Build production-ready applications using advanced
Python concepts and industry best practices

About the author
Muhammad Asif is a principal solution architect with a wide range of multi-disciplinary
experience in web development, network and cloud automation, virtualization, and
machine learning. With a strong multi-domain background, he has led many large-scale
projects to successful deployment. Although moving to more leadership roles in recent
years, Muhammad has always enjoyed solving real-world problems by using appropriate
technology and by writing the code himself. He earned a Ph.D. in computer systems
from Carleton University, Ottawa, Canada in 2012 and currently works for Nokia as
a solution lead.

About the reviewers
Harshit Jain is a data scientist with 5 years of programming experience, helping
companies build and apply advanced machine learning algorithms to enhance business
efficiency. He has a broad understanding of data science, ranging from classical machine
learning to deep learning and computer vision. He is very skilled at applying data science
techniques to e-commerce firms. During his spare time, he mentors aspiring data
scientists to sharpen their skills. His talks and articles, including Learning the Basics of
Data Science and How to Check the Impact on Marketing Activities – Market Mix Modeling,
show that data science is not just his profession but a passion. Reviewing this book is his
first, but certainly not the last, attempt to consolidate his valuable Python knowledge to
help you in your learning.
Sourabh Bhavsar is a senior full stack developer, agile, and cloud practitioner with over
7 years of experience in the software industry. He has completed a postgraduate course
in artificial intelligence and machine learning from the University of Texas at Austin,
and also holds an MBA (in marketing) and a bachelor's degree in engineering (IT) from
the University of Pune, India. He currently works at PayPal as a lead technical member
where he is responsible for designing and developing microservice-based solutions and
implementing various types of workflow and orchestration engines. Sourabh believes in
continuous learning and enjoys exploring new web technologies. When not coding, he
likes to play Tabla and read about astrology

Who this book is for
This book is for intermediate-level Python developers in any field who are looking to build
their skills to develop and manage large-scale complex projects. Developers who want to
create reusable modules and Python libraries and cloud developers building applications
for cloud deployment will also find this book useful. Prior experience with Python will
help you get the most out of this book.

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.