# Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""Parser engine for the grammar tables generated by pgen.
The grammar table must be loaded first.
See Parser/parser.c in the Python distribution for additional info on
how this parsing engine works.
"""
from contextlib import contextmanager
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Iterator,
List,
Optional,
Set,
Tuple,
Union,
cast,
)
from blib2to3.pgen2.grammar import Grammar
from blib2to3.pytree import NL, Context, Leaf, Node, RawNode, convert
# Local imports
from . import grammar, token, tokenize
if TYPE_CHECKING:
from blib2to3.pgen2.driver import TokenProxy
Results = Dict[str, NL]
Convert = Callable[[Grammar, RawNode], Union[Node, Leaf]]
DFA = List[List[Tuple[int, int]]]
DFAS = Tuple[DFA, Dict[int, int]]
def lam_sub(grammar: Grammar, node: RawNode) -> NL:
assert node[3] is not None
return Node(type=node[0], children=node[3], context=node[2])
# A placeholder node, used when parser is backtracking.
DUMMY_NODE = (-1, None, None, None)
def stack_copy(
stack: List[Tuple[DFAS, int, RawNode]],
) -> List[Tuple[DFAS, int, RawNode]]:
"""Nodeless stack copy."""
return [(dfa, label, DUMMY_NODE) for dfa, label, _ in stack]
class Recorder:
def __init__(self, parser: "Parser", ilabels: List[int], context: Context) -> None:
self.parser = parser
self._ilabels = ilabels
self.context = context # not really matter
self._dead_ilabels: Set[int] = set()
self._start_point = self.parser.stack
self._points = {ilabel: stack_copy(self._start_point) for ilabel in ilabels}
@property
def ilabels(self) -> Set[int]:
return self._dead_ilabels.symmetric_difference(self._ilabels)
@contextmanager
def switch_to(self, ilabel: int) -> Iterator[None]:
with self.backtrack():
self.parser.stack = self._points[ilabel]
try:
yield
except ParseError:
self._dead_ilabels.add(ilabel)
finally:
self.parser.stack = self._start_point
@contextmanager
def backtrack(self) -> Iterator[None]:
"""
Use the node-level invariant ones for basic parsing operations (push/pop/shift).
These still will operate on the stack; but they won't create any new nodes, or
modify the contents of any other existing nodes.
This saves us a ton of time when we are backtracking, since we
want to restore to the initial state as quick as possible, which
can only be done by having as little mutatations as possible.
"""
is_backtracking = self.parser.is_backtracking
try:
self.parser.is_backtracking = True
yield
finally:
self.parser.is_backtracking = is_backtracking
def add_token(self, tok_type: int, tok_val: str, raw: bool = False) -> None:
func: Callable[..., Any]
if raw:
func = self.parser._addtoken
else:
func = self.parser.addtoken
for ilabel in self.ilabels:
with self.switch_to(ilabel):
args = [tok_type, tok_val, self.context]
if raw:
args.insert(0, ilabel)
func(*args)
def determine_route(
self, value: Optional[str] = None, force: bool = False
) -> Optional[int]:
alive_ilabels = self.ilabels
if len(alive_ilabels) == 0:
*_, most_successful_ilabel = self._dead_ilabels
raise ParseError("bad input", most_successful_ilabel, value, self.context)
ilabel, *rest = alive_ilabels
if force or not rest:
return ilabel
else:
return None
class ParseError(Exception):
"""Exception to signal the parser is stuck."""
def __init__(
self, msg: str, type: Optional[int], value: Optional[str], context: Context
) -> None:
Exception.__init__(
self, f"{msg}: type={type!r}, value={value!r}, context={context!r}"
)
self.msg = msg
self.type = type
self.value = value
self.context = context
class Parser:
"""Parser engine.
The proper usage sequence is:
p = Parser(grammar, [converter]) # create instance
p.setup([start]) # prepare for parsing
<for each input token>:
if p.addtoken(...): # parse a token; may raise ParseError
break
root = p.rootnode # root of abstract syntax tree
A Parser instance may be reused by calling setup() repeatedly.
A Parser instance contains state pertaining to the current token
sequence, and should not be used concurrently by different threads
to parse separate token sequences.
See driver.py for how to get input tokens by tokenizing a file or
string.
Parsing is complete when addtoken() returns True; the root of the
abstract syntax tree can then be retrieved from the rootnode
instance variable. When a syntax error occurs, addtoken() raises
the ParseError exception. There is no error recovery; the parser
cannot be used after a syntax error was reported (but it can be
reinitialized by calling setup()).
"""
def __init__(self, grammar: Grammar, convert: Optional[Convert] = None) -> None:
"""Constructor.
The grammar argument is a grammar.Grammar instance; see the
grammar module for more information.
The parser is not ready yet for parsing; you must call the
setup() method to get it started.
The optional convert argument is a function mapping concrete
syntax tree nodes to abstract syntax tree nodes. If not
given, no conversion is done and the syntax tree produced is
the concrete syntax tree. If given, it must be a function of
two arguments, the first being the grammar (a grammar.Grammar
instance), and the second being the concrete syntax tree node
to be converted. The syntax tree is converted from the bottom
up.
**post-note: the convert argument is ignored since for Black's
usage, convert will always be blib2to3.pytree.convert. Allowing
this to be dynamic hurts mypyc's ability to use early binding.
These docs are left for historical and informational value.
A concrete syntax tree node is a (type, value, context, nodes)
tuple, where type is the node type (a token or symbol number),
value is None for symbols and a string for tokens, context is
None or an opaque value used for error reporting (typically a
(lineno, offset) pair), and nodes is a list of children for
symbols, and None for tokens.
An abstract syntax tree node may be anything; this is entirely
up to the converter function.
"""
self.grammar = grammar
# See note in docstring above. TL;DR this is ignored.
self.convert = convert or lam_sub
self.is_backtracking = False
self.last_token: Optional[int] = None
def setup(self, proxy: "TokenProxy", start: Optional[int] = None) -> None:
"""Prepare for parsing.
This *must* be called before starting to parse.
The optional argument is an alternative start symbol; it
defaults to the grammar's start symbol.
You can use a Parser instance to parse any number of programs;
each time you call setup() the parser is reset to an initial
state determined by the (implicit or explicit) start symbol.
"""
if start is None:
start = self.grammar.start
# Each stack entry is a tuple: (dfa, state, node).
# A node is a tuple: (type, value, context, children),
# where children is a list of nodes or None, and context may be None.
newnode: RawNode = (start, None, None, [])
stackentry = (self.grammar.dfas[start], 0, newnode)
self.stack: List[Tuple[DFAS, int, RawNode]] = [stackentry]
self.rootnode: Optional[NL] = None
self.used_names: Set[str] = set()
self.proxy = proxy
self.last_token = None
def addtoken(self, type: int, value: str, context: Context) -> bool:
"""Add a token; return True iff this is the end of the program."""
# Map from token to label
ilabels = self.classify(type, value, context)
assert len(ilabels) >= 1
# If we have only one state to advance, we'll directly
# take it as is.
if len(ilabels) == 1:
[ilabel] = ilabels
return self._addtoken(ilabel, type, value, context)
# If there are multiple states which we can advance (only
# happen under soft-keywords), then we will try all of them
# in parallel and as soon as one state can reach further than
# the rest, we'll choose that one. This is a pretty hacky
# and hopefully temporary algorithm.
#
# For a more detailed explanation, check out this post:
# https://tree.science/what-the-backtracking.html
with self.proxy.release() as proxy:
counter, force = 0, False
recorder = Recorder(self, ilabels, context)
recorder.add_token(type, value, raw=True)
next_token_value = value
while recorder.determine_route(next_token_value) is None:
if not proxy.can_advance(counter):
force = True
break
next_token_type, next_token_value, *_ = proxy.eat(counter)
if next_token_type in (tokenize.COMMENT, tokenize.NL):
counter += 1
continue
if next_token_type == tokenize.OP:
next_token_type = grammar.opmap[next_token_value]
recorder.add_token(next_token_type, next_token_value)
counter += 1
ilabel = cast(int, recorder.determine_route(next_token_value, force=force))
assert ilabel is not None
return self._addtoken(ilabel, type, value, context)
def _addtoken(self, ilabel: int, type: int, value: str, context: Context) -> bool:
# Loop until the token is shifted; may raise exceptions
while True:
dfa, state, node = self.stack[-1]
states, first = dfa
arcs = states[state]
# Look for a state with this label
for i, newstate in arcs:
t = self.grammar.labels[i][0]
if t >= 256:
# See if it's a symbol and if we're in its first set
itsdfa = self.grammar.dfas[t]
itsstates, itsfirst = itsdfa
if ilabel in itsfirst:
# Push a symbol
self.push(t, itsdfa, newstate, context)
break # To continue the outer while loop
elif ilabel == i:
# Look it up in the list of labels
# Shift a token; we're done with it
self.shift(type, value, newstate, context)
# Pop while we are in an accept-only state
state = newstate
while states[state] == [(0, state)]:
self.pop()
if not self.stack:
# Done parsing!
return True
dfa, state, node = self.stack[-1]
states, first = dfa
# Done with this token
self.last_token = type
return False
else:
if (0, state) in arcs:
# An accepting state, pop it and try something else
self.pop()
if not self.stack:
# Done parsing, but another token is input
raise ParseError("too much input", type, value, context)
else:
# No success finding a transition
raise ParseError("bad input", type, value, context)
def classify(self, type: int, value: str, context: Context) -> List[int]:
"""Turn a token into a label. (Internal)
Depending on whether the value is a soft-keyword or not,
this function may return multiple labels to choose from."""
if type == token.NAME:
# Keep a listing of all used names
self.used_names.add(value)
# Check for reserved words
if value in self.grammar.keywords:
return [self.grammar.keywords[value]]
elif value in self.grammar.soft_keywords:
assert type in self.grammar.tokens
# Current soft keywords (match, case, type) can only appear at the
# beginning of a statement. So as a shortcut, don't try to treat them
# like keywords in any other context.
# ('_' is also a soft keyword in the real grammar, but for our grammar
# it's just an expression, so we don't need to treat it specially.)
if self.last_token not in (
None,
token.INDENT,
token.DEDENT,
token.NEWLINE,
token.SEMI,
token.COLON,
):
return [self.grammar.tokens[type]]
return [
self.grammar.tokens[type],
self.grammar.soft_keywords[value],
]
ilabel = self.grammar.tokens.get(type)
if ilabel is None:
raise ParseError("bad token", type, value, context)
return [ilabel]
def shift(self, type: int, value: str, newstate: int, context: Context) -> None:
"""Shift a token. (Internal)"""
if self.is_backtracking:
dfa, state, _ = self.stack[-1]
self.stack[-1] = (dfa, newstate, DUMMY_NODE)
else:
dfa, state, node = self.stack[-1]
rawnode: RawNode = (type, value, context, None)
newnode = convert(self.grammar, rawnode)
assert node[-1] is not None
node[-1].append(newnode)
self.stack[-1] = (dfa, newstate, node)
def push(self, type: int, newdfa: DFAS, newstate: int, context: Context) -> None:
"""Push a nonterminal. (Internal)"""
if self.is_backtracking:
dfa, state, _ = self.stack[-1]
self.stack[-1] = (dfa, newstate, DUMMY_NODE)
self.stack.append((newdfa, 0, DUMMY_NODE))
else:
dfa, state, node = self.stack[-1]
newnode: RawNode = (type, None, context, [])
self.stack[-1] = (dfa, newstate, node)
self.stack.append((newdfa, 0, newnode))
def pop(self) -> None:
"""Pop a nonterminal. (Internal)"""
if self.is_backtracking:
self.stack.pop()
else:
popdfa, popstate, popnode = self.stack.pop()
newnode = convert(self.grammar, popnode)
if self.stack:
dfa, state, node = self.stack[-1]
assert node[-1] is not None
node[-1].append(newnode)
else:
self.rootnode = newnode
self.rootnode.used_names = self.used_names