1595207964
Rust’s module system is surprisingly confusing and causes a lot of frustration for beginners.
In this post, I’ll explain the module system using practical examples so you get a clear understanding of how it works and can immediately start applying this in your projects.
Since Rust’s module system is quite unique, I request the reader to read this post with an open mind and resist comparing it with how modules work in other languages.
Let’s use this file structure to simulate a real world project:
my_project
├── Cargo.toml
└─┬ src
├── main.rs
├── config.rs
├─┬ routes
│ ├── health_route.rs
│ └── user_route.rs
└─┬ models
└── user_model.rs
These are the different ways we should be able to consume our modules:
These 3 examples should be sufficient to explain how Rust’s module system works.
Let’s start with the first example - importing config.rs
in main.rs
.
// main.rs
fn main() {
println!("main");
}
// config.rs
fn print_config() {
println!("config");
}
The first mistake that everyone makes is just because we have files like config.rs
, health_route.rs
etc, we think that these files are modules
and we can import them from other files.
Here’s what we see (file system tree) and what the compiler sees (module tree):
Surprisingly, the compiler only sees the crate
module which is our main.rs
file. This is because we need to explicitly build the module tree in Rust - there’s no implicit mapping between file system tree to module tree.
We need to explicitly build the module tree in Rust, there’s no implicit mapping to file system
To add a file to the module tree, we need to declare that file as a submodule using the mod
keyword. The next thing that confuses people is that you would assume we declare a file as module in the same file. But we need to declare this in a different file! Since we only have main.rs
in the module tree, let’s declare config.rs
as a submodule in main.rs
.
The mod keyword declares a submodule
The mod
keyword has this syntax:
mod my_module;
Here, the compiler looks for my_module.rs
or my_module/mod.rs
in the same directory.
my_project
├── Cargo.toml
└─┬ src
├── main.rs
└── my_module.rs
or
my_project
├── Cargo.toml
└─┬ src
├── main.rs
└─┬ my_module
└── mod.rs
Since main.rs
and config.rs
are in the same directory, let’s declare the config module as follows:
// main.rs
+ mod config;
fn main() {
+ config::print_config();
println!("main");
}
// config.rs
fn print_config() {
println!("config");
}
We’re accessing the print_config
function using the ::
syntax.
Here’s how the module tree looks like:
We’ve successfully declared the config
module! But this is not sufficient to be able to call the print_config
function inside config.rs
. Almost everything in Rust is private by default, we need to make the function public using the pub
keyword:
The pub keyword makes things public
// main.rs
mod config;
fn main() {
config::print_config();
println!("main");
}
// config.rs
- fn print_config() {
+ pub fn print_config() {
println!("config");
}
Now, this works. We’ve successfully called a function defined in a different file!
#rust #developer
1677668905
Mocking library for TypeScript inspired by http://mockito.org/
mock
) (also abstract classes) #examplespy
) #examplewhen
) via:verify
)reset
, resetCalls
) #example, #examplecapture
) #example'Expected "convertNumberToString(strictEqual(3))" to be called 2 time(s). But has been called 1 time(s).'
)npm install ts-mockito --save-dev
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance from mock
let foo:Foo = instance(mockedFoo);
// Using instance in source code
foo.getBar(3);
foo.getBar(5);
// Explicit, readable verification
verify(mockedFoo.getBar(3)).called();
verify(mockedFoo.getBar(anything())).called();
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub method before execution
when(mockedFoo.getBar(3)).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.getBar(3));
// prints null, because "getBar(999)" was not stubbed
console.log(foo.getBar(999));
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub getter before execution
when(mockedFoo.sampleGetter).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.sampleGetter);
Syntax is the same as with getter values.
Please note, that stubbing properties that don't have getters only works if Proxy object is available (ES6).
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(2);
foo.getBar(2);
foo.getBar(3);
// Call count verification
verify(mockedFoo.getBar(1)).once(); // was called with arg === 1 only once
verify(mockedFoo.getBar(2)).twice(); // was called with arg === 2 exactly two times
verify(mockedFoo.getBar(between(2, 3))).thrice(); // was called with arg between 2-3 exactly three times
verify(mockedFoo.getBar(anyNumber()).times(4); // was called with any number arg exactly four times
verify(mockedFoo.getBar(2)).atLeast(2); // was called with arg === 2 min two times
verify(mockedFoo.getBar(anything())).atMost(4); // was called with any argument max four times
verify(mockedFoo.getBar(4)).never(); // was never called with arg === 4
// Creating mock
let mockedFoo:Foo = mock(Foo);
let mockedBar:Bar = mock(Bar);
// Getting instance
let foo:Foo = instance(mockedFoo);
let bar:Bar = instance(mockedBar);
// Some calls
foo.getBar(1);
bar.getFoo(2);
// Call order verification
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(2)); // foo.getBar(1) has been called before bar.getFoo(2)
verify(mockedBar.getFoo(2)).calledAfter(mockedFoo.getBar(1)); // bar.getFoo(2) has been called before foo.getBar(1)
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(999999)); // throws error (mockedBar.getFoo(999999) has never been called)
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(10)).thenThrow(new Error('fatal error'));
let foo:Foo = instance(mockedFoo);
try {
foo.getBar(10);
} catch (error:Error) {
console.log(error.message); // 'fatal error'
}
You can also stub method with your own implementation
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
when(mockedFoo.sumTwoNumbers(anyNumber(), anyNumber())).thenCall((arg1:number, arg2:number) => {
return arg1 * arg2;
});
// prints '50' because we've changed sum method implementation to multiply!
console.log(foo.sumTwoNumbers(5, 10));
You can also stub method to resolve / reject promise
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.fetchData("a")).thenResolve({id: "a", value: "Hello world"});
when(mockedFoo.fetchData("b")).thenReject(new Error("b does not exist"));
You can reset just mock call counter
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(1);
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
resetCalls(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
You can also reset calls of multiple mocks at once resetCalls(firstMock, secondMock, thirdMock)
Or reset mock call counter with all stubs
// Creating mock
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn("one").
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
console.log(foo.getBar(1)); // "one" - as defined in stub
console.log(foo.getBar(1)); // "one" - as defined in stub
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
reset(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
console.log(foo.getBar(1)); // null - previously added stub has been removed
You can also reset multiple mocks at once reset(firstMock, secondMock, thirdMock)
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
// Call method
foo.sumTwoNumbers(1, 2);
// Check first arg captor values
const [firstArg, secondArg] = capture(mockedFoo.sumTwoNumbers).last();
console.log(firstArg); // prints 1
console.log(secondArg); // prints 2
You can also get other calls using first()
, second()
, byCallIndex(3)
and more...
You can set multiple returning values for same matching values
const mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(anyNumber())).thenReturn('one').thenReturn('two').thenReturn('three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinitely
Another example with specific values
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn('one').thenReturn('another one');
when(mockedFoo.getBar(2)).thenReturn('two');
let foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(2)); // two
console.log(foo.getBar(1)); // another one
console.log(foo.getBar(1)); // another one - this is last defined behavior for arg '1' so it will be repeated
console.log(foo.getBar(2)); // two
console.log(foo.getBar(2)); // two - this is last defined behavior for arg '2' so it will be repeated
Short notation:
const mockedFoo:Foo = mock(Foo);
// You can specify return values as multiple thenReturn args
when(mockedFoo.getBar(anyNumber())).thenReturn('one', 'two', 'three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinity
Possible errors:
const mockedFoo:Foo = mock(Foo);
// When multiple matchers, matches same result:
when(mockedFoo.getBar(anyNumber())).thenReturn('one');
when(mockedFoo.getBar(3)).thenReturn('one');
const foo:Foo = instance(mockedFoo);
foo.getBar(3); // MultipleMatchersMatchSameStubError will be thrown, two matchers match same method call
You can mock interfaces too, just instead of passing type to mock
function, set mock
function generic type Mocking interfaces requires Proxy
implementation
let mockedFoo:Foo = mock<FooInterface>(); // instead of mock(FooInterface)
const foo: SampleGeneric<FooInterface> = instance(mockedFoo);
You can mock abstract classes
const mockedFoo: SampleAbstractClass = mock(SampleAbstractClass);
const foo: SampleAbstractClass = instance(mockedFoo);
You can also mock generic classes, but note that generic type is just needed by mock type definition
const mockedFoo: SampleGeneric<SampleInterface> = mock(SampleGeneric);
const foo: SampleGeneric<SampleInterface> = instance(mockedFoo);
You can partially mock an existing instance:
const foo: Foo = new Foo();
const spiedFoo = spy(foo);
when(spiedFoo.getBar(3)).thenReturn('one');
console.log(foo.getBar(3)); // 'one'
console.log(foo.getBaz()); // call to a real method
You can spy on plain objects too:
const foo = { bar: () => 42 };
const spiedFoo = spy(foo);
foo.bar();
console.log(capture(spiedFoo.bar).last()); // [42]
Author: NagRock
Source Code: https://github.com/NagRock/ts-mockito
License: MIT license
1643176207
Serde
*Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.*
You may be looking for:
#[derive(Serialize, Deserialize)]
Click to show Cargo.toml. Run this code in the playground.
[dependencies]
# The core APIs, including the Serialize and Deserialize traits. Always
# required when using Serde. The "derive" feature is only required when
# using #[derive(Serialize, Deserialize)] to make Serde work with structs
# and enums defined in your crate.
serde = { version = "1.0", features = ["derive"] }
# Each data format lives in its own crate; the sample code below uses JSON
# but you may be using a different one.
serde_json = "1.0"
use serde::{Serialize, Deserialize};
#[derive(Serialize, Deserialize, Debug)]
struct Point {
x: i32,
y: i32,
}
fn main() {
let point = Point { x: 1, y: 2 };
// Convert the Point to a JSON string.
let serialized = serde_json::to_string(&point).unwrap();
// Prints serialized = {"x":1,"y":2}
println!("serialized = {}", serialized);
// Convert the JSON string back to a Point.
let deserialized: Point = serde_json::from_str(&serialized).unwrap();
// Prints deserialized = Point { x: 1, y: 2 }
println!("deserialized = {:?}", deserialized);
}
Serde is one of the most widely used Rust libraries so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo but they tend not to get as many eyes as any of the above and may get closed without a response after some time.
Download Details:
Author: serde-rs
Source Code: https://github.com/serde-rs/serde
License: View license
1654894080
Serde JSON
Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.
[dependencies]
serde_json = "1.0"
You may be looking for:
#[derive(Serialize, Deserialize)]
JSON is a ubiquitous open-standard format that uses human-readable text to transmit data objects consisting of key-value pairs.
{
"name": "John Doe",
"age": 43,
"address": {
"street": "10 Downing Street",
"city": "London"
},
"phones": [
"+44 1234567",
"+44 2345678"
]
}
There are three common ways that you might find yourself needing to work with JSON data in Rust.
Serde JSON provides efficient, flexible, safe ways of converting data between each of these representations.
Any valid JSON data can be manipulated in the following recursive enum representation. This data structure is serde_json::Value
.
enum Value {
Null,
Bool(bool),
Number(Number),
String(String),
Array(Vec<Value>),
Object(Map<String, Value>),
}
A string of JSON data can be parsed into a serde_json::Value
by the serde_json::from_str
function. There is also from_slice
for parsing from a byte slice &[u8] and from_reader
for parsing from any io::Read
like a File or a TCP stream.
use serde_json::{Result, Value};
fn untyped_example() -> Result<()> {
// Some JSON input data as a &str. Maybe this comes from the user.
let data = r#"
{
"name": "John Doe",
"age": 43,
"phones": [
"+44 1234567",
"+44 2345678"
]
}"#;
// Parse the string of data into serde_json::Value.
let v: Value = serde_json::from_str(data)?;
// Access parts of the data by indexing with square brackets.
println!("Please call {} at the number {}", v["name"], v["phones"][0]);
Ok(())
}
The result of square bracket indexing like v["name"]
is a borrow of the data at that index, so the type is &Value
. A JSON map can be indexed with string keys, while a JSON array can be indexed with integer keys. If the type of the data is not right for the type with which it is being indexed, or if a map does not contain the key being indexed, or if the index into a vector is out of bounds, the returned element is Value::Null
.
When a Value
is printed, it is printed as a JSON string. So in the code above, the output looks like Please call "John Doe" at the number "+44 1234567"
. The quotation marks appear because v["name"]
is a &Value
containing a JSON string and its JSON representation is "John Doe"
. Printing as a plain string without quotation marks involves converting from a JSON string to a Rust string with as_str()
or avoiding the use of Value
as described in the following section.
The Value
representation is sufficient for very basic tasks but can be tedious to work with for anything more significant. Error handling is verbose to implement correctly, for example imagine trying to detect the presence of unrecognized fields in the input data. The compiler is powerless to help you when you make a mistake, for example imagine typoing v["name"]
as v["nmae"]
in one of the dozens of places it is used in your code.
Serde provides a powerful way of mapping JSON data into Rust data structures largely automatically.
use serde::{Deserialize, Serialize};
use serde_json::Result;
#[derive(Serialize, Deserialize)]
struct Person {
name: String,
age: u8,
phones: Vec<String>,
}
fn typed_example() -> Result<()> {
// Some JSON input data as a &str. Maybe this comes from the user.
let data = r#"
{
"name": "John Doe",
"age": 43,
"phones": [
"+44 1234567",
"+44 2345678"
]
}"#;
// Parse the string of data into a Person object. This is exactly the
// same function as the one that produced serde_json::Value above, but
// now we are asking it for a Person as output.
let p: Person = serde_json::from_str(data)?;
// Do things just like with any other Rust data structure.
println!("Please call {} at the number {}", p.name, p.phones[0]);
Ok(())
}
This is the same serde_json::from_str
function as before, but this time we assign the return value to a variable of type Person
so Serde will automatically interpret the input data as a Person
and produce informative error messages if the layout does not conform to what a Person
is expected to look like.
Any type that implements Serde's Deserialize
trait can be deserialized this way. This includes built-in Rust standard library types like Vec<T>
and HashMap<K, V>
, as well as any structs or enums annotated with #[derive(Deserialize)]
.
Once we have p
of type Person
, our IDE and the Rust compiler can help us use it correctly like they do for any other Rust code. The IDE can autocomplete field names to prevent typos, which was impossible in the serde_json::Value
representation. And the Rust compiler can check that when we write p.phones[0]
, then p.phones
is guaranteed to be a Vec<String>
so indexing into it makes sense and produces a String
.
The necessary setup for using Serde's derive macros is explained on the Using derive page of the Serde site.
Serde JSON provides a json!
macro to build serde_json::Value
objects with very natural JSON syntax.
use serde_json::json;
fn main() {
// The type of `john` is `serde_json::Value`
let john = json!({
"name": "John Doe",
"age": 43,
"phones": [
"+44 1234567",
"+44 2345678"
]
});
println!("first phone number: {}", john["phones"][0]);
// Convert to a string of JSON and print it out
println!("{}", john.to_string());
}
The Value::to_string()
function converts a serde_json::Value
into a String
of JSON text.
One neat thing about the json!
macro is that variables and expressions can be interpolated directly into the JSON value as you are building it. Serde will check at compile time that the value you are interpolating is able to be represented as JSON.
let full_name = "John Doe";
let age_last_year = 42;
// The type of `john` is `serde_json::Value`
let john = json!({
"name": full_name,
"age": age_last_year + 1,
"phones": [
format!("+44 {}", random_phone())
]
});
This is amazingly convenient, but we have the problem we had before with Value
: the IDE and Rust compiler cannot help us if we get it wrong. Serde JSON provides a better way of serializing strongly-typed data structures into JSON text.
A data structure can be converted to a JSON string by serde_json::to_string
. There is also serde_json::to_vec
which serializes to a Vec<u8>
and serde_json::to_writer
which serializes to any io::Write
such as a File or a TCP stream.
use serde::{Deserialize, Serialize};
use serde_json::Result;
#[derive(Serialize, Deserialize)]
struct Address {
street: String,
city: String,
}
fn print_an_address() -> Result<()> {
// Some data structure.
let address = Address {
street: "10 Downing Street".to_owned(),
city: "London".to_owned(),
};
// Serialize it to a JSON string.
let j = serde_json::to_string(&address)?;
// Print, write to a file, or send to an HTTP server.
println!("{}", j);
Ok(())
}
Any type that implements Serde's Serialize
trait can be serialized this way. This includes built-in Rust standard library types like Vec<T>
and HashMap<K, V>
, as well as any structs or enums annotated with #[derive(Serialize)]
.
It is fast. You should expect in the ballpark of 500 to 1000 megabytes per second deserialization and 600 to 900 megabytes per second serialization, depending on the characteristics of your data. This is competitive with the fastest C and C++ JSON libraries or even 30% faster for many use cases. Benchmarks live in the serde-rs/json-benchmark repo.
Serde is one of the most widely used Rust libraries, so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo, but they tend not to get as many eyes as any of the above and may get closed without a response after some time.
As long as there is a memory allocator, it is possible to use serde_json without the rest of the Rust standard library. This is supported on Rust 1.36+. Disable the default "std" feature and enable the "alloc" feature:
[dependencies]
serde_json = { version = "1.0", default-features = false, features = ["alloc"] }
For JSON support in Serde without a memory allocator, please see the serde-json-core
crate.
1595207964
Rust’s module system is surprisingly confusing and causes a lot of frustration for beginners.
In this post, I’ll explain the module system using practical examples so you get a clear understanding of how it works and can immediately start applying this in your projects.
Since Rust’s module system is quite unique, I request the reader to read this post with an open mind and resist comparing it with how modules work in other languages.
Let’s use this file structure to simulate a real world project:
my_project
├── Cargo.toml
└─┬ src
├── main.rs
├── config.rs
├─┬ routes
│ ├── health_route.rs
│ └── user_route.rs
└─┬ models
└── user_model.rs
These are the different ways we should be able to consume our modules:
These 3 examples should be sufficient to explain how Rust’s module system works.
Let’s start with the first example - importing config.rs
in main.rs
.
// main.rs
fn main() {
println!("main");
}
// config.rs
fn print_config() {
println!("config");
}
The first mistake that everyone makes is just because we have files like config.rs
, health_route.rs
etc, we think that these files are modules
and we can import them from other files.
Here’s what we see (file system tree) and what the compiler sees (module tree):
Surprisingly, the compiler only sees the crate
module which is our main.rs
file. This is because we need to explicitly build the module tree in Rust - there’s no implicit mapping between file system tree to module tree.
We need to explicitly build the module tree in Rust, there’s no implicit mapping to file system
To add a file to the module tree, we need to declare that file as a submodule using the mod
keyword. The next thing that confuses people is that you would assume we declare a file as module in the same file. But we need to declare this in a different file! Since we only have main.rs
in the module tree, let’s declare config.rs
as a submodule in main.rs
.
The mod keyword declares a submodule
The mod
keyword has this syntax:
mod my_module;
Here, the compiler looks for my_module.rs
or my_module/mod.rs
in the same directory.
my_project
├── Cargo.toml
└─┬ src
├── main.rs
└── my_module.rs
or
my_project
├── Cargo.toml
└─┬ src
├── main.rs
└─┬ my_module
└── mod.rs
Since main.rs
and config.rs
are in the same directory, let’s declare the config module as follows:
// main.rs
+ mod config;
fn main() {
+ config::print_config();
println!("main");
}
// config.rs
fn print_config() {
println!("config");
}
We’re accessing the print_config
function using the ::
syntax.
Here’s how the module tree looks like:
We’ve successfully declared the config
module! But this is not sufficient to be able to call the print_config
function inside config.rs
. Almost everything in Rust is private by default, we need to make the function public using the pub
keyword:
The pub keyword makes things public
// main.rs
mod config;
fn main() {
config::print_config();
println!("main");
}
// config.rs
- fn print_config() {
+ pub fn print_config() {
println!("config");
}
Now, this works. We’ve successfully called a function defined in a different file!
#rust #developer
1629837300
What we learn in this chapter:
- Rust number types and their default
- First exposure to #Rust modules and the std::io module to read input from the terminal
- Rust Variable Shadowing
- Rust Loop keyword
- Rust if/else
- First exposure to #Rust match keyword
=== Content:
00:00 - Intro & Setup
02:11 - The Plan
03:04 - Variable Secret
04:03 - Number Types
05:45 - Mutability recap
06:22 - Ask the user
07:45 - First intro to module std::io
08:29 - Rust naming conventions
09:22 - Read user input io:stdin().read_line(&mut guess)
12:46 - Break & Understand
14:20 - Parse string to number
17:10 - Variable Shadowing
18:46 - If / Else - You Win, You Loose
19:28 - Loop
20:38 - Match
23:19 - Random with rand
26:35 - Run it all
27:09 - Conclusion and next episode