Build a Call Overflow System to Manage Overloaded Phone Lines

Right now telephony systems for healthcare provider offices are overloaded with calls due to  vaccine appointment scheduling. As widespread rollout increases globally, it’s important for healthcare systems to anticipate this volume increase. In this article you will learn how to build a cloud-based interactive voice response (IVR) system with Twilio Studio and Twilio Serverless. This system will handle incoming calls so that no patient’s call will be lost; it will store the patient’s request in a database that can be used by a healthcare professional to review and follow up.

You might be wondering where exactly you would store the patient’s request. This will likely go in the patient’s Electronic Health Record (EHR). According to  cms.gov, an EHR is an electronic version of a patient’s medical history, that is maintained by the provider over time, and may include all of the key administrative clinical data relevant to that persons care under a particular provider. Some examples of EHRs include Epic and Cerner, and they can be accessed in a variety of secure ways, like using middleware such as  Redox Engine or  ELLKAY.

For building this prototype, we will use Airtable (a cloud spreadsheet-like database) to simulate the EHR that you use to safely store patient data. If you’re not familiar with Airtable, you will learn how to set up a base step-by-step.

Please note that Airtable should not be used in production and is only meant to be used for this tutorial.

First you will set up the Twilio Studio flow to handle incoming calls. Then you will configure the Airtable base in Twilio Serverless. Finally, you will add node.js code that will take the data sent from Twilio Studio and write it to the Airtable base.

Prerequisites

• A Twilio account. If you sign up for a new account through this link, you’ll get an extra $10 in credit when you upgrade.
• A Twilio phone number. Instructions on how to get one are here.
• An Airtable account.

Set up the Twilio Studio IVR flow

First, you will build a system to handle incoming calls with Twilio Studio, a stateful visual workflow builder. Twilio Studio is hosted by Twilio, so you don’t need to set up your own server or deploy anything separately. It uses Twilio Programmable Voice to gather the data via keypress or voicemail.

To make a new Twilio Studio flow, log in to your Twilio account and go to the  Studio Dashboard. Then, click the blue plus sign and give your flow the name “Call Overflow Handler.” Click next in the setup modal, scroll down and choose “Import from JSON” from the provided templates.

#serverless

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Pythonグローバル変数–グローバル変数の例を定義する方法

この記事では、グローバル変数の基本を学びます。

まず、Pythonで変数を宣言する方法と、「変数スコープ」という用語が実際に何を意味するかを学習します。

次に、ローカル変数とグローバル変数の違いを学び、グローバル変数の定義方法とglobalキーワードの使用方法を理解します。

Pythonの変数とは何ですか？どのように作成しますか？初心者のための紹介

変数はストレージコンテナと考えることができます。

これらは、コンピュータのメモリに保存したいデータ、情報、および値を保持するためのストレージコンテナです。その後、プログラムの存続期間中のある時点でそれらを参照したり、操作したりすることもできます。

変数にはシンボリック名があり、その名前は、その識別子として機能するストレージコンテナのラベルと考えることができます。

変数名は、その中に格納されているデータへの参照とポインターになります。したがって、データと情報の詳細を覚えておく必要はありません。そのデータと情報を保持する変数名を参照するだけで済みます。

変数に名前を付けるときは、変数が保持するデータを説明していることを確認してください。変数名は、将来の自分自身と一緒に作業する可能性のある他の開発者の両方にとって、明確で簡単に理解できる必要があります。

それでは、Pythonで実際に変数を作成する方法を見てみましょう。

Pythonで変数を宣言するときは、データ型を指定する必要はありません。

たとえば、Cプログラミング言語では、変数が保持するデータの型を明示的に指定する必要があります。

したがって、整数またはint型である年齢を格納したい場合、これはCで行う必要があることです。

#include <stdio.h>
 
int main(void)
{
  int age = 28;
  // 'int' is the data type
  // 'age' is the name 
  // 'age' is capable of holding integer values
  // positive/negative whole numbers or 0
  // '=' is the assignment operator
  // '28' is the value
}

ただし、これはPythonで上記を記述する方法です。

age = 28

#'age' is the variable name, or identifier
# '=' is the assignment operator
#'28' is the value assigned to the variable, so '28' is the value of 'age'

変数名は常に左側にあり、代入する値は代入演算子の後に右側に配置されます。

プログラムの存続期間中、変数の値を変更できることに注意してください。

my_age = 28

print(f"My age in 2022 is {my_age}.")

my_age = 29

print(f"My age in 2023 will be {my_age}.")

#output

#My age in 2022 is 28.
#My age in 2023 will be 29.

同じ変数名を保持しますが、値をからにmy_age変更するだけです。2829

Pythonの可変スコープとはどういう意味ですか？

変数スコープとは、変数が利用可能で、アクセス可能で、表示可能なPythonプログラムの部分と境界を指します。

Python変数のスコープには4つのタイプがあり、 LEGBルールとも呼ばれます。

• 局所、
• 囲み、
• グローバル、
• ビルトイン。

この記事の残りの部分では、グローバルスコープを使用した変数の作成について学習することに焦点を当て、ローカル変数スコープとグローバル変数スコープの違いを理解します。

Pythonでローカルスコープを使用して変数を作成する方法

関数の本体内で定義された変数にはローカルスコープがあります。つまり、その特定の関数内でのみアクセスできます。言い換えれば、それらはその関数に対して「ローカル」です。

ローカル変数にアクセスするには、関数を呼び出す必要があります。

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()


#output

#The best place to learn to code is with freeCodeCamp!

関数の本体の外部からローカルスコープを使用してその変数にアクセスしようとするとどうなるかを見てください。

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#try to print local variable 'coding_website' from outside the function
print(coding_website)

#output

#NameError: name 'coding_website' is not defined

NameErrorプログラムの残りの部分では「表示」されないため、aが発生します。定義された関数内でのみ「表示」されます。

Pythonでグローバルスコープを使用して変数を作成する方法

ファイルの先頭など、関数の外部で変数を定義すると、その変数はグローバルスコープを持ち、グローバル変数と呼ばれます。

グローバル変数は、プログラムのどこからでもアクセスできます。

関数の本体内で使用することも、関数の外部からアクセスすることもできます。

#create a global variable
coding_website = "freeCodeCamp"

def learn_to_code():
    #access the variable 'coding_website' inside the function
    print(f"The best place to learn to code is with {coding_website}!")

#call the function
learn_to_code()

#access the variable 'coding_website' from outside the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

グローバル変数とローカル変数があり、両方が同じ名前の場合はどうなりますか？

#global variable
city = "Athens"

def travel_plans():
    #local variable with the same name as the global variable
    city = "London"
    print(f"I want to visit {city} next year!")

#call function - this will output the value of local variable
travel_plans()

#reference global variable - this will output the value of global variable
print(f"I want to visit {city} next year!")

#output

#I want to visit London next year!
#I want to visit Athens next year!

上記の例では、その特定の出力を期待していなかった可能性があります。

city関数内で別の値を割り当てたときに、の値が変わると思ったかもしれません。

たぶん、私が行でグローバル変数を参照したときprint(f" I want to visit {city} next year!")、出力は#I want to visit London next year!の代わりになると予想しました#I want to visit Athens next year!。

ただし、関数が呼び出されると、ローカル変数の値が出力されます。

次に、関数の外部でグローバル変数を参照すると、グローバル変数に割り当てられた値が出力されました。

彼らはお互いに干渉しませんでした。

ただし、グローバル変数とローカル変数に同じ変数名を使用することは、ベストプラクティスとは見なされません。プログラムを実行すると混乱する結果が生じる可能性があるため、変数の名前が同じでないことを確認してください。

Pythonでキーワードを使用する方法global

グローバル変数があり、関数内でその値を変更したい場合はどうなりますか？

私がそれをしようとすると何が起こるか見てください：

#global variable
city = "Athens"

def travel_plans():
    #First, this is like when I tried to access the global variable defined outside the function. 
    # This works fine on its own, as you saw earlier on.
    print(f"I want to visit {city} next year!")

    #However, when I then try to re-assign a different value to the global variable 'city' from inside the function,
    #after trying to print it,
    #it will throw an error
    city = "London"
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#output

#UnboundLocalError: local variable 'city' referenced before assignment

デフォルトでは、Pythonは関数内でローカル変数を使用したいと考えています。

そのため、最初に変数の値を出力してから、アクセスしようとしている変数に値を再割り当てしようとすると、Pythonが混乱します。

関数内のグローバル変数の値を変更する方法は、次のglobalキーワードを使用することです。

#global variable
city = "Athens"

#print value of global variable
print(f"I want to visit {city} next year!")

def travel_plans():
    global city
    #print initial value of global variable
    print(f"I want to visit {city} next year!")
    #assign a different value to global variable from within function
    city = "London"
    #print new value
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#print value of global variable
print(f"I want to visit {city} next year!")

global次のエラーが発生するため、関数でキーワードを参照する前にキーワードを使用してくださいSyntaxError: name 'city' is used prior to global declaration。

以前、関数内で作成された変数はローカルスコープを持っているため、それらにアクセスできないことを確認しました。

globalキーワードは、関数内で宣言された変数の可視性を変更します。

def learn_to_code():
   global coding_website
   coding_website = "freeCodeCamp"
   print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()

#access variable from within the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

結論

そして、あなたはそれを持っています！これで、Pythonのグローバル変数の基本を理解し、ローカル変数とグローバル変数の違いを理解できます。

この記事がお役に立てば幸いです。

基本から始めて、インタラクティブで初心者に優しい方法で学びます。また、最後に5つのプロジェクトを構築して実践し、学んだことを強化するのに役立てます。

読んでくれてありがとう、そして幸せなコーディング！

ソース：https ：//www.freecodecamp.org/news/python-global-variables-examples/

#python 

Variables Globales De Python: Cómo Definir Un Ejemplo De Variable Glob

En este artículo, aprenderá los conceptos básicos de las variables globales.

Para empezar, aprenderá cómo declarar variables en Python y qué significa realmente el término 'ámbito de variable'.

Luego, aprenderá las diferencias entre variables locales y globales y comprenderá cómo definir variables globales y cómo usar la globalpalabra clave.

¿Qué son las variables en Python y cómo se crean? Una introducción para principiantes

Puede pensar en las variables como contenedores de almacenamiento .

Son contenedores de almacenamiento para almacenar datos, información y valores que le gustaría guardar en la memoria de la computadora. Luego puede hacer referencia a ellos o incluso manipularlos en algún momento a lo largo de la vida del programa.

Una variable tiene un nombre simbólico y puede pensar en ese nombre como la etiqueta en el contenedor de almacenamiento que actúa como su identificador.

El nombre de la variable será una referencia y un puntero a los datos almacenados en su interior. Por lo tanto, no es necesario recordar los detalles de sus datos e información; solo necesita hacer referencia al nombre de la variable que contiene esos datos e información.

Al dar un nombre a una variable, asegúrese de que sea descriptivo de los datos que contiene. Los nombres de las variables deben ser claros y fácilmente comprensibles tanto para usted en el futuro como para los otros desarrolladores con los que puede estar trabajando.

Ahora, veamos cómo crear una variable en Python.

Al declarar variables en Python, no necesita especificar su tipo de datos.

Por ejemplo, en el lenguaje de programación C, debe mencionar explícitamente el tipo de datos que contendrá la variable.

Entonces, si quisiera almacenar su edad, que es un número entero, o inttipo, esto es lo que tendría que hacer en C:

#include <stdio.h>
 
int main(void)
{
  int age = 28;
  // 'int' is the data type
  // 'age' is the name 
  // 'age' is capable of holding integer values
  // positive/negative whole numbers or 0
  // '=' is the assignment operator
  // '28' is the value
}

Sin embargo, así es como escribirías lo anterior en Python:

age = 28

#'age' is the variable name, or identifier
# '=' is the assignment operator
#'28' is the value assigned to the variable, so '28' is the value of 'age'

El nombre de la variable siempre está en el lado izquierdo y el valor que desea asignar va en el lado derecho después del operador de asignación.

Tenga en cuenta que puede cambiar los valores de las variables a lo largo de la vida de un programa:

my_age = 28

print(f"My age in 2022 is {my_age}.")

my_age = 29

print(f"My age in 2023 will be {my_age}.")

#output

#My age in 2022 is 28.
#My age in 2023 will be 29.

Mantienes el mismo nombre de variable my_age, pero solo cambias el valor de 28a 29.

¿Qué significa el alcance variable en Python?

El alcance de la variable se refiere a las partes y los límites de un programa de Python donde una variable está disponible, accesible y visible.

Hay cuatro tipos de alcance para las variables de Python, que también se conocen como la regla LEGB :

• local ,
• Encerrando ,
• globales ,
• Incorporado .

En el resto de este artículo, se centrará en aprender a crear variables con alcance global y comprenderá la diferencia entre los alcances de variables locales y globales.

Cómo crear variables con alcance local en Python

Las variables definidas dentro del cuerpo de una función tienen alcance local , lo que significa que solo se puede acceder a ellas dentro de esa función en particular. En otras palabras, son 'locales' para esa función.

Solo puede acceder a una variable local llamando a la función.

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()


#output

#The best place to learn to code is with freeCodeCamp!

Mire lo que sucede cuando trato de acceder a esa variable con un alcance local desde fuera del cuerpo de la función:

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#try to print local variable 'coding_website' from outside the function
print(coding_website)

#output

#NameError: name 'coding_website' is not defined

Plantea un NameErrorporque no es 'visible' en el resto del programa. Solo es 'visible' dentro de la función donde se definió.

Cómo crear variables con alcance global en Python

Cuando define una variable fuera de una función, como en la parte superior del archivo, tiene un alcance global y se conoce como variable global.

Se accede a una variable global desde cualquier parte del programa.

Puede usarlo dentro del cuerpo de una función, así como acceder desde fuera de una función:

#create a global variable
coding_website = "freeCodeCamp"

def learn_to_code():
    #access the variable 'coding_website' inside the function
    print(f"The best place to learn to code is with {coding_website}!")

#call the function
learn_to_code()

#access the variable 'coding_website' from outside the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

¿Qué sucede cuando hay una variable global y local, y ambas tienen el mismo nombre?

#global variable
city = "Athens"

def travel_plans():
    #local variable with the same name as the global variable
    city = "London"
    print(f"I want to visit {city} next year!")

#call function - this will output the value of local variable
travel_plans()

#reference global variable - this will output the value of global variable
print(f"I want to visit {city} next year!")

#output

#I want to visit London next year!
#I want to visit Athens next year!

En el ejemplo anterior, tal vez no esperaba ese resultado específico.

Tal vez pensaste que el valor de citycambiaría cuando le asignara un valor diferente dentro de la función.

Tal vez esperabas que cuando hice referencia a la variable global con la línea print(f" I want to visit {city} next year!"), la salida sería en #I want to visit London next year!lugar de #I want to visit Athens next year!.

Sin embargo, cuando se llamó a la función, imprimió el valor de la variable local.

Luego, cuando hice referencia a la variable global fuera de la función, se imprimió el valor asignado a la variable global.

No interfirieron entre sí.

Dicho esto, usar el mismo nombre de variable para variables globales y locales no se considera una buena práctica. Asegúrese de que sus variables no tengan el mismo nombre, ya que puede obtener algunos resultados confusos cuando ejecute su programa.

Cómo usar la globalpalabra clave en Python

¿Qué sucede si tiene una variable global pero desea cambiar su valor dentro de una función?

Mira lo que sucede cuando trato de hacer eso:

#global variable
city = "Athens"

def travel_plans():
    #First, this is like when I tried to access the global variable defined outside the function. 
    # This works fine on its own, as you saw earlier on.
    print(f"I want to visit {city} next year!")

    #However, when I then try to re-assign a different value to the global variable 'city' from inside the function,
    #after trying to print it,
    #it will throw an error
    city = "London"
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#output

#UnboundLocalError: local variable 'city' referenced before assignment

Por defecto, Python piensa que quieres usar una variable local dentro de una función.

Entonces, cuando intento imprimir el valor de la variable por primera vez y luego reasignar un valor a la variable a la que intento acceder, Python se confunde.

La forma de cambiar el valor de una variable global dentro de una función es usando la globalpalabra clave:

#global variable
city = "Athens"

#print value of global variable
print(f"I want to visit {city} next year!")

def travel_plans():
    global city
    #print initial value of global variable
    print(f"I want to visit {city} next year!")
    #assign a different value to global variable from within function
    city = "London"
    #print new value
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#print value of global variable
print(f"I want to visit {city} next year!")

Utilice la globalpalabra clave antes de hacer referencia a ella en la función, ya que obtendrá el siguiente error: SyntaxError: name 'city' is used prior to global declaration.

Anteriormente, vio que no podía acceder a las variables creadas dentro de las funciones ya que tienen un alcance local.

La globalpalabra clave cambia la visibilidad de las variables declaradas dentro de las funciones.

def learn_to_code():
   global coding_website
   coding_website = "freeCodeCamp"
   print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()

#access variable from within the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

Conclusión

¡Y ahí lo tienes! Ahora conoce los conceptos básicos de las variables globales en Python y puede distinguir las diferencias entre las variables locales y globales.

Espero que hayas encontrado útil este artículo.

Comenzará desde lo básico y aprenderá de una manera interactiva y amigable para principiantes. También construirá cinco proyectos al final para poner en práctica y ayudar a reforzar lo que ha aprendido.

¡Gracias por leer y feliz codificación!

Fuente: https://www.freecodecamp.org/news/python-global-variables-examples/

#python 

Python Global Variables – How to Define a Global Variable Example

In this article, you will learn the basics of global variables.

To begin with, you will learn how to declare variables in Python and what the term 'variable scope' actually means.

Then, you will learn the differences between local and global variables and understand how to define global variables and how to use the global keyword.

What Are Variables in Python and How Do You Create Them? An Introduction for Beginners

You can think of variables as storage containers.

They are storage containers for holding data, information, and values that you would like to save in the computer's memory. You can then reference or even manipulate them at some point throughout the life of the program.

A variable has a symbolic name, and you can think of that name as the label on the storage container that acts as its identifier.

The variable name will be a reference and pointer to the data stored inside it. So, there is no need to remember the details of your data and information – you only need to reference the variable name that holds that data and information.

When giving a variable a name, make sure that it is descriptive of the data it holds. Variable names need to be clear and easily understandable both for your future self and the other developers you may be working with.

Now, let's see how to actually create a variable in Python.

When declaring variables in Python, you don't need to specify their data type.

For example, in the C programming language, you have to mention explicitly the type of data the variable will hold.

So, if you wanted to store your age which is an integer, or int type, this is what you would have to do in C:

#include <stdio.h>
 
int main(void)
{
  int age = 28;
  // 'int' is the data type
  // 'age' is the name 
  // 'age' is capable of holding integer values
  // positive/negative whole numbers or 0
  // '=' is the assignment operator
  // '28' is the value
}

However, this is how you would write the above in Python:

age = 28

#'age' is the variable name, or identifier
# '=' is the assignment operator
#'28' is the value assigned to the variable, so '28' is the value of 'age'

The variable name is always on the left-hand side, and the value you want to assign goes on the right-hand side after the assignment operator.

Keep in mind that you can change the values of variables throughout the life of a program:

my_age = 28

print(f"My age in 2022 is {my_age}.")

my_age = 29

print(f"My age in 2023 will be {my_age}.")

#output

#My age in 2022 is 28.
#My age in 2023 will be 29.

You keep the same variable name, my_age, but only change the value from 28 to 29.

What Does Variable Scope in Python Mean?

Variable scope refers to the parts and boundaries of a Python program where a variable is available, accessible, and visible.

There are four types of scope for Python variables, which are also known as the LEGB rule:

• Local,
• Enclosing,
• Global,
• Built-in.

For the rest of this article, you will focus on learning about creating variables with global scope, and you will understand the difference between the local and global variable scopes.

How to Create Variables With Local Scope in Python

Variables defined inside a function's body have local scope, which means they are accessible only within that particular function. In other words, they are 'local' to that function.

You can only access a local variable by calling the function.

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()


#output

#The best place to learn to code is with freeCodeCamp!

Look at what happens when I try to access that variable with a local scope from outside the function's body:

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#try to print local variable 'coding_website' from outside the function
print(coding_website)

#output

#NameError: name 'coding_website' is not defined

It raises a NameError because it is not 'visible' in the rest of the program. It is only 'visible' within the function where it was defined.

How to Create Variables With Global Scope in Python

When you define a variable outside a function, like at the top of the file, it has a global scope and it is known as a global variable.

A global variable is accessed from anywhere in the program.

You can use it inside a function's body, as well as access it from outside a function:

#create a global variable
coding_website = "freeCodeCamp"

def learn_to_code():
    #access the variable 'coding_website' inside the function
    print(f"The best place to learn to code is with {coding_website}!")

#call the function
learn_to_code()

#access the variable 'coding_website' from outside the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

What happens when there is a global and local variable, and they both have the same name?

#global variable
city = "Athens"

def travel_plans():
    #local variable with the same name as the global variable
    city = "London"
    print(f"I want to visit {city} next year!")

#call function - this will output the value of local variable
travel_plans()

#reference global variable - this will output the value of global variable
print(f"I want to visit {city} next year!")

#output

#I want to visit London next year!
#I want to visit Athens next year!

In the example above, maybe you were not expecting that specific output.

Maybe you thought that the value of city would change when I assigned it a different value inside the function.

Maybe you expected that when I referenced the global variable with the line print(f" I want to visit {city} next year!"), the output would be #I want to visit London next year! instead of #I want to visit Athens next year!.

However, when the function was called, it printed the value of the local variable.

Then, when I referenced the global variable outside the function, the value assigned to the global variable was printed.

They didn't interfere with one another.

That said, using the same variable name for global and local variables is not considered a best practice. Make sure that your variables don't have the same name, as you may get some confusing results when you run your program.

How to Use the global Keyword in Python

What if you have a global variable but want to change its value inside a function?

Look at what happens when I try to do that:

#global variable
city = "Athens"

def travel_plans():
    #First, this is like when I tried to access the global variable defined outside the function. 
    # This works fine on its own, as you saw earlier on.
    print(f"I want to visit {city} next year!")

    #However, when I then try to re-assign a different value to the global variable 'city' from inside the function,
    #after trying to print it,
    #it will throw an error
    city = "London"
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#output

#UnboundLocalError: local variable 'city' referenced before assignment

By default Python thinks you want to use a local variable inside a function.

So, when I first try to print the value of the variable and then re-assign a value to the variable I am trying to access, Python gets confused.

The way to change the value of a global variable inside a function is by using the global keyword:

#global variable
city = "Athens"

#print value of global variable
print(f"I want to visit {city} next year!")

def travel_plans():
    global city
    #print initial value of global variable
    print(f"I want to visit {city} next year!")
    #assign a different value to global variable from within function
    city = "London"
    #print new value
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#print value of global variable
print(f"I want to visit {city} next year!")

Use the global keyword before referencing it in the function, as you will get the following error: SyntaxError: name 'city' is used prior to global declaration.

Earlier, you saw that you couldn't access variables created inside functions since they have local scope.

The global keyword changes the visibility of variables declared inside functions.

def learn_to_code():
   global coding_website
   coding_website = "freeCodeCamp"
   print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()

#access variable from within the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

Conclusion

And there you have it! You now know the basics of global variables in Python and can tell the differences between local and global variables.

I hope you found this article useful.

You'll start from the basics and learn in an interactive and beginner-friendly way. You'll also build five projects at the end to put into practice and help reinforce what you've learned.

Thanks for reading and happy coding!

Source: https://www.freecodecamp.org/news/python-global-variables-examples/

#python 

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

• #57 Property Wrappers as Debugging Tools
• #56 Localization through String interpolation
• #55 Implementing pseudo-inheritance between structs
• #54 Composing NSAttributedString through a Function Builder
• #53 Using switch and if as expressions
• #52 Avoiding double negatives within guard statements
• #51 Defining a custom init without loosing the compiler-generated one
• #50 Implementing a namespace through an empty enum
• #49 Using Never to represent impossible code paths
• #48 Providing a default value to a Decodable enum
• #47 Another lightweight dependency injection through default values for function parameters
• #46 Lightweight dependency injection through protocol-oriented programming
• #45 Getting rid of overabundant [weak self] and guard
• #44 Solving callback hell with function composition
• #43 Transform an asynchronous function into a synchronous one
• #42 Using KeyPaths instead of closures
• #41 Bringing some type-safety to a userInfo Dictionary
• #40 Lightweight data-binding for an MVVM implementation
• #39 Using typealias to its fullest
• #38 Writing an interruptible overload of forEach
• #37 Optimizing the use of reduce()
• #36 Avoiding hardcoded reuse identifiers
• #35 Defining a union type
• #34 Asserting that classes have associated NIBs and vice-versa
• #33 Small footprint type-erasing with functions
• #32 Performing animations sequentially
• #31 Debouncing a function call
• #30 Providing useful operators for Optional booleans
• #29 Removing duplicate values from a Sequence
• #28 Shorter syntax to deal with optional strings
• #27 Encapsulating background computation and UI update
• #26 Retrieving all the necessary data to build a debug view
• #25 Defining a function to map over dictionaries
• #24 A shorter syntax to remove nil values
• #23 Dealing with expirable values
• #22 Using parallelism to speed-up map()
• #21 Measuring execution time with minimum boilerplate
• #20 Running two pieces of code in parallel
• #19 Making good use of #file, #line and #function
• #18 Comparing Optionals through Conditional Conformance
• #17 Safely subscripting a Collection
• #16 Easier String slicing using ranges
• #15 Concise syntax for sorting using a KeyPath
• #14 Manufacturing cache-efficient versions of pure functions
• #13 Simplifying complex condition with pattern matching
• #12 Easily generating arrays of data
• #11 Using @autoclosure for cleaner call sites
• #10 Observing new and old value with RxSwift
• #09 Implicit initialization from literal values
• #08 Achieving systematic validation of data
• #07 Implementing the builder pattern with keypaths
• #06 Storing functions rather than values
• #05 Defining operators on function types
• #04 Typealiases for functions
• #03 Encapsulating state within a function
• #02 Generating all cases for an Enum
• #01 Using map on optional values

Tips

---

Download Details:

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

License: MIT license
#swift 

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