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- "This module implements an Earley Parser"
-
- # The parser uses a parse-forest to keep track of derivations and ambiguations.
- # When the parse ends successfully, a disambiguation stage resolves all ambiguity
- # (right now ambiguity resolution is not developed beyond the needs of lark)
- # Afterwards the parse tree is reduced (transformed) according to user callbacks.
- # I use the no-recursion version of Transformer, because the tree might be
- # deeper than Python's recursion limit (a bit absurd, but that's life)
- #
- # The algorithm keeps track of each state set, using a corresponding Column instance.
- # Column keeps track of new items using NewsList instances.
- #
- # Author: Erez Shinan (2017)
- # Email : erezshin@gmail.com
-
- from ..common import ParseError, UnexpectedToken, is_terminal
- from ..tree import Tree, Transformer_NoRecurse
- from .grammar_analysis import GrammarAnalyzer
-
-
- class Derivation(Tree):
- _hash = None
-
- def __init__(self, rule, items=None):
- Tree.__init__(self, 'drv', items or [])
- self.rule = rule
-
- def _pretty_label(self): # Nicer pretty for debugging the parser
- return self.rule.origin if self.rule else self.data
-
- def __hash__(self):
- if self._hash is None:
- self._hash = Tree.__hash__(self)
- return self._hash
-
- class Item(object):
- "An Earley Item, the atom of the algorithm."
-
- def __init__(self, rule, ptr, start, tree):
- self.rule = rule
- self.ptr = ptr
- self.start = start
- self.tree = tree if tree is not None else Derivation(self.rule)
-
- @property
- def expect(self):
- return self.rule.expansion[self.ptr]
-
- @property
- def is_complete(self):
- return self.ptr == len(self.rule.expansion)
-
- def advance(self, tree):
- assert self.tree.data == 'drv'
- new_tree = Derivation(self.rule, self.tree.children + [tree])
- return self.__class__(self.rule, self.ptr+1, self.start, new_tree)
-
- def __eq__(self, other):
- return self.start is other.start and self.ptr == other.ptr and self.rule == other.rule
-
- def __hash__(self):
- return hash((self.rule, self.ptr, id(self.start))) # Always runs Derivation.__hash__
-
- def __repr__(self):
- before = list(map(str, self.rule.expansion[:self.ptr]))
- after = list(map(str, self.rule.expansion[self.ptr:]))
- return '<(%d) %s : %s * %s>' % (id(self.start), self.rule.origin, ' '.join(before), ' '.join(after))
-
- class NewsList(list):
- "Keeps track of newly added items (append-only)"
-
- def __init__(self, initial=None):
- list.__init__(self, initial or [])
- self.last_iter = 0
-
- def get_news(self):
- i = self.last_iter
- self.last_iter = len(self)
- return self[i:]
-
-
-
- class Column:
- "An entry in the table, aka Earley Chart. Contains lists of items."
- def __init__(self, i, FIRST, predict_all=False):
- self.i = i
- self.to_reduce = NewsList()
- self.to_predict = NewsList()
- self.to_scan = []
- self.item_count = 0
- self.FIRST = FIRST
-
- self.predicted = set()
- self.completed = {}
- self.predict_all = predict_all
-
- def add(self, items):
- """Sort items into scan/predict/reduce newslists
-
- Makes sure only unique items are added.
- """
- for item in items:
-
- item_key = item, item.tree # Elsewhere, tree is not part of the comparison
- if item.is_complete:
- # XXX Potential bug: What happens if there's ambiguity in an empty rule?
- if item.rule.expansion and item_key in self.completed:
- old_tree = self.completed[item_key].tree
- if old_tree == item.tree:
- is_empty = not self.FIRST[item.rule.origin]
- if not is_empty:
- continue
-
- if old_tree.data != '_ambig':
- new_tree = old_tree.copy()
- new_tree.rule = old_tree.rule
- old_tree.set('_ambig', [new_tree])
- old_tree.rule = None # No longer a 'drv' node
-
- if item.tree.children[0] is old_tree: # XXX a little hacky!
- raise ParseError("Infinite recursion in grammar! (Rule %s)" % item.rule)
-
- if item.tree not in old_tree.children:
- old_tree.children.append(item.tree)
- # old_tree.children.append(item.tree)
- else:
- self.completed[item_key] = item
- self.to_reduce.append(item)
- else:
- if is_terminal(item.expect):
- self.to_scan.append(item)
- else:
- k = item_key if self.predict_all else item
- if k in self.predicted:
- continue
- self.predicted.add(k)
- self.to_predict.append(item)
-
- self.item_count += 1 # Only count if actually added
-
-
- def __bool__(self):
- return bool(self.item_count)
- __nonzero__ = __bool__ # Py2 backwards-compatibility
-
- class Parser:
- def __init__(self, parser_conf, term_matcher, resolve_ambiguity=None):
- self.analysis = GrammarAnalyzer(parser_conf)
- self.parser_conf = parser_conf
- self.resolve_ambiguity = resolve_ambiguity
-
- self.FIRST = self.analysis.FIRST
- self.postprocess = {}
- self.predictions = {}
- for rule in parser_conf.rules:
- self.postprocess[rule] = rule.alias if callable(rule.alias) else getattr(parser_conf.callback, rule.alias)
- self.predictions[rule.origin] = [x.rule for x in self.analysis.expand_rule(rule.origin)]
-
- self.term_matcher = term_matcher
-
-
- def parse(self, stream, start_symbol=None):
- # Define parser functions
- start_symbol = start_symbol or self.parser_conf.start
-
- _Item = Item
- match = self.term_matcher
-
- def predict(nonterm, column):
- assert not is_terminal(nonterm), nonterm
- return [_Item(rule, 0, column, None) for rule in self.predictions[nonterm]]
-
- def complete(item):
- name = item.rule.origin
- return [i.advance(item.tree) for i in item.start.to_predict if i.expect == name]
-
- def predict_and_complete(column):
- while True:
- to_predict = {x.expect for x in column.to_predict.get_news()
- if x.ptr} # if not part of an already predicted batch
- to_reduce = set(column.to_reduce.get_news())
- if not (to_predict or to_reduce):
- break
-
- for nonterm in to_predict:
- column.add( predict(nonterm, column) )
-
- for item in to_reduce:
- new_items = list(complete(item))
- if item in new_items:
- raise ParseError('Infinite recursion detected! (rule %s)' % item.rule)
- column.add(new_items)
-
- def scan(i, token, column):
- next_set = Column(i, self.FIRST)
- next_set.add(item.advance(token) for item in column.to_scan if match(item.expect, token))
-
- if not next_set:
- expect = {i.expect for i in column.to_scan}
- raise UnexpectedToken(token, expect, stream, i)
-
- return next_set
-
- # Main loop starts
- column0 = Column(0, self.FIRST)
- column0.add(predict(start_symbol, column0))
-
- column = column0
- for i, token in enumerate(stream):
- predict_and_complete(column)
- column = scan(i, token, column)
-
- predict_and_complete(column)
-
- # Parse ended. Now build a parse tree
- solutions = [n.tree for n in column.to_reduce
- if n.rule.origin==start_symbol and n.start is column0]
-
- if not solutions:
- raise ParseError('Incomplete parse: Could not find a solution to input')
- elif len(solutions) == 1:
- tree = solutions[0]
- else:
- tree = Tree('_ambig', solutions)
-
- if self.resolve_ambiguity:
- tree = self.resolve_ambiguity(tree)
-
- return ApplyCallbacks(self.postprocess).transform(tree)
-
-
- class ApplyCallbacks(Transformer_NoRecurse):
- def __init__(self, postprocess):
- self.postprocess = postprocess
-
- def drv(self, tree):
- return self.postprocess[tree.rule](tree.children)
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