Creating and Dropping Tables
Creating Table:
So far we have created two Tables with a set of Columns and constraints. The next thing is we have to emit DDL to the SQLite database (in this case) so that we can query with the tables. This can be done as shown below:
Python3
from sqlalchemy import create_engine# creating an engine objectengine = create_engine("sqlite+pysqlite:///:memory:", echo=True, future=True)# emitting DDLmetadata_object.create_all(engine) |
Output:
Dropping Table
The drop_all() method is used to drop all the tables in the metadata object.
Python
from sqlalchemy import create_engine# creating an engine objectengine = create_engine("sqlite+pysqlite:///:memory:", echo=True, future=True)# emitting DDLmetadata_object.drop_all(engine) |
Output:
Describing Databases with MetaData – SQLAlchemy
In this article, we are going to see how to describe Databases with MetaData using SQLAlchemy in Python.
Database Metadata describes the structure of the database in terms of Python data structures. The database usually consists of Tables and Columns. The Database Metadata serves us in generating SQL queries and Object Relational Mapping. It helps us in generating a Schema. The most fundamental objects of Database MetaData are MetaData, Table, and Column.