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111 lines
3.4 KiB
Python
111 lines
3.4 KiB
Python
from future import standard_library
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standard_library.install_aliases()
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import inspect
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import os.path
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import os
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import pickle
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import logging
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import tempfile
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import copy
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from .. import models
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logger = logging.getLogger(__name__)
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class SenpyPlugin(models.Plugin):
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def __init__(self, info=None):
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"""
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Provides a canonical name for plugins and serves as base for other
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kinds of plugins.
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"""
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if not info:
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raise models.Error(message=("You need to provide configuration"
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"information for the plugin."))
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logger.debug("Initialising {}".format(info))
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id = 'plugins/{}_{}'.format(info['name'], info['version'])
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super(SenpyPlugin, self).__init__(id=id, **info)
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self.is_activated = False
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def get_folder(self):
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return os.path.dirname(inspect.getfile(self.__class__))
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def activate(self):
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pass
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def deactivate(self):
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pass
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class AnalysisPlugin(SenpyPlugin):
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def analyse(self, *args, **kwargs):
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raise NotImplemented(
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'Your method should implement either analyse or analyse_entry')
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def analyse_entry(self, entry, parameters):
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""" An implemented plugin should override this method.
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This base method is here to adapt old style plugins which only
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implement the *analyse* function.
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Note that this method may yield an annotated entry or a list of
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entries (e.g. in a tokenizer)
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"""
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text = entry['text']
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params = copy.copy(parameters)
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params['input'] = text
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results = self.analyse(**params)
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for i in results.entries:
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yield i
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class ConversionPlugin(SenpyPlugin):
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pass
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class SentimentPlugin(models.SentimentPlugin, AnalysisPlugin):
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def __init__(self, info, *args, **kwargs):
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super(SentimentPlugin, self).__init__(info, *args, **kwargs)
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self.minPolarityValue = float(info.get("minPolarityValue", 0))
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self.maxPolarityValue = float(info.get("maxPolarityValue", 1))
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class EmotionPlugin(models.EmotionPlugin, AnalysisPlugin):
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def __init__(self, info, *args, **kwargs):
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super(EmotionPlugin, self).__init__(info, *args, **kwargs)
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self.minEmotionValue = float(info.get("minEmotionValue", -1))
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self.maxEmotionValue = float(info.get("maxEmotionValue", 1))
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class EmotionConversionPlugin(models.EmotionConversionPlugin, ConversionPlugin):
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pass
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class ShelfMixin(object):
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@property
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def sh(self):
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if not hasattr(self, '_sh') or self._sh is None:
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self.__dict__['_sh'] = {}
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if os.path.isfile(self.shelf_file):
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self.__dict__['_sh'] = pickle.load(open(self.shelf_file, 'rb'))
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return self._sh
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@sh.deleter
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def sh(self):
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if os.path.isfile(self.shelf_file):
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os.remove(self.shelf_file)
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del self.__dict__['_sh']
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self.save()
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@property
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def shelf_file(self):
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if 'shelf_file' not in self or not self['shelf_file']:
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sd = os.environ.get('SENPY_DATA', tempfile.gettempdir())
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self.shelf_file = os.path.join(sd, self.name + '.p')
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return self['shelf_file']
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def save(self):
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logger.debug('saving pickle')
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if hasattr(self, '_sh') and self._sh is not None:
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with open(self.shelf_file, 'wb') as f:
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pickle.dump(self._sh, f)
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