This brief tutorial should give you an introduction and orientation to pikepdf’s paradigm and syntax. From there, we refer to you various topics.

Opening and saving PDFs

In contrast to better known PDF libraries, pikepdf uses a single object to represent a PDF, whether reading, writing or merging. We have cleverly named this pikepdf.Pdf. In this documentation, a Pdf is a class that allows manipulate the PDF, meaning the “file” (whether it exists in memory or on a file system).

from pikepdf import Pdf

with Pdf.open('sample.pdf') as pdf:

You may of course use from pikepdf import Pdf as ... if the short class name conflicts or from pikepdf import Pdf as PDF if you prefer uppercase.

pikepdf.open() is a shorthand for pikepdf.Pdf.open().

The PDF class API follows the example of the widely-used Pillow image library. For clarity there is no default constructor since the arguments used for creation and opening are different. To make a new empty PDF, use Pdf.new() not Pdf().

Pdf.open() also accepts seekable streams as input, and pikepdf.Pdf.save() accepts streams as output. pathlib.Path objects are fully supported wherever pikepdf accepts a filename.

Creating PDFs

Using pikepdf.Pdf.new(), you can create a new PDF from scratch. pikepdf is not primarily a PDF generation library - you may find other libraries easier to use for that purpose. However, pikepdf does provide a few useful functions for creating PDFs.

from pikepdf import Pdf

pdf = Pdf.new()

Inspecting pages

Manipulating pages is fundamental to PDFs. pikepdf presents the pages in a PDF through the pikepdf.Pdf.pages property, which follows the list protocol. As such page numbers begin at 0.

Let’s open a simple PDF that contains four pages.

>>> from pikepdf import Pdf

>>> pdf = Pdf.open('../tests/resources/fourpages.pdf')

How many pages?

>>> len(pdf.pages)

pikepdf integrates with IPython and Jupyter’s rich object APIs so that you can view PDFs, PDF pages, or images within PDF in a IPython window or Jupyter notebook. This makes it easier to test visual changes.

>>> pdf
« In Jupyter you would see the PDF here »

>>> pdf.pages[0]
« In Jupyter you would see an image of the PDF page here »

You can also examine individual pages, which we’ll explore in the next section. Suffice to say that you can access pages by indexing them and slicing them.

>>> pdf.pages[0]
« In Jupyter you would see an image of the PDF page here »


pikepdf.Pdf.open() can open almost all types of encrypted PDF! Just provide the password= keyword argument.

For more details on document assembly, see PDF split, merge and document assembly.

PDF dictionaries

In PDFs, the main data structure is the dictionary, a key-value data structure much like a Python dict or attrdict. The major difference is that the keys can only be names, and the values can only be PDF types, including other dictionaries.

PDF dictionaries are represented as pikepdf.Dictionary objects, and names are of type pikepdf.Name.

>>> from pikepdf import Pdf

>>> example = Pdf.open('../tests/resources/congress.pdf')

>>> example.Root  # Show the document's root dictionary
  "/Pages": {
    "/Count": 1,
    "/Kids": [ <Pdf.pages.from_objgen(4,0)> ],
    "/Type": "/Pages"
  "/Type": "/Catalog"

Page dictionaries

A page in a PDF is just a dictionary with certain required keys that is referenced by the PDF’s “page tree”. (pikepdf manages the page tree for you, and wraps page dictionaries to provide special functions that help with managing pages.) A pikepdf.Page is a wrapper around a PDF page dictionary that provides many useful functions for working on pages.

>>> from pikepdf import Pdf

>>> example = Pdf.open('../tests/resources/congress.pdf')

>>> page1 = example.pages[0]

>>> obj_page1 = page1.obj

>>> obj_page1
  "/Contents": pikepdf.Stream(owner=<...>, data=b'q\n200.0000 0 0 304.0'..., {
    "/Length": 50
  "/MediaBox": [ 0, 0, 200, 304 ],
  "/Parent": <reference to /Pages>,
  "/Resources": {
    "/XObject": {
      "/Im0": pikepdf.Stream(owner=<...>, data=<...>, {
        "/BitsPerComponent": 8,
        "/ColorSpace": "/DeviceRGB",
        "/Filter": [ "/DCTDecode" ],
        "/Height": 1520,
        "/Length": 192956,
        "/Subtype": "/Image",
        "/Type": "/XObject",
        "/Width": 1000
  "/Type": "/Page"

repr() output

Let’s observe the page’s repr() output:

>>> repr(page1)
'<pikepdf.Page({\n  "/Contents": pikepdf.Stream(owner=<...>, data=b\'q\\n200.0000 0 0 304.0\'..., {\n    "/Length": 50\n  }),\n  "/MediaBox": [ 0, 0, 200, 304 ],\n  "/Parent": <reference to /Pages>,\n  "/Resources": {\n    "/XObject": {\n      "/Im0": pikepdf.Stream(owner=<...>, data=<...>, {\n        "/BitsPerComponent": 8,\n        "/ColorSpace": "/DeviceRGB",\n        "/Filter": [ "/DCTDecode" ],\n        "/Height": 1520,\n        "/Length": 192956,\n        "/Subtype": "/Image",\n        "/Type": "/XObject",\n        "/Width": 1000\n      })\n    }\n  },\n  "/Type": "/Page"\n})>'

The angle brackets in the output indicate that this object cannot be constructed with a Python expression because it contains a reference. When angle brackets are omitted from the repr() of a pikepdf object, then the object can be replicated with a Python expression, such as eval(repr(x)) == x. Pages typically have indirect references to themselves and other pages, so they cannot be represented as an expression.

Item and attribute notation

Dictionary keys may be looked up using attributes (page1.Type) or keys (page1['/Type']).

>>> page1.Type      # preferred notation for standard PDF names

>>> page1['/Type']  # also works

By convention, pikepdf uses attribute notation for standard names (the names that are normally part of a dictionary, according to the PDF 1.7 Reference Manual), and item notation for names that may not always appear. For example, the images belong to a page always appear at page.Resources.XObject but the names of images are arbitrarily chosen by whatever software generates the PDF (/Im0, in this case). (Whenever expressed as strings, names begin with /.)

>>> page1.Resources.XObject['/Im0']

Item notation here would be quite cumbersome: ['/Resources']['/XObject]['/Im0'] (not recommended).

Attribute notation is convenient, but not robust if elements are missing. For elements that are not always present, you can use .get(), which behaves like dict.get() in core Python. A library such as glom might help when working with complex structured data that is not always present.

(For now, we’ll set aside what a page’s Resources.XObject are for. See Working with pages for details.)

Deleting pages

Removing pages is easy too.

>>> del pdf.pages[1:3]  # Remove pages 2-3 labeled "second page" and "third page"
>>> len(pdf.pages)

Saving changes

Sign that reads "Help the pike survive"

Saving pike.

Naturally, you can save your changes with pikepdf.Pdf.save(). filename can be a pathlib.Path, which we accept everywhere.

>>> pdf.save('output.pdf')

You may save a file multiple times, and you may continue modifying it after saving. For example, you could create an unencrypted version of document, then apply a watermark, and create an encrypted version.


You may not overwrite the input file (or whatever Python object provides the data) when saving or at any other time. pikepdf assumes it will have exclusive access to the input file or input data you give it to, until pdf.close() is called.

Saving secure PDFs

To save an encrypted (password protected) PDF, use a pikepdf.Encryption object to specify the encryption settings. By default, pikepdf selects the strongest security handler and algorithm (AES-256), but allows full access to modify file contents. A pikepdf.Permissions object can be used to specify restrictions.

>>> no_extracting = pikepdf.Permissions(extract=False)

>>> pdf.save('encrypted.pdf', encryption=pikepdf.Encryption(
...      user="user password", owner="owner password", allow=no_extracting
... ))

Refer to our security documentation for more information on user/owner passwords and PDF permissions.

Running QPDF through Jobs

pikepdf can access all of the features of the qpdf command line program, and can even execute qpdf-like command lines.

>>> from pikepdf import Job

>>> Job(['pikepdf', '--check', '../tests/resources/fourpages.pdf'])

You can also specify jobs in QPDF Job JSON:

>>> job_json = {'inputFile': '../tests/resources/fourpages.pdf', 'check': ''}

>>> Job(job_json).run()

Next steps

Have a look at pikepdf topics that interest you, or jump to our detailed API reference…