Applied Data Science Coding Recipes: Python and RDBMS

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Applied Data Science Coding Recipes: Python and RDBMS

 

Python and RDBMS (Relational Database Management Systems) are a powerful combination for working with data. RDBMS is a software that allows you to store, manage, and retrieve data in a structured way. Python provides several libraries that can be used to interact with RDBMS.

Python libraries that can be used to interact with RDBMS include:

SQLAlchemy: It is a powerful and flexible Object Relational Mapping (ORM) library that allows you to interact with RDBMS using Python objects.

PyMySQL: It is a simple library that allows you to connect to and interact with a MySQL database using Python.

psycopg2: It is a library that allows you to interact with a PostgreSQL database using Python.

These libraries allow you to connect to a RDBMS, execute SQL statements, retrieve data, and perform other operations.

You can use these libraries to create a connection to a RDBMS and execute SQL statements to retrieve data, insert, update or delete data in the RDBMS. These libraries also provide a way to interact with the RDBMS using Python objects, making it easier to work with data in a programmatic way.

In summary, Python and RDBMS are a powerful combination for working with data. RDBMS is a software that allows you to store, manage, and retrieve data in a structured way. Python provides several libraries that can be used to interact with RDBMS such as SQLAlchemy, PyMySQL, and psycopg2. These libraries allow you to connect to a RDBMS, execute SQL statements, retrieve data, and perform other operations. They also provide a way to interact with the RDBMS using Python objects, making it easier to work with data in a programmatic way.

 

In this Applied Machine Learning Recipe, the reader will learn: Python and RDBMS.



Applied Data Science Coding Recipes: Python and RDBMS

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