How to Creating A Custom User Model in Django

How do I fully replace the username field with an email field for Django authentication?

This post explains step-by-step how to create a custom User model in Django so that an email address can be used as the primary user identifier instead of a username for authentication.

Keep in mind that the process outlined in this post requires significant changes to the database schema. Because of this, it's only recommended for new projects. If this is for an existing legacy project, you'll need to follow a different set of steps. For more on this, review the Migrating to a Custom User Model Mid-project in Django article.

Objectives

By the end of this article, you should be able to:

1. Describe the difference between AbstractUser and AbstractBaseUser
2. Explain why you should set up a custom User model when starting a new Django project
3. Start a new Django project with a custom User model
4. Use an email address as the primary user identifier instead of a username for authentication
5. Practice test-first development while implementing a custom User model

AbstractUser vs AbstractBaseUser

The default User model in Django uses a username to uniquely identify a user during authentication. If you'd rather use an email address, you'll need to create a custom User model by either subclassing AbstractUser or AbstractBaseUser.

Options:

1. AbstractUser: Use this option if you are happy with the existing fields on the User model and just want to remove the username field.
2. AbstractBaseUser: Use this option if you want to start from scratch by creating your own, completely new User model.

We'll look at both options, AbstractUser and AbstractBaseUser, in this post.

The steps are the same for each:

1. Create a custom User model and Manager
2. Update settings.py
3. Customize the UserCreationForm and UserChangeForm forms
4. Update the admin

It's highly recommended to set up a custom User model when starting a new Django project. Without it, you will need to create another model (like UserProfile) and link it to the Django User model with a OneToOneField if you want to add new fields to the User model.

Project Setup

Start by creating a new Django project along with a users app:

$ mkdir django-custom-user-model && cd django-custom-user-model
$ python3 -m venv env
$ source env/bin/activate

(env)$ pip install Django==3.2.2
(env)$ django-admin startproject hello_django .
(env)$ python manage.py startapp users

Feel free to swap out virtualenv and Pip for Poetry or Pipenv. For more, review Modern Python Environments.

DO NOT apply the migrations. Remember: You must create the custom User model before you apply your first migration.

Add the new app to the INSTALLED_APPS list in settings.py:

INSTALLED_APPS = [
    'django.contrib.admin',
    'django.contrib.auth',
    'django.contrib.contenttypes',
    'django.contrib.sessions',
    'django.contrib.messages',
    'django.contrib.staticfiles',

    'users',
]

Tests

Let's take a test-first approach:

from django.contrib.auth import get_user_model
from django.test import TestCase


class UsersManagersTests(TestCase):

    def test_create_user(self):
        User = get_user_model()
        user = User.objects.create_user(email='normal@user.com', password='foo')
        self.assertEqual(user.email, 'normal@user.com')
        self.assertTrue(user.is_active)
        self.assertFalse(user.is_staff)
        self.assertFalse(user.is_superuser)
        try:
            # username is None for the AbstractUser option
            # username does not exist for the AbstractBaseUser option
            self.assertIsNone(user.username)
        except AttributeError:
            pass
        with self.assertRaises(TypeError):
            User.objects.create_user()
        with self.assertRaises(TypeError):
            User.objects.create_user(email='')
        with self.assertRaises(ValueError):
            User.objects.create_user(email='', password="foo")

    def test_create_superuser(self):
        User = get_user_model()
        admin_user = User.objects.create_superuser(email='super@user.com', password='foo')
        self.assertEqual(admin_user.email, 'super@user.com')
        self.assertTrue(admin_user.is_active)
        self.assertTrue(admin_user.is_staff)
        self.assertTrue(admin_user.is_superuser)
        try:
            # username is None for the AbstractUser option
            # username does not exist for the AbstractBaseUser option
            self.assertIsNone(admin_user.username)
        except AttributeError:
            pass
        with self.assertRaises(ValueError):
            User.objects.create_superuser(
                email='super@user.com', password='foo', is_superuser=False)

Add the specs to users/tests.py, and then make sure the tests fail.

Model Manager

First, we need to add a custom Manager, by subclassing BaseUserManager, that uses an email as the unique identifier instead of a username.

Create a managers.py file in the "users" directory:

from django.contrib.auth.base_user import BaseUserManager
from django.utils.translation import ugettext_lazy as _


class CustomUserManager(BaseUserManager):
    """
    Custom user model manager where email is the unique identifiers
    for authentication instead of usernames.
    """
    def create_user(self, email, password, **extra_fields):
        """
        Create and save a User with the given email and password.
        """
        if not email:
            raise ValueError(_('The Email must be set'))
        email = self.normalize_email(email)
        user = self.model(email=email, **extra_fields)
        user.set_password(password)
        user.save()
        return user

    def create_superuser(self, email, password, **extra_fields):
        """
        Create and save a SuperUser with the given email and password.
        """
        extra_fields.setdefault('is_staff', True)
        extra_fields.setdefault('is_superuser', True)
        extra_fields.setdefault('is_active', True)

        if extra_fields.get('is_staff') is not True:
            raise ValueError(_('Superuser must have is_staff=True.'))
        if extra_fields.get('is_superuser') is not True:
            raise ValueError(_('Superuser must have is_superuser=True.'))
        return self.create_user(email, password, **extra_fields)

User Model

Decide which option you'd like to use: subclassing AbstractUser or AbstractBaseUser.

AbstractUser

Update users/models.py:

from django.contrib.auth.models import AbstractUser
from django.db import models
from django.utils.translation import ugettext_lazy as _

from .managers import CustomUserManager


class CustomUser(AbstractUser):
    username = None
    email = models.EmailField(_('email address'), unique=True)

    USERNAME_FIELD = 'email'
    REQUIRED_FIELDS = []

    objects = CustomUserManager()

    def __str__(self):
        return self.email

Here, we:

1. Created a new class called CustomUser that subclasses AbstractUser
2. Removed the username field
3. Made the email field required and unique
4. Set the USERNAME_FIELD -- which defines the unique identifier for the User model -- to email
5. Specified that all objects for the class come from the CustomUserManager

AbstractBaseUser

Update users/models.py:

from django.contrib.auth.models import AbstractBaseUser, PermissionsMixin
from django.db import models
from django.utils import timezone
from django.utils.translation import gettext_lazy as _

from .managers import CustomUserManager


class CustomUser(AbstractBaseUser, PermissionsMixin):
    email = models.EmailField(_('email address'), unique=True)
    is_staff = models.BooleanField(default=False)
    is_active = models.BooleanField(default=True)
    date_joined = models.DateTimeField(default=timezone.now)

    USERNAME_FIELD = 'email'
    REQUIRED_FIELDS = []

    objects = CustomUserManager()

    def __str__(self):
        return self.email

Here, we:

1. Created a new class called CustomUser that subclasses AbstractBaseUser
2. Added fields for email, is_staff, is_active, and date_joined
3. Set the USERNAME_FIELD -- which defines the unique identifier for the User model -- to email
4. Specified that all objects for the class come from the CustomUserManager

Settings

Add the following line to the settings.py file so that Django knows to use the new User class:

AUTH_USER_MODEL = 'users.CustomUser'

Now, you can create and apply the migrations, which will create a new database that uses the custom User model. Before we do that, let's look at what the migration will actually look like without creating the migration file, with the --dry-run flag:

(env)$ python manage.py makemigrations --dry-run --verbosity 3

You should see something similar to:

# Generated by Django 3.2.2 on 2021-05-12 20:43

from django.db import migrations, models
import django.utils.timezone


class Migration(migrations.Migration):

    initial = True

    dependencies = [
        ('auth', '0012_alter_user_first_name_max_length'),
    ]

    operations = [
        migrations.CreateModel(
            name='CustomUser',
            fields=[
                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
                ('password', models.CharField(max_length=128, verbose_name='password')),
                ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')),
                ('is_superuser', models.BooleanField(default=False, help_text='Designates that this user has all permissions without explicitly assigning them.', verbose_name='superuser status')),
                ('first_name', models.CharField(blank=True, max_length=150, verbose_name='first name')),
                ('last_name', models.CharField(blank=True, max_length=150, verbose_name='last name')),
                ('is_staff', models.BooleanField(default=False, help_text='Designates whether the user can log into this admin site.', verbose_name='staff status')),
                ('is_active', models.BooleanField(default=True, help_text='Designates whether this user should be treated as active. Unselect this instead of deleting accounts.', verbose_name='active')),
                ('date_joined', models.DateTimeField(default=django.utils.timezone.now, verbose_name='date joined')),
                ('email', models.EmailField(max_length=254, unique=True, verbose_name='email address')),
                ('groups', models.ManyToManyField(blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', related_name='user_set', related_query_name='user', to='auth.Group', verbose_name='groups')),
                ('user_permissions', models.ManyToManyField(blank=True, help_text='Specific permissions for this user.', related_name='user_set', related_query_name='user', to='auth.Permission', verbose_name='user permissions')),
            ],
            options={
                'verbose_name': 'user',
                'verbose_name_plural': 'users',
                'abstract': False,
            },
        ),
    ]

If you went the AbstractBaseUser route, you won't have fields for first_name or last_name. Why?

Make sure the migration does not include a username field. Then, create and apply the migration:

(env)$ python manage.py makemigrations
(env)$ python manage.py migrate

View the schema:

$ sqlite3 db.sqlite3

SQLite version 3.28.0 2019-04-15 14:49:49
Enter ".help" for usage hints.

sqlite> .tables

auth_group                         django_migrations
auth_group_permissions             django_session
auth_permission                    users_customuser
django_admin_log                   users_customuser_groups
django_content_type                users_customuser_user_permissions

sqlite> .schema users_customuser

CREATE TABLE IF NOT EXISTS "users_customuser" (
  "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT,
  "password" varchar(128) NOT NULL,
  "last_login" datetime NULL,
  "is_superuser" bool NOT NULL,
  "first_name" varchar(150) NOT NULL,
  "last_name" varchar(150) NOT NULL,
  "is_staff" bool NOT NULL,
  "is_active" bool NOT NULL,
  "date_joined" datetime NOT NULL,
  "email" varchar(254) NOT NULL UNIQUE
);

If you went the AbstractBaseUser route, why is last_login part of the model?

You can now reference the User model with either get_user_model() or settings.AUTH_USER_MODEL. Refer to Referencing the User model from the official docs for more info.

Also, when you create a superuser, you should be prompted to enter an email rather than a username:

(env)$ python manage.py createsuperuser

Email address: test@test.com
Password:
Password (again):
Superuser created successfully.

Make sure the tests pass:

(env)$ python manage.py test

Creating test database for alias 'default'...
System check identified no issues (0 silenced).
..
----------------------------------------------------------------------
Ran 2 tests in 0.282s

OK
Destroying test database for alias 'default'...

Forms

Next, let's subclass the UserCreationForm and UserChangeForm forms so that they use the new CustomUser model.

Create a new file in "users" called forms.py:

from django.contrib.auth.forms import UserCreationForm, UserChangeForm

from .models import CustomUser


class CustomUserCreationForm(UserCreationForm):

    class Meta:
        model = CustomUser
        fields = ('email',)


class CustomUserChangeForm(UserChangeForm):

    class Meta:
        model = CustomUser
        fields = ('email',)

Admin

Tell the admin to use these forms by subclassing UserAdmin in users/admin.py:

from django.contrib import admin
from django.contrib.auth.admin import UserAdmin

from .forms import CustomUserCreationForm, CustomUserChangeForm
from .models import CustomUser


class CustomUserAdmin(UserAdmin):
    add_form = CustomUserCreationForm
    form = CustomUserChangeForm
    model = CustomUser
    list_display = ('email', 'is_staff', 'is_active',)
    list_filter = ('email', 'is_staff', 'is_active',)
    fieldsets = (
        (None, {'fields': ('email', 'password')}),
        ('Permissions', {'fields': ('is_staff', 'is_active')}),
    )
    add_fieldsets = (
        (None, {
            'classes': ('wide',),
            'fields': ('email', 'password1', 'password2', 'is_staff', 'is_active')}
        ),
    )
    search_fields = ('email',)
    ordering = ('email',)


admin.site.register(CustomUser, CustomUserAdmin)

That's it. Run the server and log in to the admin site. You should be able to add and change users like normal.

Conclusion

In this post, we looked at how to create a custom User model so that an email address can be used as the primary user identifier instead of a username for authentication.

You can find the final code for both options, AbstractUser and AbstractBaseUser, in the django-custom-user-model repo. The final code examples include the templates, views, and URLs required for user authentication as well.

Want to learn more about customizing the Django user model? Check out the following resources:

1. Options & Objects: Customizing the Django User Model
2. How to Extend Django User Model
3. Getting the Most Out of Django's User Model (video)
4. Customizing authentication in Django
5. Django: How to Extend The User Model (aka Custom User Model)

Original article source at: https://testdriven.io

#django #model 

What is GEEK

Buddha Community

Django admin full Customization step by step

Welcome to my blog , hey everyone in this article you learn how to customize the Django app and view in the article you will know how to register  and unregister  models from the admin view how to add filtering how to add a custom input field, and a button that triggers an action on all objects and even how to change the look of your app and page using the Django suit package let’s get started.

Database

Custom Titles of Django Admin

Exclude in Django Admin

Fields in Django Admin

#django #create super user django #customize django admin dashboard #django admin #django admin custom field display #django admin customization #django admin full customization #django admin interface #django admin register all models #django customization

PyTumblr: A Python Tumblr API v2 Client

PyTumblr

Installation

Install via pip:

$ pip install pytumblr

Install from source:

$ git clone https://github.com/tumblr/pytumblr.git
$ cd pytumblr
$ python setup.py install

Usage

Create a client

A pytumblr.TumblrRestClient is the object you'll make all of your calls to the Tumblr API through. Creating one is this easy:

client = pytumblr.TumblrRestClient(
    '<consumer_key>',
    '<consumer_secret>',
    '<oauth_token>',
    '<oauth_secret>',
)

client.info() # Grabs the current user information

Two easy ways to get your credentials to are:

1. The built-in interactive_console.py tool (if you already have a consumer key & secret)
2. The Tumblr API console at https://api.tumblr.com/console
3. Get sample login code at https://api.tumblr.com/console/calls/user/info

Supported Methods

User Methods

client.info() # get information about the authenticating user
client.dashboard() # get the dashboard for the authenticating user
client.likes() # get the likes for the authenticating user
client.following() # get the blogs followed by the authenticating user

client.follow('codingjester.tumblr.com') # follow a blog
client.unfollow('codingjester.tumblr.com') # unfollow a blog

client.like(id, reblogkey) # like a post
client.unlike(id, reblogkey) # unlike a post

Blog Methods

client.blog_info(blogName) # get information about a blog
client.posts(blogName, **params) # get posts for a blog
client.avatar(blogName) # get the avatar for a blog
client.blog_likes(blogName) # get the likes on a blog
client.followers(blogName) # get the followers of a blog
client.blog_following(blogName) # get the publicly exposed blogs that [blogName] follows
client.queue(blogName) # get the queue for a given blog
client.submission(blogName) # get the submissions for a given blog

Post Methods

Creating posts

PyTumblr lets you create all of the various types that Tumblr supports. When using these types there are a few defaults that are able to be used with any post type.

The default supported types are described below.

• state - a string, the state of the post. Supported types are published, draft, queue, private
• tags - a list, a list of strings that you want tagged on the post. eg: ["testing", "magic", "1"]
• tweet - a string, the string of the customized tweet you want. eg: "Man I love my mega awesome post!"
• date - a string, the customized GMT that you want
• format - a string, the format that your post is in. Support types are html or markdown
• slug - a string, the slug for the url of the post you want

We'll show examples throughout of these default examples while showcasing all the specific post types.

Creating a photo post

Creating a photo post supports a bunch of different options plus the described default options * caption - a string, the user supplied caption * link - a string, the "click-through" url for the photo * source - a string, the url for the photo you want to use (use this or the data parameter) * data - a list or string, a list of filepaths or a single file path for multipart file upload

#Creates a photo post using a source URL
client.create_photo(blogName, state="published", tags=["testing", "ok"],
                    source="https://68.media.tumblr.com/b965fbb2e501610a29d80ffb6fb3e1ad/tumblr_n55vdeTse11rn1906o1_500.jpg")

#Creates a photo post using a local filepath
client.create_photo(blogName, state="queue", tags=["testing", "ok"],
                    tweet="Woah this is an incredible sweet post [URL]",
                    data="/Users/johnb/path/to/my/image.jpg")

#Creates a photoset post using several local filepaths
client.create_photo(blogName, state="draft", tags=["jb is cool"], format="markdown",
                    data=["/Users/johnb/path/to/my/image.jpg", "/Users/johnb/Pictures/kittens.jpg"],
                    caption="## Mega sweet kittens")

Creating a text post

Creating a text post supports the same options as default and just a two other parameters * title - a string, the optional title for the post. Supports markdown or html * body - a string, the body of the of the post. Supports markdown or html

#Creating a text post
client.create_text(blogName, state="published", slug="testing-text-posts", title="Testing", body="testing1 2 3 4")

Creating a quote post

Creating a quote post supports the same options as default and two other parameter * quote - a string, the full text of the qote. Supports markdown or html * source - a string, the cited source. HTML supported

#Creating a quote post
client.create_quote(blogName, state="queue", quote="I am the Walrus", source="Ringo")

Creating a link post

• title - a string, the title of post that you want. Supports HTML entities.
• url - a string, the url that you want to create a link post for.
• description - a string, the desciption of the link that you have

#Create a link post
client.create_link(blogName, title="I like to search things, you should too.", url="https://duckduckgo.com",
                   description="Search is pretty cool when a duck does it.")

Creating a chat post

Creating a chat post supports the same options as default and two other parameters * title - a string, the title of the chat post * conversation - a string, the text of the conversation/chat, with diablog labels (no html)

#Create a chat post
chat = """John: Testing can be fun!
Renee: Testing is tedious and so are you.
John: Aw.
"""
client.create_chat(blogName, title="Renee just doesn't understand.", conversation=chat, tags=["renee", "testing"])

Creating an audio post

Creating an audio post allows for all default options and a has 3 other parameters. The only thing to keep in mind while dealing with audio posts is to make sure that you use the external_url parameter or data. You cannot use both at the same time. * caption - a string, the caption for your post * external_url - a string, the url of the site that hosts the audio file * data - a string, the filepath of the audio file you want to upload to Tumblr

#Creating an audio file
client.create_audio(blogName, caption="Rock out.", data="/Users/johnb/Music/my/new/sweet/album.mp3")

#lets use soundcloud!
client.create_audio(blogName, caption="Mega rock out.", external_url="https://soundcloud.com/skrillex/sets/recess")

Creating a video post

Creating a video post allows for all default options and has three other options. Like the other post types, it has some restrictions. You cannot use the embed and data parameters at the same time. * caption - a string, the caption for your post * embed - a string, the HTML embed code for the video * data - a string, the path of the file you want to upload

#Creating an upload from YouTube
client.create_video(blogName, caption="Jon Snow. Mega ridiculous sword.",
                    embed="http://www.youtube.com/watch?v=40pUYLacrj4")

#Creating a video post from local file
client.create_video(blogName, caption="testing", data="/Users/johnb/testing/ok/blah.mov")

Editing a post

Updating a post requires you knowing what type a post you're updating. You'll be able to supply to the post any of the options given above for updates.

client.edit_post(blogName, id=post_id, type="text", title="Updated")
client.edit_post(blogName, id=post_id, type="photo", data="/Users/johnb/mega/awesome.jpg")

Reblogging a Post

Reblogging a post just requires knowing the post id and the reblog key, which is supplied in the JSON of any post object.

client.reblog(blogName, id=125356, reblog_key="reblog_key")

Deleting a post

Deleting just requires that you own the post and have the post id

client.delete_post(blogName, 123456) # Deletes your post :(

A note on tags: When passing tags, as params, please pass them as a list (not a comma-separated string):

client.create_text(blogName, tags=['hello', 'world'], ...)

Getting notes for a post

In order to get the notes for a post, you need to have the post id and the blog that it is on.

data = client.notes(blogName, id='123456')

The results include a timestamp you can use to make future calls.

data = client.notes(blogName, id='123456', before_timestamp=data["_links"]["next"]["query_params"]["before_timestamp"])

Tagged Methods

# get posts with a given tag
client.tagged(tag, **params)

Using the interactive console

This client comes with a nice interactive console to run you through the OAuth process, grab your tokens (and store them for future use).

You'll need pyyaml installed to run it, but then it's just:

$ python interactive-console.py

and away you go! Tokens are stored in ~/.tumblr and are also shared by other Tumblr API clients like the Ruby client.

Running tests

The tests (and coverage reports) are run with nose, like this:

python setup.py test

Author: tumblr
Source Code: https://github.com/tumblr/pytumblr
License: Apache-2.0 license

#python #api 

How model queries work in Django

How model queries work in Django

Welcome to my blog, hey everyone in this article we are going to be working with queries in Django so for any web app that you build your going to want to write a query so you can retrieve information from your database so in this article I’ll be showing you all the different ways that you can write queries and it should cover about 90% of the cases that you’ll have when you’re writing your code the other 10% depend on your specific use case you may have to get more complicated but for the most part what I cover in this article should be able to help you so let’s start with the model that I have I’ve already created it.

**Read More : **How to make Chatbot in Python.

Read More : Django Admin Full Customization step by step

let’s just get into this diagram that I made so in here:

Describe each parameter in Django querset

we’re making a simple query for the myModel table so we want to pull out all the information in the database so we have this variable which is gonna hold a return value and we have our myModel models so this is simply the myModel model name so whatever you named your model just make sure you specify that and we’re gonna access the objects attribute once we get that object’s attribute we can simply use the all method and this will return all the information in the database so we’re gonna start with all and then we will go into getting single items filtering that data and go to our command prompt.

Here and we’ll actually start making our queries from here to do this let’s just go ahead and run** Python manage.py shell** and I am in my project file so make sure you’re in there when you start and what this does is it gives us an interactive shell to actually start working with our data so this is a lot like the Python shell but because we did manage.py it allows us to do things a Django way and actually query our database now open up the command prompt and let’s go ahead and start making our first queries.

#django #django model queries #django orm #django queries #django query #model django query #model query #query with django

Exploring Mutable and Immutable in Python

In this Python article, let's learn about Mutable and Immutable in Python. 

Mutable and Immutable in Python

Mutable is a fancy way of saying that the internal state of the object is changed/mutated. So, the simplest definition is: An object whose internal state can be changed is mutable. On the other hand, immutable doesn’t allow any change in the object once it has been created.

Both of these states are integral to Python data structure. If you want to become more knowledgeable in the entire Python Data Structure, take this free course which covers multiple data structures in Python including tuple data structure which is immutable. You will also receive a certificate on completion which is sure to add value to your portfolio.

Mutable Definition

Mutable is when something is changeable or has the ability to change. In Python, ‘mutable’ is the ability of objects to change their values. These are often the objects that store a collection of data.

Immutable Definition

Immutable is the when no change is possible over time. In Python, if the value of an object cannot be changed over time, then it is known as immutable. Once created, the value of these objects is permanent.

List of Mutable and Immutable objects

Objects of built-in type that are mutable are:

• Lists
• Sets
• Dictionaries
• User-Defined Classes (It purely depends upon the user to define the characteristics) 

Objects of built-in type that are immutable are:

• Numbers (Integer, Rational, Float, Decimal, Complex & Booleans)
• Strings
• Tuples
• Frozen Sets
• User-Defined Classes (It purely depends upon the user to define the characteristics)

Object mutability is one of the characteristics that makes Python a dynamically typed language. Though Mutable and Immutable in Python is a very basic concept, it can at times be a little confusing due to the intransitive nature of immutability.

Objects in Python

In Python, everything is treated as an object. Every object has these three attributes:

• Identity – This refers to the address that the object refers to in the computer’s memory.
• Type – This refers to the kind of object that is created. For example- integer, list, string etc. 
• Value – This refers to the value stored by the object. For example – List=[1,2,3] would hold the numbers 1,2 and 3

While ID and Type cannot be changed once it’s created, values can be changed for Mutable objects.

Check out this free python certificate course to get started with Python.

Mutable Objects in Python

I believe, rather than diving deep into the theory aspects of mutable and immutable in Python, a simple code would be the best way to depict what it means in Python. Hence, let us discuss the below code step-by-step:

#Creating a list which contains name of Indian cities  

cities = [‘Delhi’, ‘Mumbai’, ‘Kolkata’]

# Printing the elements from the list cities, separated by a comma & space

for city in cities:
		print(city, end=’, ’)

Output [1]: Delhi, Mumbai, Kolkata

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [2]: 0x1691d7de8c8

#Adding a new city to the list cities

cities.append(‘Chennai’)

#Printing the elements from the list cities, separated by a comma & space 

for city in cities:
	print(city, end=’, ’)

Output [3]: Delhi, Mumbai, Kolkata, Chennai

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [4]: 0x1691d7de8c8

The above example shows us that we were able to change the internal state of the object ‘cities’ by adding one more city ‘Chennai’ to it, yet, the memory address of the object did not change. This confirms that we did not create a new object, rather, the same object was changed or mutated. Hence, we can say that the object which is a type of list with reference variable name ‘cities’ is a MUTABLE OBJECT.

Let us now discuss the term IMMUTABLE. Considering that we understood what mutable stands for, it is obvious that the definition of immutable will have ‘NOT’ included in it. Here is the simplest definition of immutable– An object whose internal state can NOT be changed is IMMUTABLE.

Again, if you try and concentrate on different error messages, you have encountered, thrown by the respective IDE; you use you would be able to identify the immutable objects in Python. For instance, consider the below code & associated error message with it, while trying to change the value of a Tuple at index 0. 

#Creating a Tuple with variable name ‘foo’

foo = (1, 2)

#Changing the index[0] value from 1 to 3

foo[0] = 3
	
TypeError: 'tuple' object does not support item assignment 

Immutable Objects in Python

Once again, a simple code would be the best way to depict what immutable stands for. Hence, let us discuss the below code step-by-step:

#Creating a Tuple which contains English name of weekdays

weekdays = ‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’

# Printing the elements of tuple weekdays

print(weekdays)

Output [1]:  (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [2]: 0x1691cc35090

#tuples are immutable, so you cannot add new elements, hence, using merge of tuples with the # + operator to add a new imaginary day in the tuple ‘weekdays’

weekdays  +=  ‘Pythonday’,

#Printing the elements of tuple weekdays

print(weekdays)

Output [3]: (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Pythonday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [4]: 0x1691cc8ad68

This above example shows that we were able to use the same variable name that is referencing an object which is a type of tuple with seven elements in it. However, the ID or the memory location of the old & new tuple is not the same. We were not able to change the internal state of the object ‘weekdays’. The Python program manager created a new object in the memory address and the variable name ‘weekdays’ started referencing the new object with eight elements in it.  Hence, we can say that the object which is a type of tuple with reference variable name ‘weekdays’ is an IMMUTABLE OBJECT.

Also Read: Understanding the Exploratory Data Analysis (EDA) in Python

Where can you use mutable and immutable objects:

Mutable objects can be used where you want to allow for any updates. For example, you have a list of employee names in your organizations, and that needs to be updated every time a new member is hired. You can create a mutable list, and it can be updated easily.

Immutability offers a lot of useful applications to different sensitive tasks we do in a network centred environment where we allow for parallel processing. By creating immutable objects, you seal the values and ensure that no threads can invoke overwrite/update to your data. This is also useful in situations where you would like to write a piece of code that cannot be modified. For example, a debug code that attempts to find the value of an immutable object.

Watch outs:  Non transitive nature of Immutability:

OK! Now we do understand what mutable & immutable objects in Python are. Let’s go ahead and discuss the combination of these two and explore the possibilities. Let’s discuss, as to how will it behave if you have an immutable object which contains the mutable object(s)? Or vice versa? Let us again use a code to understand this behaviour–

#creating a tuple (immutable object) which contains 2 lists(mutable) as it’s elements

#The elements (lists) contains the name, age & gender 

person = (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the tuple

print(person)

Output [1]: (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [2]: 0x1691ef47f88

#Changing the age for the 1st element. Selecting 1st element of tuple by using indexing [0] then 2nd element of the list by using indexing [1] and assigning a new value for age as 4

person[0][1] = 4

#printing the updated tuple

print(person)

Output [3]: (['Ayaan', 4, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [4]: 0x1691ef47f88

In the above code, you can see that the object ‘person’ is immutable since it is a type of tuple. However, it has two lists as it’s elements, and we can change the state of lists (lists being mutable). So, here we did not change the object reference inside the Tuple, but the referenced object was mutated.

Also Read: Real-Time Object Detection Using TensorFlow

Same way, let’s explore how it will behave if you have a mutable object which contains an immutable object? Let us again use a code to understand the behaviour–

#creating a list (mutable object) which contains tuples(immutable) as it’s elements

list1 = [(1, 2, 3), (4, 5, 6)]

#printing the list

print(list1)

Output [1]: [(1, 2, 3), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [2]: 0x1691d5b13c8	

#changing object reference at index 0

list1[0] = (7, 8, 9)

#printing the list

Output [3]: [(7, 8, 9), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [4]: 0x1691d5b13c8

As an individual, it completely depends upon you and your requirements as to what kind of data structure you would like to create with a combination of mutable & immutable objects. I hope that this information will help you while deciding the type of object you would like to select going forward.

Before I end our discussion on IMMUTABILITY, allow me to use the word ‘CAVITE’ when we discuss the String and Integers. There is an exception, and you may see some surprising results while checking the truthiness for immutability. For instance:
#creating an object of integer type with value 10 and reference variable name ‘x’ 

x = 10
 

#printing the value of ‘x’

print(x)

Output [1]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(x)))

Output [2]: 0x538fb560

#creating an object of integer type with value 10 and reference variable name ‘y’

y = 10

#printing the value of ‘y’

print(y)

Output [3]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(y)))

Output [4]: 0x538fb560

As per our discussion and understanding, so far, the memory address for x & y should have been different, since, 10 is an instance of Integer class which is immutable. However, as shown in the above code, it has the same memory address. This is not something that we expected. It seems that what we have understood and discussed, has an exception as well.

Quick check – Python Data Structures

Immutability of Tuple

Tuples are immutable and hence cannot have any changes in them once they are created in Python. This is because they support the same sequence operations as strings. We all know that strings are immutable. The index operator will select an element from a tuple just like in a string. Hence, they are immutable.

Exceptions in immutability

Like all, there are exceptions in the immutability in python too. Not all immutable objects are really mutable. This will lead to a lot of doubts in your mind. Let us just take an example to understand this.

Consider a tuple ‘tup’.

Now, if we consider tuple tup = (‘GreatLearning’,[4,3,1,2]) ;

We see that the tuple has elements of different data types. The first element here is a string which as we all know is immutable in nature. The second element is a list which we all know is mutable. Now, we all know that the tuple itself is an immutable data type. It cannot change its contents. But, the list inside it can change its contents. So, the value of the Immutable objects cannot be changed but its constituent objects can. change its value.

FAQs

1. Difference between mutable vs immutable in Python?

Mutable Object	Immutable Object
State of the object can be modified after it is created.	State of the object can’t be modified once it is created.
They are not thread safe.	They are thread safe
Mutable classes are not final.	It is important to make the class final before creating an immutable object.

2. What are the mutable and immutable data types in Python?

• Some mutable data types in Python are:

list, dictionary, set, user-defined classes.

• Some immutable data types are: 

int, float, decimal, bool, string, tuple, range.

3. Are lists mutable in Python?

Lists in Python are mutable data types as the elements of the list can be modified, individual elements can be replaced, and the order of elements can be changed even after the list has been created.
(Examples related to lists have been discussed earlier in this blog.)

4. Why are tuples called immutable types?

Tuple and list data structures are very similar, but one big difference between the data types is that lists are mutable, whereas tuples are immutable. The reason for the tuple’s immutability is that once the elements are added to the tuple and the tuple has been created; it remains unchanged.

A programmer would always prefer building a code that can be reused instead of making the whole data object again. Still, even though tuples are immutable, like lists, they can contain any Python object, including mutable objects.

5. Are sets mutable in Python?

A set is an iterable unordered collection of data type which can be used to perform mathematical operations (like union, intersection, difference etc.). Every element in a set is unique and immutable, i.e. no duplicate values should be there, and the values can’t be changed. However, we can add or remove items from the set as the set itself is mutable.

6. Are strings mutable in Python?

Strings are not mutable in Python. Strings are a immutable data types which means that its value cannot be updated.

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

#python 

Custom User model in Django

Behind the scenes, Django maintains a list of “authentication backends” that it checks for authentication. When somebody calls django.contrib.auth.authenticate() – as described in How to log a user in – Django tries authenticating across all of its authentication backends. If the first authentication method fails, Django tries the second one, and so on, until all backends have been attempted.

#django #authentication #python #custom-user-model #programming #development