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Table of Contents
We use nginx in our company lab environment. It often happens that my colleagues have developed an application that is now deployed in our Stage or Prod environment. To make this application accessible nginx has to be adapted. Most of the time my colleagues don't have the permission to access the server and change the configuration files and since I don't feel like doing this for everyone anymore I thought a UI could help us all. If you feel the same way I wish you a lot of fun with the application and I am looking forward to your feedback, change requests or even a star.
Containerization is now state of the art and therefore the application is delivered in a container.
-d
run as deamon in background--restart=always
restart on crash or server reboot--name nginxui
give the container a name-v /etc/nginx:/etc/nginx
map the hosts nginx directory into the container-p 8080:8080
map host port 8080 to docker container port 8080docker run -d --restart=always --name nginxui -v /etc/nginx:/etc/nginx -p 8080:8080 schenkd/nginx-ui:latest
Repository @ DockerHub
Docker Compose excerpt
# Docker Compose excerpt
services:
nginx-ui:
image: schenkd/nginx-ui:latest
ports:
- 8080:8080
volumes:
- nginx:/etc/nginx
With the menu item Main Config the Nginx specific configuration files can be extracted and updated. These are dynamically read from the Nginx directory. If a file has been added manually, it is immediately integrated into the Nginx UI Main Config menu item.
Adding a domain opens an exclusive editing window for the configuration file. This can be applied, deleted and enabled/disabled.
In general, this app does not come with authentication. However, it is easy to setup basic auth to restrict unwanted access. Here is how this can be done when using nginx.
apache2-utils
(Debian, Ubuntu) or httpd-tools
(RHEL/CentOS/Oracle Linux) is installed-c
flag, if you have created a user before, since it creates the inital user/passwort filesudo htpasswd -c /etc/apache2/.htpasswd user1
The following example adds basic auth to our nginxui app running in a docker container with a mapped port 8080. In this case, it will be accessible via nginx.mydomain.com
server {
server_name nginx.mydomain.com;
location / {
proxy_pass http://127.0.0.1:8080/;
}
auth_basic "nginxui secured";
auth_basic_user_file /etc/apache2/.htpasswd;
# [...] ommited ssl configuration
}
/etc/nginx/my.conf
filenginx -t
to make sure, that your config is validsystemctl restart nginx
(or equivalent) to restart your nginx and apply the new settingsAuthor: schenkd
Source Code: https://github.com/schenkd/nginx-ui
License: MIT License
1661577180
The following is a collection of tips I find to be useful when working with the Swift language. More content is available on my Twitter account!
Property Wrappers allow developers to wrap properties with specific behaviors, that will be seamlessly triggered whenever the properties are accessed.
While their primary use case is to implement business logic within our apps, it's also possible to use Property Wrappers as debugging tools!
For example, we could build a wrapper called @History
, that would be added to a property while debugging and would keep track of all the values set to this property.
import Foundation
@propertyWrapper
struct History<Value> {
private var value: Value
private(set) var history: [Value] = []
init(wrappedValue: Value) {
self.value = wrappedValue
}
var wrappedValue: Value {
get { value }
set {
history.append(value)
value = newValue
}
}
var projectedValue: Self {
return self
}
}
// We can then decorate our business code
// with the `@History` wrapper
struct User {
@History var name: String = ""
}
var user = User()
// All the existing call sites will still
// compile, without the need for any change
user.name = "John"
user.name = "Jane"
// But now we can also access an history of
// all the previous values!
user.$name.history // ["", "John"]
String
interpolationSwift 5 gave us the possibility to define our own custom String
interpolation methods.
This feature can be used to power many use cases, but there is one that is guaranteed to make sense in most projects: localizing user-facing strings.
import Foundation
extension String.StringInterpolation {
mutating func appendInterpolation(localized key: String, _ args: CVarArg...) {
let localized = String(format: NSLocalizedString(key, comment: ""), arguments: args)
appendLiteral(localized)
}
}
/*
Let's assume that this is the content of our Localizable.strings:
"welcome.screen.greetings" = "Hello %@!";
*/
let userName = "John"
print("\(localized: "welcome.screen.greetings", userName)") // Hello John!
structs
If you’ve always wanted to use some kind of inheritance mechanism for your structs, Swift 5.1 is going to make you very happy!
Using the new KeyPath-based dynamic member lookup, you can implement some pseudo-inheritance, where a type inherits the API of another one 🎉
(However, be careful, I’m definitely not advocating inheritance as a go-to solution 🙃)
import Foundation
protocol Inherits {
associatedtype SuperType
var `super`: SuperType { get }
}
extension Inherits {
subscript<T>(dynamicMember keyPath: KeyPath<SuperType, T>) -> T {
return self.`super`[keyPath: keyPath]
}
}
struct Person {
let name: String
}
@dynamicMemberLookup
struct User: Inherits {
let `super`: Person
let login: String
let password: String
}
let user = User(super: Person(name: "John Appleseed"), login: "Johnny", password: "1234")
user.name // "John Appleseed"
user.login // "Johnny"
NSAttributedString
through a Function BuilderSwift 5.1 introduced Function Builders: a great tool for building custom DSL syntaxes, like SwiftUI. However, one doesn't need to be building a full-fledged DSL in order to leverage them.
For example, it's possible to write a simple Function Builder, whose job will be to compose together individual instances of NSAttributedString
through a nicer syntax than the standard API.
import UIKit
@_functionBuilder
class NSAttributedStringBuilder {
static func buildBlock(_ components: NSAttributedString...) -> NSAttributedString {
let result = NSMutableAttributedString(string: "")
return components.reduce(into: result) { (result, current) in result.append(current) }
}
}
extension NSAttributedString {
class func composing(@NSAttributedStringBuilder _ parts: () -> NSAttributedString) -> NSAttributedString {
return parts()
}
}
let result = NSAttributedString.composing {
NSAttributedString(string: "Hello",
attributes: [.font: UIFont.systemFont(ofSize: 24),
.foregroundColor: UIColor.red])
NSAttributedString(string: " world!",
attributes: [.font: UIFont.systemFont(ofSize: 20),
.foregroundColor: UIColor.orange])
}
switch
and if
as expressionsContrary to other languages, like Kotlin, Swift does not allow switch
and if
to be used as expressions. Meaning that the following code is not valid Swift:
let constant = if condition {
someValue
} else {
someOtherValue
}
A common solution to this problem is to wrap the if
or switch
statement within a closure, that will then be immediately called. While this approach does manage to achieve the desired goal, it makes for a rather poor syntax.
To avoid the ugly trailing ()
and improve on the readability, you can define a resultOf
function, that will serve the exact same purpose, in a more elegant way.
import Foundation
func resultOf<T>(_ code: () -> T) -> T {
return code()
}
let randomInt = Int.random(in: 0...3)
let spelledOut: String = resultOf {
switch randomInt {
case 0:
return "Zero"
case 1:
return "One"
case 2:
return "Two"
case 3:
return "Three"
default:
return "Out of range"
}
}
print(spelledOut)
guard
statementsA guard
statement is a very convenient way for the developer to assert that a condition is met, in order for the execution of the program to keep going.
However, since the body of a guard
statement is meant to be executed when the condition evaluates to false
, the use of the negation (!
) operator within the condition of a guard
statement can make the code hard to read, as it becomes a double negative.
A nice trick to avoid such double negatives is to encapsulate the use of the !
operator within a new property or function, whose name does not include a negative.
import Foundation
extension Collection {
var hasElements: Bool {
return !isEmpty
}
}
let array = Bool.random() ? [1, 2, 3] : []
guard array.hasElements else { fatalError("array was empty") }
print(array)
init
without loosing the compiler-generated oneIt's common knowledge for Swift developers that, when you define a struct
, the compiler is going to automatically generate a memberwise init
for you. That is, unless you also define an init
of your own. Because then, the compiler won't generate any memberwise init
.
Yet, there are many instances where we might enjoy the opportunity to get both. As it turns out, this goal is quite easy to achieve: you just need to define your own init
in an extension
rather than inside the type definition itself.
import Foundation
struct Point {
let x: Int
let y: Int
}
extension Point {
init() {
x = 0
y = 0
}
}
let usingDefaultInit = Point(x: 4, y: 3)
let usingCustomInit = Point()
enum
Swift does not really have an out-of-the-box support of namespaces. One could argue that a Swift module can be seen as a namespace, but creating a dedicated Framework for this sole purpose can legitimately be regarded as overkill.
Some developers have taken the habit to use a struct
which only contains static
fields to implement a namespace. While this does the job, it requires us to remember to implement an empty private
init()
, because it wouldn't make sense for such a struct
to be instantiated.
It's actually possible to take this approach one step further, by replacing the struct
with an enum
. While it might seem weird to have an enum
with no case
, it's actually a very idiomatic way to declare a type that cannot be instantiated.
import Foundation
enum NumberFormatterProvider {
static var currencyFormatter: NumberFormatter {
let formatter = NumberFormatter()
formatter.numberStyle = .currency
formatter.roundingIncrement = 0.01
return formatter
}
static var decimalFormatter: NumberFormatter {
let formatter = NumberFormatter()
formatter.numberStyle = .decimal
formatter.decimalSeparator = ","
return formatter
}
}
NumberFormatterProvider() // ❌ impossible to instantiate by mistake
NumberFormatterProvider.currencyFormatter.string(from: 2.456) // $2.46
NumberFormatterProvider.decimalFormatter.string(from: 2.456) // 2,456
Never
to represent impossible code pathsNever
is quite a peculiar type in the Swift Standard Library: it is defined as an empty enum enum Never { }
.
While this might seem odd at first glance, it actually yields a very interesting property: it makes it a type that cannot be constructed (i.e. it possesses no instances).
This way, Never
can be used as a generic parameter to let the compiler know that a particular feature will not be used.
import Foundation
enum Result<Value, Error> {
case success(value: Value)
case failure(error: Error)
}
func willAlwaysSucceed(_ completion: @escaping ((Result<String, Never>) -> Void)) {
completion(.success(value: "Call was successful"))
}
willAlwaysSucceed( { result in
switch result {
case .success(let value):
print(value)
// the compiler knows that the `failure` case cannot happen
// so it doesn't require us to handle it.
}
})
Decodable
enum
Swift's Codable
framework does a great job at seamlessly decoding entities from a JSON stream. However, when we integrate web-services, we are sometimes left to deal with JSONs that require behaviors that Codable
does not provide out-of-the-box.
For instance, we might have a string-based or integer-based enum
, and be required to set it to a default value when the data found in the JSON does not match any of its cases.
We might be tempted to implement this via an extensive switch
statement over all the possible cases, but there is a much shorter alternative through the initializer init?(rawValue:)
:
import Foundation
enum State: String, Decodable {
case active
case inactive
case undefined
init(from decoder: Decoder) throws {
let container = try decoder.singleValueContainer()
let decodedString = try container.decode(String.self)
self = State(rawValue: decodedString) ?? .undefined
}
}
let data = """
["active", "inactive", "foo"]
""".data(using: .utf8)!
let decoded = try! JSONDecoder().decode([State].self, from: data)
print(decoded) // [State.active, State.inactive, State.undefined]
Dependency injection boils down to a simple idea: when an object requires a dependency, it shouldn't create it by itself, but instead it should be given a function that does it for him.
Now the great thing with Swift is that, not only can a function take another function as a parameter, but that parameter can also be given a default value.
When you combine both those features, you can end up with a dependency injection pattern that is both lightweight on boilerplate, but also type safe.
import Foundation
protocol Service {
func call() -> String
}
class ProductionService: Service {
func call() -> String {
return "This is the production"
}
}
class MockService: Service {
func call() -> String {
return "This is a mock"
}
}
typealias Provider<T> = () -> T
class Controller {
let service: Service
init(serviceProvider: Provider<Service> = { return ProductionService() }) {
self.service = serviceProvider()
}
func work() {
print(service.call())
}
}
let productionController = Controller()
productionController.work() // prints "This is the production"
let mockedController = Controller(serviceProvider: { return MockService() })
mockedController.work() // prints "This is a mock"
Singletons are pretty bad. They make your architecture rigid and tightly coupled, which then results in your code being hard to test and refactor. Instead of using singletons, your code should rely on dependency injection, which is a much more architecturally sound approach.
But singletons are so easy to use, and dependency injection requires us to do extra-work. So maybe, for simple situations, we could find an in-between solution?
One possible solution is to rely on one of Swift's most know features: protocol-oriented programming. Using a protocol
, we declare and access our dependency. We then store it in a private singleton, and perform the injection through an extension of said protocol
.
This way, our code will indeed be decoupled from its dependency, while at the same time keeping the boilerplate to a minimum.
import Foundation
protocol Formatting {
var formatter: NumberFormatter { get }
}
private let sharedFormatter: NumberFormatter = {
let sharedFormatter = NumberFormatter()
sharedFormatter.numberStyle = .currency
return sharedFormatter
}()
extension Formatting {
var formatter: NumberFormatter { return sharedFormatter }
}
class ViewModel: Formatting {
var displayableAmount: String?
func updateDisplay(to amount: Double) {
displayableAmount = formatter.string(for: amount)
}
}
let viewModel = ViewModel()
viewModel.updateDisplay(to: 42000.45)
viewModel.displayableAmount // "$42,000.45"
[weak self]
and guard
Callbacks are a part of almost all iOS apps, and as frameworks such as RxSwift
keep gaining in popularity, they become ever more present in our codebase.
Seasoned Swift developers are aware of the potential memory leaks that @escaping
callbacks can produce, so they make real sure to always use [weak self]
, whenever they need to use self
inside such a context. And when they need to have self
be non-optional, they then add a guard
statement along.
Consequently, this syntax of a [weak self]
followed by a guard
rapidly tends to appear everywhere in the codebase. The good thing is that, through a little protocol-oriented trick, it's actually possible to get rid of this tedious syntax, without loosing any of its benefits!
import Foundation
import PlaygroundSupport
PlaygroundPage.current.needsIndefiniteExecution = true
protocol Weakifiable: class { }
extension Weakifiable {
func weakify(_ code: @escaping (Self) -> Void) -> () -> Void {
return { [weak self] in
guard let self = self else { return }
code(self)
}
}
func weakify<T>(_ code: @escaping (T, Self) -> Void) -> (T) -> Void {
return { [weak self] arg in
guard let self = self else { return }
code(arg, self)
}
}
}
extension NSObject: Weakifiable { }
class Producer: NSObject {
deinit {
print("deinit Producer")
}
private var handler: (Int) -> Void = { _ in }
func register(handler: @escaping (Int) -> Void) {
self.handler = handler
DispatchQueue.main.asyncAfter(deadline: .now() + 1.0, execute: { self.handler(42) })
}
}
class Consumer: NSObject {
deinit {
print("deinit Consumer")
}
let producer = Producer()
func consume() {
producer.register(handler: weakify { result, strongSelf in
strongSelf.handle(result)
})
}
private func handle(_ result: Int) {
print("🎉 \(result)")
}
}
var consumer: Consumer? = Consumer()
consumer?.consume()
DispatchQueue.main.asyncAfter(deadline: .now() + 2.0, execute: { consumer = nil })
// This code prints:
// 🎉 42
// deinit Consumer
// deinit Producer
Asynchronous functions are a big part of iOS APIs, and most developers are familiar with the challenge they pose when one needs to sequentially call several asynchronous APIs.
This often results in callbacks being nested into one another, a predicament often referred to as callback hell.
Many third-party frameworks are able to tackle this issue, for instance RxSwift or PromiseKit. Yet, for simple instances of the problem, there is no need to use such big guns, as it can actually be solved with simple function composition.
import Foundation
typealias CompletionHandler<Result> = (Result?, Error?) -> Void
infix operator ~>: MultiplicationPrecedence
func ~> <T, U>(_ first: @escaping (CompletionHandler<T>) -> Void, _ second: @escaping (T, CompletionHandler<U>) -> Void) -> (CompletionHandler<U>) -> Void {
return { completion in
first({ firstResult, error in
guard let firstResult = firstResult else { completion(nil, error); return }
second(firstResult, { (secondResult, error) in
completion(secondResult, error)
})
})
}
}
func ~> <T, U>(_ first: @escaping (CompletionHandler<T>) -> Void, _ transform: @escaping (T) -> U) -> (CompletionHandler<U>) -> Void {
return { completion in
first({ result, error in
guard let result = result else { completion(nil, error); return }
completion(transform(result), nil)
})
}
}
func service1(_ completionHandler: CompletionHandler<Int>) {
completionHandler(42, nil)
}
func service2(arg: String, _ completionHandler: CompletionHandler<String>) {
completionHandler("🎉 \(arg)", nil)
}
let chainedServices = service1
~> { int in return String(int / 2) }
~> service2
chainedServices({ result, _ in
guard let result = result else { return }
print(result) // Prints: 🎉 21
})
Asynchronous functions are a great way to deal with future events without blocking a thread. Yet, there are times where we would like them to behave in exactly such a blocking way.
Think about writing unit tests and using mocked network calls. You will need to add complexity to your test in order to deal with asynchronous functions, whereas synchronous ones would be much easier to manage.
Thanks to Swift proficiency in the functional paradigm, it is possible to write a function whose job is to take an asynchronous function and transform it into a synchronous one.
import Foundation
func makeSynchrone<A, B>(_ asyncFunction: @escaping (A, (B) -> Void) -> Void) -> (A) -> B {
return { arg in
let lock = NSRecursiveLock()
var result: B? = nil
asyncFunction(arg) {
result = $0
lock.unlock()
}
lock.lock()
return result!
}
}
func myAsyncFunction(arg: Int, completionHandler: (String) -> Void) {
completionHandler("🎉 \(arg)")
}
let syncFunction = makeSynchrone(myAsyncFunction)
print(syncFunction(42)) // prints 🎉 42
Closures are a great way to interact with generic APIs, for instance APIs that allow to manipulate data structures through the use of generic functions, such as filter()
or sorted()
.
The annoying part is that closures tend to clutter your code with many instances of {
, }
and $0
, which can quickly undermine its readably.
A nice alternative for a cleaner syntax is to use a KeyPath
instead of a closure, along with an operator that will deal with transforming the provided KeyPath
in a closure.
import Foundation
prefix operator ^
prefix func ^ <Element, Attribute>(_ keyPath: KeyPath<Element, Attribute>) -> (Element) -> Attribute {
return { element in element[keyPath: keyPath] }
}
struct MyData {
let int: Int
let string: String
}
let data = [MyData(int: 2, string: "Foo"), MyData(int: 4, string: "Bar")]
data.map(^\.int) // [2, 4]
data.map(^\.string) // ["Foo", "Bar"]
userInfo
Dictionary
Many iOS APIs still rely on a userInfo
Dictionary
to handle use-case specific data. This Dictionary
usually stores untyped values, and is declared as follows: [String: Any]
(or sometimes [AnyHashable: Any]
.
Retrieving data from such a structure will involve some conditional casting (via the as?
operator), which is prone to both errors and repetitions. Yet, by introducing a custom subscript
, it's possible to encapsulate all the tedious logic, and end-up with an easier and more robust API.
import Foundation
typealias TypedUserInfoKey<T> = (key: String, type: T.Type)
extension Dictionary where Key == String, Value == Any {
subscript<T>(_ typedKey: TypedUserInfoKey<T>) -> T? {
return self[typedKey.key] as? T
}
}
let userInfo: [String : Any] = ["Foo": 4, "Bar": "forty-two"]
let integerTypedKey = TypedUserInfoKey(key: "Foo", type: Int.self)
let intValue = userInfo[integerTypedKey] // returns 4
type(of: intValue) // returns Int?
let stringTypedKey = TypedUserInfoKey(key: "Bar", type: String.self)
let stringValue = userInfo[stringTypedKey] // returns "forty-two"
type(of: stringValue) // returns String?
MVVM is a great pattern to separate business logic from presentation logic. The main challenge to make it work, is to define a mechanism for the presentation layer to be notified of model updates.
RxSwift is a perfect choice to solve such a problem. Yet, some developers don't feel confortable with leveraging a third-party library for such a central part of their architecture.
For those situation, it's possible to define a lightweight Variable
type, that will make the MVVM pattern very easy to use!
import Foundation
class Variable<Value> {
var value: Value {
didSet {
onUpdate?(value)
}
}
var onUpdate: ((Value) -> Void)? {
didSet {
onUpdate?(value)
}
}
init(_ value: Value, _ onUpdate: ((Value) -> Void)? = nil) {
self.value = value
self.onUpdate = onUpdate
self.onUpdate?(value)
}
}
let variable: Variable<String?> = Variable(nil)
variable.onUpdate = { data in
if let data = data {
print(data)
}
}
variable.value = "Foo"
variable.value = "Bar"
// prints:
// Foo
// Bar
typealias
to its fullestThe keyword typealias
allows developers to give a new name to an already existing type. For instance, Swift defines Void
as a typealias
of ()
, the empty tuple.
But a less known feature of this mechanism is that it allows to assign concrete types for generic parameters, or to rename them. This can help make the semantics of generic types much clearer, when used in specific use cases.
import Foundation
enum Either<Left, Right> {
case left(Left)
case right(Right)
}
typealias Result<Value> = Either<Value, Error>
typealias IntOrString = Either<Int, String>
forEach
Iterating through objects via the forEach(_:)
method is a great alternative to the classic for
loop, as it allows our code to be completely oblivious of the iteration logic. One limitation, however, is that forEach(_:)
does not allow to stop the iteration midway.
Taking inspiration from the Objective-C implementation, we can write an overload that will allow the developer to stop the iteration, if needed.
import Foundation
extension Sequence {
func forEach(_ body: (Element, _ stop: inout Bool) throws -> Void) rethrows {
var stop = false
for element in self {
try body(element, &stop)
if stop {
return
}
}
}
}
["Foo", "Bar", "FooBar"].forEach { element, stop in
print(element)
stop = (element == "Bar")
}
// Prints:
// Foo
// Bar
reduce()
Functional programing is a great way to simplify a codebase. For instance, reduce
is an alternative to the classic for
loop, without most the boilerplate. Unfortunately, simplicity often comes at the price of performance.
Consider that you want to remove duplicate values from a Sequence
. While reduce()
is a perfectly fine way to express this computation, the performance will be sub optimal, because of all the unnecessary Array
copying that will happen every time its closure gets called.
That's when reduce(into:_:)
comes into play. This version of reduce
leverages the capacities of copy-on-write type (such as Array
or Dictionnary
) in order to avoid unnecessary copying, which results in a great performance boost.
import Foundation
func time(averagedExecutions: Int = 1, _ code: () -> Void) {
let start = Date()
for _ in 0..<averagedExecutions { code() }
let end = Date()
let duration = end.timeIntervalSince(start) / Double(averagedExecutions)
print("time: \(duration)")
}
let data = (1...1_000).map { _ in Int(arc4random_uniform(256)) }
// runs in 0.63s
time {
let noDuplicates: [Int] = data.reduce([], { $0.contains($1) ? $0 : $0 + [$1] })
}
// runs in 0.15s
time {
let noDuplicates: [Int] = data.reduce(into: [], { if !$0.contains($1) { $0.append($1) } } )
}
UI components such as UITableView
and UICollectionView
rely on reuse identifiers in order to efficiently recycle the views they display. Often, those reuse identifiers take the form of a static hardcoded String
, that will be used for every instance of their class.
Through protocol-oriented programing, it's possible to avoid those hardcoded values, and instead use the name of the type as a reuse identifier.
import Foundation
import UIKit
protocol Reusable {
static var reuseIdentifier: String { get }
}
extension Reusable {
static var reuseIdentifier: String {
return String(describing: self)
}
}
extension UITableViewCell: Reusable { }
extension UITableView {
func register<T: UITableViewCell>(_ class: T.Type) {
register(`class`, forCellReuseIdentifier: T.reuseIdentifier)
}
func dequeueReusableCell<T: UITableViewCell>(for indexPath: IndexPath) -> T {
return dequeueReusableCell(withIdentifier: T.reuseIdentifier, for: indexPath) as! T
}
}
class MyCell: UITableViewCell { }
let tableView = UITableView()
tableView.register(MyCell.self)
let myCell: MyCell = tableView.dequeueReusableCell(for: [0, 0])
The C language has a construct called union
, that allows a single variable to hold values from different types. While Swift does not provide such a construct, it provides enums with associated values, which allows us to define a type called Either
that implements a union
of two types.
import Foundation
enum Either<A, B> {
case left(A)
case right(B)
func either(ifLeft: ((A) -> Void)? = nil, ifRight: ((B) -> Void)? = nil) {
switch self {
case let .left(a):
ifLeft?(a)
case let .right(b):
ifRight?(b)
}
}
}
extension Bool { static func random() -> Bool { return arc4random_uniform(2) == 0 } }
var intOrString: Either<Int, String> = Bool.random() ? .left(2) : .right("Foo")
intOrString.either(ifLeft: { print($0 + 1) }, ifRight: { print($0 + "Bar") })
If you're interested by this kind of data structure, I strongly recommend that you learn more about Algebraic Data Types.
Most of the time, when we create a .xib
file, we give it the same name as its associated class. From that, if we later refactor our code and rename such a class, we run the risk of forgetting to rename the associated .xib
.
While the error will often be easy to catch, if the .xib
is used in a remote section of its app, it might go unnoticed for sometime. Fortunately it's possible to build custom test predicates that will assert that 1) for a given class, there exists a .nib
with the same name in a given Bundle
, 2) for all the .nib
in a given Bundle
, there exists a class with the same name.
import XCTest
public func XCTAssertClassHasNib(_ class: AnyClass, bundle: Bundle, file: StaticString = #file, line: UInt = #line) {
let associatedNibURL = bundle.url(forResource: String(describing: `class`), withExtension: "nib")
XCTAssertNotNil(associatedNibURL, "Class \"\(`class`)\" has no associated nib file", file: file, line: line)
}
public func XCTAssertNibHaveClasses(_ bundle: Bundle, file: StaticString = #file, line: UInt = #line) {
guard let bundleName = bundle.infoDictionary?["CFBundleName"] as? String,
let basePath = bundle.resourcePath,
let enumerator = FileManager.default.enumerator(at: URL(fileURLWithPath: basePath),
includingPropertiesForKeys: nil,
options: [.skipsHiddenFiles, .skipsSubdirectoryDescendants]) else { return }
var nibFilesURLs = [URL]()
for case let fileURL as URL in enumerator {
if fileURL.pathExtension.uppercased() == "NIB" {
nibFilesURLs.append(fileURL)
}
}
nibFilesURLs.map { $0.lastPathComponent }
.compactMap { $0.split(separator: ".").first }
.map { String($0) }
.forEach {
let associatedClass: AnyClass? = bundle.classNamed("\(bundleName).\($0)")
XCTAssertNotNil(associatedClass, "File \"\($0).nib\" has no associated class", file: file, line: line)
}
}
XCTAssertClassHasNib(MyFirstTableViewCell.self, bundle: Bundle(for: AppDelegate.self))
XCTAssertClassHasNib(MySecondTableViewCell.self, bundle: Bundle(for: AppDelegate.self))
XCTAssertNibHaveClasses(Bundle(for: AppDelegate.self))
Many thanks Benjamin Lavialle for coming up with the idea behind the second test predicate.
Seasoned Swift developers know it: a protocol with associated type (PAT) "can only be used as a generic constraint because it has Self or associated type requirements". When we really need to use a PAT to type a variable, the goto workaround is to use a type-erased wrapper.
While this solution works perfectly, it requires a fair amount of boilerplate code. In instances where we are only interested in exposing one particular function of the PAT, a shorter approach using function types is possible.
import Foundation
import UIKit
protocol Configurable {
associatedtype Model
func configure(with model: Model)
}
typealias Configurator<Model> = (Model) -> ()
extension UILabel: Configurable {
func configure(with model: String) {
self.text = model
}
}
let label = UILabel()
let configurator: Configurator<String> = label.configure
configurator("Foo")
label.text // "Foo"
UIKit
exposes a very powerful and simple API to perform view animations. However, this API can become a little bit quirky to use when we want to perform animations sequentially, because it involves nesting closure within one another, which produces notoriously hard to maintain code.
Nonetheless, it's possible to define a rather simple class, that will expose a really nicer API for this particular use case 👌
import Foundation
import UIKit
class AnimationSequence {
typealias Animations = () -> Void
private let current: Animations
private let duration: TimeInterval
private var next: AnimationSequence? = nil
init(animations: @escaping Animations, duration: TimeInterval) {
self.current = animations
self.duration = duration
}
@discardableResult func append(animations: @escaping Animations, duration: TimeInterval) -> AnimationSequence {
var lastAnimation = self
while let nextAnimation = lastAnimation.next {
lastAnimation = nextAnimation
}
lastAnimation.next = AnimationSequence(animations: animations, duration: duration)
return self
}
func run() {
UIView.animate(withDuration: duration, animations: current, completion: { finished in
if finished, let next = self.next {
next.run()
}
})
}
}
var firstView = UIView()
var secondView = UIView()
firstView.alpha = 0
secondView.alpha = 0
AnimationSequence(animations: { firstView.alpha = 1.0 }, duration: 1)
.append(animations: { secondView.alpha = 1.0 }, duration: 0.5)
.append(animations: { firstView.alpha = 0.0 }, duration: 2.0)
.run()
Debouncing is a very useful tool when dealing with UI inputs. Consider a search bar, whose content is used to query an API. It wouldn't make sense to perform a request for every character the user is typing, because as soon as a new character is entered, the result of the previous request has become irrelevant.
Instead, our code will perform much better if we "debounce" the API call, meaning that we will wait until some delay has passed, without the input being modified, before actually performing the call.
import Foundation
func debounced(delay: TimeInterval, queue: DispatchQueue = .main, action: @escaping (() -> Void)) -> () -> Void {
var workItem: DispatchWorkItem?
return {
workItem?.cancel()
workItem = DispatchWorkItem(block: action)
queue.asyncAfter(deadline: .now() + delay, execute: workItem!)
}
}
let debouncedPrint = debounced(delay: 1.0) { print("Action performed!") }
debouncedPrint()
debouncedPrint()
debouncedPrint()
// After a 1 second delay, this gets
// printed only once to the console:
// Action performed!
Optional
booleansWhen we need to apply the standard boolean operators to Optional
booleans, we often end up with a syntax unnecessarily crowded with unwrapping operations. By taking a cue from the world of three-valued logics, we can define a couple operators that make working with Bool?
values much nicer.
import Foundation
func && (lhs: Bool?, rhs: Bool?) -> Bool? {
switch (lhs, rhs) {
case (false, _), (_, false):
return false
case let (unwrapLhs?, unwrapRhs?):
return unwrapLhs && unwrapRhs
default:
return nil
}
}
func || (lhs: Bool?, rhs: Bool?) -> Bool? {
switch (lhs, rhs) {
case (true, _), (_, true):
return true
case let (unwrapLhs?, unwrapRhs?):
return unwrapLhs || unwrapRhs
default:
return nil
}
}
false && nil // false
true && nil // nil
[true, nil, false].reduce(true, &&) // false
nil || true // true
nil || false // nil
[true, nil, false].reduce(false, ||) // true
Sequence
Transforming a Sequence
in order to remove all the duplicate values it contains is a classic use case. To implement it, one could be tempted to transform the Sequence
into a Set
, then back to an Array
. The downside with this approach is that it will not preserve the order of the sequence, which can definitely be a dealbreaker. Using reduce()
it is possible to provide a concise implementation that preserves ordering:
import Foundation
extension Sequence where Element: Equatable {
func duplicatesRemoved() -> [Element] {
return reduce([], { $0.contains($1) ? $0 : $0 + [$1] })
}
}
let data = [2, 5, 2, 3, 6, 5, 2]
data.duplicatesRemoved() // [2, 5, 3, 6]
Optional strings are very common in Swift code, for instance many objects from UIKit
expose the text they display as a String?
. Many times you will need to manipulate this data as an unwrapped String
, with a default value set to the empty string for nil
cases.
While the nil-coalescing operator (e.g. ??
) is a perfectly fine way to a achieve this goal, defining a computed variable like orEmpty
can help a lot in cleaning the syntax.
import Foundation
import UIKit
extension Optional where Wrapped == String {
var orEmpty: String {
switch self {
case .some(let value):
return value
case .none:
return ""
}
}
}
func doesNotWorkWithOptionalString(_ param: String) {
// do something with `param`
}
let label = UILabel()
label.text = "This is some text."
doesNotWorkWithOptionalString(label.text.orEmpty)
Every seasoned iOS developers knows it: objects from UIKit
can only be accessed from the main thread. Any attempt to access them from a background thread is a guaranteed crash.
Still, running a costly computation on the background, and then using it to update the UI can be a common pattern.
In such cases you can rely on asyncUI
to encapsulate all the boilerplate code.
import Foundation
import UIKit
func asyncUI<T>(_ computation: @autoclosure @escaping () -> T, qos: DispatchQoS.QoSClass = .userInitiated, _ completion: @escaping (T) -> Void) {
DispatchQueue.global(qos: qos).async {
let value = computation()
DispatchQueue.main.async {
completion(value)
}
}
}
let label = UILabel()
func costlyComputation() -> Int { return (0..<10_000).reduce(0, +) }
asyncUI(costlyComputation()) { value in
label.text = "\(value)"
}
A debug view, from which any controller of an app can be instantiated and pushed on the navigation stack, has the potential to bring some real value to a development process. A requirement to build such a view is to have a list of all the classes from a given Bundle
that inherit from UIViewController
. With the following extension
, retrieving this list becomes a piece of cake 🍰
import Foundation
import UIKit
import ObjectiveC
extension Bundle {
func viewControllerTypes() -> [UIViewController.Type] {
guard let bundlePath = self.executablePath else { return [] }
var size: UInt32 = 0
var rawClassNames: UnsafeMutablePointer<UnsafePointer<Int8>>!
var parsedClassNames = [String]()
rawClassNames = objc_copyClassNamesForImage(bundlePath, &size)
for index in 0..<size {
let className = rawClassNames[Int(index)]
if let name = NSString.init(utf8String:className) as String?,
NSClassFromString(name) is UIViewController.Type {
parsedClassNames.append(name)
}
}
return parsedClassNames
.sorted()
.compactMap { NSClassFromString($0) as? UIViewController.Type }
}
}
// Fetch all view controller types in UIKit
Bundle(for: UIViewController.self).viewControllerTypes()
I share the credit for this tip with Benoît Caron.
Update As it turns out, map
is actually a really bad name for this function, because it does not preserve composition of transformations, a property that is required to fit the definition of a real map
function.
Surprisingly enough, the standard library doesn't define a map()
function for dictionaries that allows to map both keys
and values
into a new Dictionary
. Nevertheless, such a function can be helpful, for instance when converting data across different frameworks.
import Foundation
extension Dictionary {
func map<T: Hashable, U>(_ transform: (Key, Value) throws -> (T, U)) rethrows -> [T: U] {
var result: [T: U] = [:]
for (key, value) in self {
let (transformedKey, transformedValue) = try transform(key, value)
result[transformedKey] = transformedValue
}
return result
}
}
let data = [0: 5, 1: 6, 2: 7]
data.map { ("\($0)", $1 * $1) } // ["2": 49, "0": 25, "1": 36]
nil
valuesSwift provides the function compactMap()
, that can be used to remove nil
values from a Sequence
of optionals when calling it with an argument that just returns its parameter (i.e. compactMap { $0 }
). Still, for such use cases it would be nice to get rid of the trailing closure.
The implementation isn't as straightforward as your usual extension
, but once it has been written, the call site definitely gets cleaner 👌
import Foundation
protocol OptionalConvertible {
associatedtype Wrapped
func asOptional() -> Wrapped?
}
extension Optional: OptionalConvertible {
func asOptional() -> Wrapped? {
return self
}
}
extension Sequence where Element: OptionalConvertible {
func compacted() -> [Element.Wrapped] {
return compactMap { $0.asOptional() }
}
}
let data = [nil, 1, 2, nil, 3, 5, nil, 8, nil]
data.compacted() // [1, 2, 3, 5, 8]
It might happen that your code has to deal with values that come with an expiration date. In a game, it could be a score multiplier that will only last for 30 seconds. Or it could be an authentication token for an API, with a 15 minutes lifespan. In both instances you can rely on the type Expirable
to encapsulate the expiration logic.
import Foundation
struct Expirable<T> {
private var innerValue: T
private(set) var expirationDate: Date
var value: T? {
return hasExpired() ? nil : innerValue
}
init(value: T, expirationDate: Date) {
self.innerValue = value
self.expirationDate = expirationDate
}
init(value: T, duration: Double) {
self.innerValue = value
self.expirationDate = Date().addingTimeInterval(duration)
}
func hasExpired() -> Bool {
return expirationDate < Date()
}
}
let expirable = Expirable(value: 42, duration: 3)
sleep(2)
expirable.value // 42
sleep(2)
expirable.value // nil
I share the credit for this tip with Benoît Caron.
map()
Almost all Apple devices able to run Swift code are powered by a multi-core CPU, consequently making a good use of parallelism is a great way to improve code performance. map()
is a perfect candidate for such an optimization, because it is almost trivial to define a parallel implementation.
import Foundation
extension Array {
func parallelMap<T>(_ transform: (Element) -> T) -> [T] {
let res = UnsafeMutablePointer<T>.allocate(capacity: count)
DispatchQueue.concurrentPerform(iterations: count) { i in
res[i] = transform(self[i])
}
let finalResult = Array<T>(UnsafeBufferPointer(start: res, count: count))
res.deallocate(capacity: count)
return finalResult
}
}
let array = (0..<1_000).map { $0 }
func work(_ n: Int) -> Int {
return (0..<n).reduce(0, +)
}
array.parallelMap { work($0) }
🚨 Make sure to only use parallelMap()
when the transform
function actually performs some costly computations. Otherwise performances will be systematically slower than using map()
, because of the multithreading overhead.
During development of a feature that performs some heavy computations, it can be helpful to measure just how much time a chunk of code takes to run. The time()
function is a nice tool for this purpose, because of how simple it is to add and then to remove when it is no longer needed.
import Foundation
func time(averagedExecutions: Int = 1, _ code: () -> Void) {
let start = Date()
for _ in 0..<averagedExecutions { code() }
let end = Date()
let duration = end.timeIntervalSince(start) / Double(averagedExecutions)
print("time: \(duration)")
}
time {
(0...10_000).map { $0 * $0 }
}
// time: 0.183973908424377
Concurrency is definitely one of those topics were the right encapsulation bears the potential to make your life so much easier. For instance, with this piece of code you can easily launch two computations in parallel, and have the results returned in a tuple.
import Foundation
func parallel<T, U>(_ left: @autoclosure () -> T, _ right: @autoclosure () -> U) -> (T, U) {
var leftRes: T?
var rightRes: U?
DispatchQueue.concurrentPerform(iterations: 2, execute: { id in
if id == 0 {
leftRes = left()
} else {
rightRes = right()
}
})
return (leftRes!, rightRes!)
}
let values = (1...100_000).map { $0 }
let results = parallel(values.map { $0 * $0 }, values.reduce(0, +))
Swift exposes three special variables #file
, #line
and #function
, that are respectively set to the name of the current file, line and function. Those variables become very useful when writing custom logging functions or test predicates.
import Foundation
func log(_ message: String, _ file: String = #file, _ line: Int = #line, _ function: String = #function) {
print("[\(file):\(line)] \(function) - \(message)")
}
func foo() {
log("Hello world!")
}
foo() // [MyPlayground.playground:8] foo() - Hello world!
Swift 4.1 has introduced a new feature called Conditional Conformance, which allows a type to implement a protocol only when its generic type also does.
With this addition it becomes easy to let Optional
implement Comparable
only when Wrapped
also implements Comparable
:
import Foundation
extension Optional: Comparable where Wrapped: Comparable {
public static func < (lhs: Optional, rhs: Optional) -> Bool {
switch (lhs, rhs) {
case let (lhs?, rhs?):
return lhs < rhs
case (nil, _?):
return true // anything is greater than nil
case (_?, nil):
return false // nil in smaller than anything
case (nil, nil):
return true // nil is not smaller than itself
}
}
}
let data: [Int?] = [8, 4, 3, nil, 12, 4, 2, nil, -5]
data.sorted() // [nil, nil, Optional(-5), Optional(2), Optional(3), Optional(4), Optional(4), Optional(8), Optional(12)]
Any attempt to access an Array
beyond its bounds will result in a crash. While it's possible to write conditions such as if index < array.count { array[index] }
in order to prevent such crashes, this approach will rapidly become cumbersome.
A great thing is that this condition can be encapsulated in a custom subscript
that will work on any Collection
:
import Foundation
extension Collection {
subscript (safe index: Index) -> Element? {
return indices.contains(index) ? self[index] : nil
}
}
let data = [1, 3, 4]
data[safe: 1] // Optional(3)
data[safe: 10] // nil
Subscripting a string with a range can be very cumbersome in Swift 4. Let's face it, no one wants to write lines like someString[index(startIndex, offsetBy: 0)..<index(startIndex, offsetBy: 10)]
on a regular basis.
Luckily, with the addition of one clever extension, strings can be sliced as easily as arrays 🎉
import Foundation
extension String {
public subscript(value: CountableClosedRange<Int>) -> Substring {
get {
return self[index(startIndex, offsetBy: value.lowerBound)...index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: CountableRange<Int>) -> Substring {
get {
return self[index(startIndex, offsetBy: value.lowerBound)..<index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: PartialRangeUpTo<Int>) -> Substring {
get {
return self[..<index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: PartialRangeThrough<Int>) -> Substring {
get {
return self[...index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: PartialRangeFrom<Int>) -> Substring {
get {
return self[index(startIndex, offsetBy: value.lowerBound)...]
}
}
}
let data = "This is a string!"
data[..<4] // "This"
data[5..<9] // "is a"
data[10...] // "string!"
By using a KeyPath
along with a generic type, a very clean and concise syntax for sorting data can be implemented:
import Foundation
extension Sequence {
func sorted<T: Comparable>(by attribute: KeyPath<Element, T>) -> [Element] {
return sorted(by: { $0[keyPath: attribute] < $1[keyPath: attribute] })
}
}
let data = ["Some", "words", "of", "different", "lengths"]
data.sorted(by: \.count) // ["of", "Some", "words", "lengths", "different"]
If you like this syntax, make sure to checkout KeyPathKit!
By capturing a local variable in a returned closure, it is possible to manufacture cache-efficient versions of pure functions. Be careful though, this trick only works with non-recursive function!
import Foundation
func cached<In: Hashable, Out>(_ f: @escaping (In) -> Out) -> (In) -> Out {
var cache = [In: Out]()
return { (input: In) -> Out in
if let cachedValue = cache[input] {
return cachedValue
} else {
let result = f(input)
cache[input] = result
return result
}
}
}
let cachedCos = cached { (x: Double) in cos(x) }
cachedCos(.pi * 2) // value of cos for 2π is now cached
When distinguishing between complex boolean conditions, using a switch
statement along with pattern matching can be more readable than the classic series of if {} else if {}
.
import Foundation
let expr1: Bool
let expr2: Bool
let expr3: Bool
if expr1 && !expr3 {
functionA()
} else if !expr2 && expr3 {
functionB()
} else if expr1 && !expr2 && expr3 {
functionC()
}
switch (expr1, expr2, expr3) {
case (true, _, false):
functionA()
case (_, false, true):
functionB()
case (true, false, true):
functionC()
default:
break
}
Using map()
on a range makes it easy to generate an array of data.
import Foundation
func randomInt() -> Int { return Int(arc4random()) }
let randomArray = (1...10).map { _ in randomInt() }
Using @autoclosure
enables the compiler to automatically wrap an argument within a closure, thus allowing for a very clean syntax at call sites.
import UIKit
extension UIView {
class func animate(withDuration duration: TimeInterval, _ animations: @escaping @autoclosure () -> Void) {
UIView.animate(withDuration: duration, animations: animations)
}
}
let view = UIView()
UIView.animate(withDuration: 0.3, view.backgroundColor = .orange)
When working with RxSwift, it's very easy to observe both the current and previous value of an observable sequence by simply introducing a shift using skip()
.
import RxSwift
let values = Observable.of(4, 8, 15, 16, 23, 42)
let newAndOld = Observable.zip(values, values.skip(1)) { (previous: $0, current: $1) }
.subscribe(onNext: { pair in
print("current: \(pair.current) - previous: \(pair.previous)")
})
//current: 8 - previous: 4
//current: 15 - previous: 8
//current: 16 - previous: 15
//current: 23 - previous: 16
//current: 42 - previous: 23
Using protocols such as ExpressibleByStringLiteral
it is possible to provide an init
that will be automatically when a literal value is provided, allowing for nice and short syntax. This can be very helpful when writing mock or test data.
import Foundation
extension URL: ExpressibleByStringLiteral {
public init(stringLiteral value: String) {
self.init(string: value)!
}
}
let url: URL = "http://www.google.fr"
NSURLConnection.canHandle(URLRequest(url: "http://www.google.fr"))
Through some clever use of Swift private
visibility it is possible to define a container that holds any untrusted value (such as a user input) from which the only way to retrieve the value is by making it successfully pass a validation test.
import Foundation
struct Untrusted<T> {
private(set) var value: T
}
protocol Validator {
associatedtype T
static func validation(value: T) -> Bool
}
extension Validator {
static func validate(untrusted: Untrusted<T>) -> T? {
if self.validation(value: untrusted.value) {
return untrusted.value
} else {
return nil
}
}
}
struct FrenchPhoneNumberValidator: Validator {
static func validation(value: String) -> Bool {
return (value.count) == 10 && CharacterSet(charactersIn: value).isSubset(of: CharacterSet.decimalDigits)
}
}
let validInput = Untrusted(value: "0122334455")
let invalidInput = Untrusted(value: "0123")
FrenchPhoneNumberValidator.validate(untrusted: validInput) // returns "0122334455"
FrenchPhoneNumberValidator.validate(untrusted: invalidInput) // returns nil
With the addition of keypaths in Swift 4, it is now possible to easily implement the builder pattern, that allows the developer to clearly separate the code that initializes a value from the code that uses it, without the burden of defining a factory method.
import UIKit
protocol With {}
extension With where Self: AnyObject {
@discardableResult
func with<T>(_ property: ReferenceWritableKeyPath<Self, T>, setTo value: T) -> Self {
self[keyPath: property] = value
return self
}
}
extension UIView: With {}
let view = UIView()
let label = UILabel()
.with(\.textColor, setTo: .red)
.with(\.text, setTo: "Foo")
.with(\.textAlignment, setTo: .right)
.with(\.layer.cornerRadius, setTo: 5)
view.addSubview(label)
🚨 The Swift compiler does not perform OS availability checks on properties referenced by keypaths. Any attempt to use a KeyPath
for an unavailable property will result in a runtime crash.
I share the credit for this tip with Marion Curtil.
When a type stores values for the sole purpose of parametrizing its functions, it’s then possible to not store the values but directly the function, with no discernable difference at the call site.
import Foundation
struct MaxValidator {
let max: Int
let strictComparison: Bool
func isValid(_ value: Int) -> Bool {
return self.strictComparison ? value < self.max : value <= self.max
}
}
struct MaxValidator2 {
var isValid: (_ value: Int) -> Bool
init(max: Int, strictComparison: Bool) {
self.isValid = strictComparison ? { $0 < max } : { $0 <= max }
}
}
MaxValidator(max: 5, strictComparison: true).isValid(5) // false
MaxValidator2(max: 5, strictComparison: false).isValid(5) // true
Functions are first-class citizen types in Swift, so it is perfectly legal to define operators for them.
import Foundation
let firstRange = { (0...3).contains($0) }
let secondRange = { (5...6).contains($0) }
func ||(_ lhs: @escaping (Int) -> Bool, _ rhs: @escaping (Int) -> Bool) -> (Int) -> Bool {
return { value in
return lhs(value) || rhs(value)
}
}
(firstRange || secondRange)(2) // true
(firstRange || secondRange)(4) // false
(firstRange || secondRange)(6) // true
Typealiases are great to express function signatures in a more comprehensive manner, which then enables us to easily define functions that operate on them, resulting in a nice way to write and use some powerful API.
import Foundation
typealias RangeSet = (Int) -> Bool
func union(_ left: @escaping RangeSet, _ right: @escaping RangeSet) -> RangeSet {
return { left($0) || right($0) }
}
let firstRange = { (0...3).contains($0) }
let secondRange = { (5...6).contains($0) }
let unionRange = union(firstRange, secondRange)
unionRange(2) // true
unionRange(4) // false
By returning a closure that captures a local variable, it's possible to encapsulate a mutable state within a function.
import Foundation
func counterFactory() -> () -> Int {
var counter = 0
return {
counter += 1
return counter
}
}
let counter = counterFactory()
counter() // returns 1
counter() // returns 2
⚠️ Since Swift 4.2,
allCases
can now be synthesized at compile-time by simply conforming to the protocolCaseIterable
. The implementation below should no longer be used in production code.
Through some clever leveraging of how enums are stored in memory, it is possible to generate an array that contains all the possible cases of an enum. This can prove particularly useful when writing unit tests that consume random data.
import Foundation
enum MyEnum { case first; case second; case third; case fourth }
protocol EnumCollection: Hashable {
static var allCases: [Self] { get }
}
extension EnumCollection {
public static var allCases: [Self] {
var i = 0
return Array(AnyIterator {
let next = withUnsafePointer(to: &i) {
$0.withMemoryRebound(to: Self.self, capacity: 1) { $0.pointee }
}
if next.hashValue != i { return nil }
i += 1
return next
})
}
}
extension MyEnum: EnumCollection { }
MyEnum.allCases // [.first, .second, .third, .fourth]
The if-let syntax is a great way to deal with optional values in a safe manner, but at times it can prove to be just a little bit to cumbersome. In such cases, using the Optional.map()
function is a nice way to achieve a shorter code while retaining safeness and readability.
import UIKit
let date: Date? = Date() // or could be nil, doesn't matter
let formatter = DateFormatter()
let label = UILabel()
if let safeDate = date {
label.text = formatter.string(from: safeDate)
}
label.text = date.map { return formatter.string(from: $0) }
label.text = date.map(formatter.string(from:)) // even shorter, tough less readable
📣 NEW 📣 Swift Tips are now available on YouTube 👇
Summary
String
interpolationstructs
NSAttributedString
through a Function Builderswitch
and if
as expressionsguard
statementsinit
without loosing the compiler-generated oneenum
Never
to represent impossible code pathsDecodable
enum
[weak self]
and guard
userInfo
Dictionary
typealias
to its fullestforEach
reduce()
Optional
booleansSequence
nil
valuesmap()
Tips
Author: vincent-pradeilles
Source code: https://github.com/vincent-pradeilles/swift-tips
License: MIT license
#swift
1647234000
Table of Contents
We use nginx in our company lab environment. It often happens that my colleagues have developed an application that is now deployed in our Stage or Prod environment. To make this application accessible nginx has to be adapted. Most of the time my colleagues don't have the permission to access the server and change the configuration files and since I don't feel like doing this for everyone anymore I thought a UI could help us all. If you feel the same way I wish you a lot of fun with the application and I am looking forward to your feedback, change requests or even a star.
Containerization is now state of the art and therefore the application is delivered in a container.
-d
run as deamon in background--restart=always
restart on crash or server reboot--name nginxui
give the container a name-v /etc/nginx:/etc/nginx
map the hosts nginx directory into the container-p 8080:8080
map host port 8080 to docker container port 8080docker run -d --restart=always --name nginxui -v /etc/nginx:/etc/nginx -p 8080:8080 schenkd/nginx-ui:latest
Repository @ DockerHub
Docker Compose excerpt
# Docker Compose excerpt
services:
nginx-ui:
image: schenkd/nginx-ui:latest
ports:
- 8080:8080
volumes:
- nginx:/etc/nginx
With the menu item Main Config the Nginx specific configuration files can be extracted and updated. These are dynamically read from the Nginx directory. If a file has been added manually, it is immediately integrated into the Nginx UI Main Config menu item.
Adding a domain opens an exclusive editing window for the configuration file. This can be applied, deleted and enabled/disabled.
In general, this app does not come with authentication. However, it is easy to setup basic auth to restrict unwanted access. Here is how this can be done when using nginx.
apache2-utils
(Debian, Ubuntu) or httpd-tools
(RHEL/CentOS/Oracle Linux) is installed-c
flag, if you have created a user before, since it creates the inital user/passwort filesudo htpasswd -c /etc/apache2/.htpasswd user1
The following example adds basic auth to our nginxui app running in a docker container with a mapped port 8080. In this case, it will be accessible via nginx.mydomain.com
server {
server_name nginx.mydomain.com;
location / {
proxy_pass http://127.0.0.1:8080/;
}
auth_basic "nginxui secured";
auth_basic_user_file /etc/apache2/.htpasswd;
# [...] ommited ssl configuration
}
/etc/nginx/my.conf
filenginx -t
to make sure, that your config is validsystemctl restart nginx
(or equivalent) to restart your nginx and apply the new settingsAuthor: schenkd
Source Code: https://github.com/schenkd/nginx-ui
License: MIT License
1659004860
Asset Sync
Synchronises Assets between Rails and S3.
Asset Sync is built to run with the new Rails Asset Pipeline feature introduced in Rails 3.1. After you run bundle exec rake assets:precompile your assets will be synchronised to your S3 bucket, optionally deleting unused files and only uploading the files it needs to.
This was initially built and is intended to work on Heroku but can work on any platform.
Upgraded from 1.x? Read UPGRADING.md
Since 2.x, Asset Sync depends on gem fog-core
instead of fog
.
This is due to fog
is including many unused storage provider gems as its dependencies.
Asset Sync has no idea about what provider will be used,
so you are responsible for bundling the right gem for the provider to be used.
In your Gemfile:
gem "asset_sync"
gem "fog-aws"
Or, to use Azure Blob storage, configure as this.
gem "asset_sync"
gem "gitlab-fog-azure-rm"
# This gem seems unmaintianed
# gem "fog-azure-rm"
To use Backblaze B2, insert these.
gem "asset_sync"
gem "fog-backblaze"
It's possible to improve asset:precompile time if you are using Rails 3.2.x the main source of which being compilation of non-digest assets.
turbo-sprockets-rails3 solves this by only compiling digest assets. Thus cutting compile time in half.
NOTE: It will be deprecated in Rails 4 as sprockets-rails has been extracted out of Rails and will only compile digest assets by default.
Configure config/environments/production.rb to use Amazon S3 as the asset host and ensure precompiling is enabled.
#config/environments/production.rb
config.action_controller.asset_host = "//#{ENV['FOG_DIRECTORY']}.s3.amazonaws.com"
Or, to use Google Storage Cloud, configure as this.
#config/environments/production.rb
config.action_controller.asset_host = "//#{ENV['FOG_DIRECTORY']}.storage.googleapis.com"
Or, to use Azure Blob storage, configure as this.
#config/environments/production.rb
config.action_controller.asset_host = "//#{ENV['AZURE_STORAGE_ACCOUNT_NAME']}.blob.core.windows.net/#{ENV['FOG_DIRECTORY']}"
Or, to use Backblaze B2, configure as this.
#config/environments/production.rb
config.action_controller.asset_host = "//f000.backblazeb2.com/file/#{ENV['FOG_DIRECTORY']}"
On HTTPS: the exclusion of any protocol in the asset host declaration above will allow browsers to choose the transport mechanism on the fly. So if your application is available under both HTTP and HTTPS the assets will be served to match.
The only caveat with this is that your S3 bucket name must not contain any periods so, mydomain.com.s3.amazonaws.com for example would not work under HTTPS as SSL certificates from Amazon would interpret our bucket name as not a subdomain of s3.amazonaws.com, but a multi level subdomain. To avoid this don't use a period in your subdomain or switch to the other style of S3 URL.
config.action_controller.asset_host = "//s3.amazonaws.com/#{ENV['FOG_DIRECTORY']}"
Or, to use Google Storage Cloud, configure as this.
config.action_controller.asset_host = "//storage.googleapis.com/#{ENV['FOG_DIRECTORY']}"
Or, to use Azure Blob storage, configure as this.
#config/environments/production.rb
config.action_controller.asset_host = "//#{ENV['AZURE_STORAGE_ACCOUNT_NAME']}.blob.core.windows.net/#{ENV['FOG_DIRECTORY']}"
On non default S3 bucket region: If your bucket is set to a region that is not the default US Standard (us-east-1) you must use the first style of url //#{ENV['FOG_DIRECTORY']}.s3.amazonaws.com
or amazon will return a 301 permanently moved when assets are requested. Note the caveat above about bucket names and periods.
If you wish to have your assets sync to a sub-folder of your bucket instead of into the root add the following to your production.rb
file
# store assets in a 'folder' instead of bucket root
config.assets.prefix = "/production/assets"
Also, ensure the following are defined (in production.rb or application.rb)
Additionally, if you depend on any configuration that is setup in your initializers
you will need to ensure that
AssetSync supports the following methods of configuration.
Using the Built-in Initializer is the default method and is supposed to be used with environment variables. It's the recommended approach for deployments on Heroku.
If you need more control over configuration you will want to use a custom rails initializer.
Configuration using a YAML file (a common strategy for Capistrano deployments) is also supported.
The recommend way to configure asset_sync is by using environment variables however it's up to you, it will work fine if you hard code them too. The main reason why using environment variables is recommended is so your access keys are not checked into version control.
The Built-in Initializer will configure AssetSync based on the contents of your environment variables.
Add your configuration details to heroku
heroku config:add AWS_ACCESS_KEY_ID=xxxx
heroku config:add AWS_SECRET_ACCESS_KEY=xxxx
heroku config:add FOG_DIRECTORY=xxxx
heroku config:add FOG_PROVIDER=AWS
# and optionally:
heroku config:add FOG_REGION=eu-west-1
heroku config:add ASSET_SYNC_GZIP_COMPRESSION=true
heroku config:add ASSET_SYNC_MANIFEST=true
heroku config:add ASSET_SYNC_EXISTING_REMOTE_FILES=keep
Or add to a traditional unix system
export AWS_ACCESS_KEY_ID=xxxx
export AWS_SECRET_ACCESS_KEY=xxxx
export FOG_DIRECTORY=xxxx
Rackspace configuration is also supported
heroku config:add RACKSPACE_USERNAME=xxxx
heroku config:add RACKSPACE_API_KEY=xxxx
heroku config:add FOG_DIRECTORY=xxxx
heroku config:add FOG_PROVIDER=Rackspace
Google Storage Cloud configuration is supported as well. The preferred option is using the GCS JSON API which requires that you create an appropriate service account, generate the signatures and make them accessible to asset sync at the prescribed location
heroku config:add FOG_PROVIDER=Google
heroku config:add GOOGLE_PROJECT=xxxx
heroku config:add GOOGLE_JSON_KEY_LOCATION=xxxx
heroku config:add FOG_DIRECTORY=xxxx
If using the S3 API the following config is required
heroku config:add FOG_PROVIDER=Google
heroku config:add GOOGLE_STORAGE_ACCESS_KEY_ID=xxxx
heroku config:add GOOGLE_STORAGE_SECRET_ACCESS_KEY=xxxx
heroku config:add FOG_DIRECTORY=xxxx
The Built-in Initializer also sets the AssetSync default for existing_remote_files to keep.
If you want to enable some of the advanced configuration options you will want to create your own initializer.
Run the included Rake task to generate a starting point.
rails g asset_sync:install --provider=Rackspace
rails g asset_sync:install --provider=AWS
rails g asset_sync:install --provider=AzureRM
rails g asset_sync:install --provider=Backblaze
The generator will create a Rails initializer at config/initializers/asset_sync.rb
.
AssetSync.configure do |config|
config.fog_provider = 'AWS'
config.fog_directory = ENV['FOG_DIRECTORY']
config.aws_access_key_id = ENV['AWS_ACCESS_KEY_ID']
config.aws_secret_access_key = ENV['AWS_SECRET_ACCESS_KEY']
config.aws_session_token = ENV['AWS_SESSION_TOKEN'] if ENV.key?('AWS_SESSION_TOKEN')
# Don't delete files from the store
# config.existing_remote_files = 'keep'
#
# Increase upload performance by configuring your region
# config.fog_region = 'eu-west-1'
#
# Set `public` option when uploading file depending on value,
# Setting to "default" makes asset sync skip setting the option
# Possible values: true, false, "default" (default: true)
# config.fog_public = true
#
# Change AWS signature version. Default is 4
# config.aws_signature_version = 4
#
# Change canned ACL of uploaded object. Default is unset. Will override fog_public if set.
# Choose from: private | public-read | public-read-write | aws-exec-read |
# authenticated-read | bucket-owner-read | bucket-owner-full-control
# config.aws_acl = nil
#
# Change host option in fog (only if you need to)
# config.fog_host = 's3.amazonaws.com'
#
# Change port option in fog (only if you need to)
# config.fog_port = "9000"
#
# Use http instead of https.
# config.fog_scheme = 'http'
#
# Automatically replace files with their equivalent gzip compressed version
# config.gzip_compression = true
#
# Use the Rails generated 'manifest.yml' file to produce the list of files to
# upload instead of searching the assets directory.
# config.manifest = true
#
# Upload the manifest file also.
# config.include_manifest = false
#
# Upload files concurrently
# config.concurrent_uploads = false
#
# Number of threads when concurrent_uploads is enabled
# config.concurrent_uploads_max_threads = 10
#
# Path to cache file to skip scanning remote
# config.remote_file_list_cache_file_path = './.asset_sync_remote_file_list_cache.json'
#
# Fail silently. Useful for environments such as Heroku
# config.fail_silently = true
#
# Log silently. Default is `true`. But you can set it to false if more logging message are preferred.
# Logging messages are sent to `STDOUT` when `log_silently` is falsy
# config.log_silently = true
#
# Allow custom assets to be cacheable. Note: The base filename will be matched
# If you have an asset with name `app.0b1a4cd3.js`, only `app.0b1a4cd3` will need to be matched
# only one of `cache_asset_regexp` or `cache_asset_regexps` is allowed.
# config.cache_asset_regexp = /\.[a-f0-9]{8}$/i
# config.cache_asset_regexps = [ /\.[a-f0-9]{8}$/i, /\.[a-f0-9]{20}$/i ]
end
Run the included Rake task to generate a starting point.
rails g asset_sync:install --use-yml --provider=Rackspace
rails g asset_sync:install --use-yml --provider=AWS
rails g asset_sync:install --use-yml --provider=AzureRM
rails g asset_sync:install --use-yml --provider=Backblaze
The generator will create a YAML file at config/asset_sync.yml
.
defaults: &defaults
fog_provider: "AWS"
fog_directory: "rails-app-assets"
aws_access_key_id: "<%= ENV['AWS_ACCESS_KEY_ID'] %>"
aws_secret_access_key: "<%= ENV['AWS_SECRET_ACCESS_KEY'] %>"
# To use AWS reduced redundancy storage.
# aws_reduced_redundancy: true
#
# You may need to specify what region your storage bucket is in
# fog_region: "eu-west-1"
#
# Change AWS signature version. Default is 4
# aws_signature_version: 4
#
# Change canned ACL of uploaded object. Default is unset. Will override fog_public if set.
# Choose from: private | public-read | public-read-write | aws-exec-read |
# authenticated-read | bucket-owner-read | bucket-owner-full-control
# aws_acl: null
#
# Change host option in fog (only if you need to)
# fog_host: "s3.amazonaws.com"
#
# Use http instead of https. Default should be "https" (at least for fog-aws)
# fog_scheme: "http"
existing_remote_files: keep # Existing pre-compiled assets on S3 will be kept
# To delete existing remote files.
# existing_remote_files: delete
# To ignore existing remote files and overwrite.
# existing_remote_files: ignore
# Automatically replace files with their equivalent gzip compressed version
# gzip_compression: true
# Fail silently. Useful for environments such as Heroku
# fail_silently: true
# Always upload. Useful if you want to overwrite specific remote assets regardless of their existence
# eg: Static files in public often reference non-fingerprinted application.css
# note: You will still need to expire them from the CDN's edge cache locations
# always_upload: ['application.js', 'application.css', !ruby/regexp '/application-/\d{32}\.css/']
# Ignored files. Useful if there are some files that are created dynamically on the server and you don't want to upload on deploy.
# ignored_files: ['ignore_me.js', !ruby/regexp '/ignore_some/\d{32}\.css/']
# Allow custom assets to be cacheable. Note: The base filename will be matched
# If you have an asset with name "app.0b1a4cd3.js", only "app.0b1a4cd3" will need to be matched
# cache_asset_regexps: ['cache_me.js', !ruby/regexp '/cache_some\.\d{8}\.css/']
development:
<<: *defaults
test:
<<: *defaults
production:
<<: *defaults
Most AssetSync configuration can be modified directly using environment variables with the Built-in initializer. e.g.
AssetSync.config.fog_provider == ENV['FOG_PROVIDER']
Simply upcase the ruby attribute names to get the equivalent environment variable to set. The only exception to that rule are the internal AssetSync config variables, they must be prepended with ASSET_SYNC_*
e.g.
AssetSync.config.gzip_compression == ENV['ASSET_SYNC_GZIP_COMPRESSION']
'keep', 'delete', 'ignore'
) what to do with previously precompiled files. default: 'keep'
true, false
) when enabled, will automatically replace files that have a gzip compressed equivalent with the compressed version. default: 'false'
true, false
) when enabled, will use the manifest.yml
generated by Rails to get the list of local files to upload. experimental. default: 'false'
true, false
) when enabled, will upload the manifest.yml
generated by Rails. default: 'false'
true, false
) when enabled, will upload the files in different Threads, this greatly improves the upload speed. default: 'false'
10
nil
true, false
) when false, will disable asset sync. default: 'true'
(enabled)['ignore_me.js', %r(ignore_some/\d{32}\.css)]
Useful if there are some files that are created dynamically on the server and you don't want to upload on deploy default: []
['cache_me.js', %r(cache_some\.\d{8}\.css)]
Useful if there are some files that are added to sprockets assets list and need to be set as 'Cacheable' on uploaded server. Only rails compiled regexp is matched internally default: []
Config Method add_local_file_paths
Adding local files by providing a block:
AssetSync.configure do |config|
# The block should return an array of file paths
config.add_local_file_paths do
# Any code that returns paths of local asset files to be uploaded
# Like Webpacker
public_root = Rails.root.join("public")
Dir.chdir(public_root) do
packs_dir = Webpacker.config.public_output_path.relative_path_from(public_root)
Dir[File.join(packs_dir, '/**/**')]
end
end
end
The blocks are run when local files are being scanned and uploaded
Config Method file_ext_to_mime_type_overrides
It's reported that mime-types
3.x returns application/ecmascript
instead of application/javascript
Such change of mime type might cause some CDN to disable asset compression
So this gem has defined a default override for file ext js
to be mapped to application/javascript
by default
To customize the overrides:
AssetSync.configure do |config|
# Clear the default overrides
config.file_ext_to_mime_type_overrides.clear
# Add/Edit overrides
# Will call `#to_s` for inputs
config.file_ext_to_mime_type_overrides.add(:js, :"application/x-javascript")
end
The blocks are run when local files are being scanned and uploaded
When using the JSON API
When using the S3 API
https://lon.identity.api.rackspacecloud.com/v2.0
If you are using anything other than the US buckets with S3 then you'll want to set the region. For example with an EU bucket you could set the following environment variable.
heroku config:add FOG_REGION=eu-west-1
Or via a custom initializer
AssetSync.configure do |config|
# ...
config.fog_region = 'eu-west-1'
end
Or via YAML
production: # ... fog_region: 'eu-west-1'
Amazon has switched to the more secure IAM User security policy model. When generating a user & policy for asset_sync you must ensure the policy has the following permissions, or you'll see the error:
Expected(200) <=> Actual(403 Forbidden)
IAM User Policy Example with minimum require permissions (replace bucket_name
with your bucket):
{
"Statement": [
{
"Action": "s3:ListBucket",
"Effect": "Allow",
"Resource": "arn:aws:s3:::bucket_name"
},
{
"Action": "s3:PutObject*",
"Effect": "Allow",
"Resource": "arn:aws:s3:::bucket_name/*"
}
]
}
If you want to use IAM roles you must set config.aws_iam_roles = true
in your initializers.
AssetSync.configure do |config|
# ...
config.aws_iam_roles = true
end
With the gzip_compression
option enabled, when uploading your assets. If a file has a gzip compressed equivalent we will replace that asset with the compressed version and sets the correct headers for S3 to serve it. For example, if you have a file master.css and it was compressed to master.css.gz we will upload the .gz file to S3 in place of the uncompressed file.
If the compressed file is actually larger than the uncompressed file we will ignore this rule and upload the standard uncompressed version.
With the fail_silently
option enabled, when running rake assets:precompile
AssetSync will never throw an error due to missing configuration variables.
With the new user_env_compile feature of Heroku (see above), this is no longer required or recommended. Yet was added for the following reasons:
With Rails 3.1 on the Heroku cedar stack, the deployment process automatically runs
rake assets:precompile
. If you are using ENV variable style configuration. Due to the methods with which Heroku compile slugs, there will be an error raised by asset_sync as the environment is not available. This causes heroku to install therails31_enable_runtime_asset_compilation
plugin which is not necessary when using asset_sync and also massively slows down the first incoming requests to your app.
To prevent this part of the deploy from failing (asset_sync raising a config error), but carry on as normal set
fail_silently
to true in your configuration and ensure to runheroku run rake assets:precompile
after deploy.
A rake task is included within the asset_sync gem to perform the sync:
namespace :assets do
desc "Synchronize assets to S3"
task :sync => :environment do
AssetSync.sync
end
end
If AssetSync.config.run_on_precompile
is true
(default), then assets will be uploaded to S3 automatically after the assets:precompile
rake task is invoked:
if Rake::Task.task_defined?("assets:precompile:nondigest")
Rake::Task["assets:precompile:nondigest"].enhance do
Rake::Task["assets:sync"].invoke if defined?(AssetSync) && AssetSync.config.run_on_precompile
end
else
Rake::Task["assets:precompile"].enhance do
Rake::Task["assets:sync"].invoke if defined?(AssetSync) && AssetSync.config.run_on_precompile
end
end
You can disable this behavior by setting AssetSync.config.run_on_precompile = false
.
You can use the gem with any Rack application, but you must specify two additional options; prefix
and public_path
.
AssetSync.configure do |config|
config.fog_provider = 'AWS'
config.fog_directory = ENV['FOG_DIRECTORY']
config.aws_access_key_id = ENV['AWS_ACCESS_KEY_ID']
config.aws_secret_access_key = ENV['AWS_SECRET_ACCESS_KEY']
config.prefix = 'assets'
# Can be a `Pathname` or `String`
# Will be converted into an `Pathname`
# If relative, will be converted into an absolute path
# via `::Rails.root` or `::Dir.pwd`
config.public_path = Pathname('./public')
end
Then manually call AssetSync.sync
at the end of your asset precompilation task.
namespace :assets do
desc 'Precompile assets'
task :precompile do
target = Pathname('./public/assets')
manifest = Sprockets::Manifest.new(sprockets, './public/assets/manifest.json')
sprockets.each_logical_path do |logical_path|
if (!File.extname(logical_path).in?(['.js', '.css']) || logical_path =~ /application\.(css|js)$/) && asset = sprockets.find_asset(logical_path)
filename = target.join(logical_path)
FileUtils.mkpath(filename.dirname)
puts "Write asset: #{filename}"
asset.write_to(filename)
manifest.compile(logical_path)
end
end
AssetSync.sync
end
end
run_on_precompile
:AssetSync.configure do |config|
# Disable automatic run on precompile in order to attach to webpacker rake task
config.run_on_precompile = false
# The block should return an array of file paths
config.add_local_file_paths do
# Support webpacker assets
public_root = Rails.root.join("public")
Dir.chdir(public_root) do
packs_dir = Webpacker.config.public_output_path.relative_path_from(public_root)
Dir[File.join(packs_dir, '/**/**')]
end
end
end
asset_sync.rake
in your lib/tasks
directory that enhances the correct task, otherwise asset_sync runs before webpacker:compile
does:if defined?(AssetSync)
Rake::Task['webpacker:compile'].enhance do
Rake::Task["assets:sync"].invoke
end
end
By adding local files outside the normal Rails assets
directory, the uploading part works, however checking that the asset was previously uploaded is not working because asset_sync is only fetching the files in the assets
directory on the remote bucket. This will mean additional time used to upload the same assets again on every precompilation.
Make sure you have a .env file with these details:-
# for AWS provider
AWS_ACCESS_KEY_ID=<yourkeyid>
AWS_SECRET_ACCESS_KEY=<yoursecretkey>
FOG_DIRECTORY=<yourbucket>
FOG_REGION=<youbucketregion>
# for AzureRM provider
AZURE_STORAGE_ACCOUNT_NAME=<youraccountname>
AZURE_STORAGE_ACCESS_KEY=<youraccesskey>
FOG_DIRECTORY=<yourcontainer>
FOG_REGION=<yourcontainerregion>
Make sure the bucket has read/write permissions. Then to run the tests:-
foreman run rake
Inspired by:
MIT License. Copyright 2011-2013 Rumble Labs Ltd. rumblelabs.com
Author: AssetSync
Source code: https://github.com/AssetSync/asset_sync
License:
1673365703
The following is a collection of tips I find to be useful when working with the Swift language. More content is available on my Twitter account!
📣 NEW 📣 Swift Tips are now available on YouTube 👇
Tips
Property Wrappers allow developers to wrap properties with specific behaviors, that will be seamlessly triggered whenever the properties are accessed.
While their primary use case is to implement business logic within our apps, it's also possible to use Property Wrappers as debugging tools!
For example, we could build a wrapper called @History
, that would be added to a property while debugging and would keep track of all the values set to this property.
import Foundation
@propertyWrapper
struct History<Value> {
private var value: Value
private(set) var history: [Value] = []
init(wrappedValue: Value) {
self.value = wrappedValue
}
var wrappedValue: Value {
get { value }
set {
history.append(value)
value = newValue
}
}
var projectedValue: Self {
return self
}
}
// We can then decorate our business code
// with the `@History` wrapper
struct User {
@History var name: String = ""
}
var user = User()
// All the existing call sites will still
// compile, without the need for any change
user.name = "John"
user.name = "Jane"
// But now we can also access an history of
// all the previous values!
user.$name.history // ["", "John"]
String
interpolationSwift 5 gave us the possibility to define our own custom String
interpolation methods.
This feature can be used to power many use cases, but there is one that is guaranteed to make sense in most projects: localizing user-facing strings.
import Foundation
extension String.StringInterpolation {
mutating func appendInterpolation(localized key: String, _ args: CVarArg...) {
let localized = String(format: NSLocalizedString(key, comment: ""), arguments: args)
appendLiteral(localized)
}
}
/*
Let's assume that this is the content of our Localizable.strings:
"welcome.screen.greetings" = "Hello %@!";
*/
let userName = "John"
print("\(localized: "welcome.screen.greetings", userName)") // Hello John!
structs
If you’ve always wanted to use some kind of inheritance mechanism for your structs, Swift 5.1 is going to make you very happy!
Using the new KeyPath-based dynamic member lookup, you can implement some pseudo-inheritance, where a type inherits the API of another one 🎉
(However, be careful, I’m definitely not advocating inheritance as a go-to solution 🙃)
import Foundation
protocol Inherits {
associatedtype SuperType
var `super`: SuperType { get }
}
extension Inherits {
subscript<T>(dynamicMember keyPath: KeyPath<SuperType, T>) -> T {
return self.`super`[keyPath: keyPath]
}
}
struct Person {
let name: String
}
@dynamicMemberLookup
struct User: Inherits {
let `super`: Person
let login: String
let password: String
}
let user = User(super: Person(name: "John Appleseed"), login: "Johnny", password: "1234")
user.name // "John Appleseed"
user.login // "Johnny"
NSAttributedString
through a Function BuilderSwift 5.1 introduced Function Builders: a great tool for building custom DSL syntaxes, like SwiftUI. However, one doesn't need to be building a full-fledged DSL in order to leverage them.
For example, it's possible to write a simple Function Builder, whose job will be to compose together individual instances of NSAttributedString
through a nicer syntax than the standard API.
import UIKit
@_functionBuilder
class NSAttributedStringBuilder {
static func buildBlock(_ components: NSAttributedString...) -> NSAttributedString {
let result = NSMutableAttributedString(string: "")
return components.reduce(into: result) { (result, current) in result.append(current) }
}
}
extension NSAttributedString {
class func composing(@NSAttributedStringBuilder _ parts: () -> NSAttributedString) -> NSAttributedString {
return parts()
}
}
let result = NSAttributedString.composing {
NSAttributedString(string: "Hello",
attributes: [.font: UIFont.systemFont(ofSize: 24),
.foregroundColor: UIColor.red])
NSAttributedString(string: " world!",
attributes: [.font: UIFont.systemFont(ofSize: 20),
.foregroundColor: UIColor.orange])
}
switch
and if
as expressionsContrary to other languages, like Kotlin, Swift does not allow switch
and if
to be used as expressions. Meaning that the following code is not valid Swift:
let constant = if condition {
someValue
} else {
someOtherValue
}
A common solution to this problem is to wrap the if
or switch
statement within a closure, that will then be immediately called. While this approach does manage to achieve the desired goal, it makes for a rather poor syntax.
To avoid the ugly trailing ()
and improve on the readability, you can define a resultOf
function, that will serve the exact same purpose, in a more elegant way.
import Foundation
func resultOf<T>(_ code: () -> T) -> T {
return code()
}
let randomInt = Int.random(in: 0...3)
let spelledOut: String = resultOf {
switch randomInt {
case 0:
return "Zero"
case 1:
return "One"
case 2:
return "Two"
case 3:
return "Three"
default:
return "Out of range"
}
}
print(spelledOut)
guard
statementsA guard
statement is a very convenient way for the developer to assert that a condition is met, in order for the execution of the program to keep going.
However, since the body of a guard
statement is meant to be executed when the condition evaluates to false
, the use of the negation (!
) operator within the condition of a guard
statement can make the code hard to read, as it becomes a double negative.
A nice trick to avoid such double negatives is to encapsulate the use of the !
operator within a new property or function, whose name does not include a negative.
import Foundation
extension Collection {
var hasElements: Bool {
return !isEmpty
}
}
let array = Bool.random() ? [1, 2, 3] : []
guard array.hasElements else { fatalError("array was empty") }
print(array)
init
without loosing the compiler-generated oneIt's common knowledge for Swift developers that, when you define a struct
, the compiler is going to automatically generate a memberwise init
for you. That is, unless you also define an init
of your own. Because then, the compiler won't generate any memberwise init
.
Yet, there are many instances where we might enjoy the opportunity to get both. As it turns out, this goal is quite easy to achieve: you just need to define your own init
in an extension
rather than inside the type definition itself.
import Foundation
struct Point {
let x: Int
let y: Int
}
extension Point {
init() {
x = 0
y = 0
}
}
let usingDefaultInit = Point(x: 4, y: 3)
let usingCustomInit = Point()
enum
Swift does not really have an out-of-the-box support of namespaces. One could argue that a Swift module can be seen as a namespace, but creating a dedicated Framework for this sole purpose can legitimately be regarded as overkill.
Some developers have taken the habit to use a struct
which only contains static
fields to implement a namespace. While this does the job, it requires us to remember to implement an empty private
init()
, because it wouldn't make sense for such a struct
to be instantiated.
It's actually possible to take this approach one step further, by replacing the struct
with an enum
. While it might seem weird to have an enum
with no case
, it's actually a very idiomatic way to declare a type that cannot be instantiated.
import Foundation
enum NumberFormatterProvider {
static var currencyFormatter: NumberFormatter {
let formatter = NumberFormatter()
formatter.numberStyle = .currency
formatter.roundingIncrement = 0.01
return formatter
}
static var decimalFormatter: NumberFormatter {
let formatter = NumberFormatter()
formatter.numberStyle = .decimal
formatter.decimalSeparator = ","
return formatter
}
}
NumberFormatterProvider() // ❌ impossible to instantiate by mistake
NumberFormatterProvider.currencyFormatter.string(from: 2.456) // $2.46
NumberFormatterProvider.decimalFormatter.string(from: 2.456) // 2,456
Never
to represent impossible code pathsNever
is quite a peculiar type in the Swift Standard Library: it is defined as an empty enum enum Never { }
.
While this might seem odd at first glance, it actually yields a very interesting property: it makes it a type that cannot be constructed (i.e. it possesses no instances).
This way, Never
can be used as a generic parameter to let the compiler know that a particular feature will not be used.
import Foundation
enum Result<Value, Error> {
case success(value: Value)
case failure(error: Error)
}
func willAlwaysSucceed(_ completion: @escaping ((Result<String, Never>) -> Void)) {
completion(.success(value: "Call was successful"))
}
willAlwaysSucceed( { result in
switch result {
case .success(let value):
print(value)
// the compiler knows that the `failure` case cannot happen
// so it doesn't require us to handle it.
}
})
Decodable
enum
Swift's Codable
framework does a great job at seamlessly decoding entities from a JSON stream. However, when we integrate web-services, we are sometimes left to deal with JSONs that require behaviors that Codable
does not provide out-of-the-box.
For instance, we might have a string-based or integer-based enum
, and be required to set it to a default value when the data found in the JSON does not match any of its cases.
We might be tempted to implement this via an extensive switch
statement over all the possible cases, but there is a much shorter alternative through the initializer init?(rawValue:)
:
import Foundation
enum State: String, Decodable {
case active
case inactive
case undefined
init(from decoder: Decoder) throws {
let container = try decoder.singleValueContainer()
let decodedString = try container.decode(String.self)
self = State(rawValue: decodedString) ?? .undefined
}
}
let data = """
["active", "inactive", "foo"]
""".data(using: .utf8)!
let decoded = try! JSONDecoder().decode([State].self, from: data)
print(decoded) // [State.active, State.inactive, State.undefined]
Dependency injection boils down to a simple idea: when an object requires a dependency, it shouldn't create it by itself, but instead it should be given a function that does it for him.
Now the great thing with Swift is that, not only can a function take another function as a parameter, but that parameter can also be given a default value.
When you combine both those features, you can end up with a dependency injection pattern that is both lightweight on boilerplate, but also type safe.
import Foundation
protocol Service {
func call() -> String
}
class ProductionService: Service {
func call() -> String {
return "This is the production"
}
}
class MockService: Service {
func call() -> String {
return "This is a mock"
}
}
typealias Provider<T> = () -> T
class Controller {
let service: Service
init(serviceProvider: Provider<Service> = { return ProductionService() }) {
self.service = serviceProvider()
}
func work() {
print(service.call())
}
}
let productionController = Controller()
productionController.work() // prints "This is the production"
let mockedController = Controller(serviceProvider: { return MockService() })
mockedController.work() // prints "This is a mock"
Singletons are pretty bad. They make your architecture rigid and tightly coupled, which then results in your code being hard to test and refactor. Instead of using singletons, your code should rely on dependency injection, which is a much more architecturally sound approach.
But singletons are so easy to use, and dependency injection requires us to do extra-work. So maybe, for simple situations, we could find an in-between solution?
One possible solution is to rely on one of Swift's most know features: protocol-oriented programming. Using a protocol
, we declare and access our dependency. We then store it in a private singleton, and perform the injection through an extension of said protocol
.
This way, our code will indeed be decoupled from its dependency, while at the same time keeping the boilerplate to a minimum.
import Foundation
protocol Formatting {
var formatter: NumberFormatter { get }
}
private let sharedFormatter: NumberFormatter = {
let sharedFormatter = NumberFormatter()
sharedFormatter.numberStyle = .currency
return sharedFormatter
}()
extension Formatting {
var formatter: NumberFormatter { return sharedFormatter }
}
class ViewModel: Formatting {
var displayableAmount: String?
func updateDisplay(to amount: Double) {
displayableAmount = formatter.string(for: amount)
}
}
let viewModel = ViewModel()
viewModel.updateDisplay(to: 42000.45)
viewModel.displayableAmount // "$42,000.45"
[weak self]
and guard
Callbacks are a part of almost all iOS apps, and as frameworks such as RxSwift
keep gaining in popularity, they become ever more present in our codebase.
Seasoned Swift developers are aware of the potential memory leaks that @escaping
callbacks can produce, so they make real sure to always use [weak self]
, whenever they need to use self
inside such a context. And when they need to have self
be non-optional, they then add a guard
statement along.
Consequently, this syntax of a [weak self]
followed by a guard
rapidly tends to appear everywhere in the codebase. The good thing is that, through a little protocol-oriented trick, it's actually possible to get rid of this tedious syntax, without loosing any of its benefits!
import Foundation
import PlaygroundSupport
PlaygroundPage.current.needsIndefiniteExecution = true
protocol Weakifiable: class { }
extension Weakifiable {
func weakify(_ code: @escaping (Self) -> Void) -> () -> Void {
return { [weak self] in
guard let self = self else { return }
code(self)
}
}
func weakify<T>(_ code: @escaping (T, Self) -> Void) -> (T) -> Void {
return { [weak self] arg in
guard let self = self else { return }
code(arg, self)
}
}
}
extension NSObject: Weakifiable { }
class Producer: NSObject {
deinit {
print("deinit Producer")
}
private var handler: (Int) -> Void = { _ in }
func register(handler: @escaping (Int) -> Void) {
self.handler = handler
DispatchQueue.main.asyncAfter(deadline: .now() + 1.0, execute: { self.handler(42) })
}
}
class Consumer: NSObject {
deinit {
print("deinit Consumer")
}
let producer = Producer()
func consume() {
producer.register(handler: weakify { result, strongSelf in
strongSelf.handle(result)
})
}
private func handle(_ result: Int) {
print("🎉 \(result)")
}
}
var consumer: Consumer? = Consumer()
consumer?.consume()
DispatchQueue.main.asyncAfter(deadline: .now() + 2.0, execute: { consumer = nil })
// This code prints:
// 🎉 42
// deinit Consumer
// deinit Producer
Asynchronous functions are a big part of iOS APIs, and most developers are familiar with the challenge they pose when one needs to sequentially call several asynchronous APIs.
This often results in callbacks being nested into one another, a predicament often referred to as callback hell.
Many third-party frameworks are able to tackle this issue, for instance RxSwift or PromiseKit. Yet, for simple instances of the problem, there is no need to use such big guns, as it can actually be solved with simple function composition.
import Foundation
typealias CompletionHandler<Result> = (Result?, Error?) -> Void
infix operator ~>: MultiplicationPrecedence
func ~> <T, U>(_ first: @escaping (CompletionHandler<T>) -> Void, _ second: @escaping (T, CompletionHandler<U>) -> Void) -> (CompletionHandler<U>) -> Void {
return { completion in
first({ firstResult, error in
guard let firstResult = firstResult else { completion(nil, error); return }
second(firstResult, { (secondResult, error) in
completion(secondResult, error)
})
})
}
}
func ~> <T, U>(_ first: @escaping (CompletionHandler<T>) -> Void, _ transform: @escaping (T) -> U) -> (CompletionHandler<U>) -> Void {
return { completion in
first({ result, error in
guard let result = result else { completion(nil, error); return }
completion(transform(result), nil)
})
}
}
func service1(_ completionHandler: CompletionHandler<Int>) {
completionHandler(42, nil)
}
func service2(arg: String, _ completionHandler: CompletionHandler<String>) {
completionHandler("🎉 \(arg)", nil)
}
let chainedServices = service1
~> { int in return String(int / 2) }
~> service2
chainedServices({ result, _ in
guard let result = result else { return }
print(result) // Prints: 🎉 21
})
Asynchronous functions are a great way to deal with future events without blocking a thread. Yet, there are times where we would like them to behave in exactly such a blocking way.
Think about writing unit tests and using mocked network calls. You will need to add complexity to your test in order to deal with asynchronous functions, whereas synchronous ones would be much easier to manage.
Thanks to Swift proficiency in the functional paradigm, it is possible to write a function whose job is to take an asynchronous function and transform it into a synchronous one.
import Foundation
func makeSynchrone<A, B>(_ asyncFunction: @escaping (A, (B) -> Void) -> Void) -> (A) -> B {
return { arg in
let lock = NSRecursiveLock()
var result: B? = nil
asyncFunction(arg) {
result = $0
lock.unlock()
}
lock.lock()
return result!
}
}
func myAsyncFunction(arg: Int, completionHandler: (String) -> Void) {
completionHandler("🎉 \(arg)")
}
let syncFunction = makeSynchrone(myAsyncFunction)
print(syncFunction(42)) // prints 🎉 42
Closures are a great way to interact with generic APIs, for instance APIs that allow to manipulate data structures through the use of generic functions, such as filter()
or sorted()
.
The annoying part is that closures tend to clutter your code with many instances of {
, }
and $0
, which can quickly undermine its readably.
A nice alternative for a cleaner syntax is to use a KeyPath
instead of a closure, along with an operator that will deal with transforming the provided KeyPath
in a closure.
import Foundation
prefix operator ^
prefix func ^ <Element, Attribute>(_ keyPath: KeyPath<Element, Attribute>) -> (Element) -> Attribute {
return { element in element[keyPath: keyPath] }
}
struct MyData {
let int: Int
let string: String
}
let data = [MyData(int: 2, string: "Foo"), MyData(int: 4, string: "Bar")]
data.map(^\.int) // [2, 4]
data.map(^\.string) // ["Foo", "Bar"]
userInfo
Dictionary
Many iOS APIs still rely on a userInfo
Dictionary
to handle use-case specific data. This Dictionary
usually stores untyped values, and is declared as follows: [String: Any]
(or sometimes [AnyHashable: Any]
.
Retrieving data from such a structure will involve some conditional casting (via the as?
operator), which is prone to both errors and repetitions. Yet, by introducing a custom subscript
, it's possible to encapsulate all the tedious logic, and end-up with an easier and more robust API.
import Foundation
typealias TypedUserInfoKey<T> = (key: String, type: T.Type)
extension Dictionary where Key == String, Value == Any {
subscript<T>(_ typedKey: TypedUserInfoKey<T>) -> T? {
return self[typedKey.key] as? T
}
}
let userInfo: [String : Any] = ["Foo": 4, "Bar": "forty-two"]
let integerTypedKey = TypedUserInfoKey(key: "Foo", type: Int.self)
let intValue = userInfo[integerTypedKey] // returns 4
type(of: intValue) // returns Int?
let stringTypedKey = TypedUserInfoKey(key: "Bar", type: String.self)
let stringValue = userInfo[stringTypedKey] // returns "forty-two"
type(of: stringValue) // returns String?
MVVM is a great pattern to separate business logic from presentation logic. The main challenge to make it work, is to define a mechanism for the presentation layer to be notified of model updates.
RxSwift is a perfect choice to solve such a problem. Yet, some developers don't feel confortable with leveraging a third-party library for such a central part of their architecture.
For those situation, it's possible to define a lightweight Variable
type, that will make the MVVM pattern very easy to use!
import Foundation
class Variable<Value> {
var value: Value {
didSet {
onUpdate?(value)
}
}
var onUpdate: ((Value) -> Void)? {
didSet {
onUpdate?(value)
}
}
init(_ value: Value, _ onUpdate: ((Value) -> Void)? = nil) {
self.value = value
self.onUpdate = onUpdate
self.onUpdate?(value)
}
}
let variable: Variable<String?> = Variable(nil)
variable.onUpdate = { data in
if let data = data {
print(data)
}
}
variable.value = "Foo"
variable.value = "Bar"
// prints:
// Foo
// Bar
typealias
to its fullestThe keyword typealias
allows developers to give a new name to an already existing type. For instance, Swift defines Void
as a typealias
of ()
, the empty tuple.
But a less known feature of this mechanism is that it allows to assign concrete types for generic parameters, or to rename them. This can help make the semantics of generic types much clearer, when used in specific use cases.
import Foundation
enum Either<Left, Right> {
case left(Left)
case right(Right)
}
typealias Result<Value> = Either<Value, Error>
typealias IntOrString = Either<Int, String>
forEach
Iterating through objects via the forEach(_:)
method is a great alternative to the classic for
loop, as it allows our code to be completely oblivious of the iteration logic. One limitation, however, is that forEach(_:)
does not allow to stop the iteration midway.
Taking inspiration from the Objective-C implementation, we can write an overload that will allow the developer to stop the iteration, if needed.
import Foundation
extension Sequence {
func forEach(_ body: (Element, _ stop: inout Bool) throws -> Void) rethrows {
var stop = false
for element in self {
try body(element, &stop)
if stop {
return
}
}
}
}
["Foo", "Bar", "FooBar"].forEach { element, stop in
print(element)
stop = (element == "Bar")
}
// Prints:
// Foo
// Bar
reduce()
Functional programing is a great way to simplify a codebase. For instance, reduce
is an alternative to the classic for
loop, without most the boilerplate. Unfortunately, simplicity often comes at the price of performance.
Consider that you want to remove duplicate values from a Sequence
. While reduce()
is a perfectly fine way to express this computation, the performance will be sub optimal, because of all the unnecessary Array
copying that will happen every time its closure gets called.
That's when reduce(into:_:)
comes into play. This version of reduce
leverages the capacities of copy-on-write type (such as Array
or Dictionnary
) in order to avoid unnecessary copying, which results in a great performance boost.
import Foundation
func time(averagedExecutions: Int = 1, _ code: () -> Void) {
let start = Date()
for _ in 0..<averagedExecutions { code() }
let end = Date()
let duration = end.timeIntervalSince(start) / Double(averagedExecutions)
print("time: \(duration)")
}
let data = (1...1_000).map { _ in Int(arc4random_uniform(256)) }
// runs in 0.63s
time {
let noDuplicates: [Int] = data.reduce([], { $0.contains($1) ? $0 : $0 + [$1] })
}
// runs in 0.15s
time {
let noDuplicates: [Int] = data.reduce(into: [], { if !$0.contains($1) { $0.append($1) } } )
}
UI components such as UITableView
and UICollectionView
rely on reuse identifiers in order to efficiently recycle the views they display. Often, those reuse identifiers take the form of a static hardcoded String
, that will be used for every instance of their class.
Through protocol-oriented programing, it's possible to avoid those hardcoded values, and instead use the name of the type as a reuse identifier.
import Foundation
import UIKit
protocol Reusable {
static var reuseIdentifier: String { get }
}
extension Reusable {
static var reuseIdentifier: String {
return String(describing: self)
}
}
extension UITableViewCell: Reusable { }
extension UITableView {
func register<T: UITableViewCell>(_ class: T.Type) {
register(`class`, forCellReuseIdentifier: T.reuseIdentifier)
}
func dequeueReusableCell<T: UITableViewCell>(for indexPath: IndexPath) -> T {
return dequeueReusableCell(withIdentifier: T.reuseIdentifier, for: indexPath) as! T
}
}
class MyCell: UITableViewCell { }
let tableView = UITableView()
tableView.register(MyCell.self)
let myCell: MyCell = tableView.dequeueReusableCell(for: [0, 0])
The C language has a construct called union
, that allows a single variable to hold values from different types. While Swift does not provide such a construct, it provides enums with associated values, which allows us to define a type called Either
that implements a union
of two types.
import Foundation
enum Either<A, B> {
case left(A)
case right(B)
func either(ifLeft: ((A) -> Void)? = nil, ifRight: ((B) -> Void)? = nil) {
switch self {
case let .left(a):
ifLeft?(a)
case let .right(b):
ifRight?(b)
}
}
}
extension Bool { static func random() -> Bool { return arc4random_uniform(2) == 0 } }
var intOrString: Either<Int, String> = Bool.random() ? .left(2) : .right("Foo")
intOrString.either(ifLeft: { print($0 + 1) }, ifRight: { print($0 + "Bar") })
If you're interested by this kind of data structure, I strongly recommend that you learn more about Algebraic Data Types.
Most of the time, when we create a .xib
file, we give it the same name as its associated class. From that, if we later refactor our code and rename such a class, we run the risk of forgetting to rename the associated .xib
.
While the error will often be easy to catch, if the .xib
is used in a remote section of its app, it might go unnoticed for sometime. Fortunately it's possible to build custom test predicates that will assert that 1) for a given class, there exists a .nib
with the same name in a given Bundle
, 2) for all the .nib
in a given Bundle
, there exists a class with the same name.
import XCTest
public func XCTAssertClassHasNib(_ class: AnyClass, bundle: Bundle, file: StaticString = #file, line: UInt = #line) {
let associatedNibURL = bundle.url(forResource: String(describing: `class`), withExtension: "nib")
XCTAssertNotNil(associatedNibURL, "Class \"\(`class`)\" has no associated nib file", file: file, line: line)
}
public func XCTAssertNibHaveClasses(_ bundle: Bundle, file: StaticString = #file, line: UInt = #line) {
guard let bundleName = bundle.infoDictionary?["CFBundleName"] as? String,
let basePath = bundle.resourcePath,
let enumerator = FileManager.default.enumerator(at: URL(fileURLWithPath: basePath),
includingPropertiesForKeys: nil,
options: [.skipsHiddenFiles, .skipsSubdirectoryDescendants]) else { return }
var nibFilesURLs = [URL]()
for case let fileURL as URL in enumerator {
if fileURL.pathExtension.uppercased() == "NIB" {
nibFilesURLs.append(fileURL)
}
}
nibFilesURLs.map { $0.lastPathComponent }
.compactMap { $0.split(separator: ".").first }
.map { String($0) }
.forEach {
let associatedClass: AnyClass? = bundle.classNamed("\(bundleName).\($0)")
XCTAssertNotNil(associatedClass, "File \"\($0).nib\" has no associated class", file: file, line: line)
}
}
XCTAssertClassHasNib(MyFirstTableViewCell.self, bundle: Bundle(for: AppDelegate.self))
XCTAssertClassHasNib(MySecondTableViewCell.self, bundle: Bundle(for: AppDelegate.self))
XCTAssertNibHaveClasses(Bundle(for: AppDelegate.self))
Many thanks Benjamin Lavialle for coming up with the idea behind the second test predicate.
Seasoned Swift developers know it: a protocol with associated type (PAT) "can only be used as a generic constraint because it has Self or associated type requirements". When we really need to use a PAT to type a variable, the goto workaround is to use a type-erased wrapper.
While this solution works perfectly, it requires a fair amount of boilerplate code. In instances where we are only interested in exposing one particular function of the PAT, a shorter approach using function types is possible.
import Foundation
import UIKit
protocol Configurable {
associatedtype Model
func configure(with model: Model)
}
typealias Configurator<Model> = (Model) -> ()
extension UILabel: Configurable {
func configure(with model: String) {
self.text = model
}
}
let label = UILabel()
let configurator: Configurator<String> = label.configure
configurator("Foo")
label.text // "Foo"
UIKit
exposes a very powerful and simple API to perform view animations. However, this API can become a little bit quirky to use when we want to perform animations sequentially, because it involves nesting closure within one another, which produces notoriously hard to maintain code.
Nonetheless, it's possible to define a rather simple class, that will expose a really nicer API for this particular use case 👌
import Foundation
import UIKit
class AnimationSequence {
typealias Animations = () -> Void
private let current: Animations
private let duration: TimeInterval
private var next: AnimationSequence? = nil
init(animations: @escaping Animations, duration: TimeInterval) {
self.current = animations
self.duration = duration
}
@discardableResult func append(animations: @escaping Animations, duration: TimeInterval) -> AnimationSequence {
var lastAnimation = self
while let nextAnimation = lastAnimation.next {
lastAnimation = nextAnimation
}
lastAnimation.next = AnimationSequence(animations: animations, duration: duration)
return self
}
func run() {
UIView.animate(withDuration: duration, animations: current, completion: { finished in
if finished, let next = self.next {
next.run()
}
})
}
}
var firstView = UIView()
var secondView = UIView()
firstView.alpha = 0
secondView.alpha = 0
AnimationSequence(animations: { firstView.alpha = 1.0 }, duration: 1)
.append(animations: { secondView.alpha = 1.0 }, duration: 0.5)
.append(animations: { firstView.alpha = 0.0 }, duration: 2.0)
.run()
Debouncing is a very useful tool when dealing with UI inputs. Consider a search bar, whose content is used to query an API. It wouldn't make sense to perform a request for every character the user is typing, because as soon as a new character is entered, the result of the previous request has become irrelevant.
Instead, our code will perform much better if we "debounce" the API call, meaning that we will wait until some delay has passed, without the input being modified, before actually performing the call.
import Foundation
func debounced(delay: TimeInterval, queue: DispatchQueue = .main, action: @escaping (() -> Void)) -> () -> Void {
var workItem: DispatchWorkItem?
return {
workItem?.cancel()
workItem = DispatchWorkItem(block: action)
queue.asyncAfter(deadline: .now() + delay, execute: workItem!)
}
}
let debouncedPrint = debounced(delay: 1.0) { print("Action performed!") }
debouncedPrint()
debouncedPrint()
debouncedPrint()
// After a 1 second delay, this gets
// printed only once to the console:
// Action performed!
Optional
booleansWhen we need to apply the standard boolean operators to Optional
booleans, we often end up with a syntax unnecessarily crowded with unwrapping operations. By taking a cue from the world of three-valued logics, we can define a couple operators that make working with Bool?
values much nicer.
import Foundation
func && (lhs: Bool?, rhs: Bool?) -> Bool? {
switch (lhs, rhs) {
case (false, _), (_, false):
return false
case let (unwrapLhs?, unwrapRhs?):
return unwrapLhs && unwrapRhs
default:
return nil
}
}
func || (lhs: Bool?, rhs: Bool?) -> Bool? {
switch (lhs, rhs) {
case (true, _), (_, true):
return true
case let (unwrapLhs?, unwrapRhs?):
return unwrapLhs || unwrapRhs
default:
return nil
}
}
false && nil // false
true && nil // nil
[true, nil, false].reduce(true, &&) // false
nil || true // true
nil || false // nil
[true, nil, false].reduce(false, ||) // true
Sequence
Transforming a Sequence
in order to remove all the duplicate values it contains is a classic use case. To implement it, one could be tempted to transform the Sequence
into a Set
, then back to an Array
. The downside with this approach is that it will not preserve the order of the sequence, which can definitely be a dealbreaker. Using reduce()
it is possible to provide a concise implementation that preserves ordering:
import Foundation
extension Sequence where Element: Equatable {
func duplicatesRemoved() -> [Element] {
return reduce([], { $0.contains($1) ? $0 : $0 + [$1] })
}
}
let data = [2, 5, 2, 3, 6, 5, 2]
data.duplicatesRemoved() // [2, 5, 3, 6]
Optional strings are very common in Swift code, for instance many objects from UIKit
expose the text they display as a String?
. Many times you will need to manipulate this data as an unwrapped String
, with a default value set to the empty string for nil
cases.
While the nil-coalescing operator (e.g. ??
) is a perfectly fine way to a achieve this goal, defining a computed variable like orEmpty
can help a lot in cleaning the syntax.
import Foundation
import UIKit
extension Optional where Wrapped == String {
var orEmpty: String {
switch self {
case .some(let value):
return value
case .none:
return ""
}
}
}
func doesNotWorkWithOptionalString(_ param: String) {
// do something with `param`
}
let label = UILabel()
label.text = "This is some text."
doesNotWorkWithOptionalString(label.text.orEmpty)
Every seasoned iOS developers knows it: objects from UIKit
can only be accessed from the main thread. Any attempt to access them from a background thread is a guaranteed crash.
Still, running a costly computation on the background, and then using it to update the UI can be a common pattern.
In such cases you can rely on asyncUI
to encapsulate all the boilerplate code.
import Foundation
import UIKit
func asyncUI<T>(_ computation: @autoclosure @escaping () -> T, qos: DispatchQoS.QoSClass = .userInitiated, _ completion: @escaping (T) -> Void) {
DispatchQueue.global(qos: qos).async {
let value = computation()
DispatchQueue.main.async {
completion(value)
}
}
}
let label = UILabel()
func costlyComputation() -> Int { return (0..<10_000).reduce(0, +) }
asyncUI(costlyComputation()) { value in
label.text = "\(value)"
}
A debug view, from which any controller of an app can be instantiated and pushed on the navigation stack, has the potential to bring some real value to a development process. A requirement to build such a view is to have a list of all the classes from a given Bundle
that inherit from UIViewController
. With the following extension
, retrieving this list becomes a piece of cake 🍰
import Foundation
import UIKit
import ObjectiveC
extension Bundle {
func viewControllerTypes() -> [UIViewController.Type] {
guard let bundlePath = self.executablePath else { return [] }
var size: UInt32 = 0
var rawClassNames: UnsafeMutablePointer<UnsafePointer<Int8>>!
var parsedClassNames = [String]()
rawClassNames = objc_copyClassNamesForImage(bundlePath, &size)
for index in 0..<size {
let className = rawClassNames[Int(index)]
if let name = NSString.init(utf8String:className) as String?,
NSClassFromString(name) is UIViewController.Type {
parsedClassNames.append(name)
}
}
return parsedClassNames
.sorted()
.compactMap { NSClassFromString($0) as? UIViewController.Type }
}
}
// Fetch all view controller types in UIKit
Bundle(for: UIViewController.self).viewControllerTypes()
I share the credit for this tip with Benoît Caron.
Update As it turns out, map
is actually a really bad name for this function, because it does not preserve composition of transformations, a property that is required to fit the definition of a real map
function.
Surprisingly enough, the standard library doesn't define a map()
function for dictionaries that allows to map both keys
and values
into a new Dictionary
. Nevertheless, such a function can be helpful, for instance when converting data across different frameworks.
import Foundation
extension Dictionary {
func map<T: Hashable, U>(_ transform: (Key, Value) throws -> (T, U)) rethrows -> [T: U] {
var result: [T: U] = [:]
for (key, value) in self {
let (transformedKey, transformedValue) = try transform(key, value)
result[transformedKey] = transformedValue
}
return result
}
}
let data = [0: 5, 1: 6, 2: 7]
data.map { ("\($0)", $1 * $1) } // ["2": 49, "0": 25, "1": 36]
nil
valuesSwift provides the function compactMap()
, that can be used to remove nil
values from a Sequence
of optionals when calling it with an argument that just returns its parameter (i.e. compactMap { $0 }
). Still, for such use cases it would be nice to get rid of the trailing closure.
The implementation isn't as straightforward as your usual extension
, but once it has been written, the call site definitely gets cleaner 👌
import Foundation
protocol OptionalConvertible {
associatedtype Wrapped
func asOptional() -> Wrapped?
}
extension Optional: OptionalConvertible {
func asOptional() -> Wrapped? {
return self
}
}
extension Sequence where Element: OptionalConvertible {
func compacted() -> [Element.Wrapped] {
return compactMap { $0.asOptional() }
}
}
let data = [nil, 1, 2, nil, 3, 5, nil, 8, nil]
data.compacted() // [1, 2, 3, 5, 8]
It might happen that your code has to deal with values that come with an expiration date. In a game, it could be a score multiplier that will only last for 30 seconds. Or it could be an authentication token for an API, with a 15 minutes lifespan. In both instances you can rely on the type Expirable
to encapsulate the expiration logic.
import Foundation
struct Expirable<T> {
private var innerValue: T
private(set) var expirationDate: Date
var value: T? {
return hasExpired() ? nil : innerValue
}
init(value: T, expirationDate: Date) {
self.innerValue = value
self.expirationDate = expirationDate
}
init(value: T, duration: Double) {
self.innerValue = value
self.expirationDate = Date().addingTimeInterval(duration)
}
func hasExpired() -> Bool {
return expirationDate < Date()
}
}
let expirable = Expirable(value: 42, duration: 3)
sleep(2)
expirable.value // 42
sleep(2)
expirable.value // nil
I share the credit for this tip with Benoît Caron.
map()
Almost all Apple devices able to run Swift code are powered by a multi-core CPU, consequently making a good use of parallelism is a great way to improve code performance. map()
is a perfect candidate for such an optimization, because it is almost trivial to define a parallel implementation.
import Foundation
extension Array {
func parallelMap<T>(_ transform: (Element) -> T) -> [T] {
let res = UnsafeMutablePointer<T>.allocate(capacity: count)
DispatchQueue.concurrentPerform(iterations: count) { i in
res[i] = transform(self[i])
}
let finalResult = Array<T>(UnsafeBufferPointer(start: res, count: count))
res.deallocate(capacity: count)
return finalResult
}
}
let array = (0..<1_000).map { $0 }
func work(_ n: Int) -> Int {
return (0..<n).reduce(0, +)
}
array.parallelMap { work($0) }
🚨 Make sure to only use parallelMap()
when the transform
function actually performs some costly computations. Otherwise performances will be systematically slower than using map()
, because of the multithreading overhead.
During development of a feature that performs some heavy computations, it can be helpful to measure just how much time a chunk of code takes to run. The time()
function is a nice tool for this purpose, because of how simple it is to add and then to remove when it is no longer needed.
import Foundation
func time(averagedExecutions: Int = 1, _ code: () -> Void) {
let start = Date()
for _ in 0..<averagedExecutions { code() }
let end = Date()
let duration = end.timeIntervalSince(start) / Double(averagedExecutions)
print("time: \(duration)")
}
time {
(0...10_000).map { $0 * $0 }
}
// time: 0.183973908424377
Concurrency is definitely one of those topics were the right encapsulation bears the potential to make your life so much easier. For instance, with this piece of code you can easily launch two computations in parallel, and have the results returned in a tuple.
import Foundation
func parallel<T, U>(_ left: @autoclosure () -> T, _ right: @autoclosure () -> U) -> (T, U) {
var leftRes: T?
var rightRes: U?
DispatchQueue.concurrentPerform(iterations: 2, execute: { id in
if id == 0 {
leftRes = left()
} else {
rightRes = right()
}
})
return (leftRes!, rightRes!)
}
let values = (1...100_000).map { $0 }
let results = parallel(values.map { $0 * $0 }, values.reduce(0, +))
Swift exposes three special variables #file
, #line
and #function
, that are respectively set to the name of the current file, line and function. Those variables become very useful when writing custom logging functions or test predicates.
import Foundation
func log(_ message: String, _ file: String = #file, _ line: Int = #line, _ function: String = #function) {
print("[\(file):\(line)] \(function) - \(message)")
}
func foo() {
log("Hello world!")
}
foo() // [MyPlayground.playground:8] foo() - Hello world!
Swift 4.1 has introduced a new feature called Conditional Conformance, which allows a type to implement a protocol only when its generic type also does.
With this addition it becomes easy to let Optional
implement Comparable
only when Wrapped
also implements Comparable
:
import Foundation
extension Optional: Comparable where Wrapped: Comparable {
public static func < (lhs: Optional, rhs: Optional) -> Bool {
switch (lhs, rhs) {
case let (lhs?, rhs?):
return lhs < rhs
case (nil, _?):
return true // anything is greater than nil
case (_?, nil):
return false // nil in smaller than anything
case (nil, nil):
return true // nil is not smaller than itself
}
}
}
let data: [Int?] = [8, 4, 3, nil, 12, 4, 2, nil, -5]
data.sorted() // [nil, nil, Optional(-5), Optional(2), Optional(3), Optional(4), Optional(4), Optional(8), Optional(12)]
Any attempt to access an Array
beyond its bounds will result in a crash. While it's possible to write conditions such as if index < array.count { array[index] }
in order to prevent such crashes, this approach will rapidly become cumbersome.
A great thing is that this condition can be encapsulated in a custom subscript
that will work on any Collection
:
import Foundation
extension Collection {
subscript (safe index: Index) -> Element? {
return indices.contains(index) ? self[index] : nil
}
}
let data = [1, 3, 4]
data[safe: 1] // Optional(3)
data[safe: 10] // nil
Subscripting a string with a range can be very cumbersome in Swift 4. Let's face it, no one wants to write lines like someString[index(startIndex, offsetBy: 0)..<index(startIndex, offsetBy: 10)]
on a regular basis.
Luckily, with the addition of one clever extension, strings can be sliced as easily as arrays 🎉
import Foundation
extension String {
public subscript(value: CountableClosedRange<Int>) -> Substring {
get {
return self[index(startIndex, offsetBy: value.lowerBound)...index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: CountableRange<Int>) -> Substring {
get {
return self[index(startIndex, offsetBy: value.lowerBound)..<index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: PartialRangeUpTo<Int>) -> Substring {
get {
return self[..<index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: PartialRangeThrough<Int>) -> Substring {
get {
return self[...index(startIndex, offsetBy: value.upperBound)]
}
}
public subscript(value: PartialRangeFrom<Int>) -> Substring {
get {
return self[index(startIndex, offsetBy: value.lowerBound)...]
}
}
}
let data = "This is a string!"
data[..<4] // "This"
data[5..<9] // "is a"
data[10...] // "string!"
By using a KeyPath
along with a generic type, a very clean and concise syntax for sorting data can be implemented:
import Foundation
extension Sequence {
func sorted<T: Comparable>(by attribute: KeyPath<Element, T>) -> [Element] {
return sorted(by: { $0[keyPath: attribute] < $1[keyPath: attribute] })
}
}
let data = ["Some", "words", "of", "different", "lengths"]
data.sorted(by: \.count) // ["of", "Some", "words", "lengths", "different"]
If you like this syntax, make sure to checkout KeyPathKit!
By capturing a local variable in a returned closure, it is possible to manufacture cache-efficient versions of pure functions. Be careful though, this trick only works with non-recursive function!
import Foundation
func cached<In: Hashable, Out>(_ f: @escaping (In) -> Out) -> (In) -> Out {
var cache = [In: Out]()
return { (input: In) -> Out in
if let cachedValue = cache[input] {
return cachedValue
} else {
let result = f(input)
cache[input] = result
return result
}
}
}
let cachedCos = cached { (x: Double) in cos(x) }
cachedCos(.pi * 2) // value of cos for 2π is now cached
When distinguishing between complex boolean conditions, using a switch
statement along with pattern matching can be more readable than the classic series of if {} else if {}
.
import Foundation
let expr1: Bool
let expr2: Bool
let expr3: Bool
if expr1 && !expr3 {
functionA()
} else if !expr2 && expr3 {
functionB()
} else if expr1 && !expr2 && expr3 {
functionC()
}
switch (expr1, expr2, expr3) {
case (true, _, false):
functionA()
case (_, false, true):
functionB()
case (true, false, true):
functionC()
default:
break
}
Using map()
on a range makes it easy to generate an array of data.
import Foundation
func randomInt() -> Int { return Int(arc4random()) }
let randomArray = (1...10).map { _ in randomInt() }
Using @autoclosure
enables the compiler to automatically wrap an argument within a closure, thus allowing for a very clean syntax at call sites.
import UIKit
extension UIView {
class func animate(withDuration duration: TimeInterval, _ animations: @escaping @autoclosure () -> Void) {
UIView.animate(withDuration: duration, animations: animations)
}
}
let view = UIView()
UIView.animate(withDuration: 0.3, view.backgroundColor = .orange)
When working with RxSwift, it's very easy to observe both the current and previous value of an observable sequence by simply introducing a shift using skip()
.
import RxSwift
let values = Observable.of(4, 8, 15, 16, 23, 42)
let newAndOld = Observable.zip(values, values.skip(1)) { (previous: $0, current: $1) }
.subscribe(onNext: { pair in
print("current: \(pair.current) - previous: \(pair.previous)")
})
//current: 8 - previous: 4
//current: 15 - previous: 8
//current: 16 - previous: 15
//current: 23 - previous: 16
//current: 42 - previous: 23
Using protocols such as ExpressibleByStringLiteral
it is possible to provide an init
that will be automatically when a literal value is provided, allowing for nice and short syntax. This can be very helpful when writing mock or test data.
import Foundation
extension URL: ExpressibleByStringLiteral {
public init(stringLiteral value: String) {
self.init(string: value)!
}
}
let url: URL = "http://www.google.fr"
NSURLConnection.canHandle(URLRequest(url: "http://www.google.fr"))
Through some clever use of Swift private
visibility it is possible to define a container that holds any untrusted value (such as a user input) from which the only way to retrieve the value is by making it successfully pass a validation test.
import Foundation
struct Untrusted<T> {
private(set) var value: T
}
protocol Validator {
associatedtype T
static func validation(value: T) -> Bool
}
extension Validator {
static func validate(untrusted: Untrusted<T>) -> T? {
if self.validation(value: untrusted.value) {
return untrusted.value
} else {
return nil
}
}
}
struct FrenchPhoneNumberValidator: Validator {
static func validation(value: String) -> Bool {
return (value.count) == 10 && CharacterSet(charactersIn: value).isSubset(of: CharacterSet.decimalDigits)
}
}
let validInput = Untrusted(value: "0122334455")
let invalidInput = Untrusted(value: "0123")
FrenchPhoneNumberValidator.validate(untrusted: validInput) // returns "0122334455"
FrenchPhoneNumberValidator.validate(untrusted: invalidInput) // returns nil
With the addition of keypaths in Swift 4, it is now possible to easily implement the builder pattern, that allows the developer to clearly separate the code that initializes a value from the code that uses it, without the burden of defining a factory method.
import UIKit
protocol With {}
extension With where Self: AnyObject {
@discardableResult
func with<T>(_ property: ReferenceWritableKeyPath<Self, T>, setTo value: T) -> Self {
self[keyPath: property] = value
return self
}
}
extension UIView: With {}
let view = UIView()
let label = UILabel()
.with(\.textColor, setTo: .red)
.with(\.text, setTo: "Foo")
.with(\.textAlignment, setTo: .right)
.with(\.layer.cornerRadius, setTo: 5)
view.addSubview(label)
🚨 The Swift compiler does not perform OS availability checks on properties referenced by keypaths. Any attempt to use a KeyPath
for an unavailable property will result in a runtime crash.
I share the credit for this tip with Marion Curtil.
When a type stores values for the sole purpose of parametrizing its functions, it’s then possible to not store the values but directly the function, with no discernable difference at the call site.
import Foundation
struct MaxValidator {
let max: Int
let strictComparison: Bool
func isValid(_ value: Int) -> Bool {
return self.strictComparison ? value < self.max : value <= self.max
}
}
struct MaxValidator2 {
var isValid: (_ value: Int) -> Bool
init(max: Int, strictComparison: Bool) {
self.isValid = strictComparison ? { $0 < max } : { $0 <= max }
}
}
MaxValidator(max: 5, strictComparison: true).isValid(5) // false
MaxValidator2(max: 5, strictComparison: false).isValid(5) // true
Functions are first-class citizen types in Swift, so it is perfectly legal to define operators for them.
import Foundation
let firstRange = { (0...3).contains($0) }
let secondRange = { (5...6).contains($0) }
func ||(_ lhs: @escaping (Int) -> Bool, _ rhs: @escaping (Int) -> Bool) -> (Int) -> Bool {
return { value in
return lhs(value) || rhs(value)
}
}
(firstRange || secondRange)(2) // true
(firstRange || secondRange)(4) // false
(firstRange || secondRange)(6) // true
Typealiases are great to express function signatures in a more comprehensive manner, which then enables us to easily define functions that operate on them, resulting in a nice way to write and use some powerful API.
import Foundation
typealias RangeSet = (Int) -> Bool
func union(_ left: @escaping RangeSet, _ right: @escaping RangeSet) -> RangeSet {
return { left($0) || right($0) }
}
let firstRange = { (0...3).contains($0) }
let secondRange = { (5...6).contains($0) }
let unionRange = union(firstRange, secondRange)
unionRange(2) // true
unionRange(4) // false
By returning a closure that captures a local variable, it's possible to encapsulate a mutable state within a function.
import Foundation
func counterFactory() -> () -> Int {
var counter = 0
return {
counter += 1
return counter
}
}
let counter = counterFactory()
counter() // returns 1
counter() // returns 2
⚠️ Since Swift 4.2,
allCases
can now be synthesized at compile-time by simply conforming to the protocolCaseIterable
. The implementation below should no longer be used in production code.
Through some clever leveraging of how enums are stored in memory, it is possible to generate an array that contains all the possible cases of an enum. This can prove particularly useful when writing unit tests that consume random data.
import Foundation
enum MyEnum { case first; case second; case third; case fourth }
protocol EnumCollection: Hashable {
static var allCases: [Self] { get }
}
extension EnumCollection {
public static var allCases: [Self] {
var i = 0
return Array(AnyIterator {
let next = withUnsafePointer(to: &i) {
$0.withMemoryRebound(to: Self.self, capacity: 1) { $0.pointee }
}
if next.hashValue != i { return nil }
i += 1
return next
})
}
}
extension MyEnum: EnumCollection { }
MyEnum.allCases // [.first, .second, .third, .fourth]
The if-let syntax is a great way to deal with optional values in a safe manner, but at times it can prove to be just a little bit to cumbersome. In such cases, using the Optional.map()
function is a nice way to achieve a shorter code while retaining safeness and readability.
import UIKit
let date: Date? = Date() // or could be nil, doesn't matter
let formatter = DateFormatter()
let label = UILabel()
if let safeDate = date {
label.text = formatter.string(from: safeDate)
}
label.text = date.map { return formatter.string(from: $0) }
label.text = date.map(formatter.string(from:)) // even shorter, tough less readable
Author: Vincent-pradeilles
Source Code: https://github.com/vincent-pradeilles/swift-tips
License: MIT license
1662351030
在任何編程語言中,我們都需要處理數據。現在,我們需要處理數據的最基本的事情之一就是以有組織的方式有效地存儲、管理和訪問它,以便我們可以在需要時將其用於我們的目的。數據結構用於滿足我們所有的需求。
數據結構是編程語言的基本構建塊。它旨在提供一種系統的方法來滿足本文前面提到的所有要求。Python 中的數據結構是List、Tuple、Dictionary 和 Set。它們被視為Python 中的隱式或內置數據結構。我們可以使用這些數據結構並對它們應用多種方法來管理、關聯、操作和利用我們的數據。
我們還有用戶定義的自定義數據結構,即Stack、Queue、Tree、Linked List和Graph。它們允許用戶完全控制其功能並將其用於高級編程目的。但是,我們將專注於本文的內置數據結構。
隱式數據結構 Python
列表幫助我們以多種數據類型順序存儲數據。它們類似於數組,除了它們可以同時存儲不同的數據類型,如字符串和數字。列表中的每個項目或元素都有一個指定的索引。由於Python 使用基於 0 的索引,因此第一個元素的索引為 0,並且繼續計數。列表的最後一個元素以 -1 開頭,可用於訪問從最後一個到第一個的元素。要創建一個列表,我們必須將項目寫在方括號內。
關於列表要記住的最重要的事情之一是它們是可變的。這僅僅意味著我們可以通過使用索引運算符直接訪問它作為賦值語句的一部分來更改列表中的元素。我們還可以對列表執行操作以獲得所需的輸出。讓我們通過代碼來更好地理解列表和列表操作。
1. 創建列表
#creating the list
my_list = ['p', 'r', 'o', 'b', 'e']
print(my_list)
輸出
['p', 'r', 'o', 'b', 'e']
2. 訪問列表中的項目
#accessing the list
#accessing the first item of the list
my_list[0]
輸出
'p'
#accessing the third item of the list
my_list[2]
'o'
3. 向列表中添加新項目
#adding item to the list
my_list + ['k']
輸出
['p', 'r', 'o', 'b', 'e', 'k']
4. 移除物品
#removing item from the list
#Method 1:
#Deleting list items
my_list = ['p', 'r', 'o', 'b', 'l', 'e', 'm']
# delete one item
del my_list[2]
print(my_list)
# delete multiple items
del my_list[1:5]
print(my_list)
輸出
['p', 'r', 'b', 'l', 'e', 'm']
['p', 'm']
#Method 2:
#with remove fucntion
my_list = ['p','r','o','k','l','y','m']
my_list.remove('p')
print(my_list)
#Method 3:
#with pop function
print(my_list.pop(1))
# Output: ['r', 'k', 'l', 'y', 'm']
print(my_list)
輸出
['r', 'o', 'k', 'l', 'y', 'm']
o
['r', 'k', 'l', 'y', 'm']
5.排序列表
#sorting of list in ascending order
my_list.sort()
print(my_list)
輸出
['k', 'l', 'm', 'r', 'y']
#sorting of list in descending order
my_list.sort(reverse=True)
print(my_list)
輸出
['y', 'r', 'm', 'l', 'k']
6. 查找列表的長度
#finding the length of list
len(my_list)
輸出
5
元組與列表非常相似,關鍵區別在於元組是 IMMUTABLE,與列表不同。一旦我們創建了一個元組或有一個元組,我們就不能改變它裡面的元素。但是,如果我們在元組中有一個元素,它本身就是一個列表,那麼我們只能在該列表中訪問或更改。要創建一個元組,我們必須在括號內寫入項目。像列表一樣,我們有類似的方法可以用於元組。讓我們通過一些代碼片段來理解使用元組。
1. 創建一個元組
#creating of tuple
my_tuple = ("apple", "banana", "guava")
print(my_tuple)
輸出
('apple', 'banana', 'guava')
2. 從元組訪問項目
#accessing first element in tuple
my_tuple[1]
輸出
'banana'
3. 元組的長度
#for finding the lenght of tuple
len(my_tuple)
輸出
3
4. 將元組轉換為列表
#converting tuple into a list
my_tuple_list = list(my_tuple)
type(my_tuple_list)
輸出
list
5. 反轉元組
#Reversing a tuple
tuple(sorted(my_tuple, reverse=True))
輸出
('guava', 'banana', 'apple')
6. 對元組進行排序
#sorting tuple in ascending order
tuple(sorted(my_tuple))
輸出
('apple', 'banana', 'guava')
7. 從元組中刪除元素
為了從元組中刪除元素,我們首先將元組轉換為列表,就像我們在上面的方法之一(第 4 點)中所做的那樣,然後遵循列表的相同過程,並顯式刪除整個元組,只需使用del聲明。
字典是一個集合,它只是意味著它用於存儲帶有某個鍵的值並提取給定鍵的值。我們可以將其視為一組鍵:值對 和字典中的每個鍵都應該是唯一的,以便我們可以相應地訪問相應的值。
字典由包含鍵:值對的花括號 { }表示。字典中的每一對都以逗號分隔。字典中的元素是無序的,當我們訪問或存儲它們時,序列並不重要。
它們是可變的,這意味著我們可以在字典中添加、刪除或更新元素。以下是一些代碼示例,可以更好地理解 python 中的字典。
需要注意的重要一點是,我們不能將可變對像用作字典中的鍵。因此,列表不允許作為字典中的鍵。
1. 創建字典
#creating a dictionary
my_dict = {
1:'Delhi',
2:'Patna',
3:'Bangalore'
}
print(my_dict)
輸出
{1: 'Delhi', 2: 'Patna', 3: 'Bangalore'}
這裡,整數是字典的鍵,與整數相關的城市名稱是字典的值。
2. 從字典中訪問項目
#access an item
print(my_dict[1])
輸出
'Delhi'
3. 字典的長度
#length of the dictionary
len(my_dict)
輸出
3
4. 對字典進行排序
#sorting based on the key
Print(sorted(my_dict.items()))
#sorting based on the values of dictionary
print(sorted(my_dict.values()))
輸出
[(1, 'Delhi'), (2, 'Bangalore'), (3, 'Patna')]
['Bangalore', 'Delhi', 'Patna']
5. 在字典中添加元素
#adding a new item in dictionary
my_dict[4] = 'Lucknow'
print(my_dict)
輸出
{1: 'Delhi', 2: 'Patna', 3: 'Bangalore', 4: 'Lucknow'}
6.從字典中刪除元素
#for deleting an item from dict using the specific key
my_dict.pop(4)
print(my_dict)
#for deleting last item from the list
my_dict.popitem()
#for clearing the dictionary
my_dict.clear()
print(my_dict)
輸出
{1: 'Delhi', 2: 'Patna', 3: 'Bangalore'}
(3, 'Bangalore')
{}
Set 是 python 中的另一種數據類型,它是一個沒有重複元素的無序集合。集合的常見用例是刪除重複值並執行成員資格測試。花括號或set()函數可用於創建集合。要記住的一件事是,在創建空集時,我們必須使用set(),和。後者創建一個空字典。 not { }
以下是一些代碼示例,可幫助您更好地理解 Python 中的集合。
1. 創建一個 集合
#creating set
my_set = {"apple", "mango", "strawberry", "apple"}
print(my_set)
輸出
{'apple', 'strawberry', 'mango'}
2. 訪問集合中的項目
#to test for an element inside the set
"apple" in my_set
輸出
True
3. 集合的長度
print(len(my_set))
輸出
3
4. 對集合進行排序
print(sorted(my_set))
輸出
['apple', 'mango', 'strawberry']
5. 在Set中添加元素
my_set.add("guava")
print(my_set)
輸出
{'apple', 'guava', 'mango', 'strawberry'}
6. 從 Set 中移除元素
my_set.remove("mango")
print(my_set)
輸出
{'apple', 'guava', 'strawberry'}
在本文中,我們瀏覽了 Python 中最常用的數據結構,並了解了與它們相關的各種方法。
鏈接:https ://www.askpython.com/python/data
#python #datastructures