tim-client 0.0.21

TIM Python Client

TIM Python Client

TIM, or Tangent Information Modeler, is Tangent Works’ automatic model building engine. It is designed specifically for time-series forecasting and anomaly detection.

The TIM Python client introduces an easy and fast way to use TIM in any Python project. As an abstraction over TIM's API, it encapsulates the logic into useful and performant functions helping users go from time-series data to insights that can generate business value.

The TIM Python client is a Python SDK to use the TIM Engine (v5). This includes methods to:

• upload a dataset,
• delete a dataset,
• retrieve a list of datasets,
• retrieve a list of dataset versions,
• create a forecasting build model job,
• execute a forecasting job,
• create and execute a forecasting build model job,
• retrieve the results of a forecasting job,
• retrieve a list of forecasting jobs,
• delete a forecasting job,
• create an anomaly detection build model job,
• execute an anomaly detection job,
• create and execute an anomaly detection build model job,
• create an anomaly detection detect job,
• create and execute an anomaly detection detect job,
• retrieve the results of an anomaly detection job,
• retrieve a list of anomaly detection jobs,
• delete an anomaly detection job,
• retrieve a list of workspaces.

Usage

Installation

To install the package run: pip install tim-client

Initialization

from tim import Tim

client = Tim(email='',password='')

Methods

Tim provides the following methods:

• client.upload_dataset
• client.delete_dataset
• client.get_datasets
• client.get_dataset_versions
• client.build_forecasting_model
• client.execute_forecast
• client.build_forecasting_model_and_execute
• client.clean_forecast
• client.get_forecast_results
• client.get_forecasting_jobs
• client.delete_forecast
• client.build_anomaly_detection_model
• client.execute_anomaly_detection
• client.build_anomaly_detection_model_and_execute
• client.create_anomaly_detection
• client.create_anomaly_detection_and_execute
• client.get_anomaly_detection_results
• client.get_anomaly_detection_jobs
• client.delete_anomaly_detection
• client.get_workspaces

Error handling

Minimal validation is performed by the Tim client, errors will be raised by the server.

Documentation

Full documentation of the API can be found at: https://docs.tangent.works

About Tangent Works

Tangent Works delivers forecasting and anomaly detection capabilities for time series data in a fast, accurate and explainable way. This enables users to drive business value from predictive analytics, empowers them to take informed decisions and helps them improve processes.

TIM has already been recognized as a winner in multiple competitions, including GEFCom 2017 and the 2017 ANDRITZ Hackathon.