The Things of Life: Materiality in Late Soviet Russia, Alexey Golubev

Stanislav Shekshnia, Alexey Ulanovsky and Veronika Zagieva have studied the work of these leaders for a decade and developed a model of leadership that delivers superior results in a specific context, that is, one of fast obsolescence, high turbulence, intense government interference, mediocre levels of human capital development and traditionally high levels of managerial control. The model is called Athletic Leadership because of the strong parallels between the protagonists' attitudes and behaviors and those of top sportspeople. Athletic Leaders share a formative experience of practising competitive sports in their youth, facing early adversity as leaders of important projects, and changing companies and industries along the way. They possess two traits that define their leadership personality: mental toughness and adaptability. Athletic CEOs also use specific iterative behavioral and mental strategies at work - 'meta-practices' of Athletic Leadership. They deliver superior operational and financial results (leadership outputs) and transform their followers, companies, industries and communities (leadership outcomes).

Written for people who are interested in the subject of leadership in business, 'Athletic CEOs: Leadership in Turbulent Times' offers interesting ideas and practical insights for people from other walks of life such as politics, government and education.

Key Features

• Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance
• Get familiar with complex concepts such as monads, concurrency, and immutability
• Apply functional Python to common Exploratory Data Analysis (EDA) programming problems

Book Description

If you're a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm.

Starting with a general overview of functional concepts, you'll explore common functional features such as first-class and higher-order functions, pure functions, and more. You'll see how these are accomplished in Python 3.6 to give you the core foundations you'll build upon. After that, you'll discover common functional optimizations for Python to help your apps reach even higher speeds.

You'll learn FP concepts such as lazy evaluation using Python's generator functions and expressions. Moving forward, you'll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you'll at look at the PyMonad project and some larger examples to put everything into perspective.

What you will learn

• Use Python's generator functions and generator expressions to work with collections in a non-strict (or lazy) manner
• Utilize Python library modules including itertools, functools, multiprocessing, and concurrent features to ensure efficient functional programs
• Use Python strings with object-oriented suffix notation and prefix notation
• Avoid stateful classes with families of tuples
• Design and implement decorators to create composite functions
• Use functions such as max(), min(), map(), filter(), and sorted()
• Write higher-order functions

Who this book is for

This book is for Python developers who would like to perform Functional programming with Python. Python Programming knowledge is assumed.