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Becoming an Enterprise Django Developer

Becoming an Enterprise Django Developer

By : Dinder, Michael Dinder
4.2 (9)
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Becoming an Enterprise Django Developer

Becoming an Enterprise Django Developer

4.2 (9)
By: Dinder, Michael Dinder

Overview of this book

Django is a powerful framework but choosing the right add-ons that match the scale and scope of your enterprise projects can be tricky. This book will help you explore the multifarious options available for enterprise Django development. Countless organizations are already using Django and more migrating to it, unleashing the power of Python with many different packages and dependencies, including AI technologies. This practical guide will help you understand practices, blueprints, and design decisions to put Django to work the way you want it to. You’ll learn various ways in which data can be rendered onto a page and discover the power of Django for large-scale production applications. Starting with the basics of getting an enterprise project up and running, you'll get to grips with maintaining the project throughout its lifecycle while learning what the Django application lifecycle is. By the end of this book, you'll have learned how to build and deploy a Django project to the web and implement various components into the site.
Table of Contents (15 chapters)
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1
Part 1 – Starting a Project
5
Part 2 – Django Components
10
Part 3 – Advanced Django Components

Exporting data into a data fixture

A data fixture is considered a collection of files that contain data objects related to the models in your application. This really refers to a directory of files that Django searches in for data; by default, that is the fixtures folder found in every Django app. This directory can also be changed by modifying the settings.py variable called FIXTURE_DIRS, but this is not necessary if you intend to use the default directory and behavior. Django fixture files can be written in JSON, JSONL, XML, or YAML file formats. This means you can easily export data from other systems if that data is exported into one of these formats, even if that other system is not a Django project. Keep in mind that the table structure of the objects must match exactly if you wish to do a clean export from an old system and import into a new system.

Usually, there is a great deal of data parsing involved when exporting from an older legacy system and importing into the newly...

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