* extra_params: to add parameters to the senpy API when this plugin is requested. Those parameters may be required, and have aliased names. For instance:
Parameter validation will fail if a required parameter without a default has not been provided, or if the definition includes a set of values and the provided one does not match one of them.
* analyse_entry: called in every user requests. It takes two parameters: ``Entry``, the entry object, and ``params``, the parameters supplied by the user. It should yield one or more ``Entry`` objects.
Plugins are loaded asynchronously, so don't worry if the activate method takes too long. The plugin will be marked as activated once it is finished executing the method.
Training a classifier can be time time consuming. To avoid running the training unnecessarily, you can use ShelfMixin to store the classifier. For instance:
You can specify a 'shelf_file' in your .senpy file. By default the ShelfMixin creates a file based on the plugin name and stores it in that plugin's folder.
Shelves may get corrupted if the plugin exists unexpectedly.
A corrupt shelf prevents the plugin from loading.
If you do not care about the pickle, you can force your plugin to remove the corrupted file and load anyway, set the 'force_shelf' to True in your .senpy file.
You can add these parameters in the definition file under the attribute "extra_params" : "{param_name}". The name of the parameter has new attributes-value pairs. The basic attributes are:
* aliases: the different names which can be used in the request to use the parameter.
* required: this option is a boolean and indicates if the parameters is binding in operation plugin.
* options: the different values of the paremeter.
* default: the default value of the parameter, this is useful in case the paremeter is required and you want to have a default value.
..code:: python
"extra_params": {
"language": {
"aliases": ["language", "l"],
"required": true,
"options": ["es","en"],
"default": "es"
}
}
This example shows how to introduce a parameter associated with language.
The extraction of this paremeter is used in the analyse method of the Plugin interface.
..code:: python
lang = params.get("language")
Where can I set up variables for using them in my plugin?