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.
install Dynaconf in a Python 3 environment
# to use with settings.py, settings.json, .env or environment vars
pip3 install dynaconf
# to include support for more file formats
pip3 install dynaconf[yaml]
pip3 install dynaconf[toml]
pip3 install dynaconf[ini]
pip3 install dynaconf[redis]
pip3 install dynaconf[vault]
# for a complete installation
pip3 install dynaconf[all]
How does it work?
# import the unique dynaconf object
from dynaconf import settings
# access your config variables
Connect(user=settings.USERNAME, passwd=settings.PASSWD)
# You can provide defaults in case config is missing
Connect(user=settings('USERNAME', 'admin'), passwd=settings('PASSWD', 1234))
Where the values come from?
Dynaconf will look for variables in the following order (by default) and you can also customize the order of loaders.
- Settings files files in the order:
settings.{py|yaml|toml|ini|json}
.env
fileexport
ed Environment Variables- Remote storage servers
- Multiple customizable sources
12factor recommended example (environment variables):
# put some variable in a .env file
echo "DYNACONF_USERNAME=admin" >> .env
# Or export directly
export DYNACONF_USERNAME=admin
export DYNACONF_PASSWD='@int 1234' # you can type the values!
Just read it
# import the unique dynaconf object
from dynaconf import settings
# access your config variables
Connect(user=settings.USERNAME, passwd=settings.PASSWD)
NOTE: You can customize the prefix
DYNACONF_
to your own namespace likeMYAPP_USERNAME
exportingNAMESPACE_FOR_DYNACONF=MYAPP
.
Features
- Read config variables from unique
dynaconf
object - Values can come from different sources:
- Load values from
settings.{py|yaml|toml|ini}
file - Load values from
.env
files - Load values from System's Exported
Environment Variables
- And even more:
- Load values from a remote Redis server
- Load values from a remote SQL database
- Load values from a remote memcached
- Load values from a remote Secrets Vault
- And if you want:
- Load values from anywhere you want, easy to implement your own loader!
- Load values from
- Flexible typing system
- Export Typed environment variables using dynaconf data type markers
export FOO=@int 42
- Export Typed environment variables using dynaconf data type markers
- Flask Support
- In your Flask application just do
FlaskDynaconf(app)
and then read values fromapp.config
object
- In your Flask application just do
- Feature Flag System
- Implement a feature flag system using dynaconf as store and checker
- Value validation
- Validate the config variables and define rules
Examples
Choose a file format to store your settings or store it in environment variables
Choose the file format that best fit your project and call it settings.{py|yaml|toml|ini}
put this file in the root directory of your project. If you don't want to have a settings
file
dynaconf can also read values from environment variables or .env
files.
Try it
0 - Install dynaconf
with TOML support
pip install dynaconf[toml]
1 - Create a settings.toml
to store default project settings
[dynaconf]
server = 'foo.com'
username = 'admin'
password = false
2 - Create .secrets.toml
to store sensitive variables
[dynaconf]
password = 'My5up3r53c4et'
3 - Create a .env
to override values in specific environments
DYNACONF_USERNAME=admin
The
.env
is optional, it also works ifexport DYNACONF_VARIABLE=x
is used
4 - Create a .gitignore
to remove .secrets.*
and .env
from VCS
.env
.secrets.*
5 - Create the program.py
from dynaconf import settings
print(settings.USERNAME)
print(settings.SERVER)
print(settings.PASSWORD)
6 - Run it
$ python program.py
admin
foo.com
My5up3r53c4et
It is possible to have multiple sources at the same time but the recommendation is to pick a single format for your configurations and use envvars or .env to override it.
Namespace support
When you are working with multiple projects using the same environment maybe you want to use different namespaces for ENV vars based configs
export DYNACONF_DATABASE="DYNADB"
export PROJ1_DATABASE="PROJ1DB"
export PROJ2_DATABASE="PROJ2DB"
and then access them
>>> from dynaconf import settings
# access default namespace settings
>>> settings.DATABASE
'DYNADB'
# switch namespaces
>>> settings.namespace('PROJ1')
>>> settings.DATABASE
'PROJ1DB'
>>> settings.namespace('PROJ2')
>>> settings.DATABASE
'PROJ2DB'
# return to default, call it without args
>>> settings.namespace()
>>> settings.DATABASE
'DYNADB'
You can also use the context manager:
>>> settings.DATABASE
'DYNADB'
>>> with settings.using_namespace('PROJ1'):
... settings.DATABASE
'PROJ1DB'
>>> with settings.using_namespace('PROJ2'):
... settings.DATABASE
'PROJ2DB'
>>> settings.DATABASE
'DYNADB'
namespace() and using_namespace() takes optional argument clean defaults to True. If you want to keep the pre-loaded values when switching namespaces set it to False.
Namespaced environment
It is usual to have e.g production
and development
environments, the way to set this is:
Using settings.py
as base file you just need other <environment>_settings.py
files.
settings.py
development_settings.py
production_settings.py
Then in your environment.
export NAMESPACE_FOR_DYNACONF=DEVELOPMENT|PRODUCTION # switch enviroment using env vars.
Or using namespace
with settings.using_namespace('development'):
# code here
settings.namespace('development')
NOTE:
settings.py
is the base andnamespace
specific overrides its vars.
using YAML
you need to install with
pip install dynaconf[yaml]
Just save a settings.yaml
in the root dir.
Using YAML is easier because it support multiple namespace in a single file.
Lets say you have NAMESPACE_FOR_DYNACONF=DYNACONF
(the default)
DYNACONF: # this is the global namespace
VARIABLE: 'this variable is available on every namespace'
HOST: null # this variable is set to None
DEVELOPMENT:
HOST: devserver.com # overrides the global or sets new
production: # upper or lower case does not matter
host: prodserver.com
Then it will be applied using env var NAMESPACE_FOR_DYNACONF
or context manager.
HINT: When using yaml namespace identifier and first level vars are case insensitive, dynaconf will always have them read as upper case.
using TOML
you need to install with
pip install dynaconf[toml]
Just save a settings.toml
in the root dir.
Using TOML is easier because it support multiple namespace in a single file.
Lets say you have NAMESPACE_FOR_DYNACONF=DYNACONF
(the default)
[dynaconf] # this is the global namespace
variable = 'this variable is available on every namespace'
HOST = false # this variable is set to False
[DEVELOPMENT]
HOST = 'devserver.com' # overrides the global or sets new
[production] # upper or lower case does not matter
host = 'prodserver.com'
Then it will be applied using env var NAMESPACE_FOR_DYNACONF
or context manager.
HINT: When using toml namespace identifier and first level vars are case insensitive, dynaconf will always have them read as upper case.
using INIFILES
you need to install dynaconf with
pip install dynaconf[ini]
Just save a settings.ini
in the root dir.
Using INI is easier because it support multiple namespace in a single file.
Lets say you have NAMESPACE_FOR_DYNACONF=DYNACONF
(the default)
[DYNACONF]
VARIABLE = "this variable is available on every namespace"
[DEVELOPMENT]
HOST = "devserver.com"
[production]
host = "prodserver.com"
Then it will be applied using env var NAMESPACE_FOR_DYNACONF
or context manager.
HINT: When using INI namespace identifier and first level vars are case insensitive, dynaconf will always have them read as upper case.
using JSON
Just save a settings.json
in the root dir.
Using JSON is easier because it support multiple namespace in a single file.
Lets say you have NAMESPACE_FOR_DYNACONF=DYNACONF
(the default)
{
"DYNACONF": {
"VARIABLE": "this variable is available on every namespace",
"HOST": null
},
"DEVELOPMENT": {
"HOST": "devserver.com"
},
"production": {
"host": "prodserver.com"
}
}
Then it will be applied using env var NAMESPACE_FOR_DYNACONF
or context manager.
HINT: When using json namespace identifier and first level vars are case insensitive, dynaconf will always have them read as upper case.
casting values from envvars
Sometimes you need to set some values as specific types, boolean, integer, float or lists and dicts.
built in casts
- @int (as_int)
- @bool (as_bool)
- @float (as_float)
- @json (as_json)
@json / as_json will use json to load a Python object from string, it is useful to get lists and dictionaries. The return is always a Python object.
strings does not need converters.
You have 2 ways to use the casts.
Casting on declaration
Dynaconf uses the AUTO_CAST
of envvars, just start your ENV vars names with a
typed prefix like in the examples below.
export DYNACONF_DEFAULT_THEME='material'
export DYNACONF_DEBUG='@bool True'
export DYNACONF_DEBUG_TOOLBAR_ENABLED='@bool False'
export DYNACONF_PAGINATION_PER_PAGE='@int 20'
export DYNACONF_MONGODB_SETTINGS='@json {"DB": "quokka_db"}'
export DYNACONF_ALLOWED_EXTENSIONS='@json ["jpg", "png"]'
Starting the settings values with @ will make dynaconf.settings to cast it in the time od load.
There is support for @int, @float, @bool, @json, @note
NOTE: To disable the AUTO_CAST you can set a env var
export AUTO_CAST_FOR_DYNACONF=off
Casting on access
export DYNACONF_USE_SSH='yes'
from dynaconf import settings
use_ssh = settings.get('USE_SSH', cast='@bool')
# or
use_ssh = settings('USE_SSH', cast='@bool')
# or
use_ssh = settings.as_bool('USE_SSH')
print use_ssh
True
more examples
export DYNACONF_USE_SSH='enabled'
export DYNACONF_ALIST='@json [1,2,3]'
export DYNACONF_ADICT='@json {"name": "Bruno"}'
export DYNACONF_AINT='@int 42'
export DYNACONF_ABOOL='@bool on'
export DYNACONF_AFLOAT='@float 42.5'
from dynaconf import settings
# original value
settings('USE_SSH')
'enabled'
# cast as bool
settings('USE_SSH', cast='@bool')
True
# also cast as bool
settings.as_bool('USE_SSH')
True
# cast defined in declaration '@bool on'
settings.ABOOL
True
# cast defined in declaration '@json {"name": "Bruno"}'
settings.ADICT
{u'name': u'Bruno'}
# cast defined in declaration '@json [1,2,3]'
settings.ALIST
[1, 2, 3]
# cast defined in decalration '@float 42.5'
settings.AFLOAT
42.5
# cast defined in declaration '@int 42'
settings.AINT
42
Defining default namespace
Include in the settings.py
or in the file defined in the envvar DYNACONF_SETTINGS or in the .env
file or in the customized LazySettings class the desired namespace
NAMESPACE_FOR_DYNACONF = 'MYPROGRAM'
Storing settings in databases
Using Hashicorp Vault
The https://www.vaultproject.io/ is a key:value store for secrets and Dynaconf can load variables from a Vault secret.
- Run a vault server Run a Vault server installed or via docker:
docker run -e 'VAULT_DEV_ROOT_TOKEN_ID=myroot' -p 8200:8200 vault
- Install support for vault in dynaconf
pip install dynaconf[vault]
- In your
.env
file or in environment variables do:
VAULT_FOR_DYNACONF_ENABLED=1
VAULT_FOR_DYNACONF_URL="http://localhost:8200"
VAULT_FOR_DYNACONF_TOKEN="myroot"
VAULT_FOR_DYNACONF_PATH="/secret/data/" # the resulting namespace will have namespace added as in /secret/data/dynaconf
Now you can have keys like PASSWORD
and TOKEN
defined in the vault and
dynaconf will read it.
To write a new secret you can use http://localhost:8200 web admin and write keys
under the /secret/dynaconf
secret database.
You can also use the Dynaconf writer via Python terminal
from dynaconf.loaders.vault_loader import write
write({'password': '123456'})
Using REDIS
1 Add the configuration for redis client
REDIS_FOR_DYNACONF = {
'host': 'localhost',
'port': 6379,
'db': 0,
'decode_responses': True
}
NOTE: if running on Python 3 include
'decode_responses': True
inREDIS_FOR_DYNACONF
Enable the loader in .env
or as environment variable
REDIS_FOR_DYNACONF_ENABLED=1
You can now write variables direct in to a redis hash named DYNACONF_< NAMESPACE >
By default DYNACONF_DYNACONF
You can also use the redis writer
from dynaconf.utils import redis_writer
from dynaconf import settings
redis_writer.write(settings, name='Bruno', database='localhost', PORT=1234)
The above data will be converted to namespaced values and recorded in redis as a hash:
DYNACONF_DYNACONF:
NAME='Bruno'
DATABASE='localhost'
PORT='@int 1234'
if you want to skip type casting, write as string intead of PORT=1234 use PORT='1234' as redis stores everything as string anyway
Data is read from redis and another loaders only once or when namespace() and using_namespace() are invoked. You can access the fresh value using settings.get_fresh(key)
There is also the fresh context manager
from dynaconf import settings
print settings.FOO # this data was loaded once on import
with settings.fresh():
print settings.FOO # this data is being directly read from loaders
And you can also force some variables to be fresh setting in your setting file
DYNACONF_ALWAYS_FRESH_VARS = ['MYSQL_HOST']
or using env vars
export DYNACONF_ALWAYS_FRESH_VARS='@json ["MYSQL_HOST"]'
Then
from dynaconf import settings
print settings.FOO # This data was loaded once on import
print settings.MYSQL_HOST # This data is being read from redis imediatelly!
Using programatically
Sometimes you want to override settings for your existing Package or Framework lets say you have a conf module exposing a settings object and used to do:
from myprogram.conf import settings
Now you want to use Dynaconf, open that conf.py
or conf/__init__.py
and do:
# coding: utf-8
from dynaconf import LazySettings
settings = LazySettings(
ENVVAR_FOR_DYNACONF="MYPROGRAM_SETTINGS_MODULE",
NAMESPACE_FOR_DYNACONF='MYPROGRAM'
)
Now you can import settings from your own program and dynaconf will do the rest!
Flask Extension
Dynaconf provides an extension to make your app.config
in Flask to be a dynaconf
instance.
from flask import Flask
from dynaconf import FlaskDynaconf
app = Flask(__name__)
FlaskDynaconf(app)
Now the app.config
will read values from dynaconf.settings
Django Extension
Dynaconf provides an extnesion to make django.conf.settings
to be a dynaconf instance
In your django project's settings.py
include:
INSTALLED_APPS = [
'dynaconf.contrib.django_dynaconf',
...
]
NOTE: The extension must be included as the first INSTALLED_APP of the list
Now create your settings.{py|yaml|toml|ini|json}
in your project's root directory
(the same folder where manage.py
is located)
Now when doing form django.conf import settings
this settings object will read values from dynaconf
DEBUGGING
By default Dynaconf only outputs the ERROR level to debug it change
export DEBUG_LEVEL_FOR_DYNACONF='INFO'
The loading precedende order
Dynaconf will perform loads in this order:
- Load Default configuration
- Load Environment variables (pre load to read initial DYNACONF_ config)
- Load Settings file in the order defined in
SETTINGS_MODULE_FOR_DYNACONF
by default will to load'settings.py,settings.yaml,settings.toml'
in this order overriding previous values - Load all loaders defined in
LOADERS_FOR_DYNACONF
by default onlyenvironment variables
will be read again and get higher precedence
The files will be tried to load in the following order allowing overrides
[
'settings.py', '.secrets.py',
'settings.yaml', 'settings.yml', '.secrets.yaml', '.secrets.yml',
'settings.toml', 'settings.tml', '.secrets.toml', '.secrets.tml',
'settings.ini', 'settings.conf', 'settings.properties',
'.secrets.ini', '.secrets.conf', '.secrets.properties',
'settings.json', '.secrets.json'
]
Customizing the loaders
In a setting file like settings.{py|yaml|toml|ini|json}
define:
LOADERS_FOR_DYNACONF = [
'dynaconf.loaders.env_loader',
'dynaconf.loaders.redis_loader',
'YourCustomLoaderPath'
]
export also works
export LOADERS_FOR_DYNACONF='@json ["loader1", "loader2"]'
Loaders will be executed in that order.
To disable loaders do:
LOADERS_FOR_DYNACONF=0
This will cause environment variables to lose the higher precedence
More examples:
Take a look at example/ for more.
This was inspired by flask.config and django.conf.settings
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