Fetch data from multiple result sets - SQL Server to Python

Question

How to union or make the multiple results sets to one, so that I can fetch the data to python dataframe

EXEC sp_MSforeachdb
@command1 = '
IF not exists(select 1 where ''?'' in  (''master'',''model'',''msdb'',''tempdb'',''dpa_dpa_sw1'',''dpa_repository''))


EXEC [?].dbo.sp_MSforeachtable
 @command1 = ''SELECT TOP 1 db_name() AS DB_Name, ''''&'''' AS  Table_name , * from &'', @replacechar=''&'' '

Python Trial

def db_connect ():
    server, username, password = 'xx.xx.xx.xx', 'sa', 'xxxx'
    conn = pyodbc.connect('DRIVER={ODBC Driver 17 for SQL Server};'
                          'SERVER=' + server
                          + ';UID=' + username + ';PWD=' + password)
    cursor = conn.cursor()
    query = ("EXEC sp_MSforeachdb @command1 = 'IF not exists(select 1 where ''?'' "
             "in  (''master'',''model'',''msdb'',''tempdb'')) EXEC [?].dbo.sp_MSforeachtable"
             " @command1 = ''SELECT TOP 1 db_name() AS DB_Name, ''''&'''' AS  Table_name"
             " , * from &'', @replacechar=''&'' ';")
    df = pd.read_sql(query, conn)
    conn.close()
    return df
df = db_connect()

Result

| DB_Name | Table_name          | id | _NAME           | _NUMERICID | _VALUE | _TIMESTAMP              | _QUALITY |
|---------|---------------------|----|-----------------|------------|--------|-------------------------|----------|
| aaaa    | [dbo].[aaa_exhaust] | 1  | aaaa_vib.00.41 | 0          | 2085   | 2022-08-06 00:30:43.517 | 192      |

In the above case I get only 1st result set, I need results of all result sets in dataframe.

Answer 1

I'm not sure if Pandas can handle multiple result sets like that. You can always use pyodbc's cursor functionality to iterate the multiple result sets, though, and construct a DataFrame like the following...

import pandas as pd
import pyodbc

server, username, password = "127.0.0.1,1433", "sa", "StrongPassw0rd"
connstring = "DRIVER={ODBC Driver 17 for SQL Server};SERVER="+server+";UID="+username+";PWD="+password
conn = pyodbc.connect(connstring)
cursor = conn.cursor().execute("""
select 1 as A;
select 2 as B;
select 3 as C;
""")

buffer = []
while True:
    # Get the column names for the current result set
    columnNames = [col[0] for col in cursor.description]

    # Get the data rows for the current result set
    for dataRow in cursor.fetchall():
        buffer.append({name: dataRow[index] for index, name in enumerate(columnNames)})

    # Iterate to the next result set, otherwise we're "done"
    if not cursor.nextset():
        break

cursor.close()
conn.close()

# Convert the buffer to a DataFrame and display the result
df = pd.DataFrame(buffer)
print(df.to_string())

Which outputs the following:

     A    B    C
0  1.0  NaN  NaN
1  NaN  2.0  NaN
2  NaN  NaN  3.0