Programming languages can be distinguished by several characteristics, but one of the most important is the nature of their type systems. Python can be characterized as having a dynamic and strong type system. Let's investigate what that means.
- Preface
- Getting started
- Obtaining and installing Python 3
- Starting Python command line REPL
- Leaving the REPL
- Code structure and significant indentation
- Python culture
- Importing standard library modules
- Getting help()
- Scalar data types: integers, floats, None and bool
- Relational operators
- Control flow: if-statements and while-loops
- Summary
- Strings and Collections
- Modularity
- Built-in types and the object model
- Exploring Built-in Collection types
- tuple – an immutable sequence of objects
- The tuple constructor
- Strings in action
- Moment of zen
- range – a collection of evenly spaced integers
- list in action
- Negative indexing for lists (and other sequences)
- Slicing lists
- Copying lists
- Shallow copies
- Repeating lists
- Finding list elements with index()
- Membership testing with count() and in
- Removing list elements by index with del
- Removing list elements by value with remove()
- Inserting into a list
- Concatenating lists
- Rearranging list elements
- Out-of-place rearrangement
- Dictionaries
- set – an unordered collection of unique elements
- Collection protocols
- Summary
- Exceptions
- Exceptions and control flow
- Handling multiple exceptions
- Programmer errors
- Empty blocks – the pass statement
- Exception objects
- Imprudent return codes
- Re-raising exceptions
- Exceptions are part of your function's API
- Guard clauses
- Exceptions, APIs, and protocols
- Choosing not to guard against TypeError
- Pythonic style – EAFP versus LBYL
- Clean-up actions
- Moment of zen
- Platform-specific code
- Summary
- Comprehensions, iterables, and generators
- Comprehensions
- Moment of zen
- Iteration protocols
- Generator functions
- Generator expressions
- Batteries included iteration tools
- Pulling it all together
- Summary
- Defining new types with classes
- Defining classes
- Instance methods
- Instance initializers
- Validation and invariants
- Adding a second class
- Collaborating classes
- Moment of zen
- Booking seats
- Naming methods for implementation details
- Sometimes the only object you need is a function
- Polymorphism and duck-typing
- Inheritance and implementation sharing
- Summary
- Files and Resource Management
- Unit testing with the Python standard library
- Debugging with PDB
- Afterword – Just the Beginning
- Virtual Environments
- Packaging and Distribution
- Installing Third-Party Packages
The Python type system
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