skip to navigation
skip to content

vdf 2.3

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

Supported versions: kv1
Unsupported: kv2 and kv3


You can grab the latest release from or via pip

pip install vdf

Install the current dev version from github

pip install git+

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), ('key2', 222)]
>>> d['key']
>>> d[(0, key)]  # get the first duplicate
>>> d[(1, key)]  # get the second duplicate
>>> 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')]

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

>>> d.has_duplicates()
>>> d.remove_all_for('key')
>>> len(d)
>>> d.has_duplicates()
File Type Py Version Uploaded on Size
vdf-2.3-py2.py3-none-any.whl (md5) Python Wheel py2.py3 2017-03-26 10KB
vdf-2.3.tar.gz (md5) Source 2017-03-26 9KB