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April 20, 2026, 2:18 p.m.
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(Last updated: April 20, 2026, 2:18 p.m.)
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SOURCE: DeNero J. Composing Programs 2025
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Textbook in PDF format Welcome to Composing Programs, a free online introduction to programming and computer science. In the tradition of SICP, this text focuses on methods for abstraction, programming paradigms, and techniques for managing the complexity of large programs. These concepts are illustrated primarily using the Python 3 programming language. Building Abstractions with Functions Getting Started Programming in Python Installing Python Interactive Sessions First Example Errors Elements of Programming Expressions Call Expressions Importing Library Functions Names and the Environment Evaluating Nested Expressions The Non-Pure Print Function Defining New Functions Environments Calling User-Defined Functions Example: Calling a User-Defined Function Local Names Choosing Names Functions as Abstractions Operators Designing Functions Documentation Default Argument Values Control Statements Compound Statements Defining Functions II: Local Assignment Conditional Statements Iteration Testing Higher-Order Functions Functions as Arguments Functions as General Methods Defining Functions III: Nested Definitions Functions as Returned Values Example: Newton's Method Currying Lambda Expressions Abstractions and First-Class Functions Function Decorators Recursive Functions The Anatomy of Recursive Functions Mutual Recursion Printing in Recursive Functions Tree Recursion Example: Partitions Building Abstractions with Data Introduction Native Data Types Data Abstraction Example: Rational Numbers Pairs Abstraction Barriers The Properties of Data Sequences Lists Sequence Iteration Sequence Processing Sequence Abstraction Strings Trees Linked Lists Mutable Data The Object Metaphor Sequence Objects Dictionaries Local State The Benefits of Non-Local Assignment The Cost of Non-Local Assignment Implementing Lists and Dictionaries Dispatch Dictionaries Propagating Constraints Object-Oriented Programming Objects and Classes Defining Classes Message Passing and Dot Expressions Class Attributes Inheritance Using Inheritance Multiple Inheritance The Role of Objects Implementing Classes and Objects Instances Classes Using Implemented Objects Object Abstraction String Conversion Special Methods Multiple Representations Generic Functions Efficiency Measuring Efficiency Memoization Orders of Growth Example: Exponentiation Growth Categories Recursive Objects Linked List Class Tree Class Sets Interpreting Computer Programs Introduction Programming Languages Functional Programming Expressions Definitions Compound values Symbolic Data Turtle graphics Exceptions Exception Objects Interpreters for Languages with Combination A Scheme-Syntax Calculator Expression Trees Parsing Expressions Calculator Evaluation Interpreters for Languages with Abstraction Structure Environments Data as Programs Data Processing Introduction Implicit Sequences Iterators Iterables Built-in Iterators For Statements Generators and Yield Statements Iterable Interface Creating Iterables with Yield Iterator Interface Streams Python Streams Declarative Programming Tables Select Statements Joins Interpreting SQL Recursive Select Statements Aggregation and Grouping Logic Programming Facts and Queries Recursive Facts Unification Pattern Matching Representing Facts and Queries The Unification Algorithm Proofs Search Distributed Computing Messages Client/Server Architecture Peer-to-Peer Systems Distributed Data Processing MapReduce Local Implementation Distributed Implementation Parallel Computing Parallelism in Python The Problem with Shared State When No Synchronization is Necessary Synchronized Data Structures Locks Barriers Message Passing Synchronization Pitfalls Conclusion Main Related Sites About Composing Programs
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