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4.7. 오류 처리 (Error Handling) - 4%

수많은 프로그래밍 언어들이 그렇듯, 러스트는 프로그래머가 오류를 처리할 수 있는 방법을 제공합니다. 일반적으로 말하길, 오류 처리는 크게 두가지 분류로 나뉜다고 일커집니다: 첫쩨, 예외와 변수 리턴. 둘째, 변수 리턴을 위한 러스트 OPT

이 쳅터에서는, 러스트에서 오류들을 처리하는 포괄적인 처리 방법에 대해 다루고자합니다. 또한, 오류를 다루는 것을 한 번에 한 조각씩 소개하고자합니다. 그래야만 모든 조각들이 어떻게 딱 들어맞는지에 대한 튼튼한 기반 지식을 가질 수 있기 때문입니다.
In this chapter, we intend to provide a comprehensive treatment of how to deal
with errors in Rust. More than that, we will attempt to introduce error handling
one piece at a time so that you'll come away with a solid working knowledge of
how everything fits together.

순진하게 하자면, 러스트의 오류 처리 방법은 수다스럽고 짜증날 수 있습니다. 이번 챕터는 우연히 마주치는 블록들을 탐험하고 정규 라이브러리를 가지고 어떻게 오류를 간결하고 인체공학적으로 다룰 수 있을지 설명하겠습니다.
When done naïvely, error handling in Rust can be verbose and annoying. This
chapter will explore those stumbling blocks and demonstrate how to use the
standard library to make error handling concise and ergonomic.

이번 챕터는 매우 깁니다. 대체로 우리는 sum types와 combinators들의 완전 처음부터 시작하고 있고, 러스트가 점진적으로 오류를 처리하도록 시키도록 시도하려고 하기 때문입니다. 따라서, 다른 표현적인 타입 시스템에 대한 경험이 있는 프로그래머들은 그냥 뛰어넘어버리고 싶을지도 모르겠네요.
This chapter is very long, mostly because we start at the very beginning with
sum types and combinators, and try to motivate the way Rust does error handling
incrementally. As such, programmers with experience in other expressive type
systems may want to jump around.

The Basics
Working with multiple error types
Standard library traits used for error handling
Case study: A program to read population data
The short story

기본

당신은 오류 처리를 상태 분석을 사용해서 연산이 성공적이었는지 아니었는지 판단하는 것이라고 생각해도 좋습니다. 앞으로 보겠지만, 인체공학적 오류 처리란 프로그래머가 계속 신경써야만 하는 명시적인 상태 분석을 줄이면서도 코드를 조립가능하게 유지하는 것을 의미합니다.
You can think of error handling as using case analysis to determine whether
a computation was successful or not. As you will see, the key to ergonomic error
handling is reducing the amount of explicit case analysis the programmer has to
do while keeping code composable.

코드를 조립가능하게 유지하는 것은 중요합니다. 그렇지않으면 기대치않은 어떤 것을 만날 때마다 <code>패닉</code>을 사용할 수도 있습니다. (패닉은 현재 작업을 되돌리고, 그리고 대부분의 경우, 프로그램 전체를 강제중단시킵니다.) 아래에 예시가 있습니다.
Keeping code composable is important, because without that requirement, we
could <code>panic</code> whenever we
come across something unexpected. (panic causes the current task to unwind,
and in most cases, the entire program aborts.) Here's an example:

// 1에서 10 사이의 수 하나를 예측합니다.
// 만일 그 수가 생각한 수가 맞으면 true를 반환하고, 그렇지 않으면 false를 반환합니다.
// Guess a number between 1 and 10.
// If it matches the number we had in mind, return true. Else, return false.
fn guess(n: i32) -> bool {
    if n < 1 || n > 10 {
        panic!("Invalid number: {}", n);
    }
    n == 5
}

fn main() {
    guess(11);
}

이 코드를 실행하려고 하면, 프로그램은 강제종료되면서 다음 메시지를 출력합니다.
If you try running this code, the program will crash with a message like this:

thread '<main>' panicked at 'Invalid number: 11', src/bin/panic-simple.rs:5

또 한가지 덜 억지스러운 예를 들어보겠습니다. 정수를 매개변수로 받아서 두배로 출력하는 프로그램이 있습니다.
Here's another example that is slightly less contrived. A program that accepts
an integer as an argument, doubles it and prints it.

use std::env;

fn main() {
    let mut argv = env::args();
    let arg: String = argv.nth(1).unwrap(); // error 1
    let n: i32 = arg.parse().unwrap(); // error 2
    println!("{}", 2 * n);
}

If you give this program zero arguments (error 1) or if the first argument
isn't an integer (error 2), the program will panic just like in the first
example.

You can think of this style of error handling as similar to a bull running
through a china shop. The bull will get to where it wants to go, but it will
trample everything in the process.

Unwrapping explained

In the previous example, we claimed
that the program would simply panic if it reached one of the two error
conditions, yet, the program does not include an explicit call to panic like
the first example. This is because the
panic is embedded in the calls to unwrap.

To “unwrap” something in Rust is to say, “Give me the result of the
computation, and if there was an error, just panic and stop the program.”
It would be better if we just showed the code for unwrapping because it is so
simple, but to do that, we will first need to explore the Option and Result
types. Both of these types have a method called unwrap defined on them.

`Option` 형식

The Option type is
defined in the standard library:

enum Option<T> {
    None,
    Some(T),
}

The Option type is a way to use Rust's type system to express the
possibility of absence. Encoding the possibility of absence into the type
system is an important concept because it will cause the compiler to force the
programmer to handle that absence. Let's take a look at an example that tries
to find a character in a string:

// Searches `haystack` for the Unicode character `needle`. If one is found, the
// byte offset of the character is returned. Otherwise, `None` is returned.
fn find(haystack: &str, needle: char) -> Option<usize> {
    for (offset, c) in haystack.char_indices() {
        if c == needle {
            return Some(offset);
        }
    }
    None
}

Notice that when this function finds a matching character, it doen't just
return the offset. Instead, it returns Some(offset). Some is a variant or
a value constructor for the Option type. You can think of it as a function
with the type fn<T>(value: T) -> Option<T>. Correspondingly, None is also a
value constructor, except it has no arguments. You can think of None as a
function with the type fn<T>() -> Option<T>.

This might seem like much ado about nothing, but this is only half of the
story. The other half is using the find function we've written. Let's try
to use it to find the extension in a file name.

# fn find(_: &str, _: char) -> Option<usize> { None }
fn main() {
    let file_name = "foobar.rs";
    match find(file_name, '.') {
        None => println!("No file extension found."),
        Some(i) => println!("File extension: {}", &file_name[i+1..]),
    }
}

This code uses pattern matching to do case
analysis on the Option<usize> returned by the find function. In fact, case
analysis is the only way to get at the value stored inside an Option<T>. This
means that you, as the programmer, must handle the case when an Option<T> is
None instead of Some(t).

But wait, what about unwrap used in <code>unwrap-double</code>?
There was no case analysis there! Instead, the case analysis was put inside the
unwrap method for you. You could define it yourself if you want:

enum Option<T> {
    None,
    Some(T),
}

impl<T> Option<T> {
    fn unwrap(self) -> T {
        match self {
            Option::Some(val) => val,
            Option::None =>
              panic!("called `Option::unwrap()` on a `None` value"),
        }
    }
}

The unwrap method abstracts away the case analysis. This is precisely the thing
that makes unwrap ergonomic to use. Unfortunately, that panic! means that
unwrap is not composable: it is the bull in the china shop.

`Option<T>` 변수들을 사용하기

In <code>option-ex-string-find</code>
we saw how to use find to discover the extension in a file name. Of course,
not all file names have a . in them, so it's possible that the file name has
no extension. This possibility of absence is encoded into the types using
Option<T>. In other words, the compiler will force us to address the
possibility that an extension does not exist. In our case, we just print out a
message saying as such.

Getting the extension of a file name is a pretty common operation, so it makes
sense to put it into a function:

# fn find(_: &str, _: char) -> Option<usize> { None }
// Returns the extension of the given file name, where the extension is defined
// as all characters proceding the first `.`.
// If `file_name` has no `.`, then `None` is returned.
fn extension_explicit(file_name: &str) -> Option<&str> {
    match find(file_name, '.') {
        None => None,
        Some(i) => Some(&file_name[i+1..]),
    }
}

(Pro-tip: don't use this code. Use the
<code>extension</code>
method in the standard library instead.)

The code stays simple, but the important thing to notice is that the type of
find forces us to consider the possibility of absence. This is a good thing
because it means the compiler won't let us accidentally forget about the case
where a file name doesn't have an extension. On the other hand, doing explicit
case analysis like we've done in extension_explicit every time can get a bit
tiresome.

In fact, the case analysis in extension_explicit follows a very common
pattern: map a function on to the value inside of an Option<T>, unless the
option is None, in which case, just return None.

Rust has parametric polymorphism, so it is very easy to define a combinator
that abstracts this pattern:

fn map<F, T, A>(option: Option<T>, f: F) -> Option<A> where F: FnOnce(T) -> A {
    match option {
        None => None,
        Some(value) => Some(f(value)),
    }
}

Indeed, map is defined as a method on Option<T> in the standard library.

Armed with our new combinator, we can rewrite our extension_explicit method
to get rid of the case analysis:

# fn find(_: &str, _: char) -> Option<usize> { None }
// Returns the extension of the given file name, where the extension is defined
// as all characters proceding the first `.`.
// If `file_name` has no `.`, then `None` is returned.
fn extension(file_name: &str) -> Option<&str> {
    find(file_name, '.').map(|i| &file_name[i+1..])
}

One other pattern that we find is very common is assigning a default value to
the case when an Option value is None. For example, maybe your program
assumes that the extension of a file is rs even if none is present. As you
might imagine, the case analysis for this is not specific to file
extensions - it can work with any Option<T>:

fn unwrap_or<T>(option: Option<T>, default: T) -> T {
    match option {
        None => default,
        Some(value) => value,
    }
}

The trick here is that the default value must have the same type as the value
that might be inside the Option<T>. Using it is dead simple in our case:

# fn find(haystack: &str, needle: char) -> Option<usize> {
#     for (offset, c) in haystack.char_indices() {
#         if c == needle {
#             return Some(offset);
#         }
#     }
#     None
# }
#
# fn extension(file_name: &str) -> Option<&str> {
#     find(file_name, '.').map(|i| &file_name[i+1..])
# }
fn main() {
    assert_eq!(extension("foobar.csv").unwrap_or("rs"), "csv");
    assert_eq!(extension("foobar").unwrap_or("rs"), "rs");
}

(Note that unwrap_or is defined as a method on Option<T> in the
standard library, so we use that here instead of the free-standing function we
defined above. Don't forget to check out the more general <code>unwrap_or_else</code>
method.)

There is one more combinator that we think is worth paying special attention to:
and_then. It makes it easy to compose distinct computations that admit the
possibility of absence. For example, much of the code in this section is
about finding an extension given a file name. In order to do this, you first
need the file name which is typically extracted from a file path. While most
file paths have a file name, not all of them do. For example, ., .. or
/.

So, we are tasked with the challenge of finding an extension given a file
path. Let's start with explicit case analysis:

# fn extension(file_name: &str) -> Option<&str> { None }
fn file_path_ext_explicit(file_path: &str) -> Option<&str> {
    match file_name(file_path) {
        None => None,
        Some(name) => match extension(name) {
            None => None,
            Some(ext) => Some(ext),
        }
    }
}

fn file_name(file_path: &str) -> Option<&str> {
  // implementation elided
  unimplemented!()
}

You might think that we could just use the map combinator to reduce the case
analysis, but its type doesn't quite fit. Namely, map takes a function that
does something only with the inner value. The result of that function is then
always rewrapped with <code>Some</code>. Instead, we need something
like map, but which allows the caller to return another Option. Its generic
implementation is even simpler than map:

fn and_then<F, T, A>(option: Option<T>, f: F) -> Option<A>
        where F: FnOnce(T) -> Option<A> {
    match option {
        None => None,
        Some(value) => f(value),
    }
}

Now we can rewrite our file_path_ext function without explicit case analysis:

# fn extension(file_name: &str) -> Option<&str> { None }
# fn file_name(file_path: &str) -> Option<&str> { None }
fn file_path_ext(file_path: &str) -> Option<&str> {
    file_name(file_path).and_then(extension)
}

The Option type has many other combinators defined in the standard
library. It is a good idea to skim this list and familiarize
yourself with what's available—they can often reduce case analysis
for you. Familiarizing yourself with these combinators will pay
dividends because many of them are also defined (with similar
semantics) for Result, which we will talk about next.

Combinators make using types like Option ergonomic because they reduce
explicit case analysis. They are also composable because they permit the caller
to handle the possibility of absence in their own way. Methods like unwrap
remove choices because they will panic if Option<T> is None.

`Result` 형식

The Result type is also
defined in the standard library:

enum Result<T, E> {
    Ok(T),
    Err(E),
}

The Result type is a richer version of Option. Instead of expressing the
possibility of absence like Option does, Result expresses the possibility
of error. Usually, the error is used to explain why the result of some
computation failed. This is a strictly more general form of Option. Consider
the following type alias, which is semantically equivalent to the real
Option<T> in every way:

type Option<T> = Result<T, ()>;

This fixes the second type parameter of Result to always be () (pronounced
“unit” or “empty tuple”). Exactly one value inhabits the () type: (). (Yup,
the type and value level terms have the same notation!)

The Result type is a way of representing one of two possible outcomes in a
computation. By convention, one outcome is meant to be expected or “Ok” while
the other outcome is meant to be unexpected or “Err”.

Just like Option, the Result type also has an
<code>unwrap</code> method
defined
in the standard library. Let's define it:

# enum Result<T, E> { Ok(T), Err(E) }
impl<T, E: ::std::fmt::Debug> Result<T, E> {
    fn unwrap(self) -> T {
        match self {
            Result::Ok(val) => val,
            Result::Err(err) =>
              panic!("called `Result::unwrap()` on an `Err` value: {:?}", err),
        }
    }
}

This is effectively the same as our definition for
<code>Option::unwrap</code>, except it includes the
error value in the panic! message. This makes debugging easier, but
it also requires us to add a <code>Debug</code> constraint on the E type
parameter (which represents our error type). Since the vast majority
of types should satisfy the Debug constraint, this tends to work out
in practice. (Debug on a type simply means that there's a reasonable
way to print a human readable description of values with that type.)

OK, let's move on to an example.

변수 파싱

The Rust standard library makes converting strings to integers dead simple.
It's so easy in fact, that it is very tempting to write something like the
following:

fn double_number(number_str: &str) -> i32 {
    2 * number_str.parse::<i32>().unwrap()
}

fn main() {
    let n: i32 = double_number("10");
    assert_eq!(n, 20);
}

At this point, you should be skeptical of calling unwrap. For example, if
the string doesn't parse as a number, you'll get a panic:

thread '<main>' panicked at 'called `Result::unwrap()` on an `Err` value: ParseIntError { kind: InvalidDigit }', /home/rustbuild/src/rust-buildbot/slave/beta-dist-rustc-linux/build/src/libcore/result.rs:729

This is rather unsightly, and if this happened inside a library you're
using, you might be understandably annoyed. Instead, we should try to
handle the error in our function and let the caller decide what to
do. This means changing the return type of double_number. But to
what? Well, that requires looking at the signature of the <code>parse</code>
method in the standard library:

impl str {
    fn parse<F: FromStr>(&self) -> Result<F, F::Err>;
}

Hmm. So we at least know that we need to use a Result. Certainly, it's
possible that this could have returned an Option. After all, a string either
parses as a number or it doesn't, right? That's certainly a reasonable way to
go, but the implementation internally distinguishes why the string didn't
parse as an integer. (Whether it's an empty string, an invalid digit, too big
or too small.) Therefore, using a Result makes sense because we want to
provide more information than simply “absence.” We want to say why the
parsing failed. You should try to emulate this line of reasoning when faced
with a choice between Option and Result. If you can provide detailed error
information, then you probably should. (We'll see more on this later.)

OK, but how do we write our return type? The parse method as defined
above is generic over all the different number types defined in the
standard library. We could (and probably should) also make our
function generic, but let's favor explicitness for the moment. We only
care about i32, so we need to find its implementation of
<code>FromStr</code> (do a CTRL-F in your browser
for “FromStr”) and look at its associated type Err. We did
this so we can find the concrete error type. In this case, it's
<code>std::num::ParseIntError</code>.
Finally, we can rewrite our function:

use std::num::ParseIntError;

fn double_number(number_str: &str) -> Result<i32, ParseIntError> {
    match number_str.parse::<i32>() {
        Ok(n) => Ok(2 * n),
        Err(err) => Err(err),
    }
}

fn main() {
    match double_number("10") {
        Ok(n) => assert_eq!(n, 20),
        Err(err) => println!("Error: {:?}", err),
    }
}

This is a little better, but now we've written a lot more code! The case
analysis has once again bitten us.

Combinators to the rescue! Just like Option, Result has lots of combinators
defined as methods. There is a large intersection of common combinators between
Result and Option. In particular, map is part of that intersection:

use std::num::ParseIntError;

fn double_number(number_str: &str) -> Result<i32, ParseIntError> {
    number_str.parse::<i32>().map(|n| 2 * n)
}

fn main() {
    match double_number("10") {
        Ok(n) => assert_eq!(n, 20),
        Err(err) => println!("Error: {:?}", err),
    }
}

The usual suspects are all there for Result, including
<code>unwrap_or</code> and
<code>and_then</code>.
Additionally, since Result has a second type parameter, there are
combinators that affect only the error type, such as
<code>map_err</code> (instead of
map) and <code>or_else</code>
(instead of and_then).

`Result` 형식의 다른 표현법

In the standard library, you may frequently see types like
Result<i32>. But wait, we defined <code>Result</code> to
have two type parameters. How can we get away with only specifying
one? The key is to define a Result type alias that fixes one of
the type parameters to a particular type. Usually the fixed type is
the error type. For example, our previous example parsing integers
could be rewritten like this:

use std::num::ParseIntError;
use std::result;

type Result<T> = result::Result<T, ParseIntError>;

fn double_number(number_str: &str) -> Result<i32> {
    unimplemented!();
}

Why would we do this? Well, if we have a lot of functions that could return
ParseIntError, then it's much more convenient to define an alias that always
uses ParseIntError so that we don't have to write it out all the time.

The most prominent place this idiom is used in the standard library is
with <code>io::Result</code>. Typically, one writes
io::Result<T>, which makes it clear that you're using the io
module's type alias instead of the plain definition from
std::result. (This idiom is also used for
<code>fmt::Result</code>.)

A brief interlude: unwrapping isn't evil

If you've been following along, you might have noticed that I've taken a pretty
hard line against calling methods like unwrap that could panic and abort
your program. Generally speaking, this is good advice.

However, unwrap can still be used judiciously. What exactly justifies use of
unwrap is somewhat of a grey area and reasonable people can disagree. I'll
summarize some of my opinions on the matter.

In examples and quick 'n' dirty code. Sometimes you're writing examples or a quick program, and error handling simply isn't important. Beating the convenience of unwrap can be hard in such scenarios, so it is very appealing.
When panicking indicates a bug in the program. When the invariants of your code should prevent a certain case from happening (like, say, popping from an empty stack), then panicking can be permissible. This is because it exposes a bug in your program. This can be explicit, like from an assert! failing, or it could be because your index into an array was out of bounds.

This is probably not an exhaustive list. Moreover, when using an
Option, it is often better to use its
<code>expect</code>
method. expect does exactly the same thing as unwrap, except it
prints a message you give to expect. This makes the resulting panic
a bit nicer to deal with, since it will show your message instead of
“called unwrap on a None value.”

My advice boils down to this: use good judgment. There's a reason why the words
“never do X” or “Y is considered harmful” don't appear in my writing. There are
trade offs to all things, and it is up to you as the programmer to determine
what is acceptable for your use cases. My goal is only to help you evaluate
trade offs as accurately as possible.

Now that we've covered the basics of error handling in Rust, and
explained unwrapping, let's start exploring more of the standard
library.

Working with multiple error types

Thus far, we've looked at error handling where everything was either an
Option<T> or a Result<T, SomeError>. But what happens when you have both an
Option and a Result? Or what if you have a Result<T, Error1> and a
Result<T, Error2>? Handling composition of distinct error types is the next
challenge in front of us, and it will be the major theme throughout the rest of
this chapter.

Composing `Option` and `Result`

So far, I've talked about combinators defined for Option and combinators
defined for Result. We can use these combinators to compose results of
different computations without doing explicit case analysis.

Of course, in real code, things aren't always as clean. Sometimes you have a
mix of Option and Result types. Must we resort to explicit case analysis,
or can we continue using combinators?

For now, let's revisit one of the first examples in this chapter:

use std::env;

fn main() {
    let mut argv = env::args();
    let arg: String = argv.nth(1).unwrap(); // error 1
    let n: i32 = arg.parse().unwrap(); // error 2
    println!("{}", 2 * n);
}

Given our new found knowledge of Option, Result and their various
combinators, we should try to rewrite this so that errors are handled properly
and the program doesn't panic if there's an error.

The tricky aspect here is that argv.nth(1) produces an Option while
arg.parse() produces a Result. These aren't directly composable. When faced
with both an Option and a Result, the solution is usually to convert the
Option to a Result. In our case, the absence of a command line parameter
(from env::args()) means the user didn't invoke the program correctly. We
could just use a String to describe the error. Let's try:

use std::env;

fn double_arg(mut argv: env::Args) -> Result<i32, String> {
    argv.nth(1)
        .ok_or("Please give at least one argument".to_owned())
        .and_then(|arg| arg.parse::<i32>().map_err(|err| err.to_string()))
}

fn main() {
    match double_arg(env::args()) {
        Ok(n) => println!("{}", n),
        Err(err) => println!("Error: {}", err),
    }
}

There are a couple new things in this example. The first is the use of the
<code>Option::ok_or</code>
combinator. This is one way to convert an Option into a Result. The
conversion requires you to specify what error to use if Option is None.
Like the other combinators we've seen, its definition is very simple:

fn ok_or<T, E>(option: Option<T>, err: E) -> Result<T, E> {
    match option {
        Some(val) => Ok(val),
        None => Err(err),
    }
}

The other new combinator used here is
<code>Result::map_err</code>.
This is just like Result::map, except it maps a function on to the error
portion of a Result value. If the Result is an Ok(...) value, then it is
returned unmodified.

We use map_err here because it is necessary for the error types to remain
the same (because of our use of and_then). Since we chose to convert the
Option<String> (from argv.nth(1)) to a Result<String, String>, we must
also convert the ParseIntError from arg.parse() to a String.

The limits of combinators

Doing IO and parsing input is a very common task, and it's one that I
personally have done a lot of in Rust. Therefore, we will use (and continue to
use) IO and various parsing routines to exemplify error handling.

Let's start simple. We are tasked with opening a file, reading all of its
contents and converting its contents to a number. Then we multiply it by 2
and print the output.

Although I've tried to convince you not to use unwrap, it can be useful
to first write your code using unwrap. It allows you to focus on your problem
instead of the error handling, and it exposes the points where proper error
handling need to occur. Let's start there so we can get a handle on the code,
and then refactor it to use better error handling.

use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> i32 {
    let mut file = File::open(file_path).unwrap(); // error 1
    let mut contents = String::new();
    file.read_to_string(&mut contents).unwrap(); // error 2
    let n: i32 = contents.trim().parse().unwrap(); // error 3
    2 * n
}

fn main() {
    let doubled = file_double("foobar");
    println!("{}", doubled);
}

(N.B. The AsRef<Path> is used because those are the
same bounds used on
<code>std::fs::File::open</code>.
This makes it ergnomic to use any kind of string as a file path.)

There are three different errors that can occur here:

A problem opening the file.
A problem reading data from the file.
A problem parsing the data as a number.

The first two problems are described via the
<code>std::io::Error</code> type. We know this
because of the return types of
<code>std::fs::File::open</code> and
<code>std::io::Read::read_to_string</code>.
(Note that they both use the <code>Result</code> type alias
idiom described previously. If you
click on the Result type, you'll see the type
alias, and consequently, the underlying
io::Error type.) The third problem is described by the
<code>std::num::ParseIntError</code>
type. The io::Error type in particular is pervasive throughout the
standard library. You will see it again and again.

Let's start the process of refactoring the file_double function. To make this
function composable with other components of the program, it should not panic
if any of the above error conditions are met. Effectively, this means that the
function should return an error if any of its operations fail. Our problem is
that the return type of file_double is i32, which does not give us any
useful way of reporting an error. Thus, we must start by changing the return
type from i32 to something else.

The first thing we need to decide: should we use Option or Result? We
certainly could use Option very easily. If any of the three errors occur, we
could simply return None. This will work and it is better than panicking,
but we can do a lot better. Instead, we should pass some detail about the error
that occurred. Since we want to express the possibility of error, we should
use Result<i32, E>. But what should E be? Since two different types of
errors can occur, we need to convert them to a common type. One such type is
String. Let's see how that impacts our code:

use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> Result<i32, String> {
    File::open(file_path)
         .map_err(|err| err.to_string())
         .and_then(|mut file| {
              let mut contents = String::new();
              file.read_to_string(&mut contents)
                  .map_err(|err| err.to_string())
                  .map(|_| contents)
         })
         .and_then(|contents| {
              contents.trim().parse::<i32>()
                      .map_err(|err| err.to_string())
         })
         .map(|n| 2 * n)
}

fn main() {
    match file_double("foobar") {
        Ok(n) => println!("{}", n),
        Err(err) => println!("Error: {}", err),
    }
}

This code looks a bit hairy. It can take quite a bit of practice before code
like this becomes easy to write. The way we write it is by following the
types. As soon as we changed the return type of file_double to
Result<i32, String>, we had to start looking for the right combinators. In
this case, we only used three different combinators: and_then, map and
map_err.

and_then is used to chain multiple computations where each computation could
return an error. After opening the file, there are two more computations that
could fail: reading from the file and parsing the contents as a number.
Correspondingly, there are two calls to and_then.

map is used to apply a function to the Ok(...) value of a Result. For
example, the very last call to map multiplies the Ok(...) value (which is
an i32) by 2. If an error had occurred before that point, this operation
would have been skipped because of how map is defined.

map_err is the trick the makes all of this work. map_err is just like
map, except it applies a function to the Err(...) value of a Result. In
this case, we want to convert all of our errors to one type: String. Since
both io::Error and num::ParseIntError implement ToString, we can call the
to_string() method to convert them.

With all of that said, the code is still hairy. Mastering use of combinators is
important, but they have their limits. Let's try a different approach: early
returns.

Early returns

I'd like to take the code from the previous section and rewrite it using early
returns. Early returns let you exit the function early. We can't return early
in file_double from inside another closure, so we'll need to revert back to
explicit case analysis.

use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> Result<i32, String> {
    let mut file = match File::open(file_path) {
        Ok(file) => file,
        Err(err) => return Err(err.to_string()),
    };
    let mut contents = String::new();
    if let Err(err) = file.read_to_string(&mut contents) {
        return Err(err.to_string());
    }
    let n: i32 = match contents.trim().parse() {
        Ok(n) => n,
        Err(err) => return Err(err.to_string()),
    };
    Ok(2 * n)
}

fn main() {
    match file_double("foobar") {
        Ok(n) => println!("{}", n),
        Err(err) => println!("Error: {}", err),
    }
}

Reasonable people can disagree over whether this code is better that the code
that uses combinators, but if you aren't familiar with the combinator approach,
this code looks simpler to read to me. It uses explicit case analysis with
match and if let. If an error occurs, it simply stops executing the
function and returns the error (by converting it to a string).

Isn't this a step backwards though? Previously, we said that the key to
ergonomic error handling is reducing explicit case analysis, yet we've reverted
back to explicit case analysis here. It turns out, there are multiple ways to
reduce explicit case analysis. Combinators aren't the only way.

The `try!` macro

A cornerstone of error handling in Rust is the try! macro. The try! macro
abstracts case analysis just like combinators, but unlike combinators, it also
abstracts control flow. Namely, it can abstract the early return pattern
seen above.

Here is a simplified definition of a try! macro:

macro_rules! try {
    ($e:expr) => (match $e {
        Ok(val) => val,
        Err(err) => return Err(err),
    });
}

(The real definition is a bit more
sophisticated. We will address that later.)

Using the try! macro makes it very easy to simplify our last example. Since
it does the case analysis and the early return for us, we get tighter code that
is easier to read:

use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> Result<i32, String> {
    let mut file = try!(File::open(file_path).map_err(|e| e.to_string()));
    let mut contents = String::new();
    try!(file.read_to_string(&mut contents).map_err(|e| e.to_string()));
    let n = try!(contents.trim().parse::<i32>().map_err(|e| e.to_string()));
    Ok(2 * n)
}

fn main() {
    match file_double("foobar") {
        Ok(n) => println!("{}", n),
        Err(err) => println!("Error: {}", err),
    }
}

The map_err calls are still necessary given
our definition of <code>try!</code>.
This is because the error types still need to be converted to String.
The good news is that we will soon learn how to remove those map_err calls!
The bad news is that we will need to learn a bit more about a couple important
traits in the standard library before we can remove the map_err calls.

Defining your own error type

Before we dive into some of the standard library error traits, I'd like to wrap
up this section by removing the use of String as our error type in the
previous examples.

Using String as we did in our previous examples is convenient because it's
easy to convert errors to strings, or even make up your own errors as strings
on the spot. However, using String for your errors has some downsides.

The first downside is that the error messages tend to clutter your
code. It's possible to define the error messages elsewhere, but unless
you're unusually disciplined, it is very tempting to embed the error
message into your code. Indeed, we did exactly this in a previous
example.

The second and more important downside is that Strings are lossy. That is,
if all errors are converted to strings, then the errors we pass to the caller
become completely opaque. The only reasonable thing the caller can do with a
String error is show it to the user. Certainly, inspecting the string to
determine the type of error is not robust. (Admittedly, this downside is far
more important inside of a library as opposed to, say, an application.)

For example, the io::Error type embeds an
<code>io::ErrorKind</code>,
which is structured data that represents what went wrong during an IO
operation. This is important because you might want to react differently
depending on the error. (e.g., A BrokenPipe error might mean quitting your
program gracefully while a NotFound error might mean exiting with an error
code and showing an error to the user.) With io::ErrorKind, the caller can
examine the type of an error with case analysis, which is strictly superior
to trying to tease out the details of an error inside of a String.

Instead of using a String as an error type in our previous example of reading
an integer from a file, we can define our own error type that represents errors
with structured data. We endeavor to not drop information from underlying
errors in case the caller wants to inspect the details.

The ideal way to represent one of many possibilities is to define our own
sum type using enum. In our case, an error is either an io::Error or a
num::ParseIntError, so a natural definition arises:

use std::io;
use std::num;

// We derive `Debug` because all types should probably derive `Debug`.
// This gives us a reasonable human readable description of `CliError` values.
#[derive(Debug)]
enum CliError {
    Io(io::Error),
    Parse(num::ParseIntError),
}

Tweaking our code is very easy. Instead of converting errors to strings, we
simply convert them to our CliError type using the corresponding value
constructor:

# #[derive(Debug)]
# enum CliError { Io(::std::io::Error), Parse(::std::num::ParseIntError) }
use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> Result<i32, CliError> {
    let mut file = try!(File::open(file_path).map_err(CliError::Io));
    let mut contents = String::new();
    try!(file.read_to_string(&mut contents).map_err(CliError::Io));
    let n: i32 = try!(contents.trim().parse().map_err(CliError::Parse));
    Ok(2 * n)
}

fn main() {
    match file_double("foobar") {
        Ok(n) => println!("{}", n),
        Err(err) => println!("Error: {:?}", err),
    }
}

The only change here is switching map_err(|e| e.to_string()) (which converts
errors to strings) to map_err(CliError::Io) or map_err(CliError::Parse).
The caller gets to decide the level of detail to report to the user. In
effect, using a String as an error type removes choices from the caller while
using a custom enum error type like CliError gives the caller all of the
conveniences as before in addition to structured data describing the error.

A rule of thumb is to define your own error type, but a String error type
will do in a pinch, particularly if you're writing an application. If you're
writing a library, defining your own error type should be strongly preferred so
that you don't remove choices from the caller unnecessarily.

Standard library traits used for error handling

The standard library defines two integral traits for error handling:
<code>std::error::Error</code> and
<code>std::convert::From</code>. While Error
is designed specifically for generically describing errors, the From
trait serves a more general role for converting values between two
distinct types.

The `Error` trait

The Error trait is defined in the standard
library:

use std::fmt::{Debug, Display};

trait Error: Debug + Display {
  /// A short description of the error.
  fn description(&self) -> &str;

  /// The lower level cause of this error, if any.
  fn cause(&self) -> Option<&Error> { None }
}

This trait is super generic because it is meant to be implemented for all
types that represent errors. This will prove useful for writing composable code
as we'll see later. Otherwise, the trait allows you to do at least the
following things:

Obtain a Debug representation of the error.
Obtain a user-facing Display representation of the error.
Obtain a short description of the error (via the description method).
Inspect the causal chain of an error, if one exists (via the cause method).

The first two are a result of Error requiring impls for both Debug and
Display. The latter two are from the two methods defined on Error. The
power of Error comes from the fact that all error types impl Error, which
means errors can be existentially quantified as a
trait object.
This manifests as either Box<Error> or &Error. Indeed, the cause method
returns an &Error, which is itself a trait object. We'll revisit the
Error trait's utility as a trait object later.

For now, it suffices to show an example implementing the Error trait. Let's
use the error type we defined in the
previous section:

use std::io;
use std::num;

// We derive `Debug` because all types should probably derive `Debug`.
// This gives us a reasonable human readable description of `CliError` values.
#[derive(Debug)]
enum CliError {
    Io(io::Error),
    Parse(num::ParseIntError),
}

This particular error type represents the possibility of two types of errors
occurring: an error dealing with I/O or an error converting a string to a
number. The error could represent as many error types as you want by adding new
variants to the enum definition.

Implementing Error is pretty straight-forward. It's mostly going to be a lot
explicit case analysis.

use std::error;
use std::fmt;

impl fmt::Display for CliError {
    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
        match *self {
            // Both underlying errors already impl `Display`, so we defer to
            // their implementations.
            CliError::Io(ref err) => write!(f, "IO error: {}", err),
            CliError::Parse(ref err) => write!(f, "Parse error: {}", err),
        }
    }
}

impl error::Error for CliError {
    fn description(&self) -> &str {
        // Both underlying errors already impl `Error`, so we defer to their
        // implementations.
        match *self {
            CliError::Io(ref err) => err.description(),
            // Normally we can just write `err.description()`, but the error
            // type has a concrete method called `description`, which conflicts
            // with the trait method. For now, we must explicitly call
            // `description` through the `Error` trait.
            CliError::Parse(ref err) => error::Error::description(err),
        }
    }

    fn cause(&self) -> Option<&error::Error> {
        match *self {
            // N.B. Both of these implicitly cast `err` from their concrete
            // types (either `&io::Error` or `&num::ParseIntError`)
            // to a trait object `&Error`. This works because both error types
            // implement `Error`.
            CliError::Io(ref err) => Some(err),
            CliError::Parse(ref err) => Some(err),
        }
    }
}

We note that this is a very typical implementation of Error: match on your
different error types and satisfy the contracts defined for description and
cause.

The `From` trait

The std::convert::From trait is
defined in the standard
library:

trait From<T> {
    fn from(T) -> Self;
}

Deliciously simple, yes? From is very useful because it gives us a generic
way to talk about conversion from a particular type T to some other type
(in this case, “some other type” is the subject of the impl, or Self).
The crux of From is the
set of implementations provided by the standard
library.

Here are a few simple examples demonstrating how From works:

let string: String = From::from("foo");
let bytes: Vec<u8> = From::from("foo");
let cow: ::std::borrow::Cow<str> = From::from("foo");

OK, so From is useful for converting between strings. But what about errors?
It turns out, there is one critical impl:

impl<'a, E: Error + 'a> From<E> for Box<Error + 'a>

This impl says that for any type that impls Error, we can convert it to a
trait object Box<Error>. This may not seem terribly surprising, but it is
useful in a generic context.

Remember the two errors we were dealing with previously? Specifically,
io::Error and num::ParseIntError. Since both impl Error, they work with
From:

use std::error::Error;
use std::fs;
use std::io;
use std::num;

// We have to jump through some hoops to actually get error values.
let io_err: io::Error = io::Error::last_os_error();
let parse_err: num::ParseIntError = "not a number".parse::<i32>().unwrap_err();

// OK, here are the conversions.
let err1: Box<Error> = From::from(io_err);
let err2: Box<Error> = From::from(parse_err);

There is a really important pattern to recognize here. Both err1 and err2
have the same type. This is because they are existentially quantified types,
or trait objects. In particularly, their underlying type is erased from the
compiler's knowledge, so it truly sees err1 and err2 as exactly the same.
Additionally, we constructed err1 and err2 using precisely the same
function call: From::from. This is because From::from is overloaded on both
its argument and its return type.

This pattern is important because it solves a problem we had earlier: it gives
us a way to reliably convert errors to the same type using the same function.

Time to revisit an old friend; the try! macro.

The real `try!` macro

Previously, we presented this definition of try!:

macro_rules! try {
    ($e:expr) => (match $e {
        Ok(val) => val,
        Err(err) => return Err(err),
    });
}

This is not it's real definition. It's real definition is
in the standard library:

macro_rules! try {
    ($e:expr) => (match $e {
        Ok(val) => val,
        Err(err) => return Err(::std::convert::From::from(err)),
    });
}

There's one tiny but powerful change: the error value is passed through
From::from. This makes the try! macro a lot more powerful because it gives
you automatic type conversion for free.

Armed with our more powerful try! macro, let's take a look at code we wrote
previously to read a file and convert its contents to an integer:

use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> Result<i32, String> {
    let mut file = try!(File::open(file_path).map_err(|e| e.to_string()));
    let mut contents = String::new();
    try!(file.read_to_string(&mut contents).map_err(|e| e.to_string()));
    let n = try!(contents.trim().parse::<i32>().map_err(|e| e.to_string()));
    Ok(2 * n)
}

Earlier, we promised that we could get rid of the map_err calls. Indeed, all
we have to do is pick a type that From works with. As we saw in the previous
section, From has an impl that let's it convert any error type into a
Box<Error>:

use std::error::Error;
use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> Result<i32, Box<Error>> {
    let mut file = try!(File::open(file_path));
    let mut contents = String::new();
    try!(file.read_to_string(&mut contents));
    let n = try!(contents.trim().parse::<i32>());
    Ok(2 * n)
}

We are getting very close to ideal error handling. Our code has very little
overhead as a result from error handling because the try! macro encapsulates
three things simultaneously:

Case analysis.
Control flow.
Error type conversion.

When all three things are combined, we get code that is unencumbered by
combinators, calls to unwrap or case analysis.

There's one little nit left: the Box<Error> type is opaque. If we
return a Box<Error> to the caller, the caller can't (easily) inspect
underlying error type. The situation is certainly better than String
because the caller can call methods like
<code>description</code>
and <code>cause</code>, but the
limitation remains: Box<Error> is opaque. (N.B. This isn't entirely
true because Rust does have runtime reflection, which is useful in
some scenarios that are beyond the scope of this
chapter.)

It's time to revisit our custom CliError type and tie everything together.

Composing custom error types

In the last section, we looked at the real try! macro and how it does
automatic type conversion for us by calling From::from on the error value.
In particular, we converted errors to Box<Error>, which works, but the type
is opaque to callers.

To fix this, we use the same remedy that we're already familiar with: a custom
error type. Once again, here is the code that reads the contents of a file and
converts it to an integer:

use std::fs::File;
use std::io::{self, Read};
use std::num;
use std::path::Path;

// We derive `Debug` because all types should probably derive `Debug`.
// This gives us a reasonable human readable description of `CliError` values.
#[derive(Debug)]
enum CliError {
    Io(io::Error),
    Parse(num::ParseIntError),
}

fn file_double_verbose<P: AsRef<Path>>(file_path: P) -> Result<i32, CliError> {
    let mut file = try!(File::open(file_path).map_err(CliError::Io));
    let mut contents = String::new();
    try!(file.read_to_string(&mut contents).map_err(CliError::Io));
    let n: i32 = try!(contents.trim().parse().map_err(CliError::Parse));
    Ok(2 * n)
}

Notice that we still have the calls to map_err. Why? Well, recall the
definitions of <code>try!</code> and <code>From</code>. The
problem is that there is no From impl that allows us to convert from error
types like io::Error and num::ParseIntError to our own custom CliError.
Of course, it is easy to fix this! Since we defined CliError, we can impl
From with it:

# #[derive(Debug)]
# enum CliError { Io(io::Error), Parse(num::ParseIntError) }
use std::io;
use std::num;

impl From<io::Error> for CliError {
    fn from(err: io::Error) -> CliError {
        CliError::Io(err)
    }
}

impl From<num::ParseIntError> for CliError {
    fn from(err: num::ParseIntError) -> CliError {
        CliError::Parse(err)
    }
}

All these impls are doing is teaching From how to create a CliError from
other error types. In our case, construction is as simple as invoking the
corresponding value constructor. Indeed, it is typically this easy.

We can finally rewrite file_double:

# use std::io;
# use std::num;
# enum CliError { Io(::std::io::Error), Parse(::std::num::ParseIntError) }
# impl From<io::Error> for CliError {
#     fn from(err: io::Error) -> CliError { CliError::Io(err) }
# }
# impl From<num::ParseIntError> for CliError {
#     fn from(err: num::ParseIntError) -> CliError { CliError::Parse(err) }
# }

use std::fs::File;
use std::io::Read;
use std::path::Path;

fn file_double<P: AsRef<Path>>(file_path: P) -> Result<i32, CliError> {
    let mut file = try!(File::open(file_path));
    let mut contents = String::new();
    try!(file.read_to_string(&mut contents));
    let n: i32 = try!(contents.trim().parse());
    Ok(2 * n)
}

The only thing we did here was remove the calls to map_err. They are no
longer needed because the try! macro invokes From::from on the error value.
This works because we've provided From impls for all the error types that
could appear.

If we modified our file_double function to perform some other operation, say,
convert a string to a float, then we'd need to add a new variant to our error
type:

use std::io;
use std::num;

enum CliError {
    Io(io::Error),
    ParseInt(num::ParseIntError),
    ParseFloat(num::ParseFloatError),
}

And add a new From impl:

# enum CliError {
#     Io(::std::io::Error),
#     ParseInt(num::ParseIntError),
#     ParseFloat(num::ParseFloatError),
# }

use std::num;

impl From<num::ParseFloatError> for CliError {
    fn from(err: num::ParseFloatError) -> CliError {
        CliError::ParseFloat(err)
    }
}

And that's it!

Advice for library writers

If your library needs to report custom errors, then you should
probably define your own error type. It's up to you whether or not to
expose its representation (like
<code>ErrorKind</code>) or keep it hidden (like
<code>ParseIntError</code>). Regardless
of how you do it, it's usually good practice to at least provide some
information about the error beyond just its String
representation. But certainly, this will vary depending on use cases.

At a minimum, you should probably implement the
<code>Error</code>
trait. This will give users of your library some minimum flexibility for
composing errors. Implementing the Error trait also
means that users are guaranteed the ability to obtain a string representation
of an error (because it requires impls for both fmt::Debug and
fmt::Display).

Beyond that, it can also be useful to provide implementations of From on your
error types. This allows you (the library author) and your users to
compose more detailed errors. For example,
<code>csv::Error</code>
provides From impls for both io::Error and byteorder::Error.

Finally, depending on your tastes, you may also want to define a
<code>Result</code> type alias, particularly if your
library defines a single error type. This is used in the standard library
for <code>io::Result</code>
and <code>fmt::Result</code>.

Case study: A program to read population data

This chapter was long, and depending on your background, it might be
rather dense. While there is plenty of example code to go along with
the prose, most of it was specifically designed to be pedagogical. So,
we're going to do something new: a case study.

For this, we're going to build up a command line program that lets you
query world population data. The objective is simple: you give it a location
and it will tell you the population. Despite the simplicity, there is a lot
that can go wrong!

The data we'll be using comes from the Data Science
Toolkit. I've prepared some data from it for this exercise. You
can either grab the world population data (41MB gzip compressed,
145MB uncompressed) or just the US population data (2.2MB gzip
compressed, 7.2MB uncompressed).

Up until now, we've kept the code limited to Rust's standard library. For a real
task like this though, we'll want to at least use something to parse CSV data,
parse the program arguments and decode that stuff into Rust types automatically. For that, we'll use the
<code>csv</code>,
and <code>rustc-serialize</code> crates.

Initial setup

We're not going to spend a lot of time on setting up a project with
Cargo because it is already covered well in the Cargo
chapter and Cargo's documentation.

To get started from scratch, run cargo new --bin city-pop and make sure your
Cargo.toml looks something like this:

[package]
name = "city-pop"
version = "0.1.0"
authors = ["Andrew Gallant <jamslam@gmail.com>"]

[[bin]]
name = "city-pop"

[dependencies]
csv = "0.*"
rustc-serialize = "0.*"
getopts = "0.*"

You should already be able to run:

cargo build --release
./target/release/city-pop
# Outputs: Hello, world!

Argument parsing

Let's get argument parsing out of the way. we won't go into too much
detail on Getopts, but there is some good documentation
describing it. The short story is that Getopts generates an argument
parser and a help message from a vector of options (The fact that it
is a vector is hidden behind a struct and a set of methods). Once the
parsing is done, we can decode the program arguments into a Rust
struct. From there, we can get information about the flags, for
instance, wether they were passed in, and what arguments they
had. Here's our program with the appropriate extern crate
statements, and the basic argument setup for Getopts:

extern crate getopts;
extern crate rustc_serialize;

use getopts::Options;
use std::env;

fn print_usage(program: &str, opts: Options) {
    println!("{}", opts.usage(&format!("Usage: {} [options] <data-path> <city>", program)));
}

fn main() {
    let args: Vec<String> = env::args().collect();
    let program = args[0].clone();

    let mut opts = Options::new();
    opts.optflag("h", "help", "Show this usage message.");

    let matches = match opts.parse(&args[1..]) {
        Ok(m)  => { m }
    Err(e) => { panic!(e.to_string()) }
    };
    if matches.opt_present("h") {
        print_usage(&program, opts);
    return;
    }
    let data_path = args[1].clone();
    let city = args[2].clone();

    // Do stuff with information
}

First, we get a vector of the arguments passed into our program. We
then store the first one, knowing that it is our program's name. Once
that's done, we set up our argument flags, in this case a simplistic
help message flag. Once we have the argument flags set up, we use
Options.parse to parse the argument vector (starting from index one,
becouse index 0 is the program name). If this was successful, we
assign matches to the parsed object, if not, we panic. Once past that,
we test if the user passed in the help flag, and if so print the usage
message. The option help messages are constructed by Getopts, so all
we have to do to print the usage message is tell it what we want it to
print for the program name and template. If the user has not passed in
the help flag, we assign the proper variables to their corresponding
arguments.

Writing the logic

We're all different in how we write code, but error handling is
usually the last thing we want to think about. This isn't very good
practice for good design, but it can be useful for rapidly
prototyping. In our case, because Rust forces us to be explicit about
error handling, it will also make it obvious what parts of our program
can cause errors. Why? Because Rust will make us call unwrap! This
can give us a nice bird's eye view of how we need to approach error
handling.

In this case study, the logic is really simple. All we need to do is parse the
CSV data given to us and print out a field in matching rows. Let's do it. (Make
sure to add extern crate csv; to the top of your file.)

// This struct represents the data in each row of the CSV file.
// Type based decoding absolves us of a lot of the nitty gritty error
// handling, like parsing strings as integers or floats.
#[derive(Debug, RustcDecodable)]
struct Row {
    country: String,
    city: String,
    accent_city: String,
    region: String,

    // Not every row has data for the population, latitude or longitude!
    // So we express them as `Option` types, which admits the possibility of
    // absence. The CSV parser will fill in the correct value for us.
    population: Option<u64>,
    latitude: Option<f64>,
    longitude: Option<f64>,
}

fn print_usage(program: &str, opts: Options) {
    println!("{}", opts.usage(&format!("Usage: {} [options] <data-path> <city>", program)));
}

fn main() {
    let args: Vec<String> = env::args().collect();
    let program = args[0].clone();

    let mut opts = Options::new();
    opts.optflag("h", "help", "Show this usage message.");

    let matches = match opts.parse(&args[1..]) {
        Ok(m)  => { m }
        Err(e) => { panic!(e.to_string()) }
    };

    if matches.opt_present("h") {
        print_usage(&program, opts);
        return;
    }

    let data_file = args[1].clone();
    let data_path = Path::new(&data_file);
    let city = args[2].clone();

    let file = fs::File::open(data_path).unwrap();
    let mut rdr = csv::Reader::from_reader(file);

    for row in rdr.decode::<Row>() {
        let row = row.unwrap();

        if row.city == city {
            println!("{}, {}: {:?}",
                row.city, row.country,
                row.population.expect("population count"));
        }
    }
}

Let's outline the errors. We can start with the obvious: the three places that
unwrap is called:

<code>fs::File::open</code> can return an <code>io::Error</code>.
<code>csv::Reader::decode</code> decodes one record at a time, and decoding a record (look at the Item associated type on the Iterator impl) can produce a <code>csv::Error</code>.
If row.population is None, then calling expect will panic.

Are there any others? What if we can't find a matching city? Tools like grep
will return an error code, so we probably should too. So we have logic errors
specific to our problem, IO errors and CSV parsing errors. We're going to
explore two different ways to approach handling these errors.

I'd like to start with Box<Error>. Later, we'll see how defining our own
error type can be useful.

Error handling with `Box<Error>`

Box<Error> is nice because it just works. You don't need to define your own
error types and you don't need any From implementations. The downside is that
since Box<Error> is a trait object, it erases the type, which means the
compiler can no longer reason about its underlying type.

Previously we started refactoring our code by
changing the type of our function from T to Result<T, OurErrorType>. In
this case, OurErrorType is just Box<Error>. But what's T? And can we add
a return type to main?

The answer to the second question is no, we can't. That means we'll need to
write a new function. But what is T? The simplest thing we can do is to
return a list of matching Row values as a Vec<Row>. (Better code would
return an iterator, but that is left as an exercise to the reader.)

Let's refactor our code into its own function, but keep the calls to unwrap.
Note that we opt to handle the possibility of a missing population count by
simply ignoring that row.

struct Row {
    // unchanged
}

struct PopulationCount {
    city: String,
    country: String,
    // This is no longer an `Option` because values of this type are only
    // constructed if they have a population count.
    count: u64,
}

fn print_usage(program: &str, opts: Options) {
    println!("{}", opts.usage(&format!("Usage: {} [options] <data-path> <city>", program)));
}

fn search<P: AsRef<Path>>(file_path: P, city: &str) -> Vec<PopulationCount> {
    let mut found = vec![];
    let file = fs::File::open(file_path).unwrap();
    let mut rdr = csv::Reader::from_reader(file);
    for row in rdr.decode::<Row>() {
        let row = row.unwrap();
        match row.population {
            None => { } // skip it
            Some(count) => if row.city == city {
                found.push(PopulationCount {
                    city: row.city,
                    country: row.country,
                    count: count,
                });
            },
        }
    }
    found
}

fn main() {
    let args: Vec<String> = env::args().collect();
    let program = args[0].clone();

    let mut opts = Options::new();
    opts.optflag("h", "help", "Show this usage message.");

    let matches = match opts.parse(&args[1..]) {
        Ok(m)  => { m }
        Err(e) => { panic!(e.to_string()) }
    };
    if matches.opt_present("h") {
        print_usage(&program, opts);
        return;
    }

    let data_file = args[1].clone();
    let data_path = Path::new(&data_file);
    let city = args[2].clone();
    for pop in search(&data_path, &city) {
        println!("{}, {}: {:?}", pop.city, pop.country, pop.count);
    }
}

While we got rid of one use of expect (which is a nicer variant of unwrap),
we still should handle the absence of any search results.

To convert this to proper error handling, we need to do the following:

Change the return type of search to be Result<Vec<PopulationCount>, Box<Error>>.
Use the <code>try!</code> macro so that errors are returned to the caller instead of panicking the program.
Handle the error in main.

Let's try it:

fn search<P: AsRef<Path>>
         (file_path: P, city: &str)
         -> Result<Vec<PopulationCount>, Box<Error+Send+Sync>> {
    let mut found = vec![];
    let file = try!(fs::File::open(file_path));
    let mut rdr = csv::Reader::from_reader(file);
    for row in rdr.decode::<Row>() {
        let row = try!(row);
        match row.population {
            None => { } // skip it
            Some(count) => if row.city == city {
                found.push(PopulationCount {
                    city: row.city,
                    country: row.country,
                    count: count,
                });
            },
        }
    }
    if found.is_empty() {
        Err(From::from("No matching cities with a population were found."))
    } else {
        Ok(found)
    }
}

Instead of x.unwrap(), we now have try!(x). Since our function returns a
Result<T, E>, the try! macro will return early from the function if an
error occurs.

There is one big gotcha in this code: we used Box<Error + Send + Sync>
instead of Box<Error>. We did this so we could convert a plain string to an
error type. We need these extra bounds so that we can use the
corresponding <code>From</code>
impls:

// We are making use of this impl in the code above, since we call `From::from`
// on a `&'static str`.
impl<'a, 'b> From<&'b str> for Box<Error + Send + Sync + 'a>

// But this is also useful when you need to allocate a new string for an
// error message, usually with `format!`.
impl From<String> for Box<Error + Send + Sync>

Now that we've seen how to do proper error handling with Box<Error>, let's
try a different approach with our own custom error type. But first, let's take
a quick break from error handling and add support for reading from stdin.

Reading from stdin

In our program, we accept a single file for input and do one pass over the
data. This means we probably should be able to accept input on stdin. But maybe
we like the current format too—so let's have both!

Adding support for stdin is actually quite easy. There are only two things we
have to do:

Tweak the program arguments so that a single parameter—the city—can be accepted while the population data is read from stdin.
Modify the program so that an option -f can take the file, if it is not passed into stdin.
Modify the search function to take an optional file path. When None, it should know to read from stdin.

First, here's the new usage:

fn print_usage(program: &str, opts: Options) {
    println!("{}", opts.usage(&format!("Usage: {} [options] <city>", program)));
}

The next part is going to be only a little harder:

...
let mut opts = Options::new();
opts.optopt("f", "file", "Choose an input file, instead of using STDIN.", "NAME");
opts.optflag("h", "help", "Show this usage message.");
...
let file = matches.opt_str("f");
let data_file = file.as_ref().map(Path::new);

let city = if !matches.free.is_empty() {
    matches.free[0].clone()
} else {
    print_usage(&program, opts);
    return;
};

for pop in search(&data_file, &city) {
    println!("{}, {}: {:?}", pop.city, pop.country, pop.count);
}
...

In this peice of code, we take file (which has the type
Option<String>), and convert it to a type that search can use, in
this case, &Option<AsRef<Path>>. Do do this, we take a reference of
file, and map Path::new onto it. In this case, as_ref() converts
the Option<String> into an Option<&str>, and from there, we can
execute Path::new to the content of the optional, and return the
optional of the new value. Once we have that, it is a simple matter of
getting the city argument and executing search.

Modifying search is slightly trickier. The csv crate can build a
parser out of
any type that implements <code>io::Read</code>.
But how can we use the same code over both types? There's actually a
couple ways we could go about this. One way is to write search such
that it is generic on some type parameter R that satisfies
io::Read. Another way is to just use trait objects:

fn search<P: AsRef<Path>>
         (file_path: &Option<P>, city: &str)
         -> Result<Vec<PopulationCount>, Box<Error+Send+Sync>> {
    let mut found = vec![];
    let input: Box<io::Read> = match *file_path {
        None => Box::new(io::stdin()),
        Some(ref file_path) => Box::new(try!(fs::File::open(file_path))),
    };
    let mut rdr = csv::Reader::from_reader(input);
    // The rest remains unchanged!
}

Error handling with a custom type

Previously, we learned how to
compose errors using a custom error type.
We did this by defining our error type as an enum and implementing Error
and From.

Since we have three distinct errors (IO, CSV parsing and not found), let's
define an enum with three variants:

#[derive(Debug)]
enum CliError {
    Io(io::Error),
    Csv(csv::Error),
    NotFound,
}

And now for impls on Display and Error:

impl fmt::Display for CliError {
    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
        match *self {
            CliError::Io(ref err) => err.fmt(f),
            CliError::Csv(ref err) => err.fmt(f),
            CliError::NotFound => write!(f, "No matching cities with a \
                                             population were found."),
        }
    }
}

impl Error for CliError {
    fn description(&self) -> &str {
        match *self {
            CliError::Io(ref err) => err.description(),
            CliError::Csv(ref err) => err.description(),
            CliError::NotFound => "not found",
        }
    }
}

Before we can use our CliError type in our search function, we need to
provide a couple From impls. How do we know which impls to provide? Well,
we'll need to convert from both io::Error and csv::Error to CliError.
Those are the only external errors, so we'll only need two From impls for
now:

impl From<io::Error> for CliError {
    fn from(err: io::Error) -> CliError {
        CliError::Io(err)
    }
}

impl From<csv::Error> for CliError {
    fn from(err: csv::Error) -> CliError {
        CliError::Csv(err)
    }
}

The From impls are important because of how
<code>try!</code> is defined. In particular, if an error occurs,
From::from is called on the error, which in this case, will convert it to our
own error type CliError.

With the From impls done, we only need to make two small tweaks to our
search function: the return type and the “not found” error. Here it is in
full:

fn search<P: AsRef<Path>>
         (file_path: &Option<P>, city: &str)
         -> Result<Vec<PopulationCount>, CliError> {
    let mut found = vec![];
    let input: Box<io::Read> = match *file_path {
        None => Box::new(io::stdin()),
        Some(ref file_path) => Box::new(try!(fs::File::open(file_path))),
    };
    let mut rdr = csv::Reader::from_reader(input);
    for row in rdr.decode::<Row>() {
        let row = try!(row);
        match row.population {
            None => { } // skip it
            Some(count) => if row.city == city {
                found.push(PopulationCount {
                    city: row.city,
                    country: row.country,
                    count: count,
                });
            },
        }
    }
    if found.is_empty() {
        Err(CliError::NotFound)
    } else {
        Ok(found)
    }
}

No other changes are necessary.

Adding functionality

Writing generic code is great, because generalizing stuff is cool, and
it can then be useful later. But sometimes, the juice isn't worth the
squeeze. Look at what we just did in the previous step:

Defined a new error type.
Added impls for Error, Display and two for From.

The big downside here is that our program didn't improve a whole lot.
There is quite a bit of overhead to representing errors with enums,
especially in short programs like this.

One useful aspect of using a custom error type like we've done here is that
the main function can now choose to handle errors differently. Previously,
with Box<Error>, it didn't have much of a choice: just print the message.
We're still doing that here, but what if we wanted to, say, add a --quiet
flag? The --quiet flag should silence any verbose output.

Right now, if the program doesn't find a match, it will output a message saying
so. This can be a little clumsy, especially if you intend for the program to
be used in shell scripts.

So let's start by adding the flags. Like before, we need to tweak the usage
string and add a flag to the Option variable. Once were done that, Getopts does the rest:

...
let mut opts = Options::new();
opts.optopt("f", "file", "Choose an input file, instead of using STDIN.", "NAME");
opts.optflag("h", "help", "Show this usage message.");
opts.optflag("q", "quit", "Silences errors and warnings.");
...

Now we just need to implement our “quiet” functionality. This requires us to
tweak the case analysis in main:

match search(&args.arg_data_path, &args.arg_city) {
    Err(CliError::NotFound) if args.flag_quiet => process::exit(1),
    Err(err) => fatal!("{}", err),
    Ok(pops) => for pop in pops {
        println!("{}, {}: {:?}", pop.city, pop.country, pop.count);
    }
}

Certainly, we don't want to be quiet if there was an IO error or if the data
failed to parse. Therefore, we use case analysis to check if the error type is
NotFound and if --quiet has been enabled. If the search failed, we still
quit with an exit code (following grep's convention).

If we had stuck with Box<Error>, then it would be pretty tricky to implement
the --quiet functionality.

This pretty much sums up our case study. From here, you should be ready to go
out into the world and write your own programs and libraries with proper error
handling.

The Short Story

Since this chapter is long, it is useful to have a quick summary for error
handling in Rust. These are some good “rules of thumb." They are emphatically
not commandments. There are probably good reasons to break every one of these
heuristics!

If you're writing short example code that would be overburdened by error handling, it's probably just fine to use unwrap (whether that's <code>Result::unwrap</code>, <code>Option::unwrap</code> or preferably <code>Option::expect</code>). Consumers of your code should know to use proper error handling. (If they don't, send them here!)
If you're writing a quick 'n' dirty program, don't feel ashamed if you use unwrap. Be warned: if it winds up in someone else's hands, don't be surprised if they are agitated by poor error messages!
If you're writing a quick 'n' dirty program and feel ashamed about panicking anyway, then using either a String or a Box<Error + Send + Sync> for your error type (the Box<Error + Send + Sync> type is because of the available <code>From</code> impls).
Otherwise, in a program, define your own error types with appropriate <code>From</code> and <code>Error</code> impls to make the <code>try!</code> macro more ergnomic.
If you're writing a library and your code can produce errors, define your own error type and implement the <code>std::error::Error</code> trait. Where appropriate, implement <code>From</code> to make both your library code and the caller's code easier to write. (Because of Rust's coherence rules, callers will not be able to impl From on your error type, so your library should do it.)
Learn the combinators defined on <code>Option</code> and <code>Result</code>. Using them exclusively can be a bit tiring at times, but I've personally found a healthy mix of try! and combinators to be quite appealing. and_then, map and unwrap_or are my favorites.

Penflip

Penflip - Write better with others

sarojaba · Rust Doc Korean

4.7. 오류 처리 (Error Handling) - 4%

목차

기본

Unwrapping explained

`Option` 형식

`Option<T>` 변수들을 사용하기

`Result` 형식

변수 파싱

`Result` 형식의 다른 표현법

A brief interlude: unwrapping isn't evil

Working with multiple error types

Composing `Option` and `Result`

The limits of combinators

Early returns

The `try!` macro

Defining your own error type

Standard library traits used for error handling

The `Error` trait

The `From` trait

The real `try!` macro

Composing custom error types

Advice for library writers

Case study: A program to read population data

Initial setup

Argument parsing

Writing the logic

Error handling with `Box<Error>`

Reading from stdin

Error handling with a custom type

Adding functionality

The Short Story

Contents

About

Quick Start

Support

Connect

sarojaba · Rust Doc Korean

4.7. 오류 처리 (Error Handling) - 4%

목차

기본

Unwrapping explained

Option 형식

Option<T> 변수들을 사용하기

Result 형식

변수 파싱

Result 형식의 다른 표현법

A brief interlude: unwrapping isn't evil

Working with multiple error types

Composing Option and Result

The limits of combinators

Early returns

The try! macro

Defining your own error type

Standard library traits used for error handling

The Error trait

The From trait

The real try! macro

Composing custom error types

Advice for library writers

Case study: A program to read population data

Initial setup

Argument parsing

Writing the logic

Error handling with Box<Error>

Reading from stdin

Error handling with a custom type

Adding functionality

The Short Story

Contents

About

Quick Start

Support

Connect

`Option` 형식

`Option<T>` 변수들을 사용하기

`Result` 형식

`Result` 형식의 다른 표현법

Composing `Option` and `Result`

The `try!` macro

The `Error` trait

The `From` trait

The real `try!` macro

Error handling with `Box<Error>`