Pineapple pipeline engine — Python runtime
Project description
pineapple-pine
Python runtime engine for the Pineapple pipeline framework.
Installation
pip install pineapple-pine
Quick Start
import json
from pine.engine import Engine
config = json.dumps({
"operators": [
{"type_name": "recall_static", "name": "recall", "$metadata": {
"common_input": [], "item_input": [], "common_output": [],
"item_output": ["id", "score"]
}, "items": [{"id": "a", "score": 1.0}]}
],
"pipeline_groups": {"main": ["recall"]}
}).encode()
engine = Engine.create(config)
result = engine.execute(common={}, items=[])
print(result.common, result.items)
Features
- Full DAG scheduling with data-hazard analysis
- ConsumesRowSet / MutatesRowSet / AdditiveWritesRowSet marker interfaces
- Framework-level field accessor (Strict / Default semantics)
- Lua operator support via
lupa - HTTP server with hot-reload
- DAG visualization (DOT / Mermaid)
- Cross-engine parity with pine-go and pine-java
Requirements
- Python >= 3.11
lupa(Lua runtime)redis(optional, for redis_get/redis_set operators)httpx(for remote_pineapple operator)
License
Apache-2.0
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github-hosted -
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