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#### The Static Lexer Model

The documentation of Spirit.Lex so far mostly was about describing the features of the dynamic model, where the tables needed for lexical analysis are generated from the regular expressions at runtime. The big advantage of the dynamic model is its flexibility, and its integration with the Spirit library and the C++ host language. Its big disadvantage is the need to spend additional runtime to generate the tables, which especially might be a limitation for larger lexical analyzers. The static model strives to build upon the smooth integration with Spirit and C++, and reuses large parts of the Spirit.Lex library as described so far, while overcoming the additional runtime requirements by using pre-generated tables and tokenizer routines. To make the code generation as simple as possible, the static model reuses the token definition types developed for the dynamic model without any changes. As will be shown in this section, building a code generator based on an existing token definition type is a matter of writing 3 lines of code.

Assuming you already built a dynamic lexer for your problem, there are two more steps needed to create a static lexical analyzer using Spirit.Lex:

1. generating the C++ code for the static analyzer (including the tokenization function and corresponding tables), and
2. modifying the dynamic lexical analyzer to use the generated code.

Both steps are described in more detail in the two sections below (for the full source code used in this example see the code here: the common token definition, the code generator, the generated code, and the static lexical analyzer).

But first we provide the code snippets needed to further understand the descriptions. Both, the definition of the used token identifier and the of the token definition class in this example are put into a separate header file to make these available to the code generator and the static lexical analyzer.

    enum tokenids
    {
        IDANY = boost::spirit::lex::min_token_id + 1,
    };

The important point here is, that the token definition class is not different from a similar class to be used for a dynamic lexical analyzer. The library has been designed in a way, that all components (dynamic lexical analyzer, code generator, and static lexical analyzer) can reuse the very same token definition syntax.

    // This token definition class can be used without any change for all three
    // possible use cases: a dynamic lexical analyzer, a code generator, and a
    // static lexical analyzer.
    template <typename BaseLexer>
    struct word_count_tokens : boost::spirit::lex::lexer<BaseLexer>
    {
        word_count_tokens()
          : word_count_tokens::base_type(
              boost::spirit::lex::match_flags::match_not_dot_newline)
        {
            // define tokens and associate them with the lexer
            word = "[^ \t\n]+";
            this->self = word | '\n' | boost::spirit::lex::token_def<>(".", IDANY);
        }

        boost::spirit::lex::token_def<std::string> word;
    };

The only thing changing between the three different use cases is the template parameter used to instantiate a concrete token definition. For the dynamic model and the code generator you probably will use the `lex::lexertl::lexer<>` template, where for the static model you will use the `lex::lexertl::static_lexer<>` type as the template parameter.

This example not only shows how to build a static lexer, but it additionally demonstrates how such a lexer can be used for parsing in conjunction with a Spirit.Qi grammar. For completeness, we provide the simple grammar used in this example. As you can see, this grammar does not have any dependencies on the static lexical analyzer, and for this reason it is not different from a grammar used either without a lexer or using a dynamic lexical analyzer as described before.

    //  This is an ordinary grammar definition following the rules defined by
    //  Spirit.Qi. There is nothing specific about it, except it gets the token
    //  definition class instance passed to the constructor to allow accessing the
    //  embedded token_def<> instances.
    template <typename Iterator>
    struct word_count_grammar : qi::grammar<Iterator>
    {
        template <typename TokenDef>
        word_count_grammar(TokenDef const& tok)
          : word_count_grammar::base_type(start)
          , c(0), w(0), l(0)
        {
            using boost::phoenix::ref;
            using boost::phoenix::size;

            //  associate the defined tokens with the lexer, at the same time
            //  defining the actions to be executed
            start =  *(   tok.word          [ ++ref(w), ref(c) += size(_1) ]
                      |   lit('\n')         [ ++ref(l), ++ref(c) ]
                      |   qi::token(IDANY)  [ ++ref(c) ]
                      )
                  ;
        }

        std::size_t c, w, l;      // counter for characters, words, and lines
        qi::rule<Iterator> start;
    };

###### Generating the Static Analyzer

The first additional step to perform in order to create a static lexical analyzer is to create a small stand alone program for creating the lexer tables and the corresponding tokenization function. For this purpose the Spirit.Lex library exposes a special API - the function `generate_static_dfa()` . It implements the whole code generator, no further code is needed. All what it takes to invoke this function is to supply a token definition instance, an output stream to use to generate the code to, and an optional string to be used as a suffix for the name of the generated function. All in all just a couple lines of code.

    int main(int argc, char* argv[])
    {
        // create the lexer object instance needed to invoke the generator
        word_count_tokens<lex::lexertl::lexer<> > word_count; // the token definition

        // open the output file, where the generated tokenizer function will be
        // written to
        std::ofstream out(argc < 2 ? "word_count_static.hpp" : argv[1]);

        // invoke the generator, passing the token definition, the output stream
        // and the name suffix of the tables and functions to be generated
        //
        // The suffix "wc" used below results in a type lexertl::static_::lexer_wc
        // to be generated, which needs to be passed as a template parameter to the
        // lexertl::static_lexer template (see word_count_static.cpp).
        return lex::lexertl::generate_static_dfa(word_count, out, "wc") ? 0 : -1;
    }

The shown code generator will generate output, which should be stored in a file for later inclusion into the static lexical analyzer as shown in the next topic (the full generated code can be viewed here).

| Note
The generated code will have compiled in the version number of the current Spirit.Lex library. This version number is used at compilation time of your static lexer object to ensure this is compiled using exactly the same version of the Spirit.Lex library as the lexer tables have been generated with. If the versions do not match you will see an compilation error mentioning an `incompatible_static_lexer_version`.

###### Modifying the Dynamic Analyzer

The second required step to convert an existing dynamic lexer into a static one is to change your main program at two places. First, you need to change the type of the used lexer (that is the template parameter used while instantiating your token definition class). While in the dynamic model we have been using the `lex::lexertl::lexer<>` template, we now need to change that to the `lex::lexertl::static_lexer<>` type. The second change is tightly related to the first one and involves correcting the corresponding `#include` statement to:

    #include <boost/spirit/include/lex_static_lexertl.hpp>

Otherwise the main program is not different from an equivalent program using the dynamic model. This feature makes it easy to develop the lexer in dynamic mode and to switch to the static mode after the code has been stabilized. The simple generator application shown above enables the integration of the code generator into any existing build process. The following code snippet provides the overall main function, highlighting the code to be changed.

    int main(int argc, char* argv[])
    {
        // Define the token type to be used: 'std::string' is available as the type
        // of the token value.
        typedef lex::lexertl::token<
            char const*, boost::mpl::vector<std::string>
        > token_type;

        // Define the lexer type to be used as the base class for our token
        // definition.
        //
        // This is the only place where the code is different from an equivalent
        // dynamic lexical analyzer. We use the `lexertl::static_lexer<>` instead of
        // the `lexertl::lexer<>` as the base class for our token defintion type.
        //
        // As we specified the suffix "wc" while generating the static tables we
        // need to pass the type lexertl::static_::lexer_wc as the second template
        // parameter below (see word_count_generate.cpp).
        typedef lex::lexertl::static_lexer<
            token_type, lex::lexertl::static_::lexer_wc
        > lexer_type;

        // Define the iterator type exposed by the lexer.
        typedef word_count_tokens<lexer_type>::iterator_type iterator_type;

        // Now we use the types defined above to create the lexer and grammar
        // object instances needed to invoke the parsing process.
        word_count_tokens<lexer_type> word_count;           // Our lexer
        word_count_grammar<iterator_type> g (word_count);   // Our parser

        // Read in the file into memory.
        std::string str (read_from_file(1 == argc ? "word_count.input" : argv[1]));
        char const* first = str.c_str();
        char const* last = &first[str.size()];

        // Parsing is done based on the the token stream, not the character stream.
        bool r = lex::tokenize_and_parse(first, last, word_count, g);

        if (r) {    // success
            std::cout << "lines: " << g.l << ", words: " << g.w
                      << ", characters: " << g.c << "\n";
        }
        else {
            std::string rest(first, last);
            std::cerr << "Parsing failed\n" << "stopped at: \""
                      << rest << "\"\n";
        }
        return 0;
    }

| Important
The generated code for the static lexer contains the token ids as they have been assigned, either explicitly by the programmer or implicitly during lexer construction. It is your responsibility to make sure that all instances of a particular static lexer type use exactly the same token ids. The constructor of the lexer object has a second (default) parameter allowing it to designate a starting token id to be used while assigning the ids to the token definitions. The requirement above is fulfilled by default as long as no `first_id` is specified during construction of the static lexer instances.