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Further Reading: Working with Data: CSV, JSON, and APIs

CSV and Data Processing

  • Python csv Module Documentation. (Tier 1) The official docs cover every parameter of reader, writer, DictReader, DictWriter, and the various quoting modes. The "Dialects and Formatting Parameters" section is particularly useful when dealing with non-standard CSV files. https://docs.python.org/3/library/csv.html

  • RFC 4180: Common Format and MIME Type for Comma-Separated Values (CSV) Files. (Tier 1) The actual specification that defines the CSV format. Short, readable, and surprisingly helpful for understanding why the csv module works the way it does — especially the quoting and escaping rules. https://www.rfc-editor.org/rfc/rfc4180

JSON

  • Python json Module Documentation. (Tier 1) Covers all four core functions plus advanced topics like custom serializers (default parameter), decoders, and the JSONEncoder class for serializing non-standard types. https://docs.python.org/3/library/json.html

  • Ecma International. The JSON Data Interchange Syntax (ECMA-404), 2nd Edition. (Tier 1) The formal JSON specification. At only 14 pages, it's one of the most concise specs in computing. Reading it will solidify your understanding of what JSON can and cannot represent. https://ecma-international.org/publications-and-standards/standards/ecma-404/

  • Crockford, D. (2006). "Introducing JSON." (Tier 1) A one-page website by JSON's creator that explains the format with railroad diagrams. Clear, elegant, and foundational. https://www.json.org/

HTTP and APIs

  • Fielding, R. T. (2000). Architectural Styles and the Design of Network-Based Software Architectures. Doctoral dissertation, University of California, Irvine. (Tier 1) The dissertation that defined REST. Chapter 5 introduces the REST architectural style. Academic but readable, and understanding the original source helps you distinguish real REST from "we just have HTTP endpoints and call it REST."

  • Mozilla Developer Network. HTTP Overview. (Tier 1) An excellent, free reference for HTTP methods, status codes, headers, and the request-response cycle. More approachable than the RFCs and constantly updated. https://developer.mozilla.org/en-US/docs/Web/HTTP/Overview

  • requests Library Documentation. (Tier 1) Kenneth Reitz's requests library is one of the most well-documented Python packages. The quickstart guide covers 90% of what you'll need. The advanced section covers sessions, SSL, streaming, and more. https://docs.python-requests.org/

Free Public APIs for Practice

  • JSONPlaceholder. (Tier 1) The fake REST API used in this chapter's examples. No authentication required. Perfect for learning HTTP requests, response handling, and data processing without worrying about API keys. https://jsonplaceholder.typicode.com/

  • DummyJSON. (Tier 1) A richer fake API with users, products, quotes, recipes, and more. Free, no auth required for basic endpoints. Used for the TaskFlow quote feature. https://dummyjson.com/

  • Public APIs List (GitHub). (Tier 2) A curated list of hundreds of free public APIs organized by category (weather, finance, games, science, etc.). Useful for finding APIs for personal projects. https://github.com/public-apis/public-apis

Data Engineering Concepts

  • Sweigart, A. Automate the Boring Stuff with Python, Chapter 16: "Working with CSV Files and JSON Data." (Tier 1) A practical, project-oriented treatment of CSV and JSON processing. Great complement to this chapter's more API-focused approach.

  • McKinney, W. Python for Data Analysis, 3rd Edition. O'Reilly, 2022. (Tier 2) Once you're comfortable with the csv and json modules, pandas (covered in this book) offers dramatically more powerful tools for data manipulation. Chapter 6 covers reading CSV/JSON, and the rest of the book shows what's possible at scale.

For the Curious

  • Kleppmann, M. (2017). Designing Data-Intensive Applications. O'Reilly. (Tier 2) A graduate-level book on data systems, but the early chapters on data models and serialization formats are accessible and will change how you think about data interchange. Covers JSON, CSV, Protocol Buffers, Avro, and when to use each.

  • Postman Learning Center. (Tier 2) Postman is a popular tool for testing APIs interactively (without writing code). Useful for exploring an API's behavior before writing Python code to call it. The learning center has free courses on API fundamentals. https://learning.postman.com/