sqlalchemy-iris

this is perfect idea and well implemented too.

It simplifies the integration of Python and IRIS. It supports various features such as schema, stream, datetime, read, and write

SQL Alchemy with IRIS is a great way to simplify the bridge between IRIS and Python objects.
Thanks @Dmitry Maslennikov for this brilliant idea to write this IRIS dialect for SQLAlchemy.

If you're looking to effortlessly link your Python apps with InterSystems IRIS databases, give SQLAlchemy-Iris a try. This handy tool acts as a smooth bridge between the two, blending the power of SQLAlchemy with InterSystems IRIS' features.

It support schema, stream, datetime, read, write !

import pandas as pd
from sqlalchemy import create_engine
engine = create_engine("iris://_SYSTEM:SYS@localhost:53126/IRISAPP")

# create fake dataframes with a bunch of columns types
# and a bunch of rows
# columns types are: int, float, string, datetime, bool
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('select * from sqlalchemy.iris_table', engine)

# print the dataframe
print(df2)

# print the table types in iris with sql type and class type
sql_def = """
SELECT Tables.TABLE_SCHEMA, Tables.TABLE_NAME, Columns.COLUMN_NAME, Columns.DATA_TYPE, Prop.Type
FROM INFORMATION_SCHEMA.TABLES AS Tables
INNER JOIN INFORMATION_SCHEMA.COLUMNS AS Columns 
    ON (Columns.TABLE_SCHEMA = Tables.TABLE_SCHEMA) AND (Columns.TABLE_NAME = Tables.TABLE_NAME)
INNER JOIN %Dictionary.CompiledProperty AS Prop 
    ON (Prop.parent = Tables.CLASSNAME and Prop.Name = Columns.COLUMN_NAME)
WHERE Tables.TABLE_NAME = 'iris_table' and Tables.TABLE_SCHEMA = 'sqlalchemy'"""

# execute the sql
df3 = pd.read_sql(sql_def, engine)

# print the dataframe
print(df3)

Result :

   index  int  float string             datetime  bool
0      0    1    1.1      a  2013-01-01 00:00:00     1
1      1    2    2.2      b  2013-01-02 00:00:00     0
2      2    3    3.3      c  2013-01-03 00:00:00     1
3      3    4    4.4      d  2013-01-04 00:00:00     0
4      4    5    5.5      e  2013-01-05 00:00:00     1
  TABLE_SCHEMA  TABLE_NAME COLUMN_NAME    DATA_TYPE                     Type
0   sqlalchemy  iris_table       index       bigint          %Library.BigInt
1   sqlalchemy  iris_table         int       bigint          %Library.BigInt
2   sqlalchemy  iris_table       float       double          %Library.Double
3   sqlalchemy  iris_table      string  longvarchar  %Stream.GlobalCharacter
4   sqlalchemy  iris_table    datetime    timestamp        %Library.DateTime
5   sqlalchemy  iris_table        bool          bit         %Library.Boolean