I am trying to pass a list like below to a sql query
x = ['1000000000164774783','1000000000253252111']
I am using sqlalchemy and pyodbc to connect to sql:
import pandas as pd
from pandas import Series,DataFrame
import pyodbc
import sqlalchemy
cnx=sqlalchemy.create_engine("mssql+pyodbc://Omnius:[email protected]:1433/Basis?driver=/opt/microsoft/sqlncli/lib64/libsqlncli-11.0.so.1790.0")
I tried using various string format functions to be used in the sql query. below is one of them
xx = ', '.join(x)
sql = "select * from Pretty_Txns where Send_Customer in (%s)" % xx
df = pd.read_sql(sql,cnx)
All of them seem to convert it into a numeric format
(1000000000164774783, 1000000000253252111) instead of ('1000000000164774783','1000000000253252111')
And hence the query fails as datatype of Send_Customer is varchar(50) in SQL
ProgrammingError: (pyodbc.ProgrammingError) ('42000', '[42000] [Microsoft][SQL Server Native Client 11.0]
[SQL Server]Error converting data type varchar to numeric. (8114) (SQLExecDirectW)')
[SQL: 'select * from Pretty_Txns where Send_Customer in (1000000000164774783, 1000000000253252111)']
As stated in the comment to the other answer, that approach can fail for a variety of reasons. What you really want to do is create an SQL statement with the required number of parameter placeholders and then use the params=
parameter of .read_sql_query()
to supply the values:
x = ['1000000000164774783','1000000000253252111']
placeholders = ','.join('?' for i in range(len(x))) # '?,?'
sql = f"select * from Pretty_Txns where Send_Customer in ({placeholders})"
df = pd.read_sql_query(sql, cnx, params=x)
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