vdf 3.2

Library for working with Valve's VDF text format

Pure python module for (de)serialization to and from VDF that works just like json.

Tested and works on python2.7, python3.3+, pypy and pypy3.

VDF is Valve’s KeyValue text file format

https://developer.valvesoftware.com/wiki/KeyValues

Supported versions: kv1

Unsupported: kv2 and kv3

Install

You can grab the latest release from https://pypi.org/project/vdf/ or via pip

pip install vdf

Install the current dev version from github

pip install git+https://github.com/ValvePython/vdf

Problems & solutions

• There are known files that contain duplicate keys. This is supported the format and makes mapping to dict impossible. For this case the module provides vdf.VDFDict that can be used as mapper instead of dict. See the example section for details.

• By default de-serialization will return a dict, which doesn’t preserve nor guarantee key order due to hash randomization. If key order is important then I suggest using collections.OrderedDict, or vdf.VDFDict.

Example usage

For text representation

import vdf

# parsing vdf from file or string
d = vdf.load(open('file.txt'))
d = vdf.loads(vdf_text)
d = vdf.parse(open('file.txt'))
d = vdf.parse(vdf_text)

# dumping dict as vdf to string
vdf_text = vdf.dumps(d)
indented_vdf = vdf.dumps(d, pretty=True)

# dumping dict as vdf to file
vdf.dump(d, open('file2.txt','w'), pretty=True)

For binary representation

d = vdf.binary_loads(vdf_bytes)
b = vdf.binary_dumps(d)

# alternative format - VBKV

d = vdf.binary_loads(vdf_bytes, alt_format=True)
b = vdf.binary_dumps(d, alt_format=True)

# VBKV with header and CRC checking

d = vdf.vbkv_loads(vbkv_bytes)
b = vdf.vbkv_dumps(d)

Using an alternative mapper

d = vdf.loads(vdf_string, mapper=collections.OrderedDict)
d = vdf.loads(vdf_string, mapper=vdf.VDFDict)

VDFDict works much like the regular dict, except it handles duplicates and remembers insert order. Additionally, keys can only be of type str. The most important difference is that when trying to assigning a key that already exist it will create a duplicate instead of reassign the value to the existing key.

>>> d = vdf.VDFDict()
>>> d['key'] = 111
>>> d['key'] = 222
>>> d
VDFDict([('key', 111), ('key', 222)])
>>> d.items()
[('key', 111), ('key', 222)]
>>> d['key']
111
>>> d[(0, 'key')]  # get the first duplicate
111
>>> d[(1, 'key')]  # get the second duplicate
222
>>> d.get_all_for('key')
[111, 222]

>>> d[(1, 'key')] = 123  # reassign specific duplicate
>>> d.get_all_for('key')
[111, 123]

>>> d['key'] = 333
>>> d.get_all_for('key')
[111, 123, 333]
>>> del d[(1, 'key')]
>>> d.get_all_for('key')
[111, 333]
>>> d[(1, 'key')]
333

>>> print vdf.dumps(d)
"key" "111"
"key" "333"

>>> d.has_duplicates()
True
>>> d.remove_all_for('key')
>>> len(d)
0
>>> d.has_duplicates()
False