This blog post will help you to get deeper into Django Migrations - how Migrations works and how to create or add our custom migrations. Migrations are mainly for keeping the data model of you database up-to-date.
By writing unit test cases, you can evaluate each code component in the initial stage itself and it'll improve your app/code performance. Which is the best practice to test your code and you can easily determine if there are any errors.
Docker, has captured the hearts and minds of the Devops community, with its platform for delivering distributed applications in containers. In this Blog Post, Lets look on how to deploy a sample django app into docker container.
Querying with Django Q objects: Q object encapsulates a SQL expression in a Python object that can be used in database-related operations. Using Q objects we can make complex queries with less and simple code.
Gitlab is a great issue tracker. You can log your project activities like issue status, deadline etc in a git repository. Before that, you need to login to Gitlab and then go to the project where you need to create/manage issues .
Django provides the comfort database migrations from its version 1.8, with which we can avoid the usage of third party packages like south. Adding migrations to new apps is straightforward - they come preconfigured to accept migrations, and so just run make migrations once you’ve made some changes. But if your app already has models and database tables, and doesn’t have migrations yet or you got your migrations messed up, you’ll need to convert your app to use migrations.
Django by default to store the files in your local file system. To make your files load quickly and secure we need to go for any third party storage systems. AWS s3 is one of the storage service for the Internet. It is designed to make web-scale computing easier for developers. django has a package called django-storages which can be used to store the files in the amazon s3 and serve them from its cloudfront service.
IPython is a set of tools developed to make it easier for the programmers to work with Python and data. IPython provides extensions to the Python programming language that make working interactively convenient and efficient. IPython Notebook lets you write and execute code, analyze data in your web browser.