Settings Files¶

Optionally you can store settings in files, dynaconf supports multiple file formats, you are recommended to choose one format but you can also use mixed settings formats across your application.

Tip

You are not required to use settings files, if not specified dynaconf can load your data only from environment variables

Supported formats¶

.toml - Default and recommended file format.
.yaml|.yml - Recommended for Django applications.
.json - Useful to reuse existing or exported settings.
.ini - Useful to reuse legacy settings.
.py - Not Recommended but supported for backwards compatibility.
.env - Useful to automate the loading of environment variables.

Info

Create your settings in desired format and specify it on settings_files argument on your dynaconf instance or pass it in -f <format> if using dynaconf init command.

Tip

Can't find the file format you need for your settings? You can create your custom loader and read any data source. read more on extending dynaconf

Reading settings from files¶

On files by default dynaconf loads all the existing keys and sections as first level settings.

settings.toml

name = "Bruno"

settings.yaml

name: Bruno

settings.json

{"name": "Bruno"}

settings.ini

name = 'Bruno'

settings.py

NAME = "Bruno"

⚠️ on .py files dynaconf only read UPPERCASE variables.

Then on your application code:

settings.name == "Bruno"

Info

The default encoding when loading the settings files is utf-8 and it can be customized via encoding parameter.

Settings file location¶

Dynaconf will search files specified in settings_file option starting the search tree on the current working dir (the directory where you program is located).

Ex:

from dynaconf import Dynaconf

settings = Dynaconf(settings_files=["settings.toml", "/etc/program/foo.yaml"])

settings.toml¶

In the above example, dynaconf will try to load settings.toml from the same directory where the program is located, also known as . and then will keep traversing the folders in backwards order until the root is located.

root is either the path where the program was invoked, or the O.S root or the root specified in root_path.

/etc/program/foo.yaml¶

Dynaconf will then recognize this as an absolute path and will try to load it directly from the specified location.

Local Settings files¶

For each file specified in settings_files dynaconf will also try to load an optional name.local.extension.

For example, settings_files=["settings.toml"] will make dynaconf to search for settings.toml and then also search for settings.local.toml

Includes¶

You can also specify includes so dynaconf can include those settings after the normal loading.

as a parameter¶

settings = Dynaconf(includes=["path/to/file.toml", "or/a/glob/*.yaml])

as a variable in a file¶

dynaconf_include = ["path/to/file.toml"]
key = value
anotherkey = value

Layered environments on files¶

It is also possible to make dynaconf to read the files separated by layered environments so each section or first level key is loaded as a distinct environment.

config.py

settings = Dynaconf(environments=True)

settings.toml

[default]
name = ""
[development]
name = "developer"
[production]
name = "admin"

settings.yaml

default:
    name: ''
development:
    name: developer
production:
    name: admin

settings.json

{
    "default": {
        "name": ""
    },
    "development": {
        "name": "developer"
    },
    "production": {
        "name": "admin"
    }
}

settings.ini

[default]
name = ""
[development]
name = "developer"
[production]
name = "admin"

ℹ️ You can define custom environment using the name you want [default] and [global] are the only environments that are special. You can for example name it [testing] or [anything]

program.py

Then in your program you can use environment variables to switch environments.

export ENV_FOR_DYNACONF=development

settings.name == "developer"

export ENV_FOR_DYNACONF=production

settings.name == "admin"

Warning

On Flask and Django extensions the default behaviour is already the layered environments. Also to switch the environment you use export FLASK_ENV=production or export DJANGO_ENV=production respectively.

Tip

It is also possible to switch environments programmatically passing env="development" to Dynaconf class on instantiation.