how to fix the error of sampling when the larger sampling than the population in AB test using python?

I am running A/B test on Data whose population is 6000 , but when I calculate the sampling , I face with the error saying "Cannot take a larger sample than population when 'replace=False'"

effect_size = sms.proportion_effectsize(0.13, 0.15)    
# Calculating effect size based on our expected rates
required_n = sms.NormalIndPower().solve_power(effect_size, power=0.8,  alpha=0.05,ratio=1)                                                  
# Calculating sample size needed

required_n = ceil(required_n)                          
# Rounding up to next whole number                          

print(required_n)

control_sample = df[df['variant'] == 'A'].sample(n=required_n, random_state=22)
treatment_sample = df[df['variant'] == 'B'].sample(n=required_n, random_state=22)

ab_test = pd.concat([control_sample, treatment_sample], axis=0)
ab_test.reset_index(drop=True, inplace=True)
ab_test