Metadata-Version: 2.4
Name: caterpillar-py
Version: 2.6.3
Summary: Library to pack and unpack structurized binary data.
Author: MatrixEditor
Maintainer: MatrixEditor
Project-URL: Homepage, https://github.com/MatrixEditor/caterpillar
Project-URL: API-Docs, https://matrixeditor.github.io/caterpillar
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: typing-extensions
Provides-Extra: lzo
Requires-Dist: lzallright; extra == "lzo"
Provides-Extra: crypt
Requires-Dist: cryptography; extra == "crypt"
Provides-Extra: all
Requires-Dist: lzallright; extra == "all"
Requires-Dist: cryptography; extra == "all"

# Caterpillar - 🐛

[![python](https://img.shields.io/badge/Python-3.12+-blue?logo=python&logoColor=yellow)](https://www.python.org/downloads/)
![![Latest Version](https://pypi.org/project/caterpillar-py/)](https://img.shields.io/github/v/release/MatrixEditor/caterpillar.svg?logo=github&label=Latest+Version)
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![GitHub issues](https://img.shields.io/github/issues/MatrixEditor/caterpillar?logo=github)
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Caterpillar is a Python 3.12+ library to pack and unpack structurized binary
data (with support for 3.10+). It enhances the capabilities of [Python Struct](https://docs.python.org/3/library/struct.html)
by enabling direct class declaration. More information about the different configuration
options will be added in the future. Documentation is [here >](https://matrixeditor.github.io/caterpillar/).

*Caterpillar* is able to:

* Pack and unpack data just from processing Python class definitions (including support for powerful 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++!!

> [!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** using the `with` syntax in 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.


## Give me some code!

```python
@bitfield(order=LittleEndian)
class Header:
    version : 4                # 4bit integer
    valid   : 1                # 1bit flag (boolean)
    ident   : (8, CharFactory) # 8bit char
    # automatic alignment to 16bits

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

    _hash_begin : DigestField.begin("hash", Md5_Algo)   # custom actions, e.g. for hashes
    names       : CString[uint8::]                      # Sequences with prefixed, computed lengths
    hash        : Md5_Field("hash", verify=True) = None # automatic hash creation and verification + default value

# Instantiation (keyword-only arguments, magic is auto-inferred):
obj = Format(
    header=Header(version=2, valid=True, ident="F"),
    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 MAGIC0*\x01\x02\x00\x00\x00\x03foo\x02a\x00b\x00)\x9a...'

# Unpacking the binary data, reads as 'UNPACK Format FROM blob'
obj2 = unpack(Format, blob)
```

This library offers extensive functionality beyond basic struct handling. For further details
on its powerful features, explore the official [documentation](https://matrixeditor.github.io/caterpillar/),
[examples](./examples/), and [test cases](./test/).

## 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)

```bash
pip install caterpillar-py
```

### Python-only installation

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

### Installation + C-extension

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


## Starting Point

Please visit the [Documentation](https://matrixeditor.github.io/caterpillar/), 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](https://github.com/construct/construct)
* [kaitai_struct](https://github.com/kaitai-io/kaitai_struct)
* [hachoir](https://hachoir.readthedocs.io/en/latest/)
* [mrcrowbar](https://github.com/moralrecordings/mrcrowbar)

The documentation also provides a [Comparison](https://matrixeditor.github.io/caterpillar/reference/introduction.html#comparison)
to these approaches.

## License

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