compgraph2txt


Namecompgraph2txt JSON
Version 1.0.0 PyPI version JSON
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SummaryVisualize computational graphs in the terminal.
upload_time2024-08-21 03:11:46
maintainerNone
docs_urlNone
authorNone
requires_python>=3.6
licenseNone
keywords computational graph graph visualization
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            # compgraph2txt 

[![Testing](https://github.com/adamviola/compgraph2txt/actions/workflows/tests.yml/badge.svg)](https://github.com/adamviola/compgraph2txt/actions/workflows/testing.yml)
![Codecov](https://img.shields.io/codecov/c/github/adamviola/compgraph2txt)


A tiny library for visualizing computational graphs in the terminal.

```
│ │ │ ╭─────────╮
│ │ │ │    A    │
│ │ │ ├─────────┤
│ ╰───┼→ a   e ─┼─╮
│   │ │─ b   f ─┼──→
├─────┼→ c   g ─┼───╮
│   │ │─ d   h ─│ │ │
│   │ │      i ─┼────→
│   │ ╰─────────╯ │ │ 
│ ╭───────────────╯ │
│ │ │ ╭─────────────╯
│ │ │ │ ╭─────────╮
│ │ │ │ │    Z    │
│ │ │ │ ├─────────┤
│ ╰─────┼→ t   x ─┼→
│   │ ╰─┼→ u   y ─│
╰───────┼→ v   z ─┼→
    ╰───┼→ w      │
        ╰─────────╯
```

<details>
<summary>Source</summary>

```python
from compgraph2txt import compgraph2txt
from networkx import MultiDiGraph

graph = MultiDiGraph()
graph.add_node(
    "A", inputs=["a", "b", "c", "d"], outputs=["e", "f", "g", "h", "i"]
)
graph.add_node("Z", inputs=["t", "u", "v", "w"], outputs=["x", "y", "z"])

# Add edges from external sources
graph.add_edge("ext1", "A", input="c")
graph.add_edge("ext1", "Z", input="v")
graph.add_edge("ext2", "A", input="a")
graph.add_edge("ext3", "Z", input="w")

# Add edges to external sinks
graph.add_edge("A", "ext", output="f")
graph.add_edge("A", "ext", output="i")
graph.add_edge("Z", "ext", output="x")
graph.add_edge("Z", "ext", output="z")
graph.add_edge("Z", "ext", output="x")
graph.add_edge("Z", "ext", output="z")

# Add edges between nodes
graph.add_edge("A", "Z", output="e", input="t")
graph.add_edge("A", "Z", output="g", input="u")

print(compgraph2txt(graph))
```

</details>

## Example: Image Background Blur Pipeline

### Source
```python
from compgraph2txt import compgraph2txt
from networkx import MultiDiGraph

graph = MultiDiGraph()
graph.add_node("Camera", inputs=[], outputs=["Image"])
graph.add_node("Foreground Detection", inputs=["Image"], outputs=["Foreground", "Background"])
graph.add_node("Blur", inputs=["Image"], outputs=["Blurred Image"])
graph.add_node("Image Overlay", inputs=["Foreground", "Background"], outputs=["Image"])
graph.add_node("Application", inputs=["Image"], outputs=[])

graph.add_edge("Camera", "Foreground Detection", output="Image", input="Image")
graph.add_edge("Foreground Detection", "Blur", output="Background", input="Image")
graph.add_edge("Blur", "Image Overlay", output="Blurred Image", input="Background")
graph.add_edge("Foreground Detection", "Image Overlay", output="Foreground", input="Foreground")
graph.add_edge("Image Overlay", "Application", output="Image", input="Image")

print(compgraph2txt(graph))
```

### Output
```
╭──────────╮
│  Camera  │
├──────────┤
│   Image ─┼─╮
╰──────────╯ │ 
╭────────────╯
│ ╭────────────────────────╮
│ │  Foreground Detection  │
│ ├────────────────────────┤
╰─┼→ Image     Foreground ─┼─╮
  │            Background ─┼───╮
  ╰────────────────────────╯ │ │ 
╭────────────────────────────╯ │
│ ╭────────────────────────────╯
│ │ ╭────────────────────────╮
│ │ │          Blur          │
│ │ ├────────────────────────┤
│ ╰─┼→ Image  Blurred Image ─┼─╮
│   ╰────────────────────────╯ │ 
│ ╭────────────────────────────╯
│ │ ╭─────────────────────╮
│ │ │    Image Overlay    │
│ │ ├─────────────────────┤
╰───┼→ Foreground  Image ─┼─╮
  ╰─┼→ Background         │ │
    ╰─────────────────────╯ │ 
╭───────────────────────────╯
│ ╭───────────────╮
│ │  Application  │
│ ├───────────────┤
╰─┼→ Image        │
  ╰───────────────╯
```

Raw data

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    "description": "# compgraph2txt \n\n[![Testing](https://github.com/adamviola/compgraph2txt/actions/workflows/tests.yml/badge.svg)](https://github.com/adamviola/compgraph2txt/actions/workflows/testing.yml)\n![Codecov](https://img.shields.io/codecov/c/github/adamviola/compgraph2txt)\n\n\nA tiny library for visualizing computational graphs in the terminal.\n\n```\n\u2502 \u2502 \u2502 \u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 \u2502 \u2502 \u2502    A    \u2502\n\u2502 \u2502 \u2502 \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 \u2570\u2500\u2500\u2500\u253c\u2192 a   e \u2500\u253c\u2500\u256e\n\u2502   \u2502 \u2502\u2500 b   f \u2500\u253c\u2500\u2500\u2192\n\u251c\u2500\u2500\u2500\u2500\u2500\u253c\u2192 c   g \u2500\u253c\u2500\u2500\u2500\u256e\n\u2502   \u2502 \u2502\u2500 d   h \u2500\u2502 \u2502 \u2502\n\u2502   \u2502 \u2502      i \u2500\u253c\u2500\u2500\u2500\u2500\u2192\n\u2502   \u2502 \u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f \u2502 \u2502 \n\u2502 \u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f \u2502\n\u2502 \u2502 \u2502 \u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\u2502 \u2502 \u2502 \u2502 \u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 \u2502 \u2502 \u2502 \u2502    Z    \u2502\n\u2502 \u2502 \u2502 \u2502 \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 \u2570\u2500\u2500\u2500\u2500\u2500\u253c\u2192 t   x \u2500\u253c\u2192\n\u2502   \u2502 \u2570\u2500\u253c\u2192 u   y \u2500\u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2192 v   z \u2500\u253c\u2192\n    \u2570\u2500\u2500\u2500\u253c\u2192 w      \u2502\n        \u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n```\n\n<details>\n<summary>Source</summary>\n\n```python\nfrom compgraph2txt import compgraph2txt\nfrom networkx import MultiDiGraph\n\ngraph = MultiDiGraph()\ngraph.add_node(\n    \"A\", inputs=[\"a\", \"b\", \"c\", \"d\"], outputs=[\"e\", \"f\", \"g\", \"h\", \"i\"]\n)\ngraph.add_node(\"Z\", inputs=[\"t\", \"u\", \"v\", \"w\"], outputs=[\"x\", \"y\", \"z\"])\n\n# Add edges from external sources\ngraph.add_edge(\"ext1\", \"A\", input=\"c\")\ngraph.add_edge(\"ext1\", \"Z\", input=\"v\")\ngraph.add_edge(\"ext2\", \"A\", input=\"a\")\ngraph.add_edge(\"ext3\", \"Z\", input=\"w\")\n\n# Add edges to external sinks\ngraph.add_edge(\"A\", \"ext\", output=\"f\")\ngraph.add_edge(\"A\", \"ext\", output=\"i\")\ngraph.add_edge(\"Z\", \"ext\", output=\"x\")\ngraph.add_edge(\"Z\", \"ext\", output=\"z\")\ngraph.add_edge(\"Z\", \"ext\", output=\"x\")\ngraph.add_edge(\"Z\", \"ext\", output=\"z\")\n\n# Add edges between nodes\ngraph.add_edge(\"A\", \"Z\", output=\"e\", input=\"t\")\ngraph.add_edge(\"A\", \"Z\", output=\"g\", input=\"u\")\n\nprint(compgraph2txt(graph))\n```\n\n</details>\n\n## Example: Image Background Blur Pipeline\n\n### Source\n```python\nfrom compgraph2txt import compgraph2txt\nfrom networkx import MultiDiGraph\n\ngraph = MultiDiGraph()\ngraph.add_node(\"Camera\", inputs=[], outputs=[\"Image\"])\ngraph.add_node(\"Foreground Detection\", inputs=[\"Image\"], outputs=[\"Foreground\", \"Background\"])\ngraph.add_node(\"Blur\", inputs=[\"Image\"], outputs=[\"Blurred Image\"])\ngraph.add_node(\"Image Overlay\", inputs=[\"Foreground\", \"Background\"], outputs=[\"Image\"])\ngraph.add_node(\"Application\", inputs=[\"Image\"], outputs=[])\n\ngraph.add_edge(\"Camera\", \"Foreground Detection\", output=\"Image\", input=\"Image\")\ngraph.add_edge(\"Foreground Detection\", \"Blur\", output=\"Background\", input=\"Image\")\ngraph.add_edge(\"Blur\", \"Image Overlay\", output=\"Blurred Image\", input=\"Background\")\ngraph.add_edge(\"Foreground Detection\", \"Image Overlay\", output=\"Foreground\", input=\"Foreground\")\ngraph.add_edge(\"Image Overlay\", \"Application\", output=\"Image\", input=\"Image\")\n\nprint(compgraph2txt(graph))\n```\n\n### Output\n```\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502  Camera  \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502   Image \u2500\u253c\u2500\u256e\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f \u2502 \n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\u2502 \u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 \u2502  Foreground Detection  \u2502\n\u2502 \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2570\u2500\u253c\u2192 Image     Foreground \u2500\u253c\u2500\u256e\n  \u2502            Background \u2500\u253c\u2500\u2500\u2500\u256e\n  \u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f \u2502 \u2502 \n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f \u2502\n\u2502 \u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\u2502 \u2502 \u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 \u2502 \u2502          Blur          \u2502\n\u2502 \u2502 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