Garnett Bogisich

Garnett Bogisich

1639800000

Tutorial to Design File input Field using CSS Materialize (step By Ste

If you want to style an input button with a path input i provide this structure with the help of Materialize CSS framework in this simple video.

#css 

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Buddha Community

Tutorial to Design File input Field using CSS Materialize (step By Ste
Chloe Butler

Chloe Butler

1667425440

Pdf2gerb: Perl Script Converts PDF Files to Gerber format

pdf2gerb

Perl script converts PDF files to Gerber format

Pdf2Gerb generates Gerber 274X photoplotting and Excellon drill files from PDFs of a PCB. Up to three PDFs are used: the top copper layer, the bottom copper layer (for 2-sided PCBs), and an optional silk screen layer. The PDFs can be created directly from any PDF drawing software, or a PDF print driver can be used to capture the Print output if the drawing software does not directly support output to PDF.

The general workflow is as follows:

  1. Design the PCB using your favorite CAD or drawing software.
  2. Print the top and bottom copper and top silk screen layers to a PDF file.
  3. Run Pdf2Gerb on the PDFs to create Gerber and Excellon files.
  4. Use a Gerber viewer to double-check the output against the original PCB design.
  5. Make adjustments as needed.
  6. Submit the files to a PCB manufacturer.

Please note that Pdf2Gerb does NOT perform DRC (Design Rule Checks), as these will vary according to individual PCB manufacturer conventions and capabilities. Also note that Pdf2Gerb is not perfect, so the output files must always be checked before submitting them. As of version 1.6, Pdf2Gerb supports most PCB elements, such as round and square pads, round holes, traces, SMD pads, ground planes, no-fill areas, and panelization. However, because it interprets the graphical output of a Print function, there are limitations in what it can recognize (or there may be bugs).

See docs/Pdf2Gerb.pdf for install/setup, config, usage, and other info.

pdf2gerb_cfg.pm

#Pdf2Gerb config settings:
#Put this file in same folder/directory as pdf2gerb.pl itself (global settings),
#or copy to another folder/directory with PDFs if you want PCB-specific settings.
#There is only one user of this file, so we don't need a custom package or namespace.
#NOTE: all constants defined in here will be added to main namespace.
#package pdf2gerb_cfg;

use strict; #trap undef vars (easier debug)
use warnings; #other useful info (easier debug)


##############################################################################################
#configurable settings:
#change values here instead of in main pfg2gerb.pl file

use constant WANT_COLORS => ($^O !~ m/Win/); #ANSI colors no worky on Windows? this must be set < first DebugPrint() call

#just a little warning; set realistic expectations:
#DebugPrint("${\(CYAN)}Pdf2Gerb.pl ${\(VERSION)}, $^O O/S\n${\(YELLOW)}${\(BOLD)}${\(ITALIC)}This is EXPERIMENTAL software.  \nGerber files MAY CONTAIN ERRORS.  Please CHECK them before fabrication!${\(RESET)}", 0); #if WANT_DEBUG

use constant METRIC => FALSE; #set to TRUE for metric units (only affect final numbers in output files, not internal arithmetic)
use constant APERTURE_LIMIT => 0; #34; #max #apertures to use; generate warnings if too many apertures are used (0 to not check)
use constant DRILL_FMT => '2.4'; #'2.3'; #'2.4' is the default for PCB fab; change to '2.3' for CNC

use constant WANT_DEBUG => 0; #10; #level of debug wanted; higher == more, lower == less, 0 == none
use constant GERBER_DEBUG => 0; #level of debug to include in Gerber file; DON'T USE FOR FABRICATION
use constant WANT_STREAMS => FALSE; #TRUE; #save decompressed streams to files (for debug)
use constant WANT_ALLINPUT => FALSE; #TRUE; #save entire input stream (for debug ONLY)

#DebugPrint(sprintf("${\(CYAN)}DEBUG: stdout %d, gerber %d, want streams? %d, all input? %d, O/S: $^O, Perl: $]${\(RESET)}\n", WANT_DEBUG, GERBER_DEBUG, WANT_STREAMS, WANT_ALLINPUT), 1);
#DebugPrint(sprintf("max int = %d, min int = %d\n", MAXINT, MININT), 1); 

#define standard trace and pad sizes to reduce scaling or PDF rendering errors:
#This avoids weird aperture settings and replaces them with more standardized values.
#(I'm not sure how photoplotters handle strange sizes).
#Fewer choices here gives more accurate mapping in the final Gerber files.
#units are in inches
use constant TOOL_SIZES => #add more as desired
(
#round or square pads (> 0) and drills (< 0):
    .010, -.001,  #tiny pads for SMD; dummy drill size (too small for practical use, but needed so StandardTool will use this entry)
    .031, -.014,  #used for vias
    .041, -.020,  #smallest non-filled plated hole
    .051, -.025,
    .056, -.029,  #useful for IC pins
    .070, -.033,
    .075, -.040,  #heavier leads
#    .090, -.043,  #NOTE: 600 dpi is not high enough resolution to reliably distinguish between .043" and .046", so choose 1 of the 2 here
    .100, -.046,
    .115, -.052,
    .130, -.061,
    .140, -.067,
    .150, -.079,
    .175, -.088,
    .190, -.093,
    .200, -.100,
    .220, -.110,
    .160, -.125,  #useful for mounting holes
#some additional pad sizes without holes (repeat a previous hole size if you just want the pad size):
    .090, -.040,  #want a .090 pad option, but use dummy hole size
    .065, -.040, #.065 x .065 rect pad
    .035, -.040, #.035 x .065 rect pad
#traces:
    .001,  #too thin for real traces; use only for board outlines
    .006,  #minimum real trace width; mainly used for text
    .008,  #mainly used for mid-sized text, not traces
    .010,  #minimum recommended trace width for low-current signals
    .012,
    .015,  #moderate low-voltage current
    .020,  #heavier trace for power, ground (even if a lighter one is adequate)
    .025,
    .030,  #heavy-current traces; be careful with these ones!
    .040,
    .050,
    .060,
    .080,
    .100,
    .120,
);
#Areas larger than the values below will be filled with parallel lines:
#This cuts down on the number of aperture sizes used.
#Set to 0 to always use an aperture or drill, regardless of size.
use constant { MAX_APERTURE => max((TOOL_SIZES)) + .004, MAX_DRILL => -min((TOOL_SIZES)) + .004 }; #max aperture and drill sizes (plus a little tolerance)
#DebugPrint(sprintf("using %d standard tool sizes: %s, max aper %.3f, max drill %.3f\n", scalar((TOOL_SIZES)), join(", ", (TOOL_SIZES)), MAX_APERTURE, MAX_DRILL), 1);

#NOTE: Compare the PDF to the original CAD file to check the accuracy of the PDF rendering and parsing!
#for example, the CAD software I used generated the following circles for holes:
#CAD hole size:   parsed PDF diameter:      error:
#  .014                .016                +.002
#  .020                .02267              +.00267
#  .025                .026                +.001
#  .029                .03167              +.00267
#  .033                .036                +.003
#  .040                .04267              +.00267
#This was usually ~ .002" - .003" too big compared to the hole as displayed in the CAD software.
#To compensate for PDF rendering errors (either during CAD Print function or PDF parsing logic), adjust the values below as needed.
#units are pixels; for example, a value of 2.4 at 600 dpi = .0004 inch, 2 at 600 dpi = .0033"
use constant
{
    HOLE_ADJUST => -0.004 * 600, #-2.6, #holes seemed to be slightly oversized (by .002" - .004"), so shrink them a little
    RNDPAD_ADJUST => -0.003 * 600, #-2, #-2.4, #round pads seemed to be slightly oversized, so shrink them a little
    SQRPAD_ADJUST => +0.001 * 600, #+.5, #square pads are sometimes too small by .00067, so bump them up a little
    RECTPAD_ADJUST => 0, #(pixels) rectangular pads seem to be okay? (not tested much)
    TRACE_ADJUST => 0, #(pixels) traces seemed to be okay?
    REDUCE_TOLERANCE => .001, #(inches) allow this much variation when reducing circles and rects
};

#Also, my CAD's Print function or the PDF print driver I used was a little off for circles, so define some additional adjustment values here:
#Values are added to X/Y coordinates; units are pixels; for example, a value of 1 at 600 dpi would be ~= .002 inch
use constant
{
    CIRCLE_ADJUST_MINX => 0,
    CIRCLE_ADJUST_MINY => -0.001 * 600, #-1, #circles were a little too high, so nudge them a little lower
    CIRCLE_ADJUST_MAXX => +0.001 * 600, #+1, #circles were a little too far to the left, so nudge them a little to the right
    CIRCLE_ADJUST_MAXY => 0,
    SUBST_CIRCLE_CLIPRECT => FALSE, #generate circle and substitute for clip rects (to compensate for the way some CAD software draws circles)
    WANT_CLIPRECT => TRUE, #FALSE, #AI doesn't need clip rect at all? should be on normally?
    RECT_COMPLETION => FALSE, #TRUE, #fill in 4th side of rect when 3 sides found
};

#allow .012 clearance around pads for solder mask:
#This value effectively adjusts pad sizes in the TOOL_SIZES list above (only for solder mask layers).
use constant SOLDER_MARGIN => +.012; #units are inches

#line join/cap styles:
use constant
{
    CAP_NONE => 0, #butt (none); line is exact length
    CAP_ROUND => 1, #round cap/join; line overhangs by a semi-circle at either end
    CAP_SQUARE => 2, #square cap/join; line overhangs by a half square on either end
    CAP_OVERRIDE => FALSE, #cap style overrides drawing logic
};
    
#number of elements in each shape type:
use constant
{
    RECT_SHAPELEN => 6, #x0, y0, x1, y1, count, "rect" (start, end corners)
    LINE_SHAPELEN => 6, #x0, y0, x1, y1, count, "line" (line seg)
    CURVE_SHAPELEN => 10, #xstart, ystart, x0, y0, x1, y1, xend, yend, count, "curve" (bezier 2 points)
    CIRCLE_SHAPELEN => 5, #x, y, 5, count, "circle" (center + radius)
};
#const my %SHAPELEN =
#Readonly my %SHAPELEN =>
our %SHAPELEN =
(
    rect => RECT_SHAPELEN,
    line => LINE_SHAPELEN,
    curve => CURVE_SHAPELEN,
    circle => CIRCLE_SHAPELEN,
);

#panelization:
#This will repeat the entire body the number of times indicated along the X or Y axes (files grow accordingly).
#Display elements that overhang PCB boundary can be squashed or left as-is (typically text or other silk screen markings).
#Set "overhangs" TRUE to allow overhangs, FALSE to truncate them.
#xpad and ypad allow margins to be added around outer edge of panelized PCB.
use constant PANELIZE => {'x' => 1, 'y' => 1, 'xpad' => 0, 'ypad' => 0, 'overhangs' => TRUE}; #number of times to repeat in X and Y directions

# Set this to 1 if you need TurboCAD support.
#$turboCAD = FALSE; #is this still needed as an option?

#CIRCAD pad generation uses an appropriate aperture, then moves it (stroke) "a little" - we use this to find pads and distinguish them from PCB holes. 
use constant PAD_STROKE => 0.3; #0.0005 * 600; #units are pixels
#convert very short traces to pads or holes:
use constant TRACE_MINLEN => .001; #units are inches
#use constant ALWAYS_XY => TRUE; #FALSE; #force XY even if X or Y doesn't change; NOTE: needs to be TRUE for all pads to show in FlatCAM and ViewPlot
use constant REMOVE_POLARITY => FALSE; #TRUE; #set to remove subtractive (negative) polarity; NOTE: must be FALSE for ground planes

#PDF uses "points", each point = 1/72 inch
#combined with a PDF scale factor of .12, this gives 600 dpi resolution (1/72 * .12 = 600 dpi)
use constant INCHES_PER_POINT => 1/72; #0.0138888889; #multiply point-size by this to get inches

# The precision used when computing a bezier curve. Higher numbers are more precise but slower (and generate larger files).
#$bezierPrecision = 100;
use constant BEZIER_PRECISION => 36; #100; #use const; reduced for faster rendering (mainly used for silk screen and thermal pads)

# Ground planes and silk screen or larger copper rectangles or circles are filled line-by-line using this resolution.
use constant FILL_WIDTH => .01; #fill at most 0.01 inch at a time

# The max number of characters to read into memory
use constant MAX_BYTES => 10 * M; #bumped up to 10 MB, use const

use constant DUP_DRILL1 => TRUE; #FALSE; #kludge: ViewPlot doesn't load drill files that are too small so duplicate first tool

my $runtime = time(); #Time::HiRes::gettimeofday(); #measure my execution time

print STDERR "Loaded config settings from '${\(__FILE__)}'.\n";
1; #last value must be truthful to indicate successful load


#############################################################################################
#junk/experiment:

#use Package::Constants;
#use Exporter qw(import); #https://perldoc.perl.org/Exporter.html

#my $caller = "pdf2gerb::";

#sub cfg
#{
#    my $proto = shift;
#    my $class = ref($proto) || $proto;
#    my $settings =
#    {
#        $WANT_DEBUG => 990, #10; #level of debug wanted; higher == more, lower == less, 0 == none
#    };
#    bless($settings, $class);
#    return $settings;
#}

#use constant HELLO => "hi there2"; #"main::HELLO" => "hi there";
#use constant GOODBYE => 14; #"main::GOODBYE" => 12;

#print STDERR "read cfg file\n";

#our @EXPORT_OK = Package::Constants->list(__PACKAGE__); #https://www.perlmonks.org/?node_id=1072691; NOTE: "_OK" skips short/common names

#print STDERR scalar(@EXPORT_OK) . " consts exported:\n";
#foreach(@EXPORT_OK) { print STDERR "$_\n"; }
#my $val = main::thing("xyz");
#print STDERR "caller gave me $val\n";
#foreach my $arg (@ARGV) { print STDERR "arg $arg\n"; }

Download Details:

Author: swannman
Source Code: https://github.com/swannman/pdf2gerb

License: GPL-3.0 license

#perl 

I am Developer

1597489568

Dynamically Add/Remove Multiple input Fields and Submit to DB with jQuery and Laravel

In this post, i will show you how to dynamically add/remove multiple input fields and submit to database with jquery in php laravel framework. As well as, i will show you how to add/remove multiple input fields and submit to database with validation in laravel.

dynamically add remove multiple input fields and submit to database with jquery and laravel app will looks like, you can see in the following picture:

add/remove multiple input fields dynamically with jquery laravel

Laravel - Add/Remove Multiple Input Fields Using jQuery, javaScript

Follow the below given easy step to create dynamically add or remove multiple input fields and submit to database with jquery in php laravel

  • Step 1: Install Laravel App
  • Step 2: Add Database Details
  • Step 3: Create Migration & Model
  • Step 4: Add Routes
  • Step 5: Create Controller by Artisan
  • Step 6: Create Blade View
  • Step 7: Run Development Server

https://www.tutsmake.com/add-remove-multiple-input-fields-in-laravel-using-jquery/

#laravel - dynamically add or remove input fields using jquery #dynamically add / remove multiple input fields in laravel 7 using jquery ajax #add/remove multiple input fields dynamically with jquery laravel #dynamically add multiple input fields and submit to database with jquery and laravel #add remove input fields dynamically with jquery and submit to database #sql

John Smith

John Smith

1657107416

Find the Best Restaurant Mobile App Development Company in Abu Dhbai

The era of mobile app development has completely changed the scenario for businesses in regions like Abu Dhabi. Restaurants and food delivery businesses are experiencing huge benefits via smart business applications. The invention and development of the food ordering app have helped all-scale businesses reach new customers and boost sales and profit. 

As a result, many business owners are searching for the best restaurant mobile app development company in Abu Dhabi. If you are also searching for the same, this article is helpful for you. It will let you know the step-by-step process to hire the right team of restaurant mobile app developers. 

Step-by-Step Process to Find the Best Restaurant App Development Company

Searching for the top mobile app development company in Abu Dhabi? Don't know the best way to search for professionals? Don't panic! Here is the step-by-step process to hire the best professionals. 

#Step 1 – Know the Company's Culture

Knowing the organization's culture is very crucial before finalizing a food ordering app development company in Abu Dhabi. An organization's personality is shaped by its common beliefs, goals, practices, or company culture. So, digging into the company culture reveals the core beliefs of the organization, its objectives, and its development team. 

Now, you might be wondering, how will you identify the company's culture? Well, you can take reference from the following sources – 

  • Social media posts 
  • App development process
  • About us Page
  • Client testimonials

#Step 2 - Refer to Clients' Reviews

Another best way to choose the On-demand app development firm for your restaurant business is to refer to the clients' reviews. Reviews are frequently available on the organization's website with a tag of "Reviews" or "Testimonials." It's important to read the reviews as they will help you determine how happy customers are with the company's app development process. 

You can also assess a company's abilities through reviews and customer testimonials. They can let you know if the mobile app developers create a valuable app or not. 

#Step 3 – Analyze the App Development Process

Regardless of the company's size or scope, adhering to the restaurant delivery app development process will ensure the success of your business application. Knowing the processes an app developer follows in designing and producing a top-notch app will help you know the working process. Organizations follow different app development approaches, so getting well-versed in the process is essential before finalizing any mobile app development company. 

#Step 4 – Consider Previous Experience

Besides considering other factors, considering the previous experience of the developers is a must. You can obtain a broad sense of the developer's capacity to assist you in creating a unique mobile application for a restaurant business.

You can also find out if the developers' have contributed to the creation of other successful applications or not. It will help you know the working capacity of a particular developer or organization. Prior experience is essential to evaluating their work. For instance, whether they haven't previously produced an app similar to yours or not. 

#Step 5 – Check for Their Technical Support

As you expect a working and successful restaurant mobile app for your business, checking on this factor is a must. A well-established organization is nothing without a good technical support team. So, ensure whatever restaurant mobile app development company you choose they must be well-equipped with a team of dedicated developers, designers, and testers. 

Strong tech support from your mobile app developers will help you identify new bugs and fix them bugs on time. All this will ensure the application's success. 

#Step 6 – Analyze Design Standards

Besides focusing on an organization's development, testing, and technical support, you should check the design standards. An appealing design is crucial in attracting new users and keeping the existing ones stick to your services. So, spend some time analyzing the design standards of an organization. Now, you might be wondering, how will you do it? Simple! By looking at the organization's portfolio. 

Whether hiring an iPhone app development company or any other, these steps apply to all. So, don't miss these steps. 

#Step 7 – Know Their Location

Finally, the last yet very crucial factor that will not only help you finalize the right person for your restaurant mobile app development but will also decide the mobile app development cost. So, you have to choose the location of the developers wisely, as it is a crucial factor in defining the cost. 

Summing Up!!!

Restaurant mobile applications have taken the food industry to heights none have ever considered. As a result, the demand for restaurant mobile app development companies has risen greatly, which is why businesses find it difficult to finalize the right person. But, we hope that after referring to this article, it will now be easier to hire dedicated developers under the desired budget. So, begin the hiring process now and get a well-craft food ordering app in hand. 

Arvilla Medhurst

Arvilla Medhurst

1661577180

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 

Dylan Iqbal

Dylan Iqbal

1561523460

Matplotlib Cheat Sheet: Plotting in Python

This Matplotlib cheat sheet introduces you to the basics that you need to plot your data with Python and includes code samples.

Data visualization and storytelling with your data are essential skills that every data scientist needs to communicate insights gained from analyses effectively to any audience out there. 

For most beginners, the first package that they use to get in touch with data visualization and storytelling is, naturally, Matplotlib: it is a Python 2D plotting library that enables users to make publication-quality figures. But, what might be even more convincing is the fact that other packages, such as Pandas, intend to build more plotting integration with Matplotlib as time goes on.

However, what might slow down beginners is the fact that this package is pretty extensive. There is so much that you can do with it and it might be hard to still keep a structure when you're learning how to work with Matplotlib.   

DataCamp has created a Matplotlib cheat sheet for those who might already know how to use the package to their advantage to make beautiful plots in Python, but that still want to keep a one-page reference handy. Of course, for those who don't know how to work with Matplotlib, this might be the extra push be convinced and to finally get started with data visualization in Python. 

You'll see that this cheat sheet presents you with the six basic steps that you can go through to make beautiful plots. 

Check out the infographic by clicking on the button below:

Python Matplotlib cheat sheet

With this handy reference, you'll familiarize yourself in no time with the basics of Matplotlib: you'll learn how you can prepare your data, create a new plot, use some basic plotting routines to your advantage, add customizations to your plots, and save, show and close the plots that you make.

What might have looked difficult before will definitely be more clear once you start using this cheat sheet! Use it in combination with the Matplotlib Gallery, the documentation.

Matplotlib 

Matplotlib is a Python 2D plotting library which produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.

Prepare the Data 

1D Data 

>>> import numpy as np
>>> x = np.linspace(0, 10, 100)
>>> y = np.cos(x)
>>> z = np.sin(x)

2D Data or Images 

>>> data = 2 * np.random.random((10, 10))
>>> data2 = 3 * np.random.random((10, 10))
>>> Y, X = np.mgrid[-3:3:100j, -3:3:100j]
>>> U = 1 X** 2 + Y
>>> V = 1 + X Y**2
>>> from matplotlib.cbook import get_sample_data
>>> img = np.load(get_sample_data('axes_grid/bivariate_normal.npy'))

Create Plot

>>> import matplotlib.pyplot as plt

Figure 

>>> fig = plt.figure()
>>> fig2 = plt.figure(figsize=plt.figaspect(2.0))

Axes 

>>> fig.add_axes()
>>> ax1 = fig.add_subplot(221) #row-col-num
>>> ax3 = fig.add_subplot(212)
>>> fig3, axes = plt.subplots(nrows=2,ncols=2)
>>> fig4, axes2 = plt.subplots(ncols=3)

Save Plot 

>>> plt.savefig('foo.png') #Save figures
>>> plt.savefig('foo.png',  transparent=True) #Save transparent figures

Show Plot

>>> plt.show()

Plotting Routines 

1D Data 

>>> fig, ax = plt.subplots()
>>> lines = ax.plot(x,y) #Draw points with lines or markers connecting them
>>> ax.scatter(x,y) #Draw unconnected points, scaled or colored
>>> axes[0,0].bar([1,2,3],[3,4,5]) #Plot vertical rectangles (constant width)
>>> axes[1,0].barh([0.5,1,2.5],[0,1,2]) #Plot horiontal rectangles (constant height)
>>> axes[1,1].axhline(0.45) #Draw a horizontal line across axes
>>> axes[0,1].axvline(0.65) #Draw a vertical line across axes
>>> ax.fill(x,y,color='blue') #Draw filled polygons
>>> ax.fill_between(x,y,color='yellow') #Fill between y values and 0

2D Data 

>>> fig, ax = plt.subplots()
>>> im = ax.imshow(img, #Colormapped or RGB arrays
      cmap= 'gist_earth', 
      interpolation= 'nearest',
      vmin=-2,
      vmax=2)
>>> axes2[0].pcolor(data2) #Pseudocolor plot of 2D array
>>> axes2[0].pcolormesh(data) #Pseudocolor plot of 2D array
>>> CS = plt.contour(Y,X,U) #Plot contours
>>> axes2[2].contourf(data1) #Plot filled contours
>>> axes2[2]= ax.clabel(CS) #Label a contour plot

Vector Fields 

>>> axes[0,1].arrow(0,0,0.5,0.5) #Add an arrow to the axes
>>> axes[1,1].quiver(y,z) #Plot a 2D field of arrows
>>> axes[0,1].streamplot(X,Y,U,V) #Plot a 2D field of arrows

Data Distributions 

>>> ax1.hist(y) #Plot a histogram
>>> ax3.boxplot(y) #Make a box and whisker plot
>>> ax3.violinplot(z)  #Make a violin plot

Plot Anatomy & Workflow 

Plot Anatomy 

 y-axis      

                           x-axis 

Workflow 

The basic steps to creating plots with matplotlib are:

1 Prepare Data
2 Create Plot
3 Plot
4 Customized Plot
5 Save Plot
6 Show Plot

>>> import matplotlib.pyplot as plt
>>> x = [1,2,3,4]  #Step 1
>>> y = [10,20,25,30] 
>>> fig = plt.figure() #Step 2
>>> ax = fig.add_subplot(111) #Step 3
>>> ax.plot(x, y, color= 'lightblue', linewidth=3)  #Step 3, 4
>>> ax.scatter([2,4,6],
          [5,15,25],
          color= 'darkgreen',
          marker= '^' )
>>> ax.set_xlim(1, 6.5)
>>> plt.savefig('foo.png' ) #Step 5
>>> plt.show() #Step 6

Close and Clear 

>>> plt.cla()  #Clear an axis
>>> plt.clf(). #Clear the entire figure
>>> plt.close(). #Close a window

Plotting Customize Plot 

Colors, Color Bars & Color Maps 

>>> plt.plot(x, x, x, x**2, x, x** 3)
>>> ax.plot(x, y, alpha = 0.4)
>>> ax.plot(x, y, c= 'k')
>>> fig.colorbar(im, orientation= 'horizontal')
>>> im = ax.imshow(img,
            cmap= 'seismic' )

Markers 

>>> fig, ax = plt.subplots()
>>> ax.scatter(x,y,marker= ".")
>>> ax.plot(x,y,marker= "o")

Linestyles 

>>> plt.plot(x,y,linewidth=4.0)
>>> plt.plot(x,y,ls= 'solid') 
>>> plt.plot(x,y,ls= '--') 
>>> plt.plot(x,y,'--' ,x**2,y**2,'-.' ) 
>>> plt.setp(lines,color= 'r',linewidth=4.0)

Text & Annotations 

>>> ax.text(1,
           -2.1, 
           'Example Graph', 
            style= 'italic' )
>>> ax.annotate("Sine", 
xy=(8, 0),
xycoords= 'data', 
xytext=(10.5, 0),
textcoords= 'data', 
arrowprops=dict(arrowstyle= "->", 
connectionstyle="arc3"),)

Mathtext 

>>> plt.title(r '$sigma_i=15$', fontsize=20)

Limits, Legends and Layouts 

Limits & Autoscaling 

>>> ax.margins(x=0.0,y=0.1) #Add padding to a plot
>>> ax.axis('equal')  #Set the aspect ratio of the plot to 1
>>> ax.set(xlim=[0,10.5],ylim=[-1.5,1.5])  #Set limits for x-and y-axis
>>> ax.set_xlim(0,10.5) #Set limits for x-axis

Legends 

>>> ax.set(title= 'An Example Axes',  #Set a title and x-and y-axis labels
            ylabel= 'Y-Axis', 
            xlabel= 'X-Axis')
>>> ax.legend(loc= 'best')  #No overlapping plot elements

Ticks 

>>> ax.xaxis.set(ticks=range(1,5),  #Manually set x-ticks
             ticklabels=[3,100, 12,"foo" ])
>>> ax.tick_params(axis= 'y', #Make y-ticks longer and go in and out
             direction= 'inout', 
              length=10)

Subplot Spacing 

>>> fig3.subplots_adjust(wspace=0.5,   #Adjust the spacing between subplots
             hspace=0.3,
             left=0.125,
             right=0.9,
             top=0.9,
             bottom=0.1)
>>> fig.tight_layout() #Fit subplot(s) in to the figure area

Axis Spines 

>>> ax1.spines[ 'top'].set_visible(False) #Make the top axis line for a plot invisible
>>> ax1.spines['bottom' ].set_position(( 'outward',10))  #Move the bottom axis line outward

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Original article source at https://www.datacamp.com

#matplotlib #cheatsheet #python