Tokenization for Julia source code



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Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens.

The goals of this package is to be

  • Fast, it currently lexes all of Julia source files in ~0.7 seconds (523 files, 1.8 million Tokens)
  • Round trippable, that is, from a stream of tokens the original string should be recoverable exactly.
  • Non error throwing. Instead of throwing errors a certain error token is returned.



The function tokenize is the main entrypoint for generating Tokens. It takes a string or a buffer and creates an iterator that will sequentially return the next Token until the end of string or buffer. The argument to tokenize can either be a String, IOBuffer or an IOStream.

julia> collect(tokenize("function f(x) end"))
 1,1-1,8          KEYWORD        "function"
 1,9-1,9          WHITESPACE     " "
 1,10-1,10        IDENTIFIER     "f"
 1,11-1,11        LPAREN         "("
 1,12-1,12        IDENTIFIER     "x"
 1,13-1,13        RPAREN         ")"
 1,14-1,14        WHITESPACE     " "
 1,15-1,17        KEYWORD        "end"
 1,18-1,17        ENDMARKER      ""


Each Token is represented by where it starts and ends, what string it contains and what type it is.

The API for a Token (non exported from the Tokenize.Tokens module) is.

startpos(t)::Tuple{Int, Int} # row and column where the token start
endpos(t)::Tuple{Int, Int}   # row and column where the token ends
startbyte(T)::Int            # byte offset where the token start
endbyte(t)::Int              # byte offset where the token ends
untokenize(t)::String        # string representation of the token
kind(t)::Token.Kind          # kind of the token
exactkind(t)::Token.Kind     # exact kind of the token

The difference between kind and exactkind is that kind returns OP for all operators and KEYWORD for all keywords while exactkind returns a unique kind for all different operators and keywords, ex;

julia> tok = collect(tokenize("⇒"))[1];

julia> Tokens.kind(tok)
OP::Tokenize.Tokens.Kind = 90

julia> Tokens.exactkind(tok)
RIGHTWARDS_DOUBLE_ARROW::Tokenize.Tokens.Kind = 128

All the different Token.Kind can be seen in the token_kinds.jl file

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