construct/construct

Construct: Declarative data structures for python that allow symmetric parsing and building

Python

1,020

1,837 commits

updated Apr 22, 2025

See the code

README

Construct 2.10
===================

Construct is a powerful **declarative** and **symmetrical** parser and builder for binary data.

Instead of writing *imperative code* to parse a piece of data, you declaratively define a *data structure* that describes your data. As this data structure is not code, you can use it in one direction to *parse* data into Pythonic objects, and in the other direction, to *build* objects into binary data.

The library provides both simple, atomic constructs (such as integers of various sizes), as well as composite ones which allow you form hierarchical and sequential structures of increasing complexity. Construct features **bit and byte granularity**, easy debugging and testing, an **easy-to-extend subclass system**, and lots of primitive constructs to make your work easier:

* Fields: raw bytes or numerical types
* Structs and Sequences: combine simpler constructs into more complex ones
* Bitwise: splitting bytes into bit-grained fields
* Adapters: change how data is represented
* Arrays/Ranges: duplicate constructs
* Meta-constructs: use the context (history) to compute the size of data
* If/Switch: branch the computational path based on the context
* On-demand (lazy) parsing: read and parse only what you require
* Pointers: jump from here to there in the data stream
* Tunneling: prefix data with a byte count or compress it


Example
---------

A ``Struct`` is a collection of ordered, named fields::

    >>> format = Struct(
    ...     "signature" / Const(b"BMP"),
    ...     "width" / Int8ub,
    ...     "height" / Int8ub,
    ...     "pixels" / Array(this.width * this.height, Byte),
    ... )
    >>> format.build(dict(width=3,height=2,pixels=[7,8,9,11,12,13]))
    b'BMP\x03\x02\x07\x08\t\x0b\x0c\r'
    >>> format.parse(b'BMP\x03\x02\x07\x08\t\x0b\x0c\r')
    Container(signature=b'BMP')(width=3)(height=2)(pixels=[7, 8, 9, 11, 12, 13])

A ``Sequence`` is a collection of ordered fields, and differs from ``Array`` and ``GreedyRange`` in that those two are homogenous::

    >>> format = Sequence(PascalString(Byte, "utf8"), GreedyRange(Byte))
    >>> format.build([u"lalaland", [255,1,2]])
    b'\nlalaland\xff\x01\x02'
    >>> format.parse(b"\x004361789432197")
    ['', [52, 51, 54, 49, 55, 56, 57, 52, 51, 50, 49, 57, 55]]

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construct/construct

Construct: Declarative data structures for python that allow symmetric parsing and building

Python

1,020

1,837 commits

updated Apr 22, 2025

See the code

README

Construct 2.10
===================

Construct is a powerful **declarative** and **symmetrical** parser and builder for binary data.

Instead of writing *imperative code* to parse a piece of data, you declaratively define a *data structure* that describes your data. As this data structure is not code, you can use it in one direction to *parse* data into Pythonic objects, and in the other direction, to *build* objects into binary data.

The library provides both simple, atomic constructs (such as integers of various sizes), as well as composite ones which allow you form hierarchical and sequential structures of increasing complexity. Construct features **bit and byte granularity**, easy debugging and testing, an **easy-to-extend subclass system**, and lots of primitive constructs to make your work easier:

* Fields: raw bytes or numerical types
* Structs and Sequences: combine simpler constructs into more complex ones
* Bitwise: splitting bytes into bit-grained fields
* Adapters: change how data is represented
* Arrays/Ranges: duplicate constructs
* Meta-constructs: use the context (history) to compute the size of data
* If/Switch: branch the computational path based on the context
* On-demand (lazy) parsing: read and parse only what you require
* Pointers: jump from here to there in the data stream
* Tunneling: prefix data with a byte count or compress it


Example
---------

A ``Struct`` is a collection of ordered, named fields::

    >>> format = Struct(
    ...     "signature" / Const(b"BMP"),
    ...     "width" / Int8ub,
    ...     "height" / Int8ub,
    ...     "pixels" / Array(this.width * this.height, Byte),
    ... )
    >>> format.build(dict(width=3,height=2,pixels=[7,8,9,11,12,13]))
    b'BMP\x03\x02\x07\x08\t\x0b\x0c\r'
    >>> format.parse(b'BMP\x03\x02\x07\x08\t\x0b\x0c\r')
    Container(signature=b'BMP')(width=3)(height=2)(pixels=[7, 8, 9, 11, 12, 13])

A ``Sequence`` is a collection of ordered fields, and differs from ``Array`` and ``GreedyRange`` in that those two are homogenous::

    >>> format = Sequence(PascalString(Byte, "utf8"), GreedyRange(Byte))
    >>> format.build([u"lalaland", [255,1,2]])
    b'\nlalaland\xff\x01\x02'
    >>> format.parse(b"\x004361789432197")
    ['', [52, 51, 54, 49, 55, 56, 57, 52, 51, 50, 49, 57, 55]]

Not written in Markdown, so it's shown here as plain text — view it formatted on GitHub.

Project health

Overall

2.4/10

Maintained

0/10

Code review

5/10
OpenSSF Scorecard

Latest release

2.10.70 · Nov 29, 2023

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