This project is using Azure Functions to develop a Basic Data Science app.
First you must create an azure account with the correct credentials.
And install Azure Core function tools
This Project is a basic REST interface based on v2 of the azure function protocol.
Evenutally this will get updated to a fully working classifier project.
To deploy the project see the publish-to-azure project below.
To test the application you can install the project into the virtual environment as listed in the Contributing section below.
python3 -m venv .venv
source .venv/bin/activate (linux) or source .venv/Scripts/activate (windows)
pip install -r requirements.txt
Once in the venv you can run the application locally within the project folder:
func start --verbose
or within VS Studio:
Start the emulator by pressing F1 and selection Azurite: Start
Run locally by going to Run & Debug panel and pushing F5 and then sending a request
Then test the app by opening a browser and running the following request: http://localhost:7071/api/HttpExample?name=Yoshi
If you deploy to Azure you can replace the http://localhost:7071 with you application URL
- https://learn.microsoft.com/en-us/azure/azure-functions/machine-learning-pytorch?tabs=bash
- https://learn.microsoft.com/en-us/azure/azure-functions/create-first-function-vs-code-python?pivots=python-mode-decorators#publish-the-project-to-azure
- https://learn.microsoft.com/en-us/azure/azure-functions/functions-bindings-http-webhook-trigger?tabs=python-v1%2Cin-process%2Cnodejs-v4%2Cfunctionsv2&pivots=programming-language-python#example
- https://learn.microsoft.com/en-us/azure/azure-functions/functions-reference-python?tabs=asgi%2Capplication-level&pivots=python-mode-decorators#development-options
- To contribute to the repository use the following:
git clone <ENTER SSH HERE>
cd reponame
git lfs install
git checkout -b feature/feature_name
git add <files>
git commit -m "Add my feature"
git push origin feature/feature_name