Implementation of key-value pair based configuration for Python applications.
Features:
- support for most common sources of application settings
- support for overriding settings in sequence
- support for nested structures and lists, using attribute notation
- strategy to use environment specific settings
- features to handle secrets and values stored in the user folder, for local development
- features to support validation of configuration items, for example using
pydantic
, or user defined classes
This library is freely inspired by .NET Core Microsoft.Extensions.Configuration
(ref. MSDN documentation, Microsoft Extensions Configuration Deep Dive).
The main class is influenced by Luciano Ramalho`s example of JSON structure explorer using attribute notation, in his book Fluent Python.
essentials-configuration
provides a way to handle configuration roots
composed of several layers, such as configuration files and environment
variables. Layers are applied in order and can override each others' values,
enabling different scenarios like configuration by environment and system
instance.
- toml files
- yaml files
- json files
- ini files
- environment variables
- secrets stored in the user folder, for development purpose
- dictionaries
- keys and values
- Azure Key Vault, using essentials-configuration-keyvault
- custom sources, implementing the
ConfigurationSource
interface
pip install essentials-configuration
To install with support for YAML
configuration files:
pip install essentials-configuration[yaml]
To install with support for YAML
configuration files and the CLI
to handle
user secrets:
pip install essentials-configuration[full]
- Azure Key Vault secrets configuration source: essentials-configuration-keyvault
Please read the list of examples in the examples folder. Below are reported some of the examples that are tested in this repository.
from config.common import ConfigurationBuilder
from config.env import EnvVars
from config.toml import TOMLFile
builder = ConfigurationBuilder(
TOMLFile("settings.toml"),
EnvVars(prefix="APP_")
)
config = builder.build()
For example, if the TOML file contains the following contents:
title = "TOML Example"
[owner]
name = "Tom Preston-Werner"
And the environment has a variable such as APP_OWNER__NAME=AAA
, the owner
name from the TOML file gets overridden by the env variable:
>>> config
<Configuration {'title': '...', 'owner': '...'}>
>>> config.title
'TOML Example'
>>> config.owner.name
'AAA'
In the following example, configuration values will include the structure
inside the file settings.json
and environment variables whose name starts
with "APP_". Settings are applied in order, so environment variables with
matching name override values from the json
file.
from config.common import ConfigurationBuilder
from config.json import JSONFile
from config.env import EnvVars
builder = ConfigurationBuilder(
JSONFile("settings.json"),
EnvVars(prefix="APP_")
)
config = builder.build()
For example, if the JSON file contains the following contents:
{
"logging": {
"level": "INFO"
},
"example": "Hello World",
"foo": "foo"
}
And the environment has a variable named APP_foo=AAA
:
>>> config
<Configuration {'logging': '...', 'example': '...', 'foo': '...'}>
>>> config.foo
'AAA'
>>> config.logging.level
'INFO'
In this example, configuration will include anything inside a file
settings.yaml
and environment variables. Settings are applied in order, so
environment variables with matching name override values from the yaml
file
(using the yaml
source requires also PyYAML
package).
from config.common import ConfigurationBuilder
from config.env import EnvVars
from config.yaml import YAMLFile
builder = ConfigurationBuilder()
builder.add_source(YAMLFile("settings.yaml"))
builder.add_source(EnvVars())
config = builder.build()
In this example, if an environment variable with name APP_ENVIRONMENT
and
value dev
exists, and a configuration file with name settings.dev.yaml
is
present, it is read to override values configured in settings.yaml
file.
import os
from config.common import ConfigurationBuilder
from config.env import EnvVars
from config.yaml import YAMLFile
environment_name = os.environ["APP_ENVIRONMENT"]
builder = ConfigurationBuilder(
YAMLFile("settings.yaml"),
YAMLFile(f"settings.{environment_name}.yaml", optional=True)
)
config = builder.build()
from config.common import ConfigurationBuilder
from config.env import EnvVars
builder = ConfigurationBuilder()
builder.add_source(EnvVars(prefix="APP_"))
config = builder.build()
INI files are parsed using the built-in configparser
module, therefore
support [DEFAULT]
section; all values are kept as strings.
from config.common import ConfigurationBuilder
from config.ini import INIFile
builder = ConfigurationBuilder()
builder.add_source(INIFile("settings.ini"))
config = builder.build()
from config.common import ConfigurationBuilder
builder = ConfigurationBuilder()
builder.add_map({"host": "localhost", "port": 8080})
builder.add_map({"hello": "world", "example": [{"id": 1}, {"id": 2}]})
config = builder.build()
assert config.host == "localhost"
assert config.port == 8080
assert config.hello == "world"
assert config.example[0].id == 1
assert config.example[1].id == 2
from config.common import ConfigurationBuilder
builder = ConfigurationBuilder()
builder.add_map({"host": "localhost", "port": 8080})
builder.add_value("port", 44555)
config = builder.build()
assert config.host == "localhost"
assert config.port == 44555
The library provides a strategy to handle secrets during local development, storing them into the user folder.
The following example shows how secrets can be configured for a project:
config settings init
config settings set "Foo" "Some secret value"
Secrets are organized by project, and the project information is obtained from
pyproject.toml
files (from the project.name
property). If pyproject.toml
file does not exist, one is generated automatically with a random name.
Then, from a Python app, it's possible to load the secrets from the user folder:
from config.common import ConfigurationBuilder
from config.json import JSONFile
from config.secrets import UserSecrets
builder = ConfigurationBuilder(JSONFile("settings.json"), UserSecrets())
config = builder.build()
print(config)
# config contains both values from `settings.json`, and secrets read from the user
# folder
Secrets are optional and should be used only for local development, they are stored in unencrypted form in the user's folder.
Production apps should use dedicated services to handle secrets, like Azure Key Vault, AWS Secrets Manager, or similar services. For Azure Key Vault, an implementation is provided in essentials-configuration-keyvault.
User settings (stored in the user's folder) can be handled using the provided config
CLI.
These settings can be useful to store secrets and other values during local development, or in general when working with desktop applications.
It is possible to override nested values by environment variables or dictionary keys using the following notation for sub properties:
- keys separated by colon ":", such as
a:d:e
- keys separated by "__", such as
a__d__e
from config.common import ConfigurationBuilder, MapSource
builder = ConfigurationBuilder(
MapSource(
{
"a": {
"b": 1,
"c": 2,
"d": {
"e": 3,
"f": 4,
},
}
}
)
)
config = builder.build()
assert config.a.b == 1
assert config.a.d.e == 3
assert config.a.d.f == 4
builder.add_value("a:d:e", 5)
config = builder.build()
assert config.a.d.e == 5
assert config.a.d.f == 4
import os
from config.common import ConfigurationBuilder, MapSource
from config.env import EnvVars
builder = ConfigurationBuilder(
MapSource(
{
"a": {
"b": 1,
"c": 2,
"d": {
"e": 3,
"f": 4,
},
}
}
)
)
config = builder.build()
assert config.a.b == 1
assert config.a.d.e == 3
assert config.a.d.f == 4
# NB: if an env variable such as:
# a:d:e=5
# or...
# a__d__e=5
#
# is defined, it overrides the value from the dictionary
os.environ["a__d__e"] = "5"
builder.sources.append(EnvVars())
config = builder.build()
assert config.a.d.e == "5"
import os
from config.common import ConfigurationBuilder, MapSource
from config.env import EnvVars
builder = ConfigurationBuilder(
MapSource(
{
"b2c": [
{"tenant": "1"},
{"tenant": "2"},
{"tenant": "3"},
]
}
),
EnvVars(),
)
os.environ["b2c__0__tenant"] = "5"
config = builder.build()
assert config.b2c[0].tenant == "5"
assert config.b2c[1].tenant == "2"
assert config.b2c[2].tenant == "3"
To bind configuration sections with types checking, for example to use pydantic
to
validate application settings, use the config.bind
method like in
the following example:
# example-01.yaml
foo:
value: "foo"
x: 100
# example
from pydantic import BaseModel
from config.common import ConfigurationBuilder
from config.yaml import YAMLFile
class FooSettings(BaseModel):
value: str
x: int
builder = ConfigurationBuilder(YAMLFile("example-01.yaml"))
config = builder.build()
# the bind method accepts a variable number of fragments to
# obtain the configuration section that should be used to instantiate the given type
foo_settings = config.bind(FooSettings, "foo")
assert isinstance(foo_settings, FooSettings)
assert foo_settings.value == "foo"
assert foo_settings.x == 100
The goal of this package is to provide a way to handle configuration roots, fetching and composing settings from different sources, usually happening once at application's start.
The library implements only a synchronous API and fetching of application settings atomically (it doesn't support generators), like application settings fetched from INI, JSON, or YAML files that are read once in memory entirely. An asynchronous API is currently out of the scope of this library, since its primary use case is to fetch configuration values once at application's start.