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Rust Your Own Lisp

deciduously profile image Ben Lovy Updated on ・15 min read

This is a fuller walk-through of the code I talked about in a previous post, Solving Problems by Avoiding Them.

The project is a translation of Build Your Own Lisp by orangeduck into Rust. His book is fantastic, both as an introduction to C and an introduction to writing an interpreter.

This post is nowhere close to a replacement for that text, by a long shot - go read the book. It's excellent. In translating to Rust, though, there are a few necessary differences worth noting. This post does not include the code in its entirety but rather examples of each concept, and may be useful for anyone attempting a similar project or translation of their own in Rust. I've also removed most debug logging for clarity. The full implementation can be found in this repo.

I learned a lot about C, interpreters, and Rust from this project, and highly recommend the exercise. For better or worse (probably worse), I've called this implementation blispr.

Rustyline

First thing's first, we've got to collect us some strings. I highly recommend rustyline, a pure-Rust readline implementation. You get line editing, keyboard commands, and command history out of the box. This is all you have to do:

fn repl(e: &mut Lenv) -> Result<()> {
    println!("Blispr v0.0.1");
    println!("Use exit(), Ctrl-C, or Ctrl-D to exit prompt");

    let mut rl = Editor::<()>::new();
    if rl.load_history("./.blispr-history.txt").is_err() {
        println!("No history found.");
    }

    loop {
        let input = rl.readline("blispr> ");

        match input {
            Ok(line) => {
                rl.add_history_entry(line.as_ref());
                print_eval_result(eval_str(e, &line));
            }
            Err(ReadlineError::Interrupted) => {
                info!("CTRL-C");
                break;
            }
            Err(ReadlineError::Eof) => {
                info!("CTRL-D");
                break;
            }
            Err(err) => {
                warn!("Error: {:?}", err);
                break;
            }
        }
    }
    rl.save_history("./.blispr-history.txt")?;
    Ok(())
}

fn print_eval_result(v: BlisprResult) {
    match v {
        Ok(res) => println!("{}", res),
        Err(e) => eprintln!("Error: {}", e),
    }
}

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One thing to note is that I'm not propagating the error that eval_str might throw up to the caller here with ? - I don't want blispr evaluation errors to crash the repl. Anything that can happen inside eval_str() I just want to inform the user about with eprintln!() and loop again. The &mut Lenv getting passed through is the global environment - more on that below.

The bulk of evaluation is hinted at in the Ok() arm of the match - the meat of the work is happening in eval_str():

pub fn eval_str(e: &mut Lenv, s: &str) -> BlisprResult {
    let parsed = BlisprParser::parse(Rule::blispr, s)?.next().unwrap();
    let mut lval_ptr = lval_read(parsed)?;
    lval_eval(e, &mut *lval_ptr)
}
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This is it, this is the entire interpreter. This function does all of the steps required to evaluate a programming language given in text string form. The first line stores the parse tree to parsed. This tags our input string with semantic grammatical tags that we'll define below. The next line reads that tree into an AST at lval_ptr, which represents the whole program as a lisp value that can be evaluated recursively. Finally we return the result of fully evaluating that AST with lval_eval, which ensures this there are no further evaluations that can happen. Any errors that happened along the way were caught with the ? operator - below we'll see what that Result<T> alias represents.

Lval

To represent the AST, I used a Rust enum called Lval:

// The recursive types hold their children in a `Vec`
type LvalChildren = Vec<Box<Lval>>;
// This is a function pointer type
pub type LBuiltin = fn(&mut Lval) -> BlisprResult;

// There are two types of function - builtin and lambda
#[derive(Clone)]
pub enum LvalFun {
    Builtin(String, LBuiltin), // (name, function pointer)
    Lambda(HashMap<String, Box<Lval>>, Box<Lval>, Box<Lval>), // (environment, formals, body), both should be Qexpr
}

// The main type - all possible Blispr values
#[derive(Debug, Clone, PartialEq)]
pub enum Lval {
    Fun(LvalFun),
    Num(i64),
    Sym(String),
    Sexpr(LvalChildren),
    Qexpr(LvalChildren),
}
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Each variant carries its contents with it. As we read the text each element is going to be converted into the proper type of Lval. For example, a string like "4" is going to be parsed into Lval::Num(4). Now this value can be used in the context of a larger evaluation. I've also implemented fmt::Display for this type, which is responsible for defining the output string to be finally displayed to the user. With the auto-derived Debug trait we get something like Lval::Num(4), and with Display we just get 4:

impl fmt::Display for Lval {
    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
        match self {
            Lval::Blispr(_cells) => write!(f, "<toplevel>"),
            Lval::Fun(lf) => match lf {
                LvalFun::Builtin(name, _) => write!(f, "<builtin: {}>", name),
                LvalFun::Lambda(_, formals, body) => write!(f, "(\\ {} {})", formals, body),
            },
            Lval::Num(n) => write!(f, "{}", n),
            Lval::Sym(s) => write!(f, "{}", s),
            Lval::Sexpr(cell) => write!(f, "({})", lval_expr_print(cell)),
            Lval::Qexpr(cell) => write!(f, "{{{}}}", lval_expr_print(cell)),
        }
    }
}

fn lval_expr_print(cell: &[Box<Lval>]) -> String {
    let mut ret = String::new();
    for i in 0..cell.len() {
        ret.push_str(&format!("{}", cell[i]));
        if i < cell.len() - 1 {
            ret.push_str(" ");
        }
    }
    ret
}
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We have numbers, symbols, functions (two different types of function - more on those later on), and two types of expression list - s-expressions and q-expressions. S-expressions will be evaluated as code, looking for a function in the first position, and q-expressions are evaluated as just lists of data. The whole program that's read in is going to be one big containing Lval::Sexpr, and we just need to evaluate it until we only have a result needing no further evaluation, either a Num, Sym, or Qexpr.

As a simple example, "+ 1 2" is going to get stored as Sexpr(Sym("+"), Num(1), Num(2)). When this Sexpr is evaluated, it will first look up + in the environment and find a function pointer to the built-in addition function: Sexpr(Fun(Builtin("+"), Num(1), Num("2"))). Then this Sexpr will be evaluated as a function call, yielding Num(3), which cannot be evaluated further.

This code makes use of the Box pointer type, which is a smart pointer to a heap-allocated value. Because an Lval can hold many different types of data, the size of a given Lval is not known at compile-time. By only storing pointers to values on the heap, we can build lists of them. Because these Boxes adhere to Rust's ownership and borrowing semantics, Rust is going to manage cleaning them up for us when they are no longer needed. This is how we'll manage our memory over the lifetime of the program - with quite a bit less ceremony than the corresponding C! To build a new one, we use a constructor. For example:

pub fn lval_num(n: i64) -> Box<Lval> {
    Box::new(Lval::Num(n))
}
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There's one of these for each variant. Calling this will allocate the appropriate space with Box::new() on the heap and return the pointer. No need to futz with a destructor - the Box will drop itself as soon as it can.

The containing types start out with an empty Vec of children, and can be manipulated with lval_add and lval_pop:

// Add lval x to lval::sexpr or lval::qexpr v
pub fn lval_add(v: &mut Lval, x: &Lval) -> Result<()> {
    match *v {
        Lval::Sexpr(ref mut children)
        | Lval::Qexpr(ref mut children)
        | Lval::Blispr(ref mut children) => {
            children.push(Box::new(x.clone()));
        }
        _ => return Err(BlisprError::NoChildren),
    }
    Ok(())
}

// Extract single element of sexpr at index i
pub fn lval_pop(v: &mut Lval, i: usize) -> BlisprResult {
    match *v {
        Lval::Sexpr(ref mut children)
        | Lval::Qexpr(ref mut children)
        | Lval::Blispr(ref mut children) => {
            let ret = (&children[i]).clone();
            children.remove(i);
            Ok(ret)
        }
        _ => Err(BlisprError::NoChildren),
    }
}
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Both of these functions mutate their first argument in place, either removing or adding a child.

Errors

One difference from the book's implementation is that I don't have a separate specific Lval::Err AST variant for handling errors in our program. Instead, I built a separate error type and leverage Result<T, E>-style error handling throughout:

#[derive(Debug)]
pub enum BlisprError {
    DivideByZero,
    EmptyList,
    FunctionFormat,
    NoChildren,
    NotANumber,
    NumArguments(usize, usize),
    ParseError(String),
    ReadlineError(String),
    WrongType(String, String),
    UnknownFunction(String),
}
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To simplify the type signatures used throughout, I have a few type aliases:

pub type Result<T> = std::result::Result<T, BlisprError>;
pub type BlisprResult = Result<Box<Lval>>;
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The majority of evaluation functions are going to return a Result<Box<Lval>, BlisprError>, now I can just type BlisprResult. The few functions here and there that don't have a success type of Box<Lval> can still use this new Result<T> alias instead of the more verbose built-in Result<T, E>, and the error type will automatically always be this BlisprError.

In order to be able to use this throughout our entire program, I've provided impl From<E> for BlisprError for a few other types of errors that are thrown, like std::io::Error and pest::error::Error for example:

impl<T> From<pest::error::Error<T>> for BlisprError
where
    T: Debug + Ord + Copy + Hash,
{
    fn from(error: pest::error::Error<T>) -> Self {
        BlisprError::ParseError(format!("{}", error))
    }
}

impl From<std::io::Error> for BlisprError {
    fn from(error: std::io::Error) -> Self {
        BlisprError::ParseError(error.to_string())
    }
}
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This way I can still use the ? operator on function calls that return these other error types inside functions that return a BlisprResult, and any errors returned will be automatically converted to the proper BlisprError for me. Instead of storing specific error-type Lvals during our evaluation that are carried through the whole computation and finally printed out, all errors are bubbled up through the type system, but you still get the full pest-generated error carried along:

blispr> eval {* 2 3)
Parse error:  --> 1:12
  |
1 | eval {* 2 3)
  |            ^---
  |
  = expected expr
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Full disclosure: to write the pest::error::Error<T> block, I just wrote what I wanted, i.e. BlisprError::ParseError(format!("{}", error)) and appeased the compiler. There is likely a better way to go about this but it works!

Parsing

The book uses the author's own parser combinator library called mpc. If I were to tackle another similar problem in C, I'd likely reach for it again. Rust, however, has its own strong ecosystem for parsing. Some of the heavyweights in this space are nom, combine, and pest. For this project I opted for pest, to stay as close to the source material as possible. Whereas nom and combine will have you defining your own parser combinators, with pest you provide a PEG (or Parsing Expression Grammar), separately from your code. Pest then uses Rust's powerful custom derive tooling to create a parse for your grammar automatically.

Here's the grammar I used for this language:

COMMENT = _{ "/*" ~ (!"*/" ~ ANY)* ~ "*/" }
WHITESPACE = _{ (" " | NEWLINE ) }

num = @{ int }
    int = { ("+" | "-")? ~ digit+ }
    digit = { '0'..'9' }

symbol = @{ (letter | digit | "_" | arithmetic_ops | "\\" | comparison_ops | "&")+ }
    letter = { 'a' .. 'z' | 'A' .. 'Z' }
    arithmetic_ops = { "+" | "-" | "*" | "/" | "%" | "^" }
    comparison_ops = { "=" | "<" | ">" | "!" }

sexpr = { "(" ~ expr* ~ ")" }

qexpr = { "{" ~ expr* ~ "}" }

expr = { num | symbol | sexpr | qexpr }

blispr = { SOI ~ expr* ~ EOI }
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This is stored in its own file called blispr.pest alongside the source code. Each line refines a parse rule. I find this exceedingly readable, and easy to tweak. Starting from the bottom, we see a unit of valid blispr consists of one or more exprs between the Start of Input (SOI) and End of Input (EOI). An expr is any of the options given. It can handle comments and whitespace for you. I also enjoy how the grammar maintained completely separately from any Rust code. It's easy to get this working with Rust:

use pest::{iterators::Pair, Parser};

#[cfg(debug_assertions)]
const _GRAMMAR: &str = include_str!("blispr.pest");

#[derive(Parser)]
#[grammar = "blispr.pest"]
pub struct BlisprParser;
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Now we can use the BlisprParser struct to parse string input into a parse tree with parse(). In order to evaluate it, though, we need to build a a big Lval AST:

fn lval_read(parsed: Pair<Rule>) -> BlisprResult {
    match parsed.as_rule() {
        Rule::blispr => {
            let mut ret = lval_blispr();
            read_to_lval(&mut ret, parsed)?;
            Ok(ret)
        }
        Rule::expr => lval_read(parsed.into_inner().next().unwrap()),
        Rule::sexpr => {
            let mut ret = lval_sexpr();
            read_to_lval(&mut ret, parsed)?;
            Ok(ret)
        }
        Rule::qexpr => {
            let mut ret = lval_qexpr();
            read_to_lval(&mut ret, parsed)?;
            Ok(ret)
        }
        Rule::num => Ok(lval_num(parsed.as_str().parse::<i64>()?)),
        Rule::symbol => Ok(lval_sym(parsed.as_str())),
        _ => unreachable!(), // COMMENT/WHITESPACE etc
    }
}
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We pass the parse tree from pest into lval_read, which will recursively build the AST for us. This function looks at the top-level rule and takes an appropriate action, either allocating a new Lval variant or adjusting the children of . Then every child in the parse tree is added as a child to this containing Lval, passing through lval_read() itself to turn it into the correct Lval. The rule for qexpr is similar, and the other rules just create the corresponding Lval from the type given. The one weird one is Rule::expr - this is a sort of meta-rule that matches any of the valid expression types, so it's not its own lval, just wrapping one of a more specific type. We just use next() to pass the actual rule found back into lval_read().

The variants contianng children use a helper which skips surrounding brackets, and just adds the actual children to the new Lval:

fn read_to_lval(mut v: &mut Lval, parsed: Pair<Rule>) -> Result<()> {
    for child in parsed.into_inner() {
        if is_bracket_or_eoi(&child) {
            continue;
        }
        lval_add(&mut v, &*lval_read(child)?)?;
    }
    Ok(())
}
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The final result of lval_read() will be a single Lval containing the entire parsed program, saved in lval_ptr. Then we call lval_eval(), which will also return a BlisprResult after reducing this tree to its most evaluated form. If the evaluation is successful we just print out the result, and if any error was raised we print that error instead.

Environment

Before we dig into how lval_eval() does its mojo lets pause and talk about the environment. This is how symbols are able to correspond to functions and values - otherwise "+" would just be that character, but we need to to specifically correspond to the addition function.

Jury's out on whether or not I have the right idea, here, but I also handled this differently from the book. The original text has you create a struct that holds two arrays and a counter, one for keys and the other for values. To perform a lookup, you find the index of that key and then return the value at that same index in the values. This struct is built before the program enters the loop, and is passed in manually to every single function that gets called.

Instead, I've opted for a HashMap data structure instead of two separated arrays with matching indices:

pub type LEnvLookup = HashMap<String, Box<Lval>>;

#[derive(Debug, PartialEq)]
pub struct Lenv<'a> {
    lookup: LEnvLookup,
    pub parent: Option<&'a Lenv<'a>>,
}
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The Lenv itself holds the lookup table and optionally a reference to a parent.

I've got some helper methods for getting, setting, and enumerating the contents:

impl Lenv {

 // ..

 pub fn get(&self, k: &str) -> BlisprResult {
        match self.lookup.get(k) {
            Some(v) => Ok(v.clone()),
            None => {
                // if we didn't find it in self, check the parent
                // this will recur all the way up to the global scope
                match &self.parent {
                    None => Err(BlisprError::UnknownFunction(k.to_string())),
                    Some(p_env) => p_env.get(k),
                }
            }
        }
    }

    // Returns an Lval containing Symbols with each k,v pair in the local env
    pub fn list_all(&self) -> BlisprResult {
        let mut ret = lval_qexpr();
        for (k, v) in &self.lookup {
            lval_add(&mut ret, &lval_sym(&format!("{}:{}", k, v)))?;
        }
        Ok(ret)
    }

    // add a value to the local env
    pub fn put(&mut self, k: String, v: Box<Lval>) {
        let current = self.lookup.entry(k).or_insert_with(|| v.clone());
        if *v != **current {
            // if it already existed, overwrite it with v
            *current = v;
        }
    }
}
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Getting a value from the environment will return a brand new Lval with a copy of what's stored, and printing out the contents will also return a ready-made Lval::Qexpr containing Symbols corresponding to each entry. We'll come back to initialization after talking a bit about evaluation.

Environments optionally hold a parent environment, and if the lookup fails in this one it will attempt the parent environment.

Eval

The lval_eval() function called in eval_str() is where the real crunching happens. This will take an Lval (that is, an AST) and recursively evaluate it to a final Lval. Most types of Lval are already evaluated fully - but any S-Expression found will need to be evaluated, and any Symbol gets looked up in the environment.

Before looking at the Rust, let's break it down in English:

  1. Check the type of Lval:

    a. Fun | Num | Qexpr - we're done - return lval as is.

    b. Symbol - Do an environment lookup with Lenv::get() - e.g., for Sym("+"), see if we have a function pointer stored at name "+". Return result of lookup, which will already be an Lval.

    c. Sexpr - Evaluate the S-Expression.

  2. If we made it to this step, we're working with an S-Expression. Everything else has already returned. Before going further, fully evaluate all children with lval_eval().

  3. Check the length of the S-Expression:

    a. 0 - empty S-Expression - return as-is

    b. 1 - single expression - pop that expression and return the result of calling lval_eval() on it

    c. Multiple expressions (function call) - pop the first expression and attempt to use it as a function on the rest of the children

Here's what that looks like in Rust:

// Fully evaluate an `Lval`
pub fn lval_eval(e: &mut Lenv, v: &mut Lval) -> BlisprResult {
    let child_count;
    let mut args_eval;
    match v {
        Lval::Blispr(forms) => {
            // If it's multiple, evaluate each and return the result of the last
            args_eval = eval_cells(e, forms)?;
            let forms_len = args_eval.len()?;
            return Ok(lval_pop(&mut args_eval, forms_len - 1)?);
        }
        Lval::Sym(s) => {
            // If it's a symbol, perform an environment lookup
            let result = e.get(&s)?;
            // The environment stores Lvals ready to go, we're done
            return Ok(result);
        }
        Lval::Sexpr(ref mut cells) => {
            // If it's a Sexpr, we're going to continue past this match
            // First recursively evaluate each child with lval_eval()
            // grab the length and evaluate the children
            child_count = cells.len();
            args_eval = eval_cells(e, cells)?;
        }
        // if it's not a sexpr, we're done, return as is
        _ => {
            return Ok(Box::new(v.clone()));
        }
    }
    if child_count == 0 {
        // It was a Sexpr, but it was empty.  We're done, return it
        Ok(Box::new(v.clone()))
    } else if child_count == 1 {
        // Single expression
        lval_eval(e, &mut *lval_pop(v, 0)?)
    } else {
        // Function call
        // We'll pop the first element off and attempt to call it on the rest of the elements
        let fp = lval_pop(&mut args_eval, 0)?;
        lval_call(e, *fp, &mut *args_eval)
    }
}
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The step that fully evaluates all the children of an S-Expression before tackling the expression itself uses a helper:

// Given a slice of boxed Lvals, return a single evaluated sexpr
fn eval_cells(e: &mut Lenv, cells: &[Box<Lval>]) -> BlisprResult {
    cells.iter().fold(Ok(lval_sexpr()), |acc, c| {
        match acc {
            Ok(mut lval) => {
                lval_add(&mut lval, &*lval_eval(e, &mut c.clone())?)?;
                Ok(lval)
            }
            // it's just a Result so we can bubble errors out of the fold
            Err(_) => unreachable!(),
        }
    })
}
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This is written as a fold using an empty Lval::Sexpr as the accumulator, using lval_add to add each new result to it.

Function calling

This gets us almost all the way there - there's one last missing step, which is lval_call().

This language has two kinds of functions: builtins and user-defined lambdas. Builtins are implemented in Rust and part of the executable itself. These are stored in the environment when it's created:

fn add_builtin(&mut self, name: &str, func: LBuiltin) {
    self.put(name.to_string(), lval_builtin(func, name))
}

pub fn new(lookup: Option<LEnvLookup>, parent: Option<&'a Lenv<'a>>) -> Self {
        let mut ret = Self {
            lookup: lookup.unwrap_or_default(),
            parent,
        };

        // Register builtins
        // The "stub" fns are dispatched separately - the function pointer stored is never called
        // these are the ones the modify the environment

        // Definiton
        ret.add_builtin("\\", builtin_lambda);
        ret.add_builtin("def", builtin_put_stub);

        // etc, lots and lots of builtins

        ret.add_builtin("max", builtin_max);

        ret
}
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Each name stores a function pointer to a Rust function. These functions manipulate lvals directly. For example, this is builtin_head, which returns the first element of an Lval::Qexpr:

pub fn builtin_head(v: &mut Lval) -> BlisprResult {
    let mut qexpr = lval_pop(v, 0)?;
    match *qexpr {
        Lval::Qexpr(ref mut children) => {
            if children.is_empty() {
                return Err(BlisprError::EmptyList);
            }
            debug!("builtin_head: Returning the first element");
            Ok(children[0].clone())
        }
        _ => Err(BlisprError::WrongType(
            "qexpr".to_string(),
            format!("{:?}", qexpr),
        )),
    }
}
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Mathematical operations all use the same function. They all accept a list of any length of Lval::Nums and will successively apply a binary operation to a running result and the next number until the list is consumed:

fn builtin_op(mut v: &mut Lval, func: &str) -> BlisprResult {
    let mut child_count;
    match *v {
        Lval::Sexpr(ref children) => {
            child_count = children.len();
        }
        _ => return Ok(Box::new(v.clone())),
    }

    let mut x = lval_pop(&mut v, 0)?;

    // If no args given and we're doing subtraction, perform unary negation
    if (func == "-" || func == "sub") && child_count == 1 {
        let x_num = x.as_num()?;
        return Ok(lval_num(-x_num));
    }

    // consume the children until empty
    // and operate on x
    while child_count > 1 {
        let y = lval_pop(&mut v, 0)?;
        child_count -= 1;
        match func {
            "+" | "add" => {
                apply_binop!(add, x, y)
            }
            "-" | "sub" => {
                apply_binop!(sub, x, y)
            }
            "*" | "mul" => {
                apply_binop!(mul, x, y)
            }
            "/" | "div" => {
                if y.as_num()? == 0 {
                    return Err(BlisprError::DivideByZero);
                } else {
                    apply_binop!(div, x, y)
                }
            }
            "%" | "rem" => {
                apply_binop!(rem, x, y)
            }
            "^" | "pow" => {
                let y_num = y.as_num()?;
                let x_num = x.as_num()?;
                let mut coll = 1;
                for _ in 0..y_num {
                    coll *= x_num;
                }
                x = lval_num(coll);
            }
            "min" => {
                let x_num = x.as_num()?;
                let y_num = y.as_num()?;
                if x_num < y_num {
                    x = lval_num(x_num);
                } else {
                    x = lval_num(y_num);
                };
            }
            "max" => {
                let x_num = x.as_num()?;
                let y_num = y.as_num()?;
                if x_num > y_num {
                    x = lval_num(x_num);
                } else {
                    x = lval_num(y_num);
                };
            }
            _ => unreachable!(),
        }
    }
    Ok(x)
}
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This is a long function - but it'd be even longer without the macro I defined:

macro_rules! apply_binop {
    ( $op:ident, $x:ident, $y:ident ) => {
        match (*$x, *$y) {
            (Lval::Num(x_num), Lval::Num(y_num)) => {
                $x = lval_num(x_num.$op(y_num));
                continue;
            }
            _ => return Err(BlisprError::NotANumber),
        }
    };
}
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This makes some of the Lval type checking quicker to type! It handles making sure both arguments are Lval::Num before trying to do something numeric with them, as in apply_binop!(add, x, y). This was my first brush with defining Rust macros, and it was a serious help.

These are fairly easy to call. Because the environment stores these ans function pointers you can simply call the function. My solution is a little hacky, because a few builtins require access to an environment, which builtin functions don't have - these special cases are dispatched separately, and everything else is just called with fp():

LvalFun::Builtin(name, fp) => match name.as_str() {
        "eval" => builtin_eval(e, args),
        "def" => builtin_def(e, args),
        "printenv" => builtin_printenv(e),
        // Otherwise, just apply the actual stored function pointer
        _ => fp(args),
},
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Calling a Lambda is a little trickier. We need to build a new environment, add any local bindings to it, and then either call the new function or return a new, partially applied lambda if not all locals were given. The machinery here is verbose - see this line for the code in context.

That's all of our pieces. With all this in place lval_eval() can handle a whole bunch of stuff, and this language actually approaches usable. This language implementation is not complete, but it's a great playground for learning about how languages work!

Discussion (11)

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Yoandy Rodriguez Martinez

Great stuff Ben!!!. A question from a fellow Rustling, why does Fun(LvalFun) works without deriving PartialEq?

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Ben Lovy Author • Edited

Good eye :) It definitely doesn't, I fudged it:

impl PartialEq for LvalFun {
    fn eq(&self, other: &LvalFun) -> bool {
        match self {
            LvalFun::Builtin(name, _) => match other {
                LvalFun::Builtin(other_name, _) => name == other_name,
                _ => false,
            },
            LvalFun::Lambda(env, formals, body) => match other {
                LvalFun::Lambda(other_env, other_f, other_b) => {
                    formals == other_f && body == other_b && env == other_env
                }
                _ => false,
            },
        }
    }
}

Builtin functions are considered "equal" if they share a name, and because there are no name collisions in the environment I deemed it "good enough".

Can you think of reasons why this wouldn't be sufficient? It's on my "revisit later" list and for now seems to be working fine.

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Yoandy Rodriguez Martinez

Oooh, I missed the part where you implemented that, nice workaround :D

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Ben Lovy Author

workaround, cheat, who knows :)

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Yoandy Rodriguez Martinez

(when (boudp 'brah-mode)
(format "Dude, we should implement Common Lisp in Rust!!!! 😱😱🤓🤓🤓"))

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Ben Lovy Author

Hah! Move over Remacs, the grown-up languages want to play.

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Yoandy Rodriguez Martinez

Back in school that was our version of "let's buy a bar"

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arj

What an impressive article. Thanks for this! I taught building an interpreter as a TA at the university and this article is really good. Well done!

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Ben Lovy Author

Wow, that's super validating to hear, as a total novice who's never taught anything to anyone! I'm glad I'm on the right track, and learned so much from putting this together I think everyone should do it for themselves.

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Dave Cridland

You might want to compare and contrast with kirit.com/Build%20me%20a%20LISP

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Ben Lovy Author

Ah, neat, thanks! A C++ implementation would likely have been a simpler translation than C, too.