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Update Matcher API
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@ -87,7 +87,7 @@ ctypedef TokenPatternC* TokenPatternC_ptr
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ctypedef pair[int, TokenPatternC_ptr] StateC
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cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id, attr_t label,
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cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id,
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object token_specs) except NULL:
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pattern = <TokenPatternC*>mem.alloc(len(token_specs) + 1, sizeof(TokenPatternC))
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cdef int i
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@ -99,15 +99,21 @@ cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id, attr_t label,
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pattern[i].attrs[j].attr = attr
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pattern[i].attrs[j].value = value
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i = len(token_specs)
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pattern[i].attrs = <AttrValueC*>mem.alloc(3, sizeof(AttrValueC))
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pattern[i].attrs = <AttrValueC*>mem.alloc(2, sizeof(AttrValueC))
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pattern[i].attrs[0].attr = ID
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pattern[i].attrs[0].value = entity_id
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pattern[i].attrs[1].attr = ENT_TYPE
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pattern[i].attrs[1].value = label
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pattern[i].nr_attr = 0
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return pattern
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cdef attr_t get_pattern_key(const TokenPatternC* pattern) except 0:
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while pattern.nr_attr != 0:
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pattern += 1
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id_attr = pattern[0].attrs[0]
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assert id_attr.attr == ID
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return id_attr.value
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cdef int get_action(const TokenPatternC* pattern, const TokenC* token) nogil:
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for attr in pattern.attrs[:pattern.nr_attr]:
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if get_token_attr(token, attr.attr) != attr.value:
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@ -175,12 +181,11 @@ cdef class Matcher:
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cdef public object _callbacks
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cdef public object _acceptors
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def __init__(self, vocab, patterns={}):
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def __init__(self, vocab):
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"""Create the Matcher.
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vocab (Vocab): The vocabulary object, which must be shared with the
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documents the matcher will operate on.
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patterns (dict): Patterns to add to the matcher.
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RETURNS (Matcher): The newly constructed object.
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"""
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self._patterns = {}
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@ -189,123 +194,105 @@ cdef class Matcher:
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self._callbacks = {}
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self.vocab = vocab
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self.mem = Pool()
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for entity_key, (etype, attrs, specs) in sorted(patterns.items()):
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self.add_entity(entity_key, attrs)
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for spec in specs:
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self.add_pattern(entity_key, spec, label=etype)
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def __reduce__(self):
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return (self.__class__, (self.vocab, self._patterns), None, None)
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property n_patterns:
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def __get__(self): return self.patterns.size()
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def __len__(self):
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return len(self._patterns)
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def add_entity(self, entity_key, attrs=None, if_exists='raise',
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acceptor=None, on_match=None):
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# TODO: replace with new Matcher.add()
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"""Add an entity to the matcher.
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def __contains__(self, key):
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return len(self._patterns)
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entity_key (unicode or int): An ID for the entity.
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attrs (dict): Attributes to associate with the `Matcher`.
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if_exists (unicode): `'raise'`, `'ignore'` or `'update'`. Controls what
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happens if the entity ID already exists. Defaults to `'raise'`.
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acceptor (function): Callback function to filter matches of the entity.
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on_match (function): Callback function to act on matches of the entity.
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def add(self, key, on_match, *patterns):
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"""Add a match-rule to the matcher.
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A match-rule consists of: an ID key, an on_match callback,
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and one or more patterns. If the key exists, the patterns
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are appended to the previous ones, and the previous on_match
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callback is replaced.
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The on_match callback will receive the arguments
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(matcher, doc, i, matches). Note that if no `on_match`
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callback is specified, the document will not be modified.
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A pattern consists of one or more token_specs,
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where a token_spec is a dictionary mapping
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attribute IDs to values. Token descriptors can also
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include quantifiers. There are currently important
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known problems with the quantifiers --- see the docs.
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"""
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if if_exists not in ('raise', 'ignore', 'update'):
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raise ValueError(
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"Unexpected value for if_exists: %s.\n"
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"Expected one of: ['raise', 'ignore', 'update']" % if_exists)
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if attrs is None:
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attrs = {}
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entity_key = self.normalize_entity_key(entity_key)
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if self.has_entity(entity_key):
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if if_exists == 'raise':
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raise KeyError(
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"Tried to add entity %s. Entity exists, and if_exists='raise'.\n"
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"Set if_exists='ignore' or if_exists='update', or check with "
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"matcher.has_entity()")
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elif if_exists == 'ignore':
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return
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self._entities[entity_key] = dict(attrs)
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self._patterns.setdefault(entity_key, [])
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self._acceptors[entity_key] = acceptor
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self._callbacks[entity_key] = on_match
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for pattern in patterns:
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if len(pattern) == 0:
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msg = ("Cannot add pattern for zero tokens to matcher.\n"
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"key: {key}\n")
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raise ValueError(msg.format(key=key))
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key = self._normalize_key(key)
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self._patterns.setdefault(key, [])
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self._callbacks[key] = on_match
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def add_pattern(self, entity_key, token_specs, label=""):
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# TODO: replace with new Matcher.add()
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"""Add a pattern to the matcher.
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for pattern in patterns:
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specs = _convert_strings(pattern, self.vocab.strings)
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self.patterns.push_back(init_pattern(self.mem, key, specs))
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self._patterns[key].append(specs)
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entity_key (unicode): An ID for the entity.
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token_specs (list): Description of the pattern to be matched.
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label (unicode): Label to assign to the matched pattern. Defaults to `""`.
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def remove(self, key):
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"""Remove a rule from the matcher.
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A KeyError is raised if the key does not exist.
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"""
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token_specs = list(token_specs)
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if len(token_specs) == 0:
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msg = ("Cannot add pattern for zero tokens to matcher.\n"
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"entity_key: {entity_key}\n"
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"label: {label}")
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raise ValueError(msg.format(entity_key=entity_key, label=label))
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entity_key = self.normalize_entity_key(entity_key)
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if not self.has_entity(entity_key):
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self.add_entity(entity_key)
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if isinstance(label, basestring):
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label = self.vocab.strings[label]
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elif label is None:
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label = 0
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spec = _convert_strings(token_specs, self.vocab.strings)
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key = self._normalize_key(key)
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self._patterns.pop(key)
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self._callbacks.pop(key)
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cdef int i = 0
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while i < self.patterns.size():
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pattern_key = get_pattern_key(self.patterns.at(i))
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if pattern_key == key:
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self.patterns.erase(self.patterns.begin()+i)
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else:
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i += 1
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self.patterns.push_back(init_pattern(self.mem, entity_key, label, spec))
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self._patterns[entity_key].append((label, token_specs))
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def has_key(self, key):
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"""Check whether the matcher has a rule with a given key.
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def add(self, entity_key, label, attrs, specs, acceptor=None, on_match=None):
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# TODO: replace with new Matcher.add()
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self.add_entity(entity_key, attrs=attrs, if_exists='update',
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acceptor=acceptor, on_match=on_match)
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for spec in specs:
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self.add_pattern(entity_key, spec, label=label)
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def normalize_entity_key(self, entity_key):
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if isinstance(entity_key, basestring):
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return self.vocab.strings[entity_key]
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else:
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return entity_key
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def has_entity(self, entity_key):
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# TODO: deprecate
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"""Check whether the matcher has an entity.
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entity_key (string or int): The entity key to check.
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RETURNS (bool): Whether the matcher has the entity.
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key (string or int): The key to check.
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RETURNS (bool): Whether the matcher has the rule.
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"""
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entity_key = self.normalize_entity_key(entity_key)
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return entity_key in self._entities
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key = self._normalize_key(key)
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return key in self._patterns
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def get_entity(self, entity_key):
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# TODO: deprecate
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"""Retrieve the attributes stored for an entity.
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def get(self, key, default=None):
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"""Retrieve the pattern stored for an entity.
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entity_key (unicode or int): The entity to retrieve.
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RETURNS (dict): The entity attributes if present, otherwise None.
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key (unicode or int): The key to retrieve.
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RETURNS (tuple): The rule, as an (on_match, patterns) tuple.
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"""
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entity_key = self.normalize_entity_key(entity_key)
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if entity_key in self._entities:
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return self._entities[entity_key]
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else:
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return None
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key = self._normalize_key(key)
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if key not in self._patterns:
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return default
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return (self._callbacks[key], self._patterns[key])
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def __call__(self, Doc doc, acceptor=None):
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def pipe(self, docs, batch_size=1000, n_threads=2):
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"""Match a stream of documents, yielding them in turn.
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docs (iterable): A stream of documents.
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batch_size (int): The number of documents to accumulate into a working set.
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n_threads (int): The number of threads with which to work on the buffer
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in parallel, if the `Matcher` implementation supports multi-threading.
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YIELDS (Doc): Documents, in order.
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"""
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for doc in docs:
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self(doc)
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yield doc
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def __call__(self, Doc doc):
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"""Find all token sequences matching the supplied patterns on the `Doc`.
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doc (Doc): The document to match over.
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RETURNS (list): A list of `(entity_key, label_id, start, end)` tuples,
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RETURNS (list): A list of `(key, label_id, start, end)` tuples,
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describing the matches. A match tuple describes a span
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`doc[start:end]`. The `label_id` and `entity_key` are both integers.
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`doc[start:end]`. The `label_id` and `key` are both integers.
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"""
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if acceptor is not None:
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raise ValueError(
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"acceptor keyword argument to Matcher deprecated. Specify acceptor "
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"functions when you add patterns instead.")
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cdef vector[StateC] partials
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cdef int n_partials = 0
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cdef int q = 0
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@ -343,13 +330,7 @@ cdef class Matcher:
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end = token_i+1
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ent_id = state.second[1].attrs[0].value
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label = state.second[1].attrs[1].value
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acceptor = self._acceptors.get(ent_id)
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if acceptor is None:
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matches.append((ent_id, label, start, end))
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else:
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match = acceptor(doc, ent_id, label, start, end)
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if match:
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matches.append(match)
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matches.append((ent_id, start, end))
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partials.resize(q)
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# Check whether we open any new patterns on this token
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for pattern in self.patterns:
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@ -374,13 +355,7 @@ cdef class Matcher:
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end = token_i+1
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ent_id = pattern[1].attrs[0].value
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label = pattern[1].attrs[1].value
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acceptor = self._acceptors.get(ent_id)
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if acceptor is None:
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matches.append((ent_id, label, start, end))
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else:
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match = acceptor(doc, ent_id, label, start, end)
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if match:
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matches.append(match)
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matches.append((ent_id, start, end))
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# Look for open patterns that are actually satisfied
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for state in partials:
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while state.second.quantifier in (ZERO, ZERO_PLUS):
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@ -390,13 +365,7 @@ cdef class Matcher:
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end = len(doc)
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ent_id = state.second.attrs[0].value
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label = state.second.attrs[0].value
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acceptor = self._acceptors.get(ent_id)
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if acceptor is None:
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matches.append((ent_id, label, start, end))
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else:
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match = acceptor(doc, ent_id, label, start, end)
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if match:
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matches.append(match)
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matches.append((ent_id, start, end))
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for i, (ent_id, label, start, end) in enumerate(matches):
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on_match = self._callbacks.get(ent_id)
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if on_match is not None:
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@ -404,18 +373,11 @@ cdef class Matcher:
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# TODO: only return (match_id, start, end)
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return matches
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def pipe(self, docs, batch_size=1000, n_threads=2):
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"""Match a stream of documents, yielding them in turn.
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docs (iterable): A stream of documents.
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batch_size (int): The number of documents to accumulate into a working set.
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n_threads (int): The number of threads with which to work on the buffer
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in parallel, if the `Matcher` implementation supports multi-threading.
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YIELDS (Doc): Documents, in order.
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"""
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for doc in docs:
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self(doc)
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yield doc
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def _normalize_key(self, key):
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if isinstance(key, basestring):
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return self.vocab.strings[key]
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else:
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return key
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def get_bilou(length):
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@ -116,8 +116,9 @@ p Match a stream of documents, yielding them in turn.
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+tag method
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p
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| Add one or more patterns to the matcher, along with a callback function
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| to handle the matches. The callback function will receive the arguments
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| Add a rule to the matcher, consisting of an ID key, one or more patterns, and
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| a callback function to act on the matches.
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| The callback function will receive the arguments
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| #[code matcher], #[code doc], #[code i] and #[code matches].
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+aside-code("Example").
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