Use PMML models in Python

Question

I've found many topics related to this on the Internet but I could find no solutions.

Suppose I want to download any PMML model from this examples list, and run them in Python (Python 3 preferably). Is there any way to do this?

I'm looking for a way to import a PMML that was deployed OUTSIDE Python and import it to use it with this language.

Answer 1

After some research I found the solution to this: the 'openscoring' library.

Using it is very simple:

import subprocess
from openscoring import Openscoring
import numpy as np

p = subprocess.Popen('java -jar openscoring-server-executable-1.4.3.jar',
             shell=True)

os = Openscoring("http://localhost:8080/openscoring")

# Deploying a PMML document DecisionTreeIris.pmml as an Iris model:   
os.deployFile("Iris", "DecisionTreeIris.pmml")

# Evaluating the Iris model with a data record:
arguments = {
    "Sepal_Length" : 5.1,
    "Sepal_Width" : 3.5,
    "Petal_Length" : 1.4,
    "Petal_Width" : 0.2
}
result = os.evaluate("Iris", arguments)
print(result)

This returns the value of the target variable in a dictionary. There is no need to go outside of Python to use PMML models anymore (you just have to run the server with Java, which can be done with Python as well as I showed above).

Answer 2

Isn't it like trying to host H2O models in python apps? Looks like a bridge from python to Java is required here too. Such bridges are not stable at all, been there, tested them. Just a general suggestion: do not mix languages between ML algos and apps code, train in python, serve in python, re-validate also in python. Legacy R and H2O models can be always re-fitted in python.

Answer 3

You could use PyPMML to apply PMML in Python, for example:

from pypmml import Model

model = Model.fromFile('DecisionTreeIris.pmml')
result = model.predict({
    "Sepal_Length" : 5.1,
    "Sepal_Width" : 3.5,
    "Petal_Length" : 1.4,
    "Petal_Width" : 0.2
})

For more info about other PMML libraries, be free to see: https://github.com/autodeployai