Pymupdf extract text example

Inthe structure of a PDF document was defined by Adobe. For Linux there are mighty command line tools available such as pdftk and pdfgrep. As a developer there is a huge excitement building your own software that is based on Python and uses PDF libraries that are freely available. This article is the beginning of a little series, and will cover these helpful Python libraries. You will learn how to read and extract the content both text and imagesrotate single pages, and split documents into its individual pages.

Extracting headers and paragraphs from pdf using PyMuPDF

Part Two will cover adding a watermark based on overlays. The range of available solutions for Python-related PDF tools, modules, and libraries is a bit confusing, and it takes a moment to figure out what is what, and which projects are maintained continuously.

Based on our research these are the candidates that are up-to-date:. PyPDF2 : A Python library to extract document information and content, split documents page-by-page, merge documents, crop pages, and add watermarks. PyPDF2 supports both unencrypted and encrypted documents. Both packages allow you to parse, analyze, and convert PDF documents. This includes the support for PDF 1. Its design aim is "to reliably extract data from sets of PDFs with as little code as possible.

It allows you to parse, analyze, and convert PDF documents. Not to be confused with its commercial pendant that has the same name. Complex tasks like creating 2D and 3D plots in publication-ready quality are built out of these primitives. ReportLab : An ambitious, industrial-strength library largely focused on precise creation of PDF documents.

It faithfully reproduces vector formats without rasterization. In order to understand the usage of PyPDF2 a combination of the official documentation and a lot of examples that are available from other resources helped. In contrast, the official PyMuPDF documentation is much clearer, and considerably faster using the library. PyPDF2 can be installed as a regular software package, or using pip3 for Python3.

The name of the Debian package is python3-pypdf2.

pymupdf extract text example

Listing 1 imports the PdfFileReader class, first. Next, using this class, it opens the document, and extracts the document information using the getDocumentInfo method, the number of pages using getDocumentInfoand the content of the first page. Please note that PyPDF2 starts counting the pages with 0, and that's why the call pdf. Eventually, the extracted information is printed to stdout.

As shown in Figure 1 above, the extracted text is printed on a continuing basis. There are no paragraphs, or sentence separations. As stated in the PyPDF2 documentation, all text data is returned in the order they are provided in the content stream of the page, and relying on it may lead to some surprises.

Displaying document information, printing the number of pages, and extracting the text of a PDF document is done in a similar way as with PyPDF2 see Listing 2. The nice thing about PyMuPDF is that it keeps the original document structure intact - entire paragraphs with linebreaks are kept as they are in the PDF document see Figure 2. Running this Python script on a page PDF, it extracted images in less than 3 seconds, which is amazing.

The individual images are stored in PNG format. In order to keep the original image format and size, instead of converting to PNG, have a look at extended versions of the scripts in the PyMuPDF wiki. Then we open the PDF file, create a reader object, and loop over all the pages using the reader object's getNumPages method.In my experience, generic pdf parsers generalise okay-ish over all documents, but for a specific use-case of somewhat similarly structured documents we can enhance performance with some code of our own!

Since pdf files consist of unstructured text, we need to find some similarities over the different documents how headers and paragraphs are separated. Now this is a good starting point for us to create a methodology. This package opens pdf documents page per page and saves all its content in a block and identifies the text sizefontcolour and flags. We iterate over the pages and blocks of the document, which is parsed by the PyMuPDF package imported as fitz and identify all the styles and attributes according to our granularity flag.

Output for one of our documents looks like this:. We again iterate over the pages of the document and the blocks. Hence, why I concatenate them with a ' ' delimiting the fact that a new block has started. In post-processing steps we can then decide what to do with these pipe-delimited parts concatenate them or separate them.

We return a list of strings with pipes in them and then are able to identify which textual parts are headers, paragraphs or subscripts, as shown below. As you can see we still need to perform several post-processing steps to clean the data and maybe order it in a different way, but this is at least a starting point. Full script and example pdf document can be found here. Sign in. Louis de Bruijn Follow. Methodology Since pdf files consist of unstructured text, we need to find some similarities over the different documents how headers and paragraphs are separated.

Use PyMuPDF to identify the paragraphs as the most used font, headers as anything larger and subscripts as anything smaller than the paragraph style. Towards Data Science A Medium publication sharing concepts, ideas, and codes.

Thanks to Ludovic Benistant. Master Information Science student, University of Groningen. Python enthusiast and Data Scientist at Ortec Finance. Towards Data Science Follow. A Medium publication sharing concepts, ideas, and codes. Write the first response. More From Medium. More from Towards Data Science.

Rhea Moutafis in Towards Data Science.It uses the method ParseTab contained in the same examples directory.

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If the document is encrypted, a decryption password will be asked for. Then the document's first page will be displayed in another dialog. A number of controls at the dialog's top and left sides exist to do several things as follows. The availability of these controls depend on the situation. Displaying page of Adobe's PDF manual:. After painting additional columns into the rectangle and again pressing Get Tablea slightly different analysis of the table is displayed, based on the column information supplied:.

They are text extraction programs. If a logical table is physically spread across more than one page of the document, it is up to you to bind them together by any logic invoked by Get Table. How to extract images. How to join PDFs. How to work with PDF embedded files. How to extract text from inside rectangles. How to extract text in natural reading order. How to add PDF form fields.

pymupdf extract text example

How to add annotations. How to show PDF Form fields. How to work with vector images. How to create simple graphics. How to create your own PDF Shape. How to add pages, images, text. How to extract fonts. How to rearrange pages.

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Algebra with geometry objects. Hyperlink maintenance. Visual table extraction. Wrapping FileOptimizer. MuPDF v1. Ubuntu Installation Experience.

The advantage of this method:

Windows Binaries Generation. Windows Binaries Installation. Skip to content. Jorj X.Appendix 1: Performance. Appendix 3: Considerations on Embedded Files. It is normally created behind the curtain, when Page text extraction methods are used, but it is also available directly.

In any case, an intermediate class, DisplayList must be created first display lists contain interpreted pages, they also provide the input for Pixmap creation. Information contained in a TextPage has the following hierarchy. Other than its name suggests, images may optionally also be part of a text page:. A span consists of adjacent characters with identical font properties: name, size, flags and color. Function TextPage. The lines within each block are concatenated by a new-line character.

This is a high-speed method with enough information to extract text contained in a given rectangle. This includes images, font information and text positions.

If wrapped in HTML header and trailer code, it can readily be displayed by an internate browser. Our above example:.

To address the font issue, you can use a simple utility script to scan through the HTML file and replace font references. This information can be used to present text in another reading order if required e.

The TextPage. We have successfully tested lxml to interpret this output. New in version 1. The following table shows the defaults settings flags parameter omitted or None for each extraction variant.

A description of the respective bit settings can be found in Preserve Text Flags. The text extraction methods differ significantly: in terms of information they supply, and in terms of resource requirements and runtimes. Generally, more information of course means that more processing is required and a higher data volume is generated. Especially images have a very significant impact. Make sure to exclude them via the flags parameter whenever you do not need them. To begin with, all methods are very fast in relation to other products out there in the market.

In terms of processing speed, we are not aware of a faster free tool. Information of interest are what do they provide? HTML text contains references to the fonts used of the original document. If these are not known to the browser a fat chance! This issue varies greatly by browser — on my Windows machine, MS Edge worked just fine, whereas Firefox looked horrible.

This seems to be the case for rotated pages and pages, where the various possible page bbox variants do not coincide e. Note We have successfully tested lxml to interpret this output. If you are not interested in images when using an output variant which includes them by default, then by all means set the respective bit off: You will experience a better performance and much lower space requirements.

More text is following in English Note Especially images have a very significant impact.

pymupdf extract text example

Last updated on Apr Created using Sphinx 1.Nevertheless we will only talk about PDF files for the sake of brevity. At places where indeed only PDF files are supported, this will be mentioned explicitely. To access a supported document, it must be opened with the following statement:. This creates a Document object doc. It is also possible to open a document from memory data, or to create a new, empty PDF. See Document for details. A document contains many attributes and functions.

PyMuPDF fully supports standard metadata. It is available for all document types, though not all entries may contain data in every single case. For details of their meanings and formats consult the PDF manuals, e.

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Adobe PDF Reference 1. Further information can also be found in chapter Document. The meta data fields are strings or None if not otherwise indicated. Be aware that not all of them necessarily contain meaningful data. Information in such streams is coded in XML. But you can extract the stream as a whole, inspect or modify it using a package like lxml and then store the result back into the PDF. If you want, you can also delete these data altogether. This will return a Python list of lists [[lvl, title, page, Other parameters describe details of the bookmark target.

Some typical uses of Page s follow:. For details see Page. This method offers lots of variations for controlling the image: resolution, colorspace, transparency, rotation, mirroring, shifting, shearing, etc. We can also use it in GUI dialog managers. Here are two examples, find more here.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

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I'm trying to extract the text included in this PDF file using Python.

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I'm using the PyPDF2 module, and have the following script:. When I run the code, I get the following output which is different from that included in the PDF document:. Was looking for a simple solution to use for python 3. Using the same code to read a pdf from FCR. The output is normal. Its documentation explains why:. After trying textract which seemed to have too many dependencies and pypdf2 which could not extract text from the pdfs I tested with and tika which was too slow I ended up using pdftotext from xpdf as already suggested in another answer and just called the binary from python directly you may need to adapt the path to pdftotext :.

I personally needed to compile xpdf. As instructions for this would blow up this answer I put them on my personal blog. You may want to use time proved xPDF and derived tools to extract text instead as pyPDF2 seems to have various issues with the text extraction still.

The long answer is that there are lot of variations how a text is encoded inside PDF and that it may require to decoded PDF string itself, then may need to map with CMAP, then may need to analyze distance between words and letters etc. In case the PDF is damaged i. The below code is a solution to the question in Python 3.

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Before running the code, make sure you have installed the PyPDF2 library in your environment. If not installed, open the command prompt and run the following command:.

Multi - page pdf can be extracted as text at single stretch instead of giving individual page number as argument using below code. You can see more details here Stripper with Python. You can download tika-app-xxx. I recommend using the following code if you need to open and read a lot of pdf files - the text of all pdf files in folder with relative path. Should be of help:. PyPDF2 does work, but results may vary.An often asked question is: "How can I extract the text within a given rectangle?

Obviously, we are cutting right through several words. Because we only fully include or exclude words do not include parts of a wordwe have to make a decision. This generic script demonstrates two separate extraction options:. Option 1 only extracts text for words fully contained in the given rectangle and delivers this:. Option 2 is more forgiving and also includes those words, that have a none-empty intersection with the rectangle.

It's output is this:. In reality, rectangle definitions will probably be made with some graphical support like in a GUI application. In those cases, incomplete words can be easily avoided. How to extract images. How to join PDFs. How to work with PDF embedded files. How to extract text from inside rectangles. How to extract text in natural reading order.

How to extract text from a rectangle

How to add PDF form fields. How to add annotations. How to show PDF Form fields. How to work with vector images. How to create simple graphics. How to create your own PDF Shape. How to add pages, images, text. How to extract fonts. How to rearrange pages. Algebra with geometry objects. Hyperlink maintenance. Visual table extraction.

Wrapping FileOptimizer.

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MuPDF v1. Ubuntu Installation Experience. Windows Binaries Generation. Windows Binaries Installation. Skip to content. How to extract text from a rectangle Jump to bottom. Here is the rectangle we want to extract: Obviously, we are cutting right through several words. Offenbar handelte es sich um eine letzte, infernalische Welle nach der Geburt des Sonnensystems. Pages


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