Parametrizing dates in SQL IN clause - using cell magic in jupyter notebook - pandas

Question

Using MSSQL db as the backend, I have a cell in my notebook with this sql which works fine.
%%sql
select * from (
select count(*) as CNT, COL1,CONVERT(VARCHAR,CAST(CREATED_DATE AS date)) as dt from TABLE1
group by COL1,CONVERT(VARCHAR,CAST(CREATED_DATE AS date))
)t
PIVOT
(
sum(CNT) for [dt] in ([2022-07-25],[2022-07-26])
) AS PivotTable
I am trying to parameterize the [IN] clause in the pivot.
Tried a few things, but without much success
import pandas as pd
from datetime import datetime
rng = pd.date_range(end = datetime.today(), periods = 5).strftime('%Y-%m-%d').tolist()
#rng = format(','.join('[{}]'.format(i) for i in rng))
#rng = pd.date_range(end = datetime.today().date(), periods = 5)
print (rng)
['2022-07-26', '2022-07-27', '2022-07-28', '2022-07-29', '2022-07-30']
select * from (
select count(*) as CNT, COL1,CONVERT(VARCHAR,CAST(CREATED_DATE AS date)) as dt from TABLE1
group by COL1,CONVERT(VARCHAR,CAST(CREATED_DATE AS date))
)t
PIVOT
(
sum(CNT) for [dt] in (:rng)
) AS PivotTable
* mssql+pymssql://---
(pymssql._pymssql.ProgrammingError) (102, b"Incorrect syntax near '('.DB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\n")
[SQL: select * from (
select count(*) as CNT, COL1,CONVERT(VARCHAR,CAST(CREATED_DATE AS date)) as dt from TABLE1
group by COL1,CONVERT(VARCHAR,CAST(CREATED_DATE AS date))
)t
PIVOT
(
sum(CNT) for [dt] in (%(rng)s)
) AS PivotTable]
[parameters: {'rng': ['2022-07-26', '2022-07-27', '2022-07-28', '2022-07-29', '2022-07-30']}]
(Background on this error at: https://sqlalche.me/e/14/f405)
any ideas on how I can achieve this. I will try creating the entire query dynamically but it will be much better if I can pass the dates alone into the query.
thanks for your time.