{"id":3035,"date":"2023-03-05T17:36:34","date_gmt":"2023-03-05T12:06:34","guid":{"rendered":"https:\/\/www.rangakrish.com\/?p=3035"},"modified":"2023-03-06T05:09:47","modified_gmt":"2023-03-05T23:39:47","slug":"julia-defining-functions-dynamically","status":"publish","type":"post","link":"https:\/\/www.rangakrish.com\/index.php\/2023\/03\/05\/julia-defining-functions-dynamically\/","title":{"rendered":"Julia: Defining Functions Dynamically"},"content":{"rendered":"

One of the widely discussed features of Julia<\/a><\/strong><\/em> is its support for metaprogramming<\/strong><\/em>. This feature makes it possible to generate and inspect the code at runtime. In essence, metaprogramming blurs the distinction between code and data. When used carefully, it can contribute to good code.<\/p>\n

Of course, Julia is<\/strong><\/em> not the only or the first language to support Metaprogramming. Many other languages such as Lisp<\/strong><\/em>, Clojure<\/strong><\/em>, Ruby<\/strong><\/em>, Elixir<\/strong><\/em>, and Python<\/strong><\/em> also have support for metaprogramming.<\/p>\n

In today\u2019s article, I would like to show how we can define functions at runtime<\/strong><\/em> in Julia<\/strong><\/em>. This technique applies to generating any code, although my focus is on defining functions.<\/p>\n

1) Generating using Strings<\/h3>\n

This is the simplest way to generate runtime code. We use the \u201cMeta.parse()\u201d<\/strong><\/em> function for this. The following example shows how it is done:<\/p>\n

\"Defining<\/a>
Defining A Function Dynamically<\/strong><\/figcaption><\/figure>\n

The function \u201cToFunction()\u201d<\/strong><\/em> takes a String<\/strong><\/em> argument and converts that to a Julia<\/strong><\/em> function. Cell[2] shows how this works. As cell[4] shows, the function can be invoked using its defined name.<\/p>\n

Here is another example that defines an \u201canonymous\u201d<\/strong><\/em> function. The behaviour is the same.<\/p>\n

\"Defining<\/a>
Defining Anonymous Function Dynamically<\/strong><\/figcaption><\/figure>\n

Some programmers might prefer to define \u201cToFunction()\u201d<\/strong> <\/em>as a \u201cmacro\u201d<\/strong><\/em> instead of as a regular function. This permits the function synthesis to happen in two stages: the AST<\/strong><\/em> is generated at \u201ccompile time\u201d<\/strong><\/em> and is turned into a function at runtime.<\/p>\n

\"Defining<\/a>
Defining A Macro Instead of Function<\/strong><\/figcaption><\/figure>\n

We can tweak our function slightly so that it accepts multiple arguments:<\/p>\n

\"Refining<\/a>
Refining the Macro<\/strong><\/figcaption><\/figure>\n

Needless to say, the supplied String<\/strong><\/em> argument must represent a valid function definition. If not, we will get an error:<\/p>\n

\"Function<\/a>
Function Definition Error<\/strong><\/figcaption><\/figure>\n

2) Generating using AST<\/h3>\n

Instead of using a String<\/strong><\/em> representation of the function to be defined, it is possible to work directly at the level of AST<\/strong><\/em>. This is essentially how \u201cmacros\u201d<\/strong><\/em> work. In the following example, the macro \u201cMakeFunction()\u201d<\/strong><\/em> takes an arbitrary \u201cExpr\u201d<\/strong><\/em> object as its argument and embeds it inside the body of the function to be synthesized.<\/p>\n

\"Synthesis<\/a>
Synthesis Using AST<\/strong><\/figcaption><\/figure>\n

Cell[21] shows how this macro is invoked. Note that the generated function is \u201canonymous\u201d<\/strong><\/em> and hence must be called using the returned function object. Cells[22] and [23] show that the function works as expected.<\/p>\n

Here is another example that passes an expression involving a variable in the current scope:<\/p>\n

\"Using<\/a>
Using a Variable in the Expression<\/strong><\/figcaption><\/figure>\n

As cells[31] and [32] show, this also works correctly.<\/p>\n

There is a useful function called \u201cmethods()\u201d<\/strong><\/em><\/a>\u00a0 that returns the method table for any given function. We can use it in our case to learn about the \u201cdynamic\u201d<\/strong><\/em> method that we synthesized:<\/p>\n

\"The<\/a>
The Methods() Function<\/strong><\/figcaption><\/figure>\n

The examples discussed above only \u201cscratch the surface\u201d as far as metaprogramming in Julia<\/strong><\/em> is concerned. I encourage you to visit the documentation<\/a> to learn more about this topic.<\/p>\n

You can download<\/strong><\/em><\/a> the JupyterLab<\/strong><\/em> notebook used in this article.<\/p>\n

Have a great weekend!<\/p>\n","protected":false},"excerpt":{"rendered":"

One of the widely discussed features of Julia is its support for metaprogramming. This feature makes it possible to generate and inspect the code at runtime. In essence, metaprogramming blurs the distinction between code and data. When used carefully, it can contribute to good code. Of course, Julia is not the only or the first […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[63,17],"tags":[64,353],"class_list":["post-3035","post","type-post","status-publish","format-standard","hentry","category-julia","category-programming","tag-julia","tag-metaprogramming"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p9OLnF-MX","jetpack-related-posts":[{"id":278,"url":"https:\/\/www.rangakrish.com\/index.php\/2016\/07\/07\/multimethods-in-julia\/","url_meta":{"origin":3035,"position":0},"title":"Multimethods in Julia","author":"admin","date":"July 7, 2016","format":false,"excerpt":"I got interested in Julia programming language quite recently, primarily because of a project involving image processing and machine learning. The language is still evolving, but already has a rich set of features and a good collection of external libraries\u00a0covering many areas. One of the highlights of the language is\u2026","rel":"","context":"In "Julia"","block_context":{"text":"Julia","link":"https:\/\/www.rangakrish.com\/index.php\/category\/julia\/"},"img":{"alt_text":"Multimethods Example","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2015\/10\/Multimethods.png?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":3017,"url":"https:\/\/www.rangakrish.com\/index.php\/2023\/02\/16\/calling-external-dll-functions-from-julia\/","url_meta":{"origin":3035,"position":1},"title":"Calling External DLL Functions from Julia","author":"admin","date":"February 16, 2023","format":false,"excerpt":"Julia supports calling external functions, especially those written in \u201cC\u201d language. As Julia documentation says, such calls do not involve any \u201cboilerplate\u201d code and hence are efficient. In today\u2019s article, I am going to show how to call functions defined in a DLL (Windows 64 bit). Instead of using direct\u2026","rel":"","context":"In "Julia"","block_context":{"text":"Julia","link":"https:\/\/www.rangakrish.com\/index.php\/category\/julia\/"},"img":{"alt_text":"The \"lispEval\" Function","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2023\/02\/code-300x117.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2023\/02\/code-300x117.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2023\/02\/code-300x117.jpg?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":3675,"url":"https:\/\/www.rangakrish.com\/index.php\/2025\/04\/24\/interfaces-without-inheritance-comparing-c-and-common-lisp\/","url_meta":{"origin":3035,"position":2},"title":"Interfaces Without Inheritance: Comparing C++ and Common Lisp","author":"admin","date":"April 24, 2025","format":false,"excerpt":"Clean interface design is a crucial aspect of software engineering since it enables code flexibility, reuse, and maintainability. Developers who prefer an object-oriented approach typically rely on inheritance to define the interface and thus establish type relationships. While this can lead to a good design if approached carefully, detractors of\u2026","rel":"","context":"In "C++"","block_context":{"text":"C++","link":"https:\/\/www.rangakrish.com\/index.php\/category\/c\/"},"img":{"alt_text":"Rectangle and Circle Defined","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/04\/cpp2-251x300.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":2935,"url":"https:\/\/www.rangakrish.com\/index.php\/2022\/11\/07\/why-learn-c\/","url_meta":{"origin":3035,"position":3},"title":"Why Learn C++","author":"admin","date":"November 7, 2022","format":false,"excerpt":"This is the third and the last article in the series \u201cWhy Learn Language-XYZ?\u201d. I talked about Prolog and Lisp earlier. The present article is on C++. 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