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207 opy/pgen2/grammar.py
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# Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""This module defines the data structures used to represent a grammar.
These are a bit arcane because they are derived from the data
structures used by Python's 'pgen' parser generator.
There's also a table here mapping operators to their names in the
token module; the Python tokenize module reports all operators as the
fallback token code OP, but the parser needs the actual token code.
"""
# Python imports
import collections
import pickle
# Local imports
from . import token, tokenize
class Grammar(object):
"""Pgen parsing tables conversion class.
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 class here does not
provide initialization of the tables; several subclasses exist to
do this (see the conv and pgen modules).
The load() method reads the tables from a pickle file, which is
much faster than the other ways offered by subclasses. The pickle
file is written by calling dump() (after loading the grammar
tables using a subclass). The report() method prints a readable
representation of the tables to stdout, for debugging.
The instance variables are as follows:
symbol2number -- a dict mapping symbol names to numbers. Symbol
numbers are always 256 or higher, to distinguish
them from token numbers, which are between 0 and
255 (inclusive).
number2symbol -- a dict mapping numbers to symbol names;
these two are each other's inverse.
states -- a list of DFAs, where each DFA is a list of
states, each state is a list of arcs, and each
arc is a (i, j) pair where i is a label and j is
a state number. The DFA number is the index into
this list. (This name is slightly confusing.)
Final states are represented by a special arc of
the form (0, j) where j is its own state number.
dfas -- a dict mapping symbol numbers to (DFA, first)
pairs, where DFA is an item from the states list
above, and first is a set of tokens that can
begin this grammar rule (represented by a dict
whose values are always 1).
labels -- a list of (x, y) pairs where x is either a token
number or a symbol number, and y is either None
or a string; the strings are keywords. The label
number is the index in this list; label numbers
are used to mark state transitions (arcs) in the
DFAs.
start -- the number of the grammar's start symbol.
keywords -- a dict mapping keyword strings to arc labels.
tokens -- a dict mapping token numbers to arc labels.
"""
def __init__(self):
self.symbol2number = {}
self.number2symbol = {}
self.states = []
self.dfas = {}
self.labels = [(0, "EMPTY")]
self.keywords = {}
self.tokens = {}
self.symbol2label = {}
self.start = 256
def dump(self, filename):
"""Dump the grammar tables to a pickle file.
dump() recursively changes all dict to OrderedDict, so the pickled file
is not exactly the same as what was passed in to dump(). load() uses the
pickled file to create the tables, but only changes OrderedDict to dict
at the top level; it does not recursively change OrderedDict to dict.
So, the loaded tables are different from the original tables that were
passed to load() in that some of the OrderedDict (from the pickled file)
are not changed back to dict. For parsing, this has no effect on
performance because OrderedDict uses dict's __getitem__ with nothing in
between.
"""
with open(filename, "wb") as f:
d = _make_deterministic(self.__dict__)
pickle.dump(d, f, 2)
def load(self, filename):
"""Load the grammar tables from a pickle file."""
with open(filename, "rb") as f:
d = pickle.load(f)
self.__dict__.update(d)
def copy(self):
"""
Copy the grammar.
"""
new = self.__class__()
for dict_attr in ("symbol2number", "number2symbol", "dfas", "keywords",
"tokens", "symbol2label"):
setattr(new, dict_attr, getattr(self, dict_attr).copy())
new.labels = self.labels[:]
new.states = self.states[:]
new.start = self.start
return new
def report(self):
"""Dump the grammar tables to standard output, for debugging."""
from pprint import pprint
print("s2n")
pprint(self.symbol2number)
print("n2s")
pprint(self.number2symbol)
print("states")
pprint(self.states)
print("dfas")
pprint(self.dfas)
print("labels")
pprint(self.labels)
print("start", self.start)
def _make_deterministic(top):
if isinstance(top, dict):
return collections.OrderedDict(
sorted(((k, _make_deterministic(v)) for k, v in top.items())))
if isinstance(top, list):
return [_make_deterministic(e) for e in top]
if isinstance(top, tuple):
return tuple(_make_deterministic(e) for e in top)
return top
# Map from operator to number (since tokenize doesn't do this)
opmap_raw = """
( LPAR
) RPAR
[ LSQB
] RSQB
: COLON
, COMMA
; SEMI
+ PLUS
- MINUS
* STAR
/ SLASH
| VBAR
& AMPER
< LESS
> GREATER
= EQUAL
. DOT
% PERCENT
` BACKQUOTE
{ LBRACE
} RBRACE
@ AT
@= ATEQUAL
== EQEQUAL
!= NOTEQUAL
<> NOTEQUAL
<= LESSEQUAL
>= GREATEREQUAL
~ TILDE
^ CIRCUMFLEX
<< LEFTSHIFT
>> RIGHTSHIFT
** DOUBLESTAR
+= PLUSEQUAL
-= MINEQUAL
*= STAREQUAL
/= SLASHEQUAL
%= PERCENTEQUAL
&= AMPEREQUAL
|= VBAREQUAL
^= CIRCUMFLEXEQUAL
<<= LEFTSHIFTEQUAL
>>= RIGHTSHIFTEQUAL
**= DOUBLESTAREQUAL
// DOUBLESLASH
//= DOUBLESLASHEQUAL
-> RARROW
"""
opmap = {}
for line in opmap_raw.splitlines():
if line:
op, name = line.split()
opmap[op] = getattr(token, name)
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201 opy/pgen2/parse.py
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# 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.
"""
# Local imports
from . import token
class ParseError(Exception):
"""Exception to signal the parser is stuck."""
def __init__(self, msg, type, value, context):
Exception.__init__(self, "%s: type=%r, value=%r, context=%r" %
(msg, type, value, context))
self.msg = msg
self.type = type
self.value = value
self.context = context
class Parser(object):
"""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, convert=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.
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
self.convert = convert or (lambda grammar, node: node)
def setup(self, start=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 = (start, None, None, [])
stackentry = (self.grammar.dfas[start], 0, newnode)
self.stack = [stackentry]
self.rootnode = None
self.used_names = set() # Aliased to self.rootnode.used_names in pop()
def addtoken(self, type, value, context):
"""Add a token; return True iff this is the end of the program."""
# Map from token to label
ilabel = self.classify(type, value, context)
# 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, v = self.grammar.labels[i]
if ilabel == i:
# Look it up in the list of labels
assert t < 256
# 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
return False
elif 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, self.grammar.dfas[t], newstate, context)
break # To continue the outer while loop
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, value, context):
"""Turn a token into a label. (Internal)"""
if type == token.NAME:
# Keep a listing of all used names
self.used_names.add(value)
# Check for reserved words
ilabel = self.grammar.keywords.get(value)
if ilabel is not None:
return ilabel
ilabel = self.grammar.tokens.get(type)
if ilabel is None:
raise ParseError("bad token", type, value, context)
return ilabel
def shift(self, type, value, newstate, context):
"""Shift a token. (Internal)"""
dfa, state, node = self.stack[-1]
newnode = (type, value, context, None)
newnode = self.convert(self.grammar, newnode)
if newnode is not None:
node[-1].append(newnode)
self.stack[-1] = (dfa, newstate, node)
def push(self, type, newdfa, newstate, context):
"""Push a nonterminal. (Internal)"""
dfa, state, node = self.stack[-1]
newnode = (type, None, context, [])
self.stack[-1] = (dfa, newstate, node)
self.stack.append((newdfa, 0, newnode))
def pop(self):
"""Pop a nonterminal. (Internal)"""
popdfa, popstate, popnode = self.stack.pop()
newnode = self.convert(self.grammar, popnode)
if newnode is not None:
if self.stack:
dfa, state, node = self.stack[-1]
node[-1].append(newnode)
else:
self.rootnode = newnode
self.rootnode.used_names = self.used_names
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386 opy/pgen2/pgen.py
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# Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
# Pgen imports
from . import grammar, token, tokenize
class PgenGrammar(grammar.Grammar):
pass
class ParserGenerator(object):
def __init__(self, filename, stream=None):
close_stream = None
if stream is None:
stream = open(filename)
close_stream = stream.close
self.filename = filename
self.stream = stream
self.generator = tokenize.generate_tokens(stream.readline)
self.gettoken() # Initialize lookahead
self.dfas, self.startsymbol = self.parse()
if close_stream is not None:
close_stream()
self.first = {} # map from symbol name to set of tokens
self.addfirstsets()
def make_grammar(self):
c = PgenGrammar()
names = list(self.dfas.keys())
names.sort()
names.remove(self.startsymbol)
names.insert(0, self.startsymbol)
for name in names:
i = 256 + len(c.symbol2number)
c.symbol2number[name] = i
c.number2symbol[i] = name
for name in names:
dfa = self.dfas[name]
states = []
for state in dfa:
arcs = []
for label, next in sorted(state.arcs.items()):
arcs.append((self.make_label(c, label), dfa.index(next)))
if state.isfinal:
arcs.append((0, dfa.index(state)))
states.append(arcs)
c.states.append(states)
c.dfas[c.symbol2number[name]] = (states, self.make_first(c, name))
c.start = c.symbol2number[self.startsymbol]
return c
def make_first(self, c, name):
rawfirst = self.first[name]
first = {}
for label in sorted(rawfirst):
ilabel = self.make_label(c, label)
##assert ilabel not in first # XXX failed on <> ... !=
first[ilabel] = 1
return first
def make_label(self, c, label):
# XXX Maybe this should be a method on a subclass of converter?
ilabel = len(c.labels)
if label[0].isalpha():
# Either a symbol name or a named token
if label in c.symbol2number:
# A symbol name (a non-terminal)
if label in c.symbol2label:
return c.symbol2label[label]
else:
c.labels.append((c.symbol2number[label], None))
c.symbol2label[label] = ilabel
return ilabel
else:
# A named token (NAME, NUMBER, STRING)
itoken = getattr(token, label, None)
assert isinstance(itoken, int), label
assert itoken in token.tok_name, label
if itoken in c.tokens:
return c.tokens[itoken]
else:
c.labels.append((itoken, None))
c.tokens[itoken] = ilabel
return ilabel
else:
# Either a keyword or an operator
assert label[0] in ('"', "'"), label
value = eval(label)
if value[0].isalpha():
# A keyword
if value in c.keywords:
return c.keywords[value]
else:
c.labels.append((token.NAME, value))
c.keywords[value] = ilabel
return ilabel
else:
# An operator (any non-numeric token)
itoken = grammar.opmap[value] # Fails if unknown token
if itoken in c.tokens:
return c.tokens[itoken]
else:
c.labels.append((itoken, None))
c.tokens[itoken] = ilabel
return ilabel
def addfirstsets(self):
names = list(self.dfas.keys())
names.sort()
for name in names:
if name not in self.first:
self.calcfirst(name)
#print name, self.first[name].keys()
def calcfirst(self, name):
dfa = self.dfas[name]
self.first[name] = None # dummy to detect left recursion
state = dfa[0]
totalset = {}
overlapcheck = {}
for label, next in state.arcs.items():
if label in self.dfas:
if label in self.first:
fset = self.first[label]
if fset is None:
raise ValueError("recursion for rule %r" % name)
else:
self.calcfirst(label)
fset = self.first[label]
totalset.update(fset)
overlapcheck[label] = fset
else:
totalset[label] = 1
overlapcheck[label] = {label: 1}
inverse = {}
for label, itsfirst in overlapcheck.items():
for symbol in itsfirst:
if symbol in inverse:
raise ValueError("rule %s is ambiguous; %s is in the"
" first sets of %s as well as %s" %
(name, symbol, label, inverse[symbol]))
inverse[symbol] = label
self.first[name] = totalset
def parse(self):
dfas = {}
startsymbol = None
# MSTART: (NEWLINE | RULE)* ENDMARKER
while self.type != token.ENDMARKER:
while self.type == token.NEWLINE:
self.gettoken()
# RULE: NAME ':' RHS NEWLINE
name = self.expect(token.NAME)
self.expect(token.OP, ":")
a, z = self.parse_rhs()
self.expect(token.NEWLINE)
#self.dump_nfa(name, a, z)
dfa = self.make_dfa(a, z)
#self.dump_dfa(name, dfa)
oldlen = len(dfa)
self.simplify_dfa(dfa)
newlen = len(dfa)
dfas[name] = dfa
#print name, oldlen, newlen
if startsymbol is None:
startsymbol = name
return dfas, startsymbol
def make_dfa(self, start, finish):
# 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. Let's represent sets as dicts with 1 for
# values.
assert isinstance(start, NFAState)
assert isinstance(finish, NFAState)
def closure(state):
base = {}
addclosure(state, base)
return base
def addclosure(state, base):
assert isinstance(state, NFAState)
if state in base:
return
base[state] = 1
for label, next in state.arcs:
if label is None:
addclosure(next, base)
states = [DFAState(closure(start), finish)]
for state in states: # NB states grows while we're iterating
arcs = {}
for nfastate in state.nfaset:
for label, next in nfastate.arcs:
if label is not None:
addclosure(next, arcs.setdefault(label, {}))
for label, nfaset in sorted(arcs.items()):
for st in states:
if st.nfaset == nfaset:
break
else:
st = DFAState(nfaset, finish)
states.append(st)
state.addarc(st, label)
return states # List of DFAState instances; first one is start
def dump_nfa(self, name, start, finish):
print("Dump of NFA for", name)
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_dfa(self, name, dfa):
print("Dump of DFA for", name)
for i, state in enumerate(dfa):
print(" State", i, state.isfinal and "(final)" or "")
for label, next in sorted(state.arcs.items()):
print(" %s -> %d" % (label, dfa.index(next)))
def simplify_dfa(self, dfa):
# 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.
# dfa is a list of DFAState instances
changes = True
while changes:
changes = False
for i, state_i in enumerate(dfa):
for j in range(i+1, len(dfa)):
state_j = dfa[j]
if state_i == state_j:
#print " unify", i, j
del dfa[j]
for state in dfa:
state.unifystate(state_j, state_i)
changes = True
break
def parse_rhs(self):
# RHS: ALT ('|' ALT)*
a, z = self.parse_alt()
if self.value != "|":
return a, z
else:
aa = NFAState()
zz = NFAState()
aa.addarc(a)
z.addarc(zz)
while self.value == "|":
self.gettoken()
a, z = self.parse_alt()
aa.addarc(a)
z.addarc(zz)
return aa, zz
def parse_alt(self):
# ALT: ITEM+
a, b = self.parse_item()
while (self.value in ("(", "[") or
self.type in (token.NAME, token.STRING)):
c, d = self.parse_item()
b.addarc(c)
b = d
return a, b
def parse_item(self):
# ITEM: '[' RHS ']' | ATOM ['+' | '*']
if self.value == "[":
self.gettoken()
a, z = self.parse_rhs()
self.expect(token.OP, "]")
a.addarc(z)
return a, z
else:
a, z = self.parse_atom()
value = self.value
if value not in ("+", "*"):
return a, z
self.gettoken()
z.addarc(a)
if value == "+":
return a, z
else:
return a, a
def parse_atom(self):
# ATOM: '(' RHS ')' | NAME | STRING
if self.value == "(":
self.gettoken()
a, z = self.parse_rhs()
self.expect(token.OP, ")")
return a, z
elif self.type in (token.NAME, token.STRING):
a = NFAState()
z = NFAState()
a.addarc(z, self.value)
self.gettoken()
return a, z
else:
self.raise_error("expected (...) or NAME or STRING, got %s/%s",
self.type, self.value)
def expect(self, type, value=None):
if self.type != type or (value is not None and self.value != value):
self.raise_error("expected %s/%s, got %s/%s",
type, value, self.type, self.value)
value = self.value
self.gettoken()
return value
def gettoken(self):
tup = next(self.generator)
while tup[0] in (tokenize.COMMENT, tokenize.NL):
tup = next(self.generator)
self.type, self.value, self.begin, self.end, self.line = tup
#print token.tok_name[self.type], repr(self.value)
def raise_error(self, msg, *args):
if args:
try:
msg = msg % args
except:
msg = " ".join([msg] + list(map(str, args)))
raise SyntaxError(msg, (self.filename, self.end[0],
self.end[1], self.line))
class NFAState(object):
def __init__(self):
self.arcs = [] # list of (label, NFAState) pairs
def addarc(self, next, label=None):
assert label is None or isinstance(label, str)
assert isinstance(next, NFAState)
self.arcs.append((label, next))
class DFAState(object):
def __init__(self, nfaset, final):
assert isinstance(nfaset, dict)
assert isinstance(next(iter(nfaset)), NFAState)
assert isinstance(final, NFAState)
self.nfaset = nfaset
self.isfinal = final in nfaset
self.arcs = {} # map from label to DFAState
def addarc(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 nfaset instance variable
assert isinstance(other, DFAState)
if self.isfinal != other.isfinal:
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 generate_grammar(filename="Grammar.txt"):
p = ParserGenerator(filename)
return p.make_grammar()
View
85 opy/pgen2/token.py
@@ -0,0 +1,85 @@
#! /usr/bin/env python3
"""Token constants (from "token.h")."""
# Taken from Python (r53757) and modified to include some tokens
# originally monkeypatched in by pgen2.tokenize
#--start constants--
ENDMARKER = 0
NAME = 1
NUMBER = 2
STRING = 3
NEWLINE = 4
INDENT = 5
DEDENT = 6
LPAR = 7
RPAR = 8
LSQB = 9
RSQB = 10
COLON = 11
COMMA = 12
SEMI = 13
PLUS = 14
MINUS = 15
STAR = 16
SLASH = 17
VBAR = 18
AMPER = 19
LESS = 20
GREATER = 21
EQUAL = 22
DOT = 23
PERCENT = 24
BACKQUOTE = 25
LBRACE = 26
RBRACE = 27
EQEQUAL = 28
NOTEQUAL = 29
LESSEQUAL = 30
GREATEREQUAL = 31
TILDE = 32
CIRCUMFLEX = 33
LEFTSHIFT = 34
RIGHTSHIFT = 35
DOUBLESTAR = 36
PLUSEQUAL = 37
MINEQUAL = 38
STAREQUAL = 39
SLASHEQUAL = 40
PERCENTEQUAL = 41
AMPEREQUAL = 42
VBAREQUAL = 43
CIRCUMFLEXEQUAL = 44
LEFTSHIFTEQUAL = 45
RIGHTSHIFTEQUAL = 46
DOUBLESTAREQUAL = 47
DOUBLESLASH = 48
DOUBLESLASHEQUAL = 49
AT = 50
ATEQUAL = 51
OP = 52
COMMENT = 53
NL = 54
RARROW = 55
AWAIT = 56
ASYNC = 57
ERRORTOKEN = 58
N_TOKENS = 59
NT_OFFSET = 256
#--end constants--
tok_name = {}
for _name, _value in list(globals().items()):
if type(_value) is type(0):
tok_name[_value] = _name
def ISTERMINAL(x):
return x < NT_OFFSET
def ISNONTERMINAL(x):
return x >= NT_OFFSET
def ISEOF(x):
return x == ENDMARKER
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576 opy/pgen2/tokenize.py

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40 opy/pygram.py
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# Copyright 2006 Google, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""Export the Python grammar and symbols."""
# Python imports
import os
# Local imports
from .pgen2 import token
from .pgen2 import driver
from . import pytree
# The grammar file
_GRAMMAR_FILE = os.path.join(os.path.dirname(__file__), "Grammar.txt")
_PATTERN_GRAMMAR_FILE = os.path.join(os.path.dirname(__file__),
"PatternGrammar.txt")
class Symbols(object):
def __init__(self, grammar):
"""Initializer.
Creates an attribute for each grammar symbol (nonterminal),
whose value is the symbol's type (an int >= 256).
"""
for name, symbol in grammar.symbol2number.items():
setattr(self, name, symbol)
python_grammar = driver.load_grammar(_GRAMMAR_FILE)
python_symbols = Symbols(python_grammar)
python_grammar_no_print_statement = python_grammar.copy()
del python_grammar_no_print_statement.keywords["print"]
pattern_grammar = driver.load_grammar(_PATTERN_GRAMMAR_FILE)
pattern_symbols = Symbols(pattern_grammar)
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854 opy/pytree.py

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