System testing with Pytest, Docker, and Flask. The composability of fixtures in pytest is an improvement over traditional xUnit setup/teardown. Learn how to combine the power of pytest fixtures with Docker to build high-level integration tests for microservices or other complex systems with multiple components
The composability of fixtures in pytest is an improvement over traditional xUnit setup/teardown, reducing the incentive to commit testing crimes such as multi-stage and stepwise tests. This is great out of the box for unit tests, but I'm going to show how to combine the power of pytest fixtures with Docker to build high-level integration tests for microservices or other complex systems with multiple components. I'll then build on that to show how to embed mock web services written with Flask right into the test code.
With a sample Java application that makes use of some external resources to offer a data processing service I'll first quick an overview of Pytest, Docker, and Flask. Then I'll mix some pre-built code with live test coding to demonstrate how to build high-level system tests which spin up the application and its dependencies in Docker. I'll then mock one of the external dependencies using Flask, allowing the test to control and verify interaction between the system components. Finally I'll show how to wrap the Flask application in a WSGI middleware that lets the test inspect interaction with the mocked service.
From a learning and development point of view, building your own is better than re-using someone else's code so I'll show how the support code for these features is relatively simple and how the audience can build it themselves to exactly meet their own needs. And I'll do it all with a sense of fun, a joke or two and maybe a little storytelling.
A complete Guide to Build and Deploy NLP Model with Python, Docker, Flask, GitLab, Jenkins. A to Z (NLP) Machine Learning Model building and Deployment. Developing the NLP Model for Sentiment analysis and Machine learning deployment on local server using flask and docker. Select the most efficient Machine Learning Model, Tune the hyper-parameters and selecting the best model using cross-validation technique. Understanding about software development and automation in real scenario and concept of end-to-end Integration.
In this Python Flask tutorial, you'll learn to build CRUD web applications using Python and Flask. Python and Flask can make building a CRUD app super easy.
A simple article to explain how dockerized a Flask App.