Forecast Pipeline 06

export_forecast.py

# Request for a forecast based on time and product filter
forecastResponse = forecastquery.get_forecast(
    PredictorName=predictorName,
    StartDate='2018-01-01T00:00:00Z',
    EndDate='2018-01-10T00:00:00Z',
    Interval="day",
    Filters={"item_id":"012"}

)

# Creating a dataframe for the prediction output
predictions = forecastResponse['Forecast']['Predictions']
pd.concat({k: pd.DataFrame(v).T for k, v in predictions.items()}, axis=0).T

forecastId = forecastResponse['Forecast']['ForecastId']

forecast.create_forecast_export_job(
    ForecastId= forecastId, 
    OutputPath = {
        "S3Uri":"s3://forecast-xxxxxx/output/"+project+"/",
        "RoleArn":roleArn
    }
)