The Fanuc FOCAS (Fanuc Open CNC API Specifications) library is the standard protocol for extracting real-time data from Fanuc CNC controllers. While Fanuc does not provide official Python hooks, developers use community-driven wrappers or custom libraries to interface with the native C libraries. FOCAS Overview and Setup
To use FOCAS with Python, the CNC machine must be configured for Ethernet communication. Versions:
FOCAS 1: Older library for legacy CNCs, typically used with Windows 7.
FOCAS 2: Modern library compatible with newer controllers and Windows 10/11. Machine Configuration: Access the SYSTEM hardkey and navigate to EMBDD settings. Set a static IP address, Subnet, and Gateway. Set the FOCAS port to TCP 8193. Restart the CNC to apply changes. Python Integration Options
Since there is no native Python library from Fanuc, you must use one of the following methods: pyfanuc · PyPI
Unlocking the data within your FANUC CNC machine doesn't require complex proprietary software. By combining FANUC FOCAS (Fanuc Open CNC API Specifications) with Python, you can build custom, automated tools for real-time monitoring, predictive maintenance, and production reporting. What is FANUC FOCAS?
FANUC FOCAS is a set of library files (DLLs) that allow external applications to communicate with FANUC CNC controllers. It serves as a bridge, enabling you to "ask" the CNC for specific information—ranging from axis positions and spindle loads to active alarm messages—and receive detailed data in return. There are two primary versions:
FOCAS 1: Designed for older CNCs and Windows versions up to Windows 7.
FOCAS 2: Supports modern CNCs and newer operating systems like Windows 10 and 11. Why Use Python for FOCAS?
While the FOCAS libraries were originally built for C/C++ or C#, using Python offers several advantages:
Rapid Development: Python's simple syntax allows you to prototype data collection scripts in a fraction of the time required by compiled languages.
Ecosystem: You can easily pipe CNC data directly into Python’s powerful data analysis libraries (like Pandas or NumPy) or visualization tools.
Platform Independence: While the official DLLs are Windows-based, certain Python wrappers and protocol analysis projects aim to extend functionality to Linux or Raspberry Pi environments. Essential Python Libraries
To get started, you don't need to write low-level protocol code from scratch. Several community-driven libraries simplify the connection: fanuc focas python
pyfanuc : A popular open-source library for connecting to controllers to read macro variables, axis data (speed/load), and positions.
Fanuc.py: A Python SDK that supports multiple protocols, including file transfers (FTP) and high-speed industrial protocols (SNPX).
ChatterTools : A higher-level library specifically designed for interfacing with various CNC machines, including FANUC, to fetch machine state data. pyfanuc · PyPI
The Challenge
John, a skilled CNC programmer, was tasked with automating a complex machining process on a FANUC-controlled CNC machine. The goal was to write a program that could read data from a file, send it to the CNC machine, and then retrieve the machining results. The catch was that the CNC machine was located in a different part of the factory, and John needed to control it remotely.
The Solution
John had heard about FANUC's FOCAS (FANUC Open CNC API) library, which allowed developers to create custom applications to control FANUC CNC machines. He decided to use Python, a language he was familiar with, to create a program that could communicate with the CNC machine using FOCAS.
John downloaded the FANUC FOCAS Python library and started studying the documentation. He was impressed by the simplicity and flexibility of the API. With FOCAS, he could read and write data to the CNC machine, execute programs, and even retrieve machining results.
The Code
John wrote a Python script that used the FOCAS library to connect to the CNC machine. He imported the necessary modules and created a Focas object to represent the CNC machine.
import focas
# Create a Focas object
cnc = focas.Focas("192.168.1.100", 8193) # IP address and port of the CNC machine
# Read data from a file
with open("data.txt", "r") as f:
data = f.read()
# Send the data to the CNC machine
cnc.write(100, data) # 100 is the address where the data will be written
# Execute a program on the CNC machine
cnc.exec_program(" machining_program")
# Retrieve machining results
results = cnc.read(200, 100) # 200 is the address where the results are stored, 100 is the length of the data
# Print the results
print(results)
The Result
John ran the script, and to his delight, it worked seamlessly. The CNC machine received the data, executed the program, and sent back the machining results. John was able to monitor the process remotely and verify that the results were accurate.
The automation of the machining process not only saved John time but also improved the overall efficiency of the factory. The use of FANUC FOCAS Python library allowed John to create a custom solution that met the specific needs of the factory. The Fanuc FOCAS (Fanuc Open CNC API Specifications)
The Future
John's success with FANUC FOCAS Python sparked his interest in exploring more automation projects. He began to investigate other FANUC products and tools, such as the FANUC ROBOT and FANUC's IIoT platform. He realized that the possibilities for automation and innovation were endless, and he was excited to see what the future held.
From that day on, John became a advocate for using FANUC FOCAS Python in automation projects, sharing his knowledge and expertise with others in the industry. The story of John and his FANUC FOCAS Python project served as an inspiration to others, demonstrating the power of automation and the importance of innovation in manufacturing.
Unlocking the Power of FANUC FOCAS with Python: A Comprehensive Guide
In the world of industrial automation, FANUC is a well-known and respected name, particularly in the realm of CNC (Computer Numerical Control) machines. One of the key features that sets FANUC apart is its FOCAS (FANUC Open Architecture and Communications) interface, which allows developers to access and control FANUC devices programmatically. In recent years, Python has emerged as a popular choice for interacting with FANUC devices via FOCAS, thanks to its ease of use, flexibility, and extensive libraries. In this article, we'll delve into the world of FANUC FOCAS and Python, exploring the benefits, tools, and techniques for leveraging this powerful combination.
What is FANUC FOCAS?
FANUC FOCAS is an open architecture and communication interface developed by FANUC, allowing users to access and control FANUC devices, such as CNC machines, robots, and servo drives, using a variety of programming languages. FOCAS provides a set of APIs (Application Programming Interfaces) that enable developers to read and write data, execute commands, and monitor the status of FANUC devices. This interface is designed to facilitate the integration of FANUC devices with external systems, such as MES (Manufacturing Execution Systems), ERP (Enterprise Resource Planning) systems, and custom applications.
Why Python for FANUC FOCAS?
Python has become a popular choice for working with FANUC FOCAS due to its:
Getting Started with FANUC FOCAS and Python
To start working with FANUC FOCAS and Python, you'll need:
PyFOCAS Library
PyFOCAS is a Python library developed by FANUC, which simplifies the interaction with FANUC devices via FOCAS. The library provides a set of Python classes and functions that allow developers to: The Result John ran the script, and to
Here's an example PyFOCAS code snippet:
import pyfocas
# Establish a connection to the FANUC device
dev = pyfocas.FocasDevice('192.168.1.100', 8193)
# Read the current position of axis 1
position = dev.read_axis_position(1)
print(position)
# Execute a program on the FANUC device
dev.execute_program('my_program')
Example Applications
The combination of FANUC FOCAS and Python opens up a wide range of possibilities for automation, data analysis, and custom application development. Here are some example applications:
Best Practices and Tips
When working with FANUC FOCAS and Python, keep in mind:
Conclusion
The combination of FANUC FOCAS and Python offers a powerful and flexible solution for automation, data analysis, and custom application development. By leveraging the PyFOCAS library and Python's extensive libraries and community resources, developers can unlock the full potential of FANUC devices and create innovative solutions that transform industries. Whether you're a seasoned developer or just starting out, this article should have provided a comprehensive introduction to the world of FANUC FOCAS and Python.
pyfanucIf you do not want to manually define ctypes structures, there are open-source wrappers like pyfanuc on PyPI (though maintenance varies).
To use a wrapper (if available/compatible):
pip install pyfanuc
from pyfanuc import fanuc
cnc = fanuc.Fanuc('192.168.1.100')
if cnc.connect():
print(cnc.get_position())
cnc.disconnect()
Note: Using raw ctypes is often preferred in industrial environments because it does not depend on a third-party Python package maintainer.
fwlib = ctypes.windll.fwlib32
with FanucConnection("192.168.1.100") as cnc: print(cnc.read_position())
| Package | Method | Ease | Features |
|---------|--------|------|----------|
| fanuc-focas (pip) | ctypes wrapper | ⭐⭐⭐⭐⭐ | Limited |
| pyfanuc (pip) | ctypes wrapper | ⭐⭐⭐⭐ | Moderate |
| Custom ctypes | Direct | ⭐⭐ | Full control |