{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is highly experimental, but we could even imagine make the notebook reactive. This can be achieved by reaching into the ipython internals and overwriting the namespace. This has bugs."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from io import BytesIO"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from reactpy import Reactive, Interact, Plot, FileData, Output\n",
"O = Output\n",
"%matplotlib widget"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"r = reactive = Reactive(lazy_eval=False)\n",
"r.update(get_ipython().user_ns)\n",
"get_ipython().user_ns = r"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
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"version_minor": 0
},
"text/plain": [
"Output(outputs=({'output_type': 'stream', 'name': 'stdout', 'text': '(2, 5)'},))"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"a = 2\n",
"b = r(lambda a: a+3)\n",
"o = O(lambda a,b: (a, b))\n",
"o"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"a = 3"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
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]
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]
},
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"c = Interact('c', (-100, 100, 1))\n",
"d = Interact('d', (-100, 100, 1))\n",
"oo = O(lambda c,d: (c,d))\n",
"oo"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"p = Plot(lambda ax, c, d: ax.plot([(x+c)*(x+d)*x for x in range(-100, 100)]))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"([0, 2, 5, 6, 8, 9, 11, 23, 21, 32], 6)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"alist = [0, 2, 5, 6, 8, 9, 11, 23, 21, 32]\n",
"item = 6\n",
"alist, item"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"first = 0\n",
"last = alist.__len__()-1\n",
"found = False\n",
"mon = O(lambda first, last, found: (first, last, found))\n",
"mon"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"while first<=last and not found:\n",
" midpoint = (first + last)//2\n",
" if alist[midpoint] == item:\n",
" found = True\n",
" else:\n",
" if item < alist[midpoint]:\n",
" last = midpoint-1\n",
" else:\n",
" first = midpoint+1"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x = 2\n",
"y = 3\n",
"@reactive\n",
"def z(x, y):\n",
" return x+y\n",
"z"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"x = 5"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"z"
]
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"metadata": {},
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"@O\n",
"def o(z):\n",
" return z\n",
"o"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"x = 39"
]
}
],
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"title_sidebar": "Contents",
"toc_cell": false,
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