[483] | 1 | dojo.provide("dojox.lang.functional.util"); |
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| 2 | |
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| 3 | dojo.require("dojox.lang.functional.lambda"); |
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| 4 | |
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| 5 | // This module provides helpers: |
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| 6 | // - inlining string lambda functions. |
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| 7 | |
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| 8 | (function(){ |
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| 9 | var df = dojox.lang.functional; |
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| 10 | |
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| 11 | dojo.mixin(df, { |
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| 12 | inlineLambda: function(/*String*/ lambda, /*String|Array*/ init, /*Function?*/ add2dict){ |
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| 13 | // summary: |
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| 14 | // Creates the inlined version of a string lambda. |
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| 15 | // lambda: |
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| 16 | // The String variable representing the lambda function. |
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| 17 | // init: |
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| 18 | // Conveys how to initialize parameters. If it is a String, then the apply() method |
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| 19 | // would be emulated treating "init" as a list of input parameters. |
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| 20 | // It it is an Array, then the call() method is emulated treating array members |
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| 21 | // as input parameters. |
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| 22 | // add2dict: |
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| 23 | // The optional function, which is used to record names of lambda parameters. |
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| 24 | // If supplied, this function is called with a name of every parameter. |
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| 25 | |
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| 26 | var s = df.rawLambda(lambda); |
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| 27 | if(add2dict){ |
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| 28 | df.forEach(s.args, add2dict); |
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| 29 | } |
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| 30 | var ap = typeof init == "string", // apply or call? |
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| 31 | n = ap ? s.args.length : Math.min(s.args.length, init.length), |
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| 32 | a = new Array(4 * n + 4), i, j = 1; |
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| 33 | for(i = 0; i < n; ++i){ |
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| 34 | a[j++] = s.args[i]; |
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| 35 | a[j++] = "="; |
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| 36 | a[j++] = ap ? init + "[" + i + "]": init[i]; |
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| 37 | a[j++] = ","; |
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| 38 | } |
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| 39 | a[0] = "("; |
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| 40 | a[j++] = "("; |
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| 41 | a[j++] = s.body; |
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| 42 | a[j] = "))"; |
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| 43 | return a.join(""); // String |
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| 44 | } |
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| 45 | }); |
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| 46 | })(); |
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