Read database into dataframe using pyodbc with parameterized query

问题

I'm using pyodbc to get data from a SQL Server, using the script shown here:

conn = pyodbc.connect('DSN=DATASOURCE')
tbl = "SELECT TableA.Field_1 \
    FROM TableA \
    WHERE TableA.Date>=2019/04/01"
SQL_Query = pd.read_sql_query(tbl, conn)
conn.close

Now I want to make this query into a Python function, where I can change the date (2019/04/01) in the example above as a function variable.

I found pyodbc offers parameterization, but all in the context of cursor.execute function.

Ideally, I'd like to create a function like this:

def DB_Query(date):
    conn = pyodbc.connect('DSN=DATASOURCE')
    tbl = "SELECT TableA.Field_1 \
    FROM TableA \
    WHERE TableA.Date>=?", date
    SQL_Query = pd.read_sql_query(tbl, conn)
    conn.close
    return SQL_Query

Apparently this doesn't work because tbl has to be a normal string, but is it possible to use pyodbc's parameterization feature together with pandas' pd.read_sql_query or pd.read_sql?

回答1:

You can parameterize read_sql_query in the same way as cursor.execute by setting the params parameter: https://pandas.pydata.org/docs/reference/api/pandas.read_sql_query.html

Example for SQL Server:

import pandas as pd

sql = '''
 select *
 from Table
 where Column = ?
'''
df = pd.read_sql(sql, params=[query_param])

Example for Oracle:

import pandas as pd

sql = '''
 select *
 from table
 where Column = :query_param
'''
df = pd.read_sql(sql, params={'query_param': 'query_value'})

来源：https://stackoverflow.com/questions/60384058/read-database-into-dataframe-using-pyodbc-with-parameterized-query