emacs-ipython-notebook/Demo.ipynb
John Miller ec9eefb83c Need to pass security cookie with ws open request
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2015-06-10 10:19:13 -05:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [
{
"data": {
"text/plain": [
"'3.4.3 |Continuum Analytics, Inc.| (default, Mar 6 2015, 12:08:17) [MSC v.1600 32 bit (Intel)]'"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import sys\n",
"sys.version"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.figure.Figure at 0x6445eb0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x672d590>]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"def plotnormal():\n",
" return plt.plot(np.random.randn(1000), np.random.randn(1000), 'o', alpha=0.3)\n",
"plotnormal()"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true,
"tags": [
"worksheet-0"
]
},
"source": [
"Errors are shown in informative ways:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"ERROR: File `'non_existent_file.py'` not found.\n"
]
}
],
"source": [
"%run non_existent_file"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [
{
"ename": "ZeroDivisionError",
"evalue": "division by zero",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mZeroDivisionError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-6-dc39888fd1d2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m4\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;31mZeroDivisionError\u001b[0m: division by zero"
]
}
],
"source": [
"x = 1\n",
"y = 4\n",
"z = y/(1-x)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [],
"source": [
"ip = get_ipython()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Installed hierarchymagic.py. To use it, type:\n",
" %load_ext hierarchymagic\n"
]
}
],
"source": [
"%install_ext https://raw.github.com/anaderi/ipython-hierarchymagic/master/hierarchymagic.py"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [],
"source": [
"%load_ext hierarchymagic"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [
{
"data": {
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Istx0WTvTZFkWtVpNe+62zWbttZrntC/z/Hbr4cc6nbbdjLleu+ujKErDuOhfa5fTbcBr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\nAMAGAQQAbP4PNwUeMzfDgQ8AAAAASUVORK5CYII=\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%hierarchy get_ipython()"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true,
"tags": [
"worksheet-0"
]
},
"source": [
"# Auto-Complete Sadness (Issue #55)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true,
"tags": [
"worksheet-0"
]
},
"source": [
"[Issue #55](https://github.com/millejoh/emacs-ipython-notebook/issues/55).\n",
"\n",
"Autocomplete doesn't play nicely with long arrays containing long strings.\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [],
"source": [
"longstring = '****************************************************************************************'\n",
"shortstring = '***'\n",
"shortarray = [shortstring + str(x) for x in range(12000)]\n",
"longarray = [longstring + str(x) for x in range(12000)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [],
"source": [
"shortarray[3]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [
{
"data": {
"text/plain": [
"'****************************************************************************************3'"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"longarray[3]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [],
"source": [
"1+1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"tags": [
"worksheet-0"
]
},
"outputs": [],
"source": []
}
],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 0
}