caterpillar-py 2.4.5

Library to pack and unpack structurized binary data.

Caterpillar - 🐛

[!WARNING] This project is still in beta/testing phase. Expect bugs, naming changes and errors while using this library. C API Reference is WIP, C extensions are supported since v2.1.0.

[!NOTE] Python 3.14 breaks with statements in class definitions since __annotations__ are added at the end of a class definition. Therefore, Digest and conditional statements ARE NOT SUPPORTED in using the with syntax Python 3.14+. As of version 2.4.5 the Digest class has a counterpart (DigestField), which can be used to manually specify a digest without the need of a ẁith statement.

Caterpillar is a Python 3.12+ library to pack and unpack structurized binary data. It enhances the capabilities of Python Struct by enabling direct class declaration. More information about the different configuration options will be added in the future. Documentation is here >.

Caterpillar is able to:

• Pack and unpack data just from processing Python class definitions (including support for bitfields, c++-like templates and c-like unions!),
• apply a wide range of data types (with endianess and architecture configuration),
• dynamically adapt structs based on their inheritance layout,
• reduce the used memory space using __slots__,
• allowing you to place conditional statements into class definitions,
• insert proper types into the class definition to support documentation and
• it helps you to create cleaner and more compact code.
• You can even extend Caterpillar and write your parsing logic in C or C++!!

Give me some code!

from caterpillar.py import *

@struct(order=LittleEndian)
class Format:
    magic: b"ITS MAGIC"       # Supports string and byte constants directly
    a: uint8                  # Primitive data types
    b: int32
    length: uint8             # String fields with computed lengths
    name: String(this.length) #  -> you can also use Prefixed(uint8)

    # wraps all following fields and creates a new attr
    # only for Python <= 3.13
    with Md5(name="hash", verify=True):
        # Sequences with prefixed, computed lengths
        names: CString[uint8::]


# Instantiation (keyword-only arguments, magic is auto-inferred):
obj = Format(a=1, b=2, length=3, name="foo", names=["a", "b"])
# Packing the object, reads as 'PACK obj FROM Format'
# objects of struct classes can be packed right away
blob = pack(obj, Format)
# results in: b'ITS MAGIC\x01\x02\x00\x00\x00\x03foo\x02a\x00b\x00\xf55...

# Unpacking the binary data, reads as 'UNPACK Format FROM blob'
obj2 = unpack(Format, blob)
assert obj2.hash == obj.hash

This library offers extensive functionality beyond basic struct handling. For further details on its powerful features, explore the official documentation, examples, and test cases.

Installation

[!NOTE] As of Caterpillar v2.1.2 it is possible to install the library without the need of compiling the C extension.

PIP installation (Python-only)

pip install caterpillar-py

Python-only installation

pip install "caterpillar[all]@git+https://github.com/MatrixEditor/caterpillar"

C-extension installation

pip install "caterpillar[all]@git+https://github.com/MatrixEditor/caterpillar/#subdirectory=src/ccaterpillar"

Starting Point

Please visit the Documentation, it contains a complete tutorial on how to use this library.

Other Approaches

A list of similar approaches to parsing structured binary data with Python can be taken from below:

• construct
• kaitai_struct
• hachoir
• mrcrowbar

The documentation also provides a Comparison to these approaches.

License

Distributed under the GNU General Public License (V3). See License for more information.