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One liner.Bidirectional integration enabling Python's data science ecosystem within .NET's FrameworX

Platform → Technology → Core → Real-Time | AI-Ready | .NET | Native | UNS | Python 

Language Selection Guide

Quick Selection Criteria

• C# - Maximum performance, real-time control, type safety
• Python - Data science, machine learning, rapid prototyping
• Both - C# for control logic, Python for analytics

Integration Patterns

1. Embedded Python Scripts

Python code runs within FrameworX's Script Tasks and Classes, with full access to tags and namespaces:

# Python accessing FrameworX tags
@Tag.Temperature = @Tag.SetPoint + 5
result = ProcessData(@Tag.ProductionRate)

2. Shell Integration

Execute external Python files while maintaining tag access:

Python and C# Integration Excellence

Solution-Specific Python Management

Call methods across languages

It not about the language syntax, it is the APIs you get access:

External Application APIs

• .NET SDK - Full platform access for C# applications
• Python SDK - Data access for analytics and ML applications

Using Python in the Solution

The Python Example illustrates how to use the Python and .NET languages for the Scripts.

This section presents a summary of that information, listing the modules in the solution where Python code can be used.

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Scripts Tasks and Classes

• Scripts / Tasks: Event driven or periodical tasks, running on the server computer. They can be written in Python, C# or VB.NET.
• Scripts / Classes: library of methods and functions that can be used on both server and client machines. They can be written in Python, C# or VB.NET.

Displays CodeBehind and Graphical Elements 

The Code Behind for the displays can be written in C#, VB.NET or JavaScript, not Python directly. But from the CodeBehind you can call tasks and methods, which can be written in Python. 

Shell Integration

• Shell Integration: allows you to execute Python code from external files.

This integration allows you to execute Python code from external files. Just create a Script Task with the following code:

result = TK.ExecutePythonShell("

analytics.py", [

@Tag.Input1, 

@Tag.Input2])
@Tag.Result = result

Testing the code

Designer Python Code Editor

Code Editor User Interface

The code editor can be accessed through Scripts / Code Editor.

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3.

Accessing Tags and Modules Properties

The access to tags and other properties for other models is exactly the same as C# or VB.NET; just use the '@' symbol to access the properties directly, as shown in the image: '@Tag.Tag1'.

.NET Interoperability

Calling ScriptClass Methods

In the Script, or in any place in your solution where Expressions are allowed, you can use the following syntax to call classes.

@Script.Class.TestClass.ExempleMethod(param1, param2)

This activation is independent of the language the class was created in.

This means C# and VB.NET can call Python classes, and Python code can call .NET classes.

Cross-Language Calls

C# calling Python:

// C# code calling Python class
var result = @Script.Class.PythonAnalytics.ProcessML(data);

Python calling C#:

# Python code calling C# method
result = @Script.Class.CSharpLogic.Calculate(param1, param2)

Direct Access Architecture

Python code accesses FrameworX objects directly through the same '@' notation used in C#:

• @Tag - Real-time tag values
• @Dataset - Database queries
• @Alarm - Alarm states
• @Historian - Time-series data

No marshaling, conversion, or intermediate layers, Python operates on the same objects as .NET code.

Development Environment

Solution-Specific Python

Each solution specifies its Python interpreter, enabling:

• Different Python versions per project
• Isolated package environments
• Consistent deployment across development and production

In-Designer Features

• Code Editor - Python syntax highlighting and IntelliSense
• Testing - Run Python scripts directly in Designer
• Debugging - Output window for print statements and errors
• Tag Access - Auto-completion for all namespace objects

Industrial Use Cases

Machine Learning Integration

# Use scikit-learn for anomaly detection
from sklearn.ensemble import IsolationForest
model = IsolationForest()
data = GetHistorianData(@Tag.Equipment)
anomalies = model.fit_predict(data)

Data Analysis

# Pandas for production analytics
import pandas as pd
df = pd.DataFrame(@Dataset.Query("SELECT * FROM Production"))
daily_avg = df.groupby('Day')['Output'].mean()
@Tag.DailyAverage = daily_avg.iloc[-1]

Custom Protocols

# Implement proprietary protocol
import struct
packet = struct.pack('>HH', @Tag.DeviceID, @Tag.Command)
response = SendCustomProtocol(packet)
@Tag.Response = struct.unpack('>H', response)[0]

System Requirements

• Python Version: 3.7 or later (3.11 recommended)
• Python.NET: Required for integration (pip install pythonnet)
• Installation: System-wide (all users) for service deployment
• Path: Python.exe must be in system PATH

Performance Considerations

Key Advantages

• No Bridge Required - Direct integration via Python.NET
• Shared Memory Space - Zero-copy data access between languages
• Production Ready - Runs as Windows service, handles 24/7 operation
• Version Flexibility - Multiple Python versions on same server
• Library Access - Full Python Package Index (PyPI) availability

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