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Developer shares 30 API examples, revealing practical limitations

By PulseAugur Editorial · [1 sources] ·

Jeffrey Turov, an independent developer, has published 30 runnable API examples demonstrating the practical outputs and limitations of various data-fetching tools. These examples, available through Apify Actors, cover diverse data types including local business information, reviews, and OpenAPI specifications. Turov emphasizes the importance of inspecting dataset details, understanding billing, and noting source anomalies rather than relying solely on successful run statuses. Key lessons highlight the need for provenance in AI answers, preserving source irregularities, validating business data before using reviews, and using small outputs to test API contracts. AI

IMPACT Provides practical insights for developers on evaluating and using AI-powered APIs, emphasizing data quality and provenance.

RANK_REASON The item describes a collection of runnable API examples and lessons learned from their outputs, which falls under tooling and practical application rather than a novel release or significant industry event.

Read on dev.to — MCP tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Developer shares 30 API examples, revealing practical limitations

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19 / 100
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The item describes a collection of runnable API examples and lessons learned from their outputs, which falls under tooling and practical application rather than a novel release or significant indus…
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product, other
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — MCP tag TIER_1 English(EN) · Jeffrey Turov ·

    I published 30 runnable API examples — here is what the real outputs taught me

    <p>A green run status is not enough to trust an API. I want to inspect the dataset, understand the billing mode and see what happened when a provider or a source misbehaved.</p> <p>I maintain 15 public Apify Actors at Adaga solutions. The toolbox now links 30 prefilled public tas…

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