I'm trying to read some PDF documents with Python.
I would like to extract a summary in the first page.
Does it exist a library able to do it?
There are two parts to your problem: first you must extract the text from the PDF, and then run that through a summarizer.
There are many utilities to extract text from a PDF, though text in a PDF may not be stored in a 'logical' order.
(For instance, a page with two text columns might be stored with the first line of both columns, followed by the next, etc; rather than all the text of the first column, then the second column, as a human would read it.)
The PDFMiner library would seem to be ideal for extracting the text. A quick Google reveals that there are several text summarizer python libraries, though I haven't used any of them and can't attest to their abilities. But parsing human language is tricky - even for humans.
https://pypi.org/project/text-summarizer/
http://ai.intelligentonlinetools.com/ml/text-summarization/
If you're using MacOS, there is a built-in text summarizing Service. Right click on any selected text and click "Summarize" to activate. Though it seems hard to incorporate this into any automated process.
Related
I need to extract pdf text using python，but pdfminer and others are too big to use,but when using simple "with open xxx as xxx" method, I met a problem , the content part didn't extract appropriately. The text looks like bytes because it start with b'. My code and the result screenshot:
with open(r"C:\Users\admin\Desktop\aaa.pdf","rb") as file:
aa=file.readlines()
for a in aa:
print(a)
Output Screenshot:
To generate an answer from the comments...
when using simple "with open xxx as xxx" method, I met a problem , the content part didn't extract appropriately
The reason is that PDF is not a plain text format but instead a binary format whose contents may be compressed and/or encrypted. For example the object you posted a screenshot of,
4 0 obj
<</Filter/FlateDecode/Length 210>>
stream
...
endstream
endobj
contains FLATE compressed data between stream and endstream (which is indicated by the Filter value FlateDecode).
But even if it was not compressed or encrypted, you might still not recognize any text displayed because each PDF font object can use its own, completely custom encoding. Furthermore, glyphs you see grouped in a text line do not need to be drawn by the same drawing instruction in the PDF, you may have to arrange all the strings in drawing instructions by coordinate to be able to find the text of a text line.
(For some more details and backgrounds read this answer which focuses on the related topic of replacement of text in a PDF.)
Thus, when you say
pdfminer and others are too big to use
please consider that they are so big for a reason: They are so big because you need that much code for adequate text extraction. This is in particular true for Chinese text; for simple PDFs with English text there are some short cuts working in benign circumstances, but for PDFs with CJK text you should not expect such short cuts.
If you want to try nonetheless and implement text extraction yourself, grab a copy of ISO 32000-1 or ISO 32000-2 (Google for pdf32000 for a free copy of the former) and study that pdf specification. Based on that information you can step by step learn to parse those binary strings to pdf objects, find content streams therein, parse the instructions in those content streams, retrieve the text pieces drawn by those instructions, and arrange those pieces correctly to a whole text.
Don't expect your solution to be much smaller than pdfminer etc...
I have a PDF file which consists of tables which can spread across various pages and may have text in between. An example of it can be found here.
I am able to convert the PDF to any format but the output files are not in any way parse-able i.e. I cannot extract data out of it as they are scattered. Here are the links to the output files which I created using pdftotext and pdftohtml.
Is there a way to extract data in a more suitable way?
Thanks in advance.
The general answer is no. pdf is a format intended for visual presentation and printing, and there is no guarantee that the contents will be in any particular order let alone structured as a table in any way other than what appears when the pdf is rendered onto paper or a screen. Sometimes there is even deliberate obfuscation to prevent anyone doing what you are attempting.
In this case it appears to be possible to cut and paste the contents of each table element. For a small number of similar files that is almost certainly the quickest thing to do. Open the pdf on the left hand of your screen, a spreadsheet or data-entry program on the right hand, then cut and paste. For a medium number - tens, hundreds? - it's probably cheapest to hire a temp to do the donkey-work. For a large number - thousands? - it would be possible to create a program to automate this process, but definitely not easy. I might think about using human input via the mouse to identify the corners of the table and the horizontal / vertical divisions, then generating cut and paste operations via control of the human interface devices. Don't ask me how. I'd have to find out if I had to do this, and I'd much rather not. It's a WOMBAT.
Whatever form of analysis you did on the pdf contents would certainly not generalize to other pdfs created by different organisations using different software, and possibly not even by the same organisation using the same process but merely a later release of the same software.
Following in the line of #nigel222, it really depends on the PDF how easily you can get the data out in some useful way.
It is best if the PDF is structured (has a document structure, created when the PDF was written). In this case, you can access the structure, and you are all set.
As structure is a fundamental necessity of an accessible PDF, you may try to "massage" the document by applying the various "make accessible" utilities floating around; definitely something to follow.
Regularly I have to go through a list of pdf files and search for specific data and add them to an excel sheet for later review. As the number of pdf files are around 50 per month, it is both time taking and frustrating to do it manually.
Can the process be automated in windows by python or any other scripting language? I require to have all the pdf files in a folder and run the script which will generate an excel sheet with all the data added. The pdf files with which I work are tabular and have similar structures.
Yes. And no. And maybe.
The problem here is not extracting something from a PDF document. Extracting something is almost always possible and there are plenty of tools available to extract content from a PDF document. Text, images, whatever you need.
The major problem (and the reason for the "no" or "maybe") is that PDF in general is not a structured file format. It doesn't care about columns, paragraphs, tables, sentences or even words. In the general case it cares only about characters on a page in a specific location.
This means that in the general case you cannot query a PDF document and ask it for every paragraph or for the third sentence in the fifth paragraph. You can ask a library to get all of the text or all of the text in a specific location. And then you have to hope the library is able to extract the text you need in a legible format. Because there doesn't even have to be the case that you can copy and paste or otherwise extra understandable characters from a PDF file. Many PDF files don't even contain enough information for that.
So... If you have a certain type of document and you can test that it predictably behaves a certain way with a certain extraction engine, then yes, you can extract information from a PDF file.
If the PDF files you receive are different all the time or the layout on the page is totally different every time than the answer is probably that you cannot reliably extract the information you want.
As a side note:
There are certain types of PDF documents that are easier to handle than others so if you're lucky that might make your life easier. Two examples:
Many PDF files will in fact contain textual information in such a way that it can be extracted in a legible way. PDF files that follow certain standards (such as PDF/A-1a, PDF/A-2a or PDF/A-2u etc...) are even required to be created this way.
Some PDF files are "tagged" which means they contain additional structural information that allows you to extract information in an easier and more meaningful way. This structure would in fact identify paragraphs, images, tables etc and if the tagging was done in a good way it could make the job of content extraction much easier.
You could use pdf2text2 in Python to extract data from your PDF.
Alternatively you can use pdftotext that is part of the Xpdf suite
I am working on a project where I have a pdf file which describes one of the health policy. What I need to do is extract the information from this PDF and try to save it in some form such that I can answer the questions related to the policy by extracting info from this PDf.
This PDF is too big, so I want to divide the PDF according to the different sections so that when a query related to some particular area comes in then I wont have to go through the entire document.
I tried solving this using some pdf converters which converts the PDFs into the HTMLs. But these converters wont convert the PDF to HTML properly so that headings will have heading tag. Also even if I convert this properly and get the proper sections out of the document, I am not getting how to store this data.(I mean in which form should I store this Data).
Is there any other solution with which I can achieve this. I am using Python and also I can use NLTK if needed. Also the format is not fixed for the PDfs, I mean to say my code should work on any kind of PDFs.
PDFMiner is great in that it has location for every bit of text it gets from the PDF. It won't be nicely put in header tags or anything like that, but if you have a consistent PDF structure in your docs you might be able to get something working.
I'm working on a project that is going to extract specified text from a pdf document. I have no experience with this type of extraction. One issue is that we don't just want a dump of all the text in the document. Rather, is there a way to extract only certain fields in the pdf? Is there a notion of pdf templates that could be used for something like this?
I'm trying to use Apple's Automator - this is able to get all the text but not specified text. Ideally, I would like someone in Pages to have for example 30 discreet rows of text and have 20 of those rows be specified as 'catalog item' and have our Automator script take ONLY those twenty lines.
Any ideas on best workflow / extraction tools for this? I would prefer only consumer level items be used such as Apple Pages, Automator, and ruby or python as a scripting language.
thx
edit #1
looks like tagged pdf's might be one way to do this - not sure how well supported on Apple Pages this is
With python, the best choice would probably be PDFMiner. It can extract the coordinates for every text string, so you can work out the rectangles in your form on your own and pick out what falls within them. It's all pretty low level, but PDF is unfortunately a pretty low level format.
Be warned that unless you already know a lot about the structure of PDF, you'll find the API and documentation rather scanty. Look around for usage examples, including here on SO.
For Ruby you might try pdf-reader for parsing a PDF and accessing both metadata and content. Extracting the specific items your interested in is another story, but how to go about doing that depends highly on what format of data you're expecting.
You can use Origami in Ruby, a framework designed to parse, analyze,
and forge PDF documents, or the Python equivalent: Origapy, a simple Python
interface for the Ruby based Origami.