Loving Common Lisp, or the Savvy Programmer's Secret Weapon

Cover Material, Copyright, and License

Preface

1. How To Read This Book?
2. Requests from the Author
3. Why Use Common Lisp?
4. Acknowledgments
5. Setting Up Your Common Lisp Development System and Quicklisp

Introduction

1. Why Did I Write this Book?
2. Free Software Tools for Common Lisp Programming
3. Making Book Examples Run Portably on Most Common Lisp Implementations
4. How is Lisp Different from Languages like Java and C++?
5. Advantages of Working in a Lisp Environment

Common Lisp Basics

1. Getting Started with SBCL
2. Making the repl Nicer using rlwrap
3. The Basics of Lisp Programming
4. Symbols
5. Operations on Lists
6. Using Arrays and Vectors
7. Using Strings
8. Using Hash Tables
9. Using Eval to Evaluate Lisp Forms
10. Using a Text Editor to Edit Lisp Source Files
11. Recovering from Errors
12. Garbage Collection
13. Loading your Working Environment Quickly
14. Functional Programming Concepts

Quicklisp

1. Using Quicklisp to Find Packages
2. Using Quicklisp to Configure Emacs and Slime

Defining Lisp Functions

1. Using Lambda Forms
2. Using Recursion
3. Closures
4. Using the Function eval

Defining Common Lisp Macros

1. Example Macro
2. Using the Splicing Operator
3. Using macroexpand-1

Using Common Lisp Loop Macros

1. dolist
2. dotimes
3. do
4. Using the loop Special Form to Iterate Over Vectors or Arrays

Common Lisp Package System

Input and Output

1. The Lisp read and read-line Functions
2. Lisp Printing Functions

Plotting Data

1. Implementing the Library
2. Packaging as a Quicklisp Project

Common Lisp Object System - CLOS

1. Example of Using a CLOS Class
2. Implementation of the HTMLstream Class
3. Using Defstruct or CLOS

Network Programming

1. An introduction to Drakma
2. An introduction to Hunchentoot
3. Complete REST Client Server Example Using JSON for Data Serialization
4. Network Programming Wrap Up

Using the Brave Search APIs

1. Setting an Environment Variable for the Access Key for Brave Search APIs
2. Example Search Script

Accessing Relational Databases

1. Database Wrap Up

Using MongoDB, Solr NoSQL Data Stores

1. MongoDB
2. A Common Lisp Solr Client
3. NoSQL Wrapup

Natural Language Processing

1. Loading and Running the NLP Library
2. Part of Speech Tagging
3. Categorizing Text
4. Detecting People’s Names and Place Names
5. Summarizing Text
6. Text Mining

Information Gathering

1. DBPedia Lookup Service
2. Web Spiders
3. Using Apache Nutch
4. Wrap Up

Using The CL Machine-Learning Library

1. Using the CLML Data Loading and Access APIs
2. K-Means Clustering of Cancer Data Set
3. SVM Classification of Cancer Data Set
4. CLML Wrap Up

Backpropagation Neural Networks

Hopfield Neural Networks

Using Python Deep Learning Models In Common Lisp With a Web Services Interface

1. Setting up the Python Web Services Used in this Chapter
2. Installing the spaCY NLP Services
3. Installing the Coreference NLP Services
4. Common Lisp Client for the spaCy NLP Web Services
5. Common Lisp Client for the Coreference NLP Web Services
6. Trouble Shooting Possible Problems - Skip if this Example Works on Your System
7. Python Interop Wrap-up

Using the PY4CL Library to Embed Python in Common Lisp

1. Project Structure, Building the Python Wrapper, and Running an Example
2. Implementation of spacy-py4cl
3. Trouble Shooting Possible Problems - Skip if this Example Works on Your System
4. Wrap-up for Using Py4CL

Semantic Web and Linked Data

1. Resource Description Framework (RDF) Data Model
2. Extending RDF with RDF Schema
3. The SPARQL Query Language
4. Case Study: Using SPARQL to Find Information about Board of Directors Members of Corporations and Organizations
5. Installing the Apache Jena Fuseki RDF Server
6. Common Lisp Client Examples for the Apache Jena Fuseki RDF Server

Implementing a Simple RDF Datastore and Partial SPARQL Support in Common Lisp

1. 1. RDF Triple Structure
2. 2. RDF Datastore
3. 3. Basic Datastore Operations
4. 4. Query Support
5. 5. SPARQL Query Structure
6. 6. SPARQL Query Parsing
7. 7. Query Execution
8. 8. Result Projection
9. 9. Main Query Execution
10. Conclusion

Automatically Generating Data for Knowledge Graphs

1. Implementation Notes
2. Generating RDF Data
3. Generating Data for the Neo4j Graph Database
4. Implementing the Top Level Application APIs
5. Implementing The Web Interface
6. Creating a Standalone Application Using SBCL
7. Augmenting RDF Triples in a Knowledge Graph Using DBPedia
8. KGCreator Wrap Up

Knowledge Graph Sampler for Creating Small Custom Knowledge Graphs

Knowledge Graph Navigator Common Library Implementation

1. Example Output
2. Project Configuration and Running the Application
3. Review of NLP Utilities Used in Application
4. Developing Low-Level SPARQL Utilities
5. Implementing the Caching Layer
6. Utilities in the Main Library File kgn-common.lisp
7. Wrap-up

Knowledge Graph Navigator Text-Based User Interface

1. Example Output
2. Text User Interface Implementation
3. Wrap-up

Knowledge Graph Navigator User Interface Using LispWorks CAPI

1. Project Configuration and Running the Application
2. Utilities to Colorize SPARQL and Generated Output
3. Main Implementation File kgn-capi-ui.lisp
4. User Interface Utilites File user-interface.lisp
5. User Interface CAPI Options Panes Definition File option-pane.lisp
6. Using LispWorks CAPI UI Toolkit
7. Wrap-up

Using the OpenAI and Mistral APIs

1. History of OpenAI
2. Common Lisp Library for Using OpenAI APIs
3. History of Mistral AI
4. Client Library for Mistral APIs

Using the Perplexity Sonar Web Search and LLM APIs

1. Example Library Use
2. Library Implementation
3. Wrap Up for the Perplexity Sonar API
4. Wrap Up Part 2: Perplexity Offers a Derivative DeepSeek R1 Model on its APIs

Using the Perplexity Sonar Web Search and LLM APIs

1. Example Library Use
2. Library Implementation
3. Wrap Up for the Perplexity Sonar API
4. Wrap Up Part 2: Perplexity Offers a Derivative DeepSeek R1 Model on its APIs

Moonshot’s Kimi K2 Model

1. Simple Text Generation
2. A More Complicated Example With Tool Use
3. Moonshot AI’s Kimi K2 Model Wrap Up

Using the Hugging Face Deep Learning Natural Language Processing APIs

1. History of Hugging Face and How They Differ from OpenAI and Anthropic
2. Common Lisp Library for Hugging Face APIs
3. Hugging Face APIs Wrapup

Using a Local Document Embeddings Vector Database With OpenAI GPT-5 APIs for Semantically Querying Your Own Data

1. Overview of Local Embeddings Vector Database to Enhance the Use of GPT3 APIs With Local Documents
2. Implementing a Local Vector Database for Document Embeddings
3. Using Local Embeddings Vector Database With OpenAI GPT APIs
4. Testing Local Embeddings Vector Database With OpenAI GPT APIs
5. Adding Chat History
6. Wrap Up for Using Local Embeddings Vector Database to Enhance the Use of GPT5 APIs With Local Documents

Prompt Engineering for Large Language Models

1. Two Types of LLMS
2. Prompt Examples
3. Prompt Engineering Wrapup

Client Library for the Google Gemini LLM APIs

1. Example Use
2. Using Google’s “Grounding Search”
3. Using Google’s “Grounding Search” With Citations

Client Library for the Tavily Web Search APIs

1. Example Use

AutoContext: Prepare Effective Prompts with Context for LLM Queries

1. Implementing the BM25 Algorithm
2. Implementing Vectorization of Text and Semantic Similarity
3. Implementation of Main Program
4. Example Generated Prompt with Context
5. Wrap Up For Generating Prompts with Contexts

Agents Orchestrating LLM Tool Use

1. Example Multi Agent Implementation
2. Code Discusion
3. test.lisp
4. Example Output
5. Multi Agent Example Wrap Up

More Agents Using X’s Grok and Perplexity APIs

1. Agent Using X’s Grok API
2. Agent Using X’s Grok API and Perplexity’s Search API

Using Common Lisp with Wolfram/One

Book Wrapup