10 Best Golang Libraries for Generating & Working with Log Files

In today's post we will learn about 10 Best Golang Libraries for Generating & Working with Log Files. 

What is a log file?

A log file is a computer-generated data file that contains information about usage patterns, activities, and operations within an operating system, application, server or another device, and is the primary data source for network observability. Log files show whether resources are performing properly and optimally, exposing possible.

Table of contents:

  • Distillog - Distilled levelled logging (think of it as stdlib + log levels).
  • Glg - glg is simple and fast leveled logging library for Go.
  • Glo - PHP Monolog inspired logging facility with identical severity levels.
  • Glog - Leveled execution logs for Go.
  • Go-cronowriter - Simple writer that rotate log files automatically based on current date and time, like cronolog.
  • Go-log - A logging library with stack traces, object dumping and optional timestamps.
  • Go-log - Simple and configurable Logging in Go, with level, formatters and writers.
  • Go-log - Log lib supports level and multi handlers.
  • Go-log - Log4j implementation in Go.
  • Go-logger - Simple logger of Go Programs, with level handlers.

1 - Distillog: Distilled levelled logging (think of it as stdlib + log levels).

What is distillog?

distillog aims to offer a minimalistic logging interface that also supports log levels. It takes the stdlib API and only slightly enhances it. Hence, you could think of it as levelled logging, distilled.

Yet another logging library for go(lang)?

Logging libraries are like opinions, everyone seems to have one -- Anon(?)

Most other logging libraries do either too little (stdlib) or too much (glog).

As with most other libraries, this one is opinionated. In terms of functionality it exposes, it attempts to sit somewhere between the stdlib and the majority of other logging libraries available (but leans mostly towards the spartan side of stdlib).

Expose an interface? Why?

By exposing an interface you can write programs that use levelled log messages, but switch between logging to various facilities by simply instantiating the appropriate logger as determined by the caller (Your program can offer a command-line switch like so - --log-to=[syslog,stderr,<file>] and the simply instantiate the appropriate logger).

Usage/examples:

As seen in the godoc, the interface is limited to:

type Logger interface {
	Debugf(format string, v ...interface{})
	Debugln(v ...interface{})

	Infof(format string, v ...interface{})
	Infoln(v ...interface{})

	Warningf(format string, v ...interface{})
	Warningln(v ...interface{})

	Errorf(format string, v ...interface{})
	Errorln(v ...interface{})

	Close() error
}

Log to stdout, or stderr using a logger instantiated like so:

outLogger := distillog.NewStdoutLogger("test")

errLogger := distillog.NewStderrLogger("test")

sysLogger := distillog.NewSyslogLogger("test")

Alternatively, you can use the package for your logging needs:

import log "github.com/amoghe/distillog"

// ... later ...

log.Infoln("Starting program")
log.Debugln("initializing the frobnicator")
log.Warningln("frobnicator failure detected, proceeding anyways...")
log.Infoln("Exiting")

If you have a file you wish to log to, you should open the file and instantiate a logger using the file handle, like so:

if fileHandle, err := ioutil.Tempfile("/tmp", "distillog-test"); err == nil {
        fileLogger := distillog.NewStreamLogger("test", fileHandle)
}

If you need a logger that manages the rotation of its files, use lumberjack, like so:

lumberjackHandle := &lumberjack.Logger{
        Filename:   "/var/log/myapp/foo.log",
        MaxSize:    500,                       // megabytes
        MaxBackups: 3,
        MaxAge:     28,                        // days
}

logger := distillog.NewStreamLogger("tag", lumberjackHandle)

// Alternatively, configure the pkg level logger to emit here

distillog.SetOutput(lumberjackHandle)

Once instantiated, you can log messages, like so:

var := "World!"
myLogger.Infof("Hello, %s", var)
myLogger.Warningln("Goodbye, cruel world!")

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2 - Glg: glg is simple and fast leveled logging library for Go.

glg is simple golang logging library

Requirement

Go 1.16

Installation

go get github.com/kpango/glg

Example

package main

import (
	"net/http"
	"time"

	"github.com/kpango/glg"
)

// NetWorkLogger sample network logger
type NetWorkLogger struct{}

func (n NetWorkLogger) Write(b []byte) (int, error) {
	// http.Post("localhost:8080/log", "", bytes.NewReader(b))
	http.Get("http://127.0.0.1:8080/log")
	glg.Success("Requested")
	glg.Infof("RawString is %s", glg.RawString(b))
	return 1, nil
}

func main() {

	// var errWriter io.Writer
	// var customWriter io.Writer
	infolog := glg.FileWriter("/tmp/info.log", 0666)

	customTag := "FINE"
	customErrTag := "CRIT"

	errlog := glg.FileWriter("/tmp/error.log", 0666)
	defer infolog.Close()
	defer errlog.Close()

	glg.Get().
		SetMode(glg.BOTH). // default is STD
		// DisableColor().
		// SetMode(glg.NONE).
		// SetMode(glg.WRITER).
		// SetMode(glg.BOTH).
		// InitWriter().
		// AddWriter(customWriter).
		// SetWriter(customWriter).
		// AddLevelWriter(glg.LOG, customWriter).
		// AddLevelWriter(glg.INFO, customWriter).
		// AddLevelWriter(glg.WARN, customWriter).
		// AddLevelWriter(glg.ERR, customWriter).
		// SetLevelWriter(glg.LOG, customWriter).
		// SetLevelWriter(glg.INFO, customWriter).
		// SetLevelWriter(glg.WARN, customWriter).
		// SetLevelWriter(glg.ERR, customWriter).
		// EnableJSON().
		SetLineTraceMode(glg.TraceLineNone).
		AddLevelWriter(glg.INFO, infolog). // add info log file destination
		AddLevelWriter(glg.ERR, errlog).   // add error log file destination
		AddLevelWriter(glg.WARN, rotate)   // add error log file destination

	glg.Info("info")
	glg.Infof("%s : %s", "info", "formatted")
	glg.Log("log")
	glg.Logf("%s : %s", "info", "formatted")
	glg.Debug("debug")
	glg.Debugf("%s : %s", "info", "formatted")
	glg.Trace("Trace")
	glg.Tracef("%s : %s", "tracef", "formatted")
	glg.Warn("warn")
	glg.Warnf("%s : %s", "info", "formatted")
	glg.Error("error")
	glg.Errorf("%s : %s", "info", "formatted")
	glg.Success("ok")
	glg.Successf("%s : %s", "info", "formatted")
	glg.Fail("fail")
	glg.Failf("%s : %s", "info", "formatted")
	glg.Print("Print")
	glg.Println("Println")
	glg.Printf("%s : %s", "printf", "formatted")

	// set global log level to ERR level
	glg.Info("before setting level to ERR this message will show")
	glg.Get().SetLevel(glg.ERR)
	glg.Info("after setting level to ERR this message will not show")
	glg.Error("this log is ERR level this will show")
	glg.Get().SetLevel(glg.DEBG)
	glg.Info("log level is now DEBG, this INFO level log will show")

	glg.Get().
		AddStdLevel(customTag, glg.STD, false).                    // user custom log level
		AddErrLevel(customErrTag, glg.STD, true).                  // user custom error log level
		SetLevelColor(glg.TagStringToLevel(customTag), glg.Cyan).  // set color output to user custom level
		SetLevelColor(glg.TagStringToLevel(customErrTag), glg.Red) // set color output to user custom level
	glg.CustomLog(customTag, "custom logging")
	glg.CustomLog(customErrTag, "custom error logging")

	// glg.Info("kpango's glg supports disable timestamp for logging")
	glg.Get().DisableTimestamp()
	glg.Info("timestamp disabled")
	glg.Warn("timestamp disabled")
	glg.Log("timestamp disabled")
	glg.Get().EnableTimestamp()
	glg.Info("timestamp enabled")
	glg.Warn("timestamp enabled")
	glg.Log("timestamp enabled")

	glg.Info("kpango's glg support line trace logging")
	glg.Error("error log shows short line trace by default")
	glg.Info("error log shows none trace by default")
	glg.Get().SetLineTraceMode(glg.TraceLineShort)
	glg.Error("after configure TraceLineShort, error log shows short line trace")
	glg.Info("after configure TraceLineShort, info log shows short line trace")
	glg.Get().DisableTimestamp()
	glg.Error("after configure TraceLineShort and DisableTimestamp, error log shows short line trace without timestamp")
	glg.Info("after configure TraceLineShort and DisableTimestamp, info log shows short line trace without timestamp")
	glg.Get().EnableTimestamp()
	glg.Get().SetLineTraceMode(glg.TraceLineLong)
	glg.Error("after configure TraceLineLong, error log shows long line trace")
	glg.Info("after configure TraceLineLong, info log shows long line trace")
	glg.Get().DisableTimestamp()
	glg.Error("after configure TraceLineLong and DisableTimestamp, error log shows long line trace without timestamp")
	glg.Info("after configure TraceLineLong and DisableTimestamp, info log shows long line trace without timestamp")
	glg.Get().EnableTimestamp()
	glg.Get().SetLineTraceMode(glg.TraceLineNone)
	glg.Error("after configure TraceLineNone, error log without line trace")
	glg.Info("after configure TraceLineNone, info log without line trace")
	glg.Get().SetLevelLineTraceMode(glg.INFO, glg.TraceLineLong)
	glg.Info("after configure Level trace INFO=TraceLineLong, only info log shows long line trace")
	glg.Error("after configure Level trace INFO=TraceLineLong, error log without long line trace")
	glg.Get().SetLevelLineTraceMode(glg.ERR, glg.TraceLineShort)
	glg.Info("after configure Level trace ERR=TraceLineShort, info log still shows long line trace")
	glg.Error("after configure Level trace ERR=TraceLineShort, error log now shows short line trace")
	glg.Get().SetLineTraceMode(glg.TraceLineNone)

	glg.Info("kpango's glg support json logging")
	glg.Get().EnableJSON()
	err := glg.Warn("kpango's glg", "support", "json", "logging")
	if err != nil {
		glg.Get().DisableJSON()
		glg.Error(err)
		glg.Get().EnableJSON()
	}
	err = glg.Info("hello", struct {
		Name   string
		Age    int
		Gender string
	}{
		Name:   "kpango",
		Age:    28,
		Gender: "male",
	}, 2020)
	if err != nil {
		glg.Get().DisableJSON()
		glg.Error(err)
		glg.Get().EnableJSON()
	}	glg.CustomLog(customTag, "custom logging")

	glg.CustomLog(customErrTag, "custom error logging")

	glg.Get().AddLevelWriter(glg.DEBG, NetWorkLogger{}) // add info log file destination

	http.Handle("/glg", glg.HTTPLoggerFunc("glg sample", func(w http.ResponseWriter, r *http.Request) {
		glg.New().
		AddLevelWriter(glg.Info, NetWorkLogger{}).
		AddLevelWriter(glg.Info, w).
		Info("glg HTTP server logger sample")
	}))

	http.ListenAndServe("port", nil)

	// fatal logging
	glg.Fatalln("fatal")
}

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3 - Glo: PHP Monolog inspired logging facility with identical severity levels.

GLO

Logging library for Golang

Inspired by Monolog for PHP, severity levels are identical

Install

go get github.com/lajosbencz/glo

Severity levels

Debug     = 100
Info      = 200
Notice    = 250
Warning   = 300
Error     = 400
Critical  = 500
Alert     = 550
Emergency = 600

Simple example

package main

import "github.com/lajosbencz/glo"

func main() {
	// Info - Warning will go to os.Stdout
	// Error - Emergency will go to os.Stderr
	log := glo.NewStdFacility()

	// goes to os.Stdout
	log.Debug("Detailed debug line: %#v", map[string]string{"x": "foo", "y": "bar"})

	// goes to os.Stderr
	log.Error("Oooof!")
}

Output:

2019-01-22T15:16:08+01:00 [DEBUG] Detailed debug line [map[x:foo y:bar]] 2019-01-22T15:16:08+01:00 [ERROR] Oooof! []

Customized example

package main

import (
	"bytes"
	"fmt"
	"os"
	"strings"

	"github.com/lajosbencz/glo"
)

func main() {
	log := glo.NewFacility()

	// write everything to a buffer
	bfr := bytes.NewBufferString("")
	handlerBfr := glo.NewHandler(bfr)
	log.PushHandler(handlerBfr)

	// write only errors and above using a short format
	handlerStd := glo.NewHandler(os.Stdout)
	formatter := glo.NewFormatter("{L}: {M}")
	filter := glo.NewFilterLevel(glo.Error)
	handlerStd.SetFormatter(formatter)
	handlerStd.PushFilter(filter)
	log.PushHandler(handlerStd)

	fmt.Println("Log output:")
	fmt.Println(strings.Repeat("=", 70))
	log.Info("Only written to the buffer")
	log.Alert("Written to both buffer and stdout")

	fmt.Println("")
	fmt.Println("Buffer contents:")
	fmt.Println(strings.Repeat("=", 70))
	fmt.Println(bfr.String())
}

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4 - Glog: Leveled execution logs for Go.

Leveled execution logs for Go.

This is an efficient pure Go implementation of leveled logs in the manner of the open source C++ package glog.

By binding methods to booleans it is possible to use the log package without paying the expense of evaluating the arguments to the log. Through the -vmodule flag, the package also provides fine-grained control over logging at the file level.

The comment from glog.go introduces the ideas:

Package glog implements logging analogous to the Google-internal C++ INFO/ERROR/V setup. It provides the functions Info, Warning, Error, Fatal, plus formatting variants such as Infof. It also provides V-style loggingcontrolled by the -v and -vmodule=file=2 flags.

Basic examples:

glog.Info("Prepare to repel boarders")
	
glog.Fatalf("Initialization failed: %s", err)

See the documentation for the V function for an explanation of these examples:

if glog.V(2) {
	glog.Info("Starting transaction...")
}
glog.V(2).Infoln("Processed", nItems, "elements")

The repository contains an open source version of the log package used inside Google. The master copy of the source lives inside Google, not here. The code in this repo is for export only and is not itself under development. Feature requests will be ignored.

Send bug reports to golang-nuts@googlegroups.com.

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5 - Go-cronowriter: Simple writer that rotate log files automatically based on current date and time, like cronolog.

This is a simple file writer that it writes message to the specified format path.

The file path is constructed based on current date and time, like cronolog.

Installation

$ go get -u github.com/utahta/go-cronowriter

Examples

import "github.com/utahta/go-cronowriter"
w := cronowriter.MustNew("/path/to/example.log.%Y%m%d")
w.Write([]byte("test"))

// output file
// /path/to/example.log.20170204

You can specify the directory as below

w := cronowriter.MustNew("/path/to/%Y/%m/%d/example.log")
w.Write([]byte("test"))

// output file
// /path/to/2017/02/04/example.log

with Location

w := cronowriter.MustNew("/path/to/example.log.%Z", writer.WithLocation(time.UTC))
w.Write([]byte("test"))

// output file
// /path/to/example.log.UTC

with Symlink

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithSymlink("/path/to/example.log"))
w.Write([]byte("test"))

// output file
// /path/to/example.log.20170204
// /path/to/example.log -> /path/to/example.log.20170204

with Mutex

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithMutex())

no use Mutex

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithNopMutex())

with Debug (stdout and stderr)

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithDebug())
w.Write([]byte("test"))

// output file, stdout and stderr
// /path/to/example.log.20170204

with Init

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithInit())

// open the file when New() method is called
// /path/to/example.log.20170204

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6 - Go-log: A logging library with stack traces, object dumping and optional timestamps.

This is a Golang library with logging related functions which I use in my different projects.

Usage

package main

import (
    "github.com/pieterclaerhout/go-log"
)

func main() {

    log.DebugMode = true
    log.DebugSQLMode = true
    log.PrintTimestamp = true
    log.PrintColors = true
    log.TimeFormat = "2006-01-02 15:04:05.000"

    myVar := map[string]string{"hello": "world"}

    log.Debug("arg1", "arg2")
    log.Debugf("arg1 %d", 1)
    log.DebugDump(myVar, "prefix")
    log.DebugSeparator("title")
    log.DebugSQL("select * from mytable")

    log.Info("arg1", "arg2")
    log.Infof("arg1 %d", 1)
    log.InfoDump(myVar, "prefix")
    log.InfoSeparator("title")

    log.Warn("arg1", "arg2")
    log.Warnf("arg1 %d", 1)
    log.WarnDump(myVar, "prefix")
    log.WarnSeparator("title")

    log.Error("arg1", "arg2")
    log.Errorf("arg1 %d", 1)
    log.ErrorDump(myVar, "prefix")
    log.ErrorSeparator("title")

    log.Fatal("arg1", "arg2")
    log.Fatalf("arg1 %d", 1)

    err1 := funcWithError()
    log.StackTrace(err1)

    err2 := funcWithError()
    log.CheckError(err2)

}

Environment variables

The defaults are taken from the environment variables:

  • DEBUG: log.DebugMode
  • DEBUG_SQL: log.DebugSQLMode
  • PRINT_TIMESTAMP: log.PrintTimestamp

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7 - Go-log: Simple and configurable Logging in Go, with level, formatters and writers.

Logging package similar to log4j for the Golang.

  • Support dynamic log level
  • Support customized formatter
    • TextFormatter
    • JSONFormatter
  • Support multiple rolling file writers
    • FixedSizeFileWriter
    • DailyFileWriter
    • AlwaysNewFileWriter

Installation

$ go get github.com/subchen/go-log

Usage

package main

import (
	"os"
	"errors"
	"github.com/subchen/go-log"
)

func main() {
	log.Debugf("app = %s", os.Args[0])
	log.Errorf("error = %v", errors.New("some error"))

	// dynamic set level
	log.Default.Level = log.WARN

	log.Debug("cannot output debug message")
	log.Errorln("can output error message", errors.New("some error"))
}

Output

Default log to console, you can set Logger.Out to set a file writer into log.

import (
	"github.com/subchen/go-log"
	"github.com/subchen/go-log/writers"
)

log.Default.Out = &writers.FixedSizeFileWriter{
	Name:	 "/tmp/test.log",
	MaxSize:  10 * 1024 * 1024, // 10m
	MaxCount: 10,
})

Three builtin writers for use

// Create log file if file size large than fixed size (10m)
// files: /tmp/test.log.0 .. test.log.10
&writers.FixedSizeFileWriter{
	Name:	 "/tmp/test.log",
	MaxSize:  10 * 1024 * 1024, // 10m
	MaxCount: 10,
}

// Create log file every day.
// files: /tmp/test.log.20160102
&writers.DailyFileWriter{
	Name: "/tmp/test.log",
	MaxCount: 10,
}

// Create log file every process.
// files: /tmp/test.log.20160102_150405
&writers.AlwaysNewFileWriter{
	Name: "/tmp/test.log",
	MaxCount: 10,
}

// Output to multiple writes
io.MultiWriter(
	os.Stdout,
	&writers.DailyFileWriter{
		Name: "/tmp/test.log",
		MaxCount: 10,
	}
	//...
)

View on Github

8 - Go-log: Log lib supports level and multi handlers.

go-log

a golang log lib supports level and multi handlers

Use

import "github.com/siddontang/go-log/log"

//log with different level
log.Info("hello world")
log.Error("hello world")

//create a logger with specified handler
h := NewStreamHandler(os.Stdout)
l := log.NewDefault(h)
l.Info("hello world")

View on Github

9 - Go-log: Log4j implementation in Go.

Go-Log. A logger, for Go!

It's sort of log and code.google.com/p/log4go compatible, so in most cases can be used without any code changes.

Breaking change

go-log was inconsistent with the default Go 'log' package, and log.Fatal calls didn't trigger an os.Exit(1).

This has been fixed in the current release of go-log, which might break backwards compatibility.

You can disable the fix by setting ExitOnFatal to false, e.g.

log.Logger().ExitOnFatal = false

Getting started

Install go-log:

go get github.com/ian-kent/go-log/log

Use the logger in your application:

import(
  "github.com/ian-kent/go-log/log"
)

// Pass a log message and arguments directly
log.Debug("Example log message: %s", "example arg")

// Pass a function which returns a log message and arguments
log.Debug(func(){[]interface{}{"Example log message: %s", "example arg"}})
log.Debug(func(i ...interface{}){[]interface{}{"Example log message: %s", "example arg"}})

You can also get the logger instance:

logger := log.Logger()
logger.Debug("Yey!")

Or get a named logger instance:

logger := log.Logger("foo.bar")

Log levels

The default log level is DEBUG.

To get the current log level:

level := logger.Level()

Or to set the log level:

// From a LogLevel
logger.SetLevel(levels.TRACE)

// From a string
logger.SetLevel(log.Stol("TRACE"))

Log appenders

The default log appender is appenders.Console(), which logs the raw message to STDOUT.

To get the current log appender:

appender := logger.Appender()

If the appender is nil, the parent loggers appender will be used instead.

If the appender eventually resolves to nil, log data will be silently dropped.

You can set the log appender:

logger.SetAppender(appenders.Console())

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10 - Go-logger: Simple logger of Go Programs, with level handlers.

A simple go logger for easy logging in your programs. Allows setting custom format for messages.

Install

go get github.com/apsdehal/go-logger

Use go get -u to update the package.

Example

Example program demonstrates how to use the logger. See below for formatting instructions.

package main

import (
	"github.com/apsdehal/go-logger"
	"os"
)

func main () {
	// Get the instance for logger class, "test" is the module name, 1 is used to
	// state if we want coloring
	// Third option is optional and is instance of type io.Writer, defaults to os.Stderr
	log, err := logger.New("test", 1, os.Stdout)
	if err != nil {
		panic(err) // Check for error
	}

	// Critically log critical
	log.Critical("This is Critical!")
	log.CriticalF("%+v", err)
	// You can also use fmt compliant naming scheme such as log.Criticalf, log.Panicf etc
	// with small 'f'
	
	// Debug
	// Since default logging level is Info this won't print anything
	log.Debug("This is Debug!")
	log.DebugF("Here are some numbers: %d %d %f", 10, -3, 3.14)
	// Give the Warning
	log.Warning("This is Warning!")
	log.WarningF("This is Warning!")
	// Show the error
	log.Error("This is Error!")
	log.ErrorF("This is Error!")
	// Notice
	log.Notice("This is Notice!")
	log.NoticeF("%s %s", "This", "is Notice!")
	// Show the info
	log.Info("This is Info!")
	log.InfoF("This is %s!", "Info")

	log.StackAsError("Message before printing stack");

	// Show warning with format
	log.SetFormat("[%{module}] [%{level}] %{message}")
	log.Warning("This is Warning!") // output: "[test] [WARNING] This is Warning!"
	// Also you can set your format as default format for all new loggers
	logger.SetDefaultFormat("%{message}")
	log2, _ := logger.New("pkg", 1, os.Stdout)
	log2.Error("This is Error!") // output: "This is Error!"

	// Use log levels to set your log priority
	log2.SetLogLevel(DebugLevel)
	// This will be printed
	log2.Debug("This is debug!")
	log2.SetLogLevel(WarningLevel)
	// This won't be printed
	log2.Info("This is an error!")
}

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Swift Tips: A Collection Useful Tips for The Swift Language

SwiftTips

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 as Debugging Tools

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"]

Localization through String interpolation

Swift 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!

Implementing pseudo-inheritance between 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"

Composing NSAttributedString through a Function Builder

Swift 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])
}

Using switch and if as expressions

Contrary 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)

Avoiding double negatives within guard statements

A 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)

Defining a custom init without loosing the compiler-generated one

It'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()

Implementing a namespace through an empty 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

Using Never to represent impossible code paths

Never 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.
    }
})

Providing a default value to a 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]

Another lightweight dependency injection through default values for function parameters

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"

Lightweight dependency injection through protocol-oriented programming

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"

Getting rid of overabundant [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

Solving callback hell with function composition

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
})

Transform an asynchronous function into a synchronous one

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

Using KeyPaths instead of closures

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"]

Bringing some type-safety to a 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?

Lightweight data-binding for an MVVM implementation

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

Using typealias to its fullest

The 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>

Writing an interruptible overload of 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

Optimizing the use of 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) } } )
}

Avoiding hardcoded reuse identifiers

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])

Defining a union type

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.

Asserting that classes have associated NIBs and vice-versa

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.

Small footprint type-erasing with functions

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"

Performing animations sequentially

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 a function call

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!

Providing useful operators for Optional booleans

When 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

Removing duplicate values from a 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]

Shorter syntax to deal with optional strings

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)

Encapsulating background computation and UI update

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)"
}

Retrieving all the necessary data to build a debug view

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.

Defining a function to map over dictionaries

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]

A shorter syntax to remove nil values

Swift 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]

Dealing with expirable values

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.

Using parallelism to speed-up 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.

Measuring execution time with minimum boilerplate

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

Running two pieces of code in parallel

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, +))

Making good use of #file, #line and #function

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!

Comparing Optionals through Conditional Conformance

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)]

Safely subscripting a Collection

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

Easier String slicing using ranges

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!"

Concise syntax for sorting using a KeyPath

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!

Manufacturing cache-efficient versions of pure functions

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

Simplifying complex conditions with pattern matching

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
}

Easily generating arrays of data

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 for cleaner call sites

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)

Observing new and old value with RxSwift

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

Implicit initialization from literal values

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"))

Achieving systematic validation of data

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

Implementing the builder pattern with keypaths

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.

Storing functions rather than values

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

Defining operators on function types

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 for functions

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

Encapsulating state within a function

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

Generating all cases for an Enum

⚠️ Since Swift 4.2, allCases can now be synthesized at compile-time by simply conforming to the protocol CaseIterable. 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]

Using map on optional values

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

Tips


Download Details:

Author: vincent-pradeilles
Source code: https://github.com/vincent-pradeilles/swift-tips

License: MIT license
#swift 

10 Best Golang Libraries for Generating & Working with Log Files

In today's post we will learn about 10 Best Golang Libraries for Generating & Working with Log Files. 

What is a log file?

A log file is a computer-generated data file that contains information about usage patterns, activities, and operations within an operating system, application, server or another device, and is the primary data source for network observability. Log files show whether resources are performing properly and optimally, exposing possible.

Table of contents:

  • Distillog - Distilled levelled logging (think of it as stdlib + log levels).
  • Glg - glg is simple and fast leveled logging library for Go.
  • Glo - PHP Monolog inspired logging facility with identical severity levels.
  • Glog - Leveled execution logs for Go.
  • Go-cronowriter - Simple writer that rotate log files automatically based on current date and time, like cronolog.
  • Go-log - A logging library with stack traces, object dumping and optional timestamps.
  • Go-log - Simple and configurable Logging in Go, with level, formatters and writers.
  • Go-log - Log lib supports level and multi handlers.
  • Go-log - Log4j implementation in Go.
  • Go-logger - Simple logger of Go Programs, with level handlers.

1 - Distillog: Distilled levelled logging (think of it as stdlib + log levels).

What is distillog?

distillog aims to offer a minimalistic logging interface that also supports log levels. It takes the stdlib API and only slightly enhances it. Hence, you could think of it as levelled logging, distilled.

Yet another logging library for go(lang)?

Logging libraries are like opinions, everyone seems to have one -- Anon(?)

Most other logging libraries do either too little (stdlib) or too much (glog).

As with most other libraries, this one is opinionated. In terms of functionality it exposes, it attempts to sit somewhere between the stdlib and the majority of other logging libraries available (but leans mostly towards the spartan side of stdlib).

Expose an interface? Why?

By exposing an interface you can write programs that use levelled log messages, but switch between logging to various facilities by simply instantiating the appropriate logger as determined by the caller (Your program can offer a command-line switch like so - --log-to=[syslog,stderr,<file>] and the simply instantiate the appropriate logger).

Usage/examples:

As seen in the godoc, the interface is limited to:

type Logger interface {
	Debugf(format string, v ...interface{})
	Debugln(v ...interface{})

	Infof(format string, v ...interface{})
	Infoln(v ...interface{})

	Warningf(format string, v ...interface{})
	Warningln(v ...interface{})

	Errorf(format string, v ...interface{})
	Errorln(v ...interface{})

	Close() error
}

Log to stdout, or stderr using a logger instantiated like so:

outLogger := distillog.NewStdoutLogger("test")

errLogger := distillog.NewStderrLogger("test")

sysLogger := distillog.NewSyslogLogger("test")

Alternatively, you can use the package for your logging needs:

import log "github.com/amoghe/distillog"

// ... later ...

log.Infoln("Starting program")
log.Debugln("initializing the frobnicator")
log.Warningln("frobnicator failure detected, proceeding anyways...")
log.Infoln("Exiting")

If you have a file you wish to log to, you should open the file and instantiate a logger using the file handle, like so:

if fileHandle, err := ioutil.Tempfile("/tmp", "distillog-test"); err == nil {
        fileLogger := distillog.NewStreamLogger("test", fileHandle)
}

If you need a logger that manages the rotation of its files, use lumberjack, like so:

lumberjackHandle := &lumberjack.Logger{
        Filename:   "/var/log/myapp/foo.log",
        MaxSize:    500,                       // megabytes
        MaxBackups: 3,
        MaxAge:     28,                        // days
}

logger := distillog.NewStreamLogger("tag", lumberjackHandle)

// Alternatively, configure the pkg level logger to emit here

distillog.SetOutput(lumberjackHandle)

Once instantiated, you can log messages, like so:

var := "World!"
myLogger.Infof("Hello, %s", var)
myLogger.Warningln("Goodbye, cruel world!")

View on Github

2 - Glg: glg is simple and fast leveled logging library for Go.

glg is simple golang logging library

Requirement

Go 1.16

Installation

go get github.com/kpango/glg

Example

package main

import (
	"net/http"
	"time"

	"github.com/kpango/glg"
)

// NetWorkLogger sample network logger
type NetWorkLogger struct{}

func (n NetWorkLogger) Write(b []byte) (int, error) {
	// http.Post("localhost:8080/log", "", bytes.NewReader(b))
	http.Get("http://127.0.0.1:8080/log")
	glg.Success("Requested")
	glg.Infof("RawString is %s", glg.RawString(b))
	return 1, nil
}

func main() {

	// var errWriter io.Writer
	// var customWriter io.Writer
	infolog := glg.FileWriter("/tmp/info.log", 0666)

	customTag := "FINE"
	customErrTag := "CRIT"

	errlog := glg.FileWriter("/tmp/error.log", 0666)
	defer infolog.Close()
	defer errlog.Close()

	glg.Get().
		SetMode(glg.BOTH). // default is STD
		// DisableColor().
		// SetMode(glg.NONE).
		// SetMode(glg.WRITER).
		// SetMode(glg.BOTH).
		// InitWriter().
		// AddWriter(customWriter).
		// SetWriter(customWriter).
		// AddLevelWriter(glg.LOG, customWriter).
		// AddLevelWriter(glg.INFO, customWriter).
		// AddLevelWriter(glg.WARN, customWriter).
		// AddLevelWriter(glg.ERR, customWriter).
		// SetLevelWriter(glg.LOG, customWriter).
		// SetLevelWriter(glg.INFO, customWriter).
		// SetLevelWriter(glg.WARN, customWriter).
		// SetLevelWriter(glg.ERR, customWriter).
		// EnableJSON().
		SetLineTraceMode(glg.TraceLineNone).
		AddLevelWriter(glg.INFO, infolog). // add info log file destination
		AddLevelWriter(glg.ERR, errlog).   // add error log file destination
		AddLevelWriter(glg.WARN, rotate)   // add error log file destination

	glg.Info("info")
	glg.Infof("%s : %s", "info", "formatted")
	glg.Log("log")
	glg.Logf("%s : %s", "info", "formatted")
	glg.Debug("debug")
	glg.Debugf("%s : %s", "info", "formatted")
	glg.Trace("Trace")
	glg.Tracef("%s : %s", "tracef", "formatted")
	glg.Warn("warn")
	glg.Warnf("%s : %s", "info", "formatted")
	glg.Error("error")
	glg.Errorf("%s : %s", "info", "formatted")
	glg.Success("ok")
	glg.Successf("%s : %s", "info", "formatted")
	glg.Fail("fail")
	glg.Failf("%s : %s", "info", "formatted")
	glg.Print("Print")
	glg.Println("Println")
	glg.Printf("%s : %s", "printf", "formatted")

	// set global log level to ERR level
	glg.Info("before setting level to ERR this message will show")
	glg.Get().SetLevel(glg.ERR)
	glg.Info("after setting level to ERR this message will not show")
	glg.Error("this log is ERR level this will show")
	glg.Get().SetLevel(glg.DEBG)
	glg.Info("log level is now DEBG, this INFO level log will show")

	glg.Get().
		AddStdLevel(customTag, glg.STD, false).                    // user custom log level
		AddErrLevel(customErrTag, glg.STD, true).                  // user custom error log level
		SetLevelColor(glg.TagStringToLevel(customTag), glg.Cyan).  // set color output to user custom level
		SetLevelColor(glg.TagStringToLevel(customErrTag), glg.Red) // set color output to user custom level
	glg.CustomLog(customTag, "custom logging")
	glg.CustomLog(customErrTag, "custom error logging")

	// glg.Info("kpango's glg supports disable timestamp for logging")
	glg.Get().DisableTimestamp()
	glg.Info("timestamp disabled")
	glg.Warn("timestamp disabled")
	glg.Log("timestamp disabled")
	glg.Get().EnableTimestamp()
	glg.Info("timestamp enabled")
	glg.Warn("timestamp enabled")
	glg.Log("timestamp enabled")

	glg.Info("kpango's glg support line trace logging")
	glg.Error("error log shows short line trace by default")
	glg.Info("error log shows none trace by default")
	glg.Get().SetLineTraceMode(glg.TraceLineShort)
	glg.Error("after configure TraceLineShort, error log shows short line trace")
	glg.Info("after configure TraceLineShort, info log shows short line trace")
	glg.Get().DisableTimestamp()
	glg.Error("after configure TraceLineShort and DisableTimestamp, error log shows short line trace without timestamp")
	glg.Info("after configure TraceLineShort and DisableTimestamp, info log shows short line trace without timestamp")
	glg.Get().EnableTimestamp()
	glg.Get().SetLineTraceMode(glg.TraceLineLong)
	glg.Error("after configure TraceLineLong, error log shows long line trace")
	glg.Info("after configure TraceLineLong, info log shows long line trace")
	glg.Get().DisableTimestamp()
	glg.Error("after configure TraceLineLong and DisableTimestamp, error log shows long line trace without timestamp")
	glg.Info("after configure TraceLineLong and DisableTimestamp, info log shows long line trace without timestamp")
	glg.Get().EnableTimestamp()
	glg.Get().SetLineTraceMode(glg.TraceLineNone)
	glg.Error("after configure TraceLineNone, error log without line trace")
	glg.Info("after configure TraceLineNone, info log without line trace")
	glg.Get().SetLevelLineTraceMode(glg.INFO, glg.TraceLineLong)
	glg.Info("after configure Level trace INFO=TraceLineLong, only info log shows long line trace")
	glg.Error("after configure Level trace INFO=TraceLineLong, error log without long line trace")
	glg.Get().SetLevelLineTraceMode(glg.ERR, glg.TraceLineShort)
	glg.Info("after configure Level trace ERR=TraceLineShort, info log still shows long line trace")
	glg.Error("after configure Level trace ERR=TraceLineShort, error log now shows short line trace")
	glg.Get().SetLineTraceMode(glg.TraceLineNone)

	glg.Info("kpango's glg support json logging")
	glg.Get().EnableJSON()
	err := glg.Warn("kpango's glg", "support", "json", "logging")
	if err != nil {
		glg.Get().DisableJSON()
		glg.Error(err)
		glg.Get().EnableJSON()
	}
	err = glg.Info("hello", struct {
		Name   string
		Age    int
		Gender string
	}{
		Name:   "kpango",
		Age:    28,
		Gender: "male",
	}, 2020)
	if err != nil {
		glg.Get().DisableJSON()
		glg.Error(err)
		glg.Get().EnableJSON()
	}	glg.CustomLog(customTag, "custom logging")

	glg.CustomLog(customErrTag, "custom error logging")

	glg.Get().AddLevelWriter(glg.DEBG, NetWorkLogger{}) // add info log file destination

	http.Handle("/glg", glg.HTTPLoggerFunc("glg sample", func(w http.ResponseWriter, r *http.Request) {
		glg.New().
		AddLevelWriter(glg.Info, NetWorkLogger{}).
		AddLevelWriter(glg.Info, w).
		Info("glg HTTP server logger sample")
	}))

	http.ListenAndServe("port", nil)

	// fatal logging
	glg.Fatalln("fatal")
}

View on Github

3 - Glo: PHP Monolog inspired logging facility with identical severity levels.

GLO

Logging library for Golang

Inspired by Monolog for PHP, severity levels are identical

Install

go get github.com/lajosbencz/glo

Severity levels

Debug     = 100
Info      = 200
Notice    = 250
Warning   = 300
Error     = 400
Critical  = 500
Alert     = 550
Emergency = 600

Simple example

package main

import "github.com/lajosbencz/glo"

func main() {
	// Info - Warning will go to os.Stdout
	// Error - Emergency will go to os.Stderr
	log := glo.NewStdFacility()

	// goes to os.Stdout
	log.Debug("Detailed debug line: %#v", map[string]string{"x": "foo", "y": "bar"})

	// goes to os.Stderr
	log.Error("Oooof!")
}

Output:

2019-01-22T15:16:08+01:00 [DEBUG] Detailed debug line [map[x:foo y:bar]] 2019-01-22T15:16:08+01:00 [ERROR] Oooof! []

Customized example

package main

import (
	"bytes"
	"fmt"
	"os"
	"strings"

	"github.com/lajosbencz/glo"
)

func main() {
	log := glo.NewFacility()

	// write everything to a buffer
	bfr := bytes.NewBufferString("")
	handlerBfr := glo.NewHandler(bfr)
	log.PushHandler(handlerBfr)

	// write only errors and above using a short format
	handlerStd := glo.NewHandler(os.Stdout)
	formatter := glo.NewFormatter("{L}: {M}")
	filter := glo.NewFilterLevel(glo.Error)
	handlerStd.SetFormatter(formatter)
	handlerStd.PushFilter(filter)
	log.PushHandler(handlerStd)

	fmt.Println("Log output:")
	fmt.Println(strings.Repeat("=", 70))
	log.Info("Only written to the buffer")
	log.Alert("Written to both buffer and stdout")

	fmt.Println("")
	fmt.Println("Buffer contents:")
	fmt.Println(strings.Repeat("=", 70))
	fmt.Println(bfr.String())
}

View on Github

4 - Glog: Leveled execution logs for Go.

Leveled execution logs for Go.

This is an efficient pure Go implementation of leveled logs in the manner of the open source C++ package glog.

By binding methods to booleans it is possible to use the log package without paying the expense of evaluating the arguments to the log. Through the -vmodule flag, the package also provides fine-grained control over logging at the file level.

The comment from glog.go introduces the ideas:

Package glog implements logging analogous to the Google-internal C++ INFO/ERROR/V setup. It provides the functions Info, Warning, Error, Fatal, plus formatting variants such as Infof. It also provides V-style loggingcontrolled by the -v and -vmodule=file=2 flags.

Basic examples:

glog.Info("Prepare to repel boarders")
	
glog.Fatalf("Initialization failed: %s", err)

See the documentation for the V function for an explanation of these examples:

if glog.V(2) {
	glog.Info("Starting transaction...")
}
glog.V(2).Infoln("Processed", nItems, "elements")

The repository contains an open source version of the log package used inside Google. The master copy of the source lives inside Google, not here. The code in this repo is for export only and is not itself under development. Feature requests will be ignored.

Send bug reports to golang-nuts@googlegroups.com.

View on Github

5 - Go-cronowriter: Simple writer that rotate log files automatically based on current date and time, like cronolog.

This is a simple file writer that it writes message to the specified format path.

The file path is constructed based on current date and time, like cronolog.

Installation

$ go get -u github.com/utahta/go-cronowriter

Examples

import "github.com/utahta/go-cronowriter"
w := cronowriter.MustNew("/path/to/example.log.%Y%m%d")
w.Write([]byte("test"))

// output file
// /path/to/example.log.20170204

You can specify the directory as below

w := cronowriter.MustNew("/path/to/%Y/%m/%d/example.log")
w.Write([]byte("test"))

// output file
// /path/to/2017/02/04/example.log

with Location

w := cronowriter.MustNew("/path/to/example.log.%Z", writer.WithLocation(time.UTC))
w.Write([]byte("test"))

// output file
// /path/to/example.log.UTC

with Symlink

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithSymlink("/path/to/example.log"))
w.Write([]byte("test"))

// output file
// /path/to/example.log.20170204
// /path/to/example.log -> /path/to/example.log.20170204

with Mutex

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithMutex())

no use Mutex

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithNopMutex())

with Debug (stdout and stderr)

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithDebug())
w.Write([]byte("test"))

// output file, stdout and stderr
// /path/to/example.log.20170204

with Init

w := cronowriter.MustNew("/path/to/example.log.%Y%m%d", writer.WithInit())

// open the file when New() method is called
// /path/to/example.log.20170204

View on Github

6 - Go-log: A logging library with stack traces, object dumping and optional timestamps.

This is a Golang library with logging related functions which I use in my different projects.

Usage

package main

import (
    "github.com/pieterclaerhout/go-log"
)

func main() {

    log.DebugMode = true
    log.DebugSQLMode = true
    log.PrintTimestamp = true
    log.PrintColors = true
    log.TimeFormat = "2006-01-02 15:04:05.000"

    myVar := map[string]string{"hello": "world"}

    log.Debug("arg1", "arg2")
    log.Debugf("arg1 %d", 1)
    log.DebugDump(myVar, "prefix")
    log.DebugSeparator("title")
    log.DebugSQL("select * from mytable")

    log.Info("arg1", "arg2")
    log.Infof("arg1 %d", 1)
    log.InfoDump(myVar, "prefix")
    log.InfoSeparator("title")

    log.Warn("arg1", "arg2")
    log.Warnf("arg1 %d", 1)
    log.WarnDump(myVar, "prefix")
    log.WarnSeparator("title")

    log.Error("arg1", "arg2")
    log.Errorf("arg1 %d", 1)
    log.ErrorDump(myVar, "prefix")
    log.ErrorSeparator("title")

    log.Fatal("arg1", "arg2")
    log.Fatalf("arg1 %d", 1)

    err1 := funcWithError()
    log.StackTrace(err1)

    err2 := funcWithError()
    log.CheckError(err2)

}

Environment variables

The defaults are taken from the environment variables:

  • DEBUG: log.DebugMode
  • DEBUG_SQL: log.DebugSQLMode
  • PRINT_TIMESTAMP: log.PrintTimestamp

View on Github

7 - Go-log: Simple and configurable Logging in Go, with level, formatters and writers.

Logging package similar to log4j for the Golang.

  • Support dynamic log level
  • Support customized formatter
    • TextFormatter
    • JSONFormatter
  • Support multiple rolling file writers
    • FixedSizeFileWriter
    • DailyFileWriter
    • AlwaysNewFileWriter

Installation

$ go get github.com/subchen/go-log

Usage

package main

import (
	"os"
	"errors"
	"github.com/subchen/go-log"
)

func main() {
	log.Debugf("app = %s", os.Args[0])
	log.Errorf("error = %v", errors.New("some error"))

	// dynamic set level
	log.Default.Level = log.WARN

	log.Debug("cannot output debug message")
	log.Errorln("can output error message", errors.New("some error"))
}

Output

Default log to console, you can set Logger.Out to set a file writer into log.

import (
	"github.com/subchen/go-log"
	"github.com/subchen/go-log/writers"
)

log.Default.Out = &writers.FixedSizeFileWriter{
	Name:	 "/tmp/test.log",
	MaxSize:  10 * 1024 * 1024, // 10m
	MaxCount: 10,
})

Three builtin writers for use

// Create log file if file size large than fixed size (10m)
// files: /tmp/test.log.0 .. test.log.10
&writers.FixedSizeFileWriter{
	Name:	 "/tmp/test.log",
	MaxSize:  10 * 1024 * 1024, // 10m
	MaxCount: 10,
}

// Create log file every day.
// files: /tmp/test.log.20160102
&writers.DailyFileWriter{
	Name: "/tmp/test.log",
	MaxCount: 10,
}

// Create log file every process.
// files: /tmp/test.log.20160102_150405
&writers.AlwaysNewFileWriter{
	Name: "/tmp/test.log",
	MaxCount: 10,
}

// Output to multiple writes
io.MultiWriter(
	os.Stdout,
	&writers.DailyFileWriter{
		Name: "/tmp/test.log",
		MaxCount: 10,
	}
	//...
)

View on Github

8 - Go-log: Log lib supports level and multi handlers.

go-log

a golang log lib supports level and multi handlers

Use

import "github.com/siddontang/go-log/log"

//log with different level
log.Info("hello world")
log.Error("hello world")

//create a logger with specified handler
h := NewStreamHandler(os.Stdout)
l := log.NewDefault(h)
l.Info("hello world")

View on Github

9 - Go-log: Log4j implementation in Go.

Go-Log. A logger, for Go!

It's sort of log and code.google.com/p/log4go compatible, so in most cases can be used without any code changes.

Breaking change

go-log was inconsistent with the default Go 'log' package, and log.Fatal calls didn't trigger an os.Exit(1).

This has been fixed in the current release of go-log, which might break backwards compatibility.

You can disable the fix by setting ExitOnFatal to false, e.g.

log.Logger().ExitOnFatal = false

Getting started

Install go-log:

go get github.com/ian-kent/go-log/log

Use the logger in your application:

import(
  "github.com/ian-kent/go-log/log"
)

// Pass a log message and arguments directly
log.Debug("Example log message: %s", "example arg")

// Pass a function which returns a log message and arguments
log.Debug(func(){[]interface{}{"Example log message: %s", "example arg"}})
log.Debug(func(i ...interface{}){[]interface{}{"Example log message: %s", "example arg"}})

You can also get the logger instance:

logger := log.Logger()
logger.Debug("Yey!")

Or get a named logger instance:

logger := log.Logger("foo.bar")

Log levels

The default log level is DEBUG.

To get the current log level:

level := logger.Level()

Or to set the log level:

// From a LogLevel
logger.SetLevel(levels.TRACE)

// From a string
logger.SetLevel(log.Stol("TRACE"))

Log appenders

The default log appender is appenders.Console(), which logs the raw message to STDOUT.

To get the current log appender:

appender := logger.Appender()

If the appender is nil, the parent loggers appender will be used instead.

If the appender eventually resolves to nil, log data will be silently dropped.

You can set the log appender:

logger.SetAppender(appenders.Console())

View on Github

10 - Go-logger: Simple logger of Go Programs, with level handlers.

A simple go logger for easy logging in your programs. Allows setting custom format for messages.

Install

go get github.com/apsdehal/go-logger

Use go get -u to update the package.

Example

Example program demonstrates how to use the logger. See below for formatting instructions.

package main

import (
	"github.com/apsdehal/go-logger"
	"os"
)

func main () {
	// Get the instance for logger class, "test" is the module name, 1 is used to
	// state if we want coloring
	// Third option is optional and is instance of type io.Writer, defaults to os.Stderr
	log, err := logger.New("test", 1, os.Stdout)
	if err != nil {
		panic(err) // Check for error
	}

	// Critically log critical
	log.Critical("This is Critical!")
	log.CriticalF("%+v", err)
	// You can also use fmt compliant naming scheme such as log.Criticalf, log.Panicf etc
	// with small 'f'
	
	// Debug
	// Since default logging level is Info this won't print anything
	log.Debug("This is Debug!")
	log.DebugF("Here are some numbers: %d %d %f", 10, -3, 3.14)
	// Give the Warning
	log.Warning("This is Warning!")
	log.WarningF("This is Warning!")
	// Show the error
	log.Error("This is Error!")
	log.ErrorF("This is Error!")
	// Notice
	log.Notice("This is Notice!")
	log.NoticeF("%s %s", "This", "is Notice!")
	// Show the info
	log.Info("This is Info!")
	log.InfoF("This is %s!", "Info")

	log.StackAsError("Message before printing stack");

	// Show warning with format
	log.SetFormat("[%{module}] [%{level}] %{message}")
	log.Warning("This is Warning!") // output: "[test] [WARNING] This is Warning!"
	// Also you can set your format as default format for all new loggers
	logger.SetDefaultFormat("%{message}")
	log2, _ := logger.New("pkg", 1, os.Stdout)
	log2.Error("This is Error!") // output: "This is Error!"

	// Use log levels to set your log priority
	log2.SetLogLevel(DebugLevel)
	// This will be printed
	log2.Debug("This is debug!")
	log2.SetLogLevel(WarningLevel)
	// This won't be printed
	log2.Info("This is an error!")
}

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Rupert  Beatty

Rupert Beatty

1673365703

Swift-tips: A Collection Useful Tips for The Swift Language

SwiftTips

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 as Debugging Tools

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"]

Localization through String interpolation

Swift 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!

Implementing pseudo-inheritance between 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"

Composing NSAttributedString through a Function Builder

Swift 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])
}

Using switch and if as expressions

Contrary 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)

Avoiding double negatives within guard statements

A 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)

Defining a custom init without loosing the compiler-generated one

It'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()

Implementing a namespace through an empty 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

Using Never to represent impossible code paths

Never 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.
    }
})

Providing a default value to a 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]

Another lightweight dependency injection through default values for function parameters

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"

Lightweight dependency injection through protocol-oriented programming

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"

Getting rid of overabundant [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

Solving callback hell with function composition

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
})

Transform an asynchronous function into a synchronous one

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

Using KeyPaths instead of closures

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"]

Bringing some type-safety to a 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?

Lightweight data-binding for an MVVM implementation

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

Using typealias to its fullest

The 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>

Writing an interruptible overload of 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

Optimizing the use of 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) } } )
}

Avoiding hardcoded reuse identifiers

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])

Defining a union type

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.

Asserting that classes have associated NIBs and vice-versa

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.

Small footprint type-erasing with functions

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"

Performing animations sequentially

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 a function call

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!

Providing useful operators for Optional booleans

When 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

Removing duplicate values from a 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]

Shorter syntax to deal with optional strings

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)

Encapsulating background computation and UI update

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)"
}

Retrieving all the necessary data to build a debug view

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.

Defining a function to map over dictionaries

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]

A shorter syntax to remove nil values

Swift 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]

Dealing with expirable values

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.

Using parallelism to speed-up 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.

Measuring execution time with minimum boilerplate

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

Running two pieces of code in parallel

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, +))

Making good use of #file, #line and #function

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!

Comparing Optionals through Conditional Conformance

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)]

Safely subscripting a Collection

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

Easier String slicing using ranges

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!"

Concise syntax for sorting using a KeyPath

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!

Manufacturing cache-efficient versions of pure functions

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

Simplifying complex conditions with pattern matching

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
}

Easily generating arrays of data

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 for cleaner call sites

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)

Observing new and old value with RxSwift

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

Implicit initialization from literal values

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"))

Achieving systematic validation of data

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

Implementing the builder pattern with keypaths

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.

Storing functions rather than values

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

Defining operators on function types

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 for functions

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

Encapsulating state within a function

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

Generating all cases for an Enum

⚠️ Since Swift 4.2, allCases can now be synthesized at compile-time by simply conforming to the protocol CaseIterable. 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]

Using map on optional values

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

Download Details:

Author: Vincent-pradeilles
Source Code: https://github.com/vincent-pradeilles/swift-tips 
License: MIT license

#swift #tips 

Royce  Reinger

Royce Reinger

1658977500

A Ruby Library for Generating Text with Recursive Template Grammars

Calyx

Calyx provides a simple API for generating text with declarative recursive grammars.

Install

Command Line

gem install calyx

Gemfile

gem 'calyx'

Examples

The best way to get started quickly is to install the gem and run the examples locally.

Any Gradient

Requires Roda and Rack to be available.

gem install roda

Demonstrates how to use Calyx to construct SVG graphics. Any Gradient generates a rectangle with a linear gradient of random colours.

Run as a web server and preview the output in a browser (http://localhost:9292):

ruby examples/any_gradient.rb

Or generate SVG files via a command line pipe:

ruby examples/any_gradient > gradient1.xml

Tiny Woodland Bot

Requires the Twitter client gem and API access configured for a specific Twitter handle.

gem install twitter

Demonstrates how to use Calyx to make a minimal Twitter bot that periodically posts unique tweets. See @tiny_woodland on Twitter and the writeup here.

TWITTER_CONSUMER_KEY=XXX-XXX
TWITTER_CONSUMER_SECRET=XXX-XXX
TWITTER_ACCESS_TOKEN=XXX-XXX
TWITTER_CONSUMER_SECRET=XXX-XXX
ruby examples/tiny_woodland_bot.rb

Faker

Faker is a popular library for generating fake names and associated sample data like internet addresses, company names and locations.

This example demonstrates how to use Calyx to reproduce the same functionality using custom lists defined in a YAML configuration file.

ruby examples/faker.rb

Usage

Require the library and inherit from Calyx::Grammar to construct a set of rules to generate a text.

require 'calyx'

class HelloWorld < Calyx::Grammar
  start 'Hello world.'
end

To generate the text itself, initialize the object and call the generate method.

hello = HelloWorld.new
hello.generate
# > "Hello world."

Obviously, this hardcoded sentence isn’t very interesting by itself. Possible variations can be added to the text by adding additional rules which provide a named set of text strings. The rule delimiter syntax ({}) can be used to substitute the generated content of other rules.

class HelloWorld < Calyx::Grammar
  start '{greeting} world.'
  greeting 'Hello', 'Hi', 'Hey', 'Yo'
end

Each time #generate runs, it evaluates the tree and randomly selects variations of rules to construct a resulting string.

hello = HelloWorld.new

hello.generate
# > "Hi world."

hello.generate
# > "Hello world."

hello.generate
# > "Yo world."

By convention, the start rule specifies the default starting point for generating the final text. You can start from any other named rule by passing it explicitly to the generate method.

class HelloWorld < Calyx::Grammar
  hello 'Hello world.'
end

hello = HelloWorld.new
hello.generate(:hello)

Block Constructors

As an alternative to subclassing, you can also construct rules unique to an instance by passing a block when initializing the class:

hello = Calyx::Grammar.new do
  start '{greeting} world.'
  greeting 'Hello', 'Hi', 'Hey', 'Yo'
end

hello.generate

Template Expressions

Basic rule substitution uses single curly brackets as delimiters for template expressions:

fruit = Calyx::Grammar.new do
  start '{colour} {fruit}'
  colour 'red', 'green', 'yellow'
  fruit 'apple', 'pear', 'tomato'
end

6.times { fruit.generate }
# => "yellow pear"
# => "red apple"
# => "green tomato"
# => "red pear"
# => "yellow tomato"
# => "green apple"

Nesting and Substitution

Rules are recursive. They can be arbitrarily nested and connected to generate larger and more complex texts.

class HelloWorld < Calyx::Grammar
  start '{greeting} {world_phrase}.'
  greeting 'Hello', 'Hi', 'Hey', 'Yo'
  world_phrase '{happy_adj} world', '{sad_adj} world', 'world'
  happy_adj 'wonderful', 'amazing', 'bright', 'beautiful'
  sad_adj 'cruel', 'miserable'
end

Nesting and hierarchy can be manipulated to balance consistency with novelty. The exact same word atoms can be combined in a variety of ways to produce strikingly different resulting texts.

module HelloWorld
  class Sentiment < Calyx::Grammar
    start '{happy_phrase}', '{sad_phrase}'
    happy_phrase '{happy_greeting} {happy_adj} world.'
    happy_greeting 'Hello', 'Hi', 'Hey', 'Yo'
    happy_adj 'wonderful', 'amazing', 'bright', 'beautiful'
    sad_phrase '{sad_greeting} {sad_adj} world.'
    sad_greeting 'Goodbye', 'So long', 'Farewell'
    sad_adj 'cruel', 'miserable'
  end

  class Mixed < Calyx::Grammar
    start '{greeting} {adj} world.'
    greeting 'Hello', 'Hi', 'Hey', 'Yo', 'Goodbye', 'So long', 'Farewell'
    adj 'wonderful', 'amazing', 'bright', 'beautiful', 'cruel', 'miserable'
  end
end

Random Sampling

By default, the outcomes of generated rules are selected with Ruby’s built-in pseudorandom number generator (as seen in methods like Kernel.rand and Array.sample). To seed the random number generator, pass in an integer seed value as the first argument to the constructor:

grammar = Calyx::Grammar.new(seed: 12345) do
  # rules...
end

Alternatively, you can pass a preconfigured instance of Ruby’s stdlib Random class:

random = Random.new(12345)

grammar = Calyx::Grammar.new(rng: random) do
  # rules...
end

When a random seed isn’t supplied, Time.new.to_i is used as the default seed, which makes each run of the generator relatively unique.

Weighted Choices

Choices can be weighted so that some rules have a greater probability of expanding than others.

Weights are defined by passing a hash instead of a list of rules where the keys are strings or symbols representing the grammar rules and the values are weights.

Weights can be represented as floats, integers or ranges.

  • Floats must be in the interval 0..1 and the given weights for a production must sum to 1.
  • Ranges must be contiguous and cover the entire interval from 1 to the maximum value of the largest range.
  • Integers (Fixnums) will produce a distribution based on the sum of all given numbers, with each number being a fraction of that sum.

The following definitions produce an equivalent weighting of choices:

Calyx::Grammar.new do
  start 'heads' => 1, 'tails' => 1
end

Calyx::Grammar.new do
  start 'heads' => 0.5, 'tails' => 0.5
end

Calyx::Grammar.new do
  start 'heads' => 1..5, 'tails' => 6..10
end

Calyx::Grammar.new do
  start 'heads' => 50, 'tails' => 50
end

There’s a lot of interesting things you can do with this. For example, you can model the triangular distribution produced by rolling 2d6:

Calyx::Grammar.new do
  start(
    '2' => 1,
    '3' => 2,
    '4' => 3,
    '5' => 4,
    '6' => 5,
    '7' => 6,
    '8' => 5,
    '9' => 4,
    '10' => 3,
    '11' => 2,
    '12' => 1
  )
end

Or reproduce Gary Gygax’s famous generation table from the original Dungeon Master’s Guide (page 171):

Calyx::Grammar.new do
  start(
    :empty => 0.6,
    :monster => 0.1,
    :monster_treasure => 0.15,
    :special => 0.05,
    :trick_trap => 0.05,
    :treasure => 0.05
  )
  empty 'Empty'
  monster 'Monster Only'
  monster_treasure 'Monster and Treasure'
  special 'Special'
  trick_trap 'Trick/Trap.'
  treasure 'Treasure'
end

String Modifiers

Dot-notation is supported in template expressions, allowing you to call any available method on the String object returned from a rule. Formatting methods can be chained arbitrarily and will execute in the same way as they would in native Ruby code.

greeting = Calyx::Grammar.new do
  start '{hello.capitalize} there.', 'Why, {hello} there.'
  hello 'hello', 'hi'
end

4.times { greeting.generate }
# => "Hello there."
# => "Hi there."
# => "Why, hello there."
# => "Why, hi there."

You can also extend the grammar with custom modifiers that provide useful formatting functions.

Filters

Filters accept an input string and return the transformed output:

greeting = Calyx::Grammar.new do
  filter :shoutycaps do |input|
    input.upcase
  end

  start '{hello.shoutycaps} there.', 'Why, {hello.shoutycaps} there.'
  hello 'hello', 'hi'
end

4.times { greeting.generate }
# => "HELLO there."
# => "HI there."
# => "Why, HELLO there."
# => "Why, HI there."

Mappings

The mapping shortcut allows you to specify a map of regex patterns pointing to their resulting substitution strings:

green_bottle = Calyx::Grammar.new do
  mapping :pluralize, /(.+)/ => '\\1s'
  start 'One green {bottle}.', 'Two green {bottle.pluralize}.'
  bottle 'bottle'
end

2.times { green_bottle.generate }
# => "One green bottle."
# => "Two green bottles."

Modifier Mixins

In order to use more intricate rewriting and formatting methods in a modifier chain, you can add methods to a module and embed it in a grammar using the modifier classmethod.

Modifier methods accept a single argument representing the input string from the previous step in the expression chain and must return a string, representing the modified output.

module FullStop
  def full_stop(input)
    input << '.'
  end
end

hello = Calyx::Grammar.new do
  modifier FullStop
  start '{hello.capitalize.full_stop}'
  hello 'hello'
end

hello.generate
# => "Hello."

To share custom modifiers across multiple grammars, you can include the module in Calyx::Modifiers. This will make the methods available to all subsequent instances:

module FullStop
  def full_stop(input)
    input << '.'
  end
end

class Calyx::Modifiers
  include FullStop
end

Monkeypatching String

Alternatively, you can combine methods from existing Gems that monkeypatch String:

require 'indefinite_article'

module FullStop
  def full_stop
    self << '.'
  end
end

class String
  include FullStop
end

noun_articles = Calyx::Grammar.new do
  start '{fruit.with_indefinite_article.capitalize.full_stop}'
  fruit 'apple', 'orange', 'banana', 'pear'
end

4.times { noun_articles.generate }
# => "An apple."
# => "An orange."
# => "A banana."
# => "A pear."

Memoized Rules

Rule expansions can be ‘memoized’ so that multiple references to the same rule return the same value. This is useful for picking a noun from a list and reusing it in multiple places within a text.

The @ sigil is used to mark memoized rules. This evaluates the rule and stores it in memory the first time it’s referenced. All subsequent references to the memoized rule use the same stored value.

# Without memoization
grammar = Calyx::Grammar.new do
  start '{name} <{name.downcase}>'
  name 'Daenerys', 'Tyrion', 'Jon'
end

3.times { grammar.generate }
# => Daenerys <jon>
# => Tyrion <daenerys>
# => Jon <tyrion>

# With memoization
grammar = Calyx::Grammar.new do
  start '{@name} <{@name.downcase}>'
  name 'Daenerys', 'Tyrion', 'Jon'
end

3.times { grammar.generate }
# => Tyrion <tyrion>
# => Daenerys <daenerys>
# => Jon <jon>

Note that the memoization symbol can only be used on the right hand side of a production rule.

Unique Rules

Rule expansions can be marked as ‘unique’, meaning that multiple references to the same rule always return a different value. This is useful for situations where the same result appearing twice would appear awkward and messy.

Unique rules are marked by the $ sigil.

grammar = Calyx::Grammar.new do
  start "{$medal}, {$medal}, {$medal}"
  medal 'Gold', 'Silver', 'Bronze'
end

grammar.generate
# => Silver, Bronze, Gold

Dynamically Constructing Rules

Template expansions can be dynamically constructed at runtime by passing a context map of rules to the #generate method:

class AppGreeting < Calyx::Grammar
  start 'Hi {username}!', 'Welcome back {username}...', 'Hola {username}'
end

context = {
  username: UserModel.username
}

greeting = AppGreeting.new
greeting.generate(context)

External File Formats

In addition to defining grammars in pure Ruby, you can load them from external JSON and YAML files:

hello = Calyx::Grammar.load('hello.yml')
hello.generate

The format requires a flat map with keys representing the left-hand side named symbols and the values representing the right hand side substitution rules.

In JSON:

{
  "start": "{greeting} world.",
  "greeting": ["Hello", "Hi", "Hey", "Yo"]
}

In YAML:

---
start: "{greeting} world."
greeting:
  - Hello
  - Hi
  - Hey
  - Yo

Accessing the Raw Generated Tree

Calling #evaluate on the grammar instance will give you access to the raw generated tree structure before it gets flattened into a string.

The tree is encoded as an array of nested arrays, with the leading symbols labeling the choices and rules selected, and the trailing terminal leaves encoding string values.

This may not make a lot of sense unless you’re familiar with the concept of s-expressions. It’s a fairly speculative feature at this stage, but it leads to some interesting possibilities.

grammar = Calyx::Grammar.new do
  start 'Riddle me ree.'
end

grammar.evaluate
# => [:start, [:choice, [:concat, [[:atom, "Riddle me ree."]]]]]

Roadmap

Rough plan for stabilising the API and features for a 1.0 release.

VersionFeatures planned
0.6block constructor
0.7support for template context map passed to generate
0.8method missing metaclass API
0.9return grammar tree from #evaluate, with flattened string from #generate being separate
0.10inject custom string functions for parameterised rules, transforms and mappings
0.11support YAML format (and JSON?)
0.12API documentation
0.13Support for unique rules
0.14Support for Ruby 2.4
0.15Options config and ‘strict mode’ error handling
0.16Improve representation of weighted probability selection
0.17Return result object from #generate calls

Credits

Author & Maintainer

Contributors

Author: Maetl
Source Code: https://github.com/maetl/calyx 
License: MIT license

#ruby #text