ideas on how to extract the text from that URL?
Here is an example of code which just produces gibberish:
r = sessions.get("http://investors.yum.com/Cache/1001242026.PDF? O=PDF&T=&Y=&D=&FID=1001242026&iid=4025819")
html = r.text
soup = BeautifulSoup(html)
text = soup.get_text()
print(text)
python html
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
|
show 1 more comment
0
I want to extract text from some URLS using Python, but I wasn't able to get anything from BeautifulSoup as the documents' HTML only includes an imbedded ID. Here is an example of a file that I would like to extract the text from: Example
Any ideas on how to extract the text from that URL?
Here is an example of code which just produces gibberish:
r = sessions.get("http://investors.yum.com/Cache/1001242026.PDF? O=PDF&T=&Y=&D=&FID=1001242026&iid=4025819")
html = r.text
soup = BeautifulSoup(html)
text = soup.get_text()
print(text)
python html
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
What have you tried so far? Can you show us your code?
– G. Anderson
Nov 27 '18 at 17:44
Edited it to show the method I tried using BeautifulSoup. If you go to the link and inspect, you can see the issue. Instead of having the text within the HTML, it just has a single link.
– Christopher Kardatzke
Nov 27 '18 at 17:55
1
That's not an html page, that's a PDF document. You can use something to pull the document off the site, then use something like pypdf2 to try to parse it
– G. Anderson
Nov 27 '18 at 17:58
Do you know if I'd have to download all the PDFs in order to process them usnig pypdf2? Ideally, I'd like to be able to just grab the text with the URLs, without taking up any disk space.
– Christopher Kardatzke
Nov 27 '18 at 18:21
If you create your parsing as a function, then you can run through the PDFs and parse them in memory
– G. Anderson
Nov 27 '18 at 18:23
|
show 1 more comment
0
0
0
I want to extract text from some URLS using Python, but I wasn't able to get anything from BeautifulSoup as the documents' HTML only includes an imbedded ID. Here is an example of a file that I would like to extract the text from: Example
Any ideas on how to extract the text from that URL?
Here is an example of code which just produces gibberish:
r = sessions.get("http://investors.yum.com/Cache/1001242026.PDF? O=PDF&T=&Y=&D=&FID=1001242026&iid=4025819")
html = r.text
soup = BeautifulSoup(html)
text = soup.get_text()
print(text)
python html
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
I want to extract text from some URLS using Python, but I wasn't able to get anything from BeautifulSoup as the documents' HTML only includes an imbedded ID. Here is an example of a file that I would like to extract the text from: Example
Any ideas on how to extract the text from that URL?
Here is an example of code which just produces gibberish:
r = sessions.get("http://investors.yum.com/Cache/1001242026.PDF? O=PDF&T=&Y=&D=&FID=1001242026&iid=4025819")
html = r.text
soup = BeautifulSoup(html)
text = soup.get_text()
print(text)
python html
python html
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
edited Nov 27 '18 at 17:54
Christopher Kardatzke
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
asked Nov 27 '18 at 17:41
Christopher KardatzkeChristopher Kardatzke
11
11
What have you tried so far? Can you show us your code?
– G. Anderson
Nov 27 '18 at 17:44
Edited it to show the method I tried using BeautifulSoup. If you go to the link and inspect, you can see the issue. Instead of having the text within the HTML, it just has a single link.
– Christopher Kardatzke
Nov 27 '18 at 17:55
1
That's not an html page, that's a PDF document. You can use something to pull the document off the site, then use something like pypdf2 to try to parse it
– G. Anderson
Nov 27 '18 at 17:58
Do you know if I'd have to download all the PDFs in order to process them usnig pypdf2? Ideally, I'd like to be able to just grab the text with the URLs, without taking up any disk space.
– Christopher Kardatzke
Nov 27 '18 at 18:21
If you create your parsing as a function, then you can run through the PDFs and parse them in memory
– G. Anderson
Nov 27 '18 at 18:23
|
show 1 more comment
What have you tried so far? Can you show us your code?
– G. Anderson
Nov 27 '18 at 17:44
Edited it to show the method I tried using BeautifulSoup. If you go to the link and inspect, you can see the issue. Instead of having the text within the HTML, it just has a single link.
– Christopher Kardatzke
Nov 27 '18 at 17:55
1
That's not an html page, that's a PDF document. You can use something to pull the document off the site, then use something like pypdf2 to try to parse it
– G. Anderson
Nov 27 '18 at 17:58
Do you know if I'd have to download all the PDFs in order to process them usnig pypdf2? Ideally, I'd like to be able to just grab the text with the URLs, without taking up any disk space.
– Christopher Kardatzke
Nov 27 '18 at 18:21
If you create your parsing as a function, then you can run through the PDFs and parse them in memory
– G. Anderson
Nov 27 '18 at 18:23
What have you tried so far? Can you show us your code?
– G. Anderson
Nov 27 '18 at 17:44
What have you tried so far? Can you show us your code?
– G. Anderson
Nov 27 '18 at 17:44
Edited it to show the method I tried using BeautifulSoup. If you go to the link and inspect, you can see the issue. Instead of having the text within the HTML, it just has a single link.
– Christopher Kardatzke
Nov 27 '18 at 17:55
Edited it to show the method I tried using BeautifulSoup. If you go to the link and inspect, you can see the issue. Instead of having the text within the HTML, it just has a single link.
– Christopher Kardatzke
Nov 27 '18 at 17:55
1
1
That's not an html page, that's a PDF document. You can use something to pull the document off the site, then use something like pypdf2 to try to parse it
– G. Anderson
Nov 27 '18 at 17:58
That's not an html page, that's a PDF document. You can use something to pull the document off the site, then use something like pypdf2 to try to parse it
– G. Anderson
Nov 27 '18 at 17:58
Do you know if I'd have to download all the PDFs in order to process them usnig pypdf2? Ideally, I'd like to be able to just grab the text with the URLs, without taking up any disk space.
– Christopher Kardatzke
Nov 27 '18 at 18:21
Do you know if I'd have to download all the PDFs in order to process them usnig pypdf2? Ideally, I'd like to be able to just grab the text with the URLs, without taking up any disk space.
– Christopher Kardatzke
Nov 27 '18 at 18:21
If you create your parsing as a function, then you can run through the PDFs and parse them in memory
– G. Anderson
Nov 27 '18 at 18:23
If you create your parsing as a function, then you can run through the PDFs and parse them in memory
– G. Anderson
Nov 27 '18 at 18:23
|
show 1 more comment
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What have you tried so far? Can you show us your code?
– G. Anderson
Nov 27 '18 at 17:44
Edited it to show the method I tried using BeautifulSoup. If you go to the link and inspect, you can see the issue. Instead of having the text within the HTML, it just has a single link.
– Christopher Kardatzke
Nov 27 '18 at 17:55
1
That's not an html page, that's a PDF document. You can use something to pull the document off the site, then use something like pypdf2 to try to parse it
– G. Anderson
Nov 27 '18 at 17:58
Do you know if I'd have to download all the PDFs in order to process them usnig pypdf2? Ideally, I'd like to be able to just grab the text with the URLs, without taking up any disk space.
– Christopher Kardatzke
Nov 27 '18 at 18:21
If you create your parsing as a function, then you can run through the PDFs and parse them in memory
– G. Anderson
Nov 27 '18 at 18:23