Treading on Python: Volume 2 Intermediate Python
Treading on Python: Volume 2 Intermediate Python
Functional Python, Decorators, Generators, and more
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
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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