Library to load configuration from various sources.
Nectarine requires Python 3.7 or above, and has been tested using Python 3.7 and 3.8.
Nectarine can be installed through pip.
$ pip3 install nectarine # Install the basic version
$ pip3 install nectarine[yaml] # Install the YAML extension
Nectarine loads the configuration from different back-ends called providers. The table below lists the available providers.
Name | Description |
---|---|
arguments | A provider that reads from the program arguments |
env | A provider that reads from the program environment variables |
dictionary | A provider that reads from a user-provided dictionary |
json | A provider that reads from a user-provided JSON file |
yaml | A provider that reads from a user-provided YAML file |
Nectarine gives you the ability to describe a configuration using Python's dataclasses, and load it from various sources (program arguments, configuration files, ...).
Let's consider a program that consumes events from a RabbitMQ broker (for example, using the awesome pika
library!).
That little program should of course allow the user to configure connection parameters such as the broker's host and
listening port, the credentials to use, etc.
Our program will accept configuration from 3 different providers:
- the program arguments
- the program environment
- a JSON configuration file, say
./conf.json
with fields for the host / port / username / password
The idea here is to allow the user to quickly override the configuration file by using the environment or the arguments.
In order to represent those connection parameters, we create the following dataclass:
from dataclasses import dataclass
@dataclass
class RabbitMQ:
host: str
username: str
password: str
port: int = 5671
The next step is to communicate with the user, obtain the configuration, and create an instance of RabbitMQ
with it. Let's see how we can achieve that with Nectarine.
Nectarine provides a load
function, which needs two things: the type to load, and a list of providers to load from.
We already have our target type (which is RabbitMQ
), thus we need to select our providers:
- for program arguments, the
arguments
provider - for program environment, the
env
provider - for the JSON file, the
json
provider
Now, we can call the load
function like below and retrieve its result:
from nectarine import load, arguments, env, json
rabbitmq = load(
target=RabbitMQ,
providers=[
arguments(),
env(prefix="RABBITMQ_"),
json("./conf.json")
]
)
print(rabbitmq)
That's pretty much it! The rabbitmq
variable is now loaded with our configuration when we run the program:
$ echo '{"host": "localhost", "port": 5671, "username": "user", "password": "pass"}' > ./conf.json
$ ./consumer.py
RabbitMQ(host='localhost', username='user', password='pass', port=5671)
$ ./consumer.py --port 1234
RabbitMQ(host='localhost', username='user', password='pass', port=1234)
- Multiple configuration providers: program arguments, environment, configuration files, ...
- Value overriding: higher-priority providers override values from lower-priority providers
- Complex structures: nested dataclasses and collections are supported
- Type checking: configuration data is checked against the type hints provided in your dataclasses
- Dataclasses features: default values or factories can be specified just as in regular dataclasses