Models

Masonite ORM
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2.0
Introduction
Installation
Orator To Masonite ORM
Other Features
Models
Models are the easiest way to interact with your tables. A model is a way for you to interact with a Python class in a simple and elegant way and have all the hard overhead stuff handled for you under the hood. A model can be used to query the data in the table or even create new records, fetch related records between tables and many other features.
Creating A Model
The first step in using models is actually creating them. You can scaffold out a model by using the command:
$ python masonite-orm model Post
You can use the --directory flag to specify the location of these models
This will create a post model like so:
from masoniteorm.models import Model
​
class Post(Model):
    """Post Model"""
    pass
From here you can do as basic or advanced queries as you want. You may need to configure your model based on your needs, though.
From here you can start querying your records:
user = User.first()
users = User.all()
active_users = User.where('active', 1).first()
We'll talk more about setting up your model below
Conventions And Configuration
Masonite ORM makes a few assumptions in order to have the easiest interface for your models.
The first is table names. Table names are assumed to be the plural of your model name. If you have a User model then the users table is assumed and if you have a model like Company then the companies table is assumed. You can realize that Masonite ORM is smart enough to know that the plural of Company is not Companys so don't worry about Masonite not being able to pick up your table name.
Table Name
If your table name is something other than the plural of your models you can change it using the __table__ attribute:
class Clients:
  __table__ = "users"
Primary Keys
The next thing Masonite assumes is the primary key. Masonite ORM assumes that the primary key name is id. You can change the primary key name easily:
class Clients:
  __primary_key__ = "user_id"
Connections
The next thing Masonite assumes is that you are using the default connection you setup in your configuration settings. You can also change this on the model:
class Clients:
  __connection__ = "staging"
Mass Assignment
By default, Masonite ORM protects against mass assignment to help prevent users from changing values on your tables you didn't want.
This is used in the create and update methods. You can set the columns you want to be mass assignable easily:
class Clients:
  __fillable__ = ["email", "active", "password"]
Guarded attributes can be used to specify those columns which are not mass assignable. You can prevent some of the fields from being mass-assigned:
class Clients:
  __guarded__ = ["password"]
Timestamps
Masonite also assumes you have created_at and updated_at columns on your table. You can easily disable this behavior:
class Clients:
  __timestamps__ = False
Timezones
Models use UTC as the default timezone. You can change the timezones on your models using the __timezone__ attribute:
class User(Model):
    __timezone__ = "Europe/Paris"
Querying
Almost all of a model's querying methods are passed off to the query builder. If you would like to see all the methods available for the query builder, see the QueryBuilder documentation here.
Single results
A query result will either have 1 or more records. If your model result has a single record then the result will be the model instance. You can then access attributes on that model instance. Here's an example:
from app.models.User import User
​
user = User.first()
user.name #== 'Joe'
user.email #== '[email protected]'
You can also get a record by its primary key:
from app.models.User import User
​
user = User.find(1)
user.name #== 'Joe'
user.email #== '[email protected]'
Collections
If your model result returns several results then it will be wrapped in a collection instance which you can use to iterate over:
from app.models.User import User
​
users = User.where('active', 1).get()
for user in users:
  user.name #== 'Joe'
  user.active #== '1'
  user.email #== '[email protected]'
If you want to find a collection of records based on the models primary key you can pass a list to the find method:
users = User.find([1,2,3])
for users in users:
  user.name #== 'Joe'
  user.active #== '1'
  user.email #== '[email protected]'
The collection class also has some handy methods you can use to interact with your data:
user_emails = User.where('active', 1).get().pluck('email') #== Collection of email addresses
If you would like to see more methods available like pluck be sure to read the Collections documentation.
Deleting
You may also quickly delete records:
from app.models.User import User
​
user = User.delete(1)
This will delete the record based on the primary key value of 1.
You can also delete based on a query:
from app.models.User import User
​
user = User.where('active', 0).delete()
Sub-queries
You may also use sub-queries to do more advanced queries using lambda expressions:
from app.models.User import User
​
users = User.where(lambda q: q.where('active', 1).where_null('deleted_at'))
# == SELECT * FROM `users` WHERE (`active` = '1' AND `deleted_at` IS NULL)
Selecting
By default, Masonite ORM performs SELECT * queries. You can change this behavior in a few ways.
The first way is to specify a __selects__ attribute with a list of column names. You may use the as keyword to alias your columns directly from this list:
class Store(Model):
    __selects__ = ["username", "administrator as is_admin"]
Now when you query your model, these selects will automatically be included:
store.all() 
#== SELECT `username`, `administrator` as is_admin FROM `users`
Another way is directly on the all() method:
store.all(["username", "administrator as is_admin"]) 
#== SELECT `username`, `administrator` as is_admin FROM `users`
This will also work on the get method as well:
store.where("active", 1).get(["username", "administrator as is_admin"]) 
#== SELECT `username`, `administrator` as is_admin FROM `users` WHERE `active` = 1
Relationships
Another great feature, when using models, is to be able to relate several models together (like how tables can relate to each other).
Belongs To (One to One)
A belongs to relationship is a one-to-one relationship between 2 table records.
You can add a one-to-one relationship easily:
from masoniteorm.relationships import belongs_to
class User:
​
  @belongs_to
  def company(self):
    from app.models.Company import Company
    return Company
It will be assumed here that the primary key of the relationship here between users and companies is {method_name}_id -> id. You can change the relating columns if that is not the case:
from masoniteorm.relationships import belongs_to
class User:
​
  @belongs_to('company_id', 'primary_key_id')
  def company(self):
    from app.models.Company import Company
    return Company
The first argument is always the column name on the current model's table and the second argument is the related field on the other table.
Has One (One to One)
In addition to belongs to, you can define the inverse of a belongs to:
from masoniteorm.relationships import has_one
class User:
​
  @has_one
  def company(self):
    from app.models.Company import Company
    return Company
Note the keys here are flipped. This is the only relationship that has the keys reversed
from masoniteorm.relationships import has_one
class User:
​
  @has_one('other_key', 'local_key')
  def company(self):
    from app.models.Company import Company
    return Company
Has Many (One to Many)
Another relationship is a one-to-many relationship where a record relates to many records, in another table:
from masoniteorm.relationships import has_many
class User:
​
  @has_many('company_id', 'id')
  def posts(self):
    from app.models.Post import Post
    return Post
The first argument is always the column name on the current model's table and the second argument is the related field on the other table.
Belongs to Many (Many To Many)
When working with many to many relationships, there is a pivot table in between that we must account for. Masonite ORM will handle this pivot table for you entirely under the hood.
In a real world situation you may have a scenario where you have products and stores.
Stores can have many products and also products can be in many stores. For example, a store can sell a red shirt and a red shirt can be sold in many different stores.
In the database this may look something like this:
stores
-------
id
name
​
product_store
--------------
id
store_id
product_id
​
product
--------
id
name
Notice that there is a pivot table called product_store that is in between stores and products.
We can use the belongs_to_many relationship to get all the products of a store easily. Let's start with the Store model:
from masoniteorm.models import Model
from masoniteorm.relationships import belongs_to_many
class Store(Model):
​
  @belongs_to_many
  def products(self):
    from app.models.Product import Product
    return Product
We can change the signature of the decorator to specify our foreign keys. In our example this would look like this:
from masoniteorm.models import Model
from masoniteorm.relationships import belongs_to_many
class Store(Model):
​
  @belongs_to_many("store_id", "product_id", "id", "id")
  def products(self):
    from app.models.Product import Product
    return Product
The first 2 keys are the foreign keys relating from stores to products through the pivot table and the last 2 keys are the foreign keys on the stores and products table.
Extra Fields On Pivot Table
If there are additional fields on your pivot table you need to fetch you can add the extra fields to the pivot record like so:
@belongs_to_many("store_id", "product_id", "id", "id", with_fields=['is_active'])
  def products(self):
    from app.models.Product import Product
    return Product
This will fetch the additional fields on the pivot table which we have access to.
Once we create this relationship we can start querying from stores directly to products:
store = Store.find(1)
for product in store.products:
    product.name #== Red Shirt
On each fetched record you can also get the pivot table and perform queries on it. This pivot record is the joining record inside the pivot table (product_store) where the store id and the product ID match. By default this attribute is pivot.
store = Store.find(1)
for product in store.products:
    product.pivot.updated_at #== 2021-01-01
    product.pivot.update({"updated_at": "2021-01-02"})
Changing Options
There are quite a few defaults that are created but there are ways to override them.
The first default is that the pivot table has a primary key called id. This is used to hydrate the record so you can update the pivot records. If you do not have a pivot primary key you can turn this feature off:
@belongs_to_many(pivot_id=None)
You can also change the ID to something other than id:
@belongs_to_many(pivot_id="other_column")
The next default is the name of the pivot table. The name of the pivot table is the singular form of both table names in alphabetical order. For example, if you are pivoting a persons table and a houses table then the table name is assumed to be house_person. You can change this naming:
@belongs_to_many(table="home_ownership")
The next default is that there are no timestamps (updated_at and created_at) on your pivot table. If you would like Masonite to manage timestamps you can:
@belongs_to_many(with_timestamps=True)
The next default is that the pivot attribute on your model will be called pivot. You can change this:
@belongs_to_many(attribute="ownerships")
Now when you need to get the pivot relationship you can do this through:
store = Store.find(1)
for product in store.products:
    product.ownerships.updated_at #== 2021-01-01
    product.ownerships.update({"updated_at": "2021-01-02"})
If you have timestamps on your pivot table, they must be called created_at and updated_at.
Has One Through (One to One)
The HasOneThrough relationship defines a relationship between 2 tables through an intermediate table. For example, you might have a Shipment that departs from a port and that Port is located in a specific Country.
So therefore, a Shipment could be related to a specific Country through a Port.
The schema would look something like this:
shipments
  shipment_id - integer - PK
  from_port_id - integer
​
ports
    port_id - integer - PK
    country_id - integer
    name - string
​
countries
    country_id - integer - PK
    name - string
To create this type of relationship you simply need to import the relationship class and return a list with 2 models. The first model is the distant table you want to join. In this case we are joining a shipment to countries so we put the Country as the first list element. The second element is the intermediate table that we need to get from Shipment to Country. In this case that is the Port model so we put that as the second element in the list.
from masoniteorm.relationships import has_one_through
​
class Shipment(Model):
​
    @has_one_through(
      "port_id", # The foreign key on the ports table
      "country_id", # The foreign key on the countries table
      "from_port_id", # The local key on the shipments table
      "country_id" # The local key on the ports table
    )
    def from_country(self):
        from app.models.Country import Country
        from app.models.Port import Port
​
        return [Country, Port]
You can then use this relationship like any other relationship:
shipment = Shipment.find(1)
shipment.from_country.name #== China
shipment.with_("from_country").first() #== eager load
shipment.has("from_country").first() #== existance check
Has Many Through (One to Many)
The HasManyThrough relationship defines a relationship between 2 tables through an intermediate table. For example, you might have a "user" that "likes" many "comments".
So in model terms, a User could be related to multiple Comment through a Like.
The schema would look something like this:
users
  user_id - integer - PK
  name - varchar
​
likes
    like_id - integer - PK
    user_id - integer - FK
    comment_id - comment_id
​
comments
    comment_id - integer - PK
    body - text
To create this type of relationship you simply need to import the relationship class and return a list with 2 models. The first model is the distant table you want to join. In this case we are joining a user to comments so we put the Comment as the first list element. The second element is the intermediate table that we need to get from User to Comment. In this case that is the Like model so we put that as the second element in the list.
from masoniteorm.relationships import has_many_through
​
class User(Model):
​
    @has_many_through(
      "like_id", # The foreign key on the intermediate (likes) table
      "comment_id", # The foreign key on the distant (comments) table
      "user_id", # The local key on the local (users) table
      "user_id" # The local key on the intermediate (likes) table
    )
    def liked_comments(self):
        from app.models.Comment import Comment
        from app.models.Like import Like
​
        return [Comment, Like]
You can then use this relationship like any other relationship:
user = User.find(1)
for comment in user.liked_comments:
  comment.body
user.with_("liked_comments").first() #== eager load comments
user.has("liked_comments").first() #== all users who have liked comments
Using Relationships
You can easily use relationships to get those related records. Here is an example on how to get the company record:
user = User.first()
user.company #== <app.models.Company>
user.company.name #== Masonite X Inc.
​
for post in user.posts:
    post.title
Getting The Relationship
Sometimes you want to be able to get the related query and append on to it on the fly.
For example, you may have a User and Phone relationship that looks like this:
class User(Model):
​
  @has_many
  def phones(self):
    return Phone
On the fly you may want to only get the active phones. You can do this by using the related() method on a model instance.
user = User.find(1)
​
# All users phones
phones = user.phones 
# All active users phones
active_phones = user.related("phones").where("active", 1).get()
With Count
The with_count method can be used to get the number of records in a relationship.
If you want to fetch the number of permissions a role has for example:
Role.with_count('permissions').get()
This will return a collection on each record with the {relationship}_count attribute. You can get this attribute like this:
roles = Role.with_count('permissions').get()
for role in roles:
  role.permissions_count #== 7
The method also works for single records
roles = Role.with_count('permissions').find(1).permissions_count #== 7
You may also optionally pass in a lambda function as a callable to pass in an additional query filter against the relationship
Role.with_count(
    'permissions',
    lambda q: (
        q.where_like("name", "%Creates%")
     )
Existence of a Relationship
Sometimes you'll need to get all records where a record has (or doesnt_have) a related record.
For example, you may want to get all users that have addresses:
users = User.has("addresses").get()
Or you may want to get all users that don't have addresses:
users = User.doesnt_have("addresses").get()
You can also perform another query on the relationship. For example, you may want all users that have addresses in the state of NY:
users = User.where_has("addresses", lambda query: (
  query.where("state", "NY")
)).get()
You may do this also with where_doesnt_have to get all users where they don't have addresses in the state of NY:
users = User.where_doesnt_have("addresses", lambda query: (
  query.where("state", "NY")
)).get()
You may also perform nested existence checks such as:
articles = Article.has("author.addresses", lambda query: (
  query.where("state", "NY")
)).get()
This would be how you would get all articles where the authors have addresses in NY.
Existence Conditionals
You also have the full support of doing OR conditionals by prefixing any of the methods with or_:
or_has
or_where_has
or_doesnt_have
or_where_doesnt_have
Polymorphic Relationships
Polymorphic relationships are when a single row can have a relationship to any other table. For example, a Like could be associated to a Comment or an Article.
Setup
On a polymorphic table, we typically have a record_type that repesents a table (or a model) and a record_id which represents the primary key value of the related table. Masonite ORM needs to know which record_type maps to which model.
We will create this map on our connection resolver. This is typically the DB variable in your database config file:
DB = ConnectionResolver().set_connection_details(DATABASES)
# ...
DB.morph_map({
    "Article": Article,
    "Comment": Comment,
})
One-to-One (Polymorphic)
When setting up a polymorphic relation it is very similiar to a normal relationship. The major difference is that you will have multiple models pointing to a single polymorphic table. In a polymorphic one-to-one relationship setup you would have a table setup like this:
comments
  - comment_id - PK
  - description - Varchar
​
article:
  - article_id - PK
  - title - Varchar
​
images
  - id - PK
  - record_type - Varchar
  - record_id - Unsigned Int
Notice the images table has record_type and record_id fields. These could be named anything but it should contain a varchar type column that will be used to map to a model as well as a column to put the foreign tables primary key value.
The models setup would look like this:
from masoniteorm.relatinships import morph_to, morph_many
​
class Image(Model):
​
  @morph_to
  def record(self):
    return
​
class Article(Model):
  
  @morph_one("record_type", "record_id")
  def image(self):
    return Like
​
class Comment(Model):
​
  @morph_one("record_type", "record_id")
  def image(self):
    return Like
One-to-Many (Polymorphic)
When setting up a polymorphic relation it is very similiar to a normal relationship. The major difference is that you will have multiple models pointing to a single polymorphic table. In a polymorphic one-to-many relationship setup you would have a table setup like this:
comments
  - comment_id - PK
  - description - Varchar
​
articles:
  - article_id - PK
  - title - Varchar
​
likes
  - id - PK
  - record_type - Varchar
  - record_id - Unsigned Int
Notice the likes table has record_type and record_id fields. These could be named anything but it should contain a varchar type column that will be used to map to a model as well as a column to put the foreign tables primary key value.
In this case the likes table still has one relationship to multiple models but the relating tables ("articles" and "comments" has many records to the likes table).
The models setup would look like this:
from masoniteorm.relatinships import morph_to, morph_many
​
class Likes(Model):
​
  @morph_to
  def record(self):
    return
​
class Article(Model):
  
  @morph_many("record_type", "record_id")
  def likes(self):
    return Like
​
class Comment(Model):
​
  @morph_many("record_type", "record_id")
  def likes(self):
    return Like
Morph To and Morph To Many
Masonite ORM has morph_to and a morph_to_many relationships. This is used to relate multiple records to the polymorphic table. These relationships are used on the polymorphic model to relate to the related models. The morph_to will return 1 result from the related model and the morph_to_many would return multiple.
The model example would look like this:
from masoniteorm.relatinships import morph_to, morph_many
​
class Likes(Model):
​
  @morph_to
  def record(self):
    return
​
class User(Model):
​
  @morph_to_many
  def record(self):
    return
Eager Loading
You can eager load any related records. Eager loading is when you preload model results instead of calling the database each time.
Let's take the example of fetching a user's phone:
users = User.all()
for user in users:
    user.phone
This will result in the query:
SELECT * FROM users
SELECT * FROM phones where user_id = 1
SELECT * FROM phones where user_id = 2
SELECT * FROM phones where user_id = 3
SELECT * FROM phones where user_id = 4
...
This will result in a lot of database calls. Now let's take a look at the same example but with eager loading:
users = User.with_('phone').get()
for user in users:
    user.phone
This would now result in this query:
SELECT * FROM users
SELECT * FROM phones where user_id IN (1, 2, 3, 4)
This resulted in only 2 queries. Any subsquent calls will pull in the result from the eager loaded result set.
You can also default all model calls with eager loading by using the __with__ attribute on the model:
from masoniteorm.models import Model
from masoniteorm.relationships import belongs_to_many
class Store(Model):
​
  __with__ = ['products']
​
  @belongs_to_many
  def products(self):
    from app.models.Product import Product
    return Product
Dynamic Relationships
You can change the relationship query that is ran on the fly using a dictionary and a lambda expression:
For example if you wanted to eager only the users phones that are activated:
users = User.with_({
  'phone': lambda q: q.where("activated", 1)
}).get()
for user in users:
    user.phone
You can use the with_ method in addition to other eager loads:
users = User.with_("friends", "cars", {
  'phone': lambda q: q.where("activated", 1)
}).get()
for user in users:
    user.phone
Nested Eager Loading
You may also eager load multiple relationships. Let's take another more advanced example...
Let's say you would like to get a user's phone as well as their contacts. The code would look like this:
users = User.all()
for user in users:
    for contact in user.phone:
        contact.name
This would result in the query:
SELECT * FROM users
SELECT * FROM phones where user_id = 1
SELECT * from contacts where phone_id = 30
SELECT * FROM phones where user_id = 2
SELECT * from contacts where phone_id = 31
SELECT * FROM phones where user_id = 3
SELECT * from contacts where phone_id = 32
SELECT * FROM phones where user_id = 4
SELECT * from contacts where phone_id = 33
...
You can see how this can get pretty large as we are looping through hundreds of users.
We can use nested eager loading to solve this by specifying the chain of relationships using . notation:
users = User.with_('phone.contacts').all()
for user in users:
    for contact in user.phone:
        contact.name
This would now result in the query:
SELECT * FROM users
SELECT * FROM phones where user_id IN (1,2,3,4)
SELECT * from contacts where phone_id IN (30, 31, 32, 33)
You can see how this would result in 3 queries no matter how many users you had.
Joining
If you have relationships on your models you can easily join them:
If you have a model that like this:
from masoniteorm.relationships import has_many
class User:
​
  @has_many('company_id', 'id')
  def posts(self):
    from app.models.Post import Post
    return Post
You can use the joins method:
User.joins('posts')
This will build out the join method.
You can also specify the clause of the join (inner, left, right). The default is an inner join
User.joins('posts', clause="right")
Additionally if you want to specify additional where clauses you can use the join_on method:
User.join_on('posts', lambda q: (
  q.where('active', 1)
))
Scopes
Scopes are a way to take common queries you may be doing and condense them into a method where you can then chain onto them. Let's say you are doing a query like getting the active user frequently:
user = User.where('active', 1).get()
We can take this query and add it as a scope:
from masoniteorm.scopes import scope
class User(Model):
​
  @scope
  def active(self, query):
    return query.where('active', 1)
Now we can simply call the active method:
user = User.active().get()
You may also pass in arguments:
from masoniteorm.scopes import scope
class User(Model):
​
  @scope
  def active(self, query, active_or_inactive):
    return query.where('active', active_or_inactive)
then pass an argument to it:
user = User.active(1).get()
user = User.active(0).get()
Soft Deleting
Masonite ORM also comes with a global scope to enable soft deleting for your models.
Simply inherit the SoftDeletesMixin scope class:
from masoniteorm.scopes import SoftDeletesMixin
​
class User(Model, SoftDeletesMixin):
  # ..
Now whenever you delete a record, instead of deleting it it will update the deleted_at record from the table to the current timestamp:
User.where("id", 1).delete()
# == UPDATE `users` SET `deleted_at` = '2020-01-01 10:00:00' WHERE `id` = 1
When you fetch records it will also only fetch undeleted records:
User.all() #== SELECT * FROM `users` WHERE `deleted_at` IS NULL
You can disable this behavior as well:
User.with_trashed().all() #== SELECT * FROM `users`
You can also get only the deleted records:
User.only_trashed().all() #== SELECT * FROM `users` WHERE `deleted_at` IS NOT NULL
You can also restore records:
User.where('admin', 1).restore() #== UPDATE `users` SET `deleted_at` = NULL WHERE `admin` = '1'
Lastly, you can override this behavior and force the delete query:
User.where('admin', 1).force_delete() #== DELETE FROM `users` WHERE `admin` = '1'
You still need to add the deleted_at datetime field to your database table for this feature to work.
There is also a soft_deletes() helper that you can use in migrations to add this field quickly.
# user migrations
with self.schema.create("users") as table:
  # ...
  table.soft_deletes()
If the column name is not called deleted_at you can change the column to a different name:
from masoniteorm.scopes import SoftDeletesMixin
​
class User(Model, SoftDeletesMixin):
  __deleted_at__ = "when_deleted"
Truncating
You can truncate the table used by the model directly on the model:
User.truncate()
Updating
You can update records:
User.find(1).update({"username": "Joe"}, {'active': 1})
When updating a record, only attributes which have changes are applied. If there are no changes, update won't be triggered.
You can override this behaviour in different ways:
you can pass force=True to update() method
User.find(1).update({"username": "Joe"}, force=True)
you can define __force_update__ attribute on the model class
class User(Model):
    __force_update__ = True
​
User.find(1).update({"username": "Joe"})
you can use force_update() method on model:
User.find(1).force_update({"username": "Joe"})
You can also update or create records as well:
User.update_or_create({"username": "Joe"}, {
    'active': 1
})
If there is a record with the username of "Joe" it will update that record or, if not present, it will create the record.
Note that when the record is created, the two dictionaries will be merged together. So if this code was to create a record it would create a record with both the username of Joe and active of 1.
When updating records the updated_at column will be automatically updated. You can control this behaviour by using activate_timestamps method:
User.activate_timestamps(False).update({"username": "Sam"})  # updated_at won't be modified during this update
Creating
You can easily create records by passing in a dictionary:
User.create({"username": "Joe"})
This will insert the record into the table, create and return the new model instance.
Note that this will only create a new model instance but will not contain any additional fields on the table. It will only have whichever fields you pass to it.
You can "refetch" the model after creating to get the rest of the record. This will use the find method to get the full record. Let's say you have a scenario in which the active flag defaults to 1 from the database level. If we create the record, the active attribute will not fetched since Masonite ORM doesn't know about this attribute.
In this case we can refetch the record using .fresh() after create:
user = User.create({"username": "Joe"}).fresh()
​
user.active #== 1
Bulk Creating
You can also bulk create using the query builder's bulk_create method:
User.bulk_create([
  {"username": "Joe"},
  {"username": "John"},
  {"username": "Bill"},
  {"username": "Nick"},
])
This will return a collection of users that have been created.
Since hydrating all the models involved in a bulk create, this could be much slower when working with a lot of records. If you are working with a lot of records then using the query builder directly without model hydrating will be faster. You can do this by getting a "new" query builder and call any required methods off that:
User.builder.new().bulk_create([
  {"username": "Joe"},
  {"username": "John"},
  {"username": "Bill"},
  {"username": "Nick"},
])
Serializing
You can serialize a model very quickly:
User.serialize()
# returns {'id': 1, 'account_id': 1, 'first_name': 'John', 'last_name': 'Doe', 'email': '[email protected]', 'password': '$2b$12$pToeQW/1qs26CCozNiAfNugRRBNjhPvtIw86dvfJ0FDNcTDUNt3TW', 'created_at': '2021-01-03T11:35:48+00:00', 'updated_at': '2021-01-08T22:06:48+00:00' }
This will return a dict of all the model fields. Some important things to note:
Date fields will be serialized with ISO format