132 lines
3.3 KiB
Markdown
132 lines
3.3 KiB
Markdown
---
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layout: default
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title: "Visualization"
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parent: "Details"
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nav_order: 3
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---
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# Visualization
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Visualizing the flow and node structure can greatly help understanding. While we do **not** include built-in visualization tools, we provide an example of how to create one using **Mermaid**.
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### Example: Visualization of Node with Mermaid
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{% raw %}
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```python
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# Generate Mermaid diagram code for a Flow or Node structure
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def build_mermaid(start):
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node_ids, visited = {}, set()
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lines = ["graph LR"]
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counter = [1] # Counter for unique node IDs
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def get_id(node):
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if node not in node_ids:
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node_ids[node] = f"N{counter[0]}"
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counter[0] += 1
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return node_ids[node]
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def connect(src, tgt):
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lines.append(f" {src} --> {tgt}")
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def walk(node, parent_id=None):
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if node in visited:
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if parent_id:
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connect(parent_id, get_id(node))
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return
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visited.add(node)
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if isinstance(node, Flow):
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# Handle Flow nodes
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if parent_id and node.start:
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connect(parent_id, get_id(node.start))
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lines.append(f"\n subgraph sub_flow_{get_id(node)}[{type(node).__name__}]")
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if node.start:
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walk(node.start)
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for succ_node in node.successors.values():
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if node.start:
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walk(succ_node, get_id(node.start))
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else:
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if parent_id:
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connect(parent_id, get_id(succ_node))
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walk(succ_node)
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lines.append(" end\n")
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else:
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# Handle simple Nodes
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curr_id = get_id(node)
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if isinstance(node, BatchNode):
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label = f'{curr_id}@{{shape: procs, label: "{type(node).__name__}"}}'
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else:
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label = f'{curr_id}@{{label: "{type(node).__name__}"}}'
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if parent_id:
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lines.append(f" {label}")
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connect(parent_id, curr_id)
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else:
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lines.append(f" {label}")
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for succ_node in node.successors.values():
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walk(succ_node, curr_id)
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walk(start)
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return "\n".join(lines)
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```
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{% endraw %}
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### Usage Example
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Here, we define some example Nodes and Flows to generate a Mermaid diagram:
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```python
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class DataPrepBatchNode(BatchNode):
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pass
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class ValidateDataNode(Node):
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pass
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class FeatureExtractionNode(Node):
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pass
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class TrainModelNode(Node):
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pass
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class EvaluateModelNode(Node):
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pass
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class ModelFlow(Flow):
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pass
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feature_node = FeatureExtractionNode()
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train_node = TrainModelNode()
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evaluate_node = EvaluateModelNode()
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feature_node >> train_node >> evaluate_node
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model_flow = ModelFlow(start=feature_node)
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data_prep_node = DataPrepBatchNode()
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validate_node = ValidateDataNode()
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data_prep_node >> validate_node >> model_flow
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build_mermaid(start=data_prep_node)
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```
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The above code produces a Mermaid diagram (e.g., use the [Mermaid Live Editor](https://mermaid.live/) to render it):
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```mermaid
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graph LR
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N1@{shape: procs, label: "DataPrepBatchNode"}
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N2@{label: "ValidateDataNode"}
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N1 --> N2
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N2 --> N3
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subgraph sub_flow_N4[ModelFlow]
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N3@{label: "FeatureExtractionNode"}
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N5@{label: "TrainModelNode"}
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N3 --> N5
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N6@{label: "EvaluateModelNode"}
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N5 --> N6
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end
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```
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