{
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{
"cell_type": "code",
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"metadata": {},
"outputs": [],
"source": [
"from reactpy import Reactive\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(4, 25, 4)"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r = Reactive()\n",
"r.a = 2\n",
"r.b = r(lambda a: a*a)\n",
"before = r.b\n",
"with r.context(a=5):\n",
" during = r.b\n",
"after = r.b\n",
"before, during, after"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"r = Reactive()\n",
"r.c = r(lambda a,b: abs(a-b))\n",
"r.result = r(lambda a,b,c: a*b + c)\n",
"\n",
"data = {}\n",
"for a, b in ((a, b) for a in range(10) \n",
" for b in range(10)):\n",
" with r.context(a=a, b=b):\n",
" data[(r.a, r.b)] = r.result "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
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"pd.Series(data).unstack()"
]
}
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