This section covers the object model pikepdf uses in more detail.
pikepdf.Object is a Python wrapper around a C++
which, as the name suggests, is a handle (or pointer) to a data structure in
memory, or possibly a reference to data that exists in a file. Importantly, an
object can be a scalar quantity (like a string) or a compound quantity (like a
list or dict, that contains other objects). The fact that the C++ class involved
here is an object handle is an implementation detail; it shouldn’t matter for
a pikepdf user.
The simplest types in PDFs are directly represented as Python types:
None stand for PDF integers, booleans and the “null”.
Decimal is used for floating point numbers in PDFs. If a
value in a PDF is assigned to a Python
float, pikepdf will convert it to
Types that are not directly convertible to Python are represented as
pikepdf.Object, a compound object that offers a superset of possible
methods, some of which only if the underlying type is suitable. Use the
EAFP idiom, or
isinstance to determine the type more precisely. This partly reflects the
fact that the PDF specification allows many data fields to be one of several
For convenience, the
repr() of a
pikepdf.Object will display a
Python expression that replicates the existing object (when possible), so it
>>> catalog_name = pdf.root.Type pikepdf.Name("/Catalog") >>> isinstance(catalog_name, pikepdf.Name) True >>> isinstance(catalog_name, pikepdf.Object) True
Making PDF objects¶
You may construct a new object with one of the classes:
pikepdf.Name- the type used for keys in PDF Dictionary objects
pikepdf.String- a text string (treated as
strdepending on context)
These may be thought of as subclasses of
pikepdf.Object. (Internally they
There are a few other classes for special PDF objects that don’t map to Python as neatly.
pikepdf.Operator- a special object involved in processing content streams
pikepdf.Stream- a special object similar to a
Dictionarywith binary data attached
pikepdf.InlineImage- an image that is embedded in content streams
The great news is that it’s often unnecessary to construct
objects when working with pikepdf. Python types are transparently converted to
the appropriate pikepdf object when passed to pikepdf APIs – when possible.
However, pikepdf sends
pikepdf.Object types back to Python on return calls,
in most cases, because pikepdf needs to keep track of objects that came from
Object lifecycle and memory management¶
As mentioned above, a
pikepdf.Object may reference data that is lazily
loaded from its source
pikepdf.Pdf. Closing the Pdf with
pikepdf.Pdf.close() will invalidate some objects, depending on whether
or not the data was loaded, and other implementation details that may change.
Generally speaking, a
pikepdf.Pdf should be held open until it is no
longer needed, and objects that were derived from it may or may not be usable
after it is closed.
Simple objects (booleans, integers, decimals,
None) are copied directly
to Python as pure Python objects.
For PDF stream objects, use
pikepdf.Object.read_bytes() to obtain a
copy of the object as pure bytes data, if this information is required after
closing a PDF.
When objects are copied from one
pikepdf.Pdf to another, the
underlying data is copied immediately into the target. As such it is possible
to merge hundreds of Pdf into one, keeping only a single source and the
target file open at a time.