Treading on Python: Volume 2 Intermediate Python
Treading on Python: Volume 2 Intermediate Python
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Treading on Python: Volume 2 Intermediate Python

Last updated on 2014-08-29

About the Book

Write Python code like the masters

These constructs, while not necessary per se, allow you to be more succinct, re-use code, and think about code in a different way. You will learn:

  • how the constructs work

  • when to use them

  • real like examples from the standard library

Understand other's code

This book covers many of these intermediate constructs that are available in Python. The book covers both Python 2 and 3. Topics include:

  • Functional programming 

  • List comprehensions

  • Generator expressions

  • Set & dict comprehensions 

  • Iteration 

  • Generators 

  • Closures 

  • Decorators

About the Author

Matt Harrison
Matt Harrison

Matt Harrison has been using Python since 2000.

He runs MetaSnake, a Python and Data Science consultancy and corporate training shop.  In the past, he has worked across the domains

of search, build management and testing, business intelligence and

storage.

He has presented and taught tutorials at conferences such as Strata, SciPy, SCALE,

PyCON and OSCON as well as local user conferences. The structure and

content of this book is based off of first hand experience teaching

Python to many individuals.

He blogs at hairysun.com and occasionally tweets useful Python

related information at @__mharrison__.

Table of Contents

  • Introduction
  • Programming Styles
  • Functional Constructs in Python
  • lambda
    • Higher-order functions
  • map
  • reduce
  • filter
  • Recursion
    • Tail call optimization
    • Unrolling recursive functions
    • Recursive tips
  • List Comprehensions
    • Nested list comprehensions
  • Generator Expressions
    • Generator (expressions) exhaust
    • No need for parentheses
    • No variable leaking
    • Generators and generator expressions
  • Dictionary Comprehensions
  • Set Comprehensions
  • The operator Module
  • Iteration in Python
  • The Iterator Protocol
    • Illustrating the iterator protocol
    • Iteration with StringIO
  • Iterator vs Iterable
    • Counting
    • Creating (self) iterator objects
    • Iterator exhaustion
    • Creating an iterable
    • Iterators can be infinite
  • Generators
    • Function generators exhaust
    • Generators return a generator object
    • Generators can be infinite
    • return stops generation
  • Object Generators
    • Object iterator reuse
    • Object method generators
  • Generators in Practice
    • Generators exhaust
    • Chaining generators
    • Debugging generators
    • Generators do not index or slice
    • Generators have no inherent length
    • Generators may be slower
    • Generators may consume less memory
    • Generators are True
    • A non-generator: xrange
    • A generator in collections.py
  • List or Generator?
    • Repeated use of data
    • Data fits into memory
    • Operating on the sequence
    • Conversion between lists and generators
    • Python is becoming more lazy
  • Real World Uses
    • Database chunking
    • Recursive generators
    • Examples from text tweaking
  • Functions
    • First-class functions
    • Function instances
    • Invoking functions
    • Functions have attributes
    • Function scope
    • Functions can be nested
  • Function Parameters
    • Parameters vs arguments
    • Normal and keyword parameters
    • Variable parameters
    • The * operator
    • Variable keyword parameters
    • Flattening dictionaries
    • Arbitrary function parameters
  • Closures
    • Common uses of closures
  • Decorators
    • A simple decorator
    • A decorator template
    • Parameterized decorators
    • Parameterized template
    • Multiple decorators
    • Common uses for decorators
  • Alternate Decorator Implementations
    • Well behaved?
    • Decorating methods
  • About the Author
    • Technical Editors

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