searope

import itertools

my_dict = {'A':['D','E'],'B':['F','G','H'],'C':['I','J']}
keys, values = zip(*my_dict.items())
permutations_dicts = [dict(zip(keys, v)) for v in itertools.product(*values)]

# this will provide you a list of dicts with the permutations:

print(permutations_dicts)
#[{'A':'D', 'B':'F', 'C':'I'}, 

searope

import random
import time
import multiprocessing as mp
import itertools as it

# just an example generator to prove lazy access by printing when it generates
def get_counter(limit=10):
    for i in range(limit):
        for j in range(limit):
            print(f"YIELDED: {i},{j}")

searope

import numpy as np

from sklearn.preprocessing import QuantileTransformer
from sklearn.metrics._scorer import _BaseScorer


class FuncScorer(_BaseScorer):
    def _score(self, method_caller, estimator, X, y_true, sample_weight=None):
        """Evaluate predicted target values for X relative to y_true.