Which Database Is Best For Python
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Using SQLite
Author: Jay Kreibich
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2010-08-17
Explains how to build database-backed applications for the Web, desktop, embedded systems, and operating systems using SQLite.
Python Data Persistence
Designed to provide an insight into the SQL and MySQL database concepts using python DESCRIPTION Python is becoming increasingly popular among data scientists. However, analysis and visualization tools need to interact with the data stored in various formats such as relational and NOSQL databases. This book aims to make the reader proficient in interacting with databases such as MySQL, SQLite, MongoDB, and Cassandra. This book assumes that the reader has no prior knowledge of programming. Hence, basic programming concepts, key concepts of OOP, serialization and data persistence have been explained in such a way that it is easy to understand. NOSQL is an emerging technology. Using MongoDB and Cassandra, the two widely used NOSQL databases are explained in detail. The knowhow of handling databases using Python will certainly be helpful for readers pursuing a career in Data Science. KEY FEATURES A practical approach Ample code examples A Quick Start Guide to Python for beginners WHAT WILL YOU LEARN Python basics and programming fundamentals Serialization libraries pickle, CSV, JSON, and XML DB-AP and, SQLAlchemy Python with Excel documents Python with MongoDB and Cassandra WHO THIS BOOK IS FOR Students and professionals who want to become proficient at database tools for a successful career in data science. Table of Contents 1. Ê Ê Getting Started 2. Ê Ê Program Flow Control 3. Ê Ê Structured Python 4. Ê Ê Python Ð OOP 5. Ê Ê File IO 6. Ê Ê Object Serialization 7. Ê Ê RDBMS Concepts 8. Ê Ê Python DB-API 9. Ê Ê Python Ð SQLAlchemy 10. Ê Python and Excel 11. Ê Python Ð PyMongo 12. Ê Python Ð Cassandra
Python for Finance
Author: Yves J. Hilpisch
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2018-12-05
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.