The dynamic configurator for your Python Project
Project description
dynaconf - The dynamic configurator for your Python Project
dynaconf a layered configuration system for Python applications - with strong support for 12-factor applications and extensions for Flask and Django.
Read the Full Documentation at: http://dynaconf.readthedocs.io/
Features
- Strict separation of settings from code (following 12-factor applications Guide).
- Define comprehensive default values.
- Store parameters in multiple file formats (.toml, .json, .yaml, .ini and .py).
- Sensitive secrets like tokens and passwords can be stored in safe places like
.secretsfile orvault server. - Parameters can optionally be stored in external services like Redis server.
- Simple feature flag system.
- Layered [environment] system.
- Environment variables can be used to override parameters.
- Support for
.envfiles to automate the export of environment variables. - Correct data types (even for environment variables).
- Have only one canonical settings module to rule all your instances.
- Drop in extension for Flask
app.configobject. - Drop in extension for Django
conf.settingsobject. - Powerful $ dynaconf CLI to help you manage your settings via console.
- Customizable Validation System to ensure correct config parameters.
- Allow the change of dynamic parameters on the fly without the need to redeploy your application.
Install Dynaconf
Python 3.x is required
# Default installation supports .toml, .py and .json file formats
# and also overriding from environment variables (.env supported)
$ pip3 install dynaconf
Getting Started
Installation
Python 3.x is required
$ pip install dynaconf
Default installation supports .toml, .py and .json file formats and also environment variables (.env supported) - to support YAML add
pip install dynaconf[yaml]orpip install dynaconf[all]
Usage
Accessing config variables in your Python application
In your Python program wherever you need to access a settings variable you use the canonical object from dynaconf import settings:
NOTE: Read the full documentation for more examples like using Dynaconf with Flask or Django
Example of program to connect to some database
from some.db import Client
from dynaconf import settings
conn = Client(
username=settings.USERNAME, # attribute style access
password=settings.get('PASSWORD'), # dict get style access
port=settings['PORT'], # dict item style access
timeout=settings.as_int('TIMEOUT'), # Forcing casting if needed
host=settings.get('HOST', 'localhost') # Providing defaults
)
Where the settings values are stored
Dynaconf aims to have a flexible and usable configuration system. Your applications can be configured via a configuration files, through environment variables, or both. Configurations are separated into environments: [development], [staging], [testing] and [production]. The working environment is selected via an environment variable.
Sensitive data like tokens, secret keys and password can be stored in .secrets.* files and/or external storages like Redis or vault secrets server.
Besides the built-in optional support to redis as settings storage dynaconf allows you to create custom loaders and store the data wherever you want e.g: databases, memory storages, other file formats, nosql databases etc.
Working environments
At any point in time, your application is operating in a given configuration environment. By default there are four such environments:
- [development]
- [staging]
- [testing]
- [production]
You can also define [custom environment] and use the pseudo-envs [default] to provide comprehensive default values and [global] to provide global values to overrride in any other environment.
Without any action, your applications by default run in the [development] environment. The environment can be changed via the ENV_FOR_DYNACONF environment variable. For example, to launch an application in the [staging] environment, we can run:
export ENV_FOR_DYNACONF=staging
or
ENV_FOR_DYNACONF=staging python yourapp.py
NOTE: When using FLask Extension the environment can be changed via
FLASK_ENVvariable and for Django Extension you can useDJANGO_ENV.
The settings files
NOTE: Read the full documentaion about dynaconf CLI to learn how to automatically create the settings files for your project.
An optional settings.{toml|py|json|ini|yaml} file can be used to specify the configuration parameters for each environment. If it is not present, only the values from environment variables are used (.env file is also supported). Dynaconf searches for the file starting at the current working directory. If it is not found there, Dynaconf checks the parent directory. Dynaconf continues checking parent directories until the root is reached.
The recommended file format is TOML but you can choose to use any of .{toml|py|json|ini|yaml}.
The file must be a series of sections, at most one for [default], optionally one for each [environment], and an optional [global] section. Each section contains key-value pairs corresponding to configuration parameters for that [environment]. If a configuration parameter is missing, the value from [default] is used. The following is a complete settings.toml file, where every standard configuration parameter is specified within the [default] section:
NOTE: if the file format choosen is
.pyas it does not support sections you can create multiple files likesettings.pyfor [default],development_settings.py,production_settings.pyandglobal_settings.py. ATTENTION using.pyis not recommended for configuration use TOML!
[default]
username = "admin"
port = 5000
host = "localhost"
message = "default message"
value = "default value"
[development]
username = "devuser"
[staging]
host = "staging.server.com"
[testing]
host = "testing.server.com"
[production]
host = "server.com"
[awesomeenv]
value = "this value is set for custom [awesomeenv]"
[global]
message = "This value overrides message of default and other envs"
The [global] pseudo-environment can be used to set and/or override configuration parameters globally. A parameter defined in a [global] section sets, or overrides if already present, that parameter in every environment. For example, given the following settings.toml file, the value of address will be "1.2.3.4" in every environment:
[global]
address = "1.2.3.4"
[development]
address = "localhost"
[production]
address = "0.0.0.0"
NOTE: The [env] name and first level variables are case insensitive as internally dynaconf will always use upper case, that means [development] and [DEVELOPMENT] are equivalent and address and ADDRESS are also equivalent. This rule does not apply for inner data structures as dictionaries and arrays.
Supported file formats
By default toml is the recommended format to store your configuration, however you can switch to a different supported format.
# If you wish to include support for more sources
pip3 install dynaconf[yaml|ini|redis|vault]
# for a complete installation
pip3 install dynaconf[all]
Once the support is installed no extra configuration is needed to load data from those files, dynaconf will search for settings files in the root directory of your application looking for the following files in the exact order below:
DYNACONF_LOADING_ORDER = [
'settings.py',
'.secrets.py',
'settings.toml',
'.secrets.toml',
'settings.yaml',
'.secrets.yaml',
'settings.ini',
'.secrets.ini',
'settings.json',
'.secrets.json',
# redis server if REDIS_ENABLED_FOR_DYNACONF=true
# vault server if VAULT_ENABLED_FOR_DYNACONF=true
# other sources if custom loaders are defined
# All environment variables prefixed with DYNACONF_
]
NOTE: Dynaconf works in an layered override mode based on the above order, so if you have multiple file formats with conflicting keys defined, the precedence will be based on the loading order.
Take a look at the example folder to see some examples of use with different file formats.
Read the docs
Documentation: http://dynaconf.readthedocs.io/
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