Why Deepstream Python Binding is Deprecated?

Accelerated Computing Intelligent Video Analytics DeepStream SDK
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Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) 3090
• DeepStream Version 7.0
• JetPack Version (valid for Jetson only)
• TensorRT Version deepstream 7 installation guide
• NVIDIA GPU Driver Version (valid for GPU only) deepstream 7.0 installation guide 535
• Issue Type( questions, new requirements, bugs)
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)

Hi everyone,

I have a question regarding the DeepStream Python bindings in DeepStream 9.0.

As far as I understand, Python bindings can still be used in DeepStream 9.0, but they are marked as deprecated. I would like to better understand the reason behind this deprecation.

From my current understanding, Python bindings still execute the core DeepStream/GStreamer/C++ components underneath, and Python is mainly used to build the pipeline and handle callbacks/probes. Because of that, I assumed the performance overhead might not be very high, especially compared to Service Maker, where there may be additional abstraction layers or wrappers.

I am trying to decide whether it is worth migrating my existing application from DeepStream Python bindings to Service Maker.

In my case, I have already made several modifications, including changes inside the Python binding source code itself. So before planning a migration, I would like to understand:

  1. Why exactly are DeepStream Python bindings deprecated in DeepStream 9.0?
  2. Is Service Maker now the recommended long-term approach for Python-based DeepStream applications?
  3. Are there any official NVIDIA documents explaining the deprecation and the migration path?
  4. From a performance and maintainability perspective, what are the main advantages of Service Maker compared to Python bindings?
  5. If an application already depends heavily on custom Python binding behavior, is migration strongly recommended, or can Python bindings still be safely used for production?

Any clarification or official documentation links would be very helpful.

Thanks.

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pyServiceMaker will be the only python interfaces of DeepStream.

Yes.

Explain for what? What do you mean by “migration path”?

Please refer to What is Deepstream Service Maker — DeepStream documentation

That depends. We don’t know what kind of customization you are mentioning.

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about the advanteges in pyServiceMaker

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Some advantages

  1. pyServiceMaker interfaces are more python style
  2. pyServiceMaker is much simpler than pyds. E.G. please compare /opt/nvidia/deepstream/deepstream/service-maker/sources/apps/python/flow_api/deepstream_test1_app/deepstream_test1.py and deepstream_python_apps/apps/deepstream-test1/deepstream_test_1.py at master · NVIDIA-AI-IOT/deepstream_python_apps
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There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks.