Unlock Your Data Potential: A Deep Dive into the STDATALOG-PYSDK

Are you a data scientist or embedded designer looking to streamline data capture, processing, and visualization? The STDATALOG-PYSDK is your answer. This powerful Python SDK from STMicroelectronics provides a comprehensive framework for handling data from various sources, empowering you to create insightful applications with ease.

What is the STDATALOG-PYSDK?

The STDATALOG-PYSDK is a Python software development kit designed to simplify data logging and analysis. It's a comprehensive framework, highly modular and perfectly suited for taking inputs from:

• Sensors
• Algorithms
• Simulated signals
• Actuator telemetries

Formerly known as HSDPython_SDK, it's evolved from function packs like FP-SNS-DATALOG1 and FP-IND-DATALOGMC, bringing years of development into a single, robust tool.

Key Benefits of Using the STDATALOG-PYSDK

Why choose the STDATALOG-PYSDK for your data-driven projects?

• Open and Modular Architecture: Offers flexibility and easy customization to fit your specific needs.
• Wide Compatibility: Developed in Python 3.12, it's also compatible with Python 3.11 and 3.10.
• Simplified Development: Provides tools and utilities to streamline the creation of data-driven applications.
• Data Science Ready: Creates structured datasets compatible with mainstream data science toolchains for seamless integration.
• Reusable Across Projects: Scripts can be easily integrated into any data science design workflow, saving you valuable time and resources.

With the STDATALOG-PYSDK, you can focus on extracting valuable insights from your data, rather than wrestling with complex data acquisition and processing tasks.

Getting Started with STDATALOG-PYSDK: Installation Guide

Installing the STDATALOG-PYSDK is a breeze with the provided installer scripts. Here's a step-by-step guide for Windows, Linux, and macOS:

Prerequisites

Before you begin, ensure you have Python (3.10, 3.11, or 3.12) installed on your machine. It's also highly recommended to use a clean virtual environment to avoid dependency conflicts.

Installation Steps

1. Clone the Repository:

   git clone --recursive https://github.com/STMicroelectronics/stdatalog-pysdk.git
   

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2. Create a Virtual Environment:

   python -m venv .venv
   

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3. Activate the Virtual Environment:

   • Windows: . \.venv\Scripts\activate
   • Linux/macOS: source .venv/bin/activate

4. Run the Installer:

   • Windows: .\STDATALOG-PYSDK_install.bat (Specify proxy if needed: .\STDATALOG-PYSDK_install.bat http://usr_name:password@proxyserver_name:port)
   • Linux/macOS:
     • sudo apt-get install dos2unix
     • dos2unix STDATALOG-PYSDK_install.sh STDATALOG-PYSDK_install_noGUI.sh STDATALOG-PYSDK_uninstall.sh
     • chmod 777 STDATALOG-PYSDK_install.sh STDATALOG-PYSDK_install_noGUI.sh STDATALOG-PYSDK_uninstall.sh
     • ./STDATALOG-PYSDK_install.sh (Specify proxy if needed: ./STDATALOG-PYSDK_install.sh http://usr_name:password@proxyserver_name:port)

5. (Linux Only) Install USB Drivers:

   cd linux_setup
   dos2unix 30-hsdatalog.rules linux_USB_config_setup.sh linux_USB_config_removal.sh
   chmod 777 linux_USB_config_setup.sh linux_USB_config_removal.sh
   ./linux_USB_config_setup.sh
   

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   Reboot your PC after installing USB drivers.

6. Test the Installation:

   cd stdatalog_examples
   python gui_applications/stdatalog/GUI/stdatalog_GUI.py
   

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Diving Deeper: Example Usage

Once installed, explore the example scripts in the stdatalog_examples directory. These examples demonstrate how to use the Python SDK for data logging to create GUI applications and process data from various sources.

Supported Devices and Boards

The STDATALOG-PYSDK supports a wide range of STMicroelectronics devices and boards, including:

• STEVAL-STWINBX1
• STEVAL-STWINKT1B
• STEVAL-MKBOXPRO
• STEVAL-PDETECT1
• STEVAL-C34KAT1/2/PM1
• B-U585I-IOT02A
• X-NUCLEO-IKS02A1 with NUCLEO-U575ZI-Q or NUCLEO-H7A3ZI-Q
• EVLSPIN32G4-ACT

Take Control of Your Data Today

The STDATALOG-PYSDK empowers you to efficiently capture, process, and visualize data, making it an invaluable asset for data scientists and embedded designers. By leveraging this software development kit, you can turn raw sensor data into actionable insights, accelerating your projects and driving innovation.