Expanding EAM Capabilities with Python: The Flexibility and Power of HxGN EAM's Python Framework

Julio Roque

Python is a popular scripting language. It’s considered the standard programming language for creating Machine Learning and Data Science models and applications. Python also adds significant capabilities to Enterprise Asset Management (EAM) applications due to its ease of use and wide range of libraries. It can automate tasks, extend applications and create custom functions. Some of the benefits of using Python for expanding EAM applications include:

• Ease of use - Python has a simple and easy-to-understand syntax, making it accessible to EAM users with varying levels of programming experience. The reduced learning curve enables a quick contribution to any EAM project.

• Increased flexibility – Python has a large and active community of developers who contribute libraries and frameworks available to extend and customize your EAM projects.

• Improved efficiency – Using Python, EAM users can quickly develop scripts to automate tasks, improving the efficiency of EAM workflow creation and troubleshooting.

HxGN EAM makes this powerful capability available to its customers via a fully integrated Python framework. This framework has two major components:

• HxGN EAM Python Studio, powered by JupyterLab – a fully integrated scripting environment leveraging the extensive abilities of JupyterLab, the industry standard for writing Python scripts. These are full Python 3 scripts, with access to Python’s extensive flexibility and libraries, access to the rich set of APIs provided by HxGN EAM, both Representational State Transfer (REST) and Simple Object Access Protocol (SOAP), and access to public APIs.

• HxGN EAM Flex Python infrastructure – a robust Kubernetes-based infrastructure that executes the Python scripts with minimal performance impact to HxGN EAM.

How can the flexibility and power of HxGN EAM’s Flex Python help my EAM project?

From simple lines of Python to enhancing an EAM function, to developing machine learning models for predictive analytics, or implementing Monte Carlo simulations and triggering work orders based on weather alerts…the possibilities are endless!

Using Python as a scripting language to expand HxGN EAM can enable EAM users to write scripts quickly, leverage existing libraries and frameworks, and integrate with other technologies, resulting in more efficient and effective EAM solutions.