API-first development has evolved from a best practice into the default strategy for many organizations in 2026, with over 80% of organizations adopting some level of API-first approach and the API management market valued in the billions of dollars and growing at double-digit rates. According to Postman’s State of the API Report 2025, 82% of organizations have adopted some level of an API-first approach, with 25% operating as fully API-first—a 12% increase from 2024. MarketsandMarkets’ API management market report projects the global API management market to grow from $7.6 billion in 2024 to $16.9 billion by 2029 at a 17.1% CAGR, driven by digital transformation, cloud and microservices, and demand for API security and governance.
At the same time, REST and OpenAPI have solidified as the dominant model for defining and consuming HTTP APIs. The OpenAPI Specification (OAS) is the industry standard for describing REST APIs in a language-agnostic way, so that both humans and machines can discover and use an API without reading source code. OpenAPI Generator and similar tools generate client libraries in Python, JavaScript, Java, and dozens of other languages from an OpenAPI spec, so that a developer can call an API with a few lines of code. In Python, that often means installing a generated client or using requests or httpx with the base URL and endpoints from the spec; either way, Python is one of the most common languages for scripting API calls, automation, and data pipelines that consume REST APIs.
A typical workflow is to read the API docs or OpenAPI spec, then write a short script that calls the API, parses the response, and uses the data. For example, a developer might use Python’s requests library to send a GET request to a REST endpoint and decode the JSON response—all in a handful of lines that run in a notebook, script, or pipeline.
import requests
r = requests.get("https://api.example.com/v1/users", params={"limit": 10})
r.raise_for_status()
users = r.json()
From there, the same pattern scales to POST requests, authentication, and pagination; the point is that Python and REST form the backbone of much of the API consumption layer in 2026.
What API-First Means in 2026
API-first means designing and building APIs as durable products—with versioning, documentation, SLAs, and roadmaps—rather than as afterthoughts or byproducts of building an application. According to Postman’s State of the API, the shift represents a fundamental change: APIs are now treated as first-class assets that power both human-facing applications and machine consumers (other services, partners, and increasingly AI agents). Organizations that are fully API-first design APIs before or alongside UI and backend logic, so that the same API serves web, mobile, and third-party integrations.
REST (Representational State Transfer) remains the dominant architectural style for HTTP APIs: resources identified by URLs, HTTP methods (GET, POST, PUT, DELETE) for operations, and JSON (or XML) for payloads. OpenAPI (formerly Swagger) provides a machine-readable description of a REST API—paths, parameters, request and response schemas—so that tools can generate clients, documentation, mocks, and tests from a single spec. In 2026, the combination of REST + OpenAPI is the default for public and partner APIs, with GraphQL and gRPC used where they fit specific needs (e.g., flexible querying, high-performance RPC).
Market Size, Speed, and the Developer Experience
The API management market is large and growing. MarketsandMarkets values the market at $7.6 billion in 2024, rising to $16.9 billion by 2029 at a 17.1% CAGR, with growth driven by cloud, microservices, and API security and governance. Postman’s State of the API Report (based on a survey of over 5,700 developers, architects, and executives) notes that 63% of developers can now produce an API within a week, up from 47% the previous year, reflecting better tooling, templates, and API-first practices. At the same time, 44% of developers still rely on chat or email for API collaboration, and 39% cite inconsistent documentation as a major roadblock—so that developer experience (docs, SDKs, sandboxes, and support) remains a differentiator for API providers.
OpenAPI and Code Generation
OpenAPI enables contract-first development: teams define the API spec (or derive it from code), then use code generators to produce clients and servers in many languages. According to the OpenAPI Specification, the spec allows both humans and computers to discover and understand API capabilities without accessing source code. OpenAPI Generator supports dozens of languages and frameworks, including Python (e.g., a python or python-legacy client), so that a team can maintain one spec and ship type-safe, documented clients for Python, JavaScript, Java, and others. In Python, the generated client typically exposes methods that map to API operations, handling serialization, authentication, and errors so that application code stays simple. For one-off scripts or pipelines, many developers still use requests or httpx with the base URL and paths from the spec—Python’s standard way to call a REST API when a generated client is not needed.
Python and the API Consumption Layer
Python is one of the most common languages for consuming REST APIs: automation scripts, data pipelines, notebooks, and backend services routinely call external APIs using requests, httpx, or generated clients. The pattern is simple: construct the URL and headers, send the request, parse the response (usually JSON), and handle errors. For GET requests, a single call is often enough; for POST or PUT, the same library is used with a JSON body. Authentication (API keys, OAuth, or tokens) is typically passed in headers. In 2026, Python’s role in the API layer is reinforced by data science and ML workflows that pull data from APIs, low-code platforms that allow Python code steps to call APIs, and orchestration (e.g., Airflow) where tasks invoke APIs. So Python appears once or twice in almost every API integration story—whether as a generated client or as a few lines of requests or httpx.
The AI-API Gap and Designing for Agents
AI agents and LLM-powered applications are increasingly consumers of APIs, but many APIs were designed for human-driven clients (browsers, mobile apps, server-side code). According to Postman’s State of the API, 89% of developers use AI tools, but only 24% design APIs specifically for AI agents—a gap that organizations are starting to address. AI-native API design may emphasize structured responses, clear schemas, idempotency, and rate limits that suit autonomous agents; API strategy and AI strategy are becoming inseparable. In 2026, the trend is toward APIs that serve both humans and agents, with OpenAPI and documentation as the contract that both sides rely on.
Security, Governance, and Unauthorized Access
APIs have become revenue drivers and integration points, but they also expand the attack surface. According to Postman’s State of the API, 51% of developers cite unauthorized agent access as a top security risk, reflecting concern about tokens, keys, and agents that call APIs with broad permissions. API governance—authentication, authorization, rate limiting, and audit—is a core function of API management platforms and gateways. In 2026, best practice is to treat APIs as products with security built in: least privilege, scoped tokens, and visibility into who and what is calling each endpoint.
Conclusion: APIs as the Glue Layer
In 2026, API-first development is the norm for over 80% of organizations, with 25% fully API-first and the API management market heading toward $17 billion by 2029. REST and OpenAPI define the dominant model for HTTP APIs, and Python is one of the primary languages for consuming those APIs—whether via requests, httpx, or generated clients. A typical integration is a few lines of Python that call an endpoint, parse JSON, and feed data into a pipeline or application; from there, the same pattern scales to authentication, pagination, and error handling.
The rise of AI agents as API consumers is creating an AI-API gap: most developers use AI, but few yet design APIs explicitly for agents. Closing that gap—with structured responses, clear contracts, and governance—will define the next phase of API-first development. For practitioners, Python once or twice in an API integration remains the standard: simple, readable, and aligned with the rest of the data and automation stack.
