#======================================================================= # # Python Lexical Analyser # # Lexical Analyser Specification # #======================================================================= from __future__ import absolute_import import types from . import Actions from . import DFA from . import Errors from . import Machines from . import Regexps # debug_flags for Lexicon constructor DUMP_NFA = 1 DUMP_DFA = 2 class State(object): """ This class is used as part of a Plex.Lexicon specification to introduce a user-defined state. Constructor: State(name, token_specifications) """ name = None tokens = None def __init__(self, name, tokens): self.name = name self.tokens = tokens class Lexicon(object): """ Lexicon(specification) builds a lexical analyser from the given |specification|. The specification consists of a list of specification items. Each specification item may be either: 1) A token definition, which is a tuple: (pattern, action) The |pattern| is a regular axpression built using the constructors defined in the Plex module. The |action| is the action to be performed when this pattern is recognised (see below). 2) A state definition: State(name, tokens) where |name| is a character string naming the state, and |tokens| is a list of token definitions as above. The meaning and usage of states is described below. Actions ------- The |action| in a token specication may be one of three things: 1) A function, which is called as follows: function(scanner, text) where |scanner| is the relevant Scanner instance, and |text| is the matched text. If the function returns anything other than None, that value is returned as the value of the token. If it returns None, scanning continues as if the IGNORE action were specified (see below). 2) One of the following special actions: IGNORE means that the recognised characters will be treated as white space and ignored. Scanning will continue until the next non-ignored token is recognised before returning. TEXT causes the scanned text itself to be returned as the value of the token. 3) Any other value, which is returned as the value of the token. States ------ At any given time, the scanner is in one of a number of states. Associated with each state is a set of possible tokens. When scanning, only tokens associated with the current state are recognised. There is a default state, whose name is the empty string. Token definitions which are not inside any State definition belong to the default state. The initial state of the scanner is the default state. The state can be changed in one of two ways: 1) Using Begin(state_name) as the action of a token. 2) Calling the begin(state_name) method of the Scanner. To change back to the default state, use '' as the state name. """ machine = None # Machine tables = None # StateTableMachine def __init__(self, specifications, debug=None, debug_flags=7, timings=None): if not isinstance(specifications, list): raise Errors.InvalidScanner("Scanner definition is not a list") if timings: from .Timing import time total_time = 0.0 time1 = time() nfa = Machines.Machine() default_initial_state = nfa.new_initial_state('') token_number = 1 for spec in specifications: if isinstance(spec, State): user_initial_state = nfa.new_initial_state(spec.name) for token in spec.tokens: self.add_token_to_machine( nfa, user_initial_state, token, token_number) token_number += 1 elif isinstance(spec, tuple): self.add_token_to_machine( nfa, default_initial_state, spec, token_number) token_number += 1 else: raise Errors.InvalidToken( token_number, "Expected a token definition (tuple) or State instance") if timings: time2 = time() total_time = total_time + (time2 - time1) time3 = time() if debug and (debug_flags & 1): debug.write("\n============= NFA ===========\n") nfa.dump(debug) dfa = DFA.nfa_to_dfa(nfa, debug=(debug_flags & 3) == 3 and debug) if timings: time4 = time() total_time = total_time + (time4 - time3) if debug and (debug_flags & 2): debug.write("\n============= DFA ===========\n") dfa.dump(debug) if timings: timings.write("Constructing NFA : %5.2f\n" % (time2 - time1)) timings.write("Converting to DFA: %5.2f\n" % (time4 - time3)) timings.write("TOTAL : %5.2f\n" % total_time) self.machine = dfa def add_token_to_machine(self, machine, initial_state, token_spec, token_number): try: (re, action_spec) = self.parse_token_definition(token_spec) # Disabled this -- matching empty strings can be useful #if re.nullable: # raise Errors.InvalidToken( # token_number, "Pattern can match 0 input symbols") if isinstance(action_spec, Actions.Action): action = action_spec else: try: action_spec.__call__ except AttributeError: action = Actions.Return(action_spec) else: action = Actions.Call(action_spec) final_state = machine.new_state() re.build_machine(machine, initial_state, final_state, match_bol=1, nocase=0) final_state.set_action(action, priority=-token_number) except Errors.PlexError as e: raise e.__class__("Token number %d: %s" % (token_number, e)) def parse_token_definition(self, token_spec): if not isinstance(token_spec, tuple): raise Errors.InvalidToken("Token definition is not a tuple") if len(token_spec) != 2: raise Errors.InvalidToken("Wrong number of items in token definition") pattern, action = token_spec if not isinstance(pattern, Regexps.RE): raise Errors.InvalidToken("Pattern is not an RE instance") return (pattern, action) def get_initial_state(self, name): return self.machine.get_initial_state(name)