Easy configuration management in python
Project description
ConfMe: Configuration Made Easy 💖
ConfMe is a simple to use, production ready application configuration management library, which takes into consideration the following three thoughts:
- Access to configuration values must be safe at runtime. No
myconfig['value1']['subvalue']
anymore! - The configuration must be checked for consistency at startup e.g. type check, range check, ...
- Secrets shall be injectable from environment variables
ConfMe makes all these features possible with just a few type annotations on plain Python objects.
Installation
ConfMe can be installed from the official python package repository pypi
pip install confme
Or, if you're using pipenv:
pipenv install confme
Or, if you're using poetry:
poetry add confme
Basic Usage of confme
Define your config structure as plain python objects with type annotations:
from confme import BaseConfig
class DatabaseConfig(BaseConfig):
host: str
port: int
user: str
class MyConfig(BaseConfig):
name: str
database: DatabaseConfig
Create a configuration yaml file with the same structure as your configuration classes have:
name: "Database Application"
database:
host: "localhost"
port: 5000
user: "any-db-user"
Load the yaml file into your Python object structure and access it in a secure manner:
my_config = MyConfig.load('config.yaml')
print(f'Using database connection {my_config.database.host} '
f'on port {my_config.database.port}')
In the background the yaml file is parsed and mapped to the defined object structure. While mapping the values to object properties, type checks are performed. If a value is not available or is not of the correct type, an error is generated already when the configuration is loaded.
Supported Annotations
ConfMe is based on pydantic and supports all annotations provided by pydantic. The most important annotations are listed and explain bellow. For the whole list, please checkout Field Types:
Secret
With the Secret annotation you can inject secrets from environment variables directly into your configuration structure. This is especially handy when you're deploying applications by using docker. Therefore, let's extend the previous example with a Secret annotation:
from confme import BaseConfig
from confme.annotation import Secret
class DatabaseConfig(BaseConfig):
...
password: str = Secret('highSecurePassword')
Now set the password to the defined environment variable:
export highSecurePassword="This is my password"
Load your config and check for the injected password.
my_config = MyConfig.load('config.yaml')
print(f'My password is: {my_config.database.password}')
Range
ConfME supports OpenRange, ClosedRange and MixedRange values. The terms open and close are similar to open and closed intervals in mathematics. This means, if you want to include the lower and upper range use ClosedRange otherwise OpenRange:
ClosedRange(2, 3)
will include 2 and 3OpenRange(2, 3)
will not include 2 and 3
If you want to have a mixture of both, e.g. include 2 but exclude 3 use MixedRange:
MixedRange(ge=2, lt=3)
will include 2 but exclude 3
from confme import BaseConfig
from confme.annotation import ClosedRange
class DatabaseConfig(BaseConfig):
...
password: int = ClosedRange(2, 3)
Enum
If a Python Enum is set as type annotation, ConfMe expect to find the enum value in the configuration file.
from confme import BaseConfig
from enum import Enum
class DatabaseConnection(Enum):
TCP = 'tcp'
UDP = 'udp'
class DatabaseConfig(BaseConfig):
...
connection_type: DatabaseConnection
Overwrite Parameters from Command Line
Especially in the Data Science and Machine Learning area it is useful to pass certain parameters for experimental purposes as command line arguments. Therefore, all properties defined in the configuration classes are automatically offered as command line arguments in the following format:
my_program.py:
from confme import BaseConfig
class DatabaseConfig(BaseConfig):
host: str
port: int
user: str
class MyConfig(BaseConfig):
name: int
database: DatabaseConfig
config = MyConfig.load('test.yaml')
When you now start your program from the command line with the --help
argument, you get the full list of all configuration options:
$ python my_program.py --help
usage: my_program.py [-h] [--name NAME] [--database.host DATABASE.HOST] [--database.port DATABASE.PORT] [--database.user DATABASE.USER]
optional arguments:
-h, --help show this help message and exit
Configuration Parameters:
With the parameters specified bellow, the configuration values from the config file can be overwritten.
--name NAME
--database.host DATABASE.HOST
--database.port DATABASE.PORT
--database.user DATABASE.USER
LICENSE
ConfMe is released under the MIT license.
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