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Python2017_zadania/labs05/Lab05.ipynb
2017-12-16 06:21:44 +01:00

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{
"cells": [
{
"cell_type": "markdown",
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"source": [
"# Python: część 3\n",
"\n",
"## Tomasz Dwojak\n",
"\n",
"### 16 grudnia 2017"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Co już było?\n",
" * podstawowe typy i struktury danych\n",
" * funkcje\n",
" * biblioteki\n",
" * klasy\n",
" * praca z plikami\n",
" * wyjątki"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Co na dziś?\n",
" * Dzielenie kodu na pliki\n",
" * Podstawy analizy danych: Pandas"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Dzielenie kodu\n",
"\n",
" * Zwiększenie jakości kodu\n",
" * Napisz raz i korzystaj w wielu sytuacjach\n",
" * Tworzenie własnej biblioteki"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Dzielenie kodu - podsumowanie\n",
" * import\n",
" * ``if __name__ == '__main__'``\n",
" * Pakiety i pliki ``__init__.py``\n",
" * zmienna PYTHONPATH i ``sys.path``"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Interpreter Pythona"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Jupyter notebook"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Argumenty do programu\n",
"\n",
" * czy potrzebujemy pyCharm żeby uruchomić prosty skrypt?"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### sys.argv\n",
" * zawiera liste wszystkich argumentów\n",
" * pierwszy element zawiera nazwe pliku"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['/usr/lib/python2.7/site-packages/ipykernel/__main__.py', '-f', '/run/user/1000/jupyter/kernel-7efdb6ca-75d5-474e-90c4-fda3dadc3282.json']\n"
]
}
],
"source": [
"import sys\n",
"print(sys.argv)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Biblioteka argparse"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [],
"source": [
"import argparse\n",
"parser = argparse.ArgumentParser()\n",
"parser.parse_args()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"source": [
"parser = argparse.ArgumentParser()\n",
"parser.add_argument(\"number\", help=\"Opis\")\n",
"args = parser.parse_args()\n",
"print(args.number)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"source": [
"parser = argparse.ArgumentParser()\n",
"parser.add_argument(\"number\", help=\"Opis\", nargs=\"+\")\n",
"args = parser.parse_args()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"source": [
"parser = argparse.ArgumentParser()\n",
"parser.add_argument(\"--verbosity\", help=\"increase output verbosity\")\n",
"args = parser.parse_args()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"source": [
"parser = argparse.ArgumentParser()\n",
"parser.add_argument(\"--verbose\", help=\"increase output verbosity\",\n",
" action=\"store_true\")\n",
"args = parser.parse_args()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"source": [
"parser = argparse.ArgumentParser()\n",
"parser.add_argument(\"-v\", \"--verbose\", help=\"increase output verbosity\",\n",
" action=\"store_true\")\n",
"args = parser.parse_args()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"source": [
"parser = argparse.ArgumentParser()\n",
"parser.add_argument(\"-v\", \"--verbose\", help=\"increase output verbosity\",\n",
" action=\"store_true\")\n",
"parser.add_argument(\"number\", help=\"Opis\", nargs=\"+\")\n",
"args = parser.parse_args()"
]
}
],
"metadata": {
"celltoolbar": "Slideshow",
"kernelspec": {
"display_name": "Python 2",
"language": "python2",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.14"
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"nbformat": 4,
"nbformat_minor": 2
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