theory Antiquotes
imports "../Appendix"
begin

section \<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_antiquotations

text \<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))
end

val 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))
end

val 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