Vicente Garcia@vgarciez

DataSentinel: Automated GraphQL Data Pipeline & Model Generator DataSentinel is an advanced, production-ready data engineering framework designed to automate the integration, parsing, and type-safe modeling of complex GraphQL APIs (such as Bitquery). Built with scalability and developer velocity in mind, the platform dynamically introspects remote GraphQL schemas, handles network resilience through exponential backoff retry mechanisms, and automatically generates robust Python data models (Pydantic/Dataclasses). By bridging the gap between raw web-3/crypto stream APIs and strongly typed backend systems, DataSentinel eliminates manual API mapping, ensures strict data validation, and accelerates down-stream data analysis and machine learning workflows. Key Features Automated Introspection & Parsing: Dynamically queries remote endpoints to map full schema topologies out of the box. Resilient Network Layer: Built-in HTTP 401/403 credential injection and exponential backoff retry handlers to guarantee pipeline uptime. Smart Code Generation: Converts complex, nested GraphQL definitions into clean, PEP-compliant Python type hints and dictionaries. Containerized & Agnostic: Fully dockerized ecosystem structured for rapid deployment across multi-chain data infrastructures.

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