In an objective to build an open platform for Machine Learning workflows and better data analytics, the latest release of Activeeon's solution includes a native Python task.
To keep it to the main benefits:
- Analyzing data in Python using numpy, pandas, TensorFlow, etc. is now greatly simplified.
- Native Python tasks run 10 to 100 times faster than Jython tasks.
- It fully integrates with existing system such as Generic Information or Variable propagation.
- Multiple Python versions are supported , even within the same workflow.
How to
A simple drag and drop of a task like any existing ones.
Simply select the python version you need.
Access variables from created on other tasks or sent by the user.
Send information to other tasks through the result variable.
3 Step Setup
Step 1: Install the Python that you want to use on your machine.
Step 2: Install the libraries (numpy, pandas, TensorFlow, etc. ) that you want to use on your machine.
Step 3: Install a module called py4j on your machine with:
Python2: pip install py4j
Python3: pip3 install py4j
For more information, do not hesitate to look at the documentation and try it.
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