.. _config: :mod:`baldaquin.config` --- Configuration ========================================= The module provides the abstract base class :class:`ConfigurationBase ` that users can inherit from in order to create concrete configuration objects with JSON I/O capabilities. This provides a convenient mechanism to create and update configuration objects suiting any specific need. The basic ideas behind the mechanism implemented here is that: * each specific configuration has its own concrete class inheriting from :class:`ConfigurationBase ` (which is achieved with no boilerplate code); * the class contains a full set of default values for the configuration parameters, so that any instance of a configuration object is guaranteed to be valid at creation time---and, in addition, to remain valid as the parameter values are updated through the lifetime of the object; * type consistency is automatically enforced whenever a parameter is set or updated; * a minimal set of optional constraints can be enforced on any of the parameters; * a configuration object can be serialized/deserialized in JSON format so that it can be written to file, and the parameter values can be updated from file. In the remaining of this section we shall see how to declare, instantiate and interact with concrete configuration objects. Declaring a concrete configuration class ---------------------------------------- A simple, and yet fully functional, concrete configuration class for an hypothetical network connection might look like the following snippet---all you really have to do is to override the ``TITLE`` and ``PARAMETER_SPECS`` top-level class members. .. code-block:: python class SampleConfiguration(ConfigurationBase): TITLE = 'A simple test configuration' PARAMETER_SPECS = ( ('enabled', 'bool', True, 'Enable connection', None, None, {}), ('ip_address', 'str', '127.0.0.1', 'IP address', None, None, {}), ('port', 'int', 20004, 'UDP port', None, None, dict(min=1024, max=65535)), ('timeout', 'float', 10., 'Connection timeout', 's', '.3f', dict(min=0.)) ) While the ``TITLE`` thing is pretty much self-explaining, the parameter specification deserves some more in-depth explanation. ``PARAMETER_SPECS`` is supposed to be an iterable of tuples matching the :class:`ConfigurationParameter ` constructor, namely: 1. the paramater name (str); 2. the `name` of the parameter type (str); 3. the default value---note its type should match that indicated by the previous name; 4. a string expressing the intent of the parameter; 5. an optional string indicating the physical units of the parameter value; 6. an optional format string for the preferred rendering of the value; 7. an optional dictionary encapsulating the constraints on the possible parameter values. In this case we are saying that the integer ``port`` parameter should be within 1024 and 65535, and that the floating-point ``timeout`` parameter should be positive. The supported optional constraints for the various data types are: * ``choices``, ``step``, ``min`` and ``max`` for integers; * ``min`` and ``max`` for floats; * ``choices`` for strings. (And if you look this closely enough you will recognize that the constraints are designed so that the map naturally to the GUI widgets that might be used to control the configuration, e.g., spin boxes for integers, and combo boxes for strings to pulled out of a pre-defined list.) Once you have a concrete class defined, you can instantiate an object, which will come up set up and ready to use, with all the default parameter values. >>> from baldaquin.config import SampleConfiguration >>> config = SampleConfiguration() >>> print(config) -------------------------------------------------------------------------------- A simple test configuration -------------------------------------------------------------------------------- enabled.............: True ip_address..........: 127.0.0.1 port................: 20004 {'min': 1024, 'max': 65535} timeout.............: 10.000 s {'min': 0.0} -------------------------------------------------------------------------------- Programmatically, you can retrieve the value of a specific parameter through the :meth:`value() ` class method, and update the value with :meth:`update_value() `. >>> print(config.value('port')) 20004 >>> config.update_value('port', 20005) >>> print(config.value('port')) 20005 >>> The :meth:`save() ` method allows to dump the (JSON-encoded) content of the configuration into file looking like .. code-block:: json { "enabled": { "name": "enabled", "type_name": "bool", "value": true, "intent": "Enable connection", "units": null, "fmt": null, "constraints": {} }, "ip_address": { "name": "ip_address", "type_name": "str", "value": "127.0.0.1", "intent": "IP address", "units": null, "fmt": null, "constraints": {} }, "port": { "name": "port", "type_name": "int", "value": 20003, "intent": "UDP port", "units": null, "fmt": null, "constraints": { "min": 1024, "max": 65535 } }, "timeout": { "name": "timeout", "type_name": "float", "value": 10.0, "intent": "Connection timeout", "units": "s", "fmt": ".3f", "constraints": { "min": 0.0 } } } and this is the basic mechanism through which applications will interact with configuration objects, with :meth:`update() ` allowing to update an existing configuration from a JSON file with the proper format. .. note:: Keep in mind that configurations are never `read` from file---they come to life with all the parameters set to their default values, and then they can be `updated` from a JSON file. When you think about, this makes extending and/or modifying existing configurations much easier as, once the concrete class is changed, all existing configuration files are automatically updated transparantly, and in case one edits a file by hand, any mistake will be promptly signaled (and corrected) without compromising the validity of the configuration object. Module documentation -------------------- .. automodule:: baldaquin.config