13. Save prediction data to SQLite database

To save all model predictions to the SQLite database, you can use the create() method for Django models.

To do this, input the Predictions model at the beginning of iris/views.py

from .models import Predictions

Then add the following to iris/views.py just before return render(request, 'home.html', {'form': form, 'prediction': prediction...

Predictions.objects.create(sepal_length=sepal_length,
                            sepal_width=sepal_width,
                            petal_length=petal_length,
                            petal_width=petal_width,
                            prediction=prediction_name)

Notice how we do not add predict_datetime because it is automatically generated.

To check that the database works try running the app locally, inputting some data, and go the Admin site to check if the data was saved.

Your iris/views.py will now look like:

from django.shortcuts import render
from .forms import ModelForm
from .models import Predictions
import pickle


def predict_model(request):
    # if this is a POST request we need to process the form data
    if request.method == 'POST':
        # create a form instance and populate it with data from the request:
        form = ModelForm(request.POST)
        # check whether it's valid:
        if form.is_valid():
            # process the data in form.cleaned_data as required
            sepal_length = form.cleaned_data['sepal_length']
            sepal_width = form.cleaned_data['sepal_width']
            petal_length = form.cleaned_data['petal_length']
            petal_width = form.cleaned_data['petal_width']

            # Run new features through ML model
            model_features = [
                [sepal_length, sepal_width, petal_length, petal_width]]
            loaded_model = pickle.load(
                open("ml_model/iris_model.pkl", 'rb'))
            prediction = loaded_model.predict(model_features)[0]

            prediction_dict = [{'name': 'setosa',
                                'img': 'https://alchetron.com/cdn/iris-setosa-0ab3145a-68f2-41ca-a529-c02fa2f5b02-resize-750.jpeg'},
                               {'name': 'versicolor',
                                'img': 'https://wiki.irises.org/pub/Spec/SpecVersicolor/iversicolor07.jpg'},
                               {'name': 'virginica',
                                'img': 'https://www.gardenia.net/storage/app/public/uploads/images/detail/xUM027N8JI22aQPImPoH3NtIMpXkm89KAIKuvTMB.jpeg'}]

            prediction_name = prediction_dict[prediction]['name']
            prediction_img = prediction_dict[prediction]['img']

            # Add prediction to database Predictions table
            Predictions.objects.create(sepal_length=sepal_length,
                                       sepal_width=sepal_width,
                                       petal_length=petal_length,
                                       petal_width=petal_width,
                                       prediction=prediction_name)

            return render(request, 'home.html', {'form': form, 'prediction': prediction,
                                                 'prediction_name': prediction_name,
                                                 'prediction_img': prediction_img})

    # if a GET (or any other method) we'll create a blank form
    else:
        form = ModelForm()

    return render(request, 'home.html', {'form': form})