TLV Python Parser - Version 0.7.1
A Tag-Length-Value (also known as Type-Length-Value) is an encoding scheme used for many protocols.
The tag is fixed in size (can be set from 1 to 4 bytes).
The length is automatically determined by how many bytes it would take to represent the size of the value by default,
but could be set to a fixed size (from 1 to 4 bytes). The value field is of variable size.
The fields are:
- Tag: An alphanumeric code that represents the kind of field the object represents;
- Length: Size of the value field (in bytes);
- Value: Variable-sized series of bytes which contains data for this field object.
Advantages of using TLV:
- Sequences are usually easy to parse;
- Unknown tags or elements can be skipped or ignored, so new versions can be added without a problem;
- Elements can be placed in any order;
- New elements can be created without breaking the protocol itself or the parsing function.
For more information, you can see: https://en.wikipedia.org/wiki/Type-length-value
Installation
You can install directly from PyPI:
pip install uttlv
Or download the source code and install using pip:
pip install .
How to use
To start using this package, just import the package and create an object
from uttlv import TLV
t = TLV()
To add a tag to object, do it like a dict value:
t[0x01] = 10
t[0x02] = 'test'
t[0x03] = bytes([1, 2, 3])
another_one = TLV()
another_one[0x05] = 234
t[0x04] = another_one
A tag can only be int, str, bytes or a TLV itself. Any other type will raise a TypeError exception.
If a tag is inserted and another object with same tag value already exists on the object, the tag will be overriden with the new value.
To get the underlying array, just call to_byte_array()
method:
arr = t.to_byte_array()
print('TLV:', arr)
Parse
To parse an array, just call the method parse_array()
:
t = TLV()
data = bytes([0x03, 0x00, 0x04, 0x00, 0x00, 0x00, 0x0A])
t.parse_array(data)
Pretty print
If you call tree()
, the object will create a string with a tree-like structure to print:
from prtlv import TLV
t = TLV()
t[0x01] = 10
print('Value:\n', t.tree())
Tag map
You can also add a dictionary to map a tag to its underline class type, so it's showed as correct type
instead of a bytearray.
The dictionary must have all keys as the tag values and its respective values as the class type of the
tag:
config = {
0x01: {TLV.Config.Type: int, TLV.Config.Name: 'NUM_POINTS'},
0x02: {TLV.Config.Type: int, TLV.Config.Name: 'IDLE_PERIOD'},
0x03: {TLV.Config.Type: str, TLV.Config.Name: 'NAME'},
0x04: {TLV.Config.Type: str, TLV.Config.Name: 'CITY'},
0x05: {TLV.Config.Type: bytes, TLV.Config.Name: 'VERSION'},
0x06: {TLV.Config.Type: bytes, TLV.Config.Name: 'DATA'},
0x07: {TLV.Config.Type: TLV, TLV.Config.Name: 'RELATED'},
0x08: {TLV.Config.Type: TLV, TLV.Config.Name: 'COMMENT'},
0x09: {TLV.Config.Type: TLV, TLV.Config.Name: 'Empty'}
}
TLV.set_global_tag_map(config)
t = TLV()
t.set_local_tag_map(config)
For now, only 'int', 'str', 'bytes', 'TLV', and a dictionary are accepted as valid classes. Any other class will raise
AttributeError.
If a tag map is configured, one can use the tag name to access its value:
t = TLV()
t['NUM_POINTS'] = 10
print(t['NUM_POINTS'])
Nested tag maps can be configured by replacing the configured type with another configuration dictionary:
config = {
0x01: {TLV.Config.Name: 'FIRST_NEST', TLV.Config.Type: {
0x01: {TLV.Config.Name: 'SECOND_NEST', TLV.Config.Type: {
0x01: {TLV.Config.Name: 'THIRD_NEST', TLV.Config.Type: int}
}}
}}
}
And also can print it with all tag names instead of values:
t.tree(use_names=True)
You can access also the tags directly:
t = TLV()
t['NUM_POINTS'] = 10
print(t.NUM_POINTS)
By default, a field defined as type str in the tag map would be encoded or decoded as utf-8. The encoder can be replaced
to use utf16, utf32 or ascii by setting it in
uttlv.tlv.ALLOWED_TYPES[str] = uttlv.tlv.encoder.Utf16Encoder
or
uttlv.tlv.ALLOWED_TYPES[str] = uttlv.tlv.encoder.Utf32Encoder
or
uttlv.tlv.ALLOWED_TYPES[str] = uttlv.tlv.encoder.AsciiEncoder
respectively.
Iterator
You can iterate through the available tags inside a TLV object by using iter()
:
t = TLV()
t.parse_array(bytes(command_data))
for command in t:
pass