CODEWITHSUNDEEP
pythonsql-serverpandaspyodbc
m.gibin
m.gibin

Reputation: 137

"TypeError: 'NoneType' object is not iterable" from pandas read_sql

I am trying to run a SQL command using pyodbc in python. in which SQL command contains multiple SELECT commands and IF statements.

but I am getting an error as follows

columns = [col_desc[0] for col_desc in cursor.description]
TypeError: 'NoneType' object is not iterable

import pyodbc
import pandas as pd
conn = pyodbc.connect("DRIVER={SQL Server};"
                "SERVER=server_name;"
                "DATABASE=master;"
                "Trusted_Connection=yes;")
cursor = conn.cursor()
script="""

If object_id ('tempdb..#Temp1')is not null
drop table #Temp1
Select distinct  a1.some_ID into #Temp1
from DOC.dbo.Document_tbl (NOLOCK)a1
from #Temp1 a1
If object_id ('tempdb..#Temp2')is not null
Drop table #Temp2
select distinct v2.some_data
into #Temp2 from tbl_name (nolock) v2 

If object_id ('tempdb..#Results')is not null
drop table #Results
select distinct a1.*,b1.####
into #Results
from #Temp1 a1
left join #Temp2 b1 on a1.## = b1.##
Select * from #Results
"""

df = pd.read_sql(script, cnxn)
writer = pd.ExcelWriter('result.xlsx')
df.to_excel(writer, sheet_name ='bar')
writer.save()

Upvotes: 5

Views: 7308

Answers (2)

Suspicious_Gardener
Suspicious_Gardener

Reputation: 126

For anyone else who is still getting this error, I have found that for some statements (A window function that aggregated null values) I also need to include SET ANSI_WARNINGS OFF;.

Upvotes: 3

Gord Thompson
Gord Thompson

Reputation: 123849

SQL command text that contains multiple SQL statements is called an anonymous code block. An anonymous code block can return multiple results, where each result can be

  • a row count,
  • a result set containing zero or more rows of data, or
  • an error.

The following example fails ...

sql = """\
SELECT 1 AS foo INTO #tmp;
SELECT * FROM #tmp;
"""
df = pd.read_sql_query(sql, cnxn)
# TypeError: 'NoneType' object is not iterable

... because the first SELECT ... INTO returns a row count before the second SELECT returns its result set.

The fix is to start the anonymous code block with SET NOCOUNT ON; which suppresses the row count and only returns the result set:

sql = """\
SET NOCOUNT ON;
SELECT 1 AS foo INTO #tmp;
SELECT * FROM #tmp;
"""
df = pd.read_sql_query(sql, cnxn)
# no error

Upvotes: 5

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