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50 lines
1.7 KiB
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50 lines
1.7 KiB
ReStructuredText
Developing new plugins
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----------------------
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Plugins Interface
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=================
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The basic methods in a plugin are:
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* __init__
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* activate: used to load memory-hungry resources
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* deactivate: used to free up resources
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* analyse: called in every user requests. It takes in the parameters supplied by a user and should return a senpy Response.
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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.
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F.A.Q.
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======
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If I'm using a classifier, where should I train it?
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???????????????????????????????????????????????????
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Training a classifier can be time time consuming. To avoid running the training unnecessarily, you can use ShelfMixin to store the classifier. For instance:
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.. code:: python
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from senpy.plugins import ShelfMixin, SenpyPlugin
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class MyPlugin(ShelfMixin, SenpyPlugin):
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def train(self):
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''' Code to train the classifier
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'''
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# Here goes the code
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# ...
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return classifier
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def activate(self):
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if 'classifier' not in self.sh:
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classifier = self.train()
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self.sh['classifier'] = classifier
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self.classifier = self.sh['classifier']
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def deactivate(self):
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self.close()
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You can speficy 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.
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Where can I find more code examples?
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????????????????????????????????????
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See: `<http://github.com/gsi-upm/senpy-plugins-community>`_.
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