![](\"files/images/PythonCamp.jpg\")
\n",
"\n",
"\n",
"Much of this material thanks to http://www.pythonbootcamp.info/\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Objectives\n",
"----------\n",
"- Introduce you to the Python language\n",
"- Get you *writing* Python code.\n",
"- Convince you of Python's utility in your research life\n",
"- Encourage good coding and data-management practices\n",
"- Don't proselytize Python... too much"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Organization\n",
"------------\n",
"- Thursday-Friday, 9:00-12:00 & 1:00-4:00\n",
"- Broken into 1-hour \"modules\"\n",
"- Short breakout coding sessions after each module\n",
"- Actual coding $\\to$ actual learning"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Course Information\n",
"------------------\n",
"\n",
"- Course website: [http://www.astro.washington.edu/vanderplas/Astr599](http://www.astro.washington.edu/vanderplas/Astr599)\n",
"- Github source: [http://github.com/jakevdp/2013_fall_ASTR599/](http://github.com/jakevdp/2013_fall_ASTR599/)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Connecting to Me\n",
"----------------\n",
"### Jake Vanderplas\n",
"\n",
"- Email: jakevdp@cs.washington.edu\n",
"- Twitter: [@jakevdp](http://www.twitter.com/jakevdp)\n",
"- Github: [jakevdp](http://github.com/jakevdp)\n",
"- Web: [http://www.astro.washington.edu/vanderplas](http://www.astro.washington.edu/vanderplas)\n",
"- Blog: [http://jakevdp.github.io](http://jakevdp.github.io)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"![](\"files/images/python-logo.png\"){kind=logo}
\n",
"\n",
"### 1. What is Python?\n",
"\n",
"### 2. Why should a scientist use Python?\n",
"\n",
"### 3. Getting started: four ways to use Python"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## What is Python?\n",
"\n",
"> Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.\n",
"\n",
"IDL, Matlab, Mathematica
\n", "\n", "### Pros:\n", " + Interactive with easy visualization tools\n", " + Extensive scientific libraries\n", " \n", "### Cons:\n", " + Costly and Proprietary\n", " + Unpleasant for large-scale computing & non-mathematical tasks" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Why should a Scientist use Python?\n", "\n", "- Python is free (BSD license) and highly portable (Linux, Mac OSX, Windows, etc.)\n", "- Interactive interpreter\n", "- Extremely readable syntax\n", "- Simple: non-professional programmers can use it effectively\n", " + great documentation\n", " + memory management is taken care of\n", " \n", " " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Why should a Scientist use Python? (cont')\n", "\n", "- Clean (and optional) object-oriented model\n", "- Rich collection of built-in types, from simple to compound\n", "- Comprehensive standard library\n", "- Well-established 3rd-party packages (NumPy, SciPy, Matplotlib)\n", "- Easy wrapping of legacy code (C, C++, Fortran)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Why should a Scientist use Python? (cont')\n", "\n", "- Python mastery is a marketable skill-set.\n", " + ([Python Job Board](http://www.python.org/community/jobs/))\n", "- By comparison, virtually no industries use IDL\n", " + (sorry...)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Why should a Scientist use Python? (cont')\n", "\n", "Amazingly Scalable
\n", "\n", "- Allows interactive experimentation\n", "- Code can be one-line scripts or million-line projects\n", "- Used by novices and full-time professionals alike\n", "\n", "The Kitchen Sink
\n", "\n", "- Python can do anything you want with impressive simplicity\n", "\n", "Performance when you need it
\n", "\n", "- As an interpreted language, Python can be slow\n", "- But there are good options to get around this (as we'll see)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# LSST Group uses it for...\n", "\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## IPython Notebook in Action:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline\n",
"\n",
"N = 200\n",
"r = 2 * rand(N)\n",
"theta = 2 * pi * rand(N)\n",
"area = 200 * r ** 2 * rand(N)\n",
"ax = plt.subplot(111, polar=True)\n",
"scatter(theta, r, c=theta, s=area, alpha=0.75)"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": [
"Data reduction & Analysis
\n", "Wrapping of LSST C++ Pipeline
\n", "Quick Calculations
\n", "Building websites
\n", "Quick Visualization
\n", "Plots for Publications
\n", "![](\"files/images/OSX_terminal.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 1. The Python command-line Interpreter\n",
"\n",
"Type ``python`` at the command-line to start the interpreter\n",
"\n",
"![](\"files/images/OSX_terminal_python.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 1. The Python Command-line Interpreter\n",
"\n",
"Execute a command: Type ``print \"hello world\"``\n",
"\n",
"![](\"files/images/OSX_terminal_hello.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 1. The Python Command-line Interpreter\n",
"\n",
"Closing the terminal:\n",
"\n",
"- Either type ``exit()`` or type ``Ctrl-d``\n",
"\n",
"![](\"files/images/OSX_terminal_exit.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 2. Editing Python (.py) files\n",
"\n",
"### This requires a text editor.\n",
"\n",
"The best option is one which includes code highlighting\n",
"\n",
"- Linux: gedit, emacs, nano, vim...\n",
"- Mac OSX: textmate, emacs, nano, vim...\n",
"- Windows: NotePad...\n",
"\n",
"### GUI-based editors with bells & whistles\n",
"\n",
"- Linux: KWrite, Scribes, eggy\n",
"- Mac OSX: TextWrangler, SublimeText\n",
"- Windows: NotePad++, SublimeText"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 2. Editing Python (.py) files\n",
"\n",
"Use your editor to open ``hello_world.py`` (here we use OSX's ``mate``)\n",
"\n",
"![](\"files/images/OSX_mate.png\")
\n",
"\n",
"Edit the file to say ``print \"hello world\"``\n",
"\n",
"![](\"files/images/mate_hello_world.png\")
\n",
"\n",
"In the terminal, run ``python hello_world.py``\n",
"\n",
"![](\"files/images/run_hello_world.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 3. The IPython command-line Interpreter\n",
"\n",
"IPython provides an enhanced command-line interface\n",
"\n",
"It can be started by typing ``ipython``:\n",
"\n",
"![](\"files/images/ipython_start.png\")
\n",
"\n",
"Useful features include tab completion, help (``?``), etc."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 3. The IPython command-line Interpreter\n",
"\n",
"Basic use is just like the standard interpreter:\n",
"\n",
"![](\"files/images/ipython_hello.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 4. The IPython Notebook\n",
"\n",
"The IPython notebook can be started by typing ``ipython notebook``:\n",
"\n",
"![](\"files/images/ipynb_command.png\")
\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 4. The IPython Notebook\n",
"\n",
"\n",
"Your web browser should open to an interactive notebook page\n",
"\n",
"![](\"files/images/ipynb_start_page.png\")
\n",
"\n",
"Notice that this slideshow is written as an IPython notebook!\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Conclusions\n",
"\n",
"- We've introduced Python and motivated its use in science\n",
"\n",
"- We've talked about four ways to use Python\n",
"\n",
"- Next up: basic training - getting started in Python"
]
}
],
"metadata": {}
}
]
}