An object-relational mapper (ORM) is a programming library that automates the conversion of data contained in relational database tables into objects that can be used in program code. SQLAlchemy is a library that allows Python programs to communicate with databases. This library is typically used as an Object Relational Mapper (ORM) tool, converting Python classes to tables in relational databases and automatically converting method calls to SQL statements.
What are the benefits of ORMs?
ORMs offer a high-level abstraction over a relational database, allowing a developer to build, read, edit, and erase data and schemas in their database using Python code rather than SQL. Instead of writing SQL statements or stored procedures, developers can work with a database using the programming language they are most familiar with.
Is it necessary to use an ORM for my web application?
Accessing relational databases does not necessitate the use of Python ORM libraries. In fact, low-level access is usually provided by a separate library known as a database connector, such as psycopg (for PostgreSQL) or MySQL-python (for MySQL). Take a look at the table below to see how ORMs can interact with various network interfaces, connectors, and relational databases.
ORM implementations in Python
There are various Python ORM implementations available, including:
- Adolet ORM
- PonyORM
- Django ORM.
Other ORMs exist, such as Canonical’s Storm, but the majority of them do not seem to be actively developed at the moment. Learn more about the big active ORMs below.
ORM in Django
The Django web interface has its own object-relational mapping module, which is often referred to as “the Django ORM” or “Django’s ORM.”
Django’s ORM performs admirably for basic and medium-complexity database operations. However, there are frequent reports that the ORM makes complex queries much more difficult to write than pure SQL or SQLAlchemy.
While it is theoretically possible to use SQL, doing so binds the queries to a particular database implementation. Since the ORM is too tightly coupled with Django, replacing the default ORM with SQLAlchemy is currently a hack solution. However, since it is now possible to modify the template engine for rendering performance in Django, swappable ORM backends will be possible in the future.
Since the bulk of Django projects are bound to the default ORM, it is best to educate yourself on specialized use cases and tools for doing the best work inside the current context.
ORM SQLAlchemy
SQLAlchemy is a popular Python ORM since it gets the abstraction level “about right” and seems to make complex database queries simpler to write in most cases than the Django ORM. If you want to learn more about using SQLAlchemy, there is an entire website dedicated to it.
ORM for Peewees
Peewee is a Python ORM implementation that is “simpler, lighter, and more hackable” than SQLAlchemy. More information on the Python ORM implementation can be found on the full Peewee tab.
Pony ORM
Pony ORM is another Python ORM that is open source and licensed under the Apache 2.0 license.
ORM for SQLObject
SQLObject is an ORM that has been actively developed as open-source for over 14 years, dating back to before 2003.
About Adolet’s ORM
Programmers are often charged with time-consuming activities like incorporating and linking a database with a network or smartphone device. This method is impossible to simplify due to the complexities of data protection.
In only a few lines of code, you can build a cloud database and begin executing SQL queries on your PostgreSQL or MySQL database. Everything you have to do is type your hidden key. Check out their documentation for more information. Currently, Adolet ORM is only open to tech firms. They also provide computing services in addition to our cloud database server optimized ORM. Currently, Adolet’s ORM is available as a Python package. Visit their website or you can contact them for more information.
