# Get senario handler
from dataiku.scenario import Scenario
scenario = Scenario()
# Create a message sender
sender = scenario.get_message_sender(channel_id="gmail") # A messaging channel
# Define your attachment
attachment = {
"destinationType": "DOWNLOAD",
"destinationDatasetProjectKey": "DKU_CHURN",
"overwriteDestinationDataset": "false",
"selection": {
"samplingMethod": "FULL",
"partitionSelectionMethod": "ALL",
"targetRatio": 0.02,
"maxRecords": 100000,
"selectedPartitions": [],
"ordering": {
"enabled": "false",
"rules": []
}
},
"advancedMode": "false",
"exportOption": {
"id": "excel",
"label": "Excel (*.xlsx)",
"canStream": "false",
"formatType": "excel",
"predefinedConfig": {
# This sample code helps you get started with the custom scenario API.
#For more details and samples, please see our Documentation
from dataiku.scenario import Scenario
# The Scenario object is the main handle from which you initiate steps
scenario = Scenario()
# A few example steps follow
# Building a dataset
scenario.build_dataset("customers_prepared", partitions="2015-01-03")
# Controlling the train of a dataset
train_ret = scenario.train_model("uSEkldfsm")
trained_model = train_ret.get_trained_model()
performance = trained_model.get_new_version_metrics().get_performance_values()
if performance["AUC"] > 0.85:
trained_model.activate_new_version()
# Sending custom reports
sender = scenario.get_message_sender("mail-scenario", "local-mail") # A messaging channel
sender.set_params(sender="*****@*****.**", recipient="*****@*****.**")
sender.send(subject="The scenario is doing well", message="All is good")