Essential Sqlalchemy Mapping Python To Databases Pdf
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Essential SQLAlchemy
Author: Jason Myers
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2015-11-27
Dive into SQLAlchemy, the popular, open-source code library that helps Python programmers work with relational databases such as Oracle, MySQL, PostgresSQL, and SQLite. Using real-world examples, this practical guide shows you how to build a simple database application with SQLAlchemy, and how to connect to multiple databases simultaneously with the same metadata. SQL is a powerful language for querying and manipulating data, but it’s tough to integrate it with your application. SQLAlchemy helps you map Python objects to database tables without substantially changing your existing Python code. If you’re an intermediate Python developer with knowledge of basic SQL syntax and relational theory, this book serves as both a learning tool and a handy reference. Essential SQLAlchemy includes several sections: SQLAlchemy Core: Provide database services to your applications in a Pythonic way with the SQL Expression Language SQLAlchemy ORM: Use the object relational mapper to bind database schema and operations to data objects in your application Alembic: Use this lightweight database migration tool to handle changes to the database as your application evolves Cookbook: Learn how to use SQLAlchemy with web frameworks like Flask and libraries like SQLAcodegen
Flask Web Development
Author: Miguel Grinberg
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2018-03-05
Take full creative control of your web applications with Flask, the Python-based microframework. With the second edition of this hands-on book, youâ??ll learn Flask from the ground up by developing a complete, real-world application created by author Miguel Grinberg. This refreshed edition accounts for important technology changes that have occurred in the past three years. Explore the frameworkâ??s core functionality, and learn how to extend applications with advanced web techniques such as database migrations and an application programming interface. The first part of each chapter provides you with reference and background for the topic in question, while the second part guides you through a hands-on implementation. If you have Python experience, youâ??re ready to take advantage of the creative freedom Flask provides. Three sections include: A thorough introduction to Flask: explore web application development basics with Flask and an application structure appropriate for medium and large applications Building Flasky: learn how to build an open source blogging application step-by-step by reusing templates, paginating item lists, and working with rich text Going the last mile: dive into unit testing strategies, performance analysis techniques, and deployment options for your Flask application
Python for Data Analysis
Author: Wes McKinney
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2017-09-25
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples