A few days ago I watched a very interesting talk by Rob Pike about writing a non-trivial lexer in Go. Rob discussed how the traditional switch-based state machine approach is cumbersome to write, because it’s not really compatible with the algorithm we want to express. The main problem is that when we return a new token, a traditional state-machine structure forces us to explicitly pack up the state of where we are and return to the caller. Especially in cases where we just want to stay in the same state, this makes code unnecessarily convoluted.
This struck a chord with me, because I’ve already written about simplifying state machine code in Python with coroutines. I couldn’t help but wonder what would be an elegant Pythonic way to implement Rob’s template lexer (watch the talk or take a look at his slides for the syntax).
What follows is my attempt, which uses the new yield from syntax from PEP 380, and hence requires Python 3.3 (which is currently in beta, but should be released soon). I’ll present the code in small chunks with explanations; the full source is available for download here. It’s heavily commented, so should be easy to grok.
First, some helper types and constants:
TOK_TEXT = 'TOK_TEXT' TOK_LEFT_META = 'TOK_LEFT_META' TOK_RIGHT_META = 'TOK_RIGHT_META' TOK_PIPE = 'TOK_PIPE' TOK_NUMBER = 'TOK_NUMBER' TOK_ID = 'TOK_ID' # A token has # type: one of the TOK_* constants # value: string value, as taken from input # Token = namedtuple('Token', 'type value')
It’s a shame Python still doesn’t have a functional enum type, isn’t it? Anyway, on to the lexer class. Here’s the complete public interface:
class TemplateLexer(object): """ A lexer for the template language. Initialize with the input string, and then call lex() which generates tokens. None is generated at EOF (and the generator expires). """ def __init__(self, input): self.input = input # self.pos points at the current character in the input string self.pos = 0 # self.tokstart points at the start of the currently processed # token self.tokstart = 0 self.state = self._lex_text def lex(self): # self.state is one of the _lex_* state functions. Each such # function yields the tokens it finds and then returns the next # state function. When EOF is encountered, None is returned as # the new state. while self.state: self.state = yield from self.state()
The lex method is a generator. It yields the lexed tokens one after the other, and it uses an interesting technique to do that. A technique you won’t find in pre-3.3 Python, because of the lack of the yield from construct. This new statement means: the following expression evaluates to a generator. Run that generator and yield the values it provides back to my caller. When the generator function returns, its return value is returned from yield from.
So what happens is this: self.state is always a function. Each such function represents a state in the lexing process. It can yield one or more tokens and eventually when some input means the state should change, it returns the new state function. Let’s take a look at a couple of such state functions before I go on with the explanation:
def _lex_text(self): # Look for the beginning of LEFT_META meta_start = self.input.find(self._LEFT_META, self.pos) if meta_start > 0: # Found. Emit all text until then (if any) and move to the # lex_left_meta state. self.pos = meta_start if self.pos > self.tokstart: yield self._emit(TOK_TEXT) return self._lex_left_meta else: # Not found. This means we're done. There may be some text # left until EOF, so emit it if there is. self.pos = len(self.input) if self.pos > self.tokstart: yield self._emit(TOK_TEXT) # Yield None to mark "no more tokens --> EOF" # Return None to stop the main lexing loop since there is no # next state. yield None return None def _lex_left_meta(self): self.pos += len(self._LEFT_META) yield self._emit(TOK_LEFT_META) return self._lex_inside_action
For completeness, here’s the _emit helper method:
def _emit(self, toktype): """ Emit the current token """ tok = Token(toktype, self.input[self.tokstart:self.pos]) self.tokstart = self.pos return tok
Note how there are two "outlets" out of each state function. One is by yield – execution is suspended while the new token is given back to the caller. Once it’s consumed, execution proceeds right after the yield. The other is a return which signals that the current state has ended, and provides the next state function to the main lexing loop. The else branch in _lex_text shows how two tokens can be yielded one after the other, before returning. There are more examples for this in the full source code.
There are two big ideas I picked up from Rob’s talk:
- When some state is finished, we know the next state, so dispatching again with a switch doesn’t feel right. Why not just directly say where we want to go next?
- When we emit a new token, do don’t want to be forced to explicitly save the state, return to the caller, and then resume from a dispatcher switch. We just want to say "suspend here, emit this token, and then continue right after". This would not be possible in a language that does not support generators or coroutines of some kind.
I believe the approach shown in my code addresses both ideas. Without the yield from construct it would be much harder to code. yield from not only allows us to call a function that acts as a sub-generator. More importantly, it allows us to both yield and return a value from the same function, with correct semantics (prior to Python 3.3, it’s impossible to do that).
It’s not perfect, however. One thing I lament is that we still have a loop in lex. It’s much more elegant than a switch dispatcher, but is it really needed? Why, instead of returning the next state function, we can’t just call it directly from the current state? The way it is currently in my code, this would eventually blow the stack up, because none of the state functions would return from these calls before EOF is reached. Therefore, I don’t think functions are the right vehicle for such a mechanism – perhaps continuations are needed here.
Also, it’s not coded as a real coroutine, although that would be possible to achieve. However, it would also impose a certain programming style on the rest of the program, which isn’t always desirable. As it stands now, this lexer is nicely self-contained. The lex method presents a simple, Pythonic generator interface that programmers are used to.
Finally, I didn’t bother researching the efficiency (speed-wise) of this approach against a classical state machine loop. Note that the code isn’t terribly speed-conscious, e.g. it copies parts of the string to tokens, which is wasteful. It’s definitely much more pleasant to write (and easier to modify) than a classical state machine, and this is very important.
P.S. I did not attempt this code to be parallel to Rob Pike’s Go code. Instead, I sought a Pythonic solution. For a more direct attempt to adapt it to Rob’s Go snippets, check out this set of gists by Piet Delport.