MindSphere SDK for Python¶
Introduction¶
The MindSphere SDK for Python enables developers to work with MindSphere easily. It is divided into a core module and several service modules, which allows developers to include only those parts of the SDK required for their use case.
The core module provides authentication, logging, credentials configuration and a common API client implementation to access the RESTful MindSphere APIs. All service modules have dependency on the core module.
The MindSphere SDK for Python provides client implementations for the following APIs:
Name | API Version |
---|---|
SDK Core | 1.0.2 |
Asset Management | 3.11.2 |
Integrated Data Lake | 3.10.0 |
IoT Time Series | 3.4.4 |
TS Aggregates | 4.2.0 |
IoT File Service | 3.2.2 |
Event Analytics | 3.1.3 |
Event Analytics | 3.1.3 |
MindConnect | 3.5.1 |
TSBulk | 3.5.0 |
Semantic Data Interconnect | 1.0.0 |
Following older SDK & API versions can be referred for backward compatibility & will be deprecated in upcoming SDK releases:
Name | API Version |
---|---|
IoT Time Series | 3.3.2 |
IoT TS Aggregates | 3.2.2 |
Refer to the Getting Started for details on installation of modules and configuration of an API clients.
Get the SDK¶
The MindSphere SDK for Python is available for download on the Siemens Industry Online Support (SIOS) Portal. The SDK core and service specific modules(.whl) are bundled into a ZIP file.
Features¶
MindSphere SDK Core¶
The core module of the MindSphere SDK for Python handles authorization, client configuration, error handling, logging, and a common API Client to access RESTful MindSphere APIs. All service modules have a dependency on the core module.
Client Configuration¶
You can easily configure the MindSphere SDK for Python through configuration parameters such as proxy settings, host environment and connection time-outs.
Token Handling Mechanism¶
The MindSphere SDK for Python provides an easy authorization mechanism. It handles technical token fetching, caching, validation and re-fetching based on user authorization tokens or service credentials as configured.
Refer to Token Handling for more information.
Logging¶
The MindSphere SDK for Python uses Python's built-in logging module. Logging can be enabled or disabled and set to the required level.
Refer to Logging for more information.
Error Handling¶
The MindSphere SDK for Python provides an error handling mechanism. Different error classes help to identify whether an error was caused by your client or by the MindSphere server. Detailed information such as error, message, HTTP status and logref are provided for investigation.
Refer to Error Handling for more information.
Any questions left?
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