Metaprogramming

(How to make Pluto)

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262 μs

Error message

The package Pluto.jl could not load because it failed to initialize.

That's not nice! Things you could try:

Restart the notebook.
Try a different Julia version.
Contact the developers of Pluto.jl about this error.

You might find useful information in the package installation log:

Be patient :)

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begin

import Pkg

import Pluto

# before switching to the clean env

Pkg.activate(mktempdir())

Pkg.add(["PlutoUI"])

using PlutoUI

end

---

What is code?

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173 μs

Julia code comes in many forms. On its way from your thoughts to raw CPU instructions, the code undergoes a number of transformations. Every time that we go down a layer, we get to a structure that is more powerful and explicit, but less expressive.

Thoughts in your head
A text file with code (String)
A syntax tree (Expr)

...

CPU instructions

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595 μs

Syntax parsing

When you write Julia code, you do so by writing a text file. Try writing some Julia code in the box below!

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351 μs

Error message

UndefVarError: TextField not defined

Stack trace

Here is what happened, the most recent locations are first:

macro expansion
from This cell: line 125
Show more...

@bind test_code TextField((50, 5); default="""

x = let

# Let's do some math!

y=123

sqrt(y)

end""")

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---

Here is your code, in its original form, a String:

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200 μs

Error message

Another cell defining test_code contains errors.

test_code

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---

Error message

Another cell defining test_code contains errors.

Don't panic!

typeof(test_code)

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---

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67.3 μs

This is where we begin our story. The first thing that Julia does is syntax parsing: it goes from a String to an Expr.

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295 μs

Error message

Another cell defining test_code contains errors.

test_expr = parse_clean(test_code)

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---

Error message

Another cell defining test_code contains errors.

Oh no! 🙀

typeof(test_expr)

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---

That's right! Julia code is just another object in Julia! But what we see might be a little confusing: it is just the code that we typed, right?

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267 μs

Well, not exactly. What you see is Julia's built-in rich display, which does its best to make the Expr readable for us. The most readable way to display an abstract Expr is to show the equivalent code.

So instead, let's look directly at the internal structure of test_expr:

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293 μs

Error message

Another cell defining test_code contains errors.

computer bad, you GREAT!

sprint_dump(test_expr)

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---

Evaluation

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186 μs

Error message

UndefVarError: TextField not defined

Stack trace

Here is what happened, the most recent locations are first:

macro expansion
from This cell: line 125
Show more...

Be patient :)

@bind eval_code TextField((50, 5); default="""

x = let

# Let's do some math!

y=123

sqrt(y)

end""")

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---

Error message

Another cell defining eval_code contains errors.

Don't panic!

eval_expr = parse_clean(eval_code)

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---

Error message

Another cell defining eval_code contains errors.

let

🏡 = Module()

Core.eval(🏡, eval_expr)

end

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---

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67.8 μs

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113 μs

sprint_dump (generic function with 1 method)

function sprint_dump(x)

Text(sprint(Base.dump, x))

end

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443 μs

parse_clean (generic function with 1 method)

function parse_clean(code)

Base.remove_linenums!(Meta.parse(code, raise=false))

end

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593 μs

In the cloud (experimental)

On your computer

Frontmatter

Preview

Metaprogramming

(How to make Pluto)

What is code?

Syntax parsing

Evaluation