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Writing about Data Science, Bioinformatics, WebDev/Django and more.
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Introduction

In this tutorial, we are going to create a nice crispy range slider using django-crispy-forms for an integer filter provided by django-filters. The tutorial can be split into four sections. In the first or prerequisite section, we will install the required packages and initiate the Django project. In the next section, we will create a simple app with a model, view, and template. In the third section, we will create the simple range filter using django-filters package without a slider. …


In this tutorial, you are going to learn how to create a dashboard for Oscar’s e-commerce framework. This tutorial starts where the first part ended.

Creating a Django-Oscar dashboard app to manage boutiques

Let’s create a new app called dashboard inside the boutique app directory:

mkdir boutique/dashboard

Then initialize a new Django app using the following command:

python manage.py startapp dashboard boutique/dashboard

You can delete admin.py, models.py and tests.py, because these are not required for the Oscar's dashboard app.

Once again after the dashboard app is created, it is necessary to register the app in INSTALLED_APPS in settings.py as shown below:

INSTALLED_APPS = [
...
'boutique.dashboard.apps.DashboardConfig',
]

If…


In this tutorial, you are going to learn how to create a new Django app and integrate it into Oscar e-commerce framework. Particularly, we will create a new sample Django app called boutique and integrate it to Oscar's default front and dashboard.

Getting ready (django-oscar)

First, it is necessary to create a virtual environment to work in. I use pipenv as a virtual environment for its simplicity and ease of use. Create a directory called /myoscarapp, move inside and run the following command:

$ pipenv shell

Then install the django-oscar using pip:

$ pip install django-oscar[sorl-thumbnail]

Now create a brand new Dango project…


Python is an amazing programming language, but it has two huge handicaps compared to compiled languages.

  • The first one is GIL or Global Interpreter Lock. GIL is an actual process lock that forces a Python interpreter to work on a single process and use only one of the cores in your CPU. Due to this lock, Python is both simple and stable but also is very slow compared to other programming languages like C or Java.
  • The second handicap is rather universal for non-statically typed aka dynamically typed programming languages. Simply put, when you do not specify the data type…

Farid Musa

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