os.system(f"python3 ../functional_testing/{py_file}")
// Create & Learn
to_predict = "rental_price"
mdb = mindsdb.Predictor(name="home_rentals_price")
//mdb.learn(to_predict=to_predict,from_data="https://s3.eu-west-2.amazonaws.com/mindsdb-example-data/home_rentals.csv",backend=backend, stop_training_in_x_seconds=20,use_gpu=use_gpu)
// Reload & Predict
model_name = "home_rentals_price"
if run_extra:
mdb.rename_model("home_rentals_price", "home_rentals_price_renamed")
model_name = "home_rentals_price_renamed"
mdb = mindsdb.Predictor(name=model_name)
prediction = mdb.predict(when={"sqft":300}, use_gpu=use_gpu)
// Test all different forms of output
// No need to print them, we"re just doing so for debugging purposes, we just want to see if the interface will crash or not
print(prediction)
print(prediction[0])
for item in prediction:
print(item)
print(type(list(prediction.evaluations.values())[0][0]))
assert("ProbabilityEvaluation" in str(type(list(prediction.evaluations.values())[0][0])))
for p in prediction:
print(p)
print(prediction[0].as_dict())
print(prediction[0].as_list())
print(prediction[0]["rental_price_confidence"])
print(type(prediction[0]["rental_price_confidence"]))
print("\n\n========================\n\n")
print(prediction[0].explain())
print("\n\n")
// See if we can get the adapted metadata
amd = mdb.get_model_data(model_name)
// Make some simple assertions about it
// @TODO: Sometimes are None, not sure why: [, validation_set_accuracy, accuracy]
for k in ["status", "name", "version", "data_source", "current_phase", "updated_at", "created_at", "train_end_at"]:
assert(type(amd[k]) == str)
assert(type(amd["predict"]) == list or type(amd["predict"]) == str)
assert(type(amd["is_active"]) == bool)
for k in amd["data_preparation"]:
assert(type(amd["data_preparation"][k]) == int or type(amd["data_preparation"][k]) == float)
assert(type(amd["validation_set_accuracy"]) == float)
assert(type(amd["accuracy"]) == float)
for k in amd["data_analysis"]:
assert(len(amd["data_analysis"][k]) > 0)
assert(type(amd["data_analysis"][k][0]) == dict)
assert(len(amd["model_analysis"]) > 0)
assert(type(amd["model_analysis"][0]) == dict)
for k in amd["force_vectors"][to_predict]["normal_data_distribution"]:
assert(len(amd["force_vectors"][to_predict]["normal_data_distribution"][k]) > 0)
for k in amd["force_vectors"][to_predict]["missing_data_distribution"]:
for sk in amd["force_vectors"][to_predict]["missing_data_distribution"][k]:
assert(len(amd["force_vectors"][to_predict]["missing_data_distribution"][k][sk]) > 0)
