[1/2] sdks/python: sink data with tecton feature store

[mohamedawnallah]

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Summary of Changes

Hello @mohamedawnallah, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request adds a new I/O connector to the Apache Beam Python SDK, enabling seamless integration with Tecton's feature store. The new functionality allows Beam pipelines to efficiently sink data into Tecton using its Stream Ingest API, supporting robust, configurable, and observable data transfer for feature engineering workflows.

Highlights

• Tecton Stream Ingest Sink: Introduces a new I/O connector for the Apache Beam Python SDK, allowing users to write data directly to Tecton's feature store via its Stream Ingest API.
• Configurable Write Operations: Provides TectonStreamWriteConfig for easy configuration of Tecton instance details, API keys, workspace, stream source, batch size, retries, timeout, and dry-run mode.
• Robust Data Handling: Implements batching of records, automatic retries for transient HTTP errors (e.g., 429, 5xx), and comprehensive error logging for failed write operations.
• Beam Integration: Leverages Beam's PTransform and DoFn patterns, including Reshuffle for efficient data distribution and Metrics for tracking write requests, errors, and records processed.

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[mohamedawnallah]

waiting on the author