BayesianNetwork.py

from pgmpy.models import DiscreteBayesianNetwork
from pgmpy.factors.discrete import TabularCPD
from pgmpy.inference import VariableElimination

model = DiscreteBayesianNetwork([
    ('Rain', 'Traffic'),
    ('Traffic', 'Late')
])

rain_cpd = TabularCPD(
    variable='Rain',
    variable_card=2,
    values=[
        [0.7],
        [0.3]
    ]
)

traffic_cpd = TabularCPD(
    variable='Traffic',
    variable_card=2,
    values=[
        [0.8, 0.2],
        [0.2, 0.8]
    ],
    evidence=['Rain'],
    evidence_card=[2]
)

late_cpd = TabularCPD(
    variable='Late',
    variable_card=2,
    values = [
        [0.9, 0.3],
        [0.1, 0.7]
    ],
    evidence=['Traffic'],
    evidence_card=[2]
)

model.add_cpds(rain_cpd, traffic_cpd, late_cpd)

print("Model valid: ", model.check_model())

inference = VariableElimination(model)

result = inference.query(
    variables=['Late'],
    evidence={'Rain': 1}
)

print(result)