unistream 0.1.2

Features

1. Efficient Record Buffering: Groups records into micro-batches with a Write-Ahead Log (WAL) for crash recovery, optimizing network bandwidth without risking data loss.

2. Non-blocking Exponential Backoff: Automatic retry with configurable backoff schedules. The retry check is time-based (no sleep), so your application thread is never blocked.

3. Checkpoint & Exactly-Once Consumption: Per-record status tracking (pending → in_progress → succeeded / failed / exhausted), UUID-based concurrency locking with auto-expiry, and stream pointer persistence for fault-tolerant consumption.

4. Pluggable Architecture: Five core abstractions (Record, Buffer, Producer, CheckPoint, Consumer) with clean ABC → Base → Concrete layering. Implement send() for a new producer or get_records() for a new consumer — the framework handles everything else.

Core Abstractions

• AbcRecord / DataClassRecord — the atomic data unit (id + create_at + serialize/deserialize).

• AbcBuffer / FileBuffer — WAL-backed batch buffer (put → should_i_emit → emit → commit).

• AbcProducer / BaseProducer / SimpleProducer — non-blocking put() event loop with retry.

• AbcCheckPoint / BaseCheckPoint / SimpleCheckpoint — per-record state machine + persistence.

• AbcConsumer / BaseConsumer / SimpleConsumer — consumption loop with tenacity retry + DLQ hook.

AI Agent Skill

A self-contained Claude Code skill is included at .claude/skills/unistream/SKILL.md. It contains the complete API reference, protocols, and usage examples — any AI coding agent with this skill loaded can build custom producers, consumers, buffers, checkpoints, and records without reading the source code.

$ pip install unistream

$ pip install --upgrade unistream