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

Are you looking to simplify data capture, processing, and visualization from sensors, simulated signals, or telemetries? The STDATALOG-PYSDK is your answer. This Python software development kit (SDK) is designed to streamline your data workflows, making it easier than ever to derive insights from various data sources. Let's explore how this powerful tool can revolutionize your data projects.

What is STDATALOG-PYSDK?

The STDATALOG-PYSDK is a comprehensive Python framework that empowers data scientists and embedded designers to efficiently handle data. Its modular architecture, open design, and compatibility with Python 3.10, 3.11, and 3.12 make it a versatile tool for any data-driven project.

Key Benefits of Using STDATALOG-PYSDK

• Simplified Data Handling: Capture, process, and visualize data from multiple sources effortlessly.
• Open and Modular Architecture: Customize the SDK to fit your specific project needs and seamlessly integrate with existing workflows.
• Compatibility with Mainstream Toolchains: Create datasets compatible with popular data science tools, ensuring reusability and collaboration.
• Enhanced Productivity: Reduce development time with pre-built tools and utilities specifically designed for data logging applications.

Getting Started with STDATALOG-PYSDK

Installation Guide

Follow these simple steps to install the STDATALOG-PYSDK and start leveraging its powerful features:

1. Prerequisites: Ensure Python 3.10, 3.11, or 3.12 is installed on your machine.
2. Create a Virtual Environment: Navigate to the STDATALOG-PYSDK root directory and run python -m venv .venv to create an isolated environment for your project dependencies.
3. Activate the Virtual Environment:
   • Windows: . \.venv\Scripts\activate
   • Linux/macOS: source .venv/bin/activate
4. Run the Installer:
   • Windows: .\STDATALOG-PYSDK_install.bat (Include proxy settings if necessary)
   • Linux/macOS: ./STDATALOG-PYSDK_install.sh (Include proxy settings if necessary, and use dos2unix to reformat files if on Linux/macOS)

Note: Using a virtual environment is highly recommended for managing dependencies and avoiding conflicts with other Python projects.

Cloning the Repository

To clone the STDATALOG-PYSDK repository correctly, use the following command:

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

This ensures that all linked submodules are included. For updates, use:

git pull
git submodule update --init --recursive

To clone a specific version (e.g., vX.Y.Z):

git clone --recursive --depth 1 --branch vX.Y.Z https://github.com/STMicroelectronics/stdatalog-pysdk.git

Example Usage

Once installed, explore the example scripts to see the STDATALOG-PYSDK in action:

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

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

Maximize Your Data Insights Today

The STDATALOG-PYSDK empowers you to efficiently capture, process, and visualize data, accelerating your data science and embedded design projects. By leveraging its modular architecture and comprehensive toolset, you can unlock valuable insights and drive innovation. Start using the STDATALOG-PYSDK today and transform your data into actionable intelligence.