What this book covers
Chapter 1, Optimal Python Development Life Cycle, helps you to understand the lifecycle of a typical Python project and its phases, with a discussion of best practices for writing Python code.
Chapter 2, Using Modularization to Handle Complex Projects, focuses on understanding the concepts of modules and packages in Python.
Chapter 3, Advanced Object-Oriented Python Programming, discusses how the advanced concepts of object-oriented programming can be implemented using Python.
Chapter 4, Python Libraries for Advanced Programming, explores advanced concepts such as iterators, generators, error and exception handling, file handling, and logging in Python.
Chapter 5, Testing and Automation with Python, introduces not only different types of test automation such as unit testing, integration testing, and system testing but also discusses how to implement unit tests using popular test frameworks.
Chapter 6, Advanced Tips and Tricks in Python, discusses advanced features of Python for data transformation, building decorators, and also how to use data structures including pandas DataFrames for analytics applications.
Chapter 7, Multiprocessing, Multithreading, and Asynchronous Programming, helps you to learn about different options for building multi-threaded or multi-processed applications using built-in libraries in Python.
Chapter 8, Scaling Out Python using Clusters, explores how to work with Apache Spark and how we can write Python applications for large data processing applications that can be executed using an Apache Spark cluster.
Chapter 9, Python Programming for the Cloud, discusses how to develop and deploy applications to a cloud platform and how to use Apache Beam in general and for Google Cloud Platform in particular.
Chapter 10, Using Python for Web Development and REST API, focuses on using the Flask framework to develop web applications, interact with databases, and build REST API or web services.
Chapter 11, Using Python for Microservices Development, introduces microservices and how to use the Django framework to build a sample microservice and integrate it with a Flask-based microservice.
Chapter 12, Building Serverless Functions using Python, addresses the role of serverless functions in cloud computing and how to build them using Python.
Chapter 13, Python and Machine Learning, helps you to understand how to use Python to build, train, and evaluate machine learning models and how to deploy them in the cloud.
Chapter 14, Using Python for Network Automation, discusses the use of Python libraries in fetching data from a network device and network management systems (NMSes) and for pushing configurational data to devices or NMSes.
