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Added GuessIt library and required libs for it.

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We now perform a guessit on the nzbName to extract movie title and year instead of a regex, this is more accurate.
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echel0n 2014-04-19 12:28:55 -07:00
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# GuessIt - A library for guessing information from filenames
# Copyright (c) 2013 Nicolas Wack <wackou@gmail.com>
#
# GuessIt is free software; you can redistribute it and/or modify it under
# the terms of the Lesser GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# GuessIt is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# Lesser GNU General Public License for more details.
#
# You should have received a copy of the Lesser GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
from __future__ import absolute_import, division, print_function, unicode_literals
from guessit import UnicodeMixin, s, u, base_text_type
import json
import datetime
import logging
log = logging.getLogger(__name__)
class GuessMetadata(object):
"""GuessMetadata contains confidence, an input string, span and related property.
If defined on a property of Guess object, it overrides the object defined as global.
:param parent: The parent metadata, used for undefined properties in self object
:type parent: :class: `GuessMedata`
:param confidence: The confidence (from 0.0 to 1.0)
:type confidence: number
:param input: The input string
:type input: string
:param span: The input string
:type span: tuple (int, int)
:param prop: The found property definition
:type prop: :class `guessit.containers._Property`
"""
def __init__(self, parent=None, confidence=None, input=None, span=None, prop=None, *args, **kwargs):
self.parent = parent
if confidence is None and self.parent is None:
self._confidence = 1.0
else:
self._confidence = confidence
self._input = input
self._span = span
self._prop = prop
@property
def confidence(self):
"""The confidence
:rtype: int
:return: confidence value
"""
return self._confidence if not self._confidence is None else self.parent.confidence if self.parent else None
@confidence.setter
def confidence(self, confidence):
self._confidence = confidence
@property
def input(self):
"""The input
:rtype: string
:return: String used to find this guess value
"""
return self._input if not self._input is None else self.parent.input if self.parent else None
@property
def span(self):
"""The span
:rtype: tuple (int, int)
:return: span of input string used to find this guess value
"""
return self._span if not self._span is None else self.parent.span if self.parent else None
@span.setter
def span(self, span):
"""The span
:rtype: tuple (int, int)
:return: span of input string used to find this guess value
"""
self._span = span
@property
def prop(self):
"""The property
:rtype: :class:`_Property`
:return: The property
"""
return self._prop if not self._prop is None else self.parent.prop if self.parent else None
@property
def raw(self):
"""Return the raw information (original match from the string,
not the cleaned version) associated with the given property name."""
if self.input and self.span:
return self.input[self.span[0]:self.span[1]]
return None
def __repr__(self, *args, **kwargs):
return object.__repr__(self, *args, **kwargs)
def _split_kwargs(**kwargs):
metadata_args = {}
for prop in dir(GuessMetadata):
try:
metadata_args[prop] = kwargs.pop(prop)
except KeyError:
pass
return metadata_args, kwargs
class Guess(UnicodeMixin, dict):
"""A Guess is a dictionary which has an associated confidence for each of
its values.
As it is a subclass of dict, you can use it everywhere you expect a
simple dict."""
def __init__(self, *args, **kwargs):
metadata_kwargs, kwargs = _split_kwargs(**kwargs)
self._global_metadata = GuessMetadata(**metadata_kwargs)
dict.__init__(self, *args, **kwargs)
self._metadata = {}
for prop in self:
self._metadata[prop] = GuessMetadata(parent=self._global_metadata)
def to_dict(self, advanced=False):
"""Return the guess as a dict containing only base types, ie:
where dates, languages, countries, etc. are converted to strings.
if advanced is True, return the data as a json string containing
also the raw information of the properties."""
data = dict(self)
for prop, value in data.items():
if isinstance(value, datetime.date):
data[prop] = value.isoformat()
elif isinstance(value, (UnicodeMixin, base_text_type)):
data[prop] = u(value)
elif isinstance(value, list):
data[prop] = [u(x) for x in value]
if advanced:
metadata = self.metadata(prop)
prop_data = {'value': data[prop]}
if metadata.raw:
prop_data['raw'] = metadata.raw
if metadata.confidence:
prop_data['confidence'] = metadata.confidence
data[prop] = prop_data
return data
def nice_string(self, advanced=False):
"""Return a string with the property names and their values,
that also displays the associated confidence to each property.
FIXME: doc with param"""
if advanced:
data = self.to_dict(advanced)
return json.dumps(data, indent=4)
else:
data = self.to_dict()
parts = json.dumps(data, indent=4).split('\n')
for i, p in enumerate(parts):
if p[:5] != ' "':
continue
prop = p.split('"')[1]
parts[i] = (' [%.2f] "' % self.confidence(prop)) + p[5:]
return '\n'.join(parts)
def __unicode__(self):
return u(self.to_dict())
def metadata(self, prop=None):
"""Return the metadata associated with the given property name
If no property name is given, get the global_metadata
"""
if prop is None:
return self._global_metadata
if not prop in self._metadata:
self._metadata[prop] = GuessMetadata(parent=self._global_metadata)
return self._metadata[prop]
def confidence(self, prop=None):
return self.metadata(prop).confidence
def set_confidence(self, prop, confidence):
self.metadata(prop).confidence = confidence
def raw(self, prop):
return self.metadata(prop).raw
def set(self, prop_name, value, *args, **kwargs):
self[prop_name] = value
self._metadata[prop_name] = GuessMetadata(parent=self._global_metadata, *args, **kwargs)
def update(self, other, confidence=None):
dict.update(self, other)
if isinstance(other, Guess):
for prop in other:
try:
self._metadata[prop] = other._metadata[prop]
except KeyError:
pass
if not confidence is None:
for prop in other:
self.set_confidence(prop, confidence)
def update_highest_confidence(self, other):
"""Update this guess with the values from the given one. In case
there is property present in both, only the one with the highest one
is kept."""
if not isinstance(other, Guess):
raise ValueError('Can only call this function on Guess instances')
for prop in other:
if prop in self and self.metadata(prop).confidence >= other.metadata(prop).confidence:
continue
self[prop] = other[prop]
self._metadata[prop] = other.metadata(prop)
def choose_int(g1, g2):
"""Function used by merge_similar_guesses to choose between 2 possible
properties when they are integers."""
v1, c1 = g1 # value, confidence
v2, c2 = g2
if (v1 == v2):
return (v1, 1 - (1 - c1) * (1 - c2))
else:
if c1 > c2:
return (v1, c1 - c2)
else:
return (v2, c2 - c1)
def choose_string(g1, g2):
"""Function used by merge_similar_guesses to choose between 2 possible
properties when they are strings.
If the 2 strings are similar, or one is contained in the other, the latter is returned
with an increased confidence.
If the 2 strings are dissimilar, the one with the higher confidence is returned, with
a weaker confidence.
Note that here, 'similar' means that 2 strings are either equal, or that they
differ very little, such as one string being the other one with the 'the' word
prepended to it.
>>> s(choose_string(('Hello', 0.75), ('World', 0.5)))
('Hello', 0.25)
>>> s(choose_string(('Hello', 0.5), ('hello', 0.5)))
('Hello', 0.75)
>>> s(choose_string(('Hello', 0.4), ('Hello World', 0.4)))
('Hello', 0.64)
>>> s(choose_string(('simpsons', 0.5), ('The Simpsons', 0.5)))
('The Simpsons', 0.75)
"""
v1, c1 = g1 # value, confidence
v2, c2 = g2
if not v1:
return g2
elif not v2:
return g1
v1, v2 = v1.strip(), v2.strip()
v1l, v2l = v1.lower(), v2.lower()
combined_prob = 1 - (1 - c1) * (1 - c2)
if v1l == v2l:
return (v1, combined_prob)
# check for common patterns
elif v1l == 'the ' + v2l:
return (v1, combined_prob)
elif v2l == 'the ' + v1l:
return (v2, combined_prob)
# if one string is contained in the other, return the shortest one
elif v2l in v1l:
return (v2, combined_prob)
elif v1l in v2l:
return (v1, combined_prob)
# in case of conflict, return the one with highest confidence
else:
if c1 > c2:
return (v1, c1 - c2)
else:
return (v2, c2 - c1)
def _merge_similar_guesses_nocheck(guesses, prop, choose):
"""Take a list of guesses and merge those which have the same properties,
increasing or decreasing the confidence depending on whether their values
are similar.
This function assumes there are at least 2 valid guesses."""
similar = [guess for guess in guesses if prop in guess]
g1, g2 = similar[0], similar[1]
other_props = set(g1) & set(g2) - set([prop])
if other_props:
log.debug('guess 1: %s' % g1)
log.debug('guess 2: %s' % g2)
for prop in other_props:
if g1[prop] != g2[prop]:
log.warning('both guesses to be merged have more than one '
'different property in common, bailing out...')
return
# merge all props of s2 into s1, updating the confidence for the
# considered property
v1, v2 = g1[prop], g2[prop]
c1, c2 = g1.confidence(prop), g2.confidence(prop)
new_value, new_confidence = choose((v1, c1), (v2, c2))
if new_confidence >= c1:
msg = "Updating matching property '%s' with confidence %.2f"
else:
msg = "Updating non-matching property '%s' with confidence %.2f"
log.debug(msg % (prop, new_confidence))
g2[prop] = new_value
g2.set_confidence(prop, new_confidence)
g1.update(g2)
guesses.remove(g2)
def merge_similar_guesses(guesses, prop, choose):
"""Take a list of guesses and merge those which have the same properties,
increasing or decreasing the confidence depending on whether their values
are similar."""
similar = [guess for guess in guesses if prop in guess]
if len(similar) < 2:
# nothing to merge
return
if len(similar) == 2:
_merge_similar_guesses_nocheck(guesses, prop, choose)
if len(similar) > 2:
log.debug('complex merge, trying our best...')
before = len(guesses)
_merge_similar_guesses_nocheck(guesses, prop, choose)
after = len(guesses)
if after < before:
# recurse only when the previous call actually did something,
# otherwise we end up in an infinite loop
merge_similar_guesses(guesses, prop, choose)
def merge_all(guesses, append=None):
"""Merge all the guesses in a single result, remove very unlikely values,
and return it.
You can specify a list of properties that should be appended into a list
instead of being merged.
>>> s(merge_all([ Guess({'season': 2}, confidence=0.6),
... Guess({'episodeNumber': 13}, confidence=0.8) ])
... ) == {'season': 2, 'episodeNumber': 13}
True
>>> s(merge_all([ Guess({'episodeNumber': 27}, confidence=0.02),
... Guess({'season': 1}, confidence=0.2) ])
... ) == {'season': 1}
True
>>> s(merge_all([ Guess({'other': 'PROPER'}, confidence=0.8),
... Guess({'releaseGroup': '2HD'}, confidence=0.8) ],
... append=['other'])
... ) == {'releaseGroup': '2HD', 'other': ['PROPER']}
True
"""
result = Guess()
if not guesses:
return result
if append is None:
append = []
for g in guesses:
# first append our appendable properties
for prop in append:
if prop in g:
result.set(prop, result.get(prop, []) + [g[prop]],
# TODO: what to do with confidence here? maybe an
# arithmetic mean...
confidence=g.metadata(prop).confidence,
input=g.metadata(prop).input,
span=g.metadata(prop).span,
prop=g.metadata(prop).prop)
del g[prop]
# then merge the remaining ones
dups = set(result) & set(g)
if dups:
log.warning('duplicate properties %s in merged result...' % [(result[p], g[p]) for p in dups])
result.update_highest_confidence(g)
# delete very unlikely values
for p in list(result.keys()):
if result.confidence(p) < 0.05:
del result[p]
# make sure our appendable properties contain unique values
for prop in append:
try:
value = result[prop]
if isinstance(value, list):
result[prop] = list(set(value))
else:
result[prop] = [value]
except KeyError:
pass
return result