Metadata-Version: 2.4
Name: envier
Version: 0.6.1
Summary: Python application configuration via the environment
Project-URL: Homepage, https://github.com/DataDog/envier
Author-email: Datadog <dev@datadoghq.com>
License: MIT License
        
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License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.7
Provides-Extra: mypy
Requires-Dist: mypy; extra == 'mypy'
Description-Content-Type: text/markdown

<h1 align="center">Envier</h1>
<h2 align="center">Python application configuration from the environment</h2>

## Synopsis

Envier is a Python library for extracting configuration from environment
variables in a declarative and (eventually) 12-factor-app-compliant way.


## Usage

The following example shows how to declare the configuration for an application
that uses the `MYAPP_DEBUG`, `MYAPP_SERVICE_HOST` and `MYAPP_SERVICE_PORT`
variables from the environment.

~~~ python
>>> from envier import Env
>>> 
>>> class GlobalConfig(Env):
>>>     __prefix__ = "myapp"
>>>     
>>>     debug_mode = Env.var(bool, "debug", default=False)
>>> 
>>>     service_host = Env.var(str, "service.host", default="localhost")
>>>     service_port = Env.var(int, "service.port", default=3000)
>>> 
>>>     _is_default_port = Env.der(bool, lambda c: c.service_port == c.spec.service_port.default)
>>> 
>>> config = GlobalConfig()
>>> config.service_port
3000
>>> config._is_default_port
True
~~~

Configurations can also be nested to create namespaces:

~~~ python
>>> from envier import Env
>>> 
>>> class ServiceConfig(Env):
>>>     __prefix__ = "service"
>>> 
>>>     host = Env.var(str, "host", default="localhost")
>>>     port = Env.var(int, "port", default=3000)
>>> 
>>> class GlobalConfig(Env):
>>>     __prefix__ = "myapp"
>>>     
>>>     debug_mode = Env.var(bool, "debug", default=False)
>>> 
>>>     service = ServiceConfig
>>> 
>>> config = GlobalConfig()
>>> config.service.port
3000
~~~

The same configuration can be obtained with implicit nesting by declaring the
`ServiceConfig` subclass inside `GlobalConfig`, and setting the class attribute
`__item__` to the name of the item the sub-configuration should be assigned to,
viz.

~~~ python
>>> from envier import Env
>>> 
>>> class GlobalConfig(Env):
>>>     __prefix__ = "myapp"
>>>     
>>>     debug_mode = Env.var(bool, "debug", default=False)
>>> 
>>>     class ServiceConfig(Env):
>>>         __item__ = __prefix__ = "service"
>>>         
>>>         host = Env.var(str, "host", default="localhost")
>>>         port = Env.var(int, "port", default=3000)
>>> 
>>> config = GlobalConfig()
>>> config.service.port
3000
~~~


## Type Checking

The library ships with a `mypy` plugin to allow for type checking. If you want
to use it, either install the library with the `mypy` extra or ensure that
`mypy` is installed, and then add `envier.mypy` to the list of extra plugins in
the `mypy` configuration.


## Roadmap

- Add support for environment files.
- Rely on type hints as support for older versions of Python is dropped.
- Derivations might require an evaluation order.
