1597320300
SFTP (SSH File Transfer Protocol) is a secure file protocol that is used to access, manage, and transfer files over an encrypted SSH transport.
When compared with the traditional FTP protocol, SFTP offers all the functionality of FTP, but it is more secure and easier to configure.
Unlike SCP , which supports only file transfers, the SFTP allows you to perform a range of operations on remote files and resume file transfers.
In this tutorial, we will show you how to use the Linux sftp
command.
To be able to transfer files via SFTP you must have write permission on the remote system.
When transferring large files, it is recommended to run the sftp
command inside a screen or tmux session.
The directory from where you run the sftp
command is the local working directory.
Don’t confuse SFTP with FTPS. Both protocol serve the same purpose. However, FTPS stands for FTP Secure, and it is an extension to the standard FTP protocol with support for TLS.
SFTP works on a client-server model. It is a subsystem of SSH and supports all SSH authentication mechanisms.
To open an SFTP connection to a remote system, use the sftp
command followed by the remote server username and the IP address or domain name:
sftp remote_username@server_ip_or_hostname
If you are connecting to the host using password authentication, you will be prompted to enter the user password.
Once connected, you will be presented with the sftp
prompt, and you can start interacting with the remote server:
Connected to remote_username@server_ip_or_hostname.
sftp>
If the remote SSH server is not listening on the default port 22 , use the -P
option to specify the SFTP port:
sftp -P custom_port remote_username@server_ip_or_hostname
Most of the SFTP commands are similar or identical to the Linux shell commands.
To get a list of all available SFTP commands, type help
, or ?
.
help
This will output a long list of all available commands, including a short description of each command:
Available commands:
bye Quit sftp
cd path Change remote directory to 'path'
...
...
version Show SFTP version
!command Execute 'command' in local shell
! Escape to local shell
? Synonym for help
When you are logged in to the remote server, your current working directory is the remote user home directory. You can check that by typing:
pwd
Remote working directory: /home/remote_username
To list the files and directories, use the ls
command:
ls
To navigate to another directory, use the cd
command. For example, to switch to the /tmp
directory you would type:
cd /tmp
The above commands are used to navigate, and work on the remote location.
The SFTP shell also provides commands for local navigation, information and file management. The local commands are prefixed with the letter l
.
For example, to print the local working directory, you would type:
cd lpwd
Local working directory: /home/local_username
#linux
1667425440
Perl script converts PDF files to Gerber format
Pdf2Gerb generates Gerber 274X photoplotting and Excellon drill files from PDFs of a PCB. Up to three PDFs are used: the top copper layer, the bottom copper layer (for 2-sided PCBs), and an optional silk screen layer. The PDFs can be created directly from any PDF drawing software, or a PDF print driver can be used to capture the Print output if the drawing software does not directly support output to PDF.
The general workflow is as follows:
Please note that Pdf2Gerb does NOT perform DRC (Design Rule Checks), as these will vary according to individual PCB manufacturer conventions and capabilities. Also note that Pdf2Gerb is not perfect, so the output files must always be checked before submitting them. As of version 1.6, Pdf2Gerb supports most PCB elements, such as round and square pads, round holes, traces, SMD pads, ground planes, no-fill areas, and panelization. However, because it interprets the graphical output of a Print function, there are limitations in what it can recognize (or there may be bugs).
See docs/Pdf2Gerb.pdf for install/setup, config, usage, and other info.
#Pdf2Gerb config settings:
#Put this file in same folder/directory as pdf2gerb.pl itself (global settings),
#or copy to another folder/directory with PDFs if you want PCB-specific settings.
#There is only one user of this file, so we don't need a custom package or namespace.
#NOTE: all constants defined in here will be added to main namespace.
#package pdf2gerb_cfg;
use strict; #trap undef vars (easier debug)
use warnings; #other useful info (easier debug)
##############################################################################################
#configurable settings:
#change values here instead of in main pfg2gerb.pl file
use constant WANT_COLORS => ($^O !~ m/Win/); #ANSI colors no worky on Windows? this must be set < first DebugPrint() call
#just a little warning; set realistic expectations:
#DebugPrint("${\(CYAN)}Pdf2Gerb.pl ${\(VERSION)}, $^O O/S\n${\(YELLOW)}${\(BOLD)}${\(ITALIC)}This is EXPERIMENTAL software. \nGerber files MAY CONTAIN ERRORS. Please CHECK them before fabrication!${\(RESET)}", 0); #if WANT_DEBUG
use constant METRIC => FALSE; #set to TRUE for metric units (only affect final numbers in output files, not internal arithmetic)
use constant APERTURE_LIMIT => 0; #34; #max #apertures to use; generate warnings if too many apertures are used (0 to not check)
use constant DRILL_FMT => '2.4'; #'2.3'; #'2.4' is the default for PCB fab; change to '2.3' for CNC
use constant WANT_DEBUG => 0; #10; #level of debug wanted; higher == more, lower == less, 0 == none
use constant GERBER_DEBUG => 0; #level of debug to include in Gerber file; DON'T USE FOR FABRICATION
use constant WANT_STREAMS => FALSE; #TRUE; #save decompressed streams to files (for debug)
use constant WANT_ALLINPUT => FALSE; #TRUE; #save entire input stream (for debug ONLY)
#DebugPrint(sprintf("${\(CYAN)}DEBUG: stdout %d, gerber %d, want streams? %d, all input? %d, O/S: $^O, Perl: $]${\(RESET)}\n", WANT_DEBUG, GERBER_DEBUG, WANT_STREAMS, WANT_ALLINPUT), 1);
#DebugPrint(sprintf("max int = %d, min int = %d\n", MAXINT, MININT), 1);
#define standard trace and pad sizes to reduce scaling or PDF rendering errors:
#This avoids weird aperture settings and replaces them with more standardized values.
#(I'm not sure how photoplotters handle strange sizes).
#Fewer choices here gives more accurate mapping in the final Gerber files.
#units are in inches
use constant TOOL_SIZES => #add more as desired
(
#round or square pads (> 0) and drills (< 0):
.010, -.001, #tiny pads for SMD; dummy drill size (too small for practical use, but needed so StandardTool will use this entry)
.031, -.014, #used for vias
.041, -.020, #smallest non-filled plated hole
.051, -.025,
.056, -.029, #useful for IC pins
.070, -.033,
.075, -.040, #heavier leads
# .090, -.043, #NOTE: 600 dpi is not high enough resolution to reliably distinguish between .043" and .046", so choose 1 of the 2 here
.100, -.046,
.115, -.052,
.130, -.061,
.140, -.067,
.150, -.079,
.175, -.088,
.190, -.093,
.200, -.100,
.220, -.110,
.160, -.125, #useful for mounting holes
#some additional pad sizes without holes (repeat a previous hole size if you just want the pad size):
.090, -.040, #want a .090 pad option, but use dummy hole size
.065, -.040, #.065 x .065 rect pad
.035, -.040, #.035 x .065 rect pad
#traces:
.001, #too thin for real traces; use only for board outlines
.006, #minimum real trace width; mainly used for text
.008, #mainly used for mid-sized text, not traces
.010, #minimum recommended trace width for low-current signals
.012,
.015, #moderate low-voltage current
.020, #heavier trace for power, ground (even if a lighter one is adequate)
.025,
.030, #heavy-current traces; be careful with these ones!
.040,
.050,
.060,
.080,
.100,
.120,
);
#Areas larger than the values below will be filled with parallel lines:
#This cuts down on the number of aperture sizes used.
#Set to 0 to always use an aperture or drill, regardless of size.
use constant { MAX_APERTURE => max((TOOL_SIZES)) + .004, MAX_DRILL => -min((TOOL_SIZES)) + .004 }; #max aperture and drill sizes (plus a little tolerance)
#DebugPrint(sprintf("using %d standard tool sizes: %s, max aper %.3f, max drill %.3f\n", scalar((TOOL_SIZES)), join(", ", (TOOL_SIZES)), MAX_APERTURE, MAX_DRILL), 1);
#NOTE: Compare the PDF to the original CAD file to check the accuracy of the PDF rendering and parsing!
#for example, the CAD software I used generated the following circles for holes:
#CAD hole size: parsed PDF diameter: error:
# .014 .016 +.002
# .020 .02267 +.00267
# .025 .026 +.001
# .029 .03167 +.00267
# .033 .036 +.003
# .040 .04267 +.00267
#This was usually ~ .002" - .003" too big compared to the hole as displayed in the CAD software.
#To compensate for PDF rendering errors (either during CAD Print function or PDF parsing logic), adjust the values below as needed.
#units are pixels; for example, a value of 2.4 at 600 dpi = .0004 inch, 2 at 600 dpi = .0033"
use constant
{
HOLE_ADJUST => -0.004 * 600, #-2.6, #holes seemed to be slightly oversized (by .002" - .004"), so shrink them a little
RNDPAD_ADJUST => -0.003 * 600, #-2, #-2.4, #round pads seemed to be slightly oversized, so shrink them a little
SQRPAD_ADJUST => +0.001 * 600, #+.5, #square pads are sometimes too small by .00067, so bump them up a little
RECTPAD_ADJUST => 0, #(pixels) rectangular pads seem to be okay? (not tested much)
TRACE_ADJUST => 0, #(pixels) traces seemed to be okay?
REDUCE_TOLERANCE => .001, #(inches) allow this much variation when reducing circles and rects
};
#Also, my CAD's Print function or the PDF print driver I used was a little off for circles, so define some additional adjustment values here:
#Values are added to X/Y coordinates; units are pixels; for example, a value of 1 at 600 dpi would be ~= .002 inch
use constant
{
CIRCLE_ADJUST_MINX => 0,
CIRCLE_ADJUST_MINY => -0.001 * 600, #-1, #circles were a little too high, so nudge them a little lower
CIRCLE_ADJUST_MAXX => +0.001 * 600, #+1, #circles were a little too far to the left, so nudge them a little to the right
CIRCLE_ADJUST_MAXY => 0,
SUBST_CIRCLE_CLIPRECT => FALSE, #generate circle and substitute for clip rects (to compensate for the way some CAD software draws circles)
WANT_CLIPRECT => TRUE, #FALSE, #AI doesn't need clip rect at all? should be on normally?
RECT_COMPLETION => FALSE, #TRUE, #fill in 4th side of rect when 3 sides found
};
#allow .012 clearance around pads for solder mask:
#This value effectively adjusts pad sizes in the TOOL_SIZES list above (only for solder mask layers).
use constant SOLDER_MARGIN => +.012; #units are inches
#line join/cap styles:
use constant
{
CAP_NONE => 0, #butt (none); line is exact length
CAP_ROUND => 1, #round cap/join; line overhangs by a semi-circle at either end
CAP_SQUARE => 2, #square cap/join; line overhangs by a half square on either end
CAP_OVERRIDE => FALSE, #cap style overrides drawing logic
};
#number of elements in each shape type:
use constant
{
RECT_SHAPELEN => 6, #x0, y0, x1, y1, count, "rect" (start, end corners)
LINE_SHAPELEN => 6, #x0, y0, x1, y1, count, "line" (line seg)
CURVE_SHAPELEN => 10, #xstart, ystart, x0, y0, x1, y1, xend, yend, count, "curve" (bezier 2 points)
CIRCLE_SHAPELEN => 5, #x, y, 5, count, "circle" (center + radius)
};
#const my %SHAPELEN =
#Readonly my %SHAPELEN =>
our %SHAPELEN =
(
rect => RECT_SHAPELEN,
line => LINE_SHAPELEN,
curve => CURVE_SHAPELEN,
circle => CIRCLE_SHAPELEN,
);
#panelization:
#This will repeat the entire body the number of times indicated along the X or Y axes (files grow accordingly).
#Display elements that overhang PCB boundary can be squashed or left as-is (typically text or other silk screen markings).
#Set "overhangs" TRUE to allow overhangs, FALSE to truncate them.
#xpad and ypad allow margins to be added around outer edge of panelized PCB.
use constant PANELIZE => {'x' => 1, 'y' => 1, 'xpad' => 0, 'ypad' => 0, 'overhangs' => TRUE}; #number of times to repeat in X and Y directions
# Set this to 1 if you need TurboCAD support.
#$turboCAD = FALSE; #is this still needed as an option?
#CIRCAD pad generation uses an appropriate aperture, then moves it (stroke) "a little" - we use this to find pads and distinguish them from PCB holes.
use constant PAD_STROKE => 0.3; #0.0005 * 600; #units are pixels
#convert very short traces to pads or holes:
use constant TRACE_MINLEN => .001; #units are inches
#use constant ALWAYS_XY => TRUE; #FALSE; #force XY even if X or Y doesn't change; NOTE: needs to be TRUE for all pads to show in FlatCAM and ViewPlot
use constant REMOVE_POLARITY => FALSE; #TRUE; #set to remove subtractive (negative) polarity; NOTE: must be FALSE for ground planes
#PDF uses "points", each point = 1/72 inch
#combined with a PDF scale factor of .12, this gives 600 dpi resolution (1/72 * .12 = 600 dpi)
use constant INCHES_PER_POINT => 1/72; #0.0138888889; #multiply point-size by this to get inches
# The precision used when computing a bezier curve. Higher numbers are more precise but slower (and generate larger files).
#$bezierPrecision = 100;
use constant BEZIER_PRECISION => 36; #100; #use const; reduced for faster rendering (mainly used for silk screen and thermal pads)
# Ground planes and silk screen or larger copper rectangles or circles are filled line-by-line using this resolution.
use constant FILL_WIDTH => .01; #fill at most 0.01 inch at a time
# The max number of characters to read into memory
use constant MAX_BYTES => 10 * M; #bumped up to 10 MB, use const
use constant DUP_DRILL1 => TRUE; #FALSE; #kludge: ViewPlot doesn't load drill files that are too small so duplicate first tool
my $runtime = time(); #Time::HiRes::gettimeofday(); #measure my execution time
print STDERR "Loaded config settings from '${\(__FILE__)}'.\n";
1; #last value must be truthful to indicate successful load
#############################################################################################
#junk/experiment:
#use Package::Constants;
#use Exporter qw(import); #https://perldoc.perl.org/Exporter.html
#my $caller = "pdf2gerb::";
#sub cfg
#{
# my $proto = shift;
# my $class = ref($proto) || $proto;
# my $settings =
# {
# $WANT_DEBUG => 990, #10; #level of debug wanted; higher == more, lower == less, 0 == none
# };
# bless($settings, $class);
# return $settings;
#}
#use constant HELLO => "hi there2"; #"main::HELLO" => "hi there";
#use constant GOODBYE => 14; #"main::GOODBYE" => 12;
#print STDERR "read cfg file\n";
#our @EXPORT_OK = Package::Constants->list(__PACKAGE__); #https://www.perlmonks.org/?node_id=1072691; NOTE: "_OK" skips short/common names
#print STDERR scalar(@EXPORT_OK) . " consts exported:\n";
#foreach(@EXPORT_OK) { print STDERR "$_\n"; }
#my $val = main::thing("xyz");
#print STDERR "caller gave me $val\n";
#foreach my $arg (@ARGV) { print STDERR "arg $arg\n"; }
Author: swannman
Source Code: https://github.com/swannman/pdf2gerb
License: GPL-3.0 license
1661577180
The following is a collection of tips I find to be useful when working with the Swift language. More content is available on my Twitter account!
Property Wrappers allow developers to wrap properties with specific behaviors, that will be seamlessly triggered whenever the properties are accessed.
While their primary use case is to implement business logic within our apps, it's also possible to use Property Wrappers as debugging tools!
For example, we could build a wrapper called @History
, that would be added to a property while debugging and would keep track of all the values set to this property.
import Foundation
@propertyWrapper
struct History<Value> {
private var value: Value
private(set) var history: [Value] = []
init(wrappedValue: Value) {
self.value = wrappedValue
}
var wrappedValue: Value {
get { value }
set {
history.append(value)
value = newValue
}
}
var projectedValue: Self {
return self
}
}
// We can then decorate our business code
// with the `@History` wrapper
struct User {
@History var name: String = ""
}
var user = User()
// All the existing call sites will still
// compile, without the need for any change
user.name = "John"
user.name = "Jane"
// But now we can also access an history of
// all the previous values!
user.$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: $0) }
label.text = date.map(formatter.string(from:)) // even shorter, tough less readable
📣 NEW 📣 Swift Tips are now available on YouTube 👇
Summary
String
interpolationstructs
NSAttributedString
through a Function Builderswitch
and if
as expressionsguard
statementsinit
without loosing the compiler-generated oneenum
Never
to represent impossible code pathsDecodable
enum
[weak self]
and guard
userInfo
Dictionary
typealias
to its fullestforEach
reduce()
Optional
booleansSequence
nil
valuesmap()
Tips
Author: vincent-pradeilles
Source code: https://github.com/vincent-pradeilles/swift-tips
License: MIT license
#swift
1673365703
The following is a collection of tips I find to be useful when working with the Swift language. More content is available on my Twitter account!
📣 NEW 📣 Swift Tips are now available on YouTube 👇
Tips
Property Wrappers allow developers to wrap properties with specific behaviors, that will be seamlessly triggered whenever the properties are accessed.
While their primary use case is to implement business logic within our apps, it's also possible to use Property Wrappers as debugging tools!
For example, we could build a wrapper called @History
, that would be added to a property while debugging and would keep track of all the values set to this property.
import Foundation
@propertyWrapper
struct History<Value> {
private var value: Value
private(set) var history: [Value] = []
init(wrappedValue: Value) {
self.value = wrappedValue
}
var wrappedValue: Value {
get { value }
set {
history.append(value)
value = newValue
}
}
var projectedValue: Self {
return self
}
}
// We can then decorate our business code
// with the `@History` wrapper
struct User {
@History var name: String = ""
}
var user = User()
// All the existing call sites will still
// compile, without the need for any change
user.name = "John"
user.name = "Jane"
// But now we can also access an history of
// all the previous values!
user.$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
1606197240
Files by Google
Google’s official file-manager app offers functionality for sharing files between Android devices. Users can share any quite file with a speed of up to 480 Mbps. the simplest part is that file-sharing even works offline, as long as both parties have the Files app installed on their Android devices. android file transfer app
Since the app is from the Android maker itself, you’ll make certain of knowledge privacy. The Android app uses WPA2 encryption to form file-sharing secure. Overall, Files by Google is one among the simplest file-sharing apps because not only are you able to share files at relentless speeds, you’ll use it as a file-manager also . The Android app is free and has no ads.
Play Store Rating — 4.6
App installs — quite five hundred million
#android file transfer app #file transfer app #best android file transfer app #transfer app
1620729846
Can you use WordPress for anything other than blogging? To your surprise, yes. WordPress is more than just a blogging tool, and it has helped thousands of websites and web applications to thrive. The use of WordPress powers around 40% of online projects, and today in our blog, we would visit some amazing uses of WordPress other than blogging.
What Is The Use Of WordPress?
WordPress is the most popular website platform in the world. It is the first choice of businesses that want to set a feature-rich and dynamic Content Management System. So, if you ask what WordPress is used for, the answer is – everything. It is a super-flexible, feature-rich and secure platform that offers everything to build unique websites and applications. Let’s start knowing them:
1. Multiple Websites Under A Single Installation
WordPress Multisite allows you to develop multiple sites from a single WordPress installation. You can download WordPress and start building websites you want to launch under a single server. Literally speaking, you can handle hundreds of sites from one single dashboard, which now needs applause.
It is a highly efficient platform that allows you to easily run several websites under the same login credentials. One of the best things about WordPress is the themes it has to offer. You can simply download them and plugin for various sites and save space on sites without losing their speed.
2. WordPress Social Network
WordPress can be used for high-end projects such as Social Media Network. If you don’t have the money and patience to hire a coder and invest months in building a feature-rich social media site, go for WordPress. It is one of the most amazing uses of WordPress. Its stunning CMS is unbeatable. And you can build sites as good as Facebook or Reddit etc. It can just make the process a lot easier.
To set up a social media network, you would have to download a WordPress Plugin called BuddyPress. It would allow you to connect a community page with ease and would provide all the necessary features of a community or social media. It has direct messaging, activity stream, user groups, extended profiles, and so much more. You just have to download and configure it.
If BuddyPress doesn’t meet all your needs, don’t give up on your dreams. You can try out WP Symposium or PeepSo. There are also several themes you can use to build a social network.
3. Create A Forum For Your Brand’s Community
Communities are very important for your business. They help you stay in constant connection with your users and consumers. And allow you to turn them into a loyal customer base. Meanwhile, there are many good technologies that can be used for building a community page – the good old WordPress is still the best.
It is the best community development technology. If you want to build your online community, you need to consider all the amazing features you get with WordPress. Plugins such as BB Press is an open-source, template-driven PHP/ MySQL forum software. It is very simple and doesn’t hamper the experience of the website.
Other tools such as wpFoRo and Asgaros Forum are equally good for creating a community blog. They are lightweight tools that are easy to manage and integrate with your WordPress site easily. However, there is only one tiny problem; you need to have some technical knowledge to build a WordPress Community blog page.
4. Shortcodes
Since we gave you a problem in the previous section, we would also give you a perfect solution for it. You might not know to code, but you have shortcodes. Shortcodes help you execute functions without having to code. It is an easy way to build an amazing website, add new features, customize plugins easily. They are short lines of code, and rather than memorizing multiple lines; you can have zero technical knowledge and start building a feature-rich website or application.
There are also plugins like Shortcoder, Shortcodes Ultimate, and the Basics available on WordPress that can be used, and you would not even have to remember the shortcodes.
5. Build Online Stores
If you still think about why to use WordPress, use it to build an online store. You can start selling your goods online and start selling. It is an affordable technology that helps you build a feature-rich eCommerce store with WordPress.
WooCommerce is an extension of WordPress and is one of the most used eCommerce solutions. WooCommerce holds a 28% share of the global market and is one of the best ways to set up an online store. It allows you to build user-friendly and professional online stores and has thousands of free and paid extensions. Moreover as an open-source platform, and you don’t have to pay for the license.
Apart from WooCommerce, there are Easy Digital Downloads, iThemes Exchange, Shopify eCommerce plugin, and so much more available.
6. Security Features
WordPress takes security very seriously. It offers tons of external solutions that help you in safeguarding your WordPress site. While there is no way to ensure 100% security, it provides regular updates with security patches and provides several plugins to help with backups, two-factor authorization, and more.
By choosing hosting providers like WP Engine, you can improve the security of the website. It helps in threat detection, manage patching and updates, and internal security audits for the customers, and so much more.
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