struct – Working with Binary Data - Python Module of the Week
struct – Working with Binary Data ?
Purpose: Convert between strings and binary data. Available In: 1.4 and later The struct module includes functions for converting between strings of bytes and native Python data types such as numbers and strings.
Functions vs. Struct Class ?
There are a set of module-level functions for working with structured values, and there is also the Struct class (new in Python 2.5). Format specifiers are converted from their string format to a compiled representation, similar to the way regular expressions are. The conversion takes some resources, so it is typically more efficient to do it once when creating a Struct instance and call methods on the instance instead of using the module-level functions. All of the examples below use the Struct class.
Packing and Unpacking ?
Structs support packing data into strings, and unpacking data from strings using format specifiers made up of characters representing the type of the data and optional count and endian-ness indicators. For complete details, refer to the standard library documentation .
In this example, the format specifier calls for an integer or long value, a two character string, and a floating point number. The spaces between the format specifiers are included here for clarity, and are ignored when the format is compiled.
import struct import binascii values = ( 1 , 'ab' , 2.7 ) s = struct . Struct ( 'I 2s f' ) packed_data = s . pack ( * values ) print 'Original values:' , values print 'Format string :' , s . format print 'Uses :' , s . size , 'bytes' print 'Packed Value :' , binascii . hexlify ( packed_data )The example converts the packed value to a sequence of hex bytes for printing with binascii.hexlify() , since some of the characters are nulls.
$ python struct_pack.py Original values: (1, 'ab', 2.7) Format string : I 2s f Uses : 12 bytes Packed Value : 0100000061620000cdcc2c40If we pass the packed value to unpack() , we get basically the same values back (note the discrepancy in the floating point value).
import struct import binascii packed_data = binascii . unhexlify ( '0100000061620000cdcc2c40' ) s = struct . Struct ( 'I 2s f' ) unpacked_data = s . unpack ( packed_data ) print 'Unpacked Values:' , unpacked_data$ python struct_unpack.py Unpacked Values: (1, 'ab', 2.700000047683716)Endianness ?
By default values are encoded using the native C library notion of “endianness”. It is easy to override that choice by providing an explicit endianness directive in the format string.
import struct import binascii values = ( 1 , 'ab' , 2.7 ) print 'Original values:' , values endianness = [ ( '@' , 'native, native' ), ( '=' , 'native, standard' ), ( '<' , 'little-endian' ), ( '>' , 'big-endian' ), ( '!' , 'network' ), ] for code , name in endianness : s = struct . Struct ( code + ' I 2s f' ) packed_data = s . pack ( * values ) print print 'Format string :' , s . format , 'for' , name print 'Uses :' , s . size , 'bytes' print 'Packed Value :' , binascii . hexlify ( packed_data ) print 'Unpacked Value :' , s . unpack ( packed_data )$ python struct_endianness.py Original values: (1, 'ab', 2.7) Format string : @ I 2s f for native, native Uses : 12 bytes Packed Value : 0100000061620000cdcc2c40 Unpacked Value : (1, 'ab', 2.700000047683716) Format string : = I 2s f for native, standard Uses : 10 bytes Packed Value : 010000006162cdcc2c40 Unpacked Value : (1, 'ab', 2.700000047683716) Format string : < I 2s f for little-endian Uses : 10 bytes Packed Value : 010000006162cdcc2c40 Unpacked Value : (1, 'ab', 2.700000047683716) Format string : > I 2s f for big-endian Uses : 10 bytes Packed Value : 000000016162402ccccd Unpacked Value : (1, 'ab', 2.700000047683716) Format string : ! I 2s f for network Uses : 10 bytes Packed Value : 000000016162402ccccd Unpacked Value : (1, 'ab', 2.700000047683716)Buffers ?
Working with binary packed data is typically reserved for highly performance sensitive situations or passing data into and out of extension modules. In such situations, you can optimize by avoiding the overhead of allocating a new buffer for each packed structure. The pack_into() and unpack_from() methods support writing to pre-allocated buffers directly.
import struct import binascii s = struct . Struct ( 'I 2s f' ) values = ( 1 , 'ab' , 2.7 ) print 'Original:' , values print print 'ctypes string buffer' import ctypes b = ctypes . create_string_buffer ( s . size ) print 'Before :' , binascii . hexlify ( b . raw ) s . pack_into ( b , 0 , * values ) print 'After :' , binascii . hexlify ( b . raw ) print 'Unpacked:' , s . unpack_from ( b , 0 ) print print 'array' import array a = array . array ( 'c' , ' \0 ' * s . size ) print 'Before :' , binascii . hexlify ( a ) s . pack_into ( a , 0 , * values ) print 'After :' , binascii . hexlify ( a ) print 'Unpacked:' , s . unpack_from ( a , 0 )The size attribute of the Struct tells us how big the buffer needs to be.
$ python struct_buffers.py Original: (1, 'ab', 2.7) ctypes string buffer Before : 000000000000000000000000 After : 0100000061620000cdcc2c40 Unpacked: (1, 'ab', 2.700000047683716) array Before : 000000000000000000000000 After : 0100000061620000cdcc2c40 Unpacked: (1, 'ab', 2.700000047683716)
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