theory Antiquotesimports "../Appendix"beginsection \<open>Useful Document Antiquotations\label{rec:docantiquotations}\<close>text \<open> {\bf Problem:} How to keep your ML-code inside a document synchronised with the actual code?\smallskip {\bf Solution:} This can be achieved with document antiquotations.\smallskip Document antiquotations can be used for ensuring consistent type-setting of various entities in a document. They can also be used for sophisticated \LaTeX-hacking. If you type on the Isabelle level\<close>print_antiquotationstext \<open> you obtain a list of all currently available document antiquotations and their options. Below we will give the code for two additional document antiquotations both of which are intended to typeset ML-code. The crucial point of these document antiquotations is that they not just print the ML-code, but also check whether it compiles. This will provide a sanity check for the code and also allows you to keep documents in sync with other code, for example Isabelle. We first describe the antiquotation \<open>ML_checked\<close> with the syntax: @{text [display] \<open>@{ML_checked "a_piece_of_code"}\<close>} The code is checked by sending the ML-expression @{text [quotes] "val _ = a_piece_of_code"} to the ML-compiler (i.e.~the function @{ML \<open>ML_Context.eval_in\<close>} in Line 8 below). The complete code of the document antiquotation is as follows:\<close>ML \<open>Input.pos_of\<close>ML%linenosgray\<open>fun ml_enclose bg en source = ML_Lex.read bg @ ML_Lex.read_source source @ ML_Lex.read en;\<close>ML%linenosgray\<open>fun ml_val code_txt = (ml_enclose "val _ = " "" code_txt)fun output_ml ctxt code_txt =let val _ = ML_Context.eval_in (SOME ctxt) ML_Compiler.flags (Input.pos_of code_txt) (ml_val code_txt)in Pretty.str (fst (Input.source_content code_txt))endval ml_checked_setup = Thy_Output.antiquotation_pretty_source @{binding "ML_checked"} (Scan.lift Args.text_input) output_ml\<close>setup \<open>ml_checked_setup\<close>text \<open> The parser @{ML \<open>(Scan.lift Args.text_input)\<close>} in Line 15 parses a string, in this case the code, and then we call the function @{ML output_ml}. As mentioned before, the parsed code is sent to the ML-compiler in Line 8 using the function @{ML ml_val}, which constructs the appropriate ML-expression, and using @{ML \<open>eval_in\<close> in ML_Context}, which calls the compiler. If the code is ``approved'' by the compiler, then the output given to @{ML \<open>antiquotation_pretty_source\<close> in Thy_Output} in the Line 15 pretty prints the code. This function expects that the code is (pretty) string. There are a number of options for antiquotations that are observed by the function @{ML \<open>output\<close> in Document_Antiquotation} when printing the code (including \<open>[display]\<close> and \<open>[quotes]\<close>). \begin{readmore} For more information about options of document antiquotations see \rsccite{sec:antiq}). \end{readmore}\<close>text \<open> The second document antiquotation we describe extends the first by a pattern that specifies what the result of the ML-code should be and checks the consistency of the actual result with the given pattern. For this we are going to implement the document antiquotation: @{text [display] \<open>@{ML_resp "a_piece_of_code" "a_pattern"}\<close>} To add some convenience and also to deal with large outputs, the user can give a partial specification by using ellipses. For example \<open>(\<dots>, \<dots>)\<close> for specifying a pair. In order to check consistency between the pattern and the output of the code, we have to change the ML-expression that is sent to the compiler: \<close>ML%linenosgray\<open>fun ml_pat pat code = ML_Lex.read "val" @ ML_Lex.read_source pat @ ML_Lex.read " = " @ ML_Lex.read_source code\<close>text \<open> Next we add a response indicator to the result using:\<close>ML %grayML\<open>fun add_resp pat = map (fn s => "> " ^ s) pat\<close>text \<open> The rest of the code of \<open>ML_resp\<close> is: \<close>ML %linenosgray\<open>fun output_ml_resp ctxt (code_txt, pat) =let val _ = ML_Context.eval_in (SOME ctxt) ML_Compiler.flags (Input.pos_of code_txt) (ml_pat pat code_txt) val code = space_explode "\n" (fst (Input.source_content code_txt)) val resp = add_resp (space_explode "\n" (fst (Input.source_content pat)))in Pretty.str (cat_lines (code @ resp))endval ml_response_setup = Thy_Output.antiquotation_pretty_source @{binding "ML_resp"} (Scan.lift (Args.text_input -- Args.text_input)) output_ml_resp\<close>setup \<open>ml_response_setup\<close>(* FIXME *)text \<open> In comparison with \<open>ML_checked\<close>, we changed the line about the compiler (Lines 4 to 5), the lines about the output (Lines 6 to 7 and 9) and the parser setup (Line 14). Now you can write @{text [display] \<open>@{ML_resp [display] "true andalso false" "false"}\<close>} to obtain @{ML_resp [display] "true andalso false" "false"} or @{text [display] \<open>@{ML_resp [display] "let val i = 3 in (i * i, "foo") end" "(9, \<dots>)"}\<close>} to obtain @{ML_resp [display] "let val i = 3 in (i * i, \"foo\") end" "(9, _)"} In both cases, the check by the compiler ensures that code and result match. A limitation of this document antiquotation, however, is that the pattern can only be given for values that can be constructed. This excludes values that are abstract datatypes, like @{ML_type thm}s and @{ML_type cterm}s.\<close>end