Skill Guide

TypeScript and Python SDK authoring with full type safety

The practice of designing and implementing client libraries (SDKs) for TypeScript and Python that enforce complete type safety from API contract to consumer code, eliminating runtime type errors.

This skill dramatically reduces integration bugs and accelerates developer onboarding, directly impacting product reliability and time-to-market. It transforms an SDK from a liability into a force multiplier for the entire developer ecosystem.

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How to Learn TypeScript and Python SDK authoring with full type safety

1. Master TypeScript's advanced types (Generics, Discriminated Unions, Mapped Types) and Python's Type Hints (typing module, Pydantic). 2. Understand API schema definitions (OpenAPI/JSON Schema). 3. Practice writing small, type-safe utility functions and classes in both languages.

1. Move to auto-generating clients from OpenAPI specs using tools like `openapi-typescript` and `openapi-python-client`. 2. Implement runtime validation (e.g., Zod, Pydantic) alongside static types. 3. Avoid common pitfalls like 'any' leakage and incorrect generic constraints. Build a small, internal API client.

1. Architect SDKs with complex, polymorphic response types and nested generics. 2. Implement advanced code generation pipelines and custom transformers. 3. Align SDK design with product strategy, versioning policies, and deprecation workflows. Mentor teams on type system design.

Practice Projects

Beginner

Project

Build a Type-Safe REST Client for a Public API

Scenario

Create a client for a simple public API (e.g., JSONPlaceholder) that provides full autocompletion and compile-time safety for all endpoints and responses.

How to Execute

1. Define the API schema using an OpenAPI spec. 2. Use `openapi-typescript` and `openapi-python-client` to generate base types/interfaces. 3. Build wrapper functions that use these generated types, ensuring all inputs and outputs are typed. 4. Write unit tests that verify type correctness at compile-time and runtime validation.

Intermediate

Project

SDK with Polymorphic Responses and Error Handling

Scenario

Extend your SDK to handle an API that returns different response shapes based on a discriminator field (e.g., `type: 'user' | 'post'`), with custom, typed error classes.

How to Execute

1. Model discriminated unions in TypeScript and equivalent tagged unions in Python (using `typing.Union` and `typing.Literal`). 2. Implement a type-safe error handling system where API errors are parsed into specific exception classes with typed payloads. 3. Create helper functions like `unwrap()` that narrow types for consumers. 4. Test the entire flow, ensuring exhaustive switch statements handle all cases.

Advanced

Project

Design & Publish a Cross-Language SDK with a Custom Code Generation Pipeline

Scenario

You are responsible for the official SDK for a complex B2B SaaS product. The SDK must support advanced features like webhooks, pagination, and batch operations across TypeScript and Python, with perfect consistency.

How to Execute

1. Define the source-of-truth API spec in a format like `smithy` or a detailed OpenAPI 3.1. 2. Build a custom code generation pipeline (using tools like `quicktype`, `openapi-generator`, or a bespoke Jinja2/Mustache script) that produces idiomatic, ergonomic code for both languages. 3. Implement advanced features: type-safe webhook payload parsers, auto-pagination iterators, and batch request builders. 4. Establish a CI/CD pipeline that runs type-checking, linting, and integration tests for both SDKs from the single spec.

Tools & Frameworks

Code Generation & Schema Tools

openapi-typescriptopenapi-python-clientquicktypeopenapi-generatorsmithy

Used to auto-generate base types and client code from an API specification, ensuring a single source of truth. `quicktype` excels at generating from raw JSON samples.

Runtime Validation & Typing Libraries

Zod (TypeScript)Pydantic (Python)io-ts (TypeScript)typing_extensions (Python)

Essential for validating data at runtime (e.g., from network, files) and converting it to a typed object, bridging the gap between dynamic data and static types.

Build, Tooling & Quality

TypeScript Compiler (tsc) --strictmypy / pyrightVitest (TS) / pytest (Python)Changesetstsup / setuptools

Core for enforcing type safety (`strict` mode), static analysis, testing, version management (`changesets`), and building distributable packages.

Interview Questions

Answer Strategy

Demonstrate knowledge of discriminated unions and exhaustive checking. Use a type guard or a result-parsing function. Sample Answer: 'I would define a discriminated union based on a `success` boolean or a `status` field. The core `getUser` function would return this union type. I'd then provide a helper function, `unwrapResult`, that uses a type predicate (`if ('error' in result)`) to narrow the type, allowing consumers to safely access `data` or `error` in a switch statement. TypeScript's control flow analysis then guarantees exhaustive handling.'

Answer Strategy

Tests pragmatic engineering judgment and communication skills. The answer should show awareness of real-world constraints. Sample Answer: 'On a previous SDK, adding a required field to a request type was a breaking change. To maintain backward compatibility, I made the field optional with a runtime validation warning, and introduced a new `StrictRequest` type with it required. I documented the migration path clearly. The decision prioritized not breaking existing users immediately while guiding them toward the new, safer contract over time.'