# 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 = <char*>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 = <attr_t*>mem.alloc(doc.length * nr_extra_attr, sizeof(attr_t))
else:
nr_extra_attr = 0
extra_attr_values = <attr_t*>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 = <TokenPatternC*>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 = <AttrValueC*>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 = <IndexValueC*>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 = <int32_t*>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 = <AttrValueC*>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