init python support

demos/python/Person.py

@@ -0,0 +1,7 @@
+class Person:
+    def __init__(self, name, parents=None) -> None:
+        self.name = name
+        self.parents = [] if parents is None else parents
+
+    def addParent(self, parent: "Person"):
+        self.parents.append(parent)

demos/python/debugvisualizer.py

@@ -0,0 +1,44 @@
+from Person import Person
+import json
+from vscodedebugvisualizer import globalVisualizationFactory
+
+
+class PersonVisualizer:
+    def checkType(self, t):
+        return isinstance(t, Person)
+
+    def visualizePerson(self, person: Person, nodes=[], edges=[]):
+        if person.name in [n["id"] for n in nodes]:
+            return nodes, edges
+
+        nodes.append(
+            {
+                "id": person.name,
+                "label": person.name,
+            }
+        )
+
+        for p in person.parents:
+            nodes, edges = self.visualizePerson(p, nodes, edges)
+            edges.append(
+                {
+                    "from": p.name,
+                    "to": person.name,
+                }
+            )
+
+        return nodes, edges
+
+    def visualize(self, person: Person):
+        jsonDict = {
+            "kind": {"graph": True},
+            "nodes": [],
+            "edges": [],
+        }
+
+        self.visualizePerson(person, jsonDict["nodes"], jsonDict["edges"])
+
+        return json.dumps(jsonDict)
+
+
+globalVisualizationFactory.addVisualizer(PersonVisualizer())

demos/python/demo.py

@@ -0,0 +1,123 @@
+import numpy as np
+
+
+# put "x" in the Debug Visualizer and use step by step
+# debugging to see the diffrent types of data visualization
+
+
+x = 5
+x = "asdf"
+x = 5.5
+x = [1, 2, 3, 4, 5, 6, "a", "b"]
+x = ["b", "a", "c", "d", "e"]
+x.sort()
+x = {
+    "asdf1": "dasdf",
+    "asdf2": "dasdf",
+    "asdf3": {"foo": "bar"},
+}
+
+x = [1, 2, 3, 4, 5, 6]
+# histogram
+x = np.concatenate([np.arange(i) for i in range(9)])
+x = x.reshape(2, -1)
+
+
+# one dimension
+x = np.arange(100)
+x = np.linspace(-np.pi, np.pi, 100)
+x = np.sin(x)
+
+# 2 dimension
+x = x.reshape(5, 20)
+# 2 dimension transpose
+x = x.transpose()
+x = x.transpose()
+
+# 3 dimensions
+x = x.reshape(2, 5, 10)
+
+# 4 dimensions
+x = x.reshape(2, 5, 2, 5)
+
+# big number
+x = np.empty(2 ** 24)
+x[0:1000000] = 1
+x[1000000:10000000] = 5
+
+# pyTorch
+try:
+    import torch
+
+    x = np.concatenate([np.arange(i) for i in range(9)])
+    x = x.reshape(2, -1)
+    x = torch.Tensor(x)
+    pass
+
+except ImportError:
+    pass
+
+
+# tensorflow
+
+try:
+    import tensorflow as tf
+
+    x = np.concatenate([np.arange(i) for i in range(9)])
+    x = x.reshape(2, -1)
+    x = tf.convert_to_tensor(x)
+    pass
+except ImportError:
+    pass
+
+
+# pandas
+
+try:
+    import pandas as pd
+    import plotly.express as px
+
+    x = px.data.gapminder().query("year == 2007")
+    pass
+except ImportError:
+    pass
+
+# custom visualizer defined in ./debugvisualizer.py (this file is included automatically)
+
+from Person import Person
+
+x = Person("Aria")
+parent1 = Person("Eduart")
+parent2 = Person("Catelyn")
+x.addParent(parent1)
+x.addParent(parent2)
+parent1.addParent(Person("Benjen"))
+
+# direct debug-visualizer json as dict with property "kind"
+
+x = {
+    "kind": {"dotGraph": True},
+    "text": '\ndigraph G {\n    subgraph cluster_0 {\n      style=filled;\n      color=lightgrey;\n      node [style=filled,color=white];\n      a0 -> a1 -> a2 -> a3;\n      label = "process #1";\n    }\n  \n    subgraph cluster_1 {\n      node [style=filled];\n      b0 -> b1 -> b2 -> b3;\n      label = "process #2";\n      color=blue\n    }\n    start -> a0;\n    start -> b0;\n    a1 -> b3;\n    b2 -> a3;\n    a3 -> a0;\n    a3 -> end;\n    b3 -> end;\n  \n    start [shape=Mdiamond];\n    end [shape=Msquare];\n}\n',
+}
+
+x = {
+    "kind": {"plotly": True},
+    "data": [
+        {
+            "mode": "lines",
+            "type": "scatter",
+            "x": ["A", "B", "C"],
+            "xaxis": "x",
+            "y": [4488916, 3918072, 3892124],
+            "yaxis": "y",
+        },
+        {
+            "cells": {"values": [["A", "B", "C"], [341319, 281489, 294786], [4488916, 3918072, 3892124]]},
+            "domain": {"x": [0.0, 1.0], "y": [0.0, 0.60]},
+            "header": {"align": "left", "font": {"size": 10}, "values": ["Date", "Number", "Output"]},
+            "type": "table",
+        },
+    ],
+    "layout": {"xaxis": {"anchor": "y", "domain": [0.0, 1.0]}, "yaxis": {"anchor": "x", "domain": [0.75, 1.0]}},
+}
+pass

demos/python/graph.py

@@ -23,10 +23,9 @@ for i in range(2,100):
     # connects the node to a random edge
     targetId = str(randint(1, i - 1))
     graph["edges"].append({"from": id, "to": targetId})
-    json_graph = dumps(graph)
     print("i is " + str(i))
     # try setting a breakpoint right above
-    # then put json_graph into the visualization console and press enter
+    # then put graph into the visualization console and press enter
     # when you step through the code each time you hit the breakpoint
     # the graph should automatically refresh!
     

demos/python/insertion_sort.py

@@ -1,5 +1,4 @@
 """Python demo for sorting using VS Code Debug Visualizer."""
-import json
 
 
 def serialize(arr):
@@ -14,7 +13,7 @@ def serialize(arr):
             }
         ],
     }
-    return json.dumps(formatted)
+    return formatted
 
 
 arr = [6, 9, 3, 12, 1, 11, 5, 13, 8, 14, 2, 4, 10, 0, 7]