first commit

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Ayxan committed 2022-05-23 00:16:32 +04:00
commit d660f2a4ca
24786 files changed
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "036cb3ce-96fe-4159-8145-40bb74b263f9",
"metadata": {},
"outputs": [],
"source": [
"import ipywidgets as widgets\n",
"widgets.IntSlider(\n",
" value=7,\n",
" min=0,\n",
" max=10,\n",
" step=1,\n",
" description='Test:',\n",
" disabled=False,\n",
" continuous_update=False,\n",
" orientation='horizontal',\n",
" readout=True,\n",
" readout_format='d'\n",
")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
@@ -0,0 +1,47 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "036cb3ce-96fe-4159-8145-40bb74b263f9",
"metadata": {},
"outputs": [],
"source": [
"import ipywidgets as widgets\n",
"widgets.IntSlider(\n",
" value=7,\n",
" min=0,\n",
" max=10,\n",
" step=1,\n",
" description='Test:',\n",
" disabled=False,\n",
" continuous_update=False,\n",
" orientation='horizontal',\n",
" readout=True,\n",
" readout_format='d'\n",
")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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@@ -0,0 +1,7 @@
from nbconvert.writers.base import WriterBase
class HelloWriter(WriterBase):
def write(self, output, resources, notebook_name=None, **kw):
with open("hello.txt", "w") as outfile:
outfile.write("hello world")
@@ -0,0 +1,5 @@
c = get_config()
# Export all the notebooks in the current directory to the sphinx_howto format.
c.NbConvertApp.notebooks = ["notebook1.ipynb"]
c.NbConvertApp.export_format = "python"
@@ -0,0 +1,32 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![image](testimage.png)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "",
"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": "3.4.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
@@ -0,0 +1,74 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f21298cc828>]"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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truncated
"text/plain": [
"<matplotlib.figure.Figure at 0x7f21541826a0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from IPython.display import set_matplotlib_formats\n",
"# generate pdf and png images\n",
"set_matplotlib_formats('pdf', 'png')\n",
"\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"\n",
"plt.plot(range(5))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [Root]",
"language": "python",
"name": "Python [Root]"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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@@ -0,0 +1,176 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# A simple SymPy example"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"First we import SymPy and initialize printing:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"outputs": [],
"source": [
"from sympy import init_printing\n",
"from sympy import *\n",
"init_printing()"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Create a few symbols:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"outputs": [],
"source": [
"x,y,z = symbols('x y z')"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Here is a basic expression:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAKMAAAAZBAMAAACvE4OgAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\nSUVORK5CYII=\n",
"text/latex": [
"$$x^{2} + 2.0 y + \\sin{\\left (z \\right )}$$"
],
"text/plain": [
" 2 \n",
"x + 2.0⋅y + sin(z)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"e = x**2 + 2.0*y + sin(z); e"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAOBAMAAADd6iHDAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAIpm7MhCriUTv3c12\nVGZoascqAAAAgElEQVQIHWNgVDJ2YICAMAb2H1BmKgPDTChzFgNDvgOEvT8AzgQKrA9gPZPYUwNk\ncXxnCGd4dWA1kMllwFDKUB9wEchUZmAIYNgMZDDwJIDIPyDiEgOjAAPLFwZWBhYFBh6BqzwfGI4y\nSJUXZXH8Zf7A+IBh////v1hzjh5/xwAAW80hUDE8HYkAAAAASUVORK5CYII=\n",
"text/latex": [
"$$2 x$$"
],
"text/plain": [
"2⋅x"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"diff(e, x)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAALsAAAAZBAMAAACbakK8AAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\nYII=\n",
"text/latex": [
"$$x^{2} z + 2.0 y z - \\cos{\\left (z \\right )}$$"
],
"text/plain": [
" 2 \n",
"x ⋅z + 2.0⋅y⋅z - cos(z)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"integrate(e, z)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"slideshow": {
"slide_type": "skip"
}
},
"outputs": [],
"source": []
}
],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 1
}
File diff suppressed because it is too large. Load diff
@@ -0,0 +1,55 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Notebook with errors"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook contains a cell which deliberately throws an exception. This is to test if `nbconvert` stops conversion if the flag `--execute` is given without `--allow-errors`. In the cells before and after the one which raises the exception we compute a couple of numbers. If they exist in the output we know that the respective cells were executed."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"print(\"Hello world, my number is {}\".format(24 - 1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"print(\"Some text before the error\")\n",
"raise RuntimeError(\"This is a deliberate exception\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"print(\"The answer to the question about life, the universe and everything is: {}\".format(43 - 1))"
]
}
],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 0
}
@@ -0,0 +1,65 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The latest trend in DevOps."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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truncated
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from IPython.display import Image\n",
"Image('containerized_deployments.jpeg', embed=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"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": "3.5.0"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
@@ -0,0 +1,51 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "e684608d",
"metadata": {},
"source": [
"![](./containerized_deployments.jpeg)"
]
},
{
"cell_type": "markdown",
"id": "e609fcaf",
"metadata": {},
"source": [
"<img src='./containerized_deployments.jpeg'></img>"
]
},
{
"cell_type": "markdown",
"id": "a0043f9e",
"metadata": {},
"source": [
"<div>\n",
" <img src='./containerized_deployments.jpeg'></img>\n",
"</div>"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
@@ -0,0 +1,30 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"function foobar(x)\n",
" 100x\n",
"end"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 0.4.0-dev",
"language": "julia",
"name": "julia-0.4"
},
"language_info": {
"name": "julia",
"version": "0.4.0"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
@@ -0,0 +1,89 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"tags": [
"mycelltag",
"mysecondcelltag"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"this cell should have tags in html output\n"
]
}
],
"source": [
"print(\"this cell should have tags in html output\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"this cell should NOT have tags in html output\n"
]
}
],
"source": [
"print(\"this cell should NOT have tags in html output\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"mymarkdowncelltag"
]
},
"source": [
"This markdown cell should have tags in the html output"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This markdown cell should **not** have tags in the html output"
]
}
],
"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": "3.7.3"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 4
}
@@ -0,0 +1,5 @@
c = get_config()
# Export all the notebooks in the current directory to the sphinx_howto format.
c.NbConvertApp.notebooks = ["notebook2.ipynb"]
c.NbConvertApp.export_format = "python"
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