A YAML parser with advanced functionalities to ease your application configuration.
This library is meant to be used in medium to large-scale applications, that have a lot of parameters to configure.
Modular applications especially can greatly benefit from using configue
to easily inject new modules.
Run pip install configue
to install from PyPI.
Run pip install .
to install from sources.
This project follows the (Semantic Versioning Specification)[https://semver.org/]. All breaking changes are described in the Changelog.
This library uses PyYAML to parse the YAML files and return the file content.
import configue
config = configue.load("/path/to/yaml/file.yml")
If you are not interested in loading the whole file, you can only load a subpath:
# config.yml
some_key:
some_list:
- first_item
- second_item:
item_key: item_value
not_loaded_key: not_loaded_value
import configue
config = configue.load("config.yml", "some_key.some_list.1.item_key")
assert config == "item_value"
Use ()
in your YAML files to instantiate classes:
# config.yml
(): "my_project.MyAwesomeClass"
my_argument: "my_value"
my_other_argument:
(): "my_project.my_module.MyOtherClass"
import configue
from my_project import MyAwesomeClass
from my_project.my_module import MyOtherClass
my_instance = configue.load("config.yml")
assert isinstance(my_instance, MyAwesomeClass)
assert my_instance.my_argument == "my_value"
assert isinstance(my_instance.my_other_argument, MyOtherClass)
This syntax also works to call functions:
# config.yml
(): "my_project.my_function"
my_argument: "world"
import configue
def my_function(my_argument: str) -> str:
return "Hello " + my_argument
my_value = configue.load("config.yml")
assert my_value == "Hello world"
# config.yml
my_argument: !ext my_project.my_module.my_variable
my_argument: !ext my_project.my_module.my_instance.my_attribute
When using the !ext
tag, the value will be imported from the corresponding python module.
# config.yml
my_object:
my_instance:
(): my_project.MyClass
my_instance_shortcut: !cfg my_object.my_instance
my_attribute_shortcut: !cfg my_object.my_instance.my_attribute
When using the !cfg
tag, the value will be loaded from the same configuration file (useful for a DRY configuration).
If you want to load an environment variable in your YAML config file, you can use this syntax:
# config.yml
my_key: ${VAR_NAME}
This will resolve as "my_value"
if the environment variable VAR_NAME
is set to this value.
If you need a default value in case the environment variable is not set:
# config.yml
my_key: ${VAR_NAME-default}
You can insert this syntax in the middle of a string:
# config.yml
my_key: prefix${VAR_NAME-default}suffix
This will resolve as "prefixmy_value_suffix"
if the value is set, "prefixdefaultsuffix"
if it is not.
If your environment variable resolves to a yaml value, it will be cast (unless you are using quotes):
# config.yml
my_key: ${VAR_NAME}
my_quoted_key: "${VAR_NAME}"
This will resolve as True
if the value is set to true
, yes
or y
, None
if the value is set to ~
or null
.
If you want to expand a relative path in your YAML config file:
# config.yml
my_path: !path my_folder/my_file.txt
Assuming your file structure looks like this:
root/
├── config.yml
└── my_folder
└── my_file.txt
The path is resolved starting from the folder containing the parent yml file, this example will resolve to
/root/my_folder/my_file.txt
Do not start the path with /
as it will be treated as an absolute path instead.
You can use environment variables in your file path.
You can import another file directly in your YAML config file:
# config.yml
my_import: !import my_folder/my_other_config.yml
# my_other_config.yml
some_key:
- var_1
- var_2
By default, the path is resolved starting from the folder containing the parent yml file, this example will resolve to
"my_import": {"some_key": [var_1, var_2]}
If you want to import only a section of the file, use the path in the tag suffix !import:some_key.0
Do not start the import path with /
as it will be treated as an absolute path instead.
You can use environment variables in your import path.
You can load the logging configuration for your application by using the logging_config_path
parameter:
# config.yml
logging_config:
version: 1
handlers:
console:
class : logging.StreamHandler
stream : ext://sys.stdout
custom_handler:
\(): my_app.CustomHandler
some_param: some_value
level: ERROR
root:
level: INFO
handlers:
- console
app_config:
some_key: some_value
not_loaded_key: not_loaded_value
import logging
import configue
app_config = configue.load("config.yml", "app_config", logging_config_path="logging_config")
assert app_config == {"some_key": "some_value"}
logger = logging.getLogger(__name__)
logger.info("Hello world!") # Uses the console handler
The logging configuration should follow the format of logging.config.dictConfig
(check the documentation for more
details).
Make sure to escape the constructors with \()
instead of ()
for handlers, formatters and filters.
Install the development dependencies with pip install -r dev.requirements.txt
.
Run python -m unitttest discover
to run the tests.
Run pylint configue
to check the files linting.