Index: Structure and Interpretation of Computer Programs (Python ver.)

SICP taught in Python 3
http://www-inst.eecs.berkeley.edu/~cs61a/sp12/book/index.html

Chapter 1: Building Abstractions with Functions

• • 1.1 Introduction
    • 1.1.1 Programming in Python
    • 1.1.2 Installing Python 3
    • 1.1.3 Interactive Sessions
    • 1.1.4 First Example
    • 1.1.5 Practical Guidance: Errors
  • 1.2 The Elements of Programming
    • 1.2.1 Expressions
    • 1.2.2 Call Expressions
    • 1.2.3 Importing Library Functions
    • 1.2.4 Names and the Environment
    • 1.2.5 Evaluating Nested Expressions
    • 1.2.6 Function Diagrams
  • 1.3 Defining New Functions
    • 1.3.1 Environments
    • 1.3.2 Calling User-Defined Functions
    • 1.3.3 Example: Calling a User-Defined Function
    • 1.3.4 Local Names
    • 1.3.5 Practical Guidance: Choosing Names
    • 1.3.6 Functions as Abstractions
    • 1.3.7 Operators
  • 1.4 Practical Guidance: The Art of the Function
    • 1.4.1 Docstrings
    • 1.4.2 Default Argument Values
  • 1.5 Control
    • 1.5.1 Statements
    • 1.5.2 Compound Statements
    • 1.5.3 Defining Functions II: Local Assignment
    • 1.5.4 Conditional Statements
    • 1.5.5 Iteration
    • 1.5.6 Practical Guidance: Testing
  • 1.6 Higher-Order Functions
    • 1.6.1 Functions as Arguments
    • 1.6.2 Functions as General Methods
    • 1.6.3 Defining Functions III: Nested Definitions
    • 1.6.4 Functions as Returned Values
    • 1.6.5 Lambda Expressions
    • 1.6.6 Example: Newton's Method
    • 1.6.7 Abstractions and First-Class Functions
    • 1.6.8 Function Decorators

Chapter 2: Building Abstractions with Objects

• • 2.1 Introduction
    • 2.1.1 The Object Metaphor
    • 2.1.2 Native Data Types
  • 2.2 Data Abstraction
    • 2.2.1 Example: Arithmetic on Rational Numbers
    • 2.2.2 Tuples
    • 2.2.3 Abstraction Barriers
    • 2.2.4 The Properties of Data
  • 2.3 Sequences
    • 2.3.1 Nested Pairs
    • 2.3.2 Recursive Lists
    • 2.3.3 Tuples II
    • 2.3.4 Sequence Iteration
    • 2.3.5 Sequence Abstraction
    • 2.3.6 Strings
    • 2.3.7 Conventional Interfaces
  • 2.4 Mutable Data
    • 2.4.1 Local State
    • 2.4.2 The Benefits of Non-Local Assignment
    • 2.4.3 The Cost of Non-Local Assignment
    • 2.4.4 Lists
    • 2.4.5 Dictionaries
    • 2.4.6 Example: Propagating Constraints
  • 2.5 Object-Oriented Programming
    • 2.5.1 Objects and Classes
    • 2.5.2 Defining Classes
    • 2.5.3 Message Passing and Dot Expressions
    • 2.5.4 Class Attributes
    • 2.5.5 Inheritance
    • 2.5.6 Using Inheritance
    • 2.5.7 Multiple Inheritance
    • 2.5.8 The Role of Objects
  • 2.6 Implementing Classes and Objects
    • 2.6.1 Instances
    • 2.6.2 Classes
    • 2.6.3 Using Implemented Objects
  • 2.7 Generic Operations
    • 2.7.1 String Conversion
    • 2.7.2 Multiple Representations
    • 2.7.3 Generic Functions

Chapter 3: The Structure and Interpretation of Computer Programs

• • 3.1 Introduction
    • 3.1.1 Programming Languages
  • 3.2 Functions and the Processes They Generate
    • 3.2.1 Recursive Functions
    • 3.2.2 The Anatomy of Recursive Functions
    • 3.2.3 Tree Recursion
    • 3.2.4 Example: Counting Change
    • 3.2.5 Orders of Growth
    • 3.2.6 Example: Exponentiation
  • 3.3 Recursive Data Structures
    • 3.3.1 Processing Recursive Lists
    • 3.3.2 Hierarchical Structures
    • 3.3.3 Sets
  • 3.4 Exceptions
    • 3.4.1 Exception Objects
  • 3.5 Interpreters for Languages with Combination
    • 3.5.1 Calculator
    • 3.5.2 Parsing
  • 3.6 Interpreters for Languages with Abstraction
    • 3.6.1 The Logo Language
    • 3.6.2 Structure
    • 3.6.3 Environments
    • 3.6.4 Data as Programs

Chapter 4: Distributed and Parallel Computing

• • 4.1 Introduction
  • 4.2 Distributed Computing
    • 4.2.1 Client/Server Systems
    • 4.2.2 Peer-to-peer Systems
    • 4.2.3 Modularity
    • 4.2.4 Message Passing
    • 4.2.5 Messages on the World Wide Web
  • 4.3 Parallel Computing
    • 4.3.1 The Problem with Shared State
    • 4.3.2 Correctness in Parallel Computation
    • 4.3.3 Protecting Shared State: Locks and Semaphores
    • 4.3.4 Staying Synchronized: Condition variables
    • 4.3.5 Deadlock

Chapter 5: Sequences and Coroutines

• • 5.1 Introduction
  • 5.2 Implicit Sequences
    • 5.2.1 Python Iterators
    • 5.2.2 For Statements
    • 5.2.3 Generators and Yield Statements
    • 5.2.4 Iterables
    • 5.2.5 Streams
  • 5.3 Coroutines
    • 5.3.1 Python Coroutines
    • 5.3.2 Produce, Filter, and Consume
    • 5.3.3 Multitasking