Django

I needed a way to sort a Django queryset based on a custom sequence of an attribute. Typically, Django allows sorting a queryset by any attribute on the model or related to it in either ascending or descending order. However, what if you need to sort the queryset following a custom sequence of attribute values? Suppose, you’re working with a model called Product where you want to sort the rows of the table based on a list of product ids that are already sorted in a particular order....

Back in the days when I was working as a data analyst, I used to spend hours inside Jupyter notebooks exploring, wrangling, and plotting data to gain insights. However, as I shifted my career gear towards backend software development, my usage of interactive exploratory tools dwindled. Nowadays, I spend the majority of my time working on a fairly large Django monolith accompanied by a fleet of microservices. Although I love my text editor and terminal emulators, I miss the ability to just start a Jupyter Notebook server and run code snippets interactively....

I was working with a table that had a similar (simplified) structure like this: | uuid | file_path | |----------------------------------|---------------------------| | b8658dfc3e80446c92f7303edf31dcbd | media/private/file_1.pdf | | 3d750874a9df47388569a23c559a4561 | media/private/file_2.csv | | d177b7f7d8b046768ab65857451a0354 | media/private/file_3.txt | | df45742175d7451dad59761f15653d9d | media/private/image_1.png | | a542966fc193470dab84351c15523042 | media/private/image_2.jpg | Let’s say the above table is represented by the following Django model: from django.db import models class FileCabinet(models.Model): uuid = models.UUIDField( primary_key=True, default=uuid.uuid4, editable=False ) file_path = models....

Django has a Model.objects.bulk_update method that allows you to update multiple objects in a single pass. While this method is a great way to speed up the update process, oftentimes it’s not fast enough. Recently, at my workplace, I found myself writing a script to update half a million user records and it was taking quite a bit of time to mutate them even after leveraging bulk update. So I wanted to see if I could use multiprocessing with ....

TIL that you can specify update_fields while saving a Django model to generate a leaner underlying SQL query. This yields better performance while updating multiple objects in a tight loop. To test that, I’m opening an IPython shell with python manage.py shell -i ipython command and creating a few user objects with the following lines: In [1]: from django.contrib.auth import User In [2]: for i in range(1000): ...: fname, lname = f'foo_{i}', f'bar_{i}' ....

I’ve rarely been able to take advantage of Django’s bulk_create / bulk_update APIs in production applications; especially in the cases where I need to create or update multiple complex objects with a script. Often time, these complex objects trigger a chain of signals or need non-trivial setups before any operations can be performed on each of them. The issue is, bulk_create / bulk_update doesn’t trigger these signals or expose any hooks to run any setup code....

At my workplace, we have a large Django monolith that powers the main website and works as the primary REST API server at the same time. We use Django Rest Framework (DRF) to build and serve the API endpoints. This means, whenever there’s an error, based on the incoming request header—we’ve to return different formats of error responses to the website and API users. The default DRF configuration returns a JSON response when the system experiences an HTTP 400 (bad request) error....

Django Rest Framework exposes a neat hook to customize the response payload of your API when errors occur. I was going through Microsoft’s REST API guideline1 and wanted to make the error response of my APIs more uniform and somewhat similar to this2. I’ll use a modified version of the quickstart example3 in the DRF docs to show how to achieve that. Also, we’ll need a POST API to demonstrate the changes better....