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‎books/Learning API Styles/summary.en.md‎

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# Book Summary: Learning API Styles
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* **Author**: Lukasz Dynowski and Marcin Dulak
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* **Genre**: Software Engineering
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* **Publication Date**: 2025
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This document summarizes the key lessons and insights extracted from the book.
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I highly recommend reading the original book for the full depth and author's perspective.
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## Before You Get Started
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* I summarize key points from useful books to learn and review quickly.
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* Simply click on `Ask AI` links after each section to dive deeper.
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## Preface
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**Summary**: The preface sets the stage by explaining how APIs are everywhere in modern tech, from smartphones to space missions, and how they've powered giants like Amazon and Google. It defines APIs as interaction points that let software components communicate without exposing underlying complexities. The book focuses on network-based APIs, born from the internet's growth and TCP/IP foundations. The authors wrote it to fill a gap in detailed overviews of various API styles, especially with growing demands from AI and LLMs. It's aimed at developers and architects wanting practical skills in API design, implementation, and trade-offs. The book covers styles like REST, GraphQL, Atom feeds, gRPC, webhooks, WebSocket, and RabbitMQ-based messaging, using a Weather Forecast Service example. It skips non-technical topics like API strategy or monetization. Setup instructions include GitHub Codespaces or local Docker for hands-on exercises.
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**Example**: Think of APIs like a universal translator in a sci-fi movie—different systems "speak" through them seamlessly, hiding all the messy details underneath.
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**Link for More Details**:
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[Ask AI: Preface](https://alisol.ir/?ai=Preface%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## API Concepts
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**Summary**: This chapter dives into what APIs really are, especially network-based ones that let software chat over the internet. An API is an interaction point hiding system complexity, like a black box where you input data and get outputs. It covers communication basics: messages (self-contained data units with payload and metadata), transmission modes (one-way simplex, alternating half-duplex, or simultaneous full-duplex), and sync vs. async styles (where sync blocks waiting for replies, async doesn't). History traces back to 1940s modular libraries, evolving through remote calls in the 70s-80s. APIs create value by treating them as products for monetization or internal efficiency. The lifecycle includes planning (with functional/non-functional requirements), design, implementation, testing (unit to end-to-end), deployment (CI/CD), maintenance (corrective to adaptive), and retirement (with deprecation notices). Governance ensures standards, while platforms manage them. Styles vary by needs—no one-size-fits-all.
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**Example**: Imagine APIs as bridges connecting cities: the style is the toll gate, trucks are requests/responses, and traffic rules are protocols. Sync means waiting for a receipt; async means dropping off and moving on.
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**Link for More Details**:
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[Ask AI: Chapter 1: API Concepts](https://alisol.ir/?ai=Chapter%201%3A%20API%20Concepts%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## API Design Patterns
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**Summary**: Here, the book outlines patterns for solid API design, starting with naming (intent-oriented for clarity, resource-oriented for REST-like endpoints) and language choices. It covers evolving APIs with backward/forward compatibility, avoiding breaking changes. Versioning strategies include path/query/header-based or semantic/calendar/hash approaches. Patterns like filtering, pagination (offset/cursor-based), sorting/counting, deletion (soft/hard), long-running tasks (polling/async), caching, rate limiting, request retries/duplication, and encoding (JSON/Avro/Protobuf) are detailed. Security patterns emphasize encryption/auth/authz, input sanitization/validation, scraping mitigation (via UUIDs/captchas), and OWASP top risks like broken auth or injection. Best practices: optimize performance with compression/binary formats, document well, and follow least surprise.
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**Example**: For pagination, it's like flipping through a phonebook—offset jumps to page 10, but cursor marks your spot with a bookmark for efficiency in large lists.
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**Link for More Details**:
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[Ask AI: Chapter 2: API Design Patterns](https://alisol.ir/?ai=Chapter%202%3A%20API%20Design%20Patterns%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## Network Protocols
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**Summary**: This chapter explains network foundations for APIs, using TCP/IP and OSI models (layers from physical to application). It details socket APIs for connections, with a TCP ECHO service example (server/client implementations via Python, netcat, Scapy, OpenSSL). Messages flow through encapsulation/decapsulation like Matryoshka dolls. Security covers cryptography basics, TLS handshakes for encryption/auth, and risks like MITM attacks—use CA-signed certs over self-signed. Exercises involve Wireshark captures to inspect traffic.
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**Example**: Picture the OSI model as a postal system: application layer writes the letter (message), transport ensures delivery (TCP), network routes it (IP), and physical sends the bits like mail trucks.
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**Link for More Details**:
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[Ask AI: Chapter 3: Network Protocols](https://alisol.ir/?ai=Chapter%203%3A%20Network%20Protocols%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## Web Protocols
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**Summary**: Building on networks, this explores web-specific protocols starting with hypertext and HTTP evolution. HTTP/0.9 was simple text; 1.0 added headers/body; 1.1 brought persistence/pipelining; 2 multiplexed streams/binary; 3 uses QUIC for faster connections/migration. Limitations like TCP HOL blocking and slow starts are addressed. Hypertext enables linked resources. Lab setups use curl/Wireshark to trace browser loads, showing DNS/TCP/HTTP impacts on speed.
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**Example**: HTTP versions are like car models: 0.9 is a basic cart, 1.1 adds cruise control, 2 turbocharges with multiple lanes, and 3 is electric with quick starts and lane-switching.
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**Link for More Details**:
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[Ask AI: Chapter 4: Web Protocols](https://alisol.ir/?ai=Chapter%204%3A%20Web%20Protocols%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## REST API
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**Summary**: REST is introduced as a style with constraints like client-server, statelessness, cacheability, uniform interface, and layered systems. Origins from Roy Fielding's thesis emphasize hypermedia (HATEOAS) for discoverability. Key parts: HTTP methods (CRUD: GET/POST/PUT/DELETE), resources/URIs, representations. Implementation uses Django for Weather Forecast Service endpoints, pagination, rate limiting, caching. Security: JWT for auth, TLS for transit. Documentation via OpenAPI (design/code-first). Trade-offs: simple but can lead to over/under-fetching; RESTful (full constraints) vs. RESTless (pragmatic). Maturity models rate adherence. Use when stateless, cacheable interactions fit.
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**Example**: REST is like a menu at a restaurant—resources are dishes (URIs), orders are methods (GET to browse, POST to add), and the bill is the response, with links to related items.
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**Link for More Details**:
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[Ask AI: Chapter 5: REST API](https://alisol.ir/?ai=Chapter%205%3A%20REST%20API%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## Query API with GraphQL
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**Summary**: GraphQL tackles REST's over/under-fetching by letting clients query exactly needed data via a schema (types, fields, resolvers). Origins at Facebook for mobile efficiency. Constructs: schema, operations (query/mutation/subscription), introspection. Implementation with Strawberry on Django for WFS queries/mutations/auth. GraphiQL for exploration. Security: auth (JWT), attacks like batch/recursive queries mitigated by depth limits/allowlisting. Trade-offs: flexible but complex caching, no native HTTP caching. Versioning via schema evolution. Use for complex, relational data where clients vary.
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**Example**: GraphQL is like a customizable pizza order—you specify toppings (fields) precisely, avoiding the whole menu (over-fetching) or multiple trips (under-fetching).
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**Link for More Details**:
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[Ask AI: Chapter 6: Query API with GraphQL](https://alisol.ir/?ai=Chapter%206%3A%20Query%20API%20with%20GraphQL%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## Web Feeds API with the Atom Protocol
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**Summary**: Web feeds push updates via syndication (RSS/Atom). Evolution from RSS to Atom for better extensibility. Atom format structures entries/categories. Implementation: Django for WFS forecasts as Atom feeds, enriched via gRPC. Reading uses feedparser. Security: basic auth, injection risks. Trade-offs: pull-based, broadcasting efficient but polling-heavy. Use for content syndication like news/weather.
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**Example**: Feeds are like newspaper subscriptions—delivered updates (entries) in a bundle, pulled when you check your mailbox instead of constant pings.
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**Link for More Details**:
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[Ask AI: Chapter 7: Web Feeds API with the Atom Protocol](https://alisol.ir/?ai=Chapter%207%3A%20Web%20Feeds%20API%20with%20the%20Atom%20Protocol%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## RPC API with gRPC
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**Summary**: gRPC is RPC-style using Protobuf for efficient binary serialization, HTTP/2 transport. Origins at Google. Types: unary, server/client/bidirectional streaming. Implementation: Protobuf defs, code gen for WFS enricher. Wire format: length-prefixed messages. Security: TLS/mTLS. Trade-offs: performant for service-to-service, but less discoverable. Versioning via proto evolution. Use for internal, low-latency calls.
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**Example**: gRPC is like a direct phone call—specify the procedure (method), pass args (Protobuf), get results fast, with streaming for ongoing chats.
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**Link for More Details**:
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[Ask AI: Chapter 8: RPC API with gRPC](https://alisol.ir/?ai=Chapter%208%3A%20RPC%20API%20with%20gRPC%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## Callback API with Webhooks
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**Summary**: Webhooks are async callbacks over HTTP for event notifications. Origins in Unix pipes. Incoming/outgoing types. Implementation: Starlette for WFS alerts, with HMAC signatures. Security: signatures, retries, idempotency. Trade-offs: real-time but delivery not guaranteed. Use for event-driven integrations like payments.
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**Example**: Webhooks are like a doorbell—event rings (POST), you respond if home, with a secret knock (HMAC) to verify it's not a prank.
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**Link for More Details**:
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[Ask AI: Chapter 9: Callback API with Webhooks](https://alisol.ir/?ai=Chapter%209%3A%20Callback%20API%20with%20Webhooks%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## Bidirectional API with WebSocket
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**Summary**: WebSocket enables full-duplex, persistent connections over HTTP upgrade. For real-time bidirectional data. Implementation: Starlette/ASGI for WFS alerts/ECHO. Protocol: frames for text/binary/ping. Security: origin validation, JWT, TLS. Trade-offs: stateful, scalable with care. Use for chats/alerts where polling wastes resources.
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**Example**: WebSocket is like a two-way radio—constant open line for instant back-and-forth, upgrading from one-way mail (HTTP).
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**Link for More Details**:
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[Ask AI: Chapter 10: Bidirectional API with WebSocket](https://alisol.ir/?ai=Chapter%2010%3A%20Bidirectional%20API%20with%20WebSocket%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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## Broker-based API with RabbitMQ
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**Summary**: Messaging uses brokers like RabbitMQ (AMQP) for async, decoupled comms. Patterns: work queues (load balance), pub/sub (broadcast), routing/topics (selective), request-response. Implementation: queues/exchanges for tasks. Delivery: at-least/most/once. Security: TLS/SASL/ACLs. Trade-offs: resilient but complex/expensive. Versioning: payload schemas. Use for guaranteed delivery, scalability in workflows.
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**Example**: RabbitMQ is like a post office—senders drop letters (messages) into boxes (queues), routed by labels (keys), with acknowledgments for delivery confirmation.
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**Link for More Details**:
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[Ask AI: Chapter 11: Broker-based API with RabbitMQ](https://alisol.ir/?ai=Chapter%2011%3A%20Broker-based%20API%20with%20RabbitMQ%7CLukasz%20Dynowski%20and%20Marcin%20Dulak%7CLearning%20API%20Styles)
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[Personal note: RabbitMQ is still solid for many uses, but in 2026, I'd consider Kafka or cloud-managed options like AWS SQS for heavier streaming loads to cut ops hassle.]
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---
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**About the summarizer**
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I'm *Ali Sol*, a Backend Developer. Learn more:
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* Website: [alisol.ir](https://alisol.ir)
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* LinkedIn: [linkedin.com/in/alisolphp](https://www.linkedin.com/in/alisolphp)

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