2 posts tagged with "django"

Hi everyone,

It's been a few weeks since our last version announcement and today I'm happy to share with you v0.20, which includes some big changes and exciting features:

• New Pricing Model - As we announced earlier this month, beginning March 15th the new pricing model took effect. The new pricing is usage-based, offering you more flexibility and cost efficiency. Read about what prompted this change and view the new pricing plans here.
• Django ORM Integration - Atlas now supports Django! Django is a popular ORM for Python. Developers using Django can now use Atlas to automatically plan schema migrations based on the desired state of their schema, instead of crafting them by hand.
• Support for PostgreSQL Extensions - Atlas now supports installing and managing PostgreSQL extensions.
• Dashboards in the Cloud - The dashboard (previously the 'Projects' page) got a whole new look in Atlas Cloud. Now you can view the state of your projects and environments at a glance.
• _SQL Server is out of Beta](#sql-server-is-out-of-beta) - SQL Server is officially out of Beta! Along with this official support, we have included some new features:
  • User-Defined Types support for SQL Server - Atlas now supports two User-Defined Types: alias types and table types.
  • Azure Active Directory (AAD) Authentication for SQL Server - Connect to your SQL Server database using AAD Authentication.

Let’s dive in!

New Pricing Model​

As of March 15th, there is a new pricing model for Atlas users. This change is a result of feedback we received from many teams that the previous $295/month minimum was prohibitive, and a gradual, usage-based pricing model would help them adopt Atlas in their organizations.

You can read the full reasoning for the change and a breakdown of the new pricing in this blog post.

Django ORM Integration​

Django is the most popular web framework in the Python community. It includes a built-in ORM which allows users to describe their data model using Python classes. Migrations are then created using the makemigrations command, which can be applied to the database using migrate command.

Among the many ORMs available in our industry, Django's automatic migration tool is one of the most powerful and robust. It can handle a wide range of schema changes, however, having been created in 2014, a very different era in software engineering, it naturally has some limitations.

Some of the limitations of Django's migration system include:

1. Database Features - Because it was created to provide interoperability across database engines, Django's migration system is centered around the "lowest common denominator" of database features.

2. Ensuring Migration Safety - Migrations are a risky business. If you're not careful, you can easily cause data loss or a production outage. Django's migration system does not provide a native way to ensure that a migration is safe to apply.

3. Modern Deployments - Django does not provide native integration with modern deployment practices such as GitOps or Infrastructure-as-Code.

Atlas, on the other hand, lets you manage your Django applications using the Database Schema-as-Code paradigm. This means that you can use Atlas to automatically plan schema migrations for your Django project, and then apply them to your database.

Read the full guide to set up Atlas for your Django project.

Support for PostgreSQL Extensions​

Postgres extensions are add-on modules that enhance the functionality of the database by introducing new objects, such as functions, data types, operators, and more.

The support for extensions has been highly requested, so we are excited to announce that they are finally available!

To load an extension, add the extension block to your schema file. For example, adding PostGIS would look similar to:

extension "postgis" {
 schema  = schema.public
 version = "3.4.1"
 comment = "PostGIS geometry and geography spatial types and functions"
}

Read more about configuring extensions in your schema here.

Dashboards in the Cloud​

Atlas Cloud has a new and improved dashboard view!

When working with multiple databases, environments, or even projects - it becomes increasingly difficult to track and manage the state of each of these components. With Atlas Cloud, we aim to provide a single source of truth, allowing you to get a clear overview of each schema, database, environment, deployment and their respective statuses.

Once you push your migration directory to the schema registry, you will be able to see a detailed dashboard like the one shown above.

Let’s break down what we see:

• The usage calendar shows when changes are made to your migration directory via the migrate push command in CI.

• The databases show the state of your target databases. This list will be populated once you have set up deployments for your migration directory. The state of the database can be one of the following:

  • Synced - the database is at the same version as the latest version of your migration directory schema.
  • Failed - the last deployment has failed on this database.
  • Pending - the database is not up to date with the latest version of your migration directory schema.

An alternate view to this page is viewing it per environment. This way, you can see a comprehensive list of the status of each database in each environment.

SQL Server out of Beta​

We are proud to announce that SQL Server is officially supported by Atlas! Since our release of SQL Server in Beta last August, our team has been working hard to refine and stabilize its performance.

In addition, we have added two new capabilities to the SQL Server driver.

User-Defined Types Support​

In SQL Server, user-defined types (UDTs) are a way to create custom data types that group together existing data types. Atlas now supports alias types and table types.

Alias Types​

Alias types allow you to create a custom data type, which can then make your code more readable and maintainable.

For example, you might want to create an alias type email_address for the VARCHAR(100) data type. Instead of rewriting this throughout the code, and in order to maintain consistency, you can simply use email_address for clarity.

In the schema.hcl file, you would define this like so:

type_alias "email_address" {
 schema = schema.dbo
 type   = varchar(100)
 null   = false
}
table "users" {
 schema = schema.dbo
 column "email_address" {
   type = type_alias.email_address
 }
}

Table Types​

Table types allow you to define a structured data type that represents a table structure. These are particularly useful for passing sets of data between stored procedures and functions. They can also be used as parameters in stored procedures or functions, allowing you to pass multiple rows of data with a single parameter.

For example, we have a type_table to describe the structure of an address. We can declare this table and later use it in a function:

type_table "address" {
 schema = schema.dbo
 column "street" {
   type = varchar(255)
 }
 column "city" {
   type = varchar(255)
 }
 column "state" {
   type = varchar(2)
 }
 column "zip" {
   type = type_alias.zip
 }
 index {
   unique  = true
   columns = [column.ssn]
 }
 check "zip_check" {
   expr = "len(zip) = 5"
 }
}
function "insert_address" {
 schema = schema.dbo
 lang   = SQL
 arg "@address_table" {
   type     = type_table.address
   readonly = true // The table type is readonly argument.
 }
 arg "@zip" {
   type = type_alias.zip
 }
 return = int
 as     = <<-SQL
 BEGIN
   DECLARE @RowCount INT;
   INSERT INTO address_table (street, city, state, zip)
   SELECT street, city, state, zip
   FROM @address_table;

   SELECT @RowCount = @ROWCOUNT;

  RETURN @RowCount;
 END
 SQL
}
type_alias "zip" {
 schema = schema.dbo
 type   = varchar(5)
 null   = false
}

Read the documentation to learn how to use these types in Atlas.

Azure Active Directory (AAD) Authentication​

Now when using SQL Server with Atlas, instead of providing your regular database URL, you can connect to your Azure instance with Azure Active Directory Authentication.

Use the fedauth parameter to specify the AAD authentication method. For more information, see the document on the underlying driver.

To connect to your Azure instance using AAD, the URL will look similar to:

azuresql://<instance>.database.windows.net?fedauth=ActiveDirectoryDefault&database=master

Wrapping up​

That's it! I hope you try out (and enjoy) all of these new features and find them useful. As always, we would love to hear your feedback and suggestions on our Discord server.

Having a visual representation of your data model can be helpful as it allows for easier comprehension of complex data structures, and enables developers to better understand and collaborate on the data model of the application they are building.

Entity relationship diagrams (ERDs) are a common way to visualize data models, by showing how data is stored in the database. ERDs are graphical representations of the entities, their attributes, and the way these entities are related to each other.

Today we are happy to announce the release of DjangoViz, a new tool for automatically creating ERDs from Django data models.

Django is an open source Python framework for building web applications quickly and efficiently. In this blog post, I will introduce DjangoViz and demonstrate how to use it for generating Django schema visualizations using the Atlas playground.

Django ORM​

Django ORM is a built-in module in the Django web framework. It offers a high-level abstraction layer that enables developers to define complex application data models with ease. Unlike traditional ORM frameworks that rely on tables and foreign keys, Django models are defined using Python objects and relationships:

from django.db import models

class User(models.Model):
    username = models.CharField(max_length=255)
    email = models.EmailField(unique=True)
    password = models.CharField(max_length=255)

class Post(models.Model):
    title = models.CharField(max_length=255)
    content = models.TextField()
    author = models.ForeignKey(User, on_delete=models.CASCADE)

When the application runs, Django translates these Python models into database schemas, mapping each model to a corresponding database table and each field to a corresponding column in the table.
When working with schemas and making changes to them, being able to understand the full picture just through code can get complicated very quickly. To help developers better understand their schema, we have created DjangoViz.

Introducing DjangoViz​

For the purpose of this demo, we will follow the Django getting started tutorial, and showcase how you can use DjangoViz to visualize the default models included by Django's startproject command.

First, install Django and create a new project:

pip install Django
django-admin startproject atlas_demo
cd atlas_demo

Install the DjangoViz package:

pip install djangoviz

Add DjangoViz to your Django project's INSTALLED_APPS in atlas_demo/settings.py:

INSTALLED_APPS = [
    ...,
    'djangoviz',
    ...
]

DjangoViz supports either PostgreSQL or MySQL, in this example we will use PostgreSQL:

Install the PostgreSQL driver:

pip install psycopg2-binary

Configure the database to work with PostgreSQL in the settings.py file:

DATABASES = {
   "default": {
       "ENGINE": "django.db.backends.postgresql_psycopg2",
       "NAME": "postgres",
       "USER": "postgres",
       "PASSWORD": "pass",
       "HOST": "127.0.0.1",
       "PORT": "5432",
   }
}

Start a PostgreSQL container:

docker run --rm -p 5432:5432  -e POSTGRES_PASSWORD=pass -d postgres:15

Now, you can visualize your schema by running the djangoviz management command from your new project directory:

python manage.py djangoviz

You will get a public link to your visualization, which will present an ERD and the schema itself in SQL or HCL:

Here is a public link to your schema visualization:
  https://gh.atlasgo.cloud/explore/ac523fef

When clicking on the link you will see the ERD of your new project:

Wrapping up​

In this post, we discussed DjangoViz, a new tool that helps to quickly visualize Django schemas. With this tool, you can easily get an overview of the data model and visual of your schema. We would love to hear your thoughts and feedback if you decide to give it a go!

Have questions? Feedback? Find our team on our Discord server ❤️.