Python to MSSQL

 import pandas as pd

import pyodbc

from sqlalchemy import create_engine # pip install SQLAlchemy

from sqlalchemy.engine import URL

import pypyodbc # pip install pypyodbc

# Database connection settings

server = 'serverName'

database = 'DB_Name'

username = 'un'

password = 'pw'

from sqlalchemy.types import (

    Boolean,

    Date,

    DateTime,

    Float,

    Integer,

    SmallInteger,

    String,

    Unicode,

    BigInteger,

)

def get_sqlalchemy_types(df_types):

    # dictionary mapping pandas dtypes to SQLAlchemy types

    dtype_to_sqlalchemy_type = {

        # 'int64': BigInteger,

        # 'float64': Float,

        'object': Unicode(length=255),

        # 'datetime64[ns]': DateTime

    }    

    # create an empty dictionary to store column names and SQLAlchemy types

    col_dict = {}    

    # loop through columns and add name and type to dictionary

    for col in df_types.columns:

        col_dtype = str(df_types[col].dtype)

        if col_dtype in dtype_to_sqlalchemy_type.keys():

            sqlalchemy_type = dtype_to_sqlalchemy_type[col_dtype]

            col_dict[col] = sqlalchemy_type

   

    return col_dict

conn_str = f'DRIVER={{ODBC Driver 17 for SQL Server}};SERVER={server};

                DATABASE={database};UID={username};PWD={password}'

conn = pyodbc.connect(conn_str)

connection_url = URL.create('mssql+pyodbc', query={'odbc_connect': conn_str})

enigne = create_engine(connection_url, module=pypyodbc)

result.to_sql('tablename', enigne, if_exists='append', index=False, schema='dbo',

dtype=get_sqlalchemy_types(result),

chunksize=100)

conn.close()