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Init Function In Python | Types Of __Init__ Constructor

What does Python's __init__ method do?

Examples of using the method __init__ on different types of objects in Python

The method

__init__

is a special method in Python that is called automatically when we create an object. This way, the method can be used to initialize the object and assign values to its attributes. Here are some examples of how the init method can be used on different types of objects in Python:

Simple class objects:

We have a basic example of creating a Python class called “Person”. The class has a special method called “ init ” which is being called when we create an object of the class. This way, the method receives two arguments, “name” and “age”, which can be assigned to the attributes “name” and “age” of the Person object. In the end, we create a Person object receiving “Maria” and age of 25 and its attributes will be displayed in the console. Look:


class Person: def __init__(self, name, age): self.name = name self.age = age Person1 = Person("Maria", 25) print(Person1.name) # "Maria" print(Person1.age) # 25

Objects of more complex classes:

The class defines a constructor ( init ) to define the attributes of the class, which in this case are: make, model, year and price of the car. Next, we create an object of type “Car” and assign it the name “car1”. Finally, the attribute values of the object “car1” can be displayed in the console using the syntax “car1.attribute”, where the desired attribute name assumes “attribute”. Look:


class Car: def __init__(self, brand, model, ano, preco): self.brand = brand self.model = model self.year = year self.price = price car1 = Car("Ford", "Fiesta", 2015, 15000) print(car1.brand) # "Ford" print(car1.model) # "Fiesta" print(car1.year) # 2015 print(car1.price) # 15000

List objects:

Now we have an example that creates a list of three elements: “Maria”, 25 and “Sao Paulo”. It then uses a loop

for

to iterate over each element in the list and prints out each element. The syntax

for elemento in lista

means that the variable

elemento

will be updated on each iteration of the for loop , matching each element in the list. Thus, the loop prints each value of

elemento

using the function

print()


list1 = ["Maria", 25, "Sao Paulo"] for element in list1: print(element) # Output: # Maria # 25 # Sao Paulo

Dictionary objects:

This example creates a Python dictionary with three keys and associated values: “name” with the value “Maria”, “age” with the value 25, and “city” with the value “São Paulo”. In this way, a loop

for

is used to iterate over the dictionary items, which are the associated keys and values. The syntax means that the variable will be updated on each iteration, matching the dictionary key, and the variable will be updated with the corresponding key value. The loop prints each key and value using the . The output of this example will be “name”, “25” and “city”.

for chave, valor in dicionario1.items() chavevalor print()


dictionary1 = {"name": "Maria", "age": 25, "city": "Sao Paulo"} for key, value in dictionary1.items(): print(key) # "nome" print(value) # 25 # Output: # nome # 25 # cidade

Custom class objects:

And finally, we have the following example creating an “Animal” class that has a constructor to define the name and age of the animal.

The class also has a “speak” method that displays the animal’s name. Next, we create the “Dog” class, which inherits the attributes and methods of the “Animal” class. The constructor of the “Dog” class adds a new attribute, “raza”, and calls the constructor of the “Animal” class. We created the “dog1” object as an instance of the “Dog” class and the “talk” method is being called. The “speak” method displays the name of the animal, which in this case is “Fido”. The output of this example will be “The animal says: Fido”. Look:


class Animal: def __init__(self, name, age): self.name = name self.age = age def speak(self): print("The animal says:") print(self.name) class dog(Animal): def __init__(self, name, age, raza): super().__init__(name, age) self.raza = raza dog1 = dog("Fido", 3, "Labrador") dog.falar() # Output: # The animal says: # Fido

These are just a few examples of how the init method can be used to initialize objects in Python. In this sense, the method is a fundamental part of object-oriented programming and can be used in many classes to define the attributes and methods of an object.

The __init__() Function

The examples above are classes and objects in their simplest form, and are not really useful in real life applications.

To understand the meaning of classes we have to understand the built-in __init__() function.

All classes have a function called __init__(), which is always executed when the class is being initiated.

Use the __init__() function to assign values to object properties, or other operations that are necessary to do when the object is being created:

Example

Create a class named Person, use the __init__() function to assign values for name and age:

def __init__(self, name, age):

self.name = name

self.age = age

p1 = Person(“John”, 36)

print(p1.name)

print(p1.age)

Note: The

__init__()

function is called automatically every time the class is being used to create a new object.

init python: Learn how to use __init__ to initialize objects in python

Python init method is a special function that we can apply to initialize a class. When we create an object of the class, the method is automatically applied and defines the object’s initial behavior. In this sense, we can use the class object as a pointer to the object being initialized, accessing the class’s attributes and methods, and performing any other operations necessary to initialize the object.In this article, we’ll explore the method __init__ in Python. Thus, learning about how we can use it to initialize classes, including what it is and how it can be applied to maintain data integrity. We’ll discuss how to create a method __init__ and the syntax needed to make it work. In addition, also learn about how to add elements efficiently and use both knowledge to improve your code.

Table of Contents

What does Python's __init__ method do?
What does Python’s __init__ method do?

Python __new__ and __init__ Examples

To better understand the differences between

__new__

and

__init__

, let’s take a look at a simple example:


class Person: def __new__(cls, name, age): print("Creating a new Person object") instance = super().__new__(cls) return instance def __init__(self, name, age): print("Initializing the Person object") self.name = name self.age = age person = Person("John Doe", 30) print(f"Person's name: {person.name}, age: {person.age}") # Creating a new Person object # Initializing the Person object # Person's name: John Doe, age: 30

In this example, we can see how the

__new__

method is called before the

__init__

method, and how they work together to create and initialize the

Person

object.

The INIT function

The INIT function initializes the data structures required by the rest of the computation of the aggregate. For example, if you write a C function, the INIT function can set up large objects or temporary files for storing intermediate results. The INIT function returns the initial result of the aggregate, which is of the state type.

The INIT function can take one or two arguments. The first argument must be the same type as the column that is aggregated. The database server uses the type of the first argument to resolve overloaded INIT functions.

For C and Java™, the first argument of the INIT function is a placeholder argument and always has a null value. Therefore, all functions that serve as INIT functions must be defined with the HANDLESNULLS modifier.

Python __init__() Function

How the __init__ method can be used to implement inheritance in Python

The method

__init__

can is being used to implement inheritance in Python, which is a way of creating classes that inherit behaviors and attributes from other classes. This is done by creating a new class that inherits from an existing class by using the keyword

class

followed by the name of the new class and the name of the base class in quotes.

You can then define the attributes and methods of the new class within the base class using the method to initialize the attributes of the new class. Also, you can override base class methods by using the keyword

def

to provide new implementations for those methods in the new class.

For example, suppose you want to create an automobile class that inherits from a vehicle class. So we can do it like this:


class Car(Vehicle): def __init__(self, make, model, year): Vehicle.__init__(self, make, model, year) self.number_of_doors = 4 self.color = "red" def start(self): print("Starting the engine...")

Here, the class

Car

inherits from the class

Vehicle

and defines a new attribute

number_of_doors

and a new method

start()

that overrides the method

start()

of the class

Vehicle

.

Thus, we are using the new class

Car

to create car objects that inherit behaviors and attributes from the class

Vehicle

and add new behaviors and attributes specific to cars.

#50 Python Tutorial for Beginners | __init__ method
#50 Python Tutorial for Beginners | __init__ method

How Does __init__() Method Work?

The python __init__ method is declared within a class and is used to initialize the attributes of an object as soon as the object is formed. While giving the definition for an __init__(self) method, a default parameter, named ‘self’ is always passed in its argument. This self represents the object of the class itself. Like in any other method of a class, in case of __init__ also ‘self’ is used as a dummy object variable for assigning values to the data members of an object.

The __init__ method is often referred to as double underscores init or dunder init for it has two underscores on each side of its name. These double underscores on both the sides of init imply that the method is invoked and used internally in Python, without being required to be called explicitly by the object.

This python __init__ method may or may not take arguments for object initialisation. You can also pass default arguments in its parameter. However, even though there is no such concept of Constructor Overloading in Python, one can still achieve polymorphism in the case of constructors in Python on the basis of its argument.

Also Read: Set in Python – How to Create a Set in Python?

Parameters in init in Python

It can take any number of arguments in it while the first parameter that will be passed in it will always be self.

Code:

Output:

Explanation:

In the above example, a class Trip is created, and an object ‘T’ is created to invoke the methods and attributes. As soon as the object is created, the__init__ method is initialized with values India and London, which are assigned to to_city and from_city, respectively. The self keyword represents the current instance of the object. So when the holiday() method is run, it prints out the values of from_city and to_city, which are London and India, respectively.

Python 3's __init__(), self, Class and Instance Objects Explained Concisely
Python 3’s __init__(), self, Class and Instance Objects Explained Concisely

Init in Python: Syntax and Examples

We can declare a __init__ method inside a class in Python using the following syntax:

class class_name(): def __init__(self): # Required initialisation for data members # Class methods … …

Let’s take an example of a class named Teacher in Python and understand the working of __init__() method through it better.


class Teacher: # definition for init method or constructor def __init__(self, name, subject): self.name = name self.subject = subject # Random member function def show(self): print(self.name, " teaches ", self.subject) T = Teacher('Preeti Srivastava', "Computer Science") # init is invoked here T.show()

Now, for the scenarios where you are required to achieve polymorphism through __init__() method, you can go with the following syntax.

class class_name(): def __init__(self, *args): Condition 1 for *args: # Required initialisation for data members Condition 2 for *args: # Required initialisation for data members ……… ……… # Class methods … …

In this case, the type of argument passed in place of *args decide what kind of initialisation has to be followed. Take a look at the example given below to get some more clarity on this.


class Teacher: def __init__(self, *args): # Naming the teacher when a single string is passed if len(args)==1 & isinstance(args[0], str): self.name = args[0] # Naming the teacher as well as the subject elif len(args)==2: self.name = args[0] self.sub = args[1] # Storing the strength of the class in case of a single int argument elif isinstance(args[0], int): self.strength = args[0] t1 = Teacher("Preeti Srivastava") print('Name of the teacher is ', t1.name) t2 = Teacher("Preeti Srivastava", "Computer Science") print(t2.name, ' teaches ', t2.sub) t3 = Teacher(32) print("Strength of the class is ", t3.strength)

Types of __init__ Constructor

There are mainly three types of Python __init__ constructors:

  1. Default __init__ constructor
  2. Parameterised __init__ Constructor
  3. __init__ With Default Parameters

The Default __init__ Constructor

The default __init__ constructor in Python is the constructor that does not accept any parameters, except for the ‘self’ parameter. The ‘self’ is a reference object for that class. The syntax for defining a default __init__ constructor is as follows:

class class_name(): def __init__(self): # Constructor statements # other class methods … …

The syntax for creating an object for a class with a default __init__ constructor is as follows:

Object_name = class_name()

Example:


class Default(): #defining default constructor def __init__(self): self.var1 = 56 self.var2 = 27 #class function for addition def add(self): print("Sum is ", self.var1 + self.var2) obj = Default() # since default constructor doesn’t take any argument obj.add()

Parameterised __init__ Constructor

When we want to pass arguments in the constructor of a class, we make use of the parameterised __init__ method. It accepts one or more than one argument other than the self. The syntax followed while defining a parameterised __init__ constructor has been given below:

class class_name(): def __init__(self, arg1, arg2, arg3, …): self.data_member1 = arg1 self.data_member2 = arg2 self.data_member2 = arg2 …… …… # other class methods … …

We declare an instance for a class with a parameterised constructor using the following syntax:

Object_name = class_name(arg1, arg2, arg3,…)

Example:


class Default(): #defining parameterised constructor def __init__(self, n1, n2): self.var1 = n1 self.var2 = n2 #class function for addition def add(self): print("Sum is ", self.var1 + self.var2) obj = Default(121, 136) #Creating object for a class with parameterised init obj.add()

The __init__ method with default parameters

As you might already know, we can pass default arguments to a member function or a constructor, be it any popular programming language. In the very same way, Python also allows us to define a __init__ method with default parameters inside a class. We use the following syntax to pass a default argument in an __init__ method within a class.

class ClassName: def __init__(self, *list of default arguments*): # Required Initialisations # Other member functions …… …….

Now, go through the following example to understand how the __init__ method with default parameters works.


class Teacher: # definition for init method or constructor with default argument def __init__(self, name = "Preeti Srivastava"): self.name = name # Random member function def show(self): print(self.name, " is the name of the teacher.") t1 = Teacher() #name is initialised with the default value of the argument t2 = Teacher('Chhavi Pathak') #name is initialised with the passed value of the argument t1.show() t2.show()

Python 3 Tutorial for Beginners #17 - The init function
Python 3 Tutorial for Beginners #17 – The init function

What Is Object-Oriented Programming?

Object-oriented programming (OOP) is a programming pattern that consists in defining objects and interacting with them. An object is a collection of complex variables and functions and can be used to represent real entities like a button, an airplane, or a person.

To declare, initialize, and manipulate objects in Python, we use classes. They serve as templates from which objects are created. The following diagram illustrates this idea:

We can see in the above diagram that the dog class contains specific dog characteristics, such as breed and eye color, as well as the abilities to run and walk. Let’s start by defining a class in Python.

What Is a Class?

A class defines and structures all of the objects that are created from it. You can view the class as an object factory. Let’s take the example of a fox terrier—a breed of dog. From an OOP standpoint, you can think of

dog

as a class that includes a dog’s characteristics such as its breed, or eye color. Since a Fox Terrier is a dog, we can create a dog object that will inherit the characteristics of its class. Classes use methods and constructors to create and define objects.

User-Defined And Special Methods

Methods are functions within a class that are designed to perform a specific task. Python differentiates between user-defined methods, written by the programmer, and special methods that are built into the language. A user-defined method is a function created by the programmer to serve a specific purpose. For instance, a

dog

class could have a

walk()

method that the dog object can use. The programmer creates this method and has it perform specific actions.

Special methods are identified by a double underscore at either side of their name, such as

__init__

. Python uses special methods to enhance the functionality of classes. Most of them work in the background and are called automatically when needed by the program. You cannot call them explicitly. For instance, when you create a new object, Python automatically calls the

__new__

method, which in turn calls the

__init__

method. The

__str__

method is called when you

print()

an object. On the other hand, user-defined methods, like

stefi.run()

, are called explicitly.

The Constructor

A constructor is a special method that the program calls upon an object’s creation. The constructor is used in the class to initialize data members to the object. With our

dog

class example, you can use a constructor to assign dog characteristics to each

Fox Terrier

object. The special method

__init__

is the Python constructor.

With an understanding of object oriented programming and classes, let’s now look at how the

__init__

method works within a Python program.

The Importance of Objects in Python

We don’t always see it when we write a program, but objects are central to the way Python works. When we declare a simple variable in Python, an object is created in the background.If we execute the following bit of code:

breed = “Doberman”

Python uses the str class that contains properties and methods, exactly like the ones you create in your own code, except it’s all happening in the background.

6.More on Modules¶

A module can contain executable statements as well as function definitions. These statements are intended to initialize the module. They are executed only the first time the module name is encountered in an import statement. [1] (They are also run if the file is executed as a script.)

Each module has its own private namespace, which is used as the global namespace
by all functions defined in the module. Thus, the author of a module can
use global variables in the module without worrying about accidental clashes
with a user’s global variables. On the other hand, if you know what you are
doing you can touch a module’s global variables with the same notation used to
refer to its functions,

modname.itemname

.

Modules can import other modules. It is customary but not required to place all

import

statements at the beginning of a module (or script, for that
matter). The imported module names, if placed at the top level of a module
(outside any functions or classes), are added to the module’s global namespace.

There is a variant of the

import

statement that imports names from a
module directly into the importing module’s namespace. For example:

>>> from fibo import fib, fib2 >>> fib(500) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377

This does not introduce the module name from which the imports are taken in the
local namespace (so in the example,

fibo

is not defined).

There is even a variant to import all names that a module defines:

>>> from fibo import * >>> fib(500) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377

This imports all names except those beginning with an underscore ().
In most cases Python programmers do not use this facility since it introduces
an unknown set of names into the interpreter, possibly hiding some things
you have already defined.

Note that in general the practice of importing from a module or package is
frowned upon, since it often causes poorly readable code. However, it is okay to
use it to save typing in interactive sessions.

If the module name is followed by

as

, then the name
following

as

is bound directly to the imported module.

>>> import fibo as fib >>> fib.fib(500) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377

This is effectively importing the module in the same way that

import fibo

will do, with the only difference of it being available as

fib

.

It can also be used when utilising

from

with similar effects:

>>> from fibo import fib as fibonacci >>> fibonacci(500) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377

Note

For efficiency reasons, each module is only imported once per interpreter
session. Therefore, if you change your modules, you must restart the
interpreter – or, if it’s just one module you want to test interactively,
use

importlib.reload()

, e.g.

import importlib;
importlib.reload(modulename)

.

6.1.Executing modules as scripts¶

When you run a Python module with

python fibo.py

the code in the module will be executed, just as if you imported it, but with
the

__name__

set to

"__main__"

. That means that by adding this code at
the end of your module:

if __name__ == “__main__”: import sys fib(int(sys.argv[1]))

you can make the file usable as a script as well as an importable module, because the code that parses the command line only runs if the module is executed as the “main” file:

$ python fibo.py 50 0 1 1 2 3 5 8 13 21 34

If the module is imported, the code is not run:

>>> import fibo >>>

This is often used either to provide a convenient user interface to a module, or for testing purposes (running the module as a script executes a test suite).

6.1.The Module Search Path¶

When a module named

spam

is imported, the interpreter first searches for
a built-in module with that name. These module names are listed in

sys.builtin_module_names

. If not found, it then searches for a file
named

spam.py

in a list of directories given by the variable

sys.path

.

sys.path

is initialized from these locations:

  • The directory containing the input script (or the current directory when no file is specified).


  • PYTHONPATH

    (a list of directory names, with the same syntax as the shell variable

    PATH

    ).
  • The installation-dependent default (by convention including a


    site-packages

    directory, handled by the

    site

    module).

More details are at The initialization of the sys.path module search path.

Note

On file systems which support symlinks, the directory containing the input script is calculated after the symlink is followed. In other words the directory containing the symlink is not added to the module search path.

After initialization, Python programs can modify

sys.path

. The
directory containing the script being run is placed at the beginning of the
search path, ahead of the standard library path. This means that scripts in that
directory will be loaded instead of modules of the same name in the library
directory. This is an error unless the replacement is intended. See section
Standard Modules for more information.

6.1.“Compiled” Python files¶

To speed up loading modules, Python caches the compiled version of each module
in the

__pycache__

directory under the name

module.version.pyc

,
where the version encodes the format of the compiled file; it generally contains
the Python version number. For example, in CPython release 3.3 the compiled
version of spam.py would be cached as

__pycache__/spam.cpython-33.pyc

. This
naming convention allows compiled modules from different releases and different
versions of Python to coexist.

Python checks the modification date of the source against the compiled version to see if it’s out of date and needs to be recompiled. This is a completely automatic process. Also, the compiled modules are platform-independent, so the same library can be shared among systems with different architectures.

Python does not check the cache in two circumstances. First, it always recompiles and does not store the result for the module that’s loaded directly from the command line. Second, it does not check the cache if there is no source module. To support a non-source (compiled only) distribution, the compiled module must be in the source directory, and there must not be a source module.

Some tips for experts:

  • You can use the


    -O

    or

    -OO

    switches on the Python command to reduce the size of a compiled module. The

    -O

    switch removes assert statements, the

    -OO

    switch removes both assert statements and __doc__ strings. Since some programs may rely on having these available, you should only use this option if you know what you’re doing. “Optimized” modules have an

    opt-

    tag and are usually smaller. Future releases may change the effects of optimization.

  • A program doesn’t run any faster when it is read from a


    .pyc

    file than when it is read from a

    .py

    file; the only thing that’s faster about

    .pyc

    files is the speed with which they are loaded.

  • The module


    compileall

    can create .pyc files for all modules in a directory.

  • There is more detail on this process, including a flow chart of the decisions, in PEP 3147.

Self and __init__() method in Python | Python Tutorials for Beginners #lec86
Self and __init__() method in Python | Python Tutorials for Beginners #lec86

Examples of init in Python

The Default init Constructor

Here is an example of a class Car that will clarify the functioning of __init__().

Code:

Output:

Explanation:

You can see in the output the order of print statements that __init__ is called first.

init with inheritance

Inheritance is a fundamental concept in OOPs. it is the way by which a class inherits the properties of another class. Here, the first class are called the base class or parent class, and the second class is called the derived class or children class.

The derived class can access the properties and methods of their parent class. In other words, the child class inherits all the methods and properties of their parent class and can add more methods and properties that are unique to them(child class) only. Inside a child class, __init__() of the parent class can be called to create objects and assign values. Here is an example:

Code:

Output:

Explanation:

In the above example, when the object of the Child class is created, __init__() of the Child class is called, which first calls the __init__() of the ParentClass. __init__() of the ParentClass prints out ‘Parent Class’ then print inside the Child class is executed.

6.Packages¶

Packages are a way of structuring Python’s module namespace by using “dotted
module names”. For example, the module name

A.B

designates a submodule
named in a package named . Just like the use of modules saves the
authors of different modules from having to worry about each other’s global
variable names, the use of dotted module names saves the authors of multi-module
packages like NumPy or Pillow from having to worry about
each other’s module names.

Suppose you want to design a collection of modules (a “package”) for the uniform
handling of sound files and sound data. There are many different sound file
formats (usually recognized by their extension, for example:

.wav

,

.aiff

,

.au

), so you may need to create and maintain a growing
collection of modules for the conversion between the various file formats.
There are also many different operations you might want to perform on sound data
(such as mixing, adding echo, applying an equalizer function, creating an
artificial stereo effect), so in addition you will be writing a never-ending
stream of modules to perform these operations. Here’s a possible structure for
your package (expressed in terms of a hierarchical filesystem):

sound/ Top-level package __init__.py Initialize the sound package formats/ Subpackage for file format conversions __init__.py wavread.py wavwrite.py aiffread.py aiffwrite.py auread.py auwrite.py … effects/ Subpackage for sound effects __init__.py echo.py surround.py reverse.py … filters/ Subpackage for filters __init__.py equalizer.py vocoder.py karaoke.py …

When importing the package, Python searches through the directories on

sys.path

looking for the package subdirectory.

The

__init__.py

files are required to make Python treat directories
containing the file as packages (unless using a namespace package, a
relatively advanced feature). This prevents directories with a common name,
such as

string

, from unintentionally hiding valid modules that occur later
on the module search path. In the simplest case,

__init__.py

can just be
an empty file, but it can also execute initialization code for the package or
set the

__all__

variable, described later.

Users of the package can import individual modules from the package, for example:

import sound.effects.echo

This loads the submodule

sound.effects.echo

. It must be referenced with
its full name.

sound.effects.echo.echofilter(input, output, delay=0.7, atten=4)

An alternative way of importing the submodule is:

from sound.effects import echo

This also loads the submodule

echo

, and makes it available without its
package prefix, so it can be used as follows:

echo.echofilter(input, output, delay=0.7, atten=4)

Yet another variation is to import the desired function or variable directly:

from sound.effects.echo import echofilter

Again, this loads the submodule

echo

, but this makes its function

echofilter()

directly available:

echofilter(input, output, delay=0.7, atten=4)

Note that when using

from package import item

, the item can be either a
submodule (or subpackage) of the package, or some other name defined in the
package, like a function, class or variable. The

import

statement first
tests whether the item is defined in the package; if not, it assumes it is a
module and attempts to load it. If it fails to find it, an

ImportError

exception is raised.

Contrarily, when using syntax like

import item.subitem.subsubitem

, each item
except for the last must be a package; the last item can be a module or a
package but can’t be a class or function or variable defined in the previous
item.

6.4.Importing * From a Package¶

Now what happens when the user writes

from sound.effects import *

? Ideally,
one would hope that this somehow goes out to the filesystem, finds which
submodules are present in the package, and imports them all. This could take a
long time and importing sub-modules might have unwanted side-effects that should
only happen when the sub-module is explicitly imported.

The only solution is for the package author to provide an explicit index of the
package. The

import

statement uses the following convention: if a package’s

__init__.py

code defines a list named

__all__

, it is taken to be the
list of module names that should be imported when

from package import *

is
encountered. It is up to the package author to keep this list up-to-date when a
new version of the package is released. Package authors may also decide not to
support it, if they don’t see a use for importing * from their package. For
example, the file

sound/effects/__init__.py

could contain the following
code:

__all__ = [“echo”, “surround”, “reverse”]

This would mean that

from sound.effects import *

would import the three
named submodules of the

sound.effects

package.

Be aware that submodules might become shadowed by locally defined names. For
example, if you added a

reverse

function to the

sound/effects/__init__.py

file, the

from sound.effects import *

would only import the two submodules

echo

and

surround

, but not the

reverse

submodule, because it is shadowed by the locally defined

reverse

function:

__all__ = [ “echo”, # refers to the ‘echo.py’ file “surround”, # refers to the ‘surround.py’ file “reverse”, # !!! refers to the ‘reverse’ function now !!! ] def reverse(msg: str): # <– this name shadows the ‘reverse.py’ submodule return msg[::-1] # in the case of a ‘from sound.effects import *’

If

__all__

is not defined, the statement

from sound.effects import *

does not import all submodules from the package

sound.effects

into the
current namespace; it only ensures that the package

sound.effects

has
been imported (possibly running any initialization code in

__init__.py

)
and then imports whatever names are defined in the package. This includes any
names defined (and submodules explicitly loaded) by

__init__.py

. It
also includes any submodules of the package that were explicitly loaded by
previous

import

statements. Consider this code:

import sound.effects.echo import sound.effects.surround from sound.effects import *

In this example, the

echo

and

surround

modules are imported in the
current namespace because they are defined in the

sound.effects

package
when the

from...import

statement is executed. (This also works when

__all__

is defined.)

Although certain modules are designed to export only names that follow certain
patterns when you use

import *

, it is still considered bad practice in
production code.

Remember, there is nothing wrong with using

from package import
specific_submodule

! In fact, this is the recommended notation unless the
importing module needs to use submodules with the same name from different
packages.

6.4.Intra-package References¶

When packages are structured into subpackages (as with the

sound

package
in the example), you can use absolute imports to refer to submodules of siblings
packages. For example, if the module

sound.filters.vocoder

needs to use
the

echo

module in the

sound.effects

package, it can use

from
sound.effects import echo

.

You can also write relative imports, with the

from module import name

form
of import statement. These imports use leading dots to indicate the current and
parent packages involved in the relative import. From the

surround

module for example, you might use:

from . import echo from .. import formats from ..filters import equalizer

Note that relative imports are based on the name of the current module. Since
the name of the main module is always

"__main__"

, modules intended for use
as the main module of a Python application must always use absolute imports.

6.4.Packages in Multiple Directories¶

Packages support one more special attribute,

__path__

. This is
initialized to be a list containing the name of the directory holding the
package’s

__init__.py

before the code in that file is executed. This
variable can be modified; doing so affects future searches for modules and
subpackages contained in the package.

While this feature is not often needed, it can be used to extend the set of modules found in a package.

Footnotes

Chapter 17 Classes and methods
17.1 Object-oriented features

Python is an object-oriented programming language, which means that it provides features that support object-oriented programming.

It is not easy to define object-oriented programming, but we have already seen some of its characteristics:

For example, the Time class defined in Chapter 16 corresponds to the way people record the time of day, and the functions we defined correspond to the kinds of things people do with times. Similarly, the Point and Rectangle classes correspond to the mathematical concepts of a point and a rectangle.

So far, we have not taken advantage of the features Python provides to support object-oriented programming. These features are not strictly necessary; most of them provide alternative syntax for things we have already done. But in many cases, the alternative is more concise and more accurately conveys the structure of the program.

For example, in the Time program, there is no obvious connection between the class definition and the function definitions that follow. With some examination, it is apparent that every function takes at least one Time object as an argument.

This observation is the motivation for methods; a method is a function that is associated with a particular class. We have seen methods for strings, lists, dictionaries and tuples. In this chapter, we will define methods for user-defined types.

Methods are semantically the same as functions, but there are two syntactic differences:

In the next few sections, we will take the functions from the previous two chapters and transform them into methods. This transformation is purely mechanical; you can do it simply by following a sequence of steps. If you are comfortable converting from one form to another, you will be able to choose the best form for whatever you are doing.

17.2 Printing objects

In Chapter 16, we defined a class named
Time and in Exercise 16.1, you
wrote a function named

class Time(object): “””represents the time of day. attributes: hour, minute, second””” def print_time(time): print ‘%.2d:%.2d:%.2d’ % (time.hour, time.minute, time.second)

To call this function, you have to pass a Time object as an argument:

>>> start = Time() >>> start.hour = 9 >>> start.minute = 45 >>> start.second = 00 >>> print_time(start) 09:45:00

To make

class Time(object): def print_time(time): print ‘%.2d:%.2d:%.2d’ % (time.hour, time.minute, time.second)

Now there are two ways to call

>>> Time.print_time(start) 09:45:00

In this use of dot notation, Time is the name of the class,
and

The second (and more concise) way is to use method syntax:

>>> start.print_time() 09:45:00

In this use of dot notation,

Inside the method, the subject is assigned to the first parameter, so in this case start is assigned to time.

By convention, the first parameter of a method is
called self, so it would be more common to write

class Time(object): def print_time(self): print ‘%.2d:%.2d:%.2d’ % (self.hour, self.minute, self.second)

The reason for this convention is an implicit metaphor:

This change in perspective might be more polite, but it is not obvious that it is useful. In the examples we have seen so far, it may not be. But sometimes shifting responsibility from the functions onto the objects makes it possible to write more versatile functions, and makes it easier to maintain and reuse code.

Exercise 1 Rewrite

17.3 Another example

Here’s a version of increment (from Section 16.3) rewritten as a method:

# inside class Time: def increment(self, seconds): seconds += self.time_to_int() return int_to_time(seconds)

This version assumes that

Here’s how you would invoke increment:

>>> start.print_time() 09:45:00 >>> end = start.increment(1337) >>> end.print_time() 10:07:17

The subject, start, gets assigned to the first parameter, self. The argument, 1337, gets assigned to the second parameter, seconds.

This mechanism can be confusing, especially if you make an error. For example, if you invoke increment with two arguments, you get:

>>> end = start.increment(1337, 460) TypeError: increment() takes exactly 2 arguments (3 given)

The error message is initially confusing, because there are only two arguments in parentheses. But the subject is also considered an argument, so all together that’s three.

17.4 A more complicated example

# inside class Time: def is_after(self, other): return self.time_to_int() > other.time_to_int()

To use this method, you have to invoke it on one object and pass the other as an argument:

>>> end.is_after(start) True

One nice thing about this syntax is that it almost reads like English: “end is after start?”

17.5 The init method

The init method (short for “initialization”) is
a special method that gets invoked when an object is instantiated.
Its full name is

# inside class Time: def __init__(self, hour=0, minute=0, second=0): self.hour = hour self.minute = minute self.second = second

It is common for the parameters of

self.hour = hour

stores the value of the parameter hour as an attribute of self.

The parameters are optional, so if you call Time with no arguments, you get the default values.

>>> time = Time() >>> time.print_time() 00:00:00

If you provide one argument, it overrides hour:

>>> time = Time (9) >>> time.print_time() 09:00:00

If you provide two arguments, they override hour and minute.

>>> time = Time(9, 45) >>> time.print_time() 09:45:00

And if you provide three arguments, they override all three default values.

Exercise 2

Write an init method for the Point class that takes x and y as optional parameters and assigns them to the corresponding attributes.

17.6 The __str__ method

For example, here is a str method for Time objects:

# inside class Time: def __str__(self): return ‘%.2d:%.2d:%.2d’ % (self.hour, self.minute, self.second)

When you print an object, Python invokes the str method:

>>> time = Time(9, 45) >>> print time 09:45:00

When I write a new class, I almost always start by writing

Exercise 3 Write a str method for the Point class. Create a Point object and print it.

17.7 Operator overloading

By defining other special methods, you can specify the behavior
of operators on user-defined types. For example, if you define
a method named

Here is what the definition might look like:

# inside class Time: def __add__(self, other): seconds = self.time_to_int() + other.time_to_int() return int_to_time(seconds)

And here is how you could use it:

>>> start = Time(9, 45) >>> duration = Time(1, 35) >>> print start + duration 11:20:00

When you apply the + operator to Time objects, Python invokes

Changing the behavior of an operator so that it works with
user-defined types is called operator overloading. For every
operator in Python there is a corresponding special method, like

Exercise 4 Write an add method for the Point class.

17.8 Type-based dispatch

In the previous section we added two Time objects, but you
also might want to add an integer to a Time object. The
following is a version of

# inside class Time: def __add__(self, other): if isinstance(other, Time): return self.add_time(other) else: return self.increment(other) def add_time(self, other): seconds = self.time_to_int() + other.time_to_int() return int_to_time(seconds) def increment(self, seconds): seconds += self.time_to_int() return int_to_time(seconds)

The built-in function isinstance takes a value and a class object, and returns True if the value is an instance of the class.

If other is a Time object,

Here are examples that use the + operator with different types:

>>> start = Time(9, 45) >>> duration = Time(1, 35) >>> print start + duration 11:20:00 >>> print start + 1337 10:07:17

Unfortunately, this implementation of addition is not commutative. If the integer is the first operand, you get

>>> print 1337 + start TypeError: unsupported operand type(s) for +: ‘int’ and ‘instance’

The problem is, instead of asking the Time object to add an integer,
Python is asking an integer to add a Time object, and it doesn’t know
how to do that. But there is a clever solution for this problem: the
special method

# inside class Time: def __radd__(self, other): return self.__add__(other)

And here’s how it’s used:

>>> print 1337 + start 10:07:17

Exercise 5 Write an add method for Points that works with either a Point object or a tuple:

17.9 Polymorphism

Type-based dispatch is useful when it is necessary, but (fortunately) it is not always necessary. Often you can avoid it by writing functions that work correctly for arguments with different types.

Many of the functions we wrote for strings will actually work for any kind of sequence. For example, in Section 11.1 we used histogram to count the number of times each letter appears in a word.

def histogram(s): d = dict() for c in s: if c not in d: d[c] = 1 else: d[c] = d[c]+1 return d

This function also works for lists, tuples, and even dictionaries, as long as the elements of s are hashable, so they can be used as keys in d.

>>> t = [‘spam’, ‘egg’, ‘spam’, ‘spam’, ‘bacon’, ‘spam’] >>> histogram(t) {‘bacon’: 1, ‘egg’: 1, ‘spam’: 4}

Functions that can work with several types are called polymorphic. Polymorphism can facilitate code reuse. For example, the built-in function sum, which adds the elements of a sequence, works as long as the elements of the sequence support addition.

Since Time objects provide an add method, they work with sum:

>>> t1 = Time(7, 43) >>> t2 = Time(7, 41) >>> t3 = Time(7, 37) >>> total = sum([t1, t2, t3]) >>> print total 23:01:00

In general, if all of the operations inside a function work with a given type, then the function works with that type.

The best kind of polymorphism is the unintentional kind, where you discover that a function you already wrote can be applied to a type you never planned for.

17.10 Debugging

It is legal to add attributes to objects at any point in the execution of a program, but if you are a stickler for type theory, it is a dubious practice to have objects of the same type with different attribute sets. It is usually a good idea to initialize all of an objects attributes in the init method.

If you are not sure whether an object has a particular attribute, you can use the built-in function hasattr (see Section 15.7).

Another way to access the attributes of an object is through the
special attribute

>>> p = Point(3, 4) >>> print p.__dict__ {‘y’: 4, ‘x’: 3}

For purposes of debugging, you might find it useful to keep this function handy:

def print_attributes(obj): for attr in obj.__dict__: print attr, getattr(obj, attr)

The built-in function getattr takes an object and an attribute name (as a string) and returns the attribute’s value.

17.11 Glossary
17.12 Exercises

Exercise 6

This exercise is a cautionary tale about one of the most common, and difficult to find, errors in Python.

Exercise 7

Visual is a Python module that provides 3-D graphics. It is not always included in a Python installation, so you might have to install it from your software repository or, if it’s not there, from vpython.org.

The following example creates a 3-D space that is 256 units wide, long and high, and sets the “center” to be the point (128, 128, 128). Then it draws a blue sphere.

from visual import * scene.range = (256, 256, 256) scene.center = (128, 128, 128) color = (0.1, 0.1, 0.9) # mostly blue sphere(pos=scene.center, radius=128, color=color)

color is an RGB tuple; that is, the elements are Red-Green-Blue levels between 0.0 and 1.0 (see wikipedia.org/wiki/RGB_color_model).

If you run this code, you should see a window with a black background and a blue sphere. If you drag the middle button up and down, you can zoom in and out. You can also rotate the scene by dragging the right button, but with only one sphere in the world, it is hard to tell the difference.

The following loop creates a cube of spheres:

t = range(0, 256, 51) for x in t: for y in t: for z in t: pos = x, y, z sphere(pos=pos, radius=10, color=color)

You can see my solution at thinkpython.com/code/color_space.py.

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__init__ method in Python is used to initialize objects of a class. It is also called a constructor.

To completely understand the concept of __init__ method, you should be familiar with:

Prerequisites – Python Class and Objects, Self

Python Classes in 1 Minute!
Python Classes in 1 Minute!

6.Standard Modules¶

Python comes with a library of standard modules, described in a separate
document, the Python Library Reference (“Library Reference” hereafter). Some
modules are built into the interpreter; these provide access to operations that
are not part of the core of the language but are nevertheless built in, either
for efficiency or to provide access to operating system primitives such as
system calls. The set of such modules is a configuration option which also
depends on the underlying platform. For example, the

winreg

module is only
provided on Windows systems. One particular module deserves some attention:

sys

, which is built into every Python interpreter. The variables

sys.ps1

and

sys.ps2

define the strings used as primary and secondary
prompts:

>>> import sys >>> sys.ps1 ‘>>> ‘ >>> sys.ps2 ‘… ‘ >>> sys.ps1 = ‘C> ‘ C> print(‘Yuck!’) Yuck! C>

These two variables are only defined if the interpreter is in interactive mode.

The variable

sys.path

is a list of strings that determines the interpreter’s
search path for modules. It is initialized to a default path taken from the
environment variable

PYTHONPATH

, or from a built-in default if

PYTHONPATH

is not set. You can modify it using standard list
operations:

>>> import sys >>> sys.path.append(‘/ufs/guido/lib/python’)

Complete Code Example

Example 1:

class Dog: def __init__(self, dogBreed,dogEyeColor): self.breed = dogBreed self.eyeColor = dogEyeColor tomita = Dog(“Fox Terrier”,”brown”) print(“This dog is a”,tomita.breed,”and his eyes are”,tomita.eyeColor)

Example 2:

class Dog: def __init__(self): self.nbLegs = 4 tomita = Dog() print(“This dog has”,tomita.nbLegs,”legs”)

Example 3:

class Dog: def __init__(self, dogBreed=”German Shepherd”,dogEyeColor=”brown”): self.breed = dogBreed self.eyeColor = dogEyeColor tomita = Dog() print(“This dog is a”,tomita.breed,”and his eyes are”,tomita.eyeColor)

Python __init__() Function

Python super function 🦸
Python super function 🦸

When to Use __init__ in Python

You should use

__init__

when you need to initialize the object. For example, you might want to use

__init__

to:

  • Set the object’s attributes.
  • Call the object’s superclass’

    __init__

    method.
  • Perform other initialization tasks.

Conclusion

So, to sum it all up, __init__ is a reserved method for classes in Python that basically behaves as the constructors. In other words, this method in a Python class is used for initialising the attributes of an object. It is invoked automatically at the time of instance creation for a class. This __init__ constructor is invoked as many times as the instances are created for a class. We can use any of the three types of __init__ constructors – default, parameterised, __init__ with default parameter – as per the need of our programming module. The ‘self’ is a mandatory parameter for any member function of a class, including the __init__ method, as it is a reference to the instance of the class created.

Even though Python does not support constructor overloading, the concept of constructor overloading can be implemented using the *args that are used for passing different numbers of arguments for different objects of a class. Furthermore, we can use the if-else statements for initialising the attributes according to the different types of arguments within the __init__ constructor. To know more about Classes and Objects in Python, you can check out this blog.

We have also seen how the __init__ method of a class works with inheritance. We can easily call the __init__ method of the base class within the __init__ method of the sub class. When an object for the subclass is created, the __init__ method of the sub class is invoked, which further invokes the __init__ method of the base class.

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__init__ in Python

What is \
What is \”self\” in Python?

Syntax

We use the method

__init__

in Python to initialize a class. When we input an object of the class, the method is applied automatically. Thus, the basic syntax of the method

__init__

is as follows:


def __init__(self, *args, **kwargs): # código a ser executado durante a inicialização do objeto

The first parameter of the method

__init__

is the argument list (

*args

). We can use it to pass construction arguments to the class when we create an object. Also, if there are no construction arguments, we can pass

None

to the first parameter.

The second parameter of the method

__init__

is the initialization parameter list (

**kwargs

). We can be using it to pass initialization parameters to the class when we input an object. So the initialization parameters are being passed as an associative key-value where the key is the parameter name and the value is the parameter value.

We run the code inside the method

__init__

when we create an object. In this way, we can use the class object as a pointer to the object being initialized, accessing the class’s attributes and methods, and performing any other operation necessary to initialize the object.

In this example below, we create a class

Car

with a method

__init__

that takes three parameters (

make

,

model

and

year

). Code within the method

__init__

assigns these values to the corresponding attributes. So we also create a method

start

and a method

stop

that print information about the car. When we create an object of the class

Car

and call the

start

and methods

stop

, the code inside the method

__init__

is executed. Look:


class Car: def __init__(self, make, model, year): self.make = make self.model = model self.year = year def start(self): print(f"Starting {self.make} {self.model} {self.year}") def stop(self): print(f"Stopping {self.make} {self.model} {self.year}") car = Car("Toyota", "Corolla", 2022)

Python3


class


A(


object


):


def


__init__(


self


, something):


print


"A init called"


self


.something


something


class


B(A):


def


__init__(


self


, something):


print


"B init called"


self


.something


something


A.__init__(


self


, something)


obj


B(


"Something"

Output:

B init calledA init called

Read: Inheritance in Python

We have covered __init__ in Python, discussed how to use __init__, and also saw some examples of using __init__ method in Python.

Constructor is a crucial concept in OOPs, and __init__ method is very similar to constructors.

Hope this article helped you in learning __init__ method, and you will be able to use it in your projects.

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Today, a programmer is bound to come across object-oriented programming (OOP) during their career. As a modern programming language, Python provides all the means to implement the object-oriented philosophy. The

__init__

method is at the core of OOP and is required to create objects.

In this article, we’ll review the paradigm of object-oriented programming before explaining why and how to use the

__init__

method.

Functions vs Classes: When to Use Which and Why?
Functions vs Classes: When to Use Which and Why?

Exceptions of init in Python

The init method in Python is the constructor for object initialization. It lacks a return value and is prone to TypeError if arguments are missing or exceed expectations. Default parameter values can be set to mitigate this. Attempting to access undefined attributes leads to an AttributeError. The init method is not mandatory, but if defined, it’s crucial for proper object setup.

Python3


class


A(


object


):


def


__init__(


self


, something):


print


"A init called"


self


.something


something


class


B(A):


def


__init__(


self


, something):


A.__init__(


self


, something)


print


"B init called"


self


.something


something


obj


B(


"Something"

Output:

A init calledB init called

So, the parent class constructor is called first. But in Python, it is not compulsory that the parent class constructor will always be called first.

The order in which the __init__ method is called for a parent or a child class can be modified. This can simply be done by calling the parent class constructor after the body of the child class constructor.

Example:

__str__ Method | Python Tutorial
__str__ Method | Python Tutorial

The Default __init__ Constructor

In Python, a constructor does not necessarily need parameters passed to it. There can be default parameters. A constructor with no mandatory parameters is called a default constructor. Let’s rewrite our class with a default constructor:

class Dog: def __init__(self, dogBreed=”German Shepherd”,dogEyeColor=”Brown”): self.breed = dogBreed self.eyeColor = dogEyeColor

If a user does not enter any values, the constructor will assign “German Shepherd” and “Brown” as the attributes.

We can now create an instance of Dog without specifying any parameter:

tomita = Dog()

Since there are no arguments to pass, we use empty parentheses after the class name. We can still display the object’s attributes:

print(“This dog is a”,tomita.breed,”and its eyes are”,tomita.eyeColor)

This gives us the following output:

This dog is a German Shepherd and its eyes are Brown

This simple code works perfectly.

Trends and news regarding the init method in recent versions of Python.

The init method is one of the main features of objects in Python, and recently, there have been some trends and new developments regarding it in recent versions of the language. In that sense, here are some of the main changes and trends:

  1. Self-registered initialization method: In Python 3.8, added a new self-registered initialization method, which allows developers to define a method

    __init__

    for objects that will be called automatically when we create an object. Thus, this allows developers to write less code and make objects easier to use.
  2. Custom initialization method: In Python 3.7, added support for custom initialization methods, which allows developers to define a

    __init__

    custom method for their objects. Thus, this method can include additional code for object initialization, in addition to the standard code.
  3. Use of decorators: Decorators are a way to modify the behavior of an object or method, without changing the source code. So, in Python 3.8, added support for initialization decorators, which allow developers to add Custom behaviors to their objects during initialization.
  4. Using generic classes: In Python 3.8, added support for generic classes, which allow developers to create classes that can be used with different data types.
  5. Static initialization method: In Python 3.9, added support for static initialization methods. This way allowing developers to define a

    __init__

    static method for their objects.
5 Tips To Organize Python Code
5 Tips To Organize Python Code

Use of Python __init__

As discussed earlier in this blog and seen from the previous examples, __init__ method is used for initialising the attributes of an object for a class. We have also understood how constructor overloading can be achieved using this method. Now, let us see how this __init__ method behaves in case of inheritance.

Inheritance allows the child class to inherit the __init__() method of the parent class along with the other data members and member functions of that class. The __init__ method of the parent or the base class is called within the __init__ method of the child or sub class. In case the parent class demands an argument, the parameter value must be passed in the __init__ method of the child class as well as at the time of object creation for the child class.


class Person(object): def __init__(self, name): self.name = name print("Initialising the name attribute") class Teacher(Person): def __init__(self, name, age): Person.__init__(self, name) # Calling init of base class self.age = age print("Age attribute of base class is initialised") def show(self): print("Name of the teacher is ", self.name) print("Age of the teacher is ", self.age) t = Teacher("Allen Park", 45) # The init of subclass is called t.show()

From the above output, we can trace the order in which the __init__ constructors have been called and executed. The object ‘t’ calls the constructor of the Teacher class, which transfers the control of the program to the constructor of the Person class. Once the __init__ of Person finishes its execution, the control returns to the constructor of the Teacher class and finishes its execution.

The __init__() Function

The examples above are classes and objects in their simplest form, and are not really useful in real life applications.

To understand the meaning of classes we have to understand the built-in __init__() function.

All classes have a function called __init__(), which is always executed when the class is being initiated.

Use the __init__() function to assign values to object properties, or other operations that are necessary to do when the object is being created:

Example

Create a class named Person, use the __init__() function to assign values for name and age:

def __init__(self, name, age):

self.name = name

self.age = age

p1 = Person(“John”, 36)

print(p1.name)

print(p1.age)

Note: The

__init__()

function is called automatically every time the class is being used to create a new object.

Modules¶

If you quit from the Python interpreter and enter it again, the definitions you have made (functions and variables) are lost. Therefore, if you want to write a somewhat longer program, you are better off using a text editor to prepare the input for the interpreter and running it with that file as input instead. This is known as creating a script. As your program gets longer, you may want to split it into several files for easier maintenance. You may also want to use a handy function that you’ve written in several programs without copying its definition into each program.

To support this, Python has a way to put definitions in a file and use them in a script or in an interactive instance of the interpreter. Such a file is called a module; definitions from a module can be imported into other modules or into the main module (the collection of variables that you have access to in a script executed at the top level and in calculator mode).

A module is a file containing Python definitions and statements. The file name
is the module name with the suffix

.py

appended. Within a module, the
module’s name (as a string) is available as the value of the global variable

__name__

. For instance, use your favorite text editor to create a file
called

fibo.py

in the current directory with the following contents:

# Fibonacci numbers module def fib(n): # write Fibonacci series up to n a, b = 0, 1 while a < n: print(a, end=’ ‘) a, b = b, a+b print() def fib2(n): # return Fibonacci series up to n result = [] a, b = 0, 1 while a < n: result.append(a) a, b = b, a+b return result

Now enter the Python interpreter and import this module with the following command:

>>> import fibo

This does not add the names of the functions defined in

fibo

directly to
the current namespace (see Python Scopes and Namespaces for more details);
it only adds the module name

fibo

there. Using
the module name you can access the functions:

>>> fibo.fib(1000) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 >>> fibo.fib2(100) [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] >>> fibo.__name__ ‘fibo’

If you intend to use a function often you can assign it to a local name:

>>> fib = fibo.fib >>> fib(500) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377

Why __init__.py File is Used in Python Projects | 2MinutesPy
Why __init__.py File is Used in Python Projects | 2MinutesPy

6.The dir() Function¶

The built-in function

dir()

is used to find out which names a module
defines. It returns a sorted list of strings:

>>> import fibo, sys >>> dir(fibo) [‘__name__’, ‘fib’, ‘fib2’] >>> dir(sys) [‘__breakpointhook__’, ‘__displayhook__’, ‘__doc__’, ‘__excepthook__’, ‘__interactivehook__’, ‘__loader__’, ‘__name__’, ‘__package__’, ‘__spec__’, ‘__stderr__’, ‘__stdin__’, ‘__stdout__’, ‘__unraisablehook__’, ‘_clear_type_cache’, ‘_current_frames’, ‘_debugmallocstats’, ‘_framework’, ‘_getframe’, ‘_git’, ‘_home’, ‘_xoptions’, ‘abiflags’, ‘addaudithook’, ‘api_version’, ‘argv’, ‘audit’, ‘base_exec_prefix’, ‘base_prefix’, ‘breakpointhook’, ‘builtin_module_names’, ‘byteorder’, ‘call_tracing’, ‘callstats’, ‘copyright’, ‘displayhook’, ‘dont_write_bytecode’, ‘exc_info’, ‘excepthook’, ‘exec_prefix’, ‘executable’, ‘exit’, ‘flags’, ‘float_info’, ‘float_repr_style’, ‘get_asyncgen_hooks’, ‘get_coroutine_origin_tracking_depth’, ‘getallocatedblocks’, ‘getdefaultencoding’, ‘getdlopenflags’, ‘getfilesystemencodeerrors’, ‘getfilesystemencoding’, ‘getprofile’, ‘getrecursionlimit’, ‘getrefcount’, ‘getsizeof’, ‘getswitchinterval’, ‘gettrace’, ‘hash_info’, ‘hexversion’, ‘implementation’, ‘int_info’, ‘intern’, ‘is_finalizing’, ‘last_traceback’, ‘last_type’, ‘last_value’, ‘maxsize’, ‘maxunicode’, ‘meta_path’, ‘modules’, ‘path’, ‘path_hooks’, ‘path_importer_cache’, ‘platform’, ‘prefix’, ‘ps1’, ‘ps2’, ‘pycache_prefix’, ‘set_asyncgen_hooks’, ‘set_coroutine_origin_tracking_depth’, ‘setdlopenflags’, ‘setprofile’, ‘setrecursionlimit’, ‘setswitchinterval’, ‘settrace’, ‘stderr’, ‘stdin’, ‘stdout’, ‘thread_info’, ‘unraisablehook’, ‘version’, ‘version_info’, ‘warnoptions’]

Without arguments,

dir()

lists the names you have defined currently:

>>> a = [1, 2, 3, 4, 5] >>> import fibo >>> fib = fibo.fib >>> dir() [‘__builtins__’, ‘__name__’, ‘a’, ‘fib’, ‘fibo’, ‘sys’]

Note that it lists all types of names: variables, modules, functions, etc.


dir()

does not list the names of built-in functions and variables. If you
want a list of those, they are defined in the standard module

builtins

:

>>> import builtins >>> dir(builtins) [‘ArithmeticError’, ‘AssertionError’, ‘AttributeError’, ‘BaseException’, ‘BlockingIOError’, ‘BrokenPipeError’, ‘BufferError’, ‘BytesWarning’, ‘ChildProcessError’, ‘ConnectionAbortedError’, ‘ConnectionError’, ‘ConnectionRefusedError’, ‘ConnectionResetError’, ‘DeprecationWarning’, ‘EOFError’, ‘Ellipsis’, ‘EnvironmentError’, ‘Exception’, ‘False’, ‘FileExistsError’, ‘FileNotFoundError’, ‘FloatingPointError’, ‘FutureWarning’, ‘GeneratorExit’, ‘IOError’, ‘ImportError’, ‘ImportWarning’, ‘IndentationError’, ‘IndexError’, ‘InterruptedError’, ‘IsADirectoryError’, ‘KeyError’, ‘KeyboardInterrupt’, ‘LookupError’, ‘MemoryError’, ‘NameError’, ‘None’, ‘NotADirectoryError’, ‘NotImplemented’, ‘NotImplementedError’, ‘OSError’, ‘OverflowError’, ‘PendingDeprecationWarning’, ‘PermissionError’, ‘ProcessLookupError’, ‘ReferenceError’, ‘ResourceWarning’, ‘RuntimeError’, ‘RuntimeWarning’, ‘StopIteration’, ‘SyntaxError’, ‘SyntaxWarning’, ‘SystemError’, ‘SystemExit’, ‘TabError’, ‘TimeoutError’, ‘True’, ‘TypeError’, ‘UnboundLocalError’, ‘UnicodeDecodeError’, ‘UnicodeEncodeError’, ‘UnicodeError’, ‘UnicodeTranslateError’, ‘UnicodeWarning’, ‘UserWarning’, ‘ValueError’, ‘Warning’, ‘ZeroDivisionError’, ‘_’, ‘__build_class__’, ‘__debug__’, ‘__doc__’, ‘__import__’, ‘__name__’, ‘__package__’, ‘abs’, ‘all’, ‘any’, ‘ascii’, ‘bin’, ‘bool’, ‘bytearray’, ‘bytes’, ‘callable’, ‘chr’, ‘classmethod’, ‘compile’, ‘complex’, ‘copyright’, ‘credits’, ‘delattr’, ‘dict’, ‘dir’, ‘divmod’, ‘enumerate’, ‘eval’, ‘exec’, ‘exit’, ‘filter’, ‘float’, ‘format’, ‘frozenset’, ‘getattr’, ‘globals’, ‘hasattr’, ‘hash’, ‘help’, ‘hex’, ‘id’, ‘input’, ‘int’, ‘isinstance’, ‘issubclass’, ‘iter’, ‘len’, ‘license’, ‘list’, ‘locals’, ‘map’, ‘max’, ‘memoryview’, ‘min’, ‘next’, ‘object’, ‘oct’, ‘open’, ‘ord’, ‘pow’, ‘print’, ‘property’, ‘quit’, ‘range’, ‘repr’, ‘reversed’, ’round’, ‘set’, ‘setattr’, ‘slice’, ‘sorted’, ‘staticmethod’, ‘str’, ‘sum’, ‘super’, ‘tuple’, ‘type’, ‘vars’, ‘zip’]

Tips for writing efficient code with the init method in Python

The method

__init__

is a special method in Python that is called automatically when creating a new instance of a class. We use this method to initialize the instance and it can be used to perform any action before the instance is applied. Here are some tips for writing efficient code with the init method in Python:

  1. Use a body argument to receive instance parameters. This is therefore useful for initializing attributes with values that vary across different instances of the class.
  2. Use the keyword

    self

    to reference class attributes and methods. As such, this is needed wherever it is being used

    self

    , as

    self

    it is a variable automatically passed to the method

    __init__

    .
  3. Initialize all attributes of the class in the method

    init

    instead of using the keyword

    default

    . This makes the code more readable and helps to avoid initialization errors.
  4. Use a block

    try-except

    to handle initialization errors. Thus, this helps ensure that your class is more robust and resilient.
  5. Use a list to initialize various class attributes. This is useful when you need to initialize several class attributes with values that are similar.
Python staticmethod and classmethod
Python staticmethod and classmethod

Python3


class


Person:


def


__init__(


self


, name):


self


.name


name


def


say_hi(


self


):


print


'Hello, my name is'


self


.name)


p1


Person(


'Nikhil'


p2


Person(


'Abhinav'


p3


Person(


'Anshul'


p1.say_hi()


p2.say_hi()


p3.say_hi()

Output:

Hello, my name is NikhilHello, my name is AbhinavHello, my name is Anshul

What is __init__ in Python?

In Python,

__init__

is a special method known as the constructor. It is automatically called when a new instance (object) of a class is created. The

__init__

method allows you to initialize the attributes (variables) of an object.

Here’s an example to illustrate the usage of

__init__

:


class MyClass: def __init__(self, name, age): self.name = name self.age = age def display_info(self): print(f"Name: {self.name}") print(f"Age: {self.age}") # Creating an instance of MyClass obj = MyClass("John", 25) # Accessing attributes and calling methods obj.display_info()

super/MRO, Python's most misunderstood feature.
super/MRO, Python’s most misunderstood feature.

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The

__init__

method is paramount to Python’s object-oriented programming.. In this article, we explained the role of the

__init__

method within the context of OOP and class definition. The

__init__

method is one of the numerous special methods built into Python, and programmers can use it with or without parameters for each class they create.

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Python3


class


Person:


def


__init__(


self


, name):


self


.name


name


def


say_hi(


self


):


print


'Hello, my name is'


self


.name)


Person(


'Nikhil'


p.say_hi()

Output:

Hello, my name is Nikhil

Understanding the code

In the above example, a person named Nikhil is created. While creating a person, “Nikhil” is passed as an argument, this argument will be passed to the __init__ method to initialize the object.

The keyword self represents the instance of a class and binds the attributes with the given arguments. Similarly, many objects of the Person class can be created by passing different names as arguments.

Below is the example of __init__ in Python with parameters

Understanding stdin, stdout, stderr in Python
Understanding stdin, stdout, stderr in Python

What Is the __new__ Method in Python?

The new method is a static method that belongs to the class itself. It’s responsible for creating and returning a new instance of the class. The method takes the class as its first argument, followed by any additional arguments that need to be passed to it.


class MyClass: def __new__(cls, *args, **kwargs): instance = super().__new__(cls) return instance

The

__new__

method is called before the

__init__

method and is often used when you need to control the object creation process, like in the case of singletons or when you want to inherit from immutable classes.

How Does the __init__ Method Work?

The

__init__

method is the Python equivalent of the C++ constructor in an object-oriented approach. The

__init__

function is called every time an object is created from a class. The

__init__

method lets the class initialize the object’s attributes and serves no other purpose. It is only used within classes.

Create a Class

Let’s begin by creating a class:

class Dog: def __init__(self,dogBreed,dogEyeColor): self.breed = dogBreed self.eyeColor = dogEyeColor…

First, we declare the class Dog using the keyword

class

. We use the keyword

def

to define a function or method, such as the

__init__

method. As you can see, the

__init__

method initializes two attributes:

breed

and

eyeColor

.

We’ll now see how to pass these parameters when declaring an object. This is where we need the keyword self to bind the object’s attributes to the arguments received.

Create an Object

Next we’ll create an object, or instance, of the class

Dog

:

…Tomita = Dog(“Fox Terrier”,”brown”)…

When we create the object

tomita

(which is the dog’s name), we first define the class from which it is created (Dog). We next pass the arguments “Fox Terrier” and “brown,” which correspond to the respective parameters of the

__init__

method of the class

Dog

.

The

__init__

method uses the keyword

self

to assign the values passed as arguments to the object attributes

self.breed

and

self.eyeColor

.

Access Object Attributes

To access an attribute of your brand new Fox Terrier object, you can use the dot (.) notation to get the value you need. A print statement helps us demonstrate how this works:

…print(“This dog is a”,tomita.breed,”and its eyes are”,tomita.eyeColor)

Executing the above code gives us the following result:

This dog is a Fox Terrier and its eyes are brown

The program accessed

tomita’s

attributes and displayed them properly.

You should put this in all your Python scripts | if __name__ == '__main__': ...
You should put this in all your Python scripts | if __name__ == ‘__main__’: …

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Python is one of the most popular coding platforms available in the industry today. Starting from amateurs to professionals, everyone used Python to code and make applications for mobile as well as web. Being such a versatile platform, there are some aspects that are not so well known among users. One of the most significant of this is the Init In Python. This article will help you explore this concept and following pointers in detail,

So let us get started then.

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If you have been using Python for sometime now, you are well aware of the fact that Python is an object oriented programming language. What this basically means is that everything that you create in the Python environment is termed as being object. Now before we begin to explore more about the __init__ function in Python, let’s get the basics out of the way.

Class

A class in Python is a category or set of different elements grouped together that share one or more similarities with one another, but yet distinct from other classes via type, quality and kind. In technical terminology, we can define a class in Python as being a blueprint for individual objects with same or exact behavior.

Object

An object in Python is one instance of a class and it can be programmed to perform the functions that have been defined in the class.

Self

The self in keyword in Python is used to all the instances in a class. By using the self keyword, one can easily access all the instances defined within a class, including its methods and attributes.

init

__init__ is one of the reserved methods in Python. In object oriented programming, it is known as a constructor. The __init__ method can be called when an object is created from the class, and access is required to initialize the attributes of the class.

Moving on with this article on Init In Python,

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From the definition of __init__ shared above, you now have somewhat of an idea at what this method exactly does. In order to further clarify this concept, let’s look at an example.

#1 Example

Aim: To program a racing game in Python with the name “NFS.”

Solution: If you want to create a racing game in Python with the name “NFS” one of the basic objects that you need to create are the individual cars. Each of the cars that you create within the game will all have different attributes, for example color, speed etc. as well as methods like change gear, accelerate, break etc.

When you code this concept into the Python interpreter it should look something like this.

class Car(object): “”” blueprint for car “”” def __init__(self, model, color, company, speed_limit): self.color = color self.company = company self.speed_limit = speed_limit self.model = model def start(self): print(“started”) def stop(self): print(“stopped”) def accelarate(self): print(“accelarating…”) “accelarator functionality here” def change_gear(self, gear_type): print(“gear changed”) ” gear related functionality here” Now that we have created the objects, let’s move on to create the individual cars in the game. maruthi_suzuki = Car(“ertiga”, “black”, “suzuki”, 60) audi = Car(“A6”, “red”, “audi”, 80)

In the above example, we have created two different car models; one being the Suzuki Ertiga and the second Audi A6. Once these objects have been successfully created, we can make use of the __init__ method to initialize and thus prepare for the next steps.

In this example, we can also make use of the self method to represent the different instances of the class and also bind the attributes with the given arguments. Using the self method will allow us to basically access the attributes and methods that we have created within the class.

Moving on with this article on Init In Python,

#2 Example

Aim: To find out the development cost of a rectangular field having the dimensions, breadth(b=120), length(l=160). The cost of 1 square metres is 2000 INR.

Solution: Keeping in mind the steps shared in the earlier example, the code for this particular example will look like the following.

class Rectangle: def __init__(self, length, breadth, unit_cost=0): self.length = length self.breadth = breadth self.unit_cost = unit_cost def get_perimeter(self): return 2 * (self.length + self.breadth) def get_area(self): return self.length * self.breadth def calculate_cost(self): area = self.get_area() return area * self.unit_cost # breadth = 120 cm, length = 160 cm, 1 cm^2 = Rs 2000 r = Rectangle(160, 120, 2000) print(“Area of Rectangle: %s cm^2” % (r.get_area())) print(“Cost of rectangular field: Rs. %s ” %(r.calculate_cost()))

As discussed in the earlier example, the self method represents the instances and attributes of the class. If you take a closer look, you will realise that we have used the methods, self.length to derive the value of the attribute length. The attribute length is already bind within the class, and we are using the self method to represent the object within the same class.

We have also made use of the method, def get_area(self): as a parameter in the above code. What this does is, every time we call upon the method it automatically passes the first argument along with other arguments in the method. Although this automation might look small at first glance, it will save a lot of time and increase efficiency in the long run.

To further clarify this discussion, take a look at the example below.

r = Rectangle(160, 120, 2000)

Note: “r” is the representation of the object outside of the class and “self” is the representation of the object inside the class.

This brings us to the end of this article on Init In Python.

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Understanding Self and __init__ Method in Python Class

2022-07-18

Before understanding the “self” and “__init__” methods in python class, it’s very helpful if we have the idea of what is a class and object.

Class :

Class is a set or category of things having some property or attribute in common and differentiated from others by kind, type, or quality.

In technical terms we can say that class is a blue print for individual objects with exact behaviour.

Object :

object is one of instances of the class. which can perform the functionalities which are defined in the class.

self :

self represents the instance of the class. By using the “self” keyword we can access the attributes and methods of the class in python.

__init__ :

“__init__” is a reseved method in python classes. It is known as a constructor in object oriented concepts. This method called when an object is created from the class and it allow the class to initialize the attributes of a class.

How can we use “__init__ ” ?

Let’s consider that you are creating a NFS game. for that we should have a car. Car can have attributes like “color”, “company”, “speed_limit” etc. and methods like “change_gear”, “start”, “accelarate”, “move” etc.


class Car(object): """ blueprint for car """ def __init__(self, model, color, company, speed_limit): self.color = color self.company = company self.speed_limit = speed_limit self.model = model def start(self): print("started") def stop(self): print("stopped") def accelarate(self): print("accelarating...") "accelarator functionality here" def change_gear(self, gear_type): print("gear changed") " gear related functionality here"

Lets try to create different types of cars


maruthi_suzuki = Car("ertiga", "black", "suzuki", 60) audi = Car("A6", "red", "audi", 80)

We have created two different types of car objects with the same class. while creating the car object we passed arguments “ertiga”, “black”, “suzuki”, 60 these arguments will pass to “__init__” method to initialize the object.

Here, the magic keyword “self” represents the instance of the class. It binds the attributes with the given arguments.

Usage of “self” in class to access the methods and attributes

Case: Find out the cost of a rectangular field with breadth(b=120), length(l=160). It costs x (2000) rupees per 1 square unit


class Rectangle: def __init__(self, length, breadth, unit_cost=0): self.length = length self.breadth = breadth self.unit_cost = unit_cost def get_perimeter(self): return 2 * (self.length + self.breadth) def get_area(self): return self.length * self.breadth def calculate_cost(self): area = self.get_area() return area * self.unit_cost # breadth = 120 cm, length = 160 cm, 1 cm^2 = Rs 2000 r = Rectangle(160, 120, 2000) print("Area of Rectangle: %s cm^2" % (r.get_area())) print("Cost of rectangular field: Rs. %s " %(r.calculate_cost()))

As we already discussed “self” represents the same object or instance of the class. If you see, inside the method “get_area” we have used “self.length” to get the value of the attribute “length”. attribute “length” is bind to the object(instance of the class) at the time of object creation. “self” represents the object inside the class. “self” works just like “r” in the statement “r = Rectangle(160, 120, 2000)”. If you see the method structure “def get_area(self): ” we have used “self” as a parameter in the method because whenever we call the method the object (instance of class) automatically passes as a first argument along with other argumets of the method.If no other arguments are provided only “self” is passed to the method. That’s the reason we use “self” to call the method inside the class(“self.get_area()”). we use object( instance of class) to call the method outside of the class definition(“r.get_area()”). “r” is the instance of the class, when we call method “r.get_area()” the instance “r” is passed as as first argument in the place of self.


r = Rectangle(160, 120, 2000) Note: "r" is the representation of the object outside of the class and "self" is the representation of the object inside the class.

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What is __init__ in Python?

__init__ method is like default constructor in C++ and Java. Constructors are used to initialize the object’s state.

The task of constructors is to initialize(assign values) to the data members of the class when an object of the class is created.

Like methods, a constructor also contains a collection of statements(i.e. instructions) that are executed at the time of Object creation. It is run as soon as an object of a class is instantiated.

The method is useful to do any initialization you want to do with your object.

Python Object Oriented Programming (OOP) - For Beginners
Python Object Oriented Programming (OOP) – For Beginners

What is init in Python?

Python is an object-oriented language. Whenever we create the object of our class, the the constructor of our class is called first. There is a method called __init__() for this task in Python. This method is called automatically whenever a new object of a class is created.

__init__ is a magic method called Dunder Methods (These are special methods whose invocation happens internally, and they start and end with double underscores). Other examples for magic methods are: __add__, __len__, __str__, etc.

Differences Between __new__ and __init__

Functional Python for the ETL Developer by Joshua Higginbotham
Functional Python for the ETL Developer by Joshua Higginbotham

Methods similar to method __init__ in Python

There are some methods similar to the method

__init__

in Python that are applied to initialize objects:


class Person: def __init__(self, name, age): self.name = name self.age = age person1 = Person("John Doe", 30) person1.setattr("age", 40) print(person1.age) # 40


class Person: def __init__(self, name, age, **kwargs): self.name = name self.age = age self.kwargs = kwargs person1 = Person("John Doe", 30, height=180) print(person1.height) # 180

Conclusion

This article had a lot of information about the init method in Python. Here is a quick summary

I’m writing some code that takes a filename, opens the file, and parses out some data. I’d like to do this in a class. The following code works:


class MyClass(): def __init__(self, filename): self.filename = filename self.stat1 = None self.stat2 = None self.stat3 = None self.stat4 = None self.stat5 = None def parse_file(): #do some parsing self.stat1 = result_from_parse1 self.stat2 = result_from_parse2 self.stat3 = result_from_parse3 self.stat4 = result_from_parse4 self.stat5 = result_from_parse5 parse_file()

But it involves me putting all of the parsing machinery in the scope of the

__init__

function for my class. That looks fine now for this simplified code, but the function

parse_file

has quite a few levels of indention as well. I’d prefer to define the function

parse_file()

as a class function like below:


class MyClass(): def __init__(self, filename): self.filename = filename self.stat1 = None self.stat2 = None self.stat3 = None self.stat4 = None self.stat5 = None parse_file() def parse_file(): #do some parsing self.stat1 = result_from_parse1 self.stat2 = result_from_parse2 self.stat3 = result_from_parse3 self.stat4 = result_from_parse4 self.stat5 = result_from_parse5

Of course this code doesn’t work because the function

parse_file()

is not within the scope of the

__init__

function. Is there a way to call a class function from within

__init__

of that class? Or am I thinking about this the wrong way?

OOP part - 35 |  Built in Attributes(__bases___) of class in python with example | MUST WATCH |
OOP part – 35 | Built in Attributes(__bases___) of class in python with example | MUST WATCH |

When to Use __new__ in Python

You should use

__new__

when you need to control the creation of the object. For example, you might want to use

__new__

to:

Python __init__ Method Defined

In Python,

__init__

is an instance method that initializes a newly created object. It takes the object as its first argument followed by additional arguments.

The method takes the object as its first argument (self), followed by any additional arguments that need to be passed to it.


class MyClass: def __init__(self, *args, **kwargs): self.attribute = 'value'

The

__init__

method is called after the object is created by the

__new__

method, and it initializes the object attributes with the values passed as arguments.

Defining __init__
Defining __init__

Keywords searched by users: init function in python

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