# cython: infer_types=True # cython: profile=True from __future__ import unicode_literals from libcpp.vector cimport vector from libc.stdint cimport int32_t from cymem.cymem cimport Pool from murmurhash.mrmr cimport hash64 import re import srsly from ..typedefs cimport attr_t from ..structs cimport TokenC from ..vocab cimport Vocab from ..tokens.doc cimport Doc, get_token_attr from ..tokens.token cimport Token from ..attrs cimport ID, attr_id_t, NULL_ATTR, ORTH, POS, TAG, DEP, LEMMA from ._schemas import TOKEN_PATTERN_SCHEMA from ..util import get_json_validator, validate_json from ..errors import Errors, MatchPatternError, Warnings, deprecation_warning from ..strings import get_string_id from ..attrs import IDS DEF PADDING = 5 cdef class Matcher: """Match sequences of tokens, based on pattern rules. DOCS: https://spacy.io/api/matcher USAGE: https://spacy.io/usage/rule-based-matching """ def __init__(self, vocab, validate=False): """Create the Matcher. vocab (Vocab): The vocabulary object, which must be shared with the documents the matcher will operate on. RETURNS (Matcher): The newly constructed object. """ self._extra_predicates = [] self._patterns = {} self._callbacks = {} self._extensions = {} self._seen_attrs = set() self.vocab = vocab self.mem = Pool() if validate: self.validator = get_json_validator(TOKEN_PATTERN_SCHEMA) else: self.validator = None def __reduce__(self): data = (self.vocab, self._patterns, self._callbacks) return (unpickle_matcher, data, None, None) def __len__(self): """Get the number of rules added to the matcher. Note that this only returns the number of rules (identical with the number of IDs), not the number of individual patterns. RETURNS (int): The number of rules. """ return len(self._patterns) def __contains__(self, key): """Check whether the matcher contains rules for a match ID. key (unicode): The match ID. RETURNS (bool): Whether the matcher contains rules for this match ID. """ return self._normalize_key(key) in self._patterns def add(self, key, on_match, *patterns): """Add a match-rule to the matcher. A match-rule consists of: an ID key, an on_match callback, and one or more patterns. If the key exists, the patterns are appended to the previous ones, and the previous on_match callback is replaced. The `on_match` callback will receive the arguments `(matcher, doc, i, matches)`. You can also set `on_match` to `None` to not perform any actions. A pattern consists of one or more `token_specs`, where a `token_spec` is a dictionary mapping attribute IDs to values, and optionally a quantifier operator under the key "op". The available quantifiers are: '!': Negate the pattern, by requiring it to match exactly 0 times. '?': Make the pattern optional, by allowing it to match 0 or 1 times. '+': Require the pattern to match 1 or more times. '*': Allow the pattern to zero or more times. The + and * operators are usually interpretted "greedily", i.e. longer matches are returned where possible. However, if you specify two '+' and '*' patterns in a row and their matches overlap, the first operator will behave non-greedily. This quirk in the semantics makes the matcher more efficient, by avoiding the need for back-tracking. key (unicode): The match ID. on_match (callable): Callback executed on match. *patterns (list): List of token descriptions. """ errors = {} for i, pattern in enumerate(patterns): if len(pattern) == 0: raise ValueError(Errors.E012.format(key=key)) if self.validator: errors[i] = validate_json(pattern, self.validator) if any(err for err in errors.values()): raise MatchPatternError(key, errors) key = self._normalize_key(key) for pattern in patterns: try: specs = _preprocess_pattern(pattern, self.vocab.strings, self._extensions, self._extra_predicates) self.patterns.push_back(init_pattern(self.mem, key, specs)) for spec in specs: for attr, _ in spec[1]: self._seen_attrs.add(attr) except OverflowError, AttributeError: raise ValueError(Errors.E154.format()) self._patterns.setdefault(key, []) self._callbacks[key] = on_match self._patterns[key].extend(patterns) def remove(self, key): """Remove a rule from the matcher. A KeyError is raised if the key does not exist. key (unicode): The ID of the match rule. """ key = self._normalize_key(key) self._patterns.pop(key) self._callbacks.pop(key) cdef int i = 0 while i < self.patterns.size(): pattern_key = get_pattern_key(self.patterns.at(i)) if pattern_key == key: self.patterns.erase(self.patterns.begin()+i) else: i += 1 def has_key(self, key): """Check whether the matcher has a rule with a given key. key (string or int): The key to check. RETURNS (bool): Whether the matcher has the rule. """ key = self._normalize_key(key) return key in self._patterns def get(self, key, default=None): """Retrieve the pattern stored for a key. key (unicode or int): The key to retrieve. RETURNS (tuple): The rule, as an (on_match, patterns) tuple. """ key = self._normalize_key(key) if key not in self._patterns: return default return (self._callbacks[key], self._patterns[key]) def pipe(self, docs, batch_size=1000, n_threads=-1): """Match a stream of documents, yielding them in turn. docs (iterable): A stream of documents. batch_size (int): Number of documents to accumulate into a working set. YIELDS (Doc): Documents, in order. """ if n_threads != -1: deprecation_warning(Warnings.W016) for doc in docs: self(doc) yield doc def __call__(self, Doc doc): """Find all token sequences matching the supplied pattern. doc (Doc): The document to match over. RETURNS (list): A list of `(key, start, end)` tuples, describing the matches. A match tuple describes a span `doc[start:end]`. The `label_id` and `key` are both integers. """ if len(set([LEMMA, POS, TAG]) & self._seen_attrs) > 0 \ and not doc.is_tagged: raise ValueError(Errors.E155.format()) if DEP in self._seen_attrs and not doc.is_parsed: raise ValueError(Errors.E156.format()) matches = find_matches(&self.patterns[0], self.patterns.size(), doc, extensions=self._extensions, predicates=self._extra_predicates) for i, (key, start, end) in enumerate(matches): on_match = self._callbacks.get(key, None) if on_match is not None: on_match(self, doc, i, matches) return matches def _normalize_key(self, key): if isinstance(key, basestring): return self.vocab.strings.add(key) else: return key def unpickle_matcher(vocab, patterns, callbacks): matcher = Matcher(vocab) for key, specs in patterns.items(): callback = callbacks.get(key, None) matcher.add(key, callback, *specs) return matcher cdef find_matches(TokenPatternC** patterns, int n, Doc doc, extensions=None, predicates=tuple()): """Find matches in a doc, with a compiled array of patterns. Matches are returned as a list of (id, start, end) tuples. To augment the compiled patterns, we optionally also take two Python lists. The "predicates" list contains functions that take a Python list and return a boolean value. It's mostly used for regular expressions. The "extra_getters" list contains functions that take a Python list and return an attr ID. It's mostly used for extension attributes. """ cdef vector[PatternStateC] states cdef vector[MatchC] matches cdef PatternStateC state cdef int i, j, nr_extra_attr cdef Pool mem = Pool() predicate_cache = mem.alloc(doc.length * len(predicates), sizeof(char)) if extensions is not None and len(extensions) >= 1: nr_extra_attr = max(extensions.values()) + 1 extra_attr_values = mem.alloc(doc.length * nr_extra_attr, sizeof(attr_t)) else: nr_extra_attr = 0 extra_attr_values = mem.alloc(doc.length, sizeof(attr_t)) for i, token in enumerate(doc): for name, index in extensions.items(): value = token._.get(name) if isinstance(value, basestring): value = token.vocab.strings[value] extra_attr_values[i * nr_extra_attr + index] = value # Main loop cdef int nr_predicate = len(predicates) for i in range(doc.length): for j in range(n): states.push_back(PatternStateC(patterns[j], i, 0)) transition_states(states, matches, predicate_cache, doc[i], extra_attr_values, predicates) extra_attr_values += nr_extra_attr predicate_cache += len(predicates) # Handle matches that end in 0-width patterns finish_states(matches, states) output = [] seen = set() for i in range(matches.size()): match = ( matches[i].pattern_id, matches[i].start, matches[i].start+matches[i].length ) # We need to deduplicate, because we could otherwise arrive at the same # match through two paths, e.g. .?.? matching 'a'. Are we matching the # first .?, or the second .? -- it doesn't matter, it's just one match. if match not in seen: output.append(match) seen.add(match) return output cdef attr_t get_ent_id(const TokenPatternC* pattern) nogil: # There have been a few bugs here. # The code was originally designed to always have pattern[1].attrs.value # be the ent_id when we get to the end of a pattern. However, Issue #2671 # showed this wasn't the case when we had a reject-and-continue before a # match. # The patch to #2671 was wrong though, which came up in #3839. while pattern.attrs.attr != ID: pattern += 1 return pattern.attrs.value cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& matches, char* cached_py_predicates, Token token, const attr_t* extra_attrs, py_predicates) except *: cdef int q = 0 cdef vector[PatternStateC] new_states cdef int nr_predicate = len(py_predicates) for i in range(states.size()): if states[i].pattern.nr_py >= 1: update_predicate_cache(cached_py_predicates, states[i].pattern, token, py_predicates) action = get_action(states[i], token.c, extra_attrs, cached_py_predicates) if action == REJECT: continue # Keep only a subset of states (the active ones). Index q is the # states which are still alive. If we reject a state, we overwrite # it in the states list, because q doesn't advance. state = states[i] states[q] = state while action in (RETRY, RETRY_ADVANCE, RETRY_EXTEND): if action == RETRY_EXTEND: # This handles the 'extend' new_states.push_back( PatternStateC(pattern=states[q].pattern, start=state.start, length=state.length+1)) if action == RETRY_ADVANCE: # This handles the 'advance' new_states.push_back( PatternStateC(pattern=states[q].pattern+1, start=state.start, length=state.length+1)) states[q].pattern += 1 if states[q].pattern.nr_py != 0: update_predicate_cache(cached_py_predicates, states[q].pattern, token, py_predicates) action = get_action(states[q], token.c, extra_attrs, cached_py_predicates) if action == REJECT: pass elif action == ADVANCE: states[q].pattern += 1 states[q].length += 1 q += 1 else: ent_id = get_ent_id(state.pattern) if action == MATCH: matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length+1)) elif action == MATCH_DOUBLE: # push match without last token if length > 0 if state.length > 0: matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length)) # push match with last token matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length+1)) elif action == MATCH_REJECT: matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length)) elif action == MATCH_EXTEND: matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length)) states[q].length += 1 q += 1 states.resize(q) for i in range(new_states.size()): states.push_back(new_states[i]) cdef int update_predicate_cache(char* cache, const TokenPatternC* pattern, Token token, predicates) except -1: # If the state references any extra predicates, check whether they match. # These are cached, so that we don't call these potentially expensive # Python functions more than we need to. for i in range(pattern.nr_py): index = pattern.py_predicates[i] if cache[index] == 0: predicate = predicates[index] result = predicate(token) if result is True: cache[index] = 1 elif result is False: cache[index] = -1 elif result is None: pass else: raise ValueError(Errors.E125.format(value=result)) cdef void finish_states(vector[MatchC]& matches, vector[PatternStateC]& states) except *: """Handle states that end in zero-width patterns.""" cdef PatternStateC state for i in range(states.size()): state = states[i] while get_quantifier(state) in (ZERO_PLUS, ZERO_ONE): is_final = get_is_final(state) if is_final: ent_id = get_ent_id(state.pattern) matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length)) break else: state.pattern += 1 cdef action_t get_action(PatternStateC state, const TokenC* token, const attr_t* extra_attrs, const char* predicate_matches) nogil: """We need to consider: a) Does the token match the specification? [Yes, No] b) What's the quantifier? [1, 0+, ?] c) Is this the last specification? [final, non-final] We can transition in the following ways: a) Do we emit a match? b) Do we add a state with (next state, next token)? c) Do we add a state with (next state, same token)? d) Do we add a state with (same state, next token)? We'll code the actions as boolean strings, so 0000 means no to all 4, 1000 means match but no states added, etc. 1: Yes, final: 1000 Yes, non-final: 0100 No, final: 0000 No, non-final 0000 0+: Yes, final: 1001 Yes, non-final: 0011 No, final: 1000 (note: Don't include last token!) No, non-final: 0010 ?: Yes, final: 1000 Yes, non-final: 0100 No, final: 1000 (note: Don't include last token!) No, non-final: 0010 Possible combinations: 1000, 0100, 0000, 1001, 0110, 0011, 0010, We'll name the bits "match", "advance", "retry", "extend" REJECT = 0000 MATCH = 1000 ADVANCE = 0100 RETRY = 0010 MATCH_EXTEND = 1001 RETRY_ADVANCE = 0110 RETRY_EXTEND = 0011 MATCH_REJECT = 2000 # Match, but don't include last token MATCH_DOUBLE = 3000 # Match both with and without last token Problem: If a quantifier is matching, we're adding a lot of open partials """ cdef char is_match is_match = get_is_match(state, token, extra_attrs, predicate_matches) quantifier = get_quantifier(state) is_final = get_is_final(state) if quantifier == ZERO: is_match = not is_match quantifier = ONE if quantifier == ONE: if is_match and is_final: # Yes, final: 1000 return MATCH elif is_match and not is_final: # Yes, non-final: 0100 return ADVANCE elif not is_match and is_final: # No, final: 0000 return REJECT else: return REJECT elif quantifier == ZERO_PLUS: if is_match and is_final: # Yes, final: 1001 return MATCH_EXTEND elif is_match and not is_final: # Yes, non-final: 0011 return RETRY_EXTEND elif not is_match and is_final: # No, final 2000 (note: Don't include last token!) return MATCH_REJECT else: # No, non-final 0010 return RETRY elif quantifier == ZERO_ONE: if is_match and is_final: # Yes, final: 3000 # To cater for a pattern ending in "?", we need to add # a match both with and without the last token return MATCH_DOUBLE elif is_match and not is_final: # Yes, non-final: 0110 # We need both branches here, consider a pair like: # pattern: .?b string: b # If we 'ADVANCE' on the .?, we miss the match. return RETRY_ADVANCE elif not is_match and is_final: # No, final 2000 (note: Don't include last token!) return MATCH_REJECT else: # No, non-final 0010 return RETRY cdef char get_is_match(PatternStateC state, const TokenC* token, const attr_t* extra_attrs, const char* predicate_matches) nogil: for i in range(state.pattern.nr_py): if predicate_matches[state.pattern.py_predicates[i]] == -1: return 0 spec = state.pattern for attr in spec.attrs[:spec.nr_attr]: if get_token_attr(token, attr.attr) != attr.value: return 0 for i in range(spec.nr_extra_attr): if spec.extra_attrs[i].value != extra_attrs[spec.extra_attrs[i].index]: return 0 return True cdef char get_is_final(PatternStateC state) nogil: if state.pattern[1].attrs[0].attr == ID and state.pattern[1].nr_attr == 0: return 1 else: return 0 cdef char get_quantifier(PatternStateC state) nogil: return state.pattern.quantifier cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id, object token_specs) except NULL: pattern = mem.alloc(len(token_specs) + 1, sizeof(TokenPatternC)) cdef int i, index for i, (quantifier, spec, extensions, predicates) in enumerate(token_specs): pattern[i].quantifier = quantifier pattern[i].attrs = mem.alloc(len(spec), sizeof(AttrValueC)) pattern[i].nr_attr = len(spec) for j, (attr, value) in enumerate(spec): pattern[i].attrs[j].attr = attr pattern[i].attrs[j].value = value pattern[i].extra_attrs = mem.alloc(len(extensions), sizeof(IndexValueC)) for j, (index, value) in enumerate(extensions): pattern[i].extra_attrs[j].index = index pattern[i].extra_attrs[j].value = value pattern[i].nr_extra_attr = len(extensions) pattern[i].py_predicates = mem.alloc(len(predicates), sizeof(int32_t)) for j, index in enumerate(predicates): pattern[i].py_predicates[j] = index pattern[i].nr_py = len(predicates) pattern[i].key = hash64(pattern[i].attrs, pattern[i].nr_attr * sizeof(AttrValueC), 0) i = len(token_specs) pattern[i].attrs = mem.alloc(2, sizeof(AttrValueC)) pattern[i].attrs[0].attr = ID pattern[i].attrs[0].value = entity_id pattern[i].nr_attr = 0 pattern[i].nr_extra_attr = 0 pattern[i].nr_py = 0 return pattern cdef attr_t get_pattern_key(const TokenPatternC* pattern) nogil: while pattern.nr_attr != 0 or pattern.nr_extra_attr != 0 or pattern.nr_py != 0: pattern += 1 id_attr = pattern[0].attrs[0] if id_attr.attr != ID: with gil: raise ValueError(Errors.E074.format(attr=ID, bad_attr=id_attr.attr)) return id_attr.value def _preprocess_pattern(token_specs, string_store, extensions_table, extra_predicates): """This function interprets the pattern, converting the various bits of syntactic sugar before we compile it into a struct with init_pattern. We need to split the pattern up into three parts: * Normal attribute/value pairs, which are stored on either the token or lexeme, can be handled directly. * Extension attributes are handled specially, as we need to prefetch the values from Python for the doc before we begin matching. * Extra predicates also call Python functions, so we have to create the functions and store them. So we store these specially as well. * Extension attributes that have extra predicates are stored within the extra_predicates. """ tokens = [] for spec in token_specs: if not spec: # Signifier for 'any token' tokens.append((ONE, [(NULL_ATTR, 0)], [], [])) continue if not isinstance(spec, dict): raise ValueError(Errors.E154.format()) ops = _get_operators(spec) attr_values = _get_attr_values(spec, string_store) extensions = _get_extensions(spec, string_store, extensions_table) predicates = _get_extra_predicates(spec, extra_predicates) for op in ops: tokens.append((op, list(attr_values), list(extensions), list(predicates))) return tokens def _get_attr_values(spec, string_store): attr_values = [] for attr, value in spec.items(): if isinstance(attr, basestring): attr = attr.upper() if attr == '_': continue elif attr == "OP": continue if attr == "TEXT": attr = "ORTH" if attr not in TOKEN_PATTERN_SCHEMA["items"]["properties"]: raise ValueError(Errors.E152.format(attr=attr)) attr = IDS.get(attr) if isinstance(value, basestring): value = string_store.add(value) elif isinstance(value, bool): value = int(value) elif isinstance(value, dict): continue else: raise ValueError(Errors.E153.format(vtype=type(value).__name__)) if attr is not None: attr_values.append((attr, value)) else: # should be caught above using TOKEN_PATTERN_SCHEMA raise ValueError(Errors.E152.format(attr=attr)) return attr_values # These predicate helper classes are used to match the REGEX, IN, >= etc # extensions to the matcher introduced in #3173. class _RegexPredicate(object): operators = ("REGEX",) def __init__(self, i, attr, value, predicate, is_extension=False): self.i = i self.attr = attr self.value = re.compile(value) self.predicate = predicate self.is_extension = is_extension self.key = (attr, self.predicate, srsly.json_dumps(value, sort_keys=True)) if self.predicate not in self.operators: raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate)) def __call__(self, Token token): if self.is_extension: value = token._.get(self.attr) else: value = token.vocab.strings[get_token_attr(token.c, self.attr)] return bool(self.value.search(value)) class _SetMemberPredicate(object): operators = ("IN", "NOT_IN") def __init__(self, i, attr, value, predicate, is_extension=False): self.i = i self.attr = attr self.value = set(get_string_id(v) for v in value) self.predicate = predicate self.is_extension = is_extension self.key = (attr, self.predicate, srsly.json_dumps(value, sort_keys=True)) if self.predicate not in self.operators: raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate)) def __call__(self, Token token): if self.is_extension: value = get_string_id(token._.get(self.attr)) else: value = get_token_attr(token.c, self.attr) if self.predicate == "IN": return value in self.value else: return value not in self.value def __repr__(self): return repr(("SetMemberPredicate", self.i, self.attr, self.value, self.predicate)) class _ComparisonPredicate(object): operators = ("==", "!=", ">=", "<=", ">", "<") def __init__(self, i, attr, value, predicate, is_extension=False): self.i = i self.attr = attr self.value = value self.predicate = predicate self.is_extension = is_extension self.key = (attr, self.predicate, srsly.json_dumps(value, sort_keys=True)) if self.predicate not in self.operators: raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate)) def __call__(self, Token token): if self.is_extension: value = token._.get(self.attr) else: value = get_token_attr(token.c, self.attr) if self.predicate == "==": return value == self.value if self.predicate == "!=": return value != self.value elif self.predicate == ">=": return value >= self.value elif self.predicate == "<=": return value <= self.value elif self.predicate == ">": return value > self.value elif self.predicate == "<": return value < self.value def _get_extra_predicates(spec, extra_predicates): predicate_types = { "REGEX": _RegexPredicate, "IN": _SetMemberPredicate, "NOT_IN": _SetMemberPredicate, "==": _ComparisonPredicate, ">=": _ComparisonPredicate, "<=": _ComparisonPredicate, ">": _ComparisonPredicate, "<": _ComparisonPredicate, } seen_predicates = {pred.key: pred.i for pred in extra_predicates} output = [] for attr, value in spec.items(): if isinstance(attr, basestring): if attr == "_": output.extend( _get_extension_extra_predicates( value, extra_predicates, predicate_types, seen_predicates)) continue elif attr.upper() == "OP": continue if attr.upper() == "TEXT": attr = "ORTH" attr = IDS.get(attr.upper()) if isinstance(value, dict): for type_, cls in predicate_types.items(): if type_ in value: predicate = cls(len(extra_predicates), attr, value[type_], type_) # Don't create a redundant predicates. # This helps with efficiency, as we're caching the results. if predicate.key in seen_predicates: output.append(seen_predicates[predicate.key]) else: extra_predicates.append(predicate) output.append(predicate.i) seen_predicates[predicate.key] = predicate.i return output def _get_extension_extra_predicates(spec, extra_predicates, predicate_types, seen_predicates): output = [] for attr, value in spec.items(): if isinstance(value, dict): for type_, cls in predicate_types.items(): if type_ in value: key = (attr, type_, srsly.json_dumps(value[type_], sort_keys=True)) if key in seen_predicates: output.append(seen_predicates[key]) else: predicate = cls(len(extra_predicates), attr, value[type_], type_, is_extension=True) extra_predicates.append(predicate) output.append(predicate.i) seen_predicates[key] = predicate.i return output def _get_operators(spec): # Support 'syntactic sugar' operator '+', as combination of ONE, ZERO_PLUS lookup = {"*": (ZERO_PLUS,), "+": (ONE, ZERO_PLUS), "?": (ZERO_ONE,), "1": (ONE,), "!": (ZERO,)} # Fix casing spec = {key.upper(): values for key, values in spec.items() if isinstance(key, basestring)} if "OP" not in spec: return (ONE,) elif spec["OP"] in lookup: return lookup[spec["OP"]] else: keys = ", ".join(lookup.keys()) raise ValueError(Errors.E011.format(op=spec["OP"], opts=keys)) def _get_extensions(spec, string_store, name2index): attr_values = [] if not isinstance(spec.get("_", {}), dict): raise ValueError(Errors.E154.format()) for name, value in spec.get("_", {}).items(): if isinstance(value, dict): # Handle predicates (e.g. "IN", in the extra_predicates, not here. continue if isinstance(value, basestring): value = string_store.add(value) if name not in name2index: name2index[name] = len(name2index) attr_values.append((name2index[name], value)) return attr_values