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March 28, 2024
The Django ORM API is incredibly flexible and abstract. However, if you do not fully understand how it operates, if you have not already, you will probably wind up with slow and heavy views. Therefore, this article offers workable answers to the N+1 and long loading time problems. For the sake of clarity, I’ll make a straightforward view that illustrates typical ORM query issues and common best practices. A python development company can support you in getting the Django query optimized.
In this blog, we will understand how to optimize ORM queries. All the steps will be discussed in depth. Stay tuned.
To Proceed further, first, let’s discuss the basics of Django ORM. What it is and what role it plays. Django supports object-relational mapping and it is one of its most important features.
Django’s ORM is basically a Python-based technique to build SQL to query and change your database and obtain results.
Django’s ORM, or Object Relational Mapping Layer, makes it easier to communicate with multiple database systems like MySQL, PostgreSQL, SQLite, etc. with application data. The Django Framework includes the ORM, which is an instance of the ORM idea.
Django’s Object-Relational Mapper lets you communicate with your database as you would with SQL, which is one of its most potent features.
We have a lot of options to optimize the Queryset thanks to Django ORM. Always keep in mind what you need and don’t require. It is simple to optimize our Queryset if we are aware of our requirements.
The maintenance of any application must include database monitoring. Early detection of database problems can help the program stay functional and accessible. Database outages may not be detected until it’s too late and the company is losing money and clients if there isn’t effective monitoring in place. So it is necessary to have a constant look at the database performance. Let’s discuss how you can do the same.
https://django-debug-toolbar.readthedocs.io/en/latest/installation.html
2. Use QuerySet.explain() to understand how specific QuerySets are executed by your database.
3. Use silk library to view DB performance.
https://silk.readthedocs.io/en/latest/
4. Write the below code in Django settings.py file
For example:
Query:
Query:
Query:
Optimize Query:
Query:
Query:
Optimize Query:
Query:
Query inside a loop:
Query:
Optimized way:
Query:
values():
It is used as an iterable and returns dictionaries instead of model instances.
Example:
Output:
values_list():
Example:
Query:
Output:
Query:
Output:
Query:
Output:
defer():
Example:
Query:
only():
Example:
Query:
Don’t do:
Example:
Query:
Do:
Query:
exists():
Don’t do:
count():
Don’t do:
Do:
Example: If you want to update multiple author countries who belong to India then you don’t use a for loop with a saving method. Use the update() method.
Don’t Do :
Query:
Do:
Query:
Syntax:
bulk_create(objs,batch_size=None,ignore_conflicts=False)
Here,
batch_size=It controls how many objects are created in a single query.
Example: If you want to enter multiple countries in the country table then use bulk_create().
Example:
If you want to name an author who lives in an Indian country then you use the filter method.
Code for getting Indian authors:
Code for shown Indian authors:
Output:
Query:
This is how Django ORM optimization works. Even though optimization is complicated, following a few basic guidelines can help a lot.