Learning Parser Combinators with Rust


18 Apr 2019

This article teaches the fundamentals of parser combinators to people who are
already Rust programmers. It assumes no other knowledge, and will explain
everything that isn’t directly related to Rust, as well as a few of the more
unexpected aspects of using Rust for this purpose. It will not teach you Rust if
you don’t already know it, and, if so, it probably also won’t teach you parser
combinators very well. If you would like to learn Rust, I recommend the book
The Rust Programming Language.

Beginner’s Mind #

There comes a point in the life of every programmer when they find themselves in
need of a parser.

The novice programmer will ask, “what is a parser?”

The intermediate programmer will say, “that’s easy, I’ll write a regular

The master programmer will say, “stand back, I know lex and yacc.”

The novice has the right idea.

Not that regular expressions aren’t great. (But please don’t try writing a
complicated parser as a regular expression.) Not that there’s no joy to be had
in employing powerful tools like parser and lexer generators that have been
honed to perfection over millennia. But learning about parsers from the ground
up is fun. It’s also something you’ll be missing out on if you stampede
directly towards regular expressions or parser generators, both of which are
only abstractions over the real problem at hand. In the beginner’s mind, as the
man said
, there
are many possibilities. In the expert’s mind, there’s only the one the expert
got used to.

In this article, we’re going to learn how to build a parser from the ground up
using a technique common in functional programming languages known as parser
. They have the advantage of being remarkably powerful once you
grasp the basic idea of them, while at the same time staying very close to first
principles, as the only abstractions here will be the ones you build yourself on
top of the basic combinators – all of which you’ll also have to build before you
get to use them.

How To Work Through This Article #

It’s highly recommended that you start a fresh Rust project and type the code
snippets into src/lib.rs as you read (you can paste it directly from the page,
but typing it in is better, as the act of doing so automatically ensures you
read the code in its entirety). Every piece of code you’re going to need is
introduced by the article in order. Mind that it sometimes introduces changed
versions of functions you’ve written previously, and that in these cases you
should replace the old version with the new one.

The code was written for rustc version 1.34.0 using the 2018 edition of the
language. You should be able to follow along using any version of the compiler
that is more recent, as long as you make sure you’re using the 2018 edition
(check that your Cargo.toml contains edition = "2018"). The code needs no
external dependencies.

To run the tests introduced in the article, as you might expect, you use cargo test.

The Xcruciating Markup Language #

We’re going to write a parser for a simplified version of XML. It looks like

  <single-element attribute="value" />

XML elements open with the symbol < and an identifier consisting of a letter
followed by any number of letters, numbers and -. This is followed by some
whitespace, and an optional list of attribute pairs: another identifier as
defined previously, followed by a = and a double quoted string. Finally, there
is either a closing /> to signify a single element with no children, or a >
to signify there is a sequence of child elements following, and finally a
closing tag starting with </, followed by an identifier which must match the
opening tag, and a final >.

That’s all we’re going to support. No namespaces, no text nodes, none of the
rest, and definitely no schema validation. We’re not even going to bother
supporting escape quotes for those strings – they start at the first double
quote and they end at the next one, and that’s it. If you want double quotes
inside your actual strings, you can take your unreasonable demands somewhere

We’re going to parse those elements into a struct that looks like this:

#[derive(Clone, Debug, PartialEq, Eq)]
struct Element {
    name: String,
    attributes: Vec<(String, String)>,
    children: Vec<Element>,

No fancy types, just a string for a name (that’s the identifier at the start of
each tag), attributes as pairs of strings (identifier and value), and a list of
child elements that look exactly the same as the parent.

(If you’re typing along, make sure you include those derives. You’re going to
need them later.)

Defining The Parser #

Well, then, it’s time to write the parser.

Parsing is a process of deriving structure from a stream of data. A parser is
something which teases out that structure.

In the discipline we’re about to explore, a parser, in its simplest form, is a
function which takes some input and returns either the parsed output along with
the remainder of the input, or an error saying “I couldn’t parse this.”

It turns out that’s also, in a nutshell, what a parser looks like in its more
complicated forms. You might complicate what the input, the output and the error
all mean, and if you’re going to have good error messages you’ll need to, but
the parser stays the same: something that consumes input and either produces
some parsed output along with what’s left of the input or lets you know it
couldn’t parse the input into the output.

Let’s write that down as a function type.

Fn(Input) -> Result<(Input, Output), Error>

More concretely, in our case, we’ll want to fill out the types so we get
something like this, because what we’re about to do is convert a string into an
Element struct, and at this point we don’t want to get into the intricacies of
error reporting, so we’ll just return the bit of the string that we couldn’t
parse as an error:

Fn(&str) -> Result<(&str, Element), &str>

We use a string slice because it’s an efficient pointer to a piece of a string,
and we can slice it up further however we please, “consuming” the input by
slicing off the bit that we’ve parsed and returning the remainder along with the

It might have been cleaner to use &[u8] (a slice of bytes, corresponding to
characters if we restrict ourselves to ASCII) as the input type, especially
because string slices behave a little differently from most slices – especially
in that you can’t index them with a single number input[0], you have to use a
slice input[0..1]. On the other hand, they have a lot of methods that are
useful for parsing strings that slices of bytes don’t have.

In fact, in general we’re going to be relying on those methods rather than
indexing it like that, because, well, Unicode. In UTF-8, and all Rust strings
are UTF-8, these indexes don’t always correspond to single characters, and it’s
better for all parties concerned that we ask the standard library to just please
deal with this for us.

Our First Parser #

Let’s try writing a parser which just looks at the first character in the string
and decides whether or not it’s the letter a.

fn the_letter_a(input: &str) -> Result<(&str, ()), &str> {
  match input.chars().next() {
      Some('a') => Ok((&input['a'.len_utf8()..], ())),
      _ => Err(input),

First, let’s look at the input and output types: we take a string slice as
input, as we’ve discussed, and we return a Result of either (&str, ()) or
the error type &str. The pair of (&str, ()) is the interesting bit: as we’ve
talked about, we’re supposed to return a tuple with the next bit of input to
parse and the result. The &str is the next input, and the result is just the
unit type (), because if this parser succeeds, it could only have had one
result (we found the letter a), and we don’t particularly need to return the
letter a in this case, we just need to indicate that we succeeded in finding

And so, let’s look at the code for the parser itself. We start by getting the
first character of the input: input.chars().next(). We weren’t kidding about
leaning on the standard library to avoid giving us Unicode headaches – we ask it
to get us an iterator chars() over the characters of the string, and we pull
the first item off it. This will be an item of type char, wrapped in an
Option, so Option<char>, where None means we tried to pull a char off an
empty string.

To make matters worse, a char isn’t necessarily even what you think of as a
character in Unicode. That would most likely be what Unicode calls a “grapheme
,” which can be
composed of several chars, which in fact represent “scalar
,” about two
levels down from grapheme clusters. However, that way lies madness, and for our
purposes we honestly aren’t even likely to see any chars outside the ASCII
set, so let’s leave it there.

We pattern match on Some('a'), which is the specific result we’re looking for,
and if that matches, we return our success value: Ok((&input['a'.len_utf8()..], ())). That is, we remove the bit we just parsed (the 'a') from the string
slice and return the rest, along with our parsed value, which is just the empty
(). Ever mindful of the Unicode monster, we ask the standard library for the
length of 'a' in UTF-8 before slicing – it’s 1, but never, ever presume about
the Unicode monster.

If we get any other Some(char), or if we get None, we return an error. As
you’ll recall, our error type right now is just going to be the string slice at
the point where parsing failed, which is the one that we got passed in as
input. It didn’t start with a, so that’s our error. It’s not a great error,
but at least it’s marginally better than just “something is wrong somewhere.”

We don’t actually need this parser to parse XML, though, but the first thing we
need to do is look for that opening <, so we’re going to need something very
similar. We’re also going to need to parse >, / and = specifically,
so maybe we can make a function which builds a parser for the character we want?

A Parser Builder #

Let’s even get fancy about this: let’s write a function that produces a parser
for a static string of any length, not just a single character. It’s even sort
of easier that way, because a string slice is already a valid UTF-8 string
slice, and we don’t have to think about the Unicode monster.

fn match_literal(expected: &'static str)
    -> impl Fn(&str) -> Result<(&str, ()), &str>
    move |input| match input.get(0..expected.len()) {
        Some(next) if next == expected => {
            Ok((&input[expected.len()..], ()))
        _ => Err(input),

Now this looks a bit different.

First of all, let’s look at the types. Instead of our function looking like a
parser, now it takes our expected string as an argument, and returns
something that looks like a parser. It’s a function that returns a function – in
other words, a higher order function. Basically, we’re writing a function that
makes a function like our the_letter_a function from before.

So, instead of doing the work in the function body, we return a closure that
does the work, and that matches our type signature for a parser from previously.

The pattern match looks the same, except we can’t match on our string literal
directly because we don’t know what it is specifically, so we use a match
condition if next == expected instead. Otherwise it’s exactly the same as
before, it’s just inside the body of a closure.

Testing Our Parser #

Let’s write a test for this to make sure we got it right.

fn literal_parser() {
    let parse_joe = match_literal("Hello Joe!");
        Ok(("", ())),
        parse_joe("Hello Joe!")
        Ok((" Hello Robert!", ())),
        parse_joe("Hello Joe! Hello Robert!")
        Err("Hello Mike!"),
        parse_joe("Hello Mike!")

First, we build the parser: match_literal("Hello Joe!"). This should consume
the string "Hello Joe!" and return the remainder of the string, or it should
fail and return the whole string.

In the first case, we just feed it the exact string it expects, and we see that
it returns an empty string and the () value that means “we parsed the expected
string and you don’t really need it returned back to you.”

In the second, we feed it the string "Hello Joe! Hello Robert!", and we see
that it does indeed consume the string "Hello Joe!" and returns the remainder
of the input: " Hello Robert!" (leading space and all).

In the third, we feed it some incorrect input, "Hello Mike!", and note that it
does indeed reject the input with an error. Not that Mike is incorrect as a
general rule, he’s just not what this parser was looking for.

A Parser For Something Less Specific #

So that lets us parse <, >, = and even </ and />. We’re practically
done already!

The next bit after the opening < is the element name. We can’t do this with a
simple string comparison. But we could do it with a regular expression…

…but let’s restrain ourselves. It’s going to be a regular expression that
would be very easy to replicate in simple code, and we don’t really need to pull
in the regex crate just for this. Let’s see if we can write our own parser for
this using nothing but Rust’s standard library.

Recalling the rule for the element name identifier, it’s as follows: one
alphabetical character, followed by zero or more of either an alphabetical
character, a number, or a dash -.

fn identifier(input: &str) -> Result<(&str, String), &str> {
    let mut matched = String::new();
    let mut chars = input.chars();

    match chars.next() {
        Some(next) if next.is_alphabetic() => matched.push(next),
        _ => return Err(input),

    while let Some(next) = chars.next() {
        if next.is_alphanumeric() || next == '-' {
        } else {

    let next_index = matched.len();
    Ok((&input[next_index..], matched))

As always, we look at the type first. This time we’re not writing a function to
build a parser, we’re just writing the parser itself, like our first time. The
notable difference here is that instead of a result type of (), we’re
returning a String in the tuple along with the remaining input. This String
is going to contain the identifier we’ve just parsed.

With that in mind, first we create an empty String and call it matched. This
is going to be our result value. We also get an iterator over the characters in
input, which we’re going to start pulling apart.

The first step is to see if there’s a letter up front. We pull the first
character off the iterator and check if it’s a letter: next.is_alphabetic().
Rust’s standard library is of course here to help us with the Unicodes – this is
going to match letters in any alphabet, not just ASCII. If it’s a letter, we
push it into our matched String, and if it’s not, well, clearly we’re not
looking at an element identifier, so we return immediately with an error.

For the second step, we keep pulling characters off the iterator, pushing them
onto the String we’re building, until we find one that isn’t either
is_alphanumeric() (that’s like is_alphabetic() except it also matches
numbers in any alphabet) or a dash '-'.

The first time we see something that doesn’t match those criteria, that means
we’re done parsing, so we break out of the loop and return the String we’ve
built, remembering to slice off the bit we’ve consumed from the input.
Likewise if the iterator runs out of characters, which means we hit the end of
the input.

It’s worth noting that we don’t return with an error when we see something that
isn’t alphanumeric or a dash. We’ve already got enough to make a valid
identifier once we’ve matched that first letter, and it’s perfectly normal for
there to be more things to parse in the input string after we’ve parsed our
identifier, so we just stop parsing and return our result. It’s only if we can’t
find even that first letter that we actually return an error, because in that
case there was definitely not an identifier here.

Remember that Element struct we’re going to parse our XML document into?

struct Element {
    name: String,
    attributes: Vec<(String, String)>,
    children: Vec<Element>,

We actually just finished the parser for the first part of it, the name field.
The String our parser returns goes right in there. It’s also the right parser
for the first part of every attribute.

Let’s test that.

fn identifier_parser() {
        Ok(("", "i-am-an-identifier".to_string())),
        Ok((" entirely an identifier", "not".to_string())),
        identifier("not entirely an identifier")
        Err("!not at all an identifier"),
        identifier("!not at all an identifier")

We see that in the first case, the string "i-am-an-identifier" is parsed in
its entirety, leaving only the empty string. In the second case, the parser
returns "not" as the identifier, and the rest of the string is returned as the
remaining input. In the third case, the parser fails outright because the first
character it finds is not a letter.

Combinators #

So now we can parse the opening <, and we can parse the following identifier,
but we need to parse both, in order, to be able to make progress here. So the
next step will be to write another parser builder function, but one that takes
two parsers as input and returns a new parser which parses both of them in
order. In other words, a parser combinator, because it combines two parsers
into a new one. Let’s see if we can do that.

fn pair<P1, P2, R1, R2>(parser1: P1, parser2: P2) -> impl Fn(&str) -> Result<(&str, (R1, R2)), &str>
    P1: Fn(&str) -> Result<(&str, R1), &str>,
    P2: Fn(&str) -> Result<(&str, R2), &str>,
    move |input| match parser1(input) {
        Ok((next_input, result1)) => match parser2(next_input) {
            Ok((final_input, result2)) => Ok((final_input, (result1, result2))),
            Err(err) => Err(err),
        Err(err) => Err(err),

It’s getting slightly complicated here, but you know what to do: start by
looking at the types.

First of all, we have four type variables: P1, P2, R1 and R2. That’s
Parser 1, Parser 2, Result 1 and Result 2. P1 and P2 are functions, and
you’ll notice that they follow the well established pattern of parser functions:
just like the return value, they take a &str as input and return a Result of
a pair of the remaining input and the result, or an error.

But look at the result types of each function: P1 is a parser that produces an
R1 if successful, and P2 likewise produces an R2. And the result of the
final parser – the one returned from our function – is (R1, R2). So the job of
this parser is to first run the parser P1 on the input, keep its result, then
run P2 on the input that P1 returned, and if both of those worked out, we
combine the two results into a tuple (R1, R2).

Looking at the code, we see that this is exactly what it does, too. We start by
running the first parser on the input, then the second parser, then we combine
the two results into a tuple and return that. If either of those parsers fail,
we return immediately with the error it gave.

This way, we should be able to combine our two parsers from before,
match_literal and identifier, to actually parse the first bit of our first
XML tag. Let’s write a test to see if it works.

fn pair_combinator() {
    let tag_opener = pair(match_literal("<"), identifier);
        Ok(("/>", ((), "my-first-element".to_string()))),
    assert_eq!(Err("oops"), tag_opener("oops"));
    assert_eq!(Err("!oops"), tag_opener("<!oops"));

It seems to work! But look at that result type: ((), String). It’s obvious
that we only care about the right hand value here, the String. This is going
to be the case rather a lot – some of our parsers only match patterns in the
input without producing values, and so their outputs can be safely ignored. To
accommodate this pattern, we’re going to use our pair combinator to write two
other combinators: left, which discards the result of the first parser and
only returns the second, and its opposite number, right, which is the one we’d
have wanted to use in our test above instead of pair – the one that discards
that () on the left hand side of the pair and only keeps our String.

Enter The Functor #

But before we go that far, let’s introduce another combinator that’s going to
make writing these two a lot simpler: map.

This combinator has one purpose: to change the type of the result. For instance,
let’s say you have a parser that returns ((), String) and you wanted to change
it to return just that String, you know, just as an arbitrary example.

To do that, we pass it a function that knows how to convert from the original
type to the new one. In our example, that’s easy: |(_left, right)| right. More
generalised, it would look like Fn(A) -> B where A is the original result
type of the parser and B is the new one.

fn map<P, F, A, B>(parser: P, map_fn: F) -> impl Fn(&str) -> Result<(&str, B), &str>
    P: Fn(&str) -> Result<(&str, A), &str>,
    F: Fn(A) -> B,
    move |input| match parser(input) {
        Ok((next_input, result)) => Ok((next_input, map_fn(result))),
        Err(err) => Err(err),

And what do the types say? P is our parser. It returns A on success. F is
the function we’re going to use to map P into our return value, which looks
the same as P except its result type is B instead of A.

In the code, we run parser(input) and, if it succeeds, we take the result
and run our function map_fn(result) on it, turning the A into a B, and
that’s our converted parser done.

Actually, let’s indulge ourselves and shorten this function a bit, because this
map thing turns out to be a common pattern that Result actually implements

fn map<P, F, A, B>(parser: P, map_fn: F) -> impl Fn(&str) -> Result<(&str, B), &str>
    P: Fn(&str) -> Result<(&str, A), &str>,
    F: Fn(A) -> B,
    move |input|
            .map(|(next_input, result)| (next_input, map_fn(result)))

This pattern is what’s called a “functor” in Haskell and its mathematical
sibling, category theory. If you’ve got a thing with a type A in it, and you
have a map function available that you can pass a function from A to B
into to turn it into the same kind of thing but with the type B in it instead,
that’s a functor. You see this a lot of places in Rust, such as in
and even
without it being explicitly named as such. And there’s a good reason for that:
you can’t really express a functor as a generalised thing in Rust’s type system,
because it lacks higher kinded types, but that’s another story, so let’s just
note that these are functors, and you just need to look for the map function
to spot one.

Time For A Trait #

You might have noticed by now that we keep repeating the shape of the parser
type signature: Fn(&str) -> Result<(&str, Output), &str>. You may be getting
as sick of reading it written out full like that as I’m getting of writing it,
so I think it’s time to introduce a trait, to make things a little more
readable, and to let us add some extensibility to our parsers.

But first of all, let’s make a type alias for that return type we keep using:

type ParseResult<'a, Output> = Result<(&'a str, Output), &'a str>;

So that now, instead of typing that monstrosity out all the time, we can just
type ParseResult<String> or similar. We’ve added a lifetime there, because the
type declaration requires it, but a lot of the time the Rust compiler should be
able to infer it for you. As a rule, try leaving the lifetime out and see if
rustc gets upset, then just put it in if it does.

The lifetime 'a, in this case, refers specifically to the lifetime of the

Now, for the trait. We need to put the lifetime in here as well, and when you’re
using the trait the lifetime is usually always required. It’s a bit of extra
typing, but it beats the previous version.

trait Parser<'a, Output> {
    fn parse(&self, input: &'a str) -> ParseResult<'a, Output>;

It has just the one method, for now: the parse() method, which should look
familiar: it’s the same as the parser function we’ve been writing.

To make this even easier, we can actually implement this trait for any function
that matches the signature of a parser:

impl<'a, F, Output> Parser<'a, Output> for F
    F: Fn(&'a str) -> ParseResult<Output>,
    fn parse(&self, input: &'a str) -> ParseResult<'a, Output> {

This way, not only can we pass around the same functions we’ve been passing
around so far as parsers fully implementing the Parser trait, we also open up
the possibility to use other kinds of types as parsers.

But, more importantly, it saves us from having to type out those function
signatures all the time. Let’s rewrite the map function to see how it works

fn map<'a, P, F, A, B>(parser: P, map_fn: F) -> impl Parser<'a, B>
    P: Parser<'a, A>,
    F: Fn(A) -> B,
    move |input|
            .map(|(next_input, result)| (next_input, map_fn(result)))

One thing to note here in particular: instead of calling the parser as a
function directly, we now have to go parser.parse(input), because we don’t
know if the type P is a function, we just knows that it implements Parser,
and so we have to stick with the interface Parser provides. Otherwise, the
function body looks exactly the same, and the types look a lot tidier. There’s
the new lifetime 'a' for some extra noise, but overall it’s quite an

If we rewrite the pair function in the same way, it’s even more tidy now:

fn pair<'a, P1, P2, R1, R2>(parser1: P1, parser2: P2) -> impl Parser<'a, (R1, R2)>
    P1: Parser<'a, R1>,
    P2: Parser<'a, R2>,
    move |input| match parser1.parse(input) {
        Ok((next_input, result1)) => match parser2.parse(next_input) {
            Ok((final_input, result2)) => Ok((final_input, (result1, result2))),
            Err(err) => Err(err),
        Err(err) => Err(err),

Same thing here: the only changes are the tidied up type signatures and the need
to go parser.parse(input) instead of parser(input).

Actually, let’s tidy up pair‘s function body too, the same way we did with

fn pair<'a, P1, P2, R1, R2>(parser1: P1, parser2: P2) -> impl Parser<'a, (R1, R2)>
    P1: Parser<'a, R1>,
    P2: Parser<'a, R2>,
    move |input| {
        parser1.parse(input).and_then(|(next_input, result1)| {
                .map(|(last_input, result2)| (last_input, (result1, result2)))

The and_then method on Result is similar to map, except that the mapping
function doesn’t return the new value to go inside the Result, but a new
Result altogether. The code above is identical in effect to the previous
version written out with all those match blocks. We’re going to get back to
and_then later, but in the here and now, let’s actually get those left and
right combinators implemented, now that we have a nice and tidy map.

Left And Right #

With pair and map in place, we can write left and right very succinctly:

fn left<'a, P1, P2, R1, R2>(parser1: P1, parser2: P2) -> impl Parser<'a, R1>
    P1: Parser<'a, R1>,
    P2: Parser<'a, R2>,
    map(pair(parser1, parser2), |(left, _right)| left)

fn right<'a, P1, P2, R1, R2>(parser1: P1, parser2: P2) -> impl Parser<'a, R2>
    P1: Parser<'a, R1>,
    P2: Parser<'a, R2>,
    map(pair(parser1, parser2), |(_left, right)| right)

We use the pair combinator to combine the two parsers into a parser for a
tuple of their results, and then we use the map combinator to select just the
part of the tuple we want to keep.

Rewriting our test for the first two pieces of our element tag, it’s now just a
little bit cleaner, and in the process we’ve gained some important new parser
combinator powers.

We have to update our two parsers to use Parser and ParseResult first,
though. match_literal is the more complicated one:

fn match_literal<'a>(expected: &'static str) -> impl Parser<'a, ()> {
    move |input: &'a str| match input.get(0..expected.len()) {
        Some(next) if next == expected => Ok((&input[expected.len()..], ())),
        _ => Err(input),

In addition to changing the return type, we also have to make sure the input
type on the closure is &'a str, or rustc gets upset.

For identifier, just change the return type and you’re done, inference takes
care of the lifetimes for you:

fn identifier(input: &str) -> ParseResult<String> {

And now the test, satisfyingly absent that ungainly () in the result.

fn right_combinator() {
    let tag_opener = right(match_literal("<"), identifier);
        Ok(("/>", "my-first-element".to_string())),
    assert_eq!(Err("oops"), tag_opener.parse("oops"));
    assert_eq!(Err("!oops"), tag_opener.parse("<!oops"));

One Or More #

Let’s continue parsing that element tag. We’ve got the opening <, and we’ve
got the identifier. What’s next? That should be our first attribute pair.

No, actually, those attributes are optional. We’re going to have to find a way
to deal with things being optional.

No, wait, hold on, there’s actually something we have to deal with even before
we get as far as the first optional attribute pair: whitespace.

Between the end of the element name and the start of the first attribute name
(if there is one), there’s a space. We need to deal with that space.

It’s even worse than that – we need to deal with one or more spaces, because
<element      attribute="value"/> is valid syntax too, even if it’s a bit over
the top with the spaces. So this seems to be a good time to think about whether
we could write a combinator that expresses the idea of one or more parsers.

We’ve dealt with this already in our identifier parser, but it was all done
manually there. Not surprisingly, the code for the general idea isn’t all that

fn one_or_more<'a, P, A>(parser: P) -> impl Parser<'a, Vec<A>>
    P: Parser<'a, A>,
    move |mut input| {
        let mut result = Vec::new();

        if let Ok((next_input, first_item)) = parser.parse(input) {
            input = next_input;
        } else {
            return Err(input);

        while let Ok((next_input, next_item)) = parser.parse(input) {
            input = next_input;

        Ok((input, result))

First of all, the return type of the parser we’re building from is A, and the
return type of the combined parser is Vec<A> – any number of As.

The code does indeed look very similar to identifier. First, we parse the
first element, and if it’s not there, we return with an error. Then we parse as
many more elements as we can, until the parser fails, at which point we return
the vector with the elements we collected.

Looking at that code, how easy would it be to adapt it to the idea of zero or
more? We just need to remove that first run of the parser:

fn zero_or_more<'a, P, A>(parser: P) -> impl Parser<'a, Vec<A>>
    P: Parser<'a, A>,
    move |mut input| {
        let mut result = Vec::new();

        while let Ok((next_input, next_item)) = parser.parse(input) {
            input = next_input;

        Ok((input, result))

Let’s write some tests to make sure those two work.

fn one_or_more_combinator() {
    let parser = one_or_more(match_literal("ha"));
    assert_eq!(Ok(("", vec![(), (), ()])), parser.parse("hahaha"));
    assert_eq!(Err("ahah"), parser.parse("ahah"));
    assert_eq!(Err(""), parser.parse(""));

fn zero_or_more_combinator() {
    let parser = zero_or_more(match_literal("ha"));
    assert_eq!(Ok(("", vec![(), (), ()])), parser.parse("hahaha"));
    assert_eq!(Ok(("ahah", vec![])), parser.parse("ahah"));
    assert_eq!(Ok(("", vec![])), parser.parse(""));

Note the difference between the two: for one_or_more, finding an empty string
is an error, because it needs to see at least one case of its sub-parser, but
for zero_or_more, an empty string just means the zero case, which is not an

At this point, it’s reasonable to start thinking about ways to generalise these
two, because one is an exact copy of the other with just one bit removed. It
might be tempting to express one_or_more in terms of zero_or_more with
something like this:

fn one_or_more<'a, P, A>(parser: P) -> impl Parser<'a, Vec<A>>
    P: Parser<'a, A>,
    map(pair(parser, zero_or_more(parser)), |(head, mut tail)| {
        tail.insert(0, head);

Here, we run into Rust Problems, and I don’t even mean the problem of not having
a cons method for Vec, but I know every Lisp programmer reading that bit of
code was thinking it. No, it’s worse than that: it’s ownership.

We own that parser, so we can’t go passing it as an argument twice, the compiler
will start shouting at you that you’re trying to move an already moved value. So
can we make our combinators take references instead? No, it turns out, not
without running into another whole set of borrow checker troubles – and we’re
not going to even go there right now. And because these parsers are functions,
they don’t do anything so straightforward as to implement Clone, which would
have saved the day very tidily, so we’re stuck with a constraint that we can’t
repeat our parsers easily in combinators.

That isn’t necessarily a big problem, though. It means we can’t express
one_or_more using combinators, but it turns out those two are usually the only
combinators you need anyway which tend to reuse parsers, and, if you wanted to
get really fancy, you could write a combinator that takes a RangeBound in
addition to a parser and repeats it according to a range: range(0..) for
zero_or_more, range(1..) for one_or_more, range(5..=6) for exactly five
or six, wherever your heart takes you.

Let’s leave that as an exercise for the reader, though. Right now, we’re going
to be perfectly fine with just zero_or_more and one_or_more.

Another exercise might be to find a way around those ownership issues – maybe by
wrapping a parser in an Rc to make it clonable?

A Predicate Combinator #

We now have the building blocks we need to parse that whitespace with
one_or_more, and to parse the attribute pairs with zero_or_more.

Actually, hold on a moment. We don’t really want to parse the whitespace then
parse the attributes. If you think about it, if there are no attributes, the
whitespace is optional, and we could encounter an immediate > or />. But if
there’s an attribute, there must be whitespace first. Lucky for us, there must
also be whitespace between each attribute, if there are several, so what we’re
really looking at here is a sequence of zero or more occurrences of one or
whitespace items followed by the attribute.

We need a parser for a single item of whitespace first. We can go one of three ways here.

One, we can be silly and use our match_literal parser with a string containing
just a single space. Why is that silly? Because whitespace is also line breaks,
tabs and a whole number of strange Unicode characters which render as
whitespace. We’re going to have to lean on Rust’s standard library again, and of
course char has an is_whitespace method just like it had is_alphabetic and

Two, we can just write out a parser which consumes any number of whitespace
characters using the is_whitespace predicate much like we wrote our
identifier earlier.

Three, we can be clever, and we do like being clever. We could write a parser
any_char which returns a single char as long as there is one left in the
input, and a combinator pred which takes a parser and a predicate function,
and combine the two like this: pred(any_char, |c| c.is_whitespace()). This has
the added bonus of making it really easy to write the final parser we’re going
to need too: the quoted string for the attribute values.

The any_char parser is straightforward as a parser, but we have to remember to
be mindful of those UTF-8 gotchas.

fn any_char(input: &str) -> ParseResult<char> {
    match input.chars().next() {
        Some(next) => Ok((&input[next.len_utf8()..], next)),
        _ => Err(input),

And the pred combinator also doesn’t hold any surprises to our now seasoned
eyes. We invoke the parser, then we call our predicate function on the value if
the parser succeeded, and only if that returns true do we actually return a
success, otherwise we return as much of an error as a failed parse would.

fn pred<'a, P, A, F>(parser: P, predicate: F) -> impl Parser<'a, A>
    P: Parser<'a, A>,
    F: Fn(&A) -> bool,
    move |input| {
        if let Ok((next_input, value)) = parser.parse(input) {
            if predicate(&value) {
                return Ok((next_input, value));

And a quick test to make sure everything is in order:

fn predicate_combinator() {
    let parser = pred(any_char, |c| *c == 'o');
    assert_eq!(Ok(("mg", 'o')), parser.parse("omg"));
    assert_eq!(Err("lol"), parser.parse("lol"));

With these two in place, we can write our whitespace_char parser with a quick

fn whitespace_char<'a>() -> impl Parser<'a, char> {
    pred(any_char, |c| c.is_whitespace())

And, now that we have whitespace_char, we can also express the idea we were
heading towards, one or more whitespace, and its sister idea, zero or more
. Let’s indulge ourselves in some brevity and call them space1 and
space0 respectively.

fn space1<'a>() -> impl Parser<'a, Vec<char>> {

fn space0<'a>() -> impl Parser<'a, Vec<char>> {

Quoted Strings #

With all that sorted, can we now, at last, parse those attributes? Yes, we just
need to make sure we have all the individual parsers for the components of the
attributes. We’ve got identifier already for the attribute name (though it’s
tempting to rewrite it using any_char and pred plus our *_or_more
combinators). The = is just match_literal("="). We’re short one quoted
string parser, though, so let’s build that. Fortunately, we’ve already got all
the combinators we need to do it.

fn quoted_string<'a>() -> impl Parser<'a, String> {
                zero_or_more(pred(any_char, |c| *c != '"')),
        |chars| chars.into_iter().collect(),

The nesting of combinators is getting slightly annoying at this point, but we’re
going to resist refactoring everything to fix it just for now, and instead focus
on what’s going on here.

The outermost combinator is a map, because of the aforemenetioned annoying
nesting, and it’s a terrible place to start if we’re going to understand this
one, so let’s try and find where it really starts: the first quote character.
Inside the map, there’s a right, and the first part of the right is the
one we’re looking for: the match_literal("""). That’s our opening quote.

The second part of that right is the rest of the string. That’s inside the
left, and we quickly note that the right hand argument of that left, the
one we ignore, is the other match_literal(""") – the closing quote. So the
left hand part is our quoted string.

We take advantage of our new pred and any_char here to get a parser that
accepts anything but another quote, and we put that in zero_or_more, so that
what we’re saying is as follows:

  • one quote
  • followed by zero or more things that are not another quote
  • followed by another quote

And, between the right and the left, we discard the quotes from the result
value and get our quoted string back.

But wait, that’s not a string. Remember what zero_or_more returns? A Vec<A>
for the inner parser’s return type A. For any_char, that’s char. What
we’ve got, then, is not a string but a Vec<char>. That’s where the map comes
in: we use it to turn a Vec<char> into a String by leveraging the fact that
you can build a String from an Iterator<Item = char>, so we can just call
vec_of_chars.into_iter().collect() and, thanks to the power of type inference,
we have our String.

Let’s just write a quick test to make sure that’s all right before we go on,
because if we needed that many words to explain it, it’s probably not something
we should leave to our faith in ourselves as programmers.

fn quoted_string_parser() {
        Ok(("", "Hello Joe!".to_string())),
        quoted_string().parse(""Hello Joe!"")

So, now, finally, I swear, let’s get those attributes parsed.

At Last, Parsing Attributes #

We can now parse whitespace, identifiers, = signs and quoted strings. That,
finally, is all we need for parsing attributes.

First, let’s write a parser for an attribute pair. We’re going to be storing
them as a Vec<(String, String)>, as you may recall, so it feels like we’d need
a parser for that (String, String) to feed to our trusty zero_or_more
combinator. Let’s see if we can build one.

fn attribute_pair<'a>() -> impl Parser<'a, (String, String)> {
    pair(identifier, right(match_literal("="), quoted_string()))

Without even breaking a sweat! To summarise: we already have a handy combinator
for parsing a tuple of values, pair, so we use that with the identifier
parser, yielding a String, and a right with the = sign, whose value we
don’t want to keep, and our fresh quoted_string parser, which gets us the
other String.

Now, let’s combine that with zero_or_more to build that vector – but let’s not
forget that whitespace in between them.

fn attributes<'a>() -> impl Parser<'a, Vec<(String, String)>> {
    zero_or_more(right(space1(), attribute_pair()))

Zero or more occurrences of the following: one or more whitespace characters,
then an attribute pair. We use right to discard the whitespace and keep the
attribute pair.

Let’s test it.

fn attribute_parser() {
                ("one".to_string(), "1".to_string()),
                ("two".to_string(), "2".to_string())
        attributes().parse(" one="1" two="2"")

Tests are green! Ship it!

Actually, no, at this point in the narrative, my rustc was complaining that my
types are getting terribly complicated, and that I need to increase the max
allowed type size to carry on. It’s a good chance you’re getting the same error
at this point, and if you are, you need to know how to deal with it. Fortunatey,
in these situations, rustc generally gives good advice, so when it tells you to
add #![type_length_limit = "…some big number…"] to the top of your file,
just do as it says. Actually, just go ahead and make it #![type_length_limit = "16777216"], which is going to let us carry on a bit further into the
stratosphere of complicated types. Full steam ahead, we’re type astronauts now!

So Close Now #

At this point, things seem like they’re just about to start coming together,
which is a bit of a relief, as our types are fast approaching NP-completeness.
We just have the two versions of the element tag to deal with: the single
element and the parent element with children, but we’re feeling pretty confident
that once we have those, parsing the children will be just a matter of
zero_or_more, right?

So let’s do the single element first, deferring the question of children for a
little bit. Or, even better, let’s first write a parser for everything the two
have in common: the opening <, the element name, and the attributes. Let’s see
if we can get a result type of (String, Vec<(String, String)>) out of a couple
of combinators.

fn element_start<'a>() -> impl Parser<'a, (String, Vec<(String, String)>)> {
    right(match_literal("<"), pair(identifier, attributes()))

With that in place, we can quickly tack the tag closer on it to make a parser
for the singe element.

fn single_element<'a>() -> impl Parser<'a, Element> {
        left(element_start(), match_literal("/>")),
        |(name, attributes)| Element {
            children: vec![],

Hooray, it feels like we’re within reach of our goal – we’re actually
constructing an Element now!

Let’s test this miracle of modern technology.

fn single_element_parser() {
            Element {
                name: "div".to_string(),
                attributes: vec![("class".to_string(), "float".to_string())],
                children: vec![]
        single_element().parse("<div class="float"/>")

…and I think we just ran out of stratosphere.

The return type of single_element is so complicated that the compiler will
grind away for a very long time until it runs into the very large type size
limit we gave it earlier, asking for an even larger one. It’s clear we can no
longer ignore this problem, as it’s a rather trivial parser and a compilation
time of several minutes – maybe even several hours for the finished product –
seems mildly unreasonsable.

Before proceeding, you’d better comment out those two functions and tests while
we fix things…

To Infinity And Beyond #

If you’ve ever tried writing a recursive type in Rust, you might already know
the solution to our little problem.

A very simple example of a recursive type is a singly linked list. You can
express it, in principle, as an enum like this:

enum List<A> {
    Cons(A, List<A>),

To which rustc will, very sensibly, object that your recursive type List<A>
has an infinite size, because inside every List::<A>::Cons is another
List<A>, and that means it’s List<A>s all the way down into infinity. As far
as rustc is concerned, we’re asking for an infinite list, and we’re asking it to
be able to allocate an infinite list.

In many languages, an infinite list isn’t a problem in principle for the type
system, and it’s actually not for Rust either. The problem is that in Rust, as
mentioned, we need to be able to allocate it, or, rather, we need to be able
to determine the size of a type up front when we construct it, and when the
type is infinite, that means the size must be infinite too.

The solution is to employ a bit of indirection. Instead of our List::Cons
being an element of A and another list of A, instead we make it an element
of A and a pointer to a list of A. We know the size of a pointer, and it’s
the same no matter what it points to, and so our List::Cons now has a fixed
and predictable size no matter the size of the list. And the way to turn an
owned thing into a pointer to an owned thing on the heap, in Rust, is to Box

enum List<A> {
    Cons(A, Box<List<A>>),

Another interesting feature of Box is that the type inside it can be abstract.
This means that instead of our by now incredibly complicated parser function
types, we can let the type checker deal with a very succinct Box<dyn Parser<'a, A>> instead.

That sounds great. What’s the downside? Well, we might be losing a cycle or two
to having to follow that pointer, and it could be that the compiler loses some
opportunities to optimise our parser. But recall Knuth’s admonition about
premature optimisation: it’s going to be fine. You can afford those cycles.
You’re here to learn about parser combinators, not to learn about hand written
hyperspecialised SIMD parsers (although
they’re exciting in their own right).

So let’s proceed to implement Parser for a boxed parser function in addition
to the bare functions we’ve been using so far.

struct BoxedParser<'a, Output> {
    parser: Box<dyn Parser<'a, Output> + 'a>,

impl<'a, Output> BoxedParser<'a, Output> {
    fn new<P>(parser: P) -> Self
        P: Parser<'a, Output> + 'a,
        BoxedParser {
            parser: Box::new(parser),

impl<'a, Output> Parser<'a, Output> for BoxedParser<'a, Output> {
    fn parse(&self, input: &'a str) -> ParseResult<'a, Output> {

We create a new type BoxedParser to hold our box, for the sake of propriety.
To create a new BoxedParser from any other kind of parser (including another
BoxedParser, even if that would be pointless), we provide a function
BoxedParser::new(parser) which does nothing more than put that parser in a
Box inside our new type. Finally, we implement Parser for it, so that it can
be used interchangeably as a parser.

This leaves us with the ability to put a parser function in a Box, and the
BoxedParser will work as a Parser just as well as the function. Now, as
previously mentioned, that means moving the boxed parser to the heap and having
to deref a pointer to get to it, which can cost us several precious
, so we might actually want to hold off on boxing everything. It’s
enough to just box some of the more popular combinators.

An Opportunity Presents Itself #

But, just a moment, this presents us with an opportunity to fix another thing
that’s starting to become a bit of a bother.

Remember the last couple of parsers we wrote? Because our combinators are
standalone functions, when we nest a nontrivial number of them, our code starts
getting a little bit unreadable. Recall our quoted_string parser:

fn quoted_string<'a>() -> impl Parser<'a, String> {
                zero_or_more(pred(any_char, |c| *c != '"')),
        |chars| chars.into_iter().collect(),

It would read a lot better if we could make those combinators methods on the
parser instead of standalone functions. What if we could declare our combinators
as methods on the Parser trait?

The problem is that if we do that, we lose the ability to lean on impl Trait
for our return types, because impl Trait isn’t allowed in trait declarations.

…but now we have BoxedParser. We can’t declare a trait method that returns
impl Parser<'a, A>, but we most certainly can declare one that returns
BoxedParser<'a, A>.

The best part is that we can even declare these with default implementations, so
that we don’t have to reimplement every combinator for every type that
implements Parser.

Let’s try it out with map, by extending our Parser trait as follows:

trait Parser<'a, Output> {
    fn parse(&self, input: &'a str) -> ParseResult<'a, Output>;

    fn map<F, NewOutput>(self, map_fn: F) -> BoxedParser<'a, NewOutput>
        Self: Sized + 'a,
        Output: 'a,
        NewOutput: 'a,
        F: Fn(Output) -> NewOutput + 'a,
        BoxedParser::new(map(self, map_fn))

That’s a lot of 'as, but, alas, they’re all necessary. Luckily, we can still
reuse our old combinator functions unchanged – and, as an added bonus, not only
do we get a nicer syntax for applying them, we also get rid of the explosive
impl Trait types by boxing them up automatically.

Now we can improve our quoted_string parser slightly:

fn quoted_string<'a>() -> impl Parser<'a, String> {
            zero_or_more(pred(any_char, |c| *c != '"')),
    .map(|chars| chars.into_iter().collect())

It’s now more obvious at first glance that the .map() is being called on the
result of the right().

We could also give pair, left and right the same treatment, but in the
case of these three, I think it reads easier when they’re functions, because
they mirror the structure of pair‘s output type. If you disagree, it’s
entirely possible to add them to the trait just like we did with map, and
you’re very welcome to go ahead and try it out as an exercise.

Another prime candidate, though, is pred. Let’s add a definition for it to the
Parser trait:

fn pred<F>(self, pred_fn: F) -> BoxedParser<'a, Output>
    Self: Sized + 'a,
    Output: 'a,
    F: Fn(&Output) -> bool + 'a,
    BoxedParser::new(pred(self, pred_fn))

This lets us rewrite the line in quoted_string with the pred call like this:

zero_or_more(any_char.pred(|c| *c != '"')),

I think that reads a little nicer, and I think we’ll leave the zero_or_more as
it is too – it reads like “zero or more of any_char with the following
predicate applied,” and that sounds about right to me. Once again, you can also
go ahead and move zero_or_more and one_or_more into the trait if you prefer
to go all in.

In addition to rewriting quoted_string, let’s also fix up the map in

fn single_element<'a>() -> impl Parser<'a, Element> {
    left(element_start(), match_literal("/>")).map(|(name, attributes)| Element {
        children: vec![],

Let’s try and uncomment back element_start and the tests we commented out
earlier and see if things got better. Get that code back in the game and try
running the tests…

…and, yep, compilation time is back to normal now. You can even go ahead and
remove that type size setting at the top of your file, you’re not going to need
it any more.

And that was just from boxing two maps and a predand we got a nicer
syntax out of it!

Having Children #

Now let’s write the parser for the opening tag for a parent element. It’s almost
identical to single_element, except it ends in a > rather than a />. It’s
also followed by zero or more children and a closing tag, but first we need to
parse the actual opening tag, so let’s get that done.

fn open_element<'a>() -> impl Parser<'a, Element> {
    left(element_start(), match_literal(">")).map(|(name, attributes)| Element {
        children: vec![],

Now, how do we get those children? They’re going to be either single elements or
parent elements themselves, and there are zero or more of them, so we have our
trusty zero_or_more combinator, but what do we feed it? One thing we haven’t
dealt with yet is a multiple choice parser: something that parses either a
single element or a parent element.

To get there, we need a combinator which tries two parsers in order: if the
first parser succeeds, we’re done, we return its result and that’s it. If it
fails, instead of returning an error, instead we try the second parser on the
same input
. If that succeeds, great, and if it doesn’t, we return the error
too, as that means both our parsers have failed, and that’s an overall failure.

fn either<'a, P1, P2, A>(parser1: P1, parser2: P2) -> impl Parser<'a, A>
    P1: Parser<'a, A>,
    P2: Parser<'a, A>,
    move |input| match parser1.parse(input) {
        ok @ Ok(_) => ok,
        Err(_) => parser2.parse(input),

This allows us to declare a parser element which matches either a single
element or a parent element (and, for now, let’s just use open_element to
represent it, and we’ll deal with the children once we have element down).

fn element<'a>() -> impl Parser<'a, Element> {
    either(single_element(), open_element())

Now let’s add a parser for the closing tag. It has the interesting property of
having to match the opening tag, which means the parser has to know what the
name of the opening tag is. But that’s what function arguments are for, yes?

fn close_element<'a>(expected_name: String) -> impl Parser<'a, String> {
    right(match_literal("</"), left(identifier, match_literal(">")))
        .pred(move |name| name == &expected_name)

That pred combinator is proving really useful, isn’t it?

And now, let’s put it all together for the full parent element parser, children
and all:

fn parent_element<'a>() -> impl Parser<'a, Element> {
        left(zero_or_more(element()), close_element(…oops)),

Oops. How do we pass that argument to close_element now? I think we’re short
one final combinator.

We’re so close now. Once we’ve solved this one last problem to get
parent_element working, we should be able to replace the open_element
placeholder in the element parser with our new parent_element, and that’s
it, we have a fully working XML parser.

Remember I said we’d get back to and_then later? Well, later is here. The
combinator we need is, in fact, and_then: we need something that takes a
parser, and a function that takes the result of a parser and returns a new
parser, which we’ll then run. It’s a bit like pair, except instead of just
collecting both results in a tuple, we thread them through a function. It’s also
just how and_then works with Results and Options, except it’s a bit easier
to follow because Results and Options don’t really do anything, they’re
just things that hold some data (or not, as the case may be).

So let’s try writing an implementation for it.

fn and_then<'a, P, F, A, B, NextP>(parser: P, f: F) -> impl Parser<'a, B>
    P: Parser<'a, A>,
    NextP: Parser<'a, B>,
    F: Fn(A) -> NextP,
    move |input| match parser.parse(input) {
        Ok((next_input, result)) => f(result).parse(next_input),
        Err(err) => Err(err),

Looking at the types, there are a lot of type variables, but we know P, our
input parser, which has a result type of A. Our function F, however, where
map had a function from A to B, the crucial difference is that and_then
takes a function from A to a new parser NextP, which has a result type of
B. The final result type is B, so we can assume that whatever comes out of
our NextP will be the final result.

The code is a bit less complicated: we start by running our input parser, and if
it fails, it fails and we’re done, but if if succeeds, now we call our function
f on the result (of type A), and what comes out of f(result) is a new
parser, with a result type of B. We run this parser on the next bit of
input, and we return the result directly. If it fails, it fails there, and if it
succeeds, we have our value of type B.

One more time: we run our parser of type P first, and if it succeeds, we call
the function f with the result of parser P to get our next parser of type
NextP, which we then run, and that’s the final result.

Let’s also add it straight away to the Parser trait, because this one, like
map, is definitely going to read better that way.

fn and_then<F, NextParser, NewOutput>(self, f: F) -> BoxedParser<'a, NewOutput>
    Self: Sized + 'a,
    Output: 'a,
    NewOutput: 'a,
    NextParser: Parser<'a, NewOutput> + 'a,
    F: Fn(Output) -> NextParser + 'a,
    BoxedParser::new(and_then(self, f))

OK, now, what’s it good for?

First of all, we can almost implement pair using it:

fn pair<'a, P1, P2, R1, R2>(parser1: P1, parser2: P2) -> impl Parser<'a, (R1, R2)>
    P1: Parser<'a, R1> + 'a,
    P2: Parser<'a, R2> + 'a,
    R1: 'a + Clone,
    R2: 'a,
    parser1.and_then(move |result1| parser2.map(move |result2| (result1.clone(), result2)))

It looks very neat, but there’s a problem: parser2.map() consumes parser2 to
create the wrapped parser, and the function is a Fn, not a FnOnce, so it’s
not allowed to consume parser2, just take a reference to it. Rust Problems, in
other words. In a higher level language where these things aren’t an issue, this
would have been a really neat way to define pair.

What we can do with it even in Rust, though, is use that function to lazily
generate the right version of our close_element parser, or, in other words, we
can get it to pass that argument into it.

Recalling our failed attempt:

fn parent_element<'a>() -> impl Parser<'a, Element> {
        left(zero_or_more(element()), close_element(…oops)),

Using and_then, we can now get this right by using that function to build the
right version of close_element on the spot.

fn parent_element<'a>() -> impl Parser<'a, Element> {
    open_element().and_then(|el| {
        left(zero_or_more(element()), close_element(el.name.clone())).map(move |children| {
            let mut el = el.clone();
            el.children = children;

It looks a bit more complicated now, because the and_then has to go on
open_element(), where we find out the name that goes into close_element.
This means that the rest of the parser after open_element all has to be
constructed inside the and_then closure. Moreover, because that closure is now
the sole recipient of the Element result from open_element, the parser we
return also has to carry that info forward.

The inner closure, which we map over the generated parser, has a reference to
the Element (el) from the outer closure. We have to clone() it because
we’re in a Fn and thus only have a reference to it. We take the result of the
inner parser (our Vec<Element> of children) and add that to our cloned
Element, and we return that as our final result.

All we need to do now is go back to our element parser and make sure we change
open_element to parent_element, so it parses the whole element structure
instead of just the start of it, and I believe we’re done!

Are You Going To Say The M Word Or Do I Have To? #

Remember we talked about how the map pattern is called a “functor” on Planet

The and_then pattern is another thing you see a lot in Rust, in generally the
same places as map. It’s called
on Iterator, but it’s the same pattern as the rest.

The fancy word for it is “monad.” If you’ve got a thing Thing<A>, and you have
an and_then function available that you can pass a function from A to
Thing<B> into, so that now you have a new Thing<B> instead, that’s a monad.

The function might get called instantly, like when you have an Option<A>, we
already know if it’s a Some(A) or a None, so we apply the function directly
if it’s a Some(A), giving us a Some(B).

It might also be called lazily. For instance, if you have a Future<A> that is
still waiting to resolve, instead of and_then immediately calling the function
to create a Future<B>, instead it creates a new Future<B> which contains
both the Future<A> and the function, and which then waits for Future<A> to
finish. When it does, it calls the function with the result of the Future<A>,
and Bob’s your uncle1, you get your Future<B> back.
In other words, in the case of a Future you can think of the function you pass
to and_then as a callback function, because it gets called with the result
of the original future when it completes. It’s also a little more interesting
than that, because it returns a new Future, which may or may not have
already been resolved, so it’s a way to chain futures together.

As with functors, though, Rust’s type system isn’t currently capable of
expressing monads, so let’s only note that this pattern is called a monad, and
that, rather disappointingly, it’s got nothing at all to do with burritos,
contrary to what they say on the internets, and move on.

Whitespace, Redux #

Just one last thing.

We should have a parser capable of parsing some XML now, but it’s not very
appreciative of whitespace. Arbitrary whitespace should be allowed between tags,
so that we’re free to insert line breaks and such between our tags (and
whitespace should in principle be allowed between identifiers and literals, like
< div / >, but let’s skip that).

We should be able to put together a quick combinator for that with no effort at
this point.

fn whitespace_wrap<'a, P, A>(parser: P) -> impl Parser<'a, A>
    P: Parser<'a, A>,
    right(space0(), left(parser, space0()))

If we wrap element in that, it will ignore all leading and trailing whitespace
around element, which means we’re free to use as many line breaks and as much
indentation as we like.

fn element<'a>() -> impl Parser<'a, Element> {
    whitespace_wrap(either(single_element(), parent_element()))

We’re Finally There! #

I think we did it! Let’s write an integration test to celebrate.

fn xml_parser() {
    let doc = r#"
        <top label="Top">
            <semi-bottom label="Bottom"/>
                <bottom label="Another bottom"/>
    let parsed_doc = Element {
        name: "top".to_string(),
        attributes: vec![("label".to_string(), "Top".to_string())],
        children: vec![
            Element {
                name: "semi-bottom".to_string(),
                attributes: vec![("label".to_string(), "Bottom".to_string())],
                children: vec![],
            Element {
                name: "middle".to_string(),
                attributes: vec![],
                children: vec![Element {
                    name: "bottom".to_string(),
                    attributes: vec![("label".to_string(), "Another bottom".to_string())],
                    children: vec![],
    assert_eq!(Ok(("", parsed_doc)), element().parse(doc));

And one that fails because of a mismatched closing tag, just to make sure we got
that bit right:

fn mismatched_closing_tag() {
    let doc = r#"
    assert_eq!(Err("</middle>"), element().parse(doc));

The good news is that it returns the mismatched closing tag as the error. The
bad news is that it doesn’t actually say that the problem is a mismatched
closing tag, just where the error is. It’s better than nothing, but, honestly,
as error messages go, it’s still terrible. But turning this into a thing that
actually gives good errors is the topic for another, and probably at least as
long, article.

Let’s focus on the good news: we wrote a parser from scratch using parser
combinators! We know that a parser forms both a functor and a monad, so you can
now impress people at parties with your daunting knowledge of category

Most importantly, we now know how parser combinators work from the ground up.
Nobody can stop us now!

Victory Puppies #

Further Resources #

First of all, I’m guilty of explaining monads to you in strictly Rusty terms, and
I know that Phil Wadler would be very upset with me if I didn’t point you
towards his seminal

which goes into much more exciting detail about them – including how they relate
to parser combinators.

The ideas in this article are extremely similar to the ideas behind the
pom parser combinator library, and if this has
made you want to work with parser combinators in the same style, I can highly
recommend it.

The state of the art in Rust parser combinators is still
nom, to the extent that the aforementioned
pom is clearly derivatively named (and there’s no higher praise than that),
but it takes a very different approach from what we’ve built here today.

Another popular parser combinator library for Rust is
combine, which may be worth a look as

The seminal parser combinator library for Haskell is

Finally, I owe my first awareness of parser combinators to the book
Programming in Haskell by Graham
Hutton, which is a great read and has the positive side effect of also teaching
you Haskell.

Licence #

This work is copyright Bodil Stokke and is licensed under the Creative Commons
Attribution-NonCommercial-ShareAlike 4.0 International Licence. To view a copy
of this licence, visit http://creativecommons.org/licenses/by-nc-sa/4.0/.

1: He isn’t really your uncle.

2: Please don’t be that person at parties.

Leave a Reply

Your email address will not be published. Required fields are marked *

Next Post

Ask a Pro: What is Suspension Trauma (aka Harness Hang Syndrome)?

Fri Apr 19 , 2019

You May Like