ProgTutorial/Recipes/Antiquotes.thy
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theory Antiquotes
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imports "../Appendix"
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begin
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section \<open>Useful Document Antiquotations\label{rec:docantiquotations}\<close>
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text \<open>
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  {\bf Problem:} 
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  How to keep your ML-code inside a document synchronised with the actual code?\smallskip
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  {\bf Solution:} This can be achieved with document antiquotations.\smallskip
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  Document antiquotations can be used for ensuring consistent type-setting of
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  various entities in a document. They can also be used for sophisticated
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  \LaTeX-hacking. If you type on the Isabelle level
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\<close>
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print_antiquotations
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text \<open>
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  you obtain a list of all currently available document antiquotations and
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  their options.  
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  Below we will give the code for two additional document
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  antiquotations both of which are intended to typeset ML-code. The crucial point
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  of these document antiquotations is that they not just print the ML-code, but also 
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  check whether it compiles. This will provide a sanity check for the code
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  and also allows you to keep documents in sync with other code, for example
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  Isabelle.
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  We first describe the antiquotation \<open>ML_checked\<close> with the syntax:
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  @{text [display] \<open>@{ML_checked "a_piece_of_code"}\<close>}
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  The code is checked by sending the ML-expression @{text [quotes] "val _ =
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  a_piece_of_code"} to the ML-compiler (i.e.~the function @{ML \<open>ML_Context.eval_source_in\<close>} in Line 7 below). The complete code of the
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  document antiquotation is as follows:
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\<close>
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ML \<open>Input.pos_of\<close>
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ML%linenosgray\<open>fun ml_enclose bg en source =
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  ML_Lex.read bg @ ML_Lex.read_source source @ ML_Lex.read en;\<close>
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ML%linenosgray\<open>fun ml_val code_txt = (ml_enclose "val _ = " "" code_txt)
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fun output_ml ctxt code_txt =
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let
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  val _ = ML_Context.eval_in (SOME ctxt) ML_Compiler.flags 
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    (Input.pos_of code_txt) (ml_val code_txt)
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in 
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   Pretty.str (fst (Input.source_content code_txt))
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end
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val ml_checked_setup = Thy_Output.antiquotation_pretty_source 
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  @{binding "ML_checked"} (Scan.lift Args.text_input) output_ml\<close>
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setup \<open>ml_checked_setup\<close>
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text \<open>
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  The parser @{ML \<open>(Scan.lift Args.name)\<close>} in Line 7 parses a string, in this
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  case the code, and then calls the function @{ML output_ml}. As mentioned
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  before, the parsed code is sent to the ML-compiler in Line 4 using the
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  function @{ML ml_val}, which constructs the appropriate ML-expression, and
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  using @{ML \<open>eval_in\<close> in ML_Context}, which calls the compiler.  If the code is
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  ``approved'' by the compiler, then the output function @{ML \<open>output\<close> in
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  Document_Antiquotation} in the next line pretty prints the code. This function expects
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  that the code is a list of (pretty)strings where each string correspond to a
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  line in the output. Therefore the use of @{ML \<open>(space_explode "\\n" txt)\<close>
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  for txt} which produces such a list according to linebreaks.  There are a
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  number of options for antiquotations that are observed by the function 
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  @{ML \<open>output\<close> in Document_Antiquotation} when printing the code (including \<open>[display]\<close> 
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  and \<open>[quotes]\<close>). The function @{ML \<open>antiquotation_raw\<close> in Thy_Output} in 
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  Line 7 sets up the new document antiquotation.
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  \begin{readmore}
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  For more information about options of document antiquotations see \rsccite{sec:antiq}).
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  \end{readmore}
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  Since we used the argument @{ML \<open>Position.none\<close>}, the compiler cannot give specific 
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  information about the line number, in case an error is detected. We 
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  can improve the code above slightly by writing 
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\<close>
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text \<open>
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  where in Lines 1 and 2 the positional information is properly treated. The
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  parser @{ML Parse.position} encodes the positional information in the 
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  result.
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  We can now write \<open>@{ML_checked2 "2 + 3"}\<close> in a document in order to
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  obtain @{ML_checked "2 + 3"} and be sure that this code compiles until
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  somebody changes the definition of addition.
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  The second document antiquotation we describe extends the first by a pattern
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  that specifies what the result of the ML-code should be and checks the
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  consistency of the actual result with the given pattern. For this we are
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  going to implement the document antiquotation:
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  @{text [display] \<open>@{ML_resp "a_piece_of_code" "a_pattern"}\<close>}
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  To add some convenience and also to deal with large outputs, the user can
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  give a partial specification by using ellipses. For example \<open>(\<dots>, \<dots>)\<close>
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  for specifying a pair.  In order to check consistency between the pattern
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  and the output of the code, we have to change the ML-expression that is sent 
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  to the compiler: in \<open>ML_checked2\<close> we sent the expression @{text [quotes]
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  "val _ = a_piece_of_code"} to the compiler; now the wildcard \<open>_\<close>
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  must be be replaced by the given pattern. However, we have to remove all
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  ellipses from it and replace them by @{text [quotes] "_"}. The following 
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  function will do this:
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\<close>
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ML%linenosgray\<open>fun ml_pat pat code =
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  ML_Lex.read "val" @ 
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  ML_Lex.read_source pat @ 
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  ML_Lex.read " = " @ 
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  ML_Lex.read_source code\<close>
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text \<open>
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  Next we add a response indicator to the result using:
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\<close>
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ML %grayML\<open>fun add_resp pat = map (fn s => "> " ^ s) pat\<close>
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text \<open>
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  The rest of the code of \<open>ML_resp\<close> is: 
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\<close>
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ML %linenosgray\<open>
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fun output_ml_resp ctxt (code_txt, pat) =
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let
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  val _ = ML_Context.eval_in (SOME ctxt) ML_Compiler.flags 
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    (Input.pos_of code_txt) (ml_pat pat code_txt)
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  val code = space_explode "\n" (fst (Input.source_content code_txt))
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  val resp = add_resp (space_explode "\n" (fst (Input.source_content pat)))
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in 
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   Pretty.str (cat_lines (code @ resp))
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end
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val ml_response_setup = Thy_Output.antiquotation_pretty_source 
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  @{binding "ML_resp"} 
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  (Scan.lift (Args.text_input -- Args.text_input)) 
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  output_ml_resp
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\<close>
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setup \<open>ml_response_setup\<close>
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(* FIXME *)
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text \<open>
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  In comparison with \<open>ML_checked\<close>, we only changed the line about 
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  the compiler (Line~2), the lines about
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  the output (Lines 4 to 7) and the parser in the setup (Line 11). Now 
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  you can write
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  @{text [display] \<open>@{ML_resp [display] "true andalso false" "false"}\<close>}
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  to obtain
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  @{ML_resp [display] "true andalso false" "false"} 
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  or 
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  @{text [display] \<open>@{ML_resp [display] "let val i = 3 in (i * i, "foo") end" "(9, \<dots>)"}\<close>}
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  to obtain
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  @{ML_resp [display] "let val i = 3 in (i * i, \"foo\") end" "(9, _)"} 
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  In both cases, the check by the compiler ensures that code and result
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  match. A limitation of this document antiquotation, however, is that the
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  pattern can only be given for values that can be constructed. This excludes
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  values that are abstract datatypes, like @{ML_type thm}s and @{ML_type cterm}s.
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\<close>
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end