generating dynamic query in python

Question

I have a list which contain tablename like table A, table B , table C ... etc. This list of tables may change depend upon some conditions . Sometime list may have 4 tables or 6 tables .

tables = [table A, table B , table C, table D]

schema definition of tables present in list is same .

i want to generate a query as below .

select col A from table A 
union distinct    
select col A from table B
 union distinct 
 select col A from table C 
 union distinct  select col A
 from table D

size of query may increase or decrease depending upon tables in list

Once query is prepared . its needs to be executed in bigquery via python

Yev Guyduy · Accepted Answer · 2022-02-03 17:04:21Z

Given question I am not sure about overall setup and where this final query needs to be executed.

Since title of question has "dynamic" in it I am providing a solution using f strings which should allow most dynamic insertion.

Here is a way using f strings and pandas library for Big query.

import pandas as pd
from pandas.io import gbq

### create your final sql string to be executed to which you will append
final_sql_string = """
"""

tables = ['table_A', 'table_B', 'table_C', 'table_D']

for table in tables:

    ### if this is your last table in list no need for union
    if table == tables[-1]:

        ### build out your query via f string 
        sql_string= f"""select col_A from `your_project.your_dataset.{table}`"""

        ### join via newline to your final sql query string
        final_sql_string = "\n".join((final_sql_string, sql_string))

    ### if table is not last table then need to union
    else:
        sql_string= f"""select col_A from `your_project.your_dataset.{table}` union distinct """
        final_sql_string = "\n".join((final_sql_string, sql_string))


### optional - check what your sql looks like        
print(final_sql_string)

### submit to bq via pandas to get a pandas dataframe back
### on first try will ask to authorize against your project    
pandas_dataframe_from_sql = gbq.read_gbq(final_sql_string,
                                         project_id = 'your_project_id')

Sample of print statement from above

select col_A from `your_project.your_dataset.table_A` union distinct 
select col_A from `your_project.your_dataset.table_B` union distinct 
select col_A from `your_project.your_dataset.table_C` union distinct 
select col_A from `your_project.your_dataset.table_D`

If you are executing via google cloud SDK you can insert this sql within as well.

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