m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code (Python, C, Java).

• Installation
• Supported Languages
• Supported Models
• Classification Output
• Usage
• CLI
• FAQ

Supported Python version is >= 3.4.

pip install m2cgen

• Python
• Java
• C

Here's a simple example of how a trained linear model can be represented in Java code:

from sklearn.datasets import load_boston
from sklearn import linear_model
import m2cgen as m2c

boston = load_boston()
X, y = boston.data, boston.target

estimator = linear_model.LinearRegression()
estimator.fit(X, y)

code = m2c.export_to_java(estimator)

The example of the generated code:

public class Model {

    public static double score(double[] input) {
        return (((((((((((((36.45948838508965) + ((input[0]) * (-0.10801135783679647))) + ((input[1]) * (0.04642045836688297))) + ((input[2]) * (0.020558626367073608))) + ((input[3]) * (2.6867338193449406))) + ((input[4]) * (-17.76661122830004))) + ((input[5]) * (3.8098652068092163))) + ((input[6]) * (0.0006922246403454562))) + ((input[7]) * (-1.475566845600257))) + ((input[8]) * (0.30604947898516943))) + ((input[9]) * (-0.012334593916574394))) + ((input[10]) * (-0.9527472317072884))) + ((input[11]) * (0.009311683273794044))) + ((input[12]) * (-0.5247583778554867));
    }
}

You can find more examples of generated code for different models/languages here

m2cgen can be used as a CLI tool to generate code using serialized model objects (pickle protocol):

$ m2cgen <pickle_file> --language <language> [--indent <indent>]
         [--class_name <class_name>] [--package_name <package_name>]
         [--recursion-limit <recursion_limit>]

Piping is also supported:

$ cat <pickle_file> | m2cgen --language <language>

Q: Generation fails with RuntimeError: maximum recursion depth exceeded error.

A: If this error occurs while generating code using an ensemble model, try to reduce the number of trained estimators within that model. Alternatively you can increase the maximum recursion depth with sys.setrecursionlimit(<new_depth>).