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

A fork of ValvePython/vdf, which has apparently been abandoned.

Supports Python 3.6+ and PyPy 3.10

VDF is Valve's KeyValue text file format

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

Supported versions: kv1

Unsupported: kv2 and kv3

Install

WARNING: Only ValvePython's (out of date) version is on PyPI.

Installing directly from github repository:

# master
pip install "git+https://github.com/solsticegamestudios/vdf"

# specific version
pip install "git+https://github.com/solsticegamestudios/[email protected]"

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.

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