En primer lugar, ¿qué es Python? Según su creador, Guido van Rossum, Python es un:
"El lenguaje de programación de alto nivel, y su filosofía de diseño central tiene que ver con la legibilidad del código y una sintaxis que permite a los programadores expresar conceptos en unas pocas líneas de código".Para mí, la primera razón para aprender Python fue que, de hecho, es una hermosalenguaje de programación. Fue muy natural codificarlo y expresar mis pensamientos.
Otra razón fue que podemos usar la codificación en Python de múltiples maneras: la ciencia de datos, el desarrollo web y el aprendizaje automático brillan aquí. Quora, Pinterest y Spotify usan Python para su desarrollo web backend. Así que aprendamos un poco al respecto.
Los basicos
1. Variables
Puede pensar en las variables como palabras que almacenan un valor. Simple como eso.
En Python, es muy fácil definir una variable y establecerle un valor. Imagina que quieres almacenar el número 1 en una variable llamada "uno". Vamos a hacerlo:
one = 1¿Qué tan simple fue eso? Acaba de asignar el valor 1 a la variable "uno".
two = 2 some_number = 10000Y puede asignar cualquier otro valor a cualquier otra variable que desee. Como puede ver en la tabla anterior, la variable " dos " almacena el número entero 2 y " algún_numero " almacena 10.000 .
Además de los enteros, también podemos usar valores booleanos (Verdadero / Falso), cadenas, flotantes y muchos otros tipos de datos.
# booleans true_boolean = True false_boolean = False # string my_name = "Leandro Tk" # float book_price = 15.802. Control de flujo: declaraciones condicionales
" Si " usa una expresión para evaluar si una declaración es verdadera o falsa. Si es Verdadero, ejecuta lo que está dentro de la declaración "si". Por ejemplo:
if True: print("Hello Python If") if 2 > 1: print("2 is greater than 1")2 es mayor que 1 , por lo que se ejecuta el código de " impresión ".
La instrucción " else " se ejecutará si la expresión " if " es falsa .
if 1 > 2: print("1 is greater than 2") else: print("1 is not greater than 2")1 no es mayor que 2 , por lo que se ejecutará el código dentro de la instrucción " else ".
También puede utilizar una declaración " elif ":
if 1 > 2: print("1 is greater than 2") elif 2 > 1: print("1 is not greater than 2") else: print("1 is equal to 2")3. Bucle / iterador
En Python, podemos iterar de diferentes formas. Hablaré de dos: mientrasy para .
Mientras se realiza un bucle: mientras la declaración sea verdadera, se ejecutará el código dentro del bloque. Entonces, este código imprimirá el número del 1 al 10 .
num = 1 while num <= 10: print(num) num += 1El tiempo de bucle necesita una “ condición de bucle. ”Si permanece True, continúa iterando. En este ejemplo, cuando numes igual a la condición11 del bucleFalse .
Otro código básico para entenderlo mejor:
loop_condition = True while loop_condition: print("Loop Condition keeps: %s" %(loop_condition)) loop_condition = FalseLa condición del bucle es Trueque sigue iterando, hasta que la establecemos en False.
For Looping : aplica la variable " num " al bloque, y la instrucción " for " lo repetirá por usted. Este código se imprimirá igual que el código while : de 1 a 10 .
for i in range(1, 11): print(i)¿Ver? Es tan simple. El rango comienza con 1y va hasta el 11elemento th ( 10es el 10elemento th).
Lista: Colección | Array | Estructura de datos
Imagina que quieres almacenar el entero 1 en una variable. Pero tal vez ahora quieras almacenar 2. Y 3, 4, 5…
¿Tengo otra forma de almacenar todos los enteros que quiero, pero no en millones de variables ? Lo has adivinado: de hecho, hay otra forma de almacenarlos.
List is a collection that can be used to store a list of values (like these integers that you want). So let’s use it:
my_integers = [1, 2, 3, 4, 5]It is really simple. We created an array and stored it on my_integer.
But maybe you are asking: “How can I get a value from this array?”
Great question. List has a concept called index. The first element gets the index 0 (zero). The second gets 1, and so on. You get the idea.
To make it clearer, we can represent the array and each element with its index. I can draw it:
Using the Python syntax, it’s also simple to understand:
my_integers = [5, 7, 1, 3, 4] print(my_integers[0]) # 5 print(my_integers[1]) # 7 print(my_integers[4]) # 4Imagine that you don’t want to store integers. You just want to store strings, like a list of your relatives’ names. Mine would look something like this:
relatives_names = [ "Toshiaki", "Juliana", "Yuji", "Bruno", "Kaio" ] print(relatives_names[4]) # KaioIt works the same way as integers. Nice.
We just learned how Lists indices work. But I still need to show you how we can add an element to the List data structure (an item to a list).
The most common method to add a new value to a List is append. Let’s see how it works:
bookshelf = [] bookshelf.append("The Effective Engineer") bookshelf.append("The 4 Hour Work Week") print(bookshelf[0]) # The Effective Engineer print(bookshelf[1]) # The 4 Hour Work Weekappend is super simple. You just need to apply the element (eg. “The Effective Engineer”) as the append parameter.
Well, enough about Lists. Let’s talk about another data structure.
Dictionary: Key-Value Data Structure
Now we know that Lists are indexed with integer numbers. But what if we don’t want to use integer numbers as indices? Some data structures that we can use are numeric, string, or other types of indices.
Let’s learn about the Dictionary data structure. Dictionary is a collection of key-value pairs. Here’s what it looks like:
dictionary_example = { "key1": "value1", "key2": "value2", "key3": "value3" }The key is the index pointing to thevalue. How do we access the Dictionaryvalue? You guessed it — using the key. Let’s try it:
dictionary_tk = { "name": "Leandro", "nickname": "Tk", "nationality": "Brazilian" } print("My name is %s" %(dictionary_tk["name"])) # My name is Leandro print("But you can call me %s" %(dictionary_tk["nickname"])) # But you can call me Tk print("And by the way I'm %s" %(dictionary_tk["nationality"])) # And by the way I'm BrazilianI created a Dictionary about me. My name, nickname, and nationality. Those attributes are the Dictionarykeys.
As we learned how to access the List using index, we also use indices (keys in the Dictionary context) to access the value stored in the Dictionary.
In the example, I printed a phrase about me using all the values stored in the Dictionary. Pretty simple, right?
Another cool thing about Dictionary is that we can use anything as the value. In the DictionaryI created, I want to add the key “age” and my real integer age in it:
dictionary_tk = { "name": "Leandro", "nickname": "Tk", "nationality": "Brazilian", "age": 24 } print("My name is %s" %(dictionary_tk["name"])) # My name is Leandro print("But you can call me %s" %(dictionary_tk["nickname"])) # But you can call me Tk print("And by the way I'm %i and %s" %(dictionary_tk["age"], dictionary_tk["nationality"])) # And by the way I'm BrazilianHere we have a key (age) value (24) pair using string as the key and integer as the value.
As we did with Lists, let’s learn how to add elements to a Dictionary. The keypointing to avalue is a big part of what Dictionary is. This is also true when we are talking about adding elements to it:
dictionary_tk = { "name": "Leandro", "nickname": "Tk", "nationality": "Brazilian" } dictionary_tk['age'] = 24 print(dictionary_tk) # {'nationality': 'Brazilian', 'age': 24, 'nickname': 'Tk', 'name': 'Leandro'} We just need to assign a value to a Dictionarykey. Nothing complicated here, right?
Iteration: Looping Through Data Structures
As we learned in the Python Basics, the List iteration is very simple. We Pythondevelopers commonly use For looping. Let’s do it:
bookshelf = [ "The Effective Engineer", "The 4-hour Workweek", "Zero to One", "Lean Startup", "Hooked" ] for book in bookshelf: print(book)So for each book in the bookshelf, we (can do everything with it) print it. Pretty simple and intuitive. That’s Python.
For a hash data structure, we can also use the for loop, but we apply the key :
dictionary = { "some_key": "some_value" } for key in dictionary: print("%s --> %s" %(key, dictionary[key])) # some_key --> some_valueThis is an example how to use it. For each key in the dictionary , we print the key and its corresponding value.
Another way to do it is to use the iteritems method.
dictionary = { "some_key": "some_value" } for key, value in dictionary.items(): print("%s --> %s" %(key, value)) # some_key --> some_valueWe did name the two parameters as key and value, but it is not necessary. We can name them anything. Let’s see it:
dictionary_tk = { "name": "Leandro", "nickname": "Tk", "nationality": "Brazilian", "age": 24 } for attribute, value in dictionary_tk.items(): print("My %s is %s" %(attribute, value)) # My name is Leandro # My nickname is Tk # My nationality is Brazilian # My age is 24We can see we used attribute as a parameter for the Dictionarykey, and it works properly. Great!
Classes & Objects
A little bit of theory:
Objects are a representation of real world objects like cars, dogs, or bikes. The objects share two main characteristics: data and behavior.
Cars have data, like number of wheels, number of doors, and seating capacity They also exhibit behavior: they can accelerate, stop, show how much fuel is left, and so many other things.
We identify data as attributes and behavior as methods in object-oriented programming. Again:
Data → Attributes and Behavior → Methods
And a Class is the blueprint from which individual objects are created. In the real world, we often find many objects with the same type. Like cars. All the same make and model (and all have an engine, wheels, doors, and so on). Each car was built from the same set of blueprints and has the same components.
Python Object-Oriented Programming mode: ON
Python, as an Object-Oriented programming language, has these concepts: class and object.
A class is a blueprint, a model for its objects.
So again, a class it is just a model, or a way to define attributes and behavior (as we talked about in the theory section). As an example, a vehicle class has its own attributes that define what objects are vehicles. The number of wheels, type of tank, seating capacity, and maximum velocity are all attributes of a vehicle.
With this in mind, let’s look at Python syntax for classes:
class Vehicle: passWe define classes with a class statement — and that’s it. Easy, isn’t it?
Objects are instances of a class. We create an instance by naming the class.
car = Vehicle() print(car) # Here car is an object (or instance) of the classVehicle.
Remember that our vehicle class has four attributes: number of wheels, type of tank, seating capacity, and maximum velocity. We set all these attributes when creating a vehicle object. So here, we define our class to receive data when it initiates it:
class Vehicle: def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity): self.number_of_wheels = number_of_wheels self.type_of_tank = type_of_tank self.seating_capacity = seating_capacity self.maximum_velocity = maximum_velocityWe use the initmethod. We call it a constructor method. So when we create the vehicle object, we can define these attributes. Imagine that we love the Tesla Model S, and we want to create this kind of object. It has four wheels, runs on electric energy, has space for five seats, and the maximum velocity is 250km/hour (155 mph). Let’s create this object:
tesla_model_s = Vehicle(4, 'electric', 5, 250)Four wheels + electric “tank type” + five seats + 250km/hour maximum speed.
All attributes are set. But how can we access these attributes’ values? We send a message to the object asking about them. We call it a method. It’s the object’s behavior. Let’s implement it:
class Vehicle: def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity): self.number_of_wheels = number_of_wheels self.type_of_tank = type_of_tank self.seating_capacity = seating_capacity self.maximum_velocity = maximum_velocity def number_of_wheels(self): return self.number_of_wheels def set_number_of_wheels(self, number): self.number_of_wheels = numberThis is an implementation of two methods: number_of_wheels and set_number_of_wheels. We call it getter & setter. Because the first gets the attribute value, and the second sets a new value for the attribute.
In Python, we can do that using @property (decorators) to define getters and setters. Let’s see it with code:
class Vehicle: def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity): self.number_of_wheels = number_of_wheels self.type_of_tank = type_of_tank self.seating_capacity = seating_capacity self.maximum_velocity = maximum_velocity @property def number_of_wheels(self): return self.__number_of_wheels @number_of_wheels.setter def number_of_wheels(self, number): self.__number_of_wheels = numberAnd we can use these methods as attributes:
tesla_model_s = Vehicle(4, 'electric', 5, 250) print(tesla_model_s.number_of_wheels) # 4 tesla_model_s.number_of_wheels = 2 # setting number of wheels to 2 print(tesla_model_s.number_of_wheels) # 2This is slightly different than defining methods. The methods work as attributes. For example, when we set the new number of wheels, we don’t apply two as a parameter, but set the value 2 to number_of_wheels. This is one way to write pythonicgetter and setter code.
But we can also use methods for other things, like the “make_noise” method. Let’s see it:
class Vehicle: def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity): self.number_of_wheels = number_of_wheels self.type_of_tank = type_of_tank self.seating_capacity = seating_capacity self.maximum_velocity = maximum_velocity def make_noise(self): print('VRUUUUUUUM')Cuando llamamos a este método, simplemente devuelve una cadena “ VRRRRUUUUM. "
tesla_model_s = Vehicle(4, 'electric', 5, 250) tesla_model_s.make_noise() # VRUUUUUUUMEncapsulación: Ocultar información
La encapsulación es un mecanismo que restringe el acceso directo a los datos y métodos de los objetos. Pero al mismo tiempo, facilita la operación sobre esos datos (métodos de objetos).
“La encapsulación se puede utilizar para ocultar los miembros de datos y la función de los miembros. Según esta definición, encapsulación significa que la representación interna de un objeto generalmente está oculta a la vista fuera de la definición del objeto ". - WikipediaToda representación interna de un objeto está oculta al exterior. Solo el objeto puede interactuar con sus datos internos.
En primer lugar, tenemos que entender cómo publicy non-publicde instancia de variables y métodos de trabajo.
Variables de instancia pública
For a Python class, we can initialize a public instance variable within our constructor method. Let’s see this:
Within the constructor method:
class Person: def __init__(self, first_name): self.first_name = first_nameHere we apply the first_name value as an argument to the public instance variable.
tk = Person('TK') print(tk.first_name) # => TKWithin the class:
class Person: first_name = 'TK'Here, we do not need to apply the first_name as an argument, and all instance objects will have a class attribute initialized with TK.
tk = Person() print(tk.first_name) # => TKCool. We have now learned that we can use public instance variables and class attributes. Another interesting thing about the public part is that we can manage the variable value. What do I mean by that? Our object can manage its variable value: Get and Set variable values.
Keeping the Person class in mind, we want to set another value to its first_name variable:
tk = Person('TK') tk.first_name = 'Kaio' print(tk.first_name) # => KaioAquí vamos. Simplemente establecemos otro valor ( kaio) para la first_namevariable de instancia y actualiza el valor. Simple como eso. Como es una publicvariable, podemos hacer eso.
Variable de instancia no pública
No usamos el término "privado" aquí, ya que ningún atributo es realmente privado en Python (sin una cantidad de trabajo generalmente innecesaria). - PEP 8Como el public instance variable, podemos definir non-public instance variableambos dentro del método constructor o dentro de la clase. La diferencia de sintaxis es: para non-public instance variables, use un guión bajo ( _) antes del variablenombre.
_spam. Ej.
) Debe tratarse como una parte no pública de la API (ya sea una función, un método o un miembro de datos) " - Fundación de software Python
He aquí un ejemplo:
class Person: def __init__(self, first_name, email): self.first_name = first_name self._email = email¿Viste la emailvariable? Así es como definimos a non-public variable:
tk = Person('TK', '[email protected]') print(tk._email) # [email protected]Non-public variablesson solo una convención y deben tratarse como una parte no pública de la API.
Entonces usamos un método que nos permite hacerlo dentro de nuestra definición de clase. Implementemos dos métodos ( emaily update_email) para entenderlo:
class Person: def __init__(self, first_name, email): self.first_name = first_name self._email = email def update_email(self, new_email): self._email = new_email def email(self): return self._emailAhora podemos actualizar y acceder non-public variablesusando esos métodos. Veamos:
tk = Person('TK', '[email protected]') print(tk.email()) # => [email protected] # tk._email = '[email protected]' -- treat as a non-public part of the class API print(tk.email()) # => [email protected] tk.update_email('[email protected]') print(tk.email()) # => [email protected]- We initiated a new object with
first_nameTK andemail[email protected] - Printed the email by accessing the
non-public variablewith a method - Tried to set a new
emailout of our class - We need to treat
non-public variableasnon-publicpart of the API - Updated the
non-public variablewith our instance method - Success! We can update it inside our class with the helper method
Public Method
With public methods, we can also use them out of our class:
class Person: def __init__(self, first_name, age): self.first_name = first_name self._age = age def show_age(self): return self._ageLet’s test it:
tk = Person('TK', 25) print(tk.show_age()) # => 25Great — we can use it without any problem.
Non-public Method
But with non-public methods we aren’t able to do it. Let’s implement the same Person class, but now with a show_agenon-public method using an underscore (_).
class Person: def __init__(self, first_name, age): self.first_name = first_name self._age = age def _show_age(self): return self._ageAnd now, we’ll try to call this non-public method with our object:
tk = Person('TK', 25) print(tk._show_age()) # => 25Non-public methodsson solo una convención y deben tratarse como una parte no pública de la API.
Aquí hay un ejemplo de cómo podemos usarlo:
class Person: def __init__(self, first_name, age): self.first_name = first_name self._age = age def show_age(self): return self._get_age() def _get_age(self): return self._age tk = Person('TK', 25) print(tk.show_age()) # => 25Aquí tenemos una _get_agenon-public methody una show_agepublic method. El show_agepuede ser usado por nuestro objeto (fuera de nuestra clase) y el _get_ageúnico usado dentro de nuestra definición de clase ( show_agemétodo interno ). Pero de nuevo: como una cuestión de convención.
Resumen de encapsulación
Con el encapsulado podemos asegurarnos de que la representación interna del objeto quede oculta al exterior.
Herencia: comportamientos y características
Ciertos objetos tienen algunas cosas en común: su comportamiento y características.
Por ejemplo, heredé algunas características y comportamientos de mi padre. Heredé sus ojos y cabello como características, y su impaciencia e introversión como comportamientos.
In object-oriented programming, classes can inherit common characteristics (data) and behavior (methods) from another class.
Let’s see another example and implement it in Python.
Imagine a car. Number of wheels, seating capacity and maximum velocity are all attributes of a car. We can say that anElectricCar class inherits these same attributes from the regular Car class.
class Car: def __init__(self, number_of_wheels, seating_capacity, maximum_velocity): self.number_of_wheels = number_of_wheels self.seating_capacity = seating_capacity self.maximum_velocity = maximum_velocityOur Car class implemented:
my_car = Car(4, 5, 250) print(my_car.number_of_wheels) print(my_car.seating_capacity) print(my_car.maximum_velocity)Once initiated, we can use all instance variables created. Nice.
In Python, we apply a parent class to the child class as a parameter. An ElectricCar class can inherit from our Car class.
class ElectricCar(Car): def __init__(self, number_of_wheels, seating_capacity, maximum_velocity): Car.__init__(self, number_of_wheels, seating_capacity, maximum_velocity)Simple as that. We don’t need to implement any other method, because this class already has it (inherited from Car class). Let’s prove it:
my_electric_car = ElectricCar(4, 5, 250) print(my_electric_car.number_of_wheels) # => 4 print(my_electric_car.seating_capacity) # => 5 print(my_electric_car.maximum_velocity) # => 250Beautiful.
That’s it!
We learned a lot of things about Python basics:
- How Python variables work
- How Python conditional statements work
- How Python looping (while & for) works
- How to use Lists: Collection | Array
- Dictionary Key-Value Collection
- How we can iterate through these data structures
- Objects and Classes
- Attributes as objects’ data
- Methods as objects’ behavior
- Using Python getters and setters & property decorator
- Encapsulation: hiding information
- Inheritance: behaviors and characteristics
Congrats! You completed this dense piece of content about Python.
If you want a complete Python course, learn more real-world coding skills and build projects, try One Month Python Bootcamp. See you there ☺
For more stories and posts about my journey learning & mastering programming, follow my publication The Renaissance Developer.
Have fun, keep learning, and always keep coding.
My Twitter & Github. ☺