AGramfort's Python introduction

intro

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  "name": "Lecture-0-Scientific-Computing-with-Python"
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      "So Python...\n",
      "=============\n",
      "\n",
      "A. Gramfort ([email protected]) http://alexandre.gramfort.net\n",
      "\n",
      "based on the work of J.R. Johansson ([email protected]) http://dml.riken.jp/~rob/"
     ]
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      "What is Python?\n",
      "---------------\n",
      "\n",
      "[Python](http://www.python.org/) is a modern, general-purpose, object-oriented, high-level programming language.\n",
      "\n",
      "General characteristics of Python:\n",
      "\n",
      "* **clean and simple language:** Easy-to-read and intuitive code, easy-to-learn minimalistic syntax, maintainability scales well with size of projects\n",
      "* **expressive language:** Fewer lines of code, fewer bugs, easier to maintain.\n",
      "\n",
      "Technical details:\n",
      "\n",
      "* **dynamically typed:** No need to define the type of variables, function arguments or return types.\n",
      "* **automatic memory management:** No need to explicitly allocate and deallocate memory for variables and data arrays. No memory leak bugs. \n",
      "* **interpreted:** No need to compile the code. The Python interpreter reads and executes the python code directly.\n",
      "\n",
      "Advantages:\n",
      "\n",
      "* **Ease of programming**: minimize development time, debug and code maintainance.\n",
      "* **Encourage good programming practices**:\n",
      " * Modular, *relatively* good system for packaging and re-use of code.\n",
      " * Documentation tightly integrated with the code.\n",
      " * Forces code indentation\n",
      "* A **large standard library**, and a **large collection of add-on packages**.\n",
      "\n",
      "Disadvantages:\n",
      "\n",
      "* Since Python is an **interpreted** and **dynamically typed** programming language, the execution of python can be code slow compared to compiled statically typed programming languages, such as C and Fortran. \n",
      "* Somewhat decentralized, with different environment, packages and documentation spread out at different places. Can make it harder to get started."
     ]
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      "What makes python suitable for scientific computing?\n",
      "----------------------------------------------------\n",
      "\n",
      "<img src=\"https://raw.github.com/jrjohansson/scientific-python-lectures/master/images/optimizing-what.png\" width=\"600\">\n",
      "\n",
      "* Python has a strong position in scientific computing: \n",
      "    * Large community of users, easy to find help and documentation.\n",
      "\n",
      "* Extensive ecosystem of scientific libraries and environments\n",
      "    * numpy: http://numpy.scipy.org - Numerical Python\n",
      "    * scipy: http://www.scipy.org -  Scientific Python\n",
      "    * matplotlib: http://www.matplotlib.org - graphics library\n",
      "\n",
      "* Great performance due to close integration with time-tested and highly optimized codes written in C and Fortran:\n",
      "    * blas, altas blas, lapack, arpack, Intel MKL, ...\n",
      "\n",
      "* Good support for \n",
      "    * Parallel processing with processes and threads (have a look at http://pythonhosted.org/joblib/)\n",
      "    * Interprocess communication (MPI)\n",
      "    * GPU computing (OpenCL and CUDA)\n",
      "\n",
      "* Readily available and suitable for use on high-performance computing clusters. \n",
      "\n",
      "* No license costs, no unnecessary use of research budget."
     ]
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      "### Python interpreter\n",
      "\n",
      "The standard way to use Python is via the Python interpreter. It is a program that reads and executes the python code in files passed to it as arguments. At the command prompt, the command ``python`` is used to invoke the Python interpreter.\n",
      "\n",
      "For example, to run a file ``my_program.py`` that contains python code from the command prompt, use::\n",
      "\n",
      "    $ python my_program.py\n",
      "\n",
      "We can also start the interpreter by simply typing ``python`` at the command line, and interactively type python code into the interpreter. \n",
      "\n",
      "<!-- <img src=\"files/images/python-screenshot.jpg\" width=\"600\"> -->\n",
      "<img src=\"https://raw.github.com/jrjohansson/scientific-python-lectures/master/images/python-screenshot.jpg\" width=\"600\">\n",
      "\n",
      "**Works but not good enough** when developing scientific applications...."
     ]
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      "### IPython\n",
      "\n",
      "IPython is a powerful and user friendly interactive shell.\n",
      "\n",
      "<!-- <img src=\"files/images/ipython-screenshot.jpg\" width=\"600\"> -->\n",
      "<img src=\"https://raw.github.com/jrjohansson/scientific-python-lectures/master/images/ipython-screenshot.jpg\" width=\"600\">\n",
      "\n",
      "Some of the many useful features of IPython includes:\n",
      "\n",
      "* Command history, which can be browsed with the up and down arrows on the keyboard.\n",
      "* Tab auto-completion.\n",
      "* In-line editing of code.\n",
      "* Object introspection, and automatic extract of documentation strings from python objects like classes and functions.\n",
      "* Good interaction with operating system shell.\n",
      "* Support for multiple parallel back-end processes, that can run on computing clusters or cloud services like Amazon EE2.\n",
      "\n",
      "WATCH : https://www.youtube.com/watch?v=2G5YTlheCbw\n"
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      "IPython notebook\n",
      "----------------\n",
      "\n",
      "[IPython notebook](<http://ipython.org/ipython-doc/dev/interactive/htmlnotebook.html/) is an HTML-based notebook environment for Python, similar to Mathematica or Maple.\n",
      "\n",
      "<!-- <img src=\"files/images/ipython-notebook-screenshot.jpg\" width=\"800\"> -->\n",
      "<img src=\"https://raw.github.com/jrjohansson/scientific-python-lectures/master/images/ipython-notebook-screenshot.jpg\" width=\"800\">\n",
      "\n",
      "To start a new IPython notebook session, run the following command:\n",
      "\n",
      "    $ ipython notebook\n",
      "\n",
      "from a directory where you want the notebooks to be stored. This will open a new browser window (or a new tab in an existing window) with an index page where existing notebooks are shown and from which new notebooks can be created."
     ]
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      "Spyder\n",
      "------\n",
      "\n",
      "[Spyder](http://code.google.com/p/spyderlib/) is a MATLAB-like IDE for scientific computing with python. It has the many advantages of a traditional IDE environment, for example that everything from code editing, execution and debugging is carried out in a single environment, and work on different calculations can be organized as projects in the IDE environment.\n",
      "\n",
      "<!-- <img src=\"files/images/spyder-screenshot.jpg\" width=\"800\"> -->\n",
      "<img src=\"https://raw.github.com/jrjohansson/scientific-python-lectures/master/images/spyder-screenshot.jpg\" width=\"800\">\n",
      "\n",
      "Some advantages of Spyder:\n",
      "\n",
      "* Powerful code editor, with syntax high-lighting, dynamic code introspection and integration with the python debugger.\n",
      "* Variable explorer, IPython command prompt.\n",
      "* Integrated documentation and help."
     ]
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     "source": [
      "## Versions of Python\n",
      "\n",
      "There are currently two versions of python: Python 2 and Python 3. Python 3 will supercede Python 2 some day...\n",
      "\n",
      "To see which version of Python you have, run\n",
      "    \n",
      "    $ python --version\n",
      "    Python 2.7.3\n",
      "    $ python3.2 --version\n",
      "    Python 3.2.3\n",
      "\n",
      "Several versions of Python can be installed in parallel, as shown above.\n"
     ]
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      "## Installation\n",
      "\n",
      "### Linux\n",
      "\n",
      "In Ubuntu Linux, to installing python and all the requirements run:\n",
      "\n",
      "    $ sudo apt-get install python ipython ipython-notebook\n",
      "    $ sudo apt-get install python-numpy python-scipy python-matplotlib python-sympy\n",
      "    $ sudo apt-get install spyder\n",
      "\n",
      "### MacOS X\n",
      "\n",
      "*Macports*\n",
      "\n",
      "Python is included by default in Mac OS X, but for our purposes it will be useful to install a new python environment using [Macports](http://www.macports.org/), because it makes it much easier to install all the required additional packages. Using Macports, we can install what we need with:\n",
      "\n",
      "    $ sudo port install py27-ipython +pyside+notebook+parallel+scientific\n",
      "    $ sudo port install py27-scipy py27-matplotlib py27-sympy\n",
      "    $ sudo port install py27-spyder\n",
      "\n",
      "These will associate the commands `python` and `ipython` with the versions installed via macports (instead of the one that is shipped with Mac OS X), run the following commands:\n",
      "\n",
      "    $ sudo port select python python27\n",
      "    $ sudo port select ipython ipython27\n",
      "\n",
      "*Fink*\n",
      "\n",
      "Or, alternatively, you can use the [Fink](http://www.finkproject.org/) package manager. After installing Fink, use the following command to install python and the packages that we need:\n",
      "\n",
      "    $ sudo fink install python27 ipython-py27 numpy-py27 matplotlib-py27 scipy-py27 sympy-py27\n",
      "    $ sudo fink install spyder-mac-py27\n",
      "\n",
      "*EPD*\n",
      "\n",
      "See https://www.enthought.com/products/epd (Free for academic use)\n",
      "or EPD Free\n",
      "\n",
      "### Windows\n",
      "\n",
      "Windows lacks a good packaging system, so the easiest way to setup a Python environment is to install a pre-packaged distribution. Some good alternatives are:\n",
      "\n",
      " * [Enthought Python Distribution](http://www.enthought.com/products/epd.php). EPD is a commercial product but is available free for academic use.\n",
      " * [Anaconda CE](http://continuum.io/downloads.html). Anaconda Pro is a commercial product, but Anaconda Community Edition is free.\n",
      " * [Python(x,y)](http://code.google.com/p/pythonxy/). Fully open source.\n",
      "\n",
      "\n",
      "#### Note\n",
      "\n",
      "Anaconda CE is also available for Linux and Max OS X."
     ]
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     "source": [
      "## Further reading\n",
      "\n",
      " * [Python](http://www.python.org>). The official Python web site.\n",
      " * [Python tutorials](http://docs.python.org/2/tutorial/). The official Python tutorials.\n",
      " * [Think Python](http://www.greenteapress.com/thinkpython/). A free book on Python."
     ]
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