Skip to main content

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

Project description

Dataconf

Actions Status PyPI version

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

Getting started

Requires at least Python 3.8.

# pypi
pip install dataconf
poetry add dataconf

# remote master
pip install --upgrade git+https://github.com/zifeo/dataconf.git
poetry add git+https://github.com/zifeo/dataconf.git

# local repo/dev
poetry install
pre-commit install

Usage

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 = [
    a
    b
]
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:
    pass
    
@dataclass
class Person(AbstractBaseClass):
    name: Text
        
@dataclass
class Zone(AbstractBaseClass):
    area_code: int

@dataclass
class Nested:
    a: Text
    b: float

@dataclass
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={}
# )

@dataclass
class Example:
    hello: str
    world: str
    foo: List[str]

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

print(
    dataconf
    .multi
    .url('https://raw.githubusercontent.com/zifeo/dataconf/main/confs/simple.hocon')
    .env('DC')
    .on(Example)
)
# Example(hello='bonjour',world='monde')

API

import dataconf

conf = dataconf.string('{ name: Test }', Config)
conf = dataconf.string('name:\n\tvalue: Test', Config, loader=dataconf.YAML)  # dataconf.HOCON by default
conf = dataconf.env('PREFIX_', Config)
conf = dataconf.dict({'name': 'Test'}, Config)
conf = dataconf.url('https://raw.githubusercontent.com/zifeo/dataconf/master/confs/test.hocon', Config)  # hocon, json, yaml, properties
conf = dataconf.file('confs/test.hocon', Config)  # hocon, json, yaml, properties
conf = dataconf.cli(sys.argv, Config)

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

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

For full HOCON capabilities see here.

Parse env vars

PREFIX_VAR=a
PREFIX_VAR_NAME=b
PREFIX_TEST__NAME=c
PREFIX_LS_0=d
PREFIX_LS_1=e
PREFIX_LSLS_0_0=f
PREFIX_LSOB_0__NAME=g
PREFIX_NESTED_="{ name: Test }"
PREFIX_SUB_="{ value: ${PREFIX_VAR} }"

is equivalent to

{
    var = a
    var_name = b
    test {
        name = c
    }
    ls = [
        d
        e
    ]
    lsls = [
        [
            f
        ]
    ]
    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.

Parse CLI arguments

Same as env vars parse (dashes are converted to underscore, e.g. TEST_A--test-a).

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'>

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dataconf-2.4.0.tar.gz (15.8 kB view hashes)

Uploaded Source

Built Distribution

dataconf-2.4.0-py3-none-any.whl (15.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page