Implemented it with SQL Procedure

CREATE OR REPLACE PROCEDURE %ZDJANGO.CLONE_DATABASE(sourceNS %String, targetNS %String)
LANGUAGE OBJECTSCRIPT
{
	new $namespace
	set $namespace = "%SYS"
	
	$$$ThrowOnError(##class(Config.Namespaces).Get(sourceNS, .sourceNSparams))
	$$$ThrowOnError(##class(Config.Namespaces).Get(targetNS, .targetNSparams))
	
	for kind="Globals", "Routines" {
		$$$ThrowOnError(##class(Config.Databases).Get(sourceNSparams(kind), .sourceDBparams))
		$$$ThrowOnError(##class(Config.Databases).Get(targetNSparams(kind), .targetDBparams))
		
		set from = sourceDBparams("Directory")
		set to = targetDBparams("Directory")
		
		quit:$Data(done(to))
		set done(to) = "" 
		
		$$$ThrowOnError(##class(SYS.Database).Copy(from, to, , , 4))
	}
} 

DANGER: Do not use it, made specifically for my case, it may overwrite database

Example of using SQLAlchemy+Pandas, works with this Cloud SQL as well

from sqlalchemy import create_engine
import pandas as pd

server = '<your-server-hostname>'
port = 1972
namespace = 'USER'
username = 'SQLAdmin'
password = '<YOUR_PASSWORD>'

url = f"iris://{username}:{password}@{server}:{port}/{namespace}"
print(url)
engine = create_engine(url)

df = pd.DataFrame({
    'int': [1, 2, 3, 4, 5],
    'float': [1.1, 2.2, 3.3, 4.4, 5.5],
    'string': ['a', 'b', 'c', 'd', 'e'],
    'datetime': pd.date_range('20130101', periods=5),
    'bool': [True, False, True, False, True]
})

# create a table in IRIS
df.to_sql('iris_table', engine, if_exists='replace', schema='sqlalchemy')

# read the table back from IRIS 
df2 =  pd.read_sql_table('iris_table', engine, schema='sqlalchemy')
# print the dataframe
print(df2)