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POJulia, speeding up eval
 

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    <p>Julia has the very nice feature of having access to its own syntactic tree, which makes it easy to generate new functions programatically, but it's much slower than the normal Julia code.</p> <p>For example:</p> <pre><code>julia&gt; timing = @time for i in [1:100] tan(pi/2*rand()); end elapsed time: 1.513e-5 seconds (896 bytes allocated) julia&gt; timing = @time for i in [1:100] x = pi/2*rand(); eval(:(tan(x))); end elapsed time: 0.0080231 seconds (23296 bytes allocated) julia&gt; timing = @time for i in [1:100] eval(:(tan(pi/2*rand()))); end elapsed time: 0.017245327 seconds (90496 bytes allocated) </code></pre> <p>Is there a way to give to <code>eval</code> the same speed as the normal Julia code?</p> <p>EDIT: I was able to slightly speed up eval using the <code>precompile</code> function, but that still not enough:</p> <pre><code>julia&gt; tmp3 = :(sin(x)) :(sin(x)) julia&gt; timing = @time for i in [1:100000] x = pi/2*rand(); eval(tmp3); end elapsed time: 8.651145772 seconds (13602336 bytes allocated) julia&gt; precompile(tmp3,(Float64,Float64)) julia&gt; timing = @time for i in [1:100000] x = pi/2*rand(); eval(tmp3); end elapsed time: 8.611654016 seconds (13600048 bytes allocated) </code></pre> <p>EDIT2:</p> <p>@Ivarne suggested me to provide details on my project. Well, I would like to use the meta-programming capabilities of Julia to calculate the symbolic derivatives and run them.</p> <p>I wrote a function <code>derivative(ex::Expr,arg::Symbol)</code> that takes and expression and an argument, and returns a new expression that is the derivative of <code>ex</code> with respect to <code>arg</code>. Unfortunately, the resulting <code>Expr</code> takes too long to evaluate.</p> <p>EDIT3: as a conclusion, the performances using <code>@eval</code> instead of <code>eval</code>:</p> <pre><code>julia&gt; timing = @time for i in [1:100000] x = pi/2*rand(); @eval(tmp3); end elapsed time: 0.005821547 seconds (13600048 bytes allocated) </code></pre> <p><code>tmp3</code> is still <code>:(sin(x))</code></p>
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    1. COdo you understand that this shouldn't be important in most applications? macro expansion (which is where you manipulate julia's ast) typically occurs at compile time, not run time. so this slows down compilation a little bit, but not a running program.
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    2. CO@andrewcooke Well, that was the point of my question. Can I do something like `myExpression() = compile(:(tan(pi/2*rand())))` or `myExpression(x) = compile(:(tan(x)))` to create at run time a compiled object?
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