{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"toc": "true"
},
"source": [
"# Table of Contents\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Testing [lolviz](https://github.com/parrt/lolviz)\n",
"\n",
"I liked how the [lolviz](https://github.com/parrt/lolviz) module looked like. Let's try it!"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPython 3.6.5\n",
"IPython 6.4.0\n",
"\n",
"lolviz n\u0007\n",
"\n",
"compiler : GCC 7.3.0\n",
"system : Linux\n",
"release : 4.15.0-23-generic\n",
"machine : x86_64\n",
"processor : x86_64\n",
"CPU cores : 4\n",
"interpreter: 64bit\n"
]
}
],
"source": [
"%load_ext watermark\n",
"%watermark -v -m -p lolviz"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from lolviz import *"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Testing naively"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" digraph G {\n",
" nodesep=.05;\n",
" node [penwidth=\"0.5\", width=.1,height=.1];\n",
" node139621679300936 [shape=\"box\", space=\"0.0\", margin=\"0.01\", fontcolor=\"#444443\", fontname=\"Helvetica\", label=<\n",
"\n",
"| 0 | \n",
"1 | \n",
"2 | \n",
"3 | \n",
"
\n",
"\n",
"| 'hi' | \n",
"'mom' | \n",
"{3, 4} | \n",
"{'parrt': 'user'} | \n",
"
\n",
">];\n",
"}\n",
"\n"
]
},
{
"data": {
"text/plain": [
"'Source.gv.pdf'"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = ['hi', 'mom', {3, 4}, {\"parrt\": \"user\"}]\n",
"g = listviz(data)\n",
"print(g.source) # if you want to see the graphviz source\n",
"g.view() # render and show graphviz.files.Source object"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It opened a window showing me this image:\n",
"\n",
"![](\"data/Testing_the_lolviz_Python_module_1.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Testing from within a Jupyter notebook\n",
"\n",
"I test here all [the features of lolviz](https://github.com/parrt/lolviz#functionality) :"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### List"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"squares = [ i**2 for i in range(10) ]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"squares"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"listviz(squares)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### List of lists"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"n, m = 3, 4\n",
"example_matrix = [[0 if i != j else 1 for i in range(n)] for j in range(m)]"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 0, 0]]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"example_matrix"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lolviz(example_matrix)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### List of lists of lists???"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"n, m, o = 2, 3, 4\n",
"example_3D_matrix = [[[\n",
" 1 if i < j < k else 0\n",
" for i in range(n)]\n",
" for j in range(m)]\n",
" for k in range(o)]"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[[0, 0], [0, 0], [0, 0]],\n",
" [[0, 0], [0, 0], [0, 0]],\n",
" [[0, 0], [1, 0], [0, 0]],\n",
" [[0, 0], [1, 0], [1, 1]]]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"example_3D_matrix"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lolviz(example_3D_matrix)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It works, even if it is not as pretty."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Tree\n",
"Only for binary trees, apparently. Let's try with a dictionary that looks like a binary tree:"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"anakin = {\n",
" \"name\": \"Anakin Skywalker\",\n",
" \"son\": {\n",
" \"name\": \"Luke Skywalker\",\n",
" },\n",
" \"daughter\": {\n",
" \"name\": \"Leia Skywalker\",\n",
" },\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'daughter': {'name': 'Leia Skywalker'},\n",
" 'name': 'Anakin Skywalker',\n",
" 'son': {'name': 'Luke Skywalker'}}\n"
]
}
],
"source": [
"from pprint import pprint\n",
"pprint(anakin)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'dict' object has no attribute '__dict__'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtreeviz\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmyDict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0manakin\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mleftfield\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'son'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrightfield\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'daugther'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/lolviz.py\u001b[0m in \u001b[0;36mtreeviz\u001b[0;34m(root, leftfield, rightfield)\u001b[0m\n\u001b[1;32m 102\u001b[0m \u001b[0mnodename\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"node%d\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mid\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 103\u001b[0m \u001b[0mfields\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 104\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__dict__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 105\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0mleftfield\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0mrightfield\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 106\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute '__dict__'"
]
}
],
"source": [
"treeviz(anakin, leftfield='son', rightfield='daugther')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It doesn't work out of the box for dictionaries, sadly.\n",
"\n",
"Let's check another example:"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"class Tree:\n",
" def __init__(self, value, left=None, right=None):\n",
" self.value = value\n",
" self.left = left\n",
" self.right = right\n",
" \n",
"root = Tree('parrt',\n",
" Tree('mary',\n",
" Tree('jim',\n",
" Tree('srinivasan'),\n",
" Tree('april'))),\n",
" Tree('xue',None,Tree('mike')))\n",
"\n",
"treeviz(root)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Objects"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"objviz(anakin)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"objviz(anakin.values())"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"objviz(anakin.items())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For complex numbers for instance?"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [],
"source": [
"z = 1+4j"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(1+4j)\n"
]
}
],
"source": [
"print(z)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"objviz(z)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"OK, this fails."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Calls"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"def factorial(n):\n",
" if n < 0: return 0\n",
" elif n == 0: return 1\n",
" else: return n * factorial(n - 1)"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0! = 1\n",
"1! = 1\n",
"2! = 2\n",
"3! = 6\n",
"4! = 24\n",
"5! = 120\n",
"6! = 720\n",
"7! = 5040\n",
"8! = 40320\n",
"9! = 362880\n",
"10! = 3628800\n",
"11! = 39916800\n"
]
}
],
"source": [
"for n in range(12):\n",
" print(f\"{n}! = {factorial(n)}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And now with some visualization:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from IPython.display import display"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"def factorial2(n):\n",
" display(callsviz(varnames=[\"n\"]))\n",
" if n < 0: return 0\n",
" elif n == 0: return 1\n",
" else: return n * factorial2(n - 1)"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"4! = 24\n"
]
}
],
"source": [
"n = 4\n",
"print(f\"{n}! = {factorial2(n)}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We really see the \"call stack\" as the system keeps track of the nested calls. I like that! 👌"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### String"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'0123456789abcdefABCDEF'"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import string\n",
"string.hexdigits"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"strviz(string.hexdigits)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Conclusion\n",
"That's it. See [this other example](https://github.com/parrt/lolviz/blob/master/examples.ipynb) for more."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
},
"toc": {
"colors": {
"hover_highlight": "#DAA520",
"running_highlight": "#FF0000",
"selected_highlight": "#FFD700"
},
"moveMenuLeft": true,
"nav_menu": {
"height": "226px",
"width": "252px"
},
"navigate_menu": true,
"number_sections": true,
"sideBar": false,
"threshold": 4,
"toc_cell": true,
"toc_section_display": "block",
"toc_window_display": true
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}