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An opinionated and statically-typed TypeScript SDK generator

Hacker News

An opinionated and statically-typed TypeScript SDK generator

Hi Hacker News! My name is Sagar, I’m working on a startup called Speakeasy - we’re making all APIs self-service. The platform is currently in beta, but we’re independently launching this tool which you can use to generate language-idiomatic, statically-typed TS SDKs from any public OpenAPI schemas. We hope to continue iterating on this to give devs a way to easily generate high fidelity client SDKs for all the major languages. Inspiration for this product is from past experiences struggling with OpenAPI. I was originally optimistic about using the OpenAPI tools to build out our offering, but quickly realized that the tools left a lot to be desired, and would not have provided our end users with the developer experience we wanted. While it’s not exhaustive, we’ve tried to address some of the biggest gaps in this tool: * Low-dependency - To try and keep the SDK isomorphic (i.e. available both for Browsers and Node.JS servers), we wrap axios, but that’s it.This is intended to be idiomatic typescript; very similar to code a human would write; with the caveat that the typing is only as strict as the OpenAPI specification. * Code just like a human would write - At this point static typing is everywhere. So wherever possible, we generate typed structures, construct path variables automatically, pass through query parameters, and expose strictly typed input / output body types. * Future direction - There’s value in being neutral, but we felt like there is more value in being opinionated. In the future we’ll add features like built-in Pagination, Retries (Backoff/Jitter etc), Auth integrations, which should be handled in the SDK. We’re planning to continue improving this service, so would love to hear what you think of the choices we’ve made, the issues we should address next, and what languages we should work on supporting.

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, using · Missing: mac, agents, macos
89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para, ios · Missing: supports, reddit linkedin, podcasting
85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, users, way · Missing: mobile apps, personal, entrepreneurs
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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