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Something really important to note is that the Azure deployment script will automatically install your PyPi requirements listed in requirements.txt onto the container each time it is deployed.įor that reason, I recommend that you put additional planning into separating the requirements of your virtual environments. Virtual environment, and then running pip freeze > requirements.txt to save the state of the environment so that it is reproducible. Knowledge and experience with Python and DjangoĪ common developer workflow is to create a local virtual environment, install the dependencies and tools needed for running the application, testing it, and linting it into the same.The code for this tutorial is up on my GitHub. How to setup error monitoring and performance metrics in Azure Application Insights.How to test the performance of your application and fine tune it.How to harden the security of your development and runtime environments.How to test your application locally and on CI/CD.How to use Azure Storage to host your static and media files.How to use Azure Postgres services for the Django database.

How to set up your development environment for reproducability.I’m not going to cover how to create or write a Django application, but instead, we’re going to focus on the last mile of development- getting it into production.

In this tutorial, I’m assuming that you have written or are writing a Python web application that uses Django, and you want to deploy that application onto Microsoft Azure.

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