A B testing analysis with confidence intervals and guardrails

                  import numpy as np
from statsmodels.stats.proportion import proportions_ztest, confint_proportions_2indep

control_conversions = 920
control_users = 12_500
treatment_conversions = 1_015
treatment_users = 12_430

z_stat, p_value = proportions_ztest(
    count=[treatment_conversions, control_conversions],
    nobs=[treatment_users, control_users],
)

ci_low, ci_high = confint_proportions_2indep(
    count1=treatment_conversions,
    nobs1=treatment_users,
    count2=control_conversions,
    nobs2=control_users,
    method='wald',
)

print({'z_stat': float(z_stat), 'p_value': float(p_value), 'ci': [float(ci_low), float(ci_high)]})