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Simple dataclasses configuration management for Python with hocon/json/yaml/properties/env-vars/dict support.

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Simple dataclasses configuration management for Python with hocon/json/yaml/properties/env-vars/dict support, based on awesome and lightweight pyhocon parsing library.

Getting started

Requires at least Python 3.8.

# pypi
pip install dataconf
poetry add dataconf

# remote master
pip install --upgrade git+
poetry add git+

# local repo/dev
poetry install
pre-commit install


import os
from dataclasses import dataclass, field
from typing import List, Dict, Text, Union
from dateutil.relativedelta import relativedelta
from datetime import datetime
import dataconf

conf = """
str_name = test
str_name = ${?HOME}
dash-to-underscore = true
float_num = 2.2
iso_datetime = "2000-01-01T20:00:00"
# this is a comment
list_data = [
nested {
    a = test
    b : 1
nested_list = [
        a = test1
        b : 2.5
duration = 2s
union = 1
people {
    name = Thailand
zone {
    area_code = 42

class AbstractBaseClass:
class Person(AbstractBaseClass):
    name: Text
class Zone(AbstractBaseClass):
    area_code: int

class Nested:
    a: Text
    b: float

class Config:
    str_name: Text
    dash_to_underscore: bool
    float_num: float
    iso_datetime: datetime
    list_data: List[Text]
    nested: Nested
    nested_list: List[Nested]
    duration: relativedelta
    union: Union[Text, int]
    people: AbstractBaseClass
    zone: AbstractBaseClass
    default: Text = 'hello'
    default_factory: Dict[Text, Text] = field(default_factory=dict)

print(dataconf.string(conf, Config))
# Config(
#   str_name='/users/root',
#   dash_to_underscore=True,
#   float_num=2.2,
#   list_data=['a', 'b'],
#   nested=Nested(a='test'),
#   nested_list=[Nested(a='test1', b=2.5)],
#   duration=relativedelta(seconds=+2), 
#   union=1, 
#   people=Person(name='Thailand'), 
#   zone=Zone(area_code=42),
#   default='hello', 
#   default_factory={}
# )

class Example:
    hello: string
    world: string

os.environ['DC_WORLD'] = 'monde'

# Example(hello='bonjour',world='monde')


import dataconf

conf = dataconf.string('{ name: Test }', Config)
conf = dataconf.env('PREFIX_', Config)
conf = dataconf.dict({'name': 'Test'}, Config)
conf = dataconf.url('', Config)
conf = dataconf.file('confs/test.{hocon,json,yaml,properties}', Config)

# Aggregation
conf = dataconf.multi.string(...).env(...).url(...).file(...).dict(...).on(Config)

# Same api as Python json/yaml packages (e.g. `load`, `loads`, `dump`, `dumps`)
conf = dataconf.load('confs/test.{hocon,json,yaml,properties}', Config)
dataconf.dump('confs/test.hocon', conf, out='hocon')
dataconf.dump('confs/test.json', conf, out='json')
dataconf.dump('confs/test.yaml', conf, out='yaml')
dataconf.dump('confs/', conf, out='properties')

For full HOCON capabilities see here.

Env dict/list parsing

PREFIX_NESTED_="{ name: Test }"
PREFIX_SUB_="{ value: ${PREFIX_VAR} }"

is equivalent to

    var = a
    var_name = b
    test {
        name = c
    ls = [
    lsls = [
    lsob = [
            name = g
    nested {
        # parse nested config by suffixing env var with `_`
        name: Test
    sub {
        # will have value "a" at parsing, useful for aliases
        value = ${PREFIX_VAR}

Note that when using .env source, the strict mode is disabled and value might be casted.

CLI usage

Can be used for validation or converting between supported file formats (-o).

dataconf -c confs/test.hocon -m tests.configs -d TestConf -o hocon
# dataconf.exceptions.TypeConfigException: expected type <class 'datetime.timedelta'> at .duration, got <class 'int'>

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