227 lines
7.5 KiB
Python
227 lines
7.5 KiB
Python
import asyncio
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class BaseNode:
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"""
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A base node that provides:
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- preprocess()
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- process()
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- postprocess()
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- run() -- just runs itself (no chaining)
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"""
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def __init__(self):
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self.parameters = {}
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self.successors = {}
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def set_parameters(self, params):
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self.parameters.update(params)
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def add_successor(self, node, condition="default"):
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if condition in self.successors:
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print(f"Warning: overwriting existing successor for condition '{condition}'")
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self.successors[condition] = node
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return node
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def preprocess(self, shared_storage):
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return None
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def process(self, shared_storage, prep_result):
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return None
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def _process(self, shared_storage, prep_result):
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# Could have retry logic or other wrap logic
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return self.process(shared_storage, prep_result)
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def postprocess(self, shared_storage, prep_result, proc_result):
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return "default"
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def run(self, shared_storage=None):
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prep = self.preprocess(shared_storage)
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proc = self._process(shared_storage, prep)
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return self.postprocess(shared_storage, prep, proc)
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def __rshift__(self, other):
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"""
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For chaining with >> operator, e.g. node1 >> node2
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"""
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return self.add_successor(other)
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def __gt__(self, other):
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"""
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For chaining with > operator, e.g. node1 > "some_condition"
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then >> node2
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"""
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if isinstance(other, str):
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return _ConditionalTransition(self, other)
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elif isinstance(other, BaseNode):
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return self.add_successor(other)
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raise TypeError("Unsupported operand type")
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def __call__(self, condition):
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"""
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For node("condition") >> next_node syntax
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"""
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return _ConditionalTransition(self, condition)
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class _ConditionalTransition:
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"""
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Helper for Node > 'condition' >> AnotherNode style
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"""
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def __init__(self, source_node, condition):
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self.source_node = source_node
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self.condition = condition
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def __rshift__(self, target_node):
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return self.source_node.add_successor(target_node, self.condition)
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# robust running process
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class Node(BaseNode):
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def __init__(self, max_retries=1):
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super().__init__()
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self.max_retries = max_retries
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def process_after_fail(self, shared_storage, data, exc):
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raise exc
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# return "fail"
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def _process(self, shared_storage, data):
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for attempt in range(self.max_retries):
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try:
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return super()._process(shared_storage, data)
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except Exception as e:
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if attempt == self.max_retries - 1:
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return self.process_after_fail(shared_storage, data, e)
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class Flow(BaseNode):
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def __init__(self, start_node=None):
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self.start_node = start_node
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def _process(self, shared_storage, _):
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current_node = self.start_node
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while current_node:
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condition = current_node.run(shared_storage)
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current_node = current_node.successors.get(condition, None)
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def postprocess(self, shared_storage, prep_result, proc_result):
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return None
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class AsyncNode(Node):
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"""
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A Node whose postprocess step is async.
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You can also override process() to be async if needed.
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"""
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async def postprocess_async(self, shared_storage, prep_result, proc_result):
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"""
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Async version of postprocess. By default, returns "default".
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Override as needed.
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"""
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await asyncio.sleep(0) # trivial async pause (no-op)
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return "default"
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async def run_async(self, shared_storage=None):
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"""
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Async version of run.
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If your process method is also async, you'll need to adapt accordingly.
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"""
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# We can keep preprocess synchronous or make it async as well,
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# depending on your usage. Here it's left as sync for simplicity.
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prep = self.preprocess(shared_storage)
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# process can remain sync if you prefer, or you can define an async process.
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proc = self._process(shared_storage, prep)
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# postprocess is async
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return await self.postprocess_async(shared_storage, prep, proc)
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class AsyncFlow(Flow):
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"""
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A Flow that can handle a mixture of sync and async nodes.
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If the node is an AsyncNode, calls `run_async`.
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Otherwise, calls `run`.
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"""
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async def _process(self, shared_storage, _):
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current_node = self.start_node
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while current_node:
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if hasattr(current_node, "run_async") and callable(current_node.run_async):
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# If it's an async node, await its run_async
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condition = await current_node.run_async(shared_storage)
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else:
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# Otherwise, assume it's a sync node
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condition = current_node.run(shared_storage)
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current_node = current_node.successors.get(condition, None)
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async def run_async(self, shared_storage=None):
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"""
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Kicks off the async flow. Similar to Flow.run,
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but uses our async _process method.
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"""
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prep = self.preprocess(shared_storage)
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# Note: flows typically don't need a meaningful process step
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# because the "process" is the iteration through the nodes.
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await self._process(shared_storage, prep)
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return self.postprocess(shared_storage, prep, None)
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class BatchNode(BaseNode):
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def __init__(self, max_retries=5, delay_s=0.1):
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super().__init__()
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self.max_retries = max_retries
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self.delay_s = delay_s
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def preprocess(self, shared_storage):
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return []
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def process_one(self, shared_storage, item):
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return None
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def process_one_after_fail(self, shared_storage, item, exc):
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print(f"[FAIL_ITEM] item={item}, error={exc}")
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# By default, just return a "fail" marker. Could be anything you want.
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return "fail"
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async def _process_one(self, shared_storage, item):
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for attempt in range(self.max_retries):
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try:
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return await self.process_one(shared_storage, item)
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except Exception as e:
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if attempt == self.max_retries - 1:
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# If out of retries, let a subclass handle what to do next
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return await self.process_one_after_fail(shared_storage, item, e)
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await asyncio.sleep(self.delay_s)
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async def _process(self, shared_storage, items):
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results = []
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for item in items:
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r = await self._process_one(shared_storage, item)
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results.append(r)
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return results
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class BatchFlow(BaseNode):
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def __init__(self, start_node=None):
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super().__init__()
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self.start_node = start_node
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def preprocess(self, shared_storage):
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return []
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async def _process_one(self, shared_storage, param_dict):
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node_parameters = self.parameters.copy()
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node_parameters.update(param_dict)
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if self.start_node:
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current_node = self.start_node
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while current_node:
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# set the combined parameters
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current_node.set_parameters(node_parameters)
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current_node = await current_node._run_one(shared_storage or {})
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async def _process(self, shared_storage, items):
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results = []
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for param_dict in items:
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await self._process_one(shared_storage, param_dict)
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results.append(f"Ran sub-flow for param_dict={param_dict}")
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return results |