Sql With Python - Om Prakash Shakya - Bog

This book is about the recipes on PYODBC and SQLAlchemy to work with Microsoft SQL Server databases and its data in table. Here are various recipes covering almost all the activities that are required by a Data Engineer, Scientist, Analyst or Python Developer. The book is divided into two sections, PYODBC recipes SQLAlchemy recipies The topic starts with the heading or title and gives some context about the topic and the lists the complete code block of that topic. After that there may be one or more approaches or ways that we have implemented in that topic. The book covers the over the following topics and recipes, Introduction to Python, SQL, VS Code, Python extensions, pyodbc, sqlalchemy, odbc driver Guidance on installing python, VS code, pyodbc, sqlalchemy Setting up database, tables, and creating stored procedures used in this book. Then code recipes are divided into 2 parts, pyodbc recipes sqlalchemy recipes Both are covering the following topics, Multiple ways to prepare connection string and connecting SQL Server PYODBC connection, cursor, commit, execute, objects & methods CRUD Operations (insert, update, delete, and select/read data) with various approaches Handling parameters of parameterized SQL queries & USPs Handling SQL 'IN' operator parameters Handling multiple resultsets of USP How to handle multiple parameters Different approaches to create and pass parameters Cursor functions fetchall(), fetchone(), fetchval(), fetchmany(), rowcount etc. Accessing rows & columns of a result set Working with row by row or batch of rows pandas methods read_sql(), read_sql_query(), read_table() Calling stored procedures with & without parameters Working with multiple databases, and looping through list of databases Using 'with' statement SQLALCHEMY core data api SQLALCHEMY engine url, engine, connection, execute, cursor etc. SQLALCHEMY exec_driver_sql(), raw_connection(), etc. Working with pandas dataframe to insert & update multiple records And many more important topics in pyodbc, and sqlalchemy ...