| #======================================================================= |
| # |
| # Python Lexical Analyser |
| # |
| # Lexical Analyser Specification |
| # |
| #======================================================================= |
| |
| import types |
| |
| import Actions |
| import DFA |
| import Errors |
| import Machines |
| 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 type(specifications) != types.ListType: |
| 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 = token_number + 1 |
| elif type(spec) == types.TupleType: |
| self.add_token_to_machine( |
| nfa, default_initial_state, spec, token_number) |
| 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, e: |
| raise e.__class__("Token number %d: %s" % (token_number, e)) |
| |
| def parse_token_definition(self, token_spec): |
| if type(token_spec) != types.TupleType: |
| 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) |
| |
| |
| |