378 lines
14 KiB
Python
378 lines
14 KiB
Python
# Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
|
|
# Licensed to PSF under a Contributor Agreement.
|
|
|
|
# Modifications:
|
|
# Copyright David Halter and Contributors
|
|
# Modifications are dual-licensed: MIT and PSF.
|
|
|
|
"""
|
|
This module defines the data structures used to represent a grammar.
|
|
|
|
Specifying grammars in pgen is possible with this grammar::
|
|
|
|
grammar: (NEWLINE | rule)* ENDMARKER
|
|
rule: NAME ':' rhs NEWLINE
|
|
rhs: items ('|' items)*
|
|
items: item+
|
|
item: '[' rhs ']' | atom ['+' | '*']
|
|
atom: '(' rhs ')' | NAME | STRING
|
|
|
|
This grammar is self-referencing.
|
|
|
|
This parser generator (pgen2) was created by Guido Rossum and used for lib2to3.
|
|
Most of the code has been refactored to make it more Pythonic. Since this was a
|
|
"copy" of the CPython Parser parser "pgen", there was some work needed to make
|
|
it more readable. It should also be slightly faster than the original pgen2,
|
|
because we made some optimizations.
|
|
"""
|
|
|
|
from ast import literal_eval
|
|
|
|
from parso.pgen2.grammar_parser import GrammarParser, NFAState
|
|
|
|
|
|
class Grammar(object):
|
|
"""
|
|
Once initialized, this class supplies the grammar tables for the
|
|
parsing engine implemented by parse.py. The parsing engine
|
|
accesses the instance variables directly.
|
|
|
|
The only important part in this parsers are dfas and transitions between
|
|
dfas.
|
|
"""
|
|
|
|
def __init__(self, start_nonterminal, rule_to_dfas, reserved_syntax_strings):
|
|
self.nonterminal_to_dfas = rule_to_dfas # Dict[str, List[DFAState]]
|
|
self.reserved_syntax_strings = reserved_syntax_strings
|
|
self.start_nonterminal = start_nonterminal
|
|
|
|
|
|
class DFAPlan(object):
|
|
"""
|
|
Plans are used for the parser to create stack nodes and do the proper
|
|
DFA state transitions.
|
|
"""
|
|
def __init__(self, next_dfa, dfa_pushes=[]):
|
|
self.next_dfa = next_dfa
|
|
self.dfa_pushes = dfa_pushes
|
|
|
|
def __repr__(self):
|
|
return '%s(%s, %s)' % (self.__class__.__name__, self.next_dfa, self.dfa_pushes)
|
|
|
|
|
|
class DFAState(object):
|
|
"""
|
|
The DFAState object is the core class for pretty much anything. DFAState
|
|
are the vertices of an ordered graph while arcs and transitions are the
|
|
edges.
|
|
|
|
Arcs are the initial edges, where most DFAStates are not connected and
|
|
transitions are then calculated to connect the DFA state machines that have
|
|
different nonterminals.
|
|
"""
|
|
def __init__(self, from_rule, nfa_set, final):
|
|
assert isinstance(nfa_set, set)
|
|
assert isinstance(next(iter(nfa_set)), NFAState)
|
|
assert isinstance(final, NFAState)
|
|
self.from_rule = from_rule
|
|
self.nfa_set = nfa_set
|
|
self.arcs = {} # map from terminals/nonterminals to DFAState
|
|
# In an intermediary step we set these nonterminal arcs (which has the
|
|
# same structure as arcs). These don't contain terminals anymore.
|
|
self.nonterminal_arcs = {}
|
|
|
|
# Transitions are basically the only thing that the parser is using
|
|
# with is_final. Everyting else is purely here to create a parser.
|
|
self.transitions = {} #: Dict[Union[TokenType, ReservedString], DFAPlan]
|
|
self.is_final = final in nfa_set
|
|
|
|
def add_arc(self, next_, label):
|
|
assert isinstance(label, str)
|
|
assert label not in self.arcs
|
|
assert isinstance(next_, DFAState)
|
|
self.arcs[label] = next_
|
|
|
|
def unifystate(self, old, new):
|
|
for label, next_ in self.arcs.items():
|
|
if next_ is old:
|
|
self.arcs[label] = new
|
|
|
|
def __eq__(self, other):
|
|
# Equality test -- ignore the nfa_set instance variable
|
|
assert isinstance(other, DFAState)
|
|
if self.is_final != other.is_final:
|
|
return False
|
|
# Can't just return self.arcs == other.arcs, because that
|
|
# would invoke this method recursively, with cycles...
|
|
if len(self.arcs) != len(other.arcs):
|
|
return False
|
|
for label, next_ in self.arcs.items():
|
|
if next_ is not other.arcs.get(label):
|
|
return False
|
|
return True
|
|
|
|
__hash__ = None # For Py3 compatibility.
|
|
|
|
def __repr__(self):
|
|
return '<%s: %s is_final=%s>' % (
|
|
self.__class__.__name__, self.from_rule, self.is_final
|
|
)
|
|
|
|
|
|
class ReservedString(object):
|
|
"""
|
|
Most grammars will have certain keywords and operators that are mentioned
|
|
in the grammar as strings (e.g. "if") and not token types (e.g. NUMBER).
|
|
This class basically is the former.
|
|
"""
|
|
|
|
def __init__(self, value):
|
|
self.value = value
|
|
|
|
def __repr__(self):
|
|
return '%s(%s)' % (self.__class__.__name__, self.value)
|
|
|
|
|
|
def _simplify_dfas(dfas):
|
|
"""
|
|
This is not theoretically optimal, but works well enough.
|
|
Algorithm: repeatedly look for two states that have the same
|
|
set of arcs (same labels pointing to the same nodes) and
|
|
unify them, until things stop changing.
|
|
|
|
dfas is a list of DFAState instances
|
|
"""
|
|
changes = True
|
|
while changes:
|
|
changes = False
|
|
for i, state_i in enumerate(dfas):
|
|
for j in range(i + 1, len(dfas)):
|
|
state_j = dfas[j]
|
|
if state_i == state_j:
|
|
#print " unify", i, j
|
|
del dfas[j]
|
|
for state in dfas:
|
|
state.unifystate(state_j, state_i)
|
|
changes = True
|
|
break
|
|
|
|
|
|
def _make_dfas(start, finish):
|
|
"""
|
|
Uses the powerset construction algorithm to create DFA states from sets of
|
|
NFA states.
|
|
|
|
Also does state reduction if some states are not needed.
|
|
"""
|
|
# To turn an NFA into a DFA, we define the states of the DFA
|
|
# to correspond to *sets* of states of the NFA. Then do some
|
|
# state reduction.
|
|
assert isinstance(start, NFAState)
|
|
assert isinstance(finish, NFAState)
|
|
|
|
def addclosure(nfa_state, base_nfa_set):
|
|
assert isinstance(nfa_state, NFAState)
|
|
if nfa_state in base_nfa_set:
|
|
return
|
|
base_nfa_set.add(nfa_state)
|
|
for nfa_arc in nfa_state.arcs:
|
|
if nfa_arc.nonterminal_or_string is None:
|
|
addclosure(nfa_arc.next, base_nfa_set)
|
|
|
|
base_nfa_set = set()
|
|
addclosure(start, base_nfa_set)
|
|
states = [DFAState(start.from_rule, base_nfa_set, finish)]
|
|
for state in states: # NB states grows while we're iterating
|
|
arcs = {}
|
|
# Find state transitions and store them in arcs.
|
|
for nfa_state in state.nfa_set:
|
|
for nfa_arc in nfa_state.arcs:
|
|
if nfa_arc.nonterminal_or_string is not None:
|
|
nfa_set = arcs.setdefault(nfa_arc.nonterminal_or_string, set())
|
|
addclosure(nfa_arc.next, nfa_set)
|
|
|
|
# Now create the dfa's with no None's in arcs anymore. All Nones have
|
|
# been eliminated and state transitions (arcs) are properly defined, we
|
|
# just need to create the dfa's.
|
|
for nonterminal_or_string, nfa_set in arcs.items():
|
|
for nested_state in states:
|
|
if nested_state.nfa_set == nfa_set:
|
|
# The DFA state already exists for this rule.
|
|
break
|
|
else:
|
|
nested_state = DFAState(start.from_rule, nfa_set, finish)
|
|
states.append(nested_state)
|
|
|
|
state.add_arc(nested_state, nonterminal_or_string)
|
|
return states # List of DFAState instances; first one is start
|
|
|
|
|
|
def _dump_nfa(start, finish):
|
|
print("Dump of NFA for", start.from_rule)
|
|
todo = [start]
|
|
for i, state in enumerate(todo):
|
|
print(" State", i, state is finish and "(final)" or "")
|
|
for label, next_ in state.arcs:
|
|
if next_ in todo:
|
|
j = todo.index(next_)
|
|
else:
|
|
j = len(todo)
|
|
todo.append(next_)
|
|
if label is None:
|
|
print(" -> %d" % j)
|
|
else:
|
|
print(" %s -> %d" % (label, j))
|
|
|
|
|
|
def _dump_dfas(dfas):
|
|
print("Dump of DFA for", dfas[0].from_rule)
|
|
for i, state in enumerate(dfas):
|
|
print(" State", i, state.is_final and "(final)" or "")
|
|
for nonterminal, next_ in state.arcs.items():
|
|
print(" %s -> %d" % (nonterminal, dfas.index(next_)))
|
|
|
|
|
|
def generate_grammar(bnf_grammar, token_namespace):
|
|
"""
|
|
``bnf_text`` is a grammar in extended BNF (using * for repetition, + for
|
|
at-least-once repetition, [] for optional parts, | for alternatives and ()
|
|
for grouping).
|
|
|
|
It's not EBNF according to ISO/IEC 14977. It's a dialect Python uses in its
|
|
own parser.
|
|
"""
|
|
rule_to_dfas = {}
|
|
start_nonterminal = None
|
|
for nfa_a, nfa_z in GrammarParser(bnf_grammar).parse():
|
|
#_dump_nfa(a, z)
|
|
dfas = _make_dfas(nfa_a, nfa_z)
|
|
#_dump_dfas(dfas)
|
|
# oldlen = len(dfas)
|
|
_simplify_dfas(dfas)
|
|
# newlen = len(dfas)
|
|
rule_to_dfas[nfa_a.from_rule] = dfas
|
|
#print(nfa_a.from_rule, oldlen, newlen)
|
|
|
|
if start_nonterminal is None:
|
|
start_nonterminal = nfa_a.from_rule
|
|
|
|
reserved_strings = {}
|
|
for nonterminal, dfas in rule_to_dfas.items():
|
|
for dfa_state in dfas:
|
|
for terminal_or_nonterminal, next_dfa in dfa_state.arcs.items():
|
|
if terminal_or_nonterminal in rule_to_dfas:
|
|
dfa_state.nonterminal_arcs[terminal_or_nonterminal] = next_dfa
|
|
else:
|
|
transition = _make_transition(
|
|
token_namespace,
|
|
reserved_strings,
|
|
terminal_or_nonterminal
|
|
)
|
|
dfa_state.transitions[transition] = DFAPlan(next_dfa)
|
|
|
|
_calculate_tree_traversal(rule_to_dfas)
|
|
return Grammar(start_nonterminal, rule_to_dfas, reserved_strings)
|
|
|
|
|
|
def _make_transition(token_namespace, reserved_syntax_strings, label):
|
|
"""
|
|
Creates a reserved string ("if", "for", "*", ...) or returns the token type
|
|
(NUMBER, STRING, ...) for a given grammar terminal.
|
|
"""
|
|
if label[0].isalpha():
|
|
# A named token (e.g. NAME, NUMBER, STRING)
|
|
return getattr(token_namespace, label)
|
|
else:
|
|
# Either a keyword or an operator
|
|
assert label[0] in ('"', "'"), label
|
|
assert not label.startswith('"""') and not label.startswith("'''")
|
|
value = literal_eval(label)
|
|
try:
|
|
return reserved_syntax_strings[value]
|
|
except KeyError:
|
|
r = reserved_syntax_strings[value] = ReservedString(value)
|
|
return r
|
|
|
|
|
|
def _calculate_tree_traversal(nonterminal_to_dfas):
|
|
"""
|
|
By this point we know how dfas can move around within a stack node, but we
|
|
don't know how we can add a new stack node (nonterminal transitions).
|
|
"""
|
|
# Map from grammar rule (nonterminal) name to a set of tokens.
|
|
first_plans = {}
|
|
|
|
nonterminals = list(nonterminal_to_dfas.keys())
|
|
nonterminals.sort()
|
|
for nonterminal in nonterminals:
|
|
if nonterminal not in first_plans:
|
|
_calculate_first_plans(nonterminal_to_dfas, first_plans, nonterminal)
|
|
|
|
# Now that we have calculated the first terminals, we are sure that
|
|
# there is no left recursion.
|
|
|
|
for dfas in nonterminal_to_dfas.values():
|
|
for dfa_state in dfas:
|
|
transitions = dfa_state.transitions
|
|
for nonterminal, next_dfa in dfa_state.nonterminal_arcs.items():
|
|
for transition, pushes in first_plans[nonterminal].items():
|
|
if transition in transitions:
|
|
prev_plan = transitions[transition]
|
|
# Make sure these are sorted so that error messages are
|
|
# at least deterministic
|
|
choices = sorted([
|
|
(
|
|
prev_plan.dfa_pushes[0].from_rule
|
|
if prev_plan.dfa_pushes
|
|
else prev_plan.next_dfa.from_rule
|
|
),
|
|
(
|
|
pushes[0].from_rule
|
|
if pushes else next_dfa.from_rule
|
|
),
|
|
])
|
|
raise ValueError(
|
|
"Rule %s is ambiguous; given a %s token, we "
|
|
"can't determine if we should evaluate %s or %s."
|
|
% (
|
|
(
|
|
dfa_state.from_rule,
|
|
transition,
|
|
) + tuple(choices)
|
|
)
|
|
)
|
|
transitions[transition] = DFAPlan(next_dfa, pushes)
|
|
|
|
|
|
def _calculate_first_plans(nonterminal_to_dfas, first_plans, nonterminal):
|
|
"""
|
|
Calculates the first plan in the first_plans dictionary for every given
|
|
nonterminal. This is going to be used to know when to create stack nodes.
|
|
"""
|
|
dfas = nonterminal_to_dfas[nonterminal]
|
|
new_first_plans = {}
|
|
first_plans[nonterminal] = None # dummy to detect left recursion
|
|
# We only need to check the first dfa. All the following ones are not
|
|
# interesting to find first terminals.
|
|
state = dfas[0]
|
|
for transition, next_ in state.transitions.items():
|
|
# It's a string. We have finally found a possible first token.
|
|
new_first_plans[transition] = [next_.next_dfa]
|
|
|
|
for nonterminal2, next_ in state.nonterminal_arcs.items():
|
|
# It's a nonterminal and we have either a left recursion issue
|
|
# in the grammar or we have to recurse.
|
|
try:
|
|
first_plans2 = first_plans[nonterminal2]
|
|
except KeyError:
|
|
first_plans2 = _calculate_first_plans(nonterminal_to_dfas, first_plans, nonterminal2)
|
|
else:
|
|
if first_plans2 is None:
|
|
raise ValueError("left recursion for rule %r" % nonterminal)
|
|
|
|
for t, pushes in first_plans2.items():
|
|
new_first_plans[t] = [next_] + pushes
|
|
|
|
first_plans[nonterminal] = new_first_plans
|
|
return new_first_plans
|