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Tokn is a ruby gem that generates automatons from regular expressions to extract tokens from text files.
Written by Jeff Sember, March 2013.
Source code documentation can be found here.
For a simple example, suppose a particular text file is designed to have tokens of the following three types:
'a' followed by any number of 'a' or 'b'
'b' followed by either 'aa' or zero or more 'b'
'bbb'
We will also allow an additional token, one or more spaces, to separate them. These four token types can be written using regular expressions as:
sep: \s
tku: a(a|b)*
tkv: b(aa|b*)
tkw: bbb
We've given each token definition a name (to the left of the colon).
Now suppose your program needs to read a text file and interpret the tokens it finds there.
This can be done using the DFA (deterministic finite state automaton) found at: http://www.cs.ubc.ca/~jpsember/sample_dfa.pdf
The token extraction algorithm has these steps:
The tokn module provides a simple and efficient way to perform this tokenization process. Its major accomplishment is not just performing the above six steps, but rather that it also can construct, from a set of token definitions, the DFA to be used in these steps. Such DFAs are very useful, and can be used by non-Ruby programs as well.
There are three object classes of interest: DFA, Tokenizer, and Token. A DFA is compiled once from a script containing token definitions (e.g, "tku: b(aa|b*) ..."), and can then be stored (either in memory, or on disk as a JSON string) for later use.
When tokens need to be extracted from a source file (or simple string), a Tokenizer is constructed. It requires both the DFA and the source file as input. Once this is done, individual Token objects can be read from the Tokenizer.
Here's some example Ruby code showing how a text file "source.txt" can be split into tokens. We'll assume there's a text file "tokendefs.txt" that contains the definitions shown earlier.
require "Tokenizer"
include Tokn
dfa = DFA.from_script(readTextFile("tokendefs.txt"))
t = Tokenizer.new(dfa, readTextFile("source.txt"))
while t.hasNext
k = t.read # read token
next if t.typeOf(k) == "sep" # skip 'whitespace'
...do something with the token ...
end
If later, another file needs to be tokenized, a new Tokenizer object can be constructed and given the same dfa object as earlier.
The module has two utility scripts: tokncompile, and toknprocess. These can be found in the bin/ directory.
The tokncompile script reads a token definition script from standard input, and compiles it to a DFA. For example, if you are in the tokn/test/data directory, you can type:
tokncompile < sampletokens.txt > compileddfa.txt
It will produce the JSON encoding of the appropriate DFA. For a description of how this JSON string represents the DFA, see Dfa.rb.
The toknprocess script takes two arguments: the name of a file containing a previously compiled DFA, and the name of a source file. It extracts the sequence of tokens from the source file to the standard output:
toknprocess compileddfa.txt sampletext.txt
This will produce the following output:
WS 1 1 // Example source file that can be tokenized
WS 2 1
ID 3 1 speed
WS 3 6
ASSIGN 3 7 =
WS 3 8
INT 3 9 42
WS 3 11
WS 3 14 // speed of object
WS 4 1
ID 5 1 gravity
WS 5 8
ASSIGN 5 9 =
WS 5 10
DBL 5 11 -9.80
WS 5 16
ID 7 1 title
WS 7 6
ASSIGN 7 7 =
WS 7 8
LBL 7 9 'This is a string with \' an escaped delimiter'
WS 7 56
IF 9 1 if
WS 9 3
ID 9 4 gravity
WS 9 11
EQUIV 9 12 ==
WS 9 14
INT 9 15 12
WS 9 17
BROP 9 18 {
WS 9 19
DO 10 3 do
WS 10 5
ID 10 6 something
WS 10 15
BRCL 11 1 }
WS 11 2
The extra linefeeds are the result of a token containing a linefeed.
You could construct a regular expression describing each possible token, and use that to extract a token from the start of a string; you could then remove that token from the string, and repeat. The trouble is that the regular expression has no easy way to indicate which individual token's expression was matched. You would then (presumably) have to match the returned token with each individual regular expression to identify the token type.
Another reason why standard regular expressions can be troublesome is that their implementations actually 'recognize' a richer class of tokens than the ones described here. This extra power can come at a cost; in some pathological cases, the running time can become exponential.
The tokn tool is capable of extracting tokens made up of characters that have codes in the entire Unicode range: 0 through 0x10ffff (hex). In fact, the labels on the DFA edges can be viewed as sets of any nonnegative integers (negative values are reserved for the token identifiers). Note however that the current implementation only reads Ruby characters from the input, which I believe are only 8 bits wide.
FAQs
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We found that tokn demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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