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senpy/example-plugins
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J. Fernando Sánchez 83b23dbdf4 UI improvements 
* Add option to add multiple plugins
* Improve UI hints for collapsed parameters
* Refactored plugins without requirements
* Hide evaluation tab for the moment. You can see it by adding "?evaluation" to
  the URL.
2018-06-18 16:46:49 +02:00
..
sklearn Add evaluation tests 2018-04-24 19:36:50 +02:00
async_plugin.py Macro commit 2018-01-06 21:03:20 +01:00
basic_analyse_entry_plugin.py Last batch of big changes 2018-01-06 21:03:36 +01:00
basic_box_plugin.py Add evaluation tests 2018-04-24 19:36:50 +02:00
basic_plugin.py Add evaluation tests 2018-04-24 19:36:50 +02:00
basic.py Last batch of big changes 2018-01-06 21:03:36 +01:00
configurable_plugin.py UI improvements 2018-06-18 16:46:49 +02:00
dummy_plugin.py Macro commit 2018-01-06 21:03:20 +01:00
dummy_required_plugin.py Add sklearn 2018-01-07 23:02:38 +01:00
mynoop.py Macro commit 2018-01-06 21:03:20 +01:00
mynoop.senpy Macro commit 2018-01-06 21:03:20 +01:00
parameterized_plugin.py Last batch of big changes 2018-01-06 21:03:36 +01:00
README.md Last batch of big changes 2018-01-06 21:03:36 +01:00
sleep_plugin.py Macro commit 2018-01-06 21:03:20 +01:00

README.md

This is a collection of plugins that exemplify certain aspects of plugin development with senpy.

The first series of plugins the basic ones. Their starting point is a classification function defined in basic.py. They all include testing and running them as a script will run all tests. In ascending order of customization, the plugins are:

  • Basic is the simplest plugin of all. It leverages the SentimentBox Plugin class to create a plugin out of a classification method, and MappingMixin to convert the labels from (pos, neg) to (marl:Positive, marl:Negative
  • Basic_box is just like the previous one, but replaces the mixin with a custom function.
  • Basic_configurable is a version of basic with a configurable map of emojis for each sentiment.
  • Basic_parameterized like basic_info, but users set the map in each query (via extra_parameters).
  • Basic_analyse_entry uses the more general analyse_entry method and adds the annotations individually.

In rest of the plugins show advanced topics:

  • mynoop: shows how to add a definition file with external requirements for a plugin. Doing this with a python-only module would require moving all imports of the requirements to their functions, which is considered bad practice.
  • Async: a barebones example of training a plugin and analyzing data in parallel.

All of the plugins in this folder include a set of test cases and they are periodically tested with the latest version of senpy.

Additioanlly, for an example of stand-alone plugin that can be tested and deployed with docker, take a look at: lab.cluster.gsi.dit.upm.es/senpy/plugin-example bbm