import pandas as pd
import random
import datetime
def random_dt_bw(start_date,end_date):
days_between = (end_date - start_date).days
random_num_days = random.randrange(days_between)
random_dt = start_date + datetime.timedelta(days=random_num_days)
return random_dt
def generate_data(n=1000):
items = [f"i_{x}" for x in range(n)]
start_dates = [random_dt_bw(datetime.date(2020,1,1),datetime.date(2020,9,1)) for x in range(n)]
end_dates = [x + datetime.timedelta(days=random.randint(1,10)) for x in start_dates]
offerDf = pd.DataFrame({"Item":items,
"StartDt":start_dates,
"EndDt":end_dates})
transaction_items = [f"i_{random.randint(0,n)}" for x in range(5*n)]
transaction_dt = [random_dt_bw(datetime.date(2020,1,1),datetime.date(2020,9,1)) for x in range(5*n)]
sales_amt = [random.randint(0,1000) for x in range(5*n)]
transactionDf = pd.DataFrame({"Item":transaction_items,"TransactionDt":transaction_dt,"Sales":sales_amt})
return offerDf,transactionDf
q = """
SELECT A.*,B.TransactionDt,B.Sales
FROM
offerDf A
INNER JOIN
transactionDf B
ON
A.Item = B.Item AND
A.StartDt <= B.TransactionDt AND
A.EndDt >= B.TransactionDt;
"""
pandaSQL_solution = pysqldf(q)