Source code for mlprodict.grammar_sklearn.g_sklearn_identify

# -*- coding: utf-8 -*-
Helpers to identify an interpreter.

from import change_style
from .g_sklearn_linear_model import sklearn_logistic_regression, sklearn_linear_regression
from .g_sklearn_preprocessing import sklearn_standard_scaler
from .g_sklearn_tree import sklearn_decision_tree_regressor

[docs]def __pep8(): assert sklearn_decision_tree_regressor assert sklearn_linear_regression assert sklearn_logistic_regression assert sklearn_standard_scaler
[docs]def identify_interpreter(model): """ Identifies the interpreter for a *scikit-learn* model. :param model: model to identify :return: interpreter :githublink:`%|py|25` """ class_name = model.__class__.__name__ pyname = change_style(class_name) skconv = "sklearn_" + pyname loc = globals().copy() convs = {k: v for k, v in loc.items() if k.startswith("sklearn")} if len(convs) == 0: raise ValueError("No found interpreters, possibilities=\n{0}".format( "\n".join(sorted(loc.keys())))) if skconv in convs: return convs[skconv] else: # pragma: no cover raise NotImplementedError( "Model class '{0}' is not yet implemented. Available interpreters:\n{1}".format( class_name, "\n".join( sorted( convs.keys()))))