Data science friendly ORM (Object Relational Mapping) library combining Python, Pandas, and various SQL dialects For full documentation see official documentation - currently unavailable but we're working on it!
Use the package manager pip to install dbhydra.
pip install dbhydraimport dbhydra.dbhydra_core as dh
db1=dh.db()
table1 = dh.Table(db1,"test",["test1","test2","test3","test4"],["int","int","int","int"])
#table1.drop()
#table1.create()
#rows=[[1,2,3,4],[5,4,7,9]]
#table1.insert(rows)
list1=table1.select("SELECT * FROM test")
print(list1)
#list2=table1.select_all()
#print(list2)
#table1.drop()
table1.export_to_xlsx()
tables=db1.get_all_tables()
table_dict=db1.generate_table_dict()
print(tables)
columns=table_dict['test'].get_all_columns()
types=table_dict['test'].get_all_types()
print(columns,types)
table_test=dh.Table.init_all_columns(db1,"test")
print(table_test.columns)
table2 = dh.Table(db1,"test_new",["id","test2"],["int","nvarchar(20)"])
#table2.create()
#table2.drop()Aims: Easy integration with Pandas, SQL SERVER/MySQL database, and exports/imports to/from excel/CSV format
Done: Table functions (Create, Drop, Select, Update, Insert, and Delete) should be working fine
Todo: Group by, Order by, Where, Linking of FK, Customizable PK,...
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.