PPI::Tokenizer(3) User Contributed Perl Documentation PPI::Tokenizer(3)NAME
PPI::Tokenizer - The Perl Document Tokenizer
SYNOPSIS
# Create a tokenizer for a file, array or string
$Tokenizer = PPI::Tokenizer->new( 'filename.pl' );
$Tokenizer = PPI::Tokenizer->new( \@lines );
$Tokenizer = PPI::Tokenizer->new( \$source );
# Return all the tokens for the document
my $tokens = $Tokenizer->all_tokens;
# Or we can use it as an iterator
while ( my $Token = $Tokenizer->get_token ) {
print "Found token '$Token'\n";
}
# If we REALLY need to manually nudge the cursor, you
# can do that to (The lexer needs this ability to do rollbacks)
$is_incremented = $Tokenizer->increment_cursor;
$is_decremented = $Tokenizer->decrement_cursor;
DESCRIPTION
PPI::Tokenizer is the class that provides Tokenizer objects for use in
breaking strings of Perl source code into Tokens.
By the time you are reading this, you probably need to know a little
about the difference between how perl parses Perl "code" and how PPI
parsers Perl "documents".
"perl" itself (the interpreter) uses a heavily modified lex
specification to specify its parsing logic, maintains several types of
state as it goes, and incrementally tokenizes, lexes AND EXECUTES at
the same time.
In fact, it is provably impossible to use perl's parsing method without
simultaneously executing code. A formal mathematical proof has been
published demonstrating the method.
This is where the truism "Only perl can parse Perl" comes from.
PPI uses a completely different approach by abandoning the (impossible)
ability to parse Perl the same way that the interpreter does, and
instead parsing the source as a document, using a document structure
independantly derived from the Perl documentation and approximating the
perl interpreter interpretation as closely as possible.
It was touch and go for a long time whether we could get it close
enough, but in the end it turned out that it could be done.
In this approach, the tokenizer "PPI::Tokenizer" is implemented
separately from the lexer PPI::Lexer.
The job of "PPI::Tokenizer" is to take pure source as a string and
break it up into a stream/set of tokens, and contains most of the
"black magic" used in PPI. By comparison, the lexer implements a
relatively straight forward tree structure, and has an implementation
that is uncomplicated (compared to the insanity in the tokenizer at
least).
The Tokenizer uses an immense amount of heuristics, guessing and cruft,
supported by a very VERY flexible internal API, but fortunately it was
possible to largely encapsulate the black magic, so there is not a lot
that gets exposed to people using the "PPI::Tokenizer" itself.
METHODS
Despite the incredible complexity, the Tokenizer itself only exposes a
relatively small number of methods, with most of the complexity
implemented in private methods.
new $file | \@lines | \$source
The main "new" constructor creates a new Tokenizer object. These
objects have no configuration parameters, and can only be used once, to
tokenize a single perl source file.
It takes as argument either a normal scalar containing source code, a
reference to a scalar containing source code, or a reference to an
ARRAY containing newline-terminated lines of source code.
Returns a new "PPI::Tokenizer" object on success, or throws a
PPI::Exception exception on error.
get_token
When using the PPI::Tokenizer object as an iterator, the "get_token"
method is the primary method that is used. It increments the cursor and
returns the next Token in the output array.
The actual parsing of the file is done only as-needed, and a line at a
time. When "get_token" hits the end of the token array, it will cause
the parser to pull in the next line and parse it, continuing as needed
until there are more tokens on the output array that get_token can then
return.
This means that a number of Tokenizer objects can be created, and won't
consume significant CPU until you actually begin to pull tokens from
it.
Return a PPI::Token object on success, 0 if the Tokenizer had reached
the end of the file, or "undef" on error.
all_tokens
When not being used as an iterator, the "all_tokens" method tells the
Tokenizer to parse the entire file and return all of the tokens in a
single ARRAY reference.
It should be noted that "all_tokens" does NOT interfere with the use of
the Tokenizer object as an iterator (does not modify the token cursor)
and use of the two different mechanisms can be mixed safely.
Returns a reference to an ARRAY of PPI::Token objects on success or
throws an exception on error.
increment_cursor
Although exposed as a public method, "increment_method" is implemented
for expert use only, when writing lexers or other components that work
directly on token streams.
It manually increments the token cursor forward through the file, in
effect "skipping" the next token.
Return true if the cursor is incremented, 0 if already at the end of
the file, or "undef" on error.
decrement_cursor
Although exposed as a public method, "decrement_method" is implemented
for expert use only, when writing lexers or other components that work
directly on token streams.
It manually decrements the token cursor backwards through the file, in
effect "rolling back" the token stream. And indeed that is what it is
primarily intended for, when the component that is consuming the token
stream needs to implement some sort of "roll back" feature in its use
of the token stream.
Return true if the cursor is decremented, 0 if already at the beginning
of the file, or "undef" on error.
NOTES
How the Tokenizer Works
Understanding the Tokenizer is not for the feint-hearted. It is by far
the most complex and twisty piece of perl I've ever written that is
actually still built properly and isn't a terrible spaghetti-like mess.
In fact, you probably want to skip this section.
But if you really want to understand, well then here goes.
Source Input and Clean Up
The Tokenizer starts by taking source in a variety of forms, sucking it
all in and merging into one big string, and doing our own internal line
split, using a "universal line separator" which allows the Tokenizer to
take source for any platform (and even supports a few known types of
broken newlines caused by mixed mac/pc/*nix editor screw ups).
The resulting array of lines is used to feed the tokenizer, and is also
accessed directly by the heredoc-logic to do the line-oriented part of
here-doc support.
Doing Things the Old Fashioned Way
Due to the complexity of perl, and after 2 previously aborted parser
attempts, in the end the tokenizer was fashioned around a line-buffered
character-by-character method.
That is, the Tokenizer pulls and holds a line at a time into a line
buffer, and then iterates a cursor along it. At each cursor position, a
method is called in whatever token class we are currently in, which
will examine the character at the current position, and handle it.
As the handler methods in the various token classes are called, they
build up a output token array for the source code.
Various parts of the Tokenizer use look-ahead, arbitrary-distance look-
behind (although currently the maximum is three significant tokens), or
both, and various other heuristic guesses.
I've been told it is officially termed a "backtracking parser with
infinite lookaheads".
State Variables
Aside from the current line and the character cursor, the Tokenizer
maintains a number of different state variables.
Current Class
The Tokenizer maintains the current token class at all times. Much
of the time is just going to be the "Whitespace" class, which is
what the base of a document is. As the tokenizer executes the
various character handlers, the class changes a lot as it moves a
long. In fact, in some instances, the character handler may not
handle the character directly itself, but rather change the
"current class" and then hand off to the character handler for the
new class.
Because of this, and some other things I'll deal with later, the
number of times the character handlers are called does not in fact
have a direct relationship to the number of actual characters in
the document.
Current Zone
Rather than create a class stack to allow for infinitely nested
layers of classes, the Tokenizer recognises just a single layer.
To put it a different way, in various parts of the file, the
Tokenizer will recognise different "base" or "substrate" classes.
When a Token such as a comment or a number is finalised by the
tokenizer, it "falls back" to the base state.
This allows proper tokenization of special areas such as __DATA__
and __END__ blocks, which also contain things like comments and
POD, without allowing the creation of any significant Tokens inside
these areas.
For the main part of a document we use PPI::Token::Whitespace for
this, with the idea being that code is "floating in a sea of
whitespace".
Current Token
The final main state variable is the "current token". This is the
Token that is currently being built by the Tokenizer. For certain
types, it can be manipulated and morphed and change class quite a
bit while being assembled, as the Tokenizer's understanding of the
token content changes.
When the Tokenizer is confident that it has seen the end of the
Token, it will be "finalized", which adds it to the output token
array and resets the current class to that of the zone that we are
currently in.
I should also note at this point that the "current token" variable
is optional. The Tokenizer is capable of knowing what class it is
currently set to, without actually having accumulated any
characters in the Token.
Making It Faster
As I'm sure you can imagine, calling several different methods for each
character and running regexes and other complex heuristics made the
first fully working version of the tokenizer extremely slow.
During testing, I created a metric to measure parsing speed called
LPGC, or "lines per gigacycle" . A gigacycle is simple a billion CPU
cycles on a typical single-core CPU, and so a Tokenizer running at
"1000 lines per gigacycle" should generate around 1200 lines of
tokenized code when running on a 1200 MHz processor.
The first working version of the tokenizer ran at only 350 LPGC, so to
tokenize a typical large module such as ExtUtils::MakeMaker took 10-15
seconds. This sluggishness made it unpractical for many uses.
So in the current parser, there are multiple layers of optimisation
very carefully built in to the basic. This has brought the tokenizer up
to a more reasonable 1000 LPGC, at the expense of making the code quite
a bit twistier.
Making It Faster - Whole Line Classification
The first step in the optimisation process was to add a hew handler to
enable several of the more basic classes (whitespace, comments) to be
able to be parsed a line at a time. At the start of each line, a
special optional handler (only supported by a few classes) is called to
check and see if the entire line can be parsed in one go.
This is used mainly to handle things like POD, comments, empty lines,
and a few other minor special cases.
Making It Faster - Inlining
The second stage of the optimisation involved inlining a small number
of critical methods that were repeated an extremely high number of
times. Profiling suggested that there were about 1,000,000 individual
method calls per gigacycle, and by cutting these by two thirds a
significant speed improvement was gained, in the order of about 50%.
You may notice that many methods in the "PPI::Tokenizer" code look very
nested and long hand. This is primarily due to this inlining.
At around this time, some statistics code that existed in the early
versions of the parser was also removed, as it was determined that it
was consuming around 15% of the CPU for the entire parser, while making
the core more complicated.
A judgment call was made that with the difficulties likely to be
encountered with future planned enhancements, and given the relatively
high cost involved, the statistics features would be removed from the
Tokenizer.
Making It Faster - Quote Engine
Once inlining had reached diminishing returns, it became obvious from
the profiling results that a huge amount of time was being spent
stepping a char at a time though long, simple and "syntactically
boring" code such as comments and strings.
The existing regex engine was expanded to also encompass quotes and
other quote-like things, and a special abstract base class was added
that provided a number of specialised parsing methods that would "scan
ahead", looking out ahead to find the end of a string, and updating the
cursor to leave it in a valid position for the next call.
This is also the point at which the number of character handler calls
began to greatly differ from the number of characters. But it has been
done in a way that allows the parser to retain the power of the
original version at the critical points, while skipping through the
"boring bits" as needed for additional speed.
The addition of this feature allowed the tokenizer to exceed 1000 LPGC
for the first time.
Making It Faster - The "Complete" Mechanism
As it became evident that great speed increases were available by using
this "skipping ahead" mechanism, a new handler method was added that
explicitly handles the parsing of an entire token, where the structure
of the token is relatively simple. Tokens such as symbols fit this
case, as once we are passed the initial sigil and word char, we know
that we can skip ahead and "complete" the rest of the token much more
easily.
A number of these have been added for most or possibly all of the
common cases, with most of these "complete" handlers implemented using
regular expressions.
In fact, so many have been added that at this point, you could arguably
reclassify the tokenizer as a "hybrid regex, char-by=char heuristic
tokenizer". More tokens are now consumed in "complete" methods in a
typical program than are handled by the normal char-by-char methods.
Many of the these complete-handlers were implemented during the writing
of the Lexer, and this has allowed the full parser to maintain around
1000 LPGC despite the increasing weight of the Lexer.
Making It Faster - Porting To C (In Progress)
While it would be extraordinarily difficult to port all of the
Tokenizer to C, work has started on a PPI::XS "accelerator" package
which acts as a separate and automatically-detected add-on to the main
PPI package.
PPI::XS implements faster versions of a variety of functions scattered
over the entire PPI codebase, from the Tokenizer Core, Quote Engine,
and various other places, and implements them identically in XS/C.
In particular, the skip-ahead methods from the Quote Engine would
appear to be extremely amenable to being done in C, and a number of
other functions could be cherry-picked one at a time and implemented in
C.
Each method is heavily tested to ensure that the functionality is
identical, and a versioning mechanism is included to ensure that if a
function gets out of sync, PPI::XS will degrade gracefully and just not
replace that single method.
TO DO
- Add an option to reset or seek the token stream...
- Implement more Tokenizer functions in PPI::XS
SUPPORT
See the support section in the main module.
AUTHOR
Adam Kennedy <adamk@cpan.org>
COPYRIGHT
Copyright 2001 - 2011 Adam Kennedy.
This program is free software; you can redistribute it and/or modify it
under the same terms as Perl itself.
The full text of the license can be found in the LICENSE file included
with this module.
perl v5.12.5 2011-02-25 PPI::Tokenizer(3)
