python_fm_intro.ipynb

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    "# Working with Python: functions and modules\n",
    "\n",
    "<center><img src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/c/c3/Python-logo-notext.svg/240px-Python-logo-notext.svg.png\" /></center>"
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   "source": [
    "## Presenters\n",
    "\n",
    "- Anne\n",
    "- Mukarram"
   ]
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    "## Aims\n",
    "\n",
    "This course will cover concepts and strategies for working **more effectively** with Python with the aim of: \n",
    "\n",
    "- Writing **reusable** code, using **functions** and **libraries**\n",
    "- Acquiring a working knowledge of **key concepts** which are prerequisites for advanced programming in Python e.g. writing modules and classes\n",
    "- During this course you will learn about:\n",
    "    - Writing functions\n",
    "    - Best practices to write reusable code\n",
    "    - Structuring code in a custom module\n",
    "    - Using Python libraries\n",
    "    - Drawing plots with Matplotlib and working with biological data using BioPython"
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   "source": [
    "## Learning objectives\n",
    "- **Recall** the basic syntax, how to print and define variables\n",
    "- **List** the most common data structures in Python\n",
    "- **Explain** how to write conditions and loops in Python\n",
    "- **Practice** reading and writing files with Python\n",
    "- **Explain** how to write user-defined functions and modules in Python\n",
    "- **Use** existing in-built as well as third-party Python libraries\n",
    "- **Solve** more complex exercises using these concepts"
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    "## Course schedule\n",
    "\n",
    "- 09:30-10:00: [0h30] **Introduction**\n",
    "- 10:00-11:00: [1h00] **Session 1** - Introduction to Python\n",
    "- 11:00-11:15: *break*\n",
    "- 11:15-13:00: [1h45] **Session 2** - Functions\n",
    "- 13:00-14:00: *lunch break*\n",
    "- 14:00-15:15: [1h15] **Session 3** - Modules\n",
    "- 15:15-15:30: *break*\n",
    "- 15:30-16:30: [1h00] **Session 4** - Matplotlib & BioPython"
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    "## Course materials\n",
    "\n",
    "- There are two course webpages with links to the materials, example solutions to the exercises etc.:\n",
    "    - http://pycam.github.io\n",
    "    - https://github.com/pycam\n",
    "- We’d like you to follow along with the example code as we go through the material, and attempt the exercises to practice what you’ve learned\n",
    "- Questions are welcome at any point!\n",
    "- If you have specific projects/problems that you think could be attempted using Python, we are happy to (try to) help during the exercises. Just let us know!\n"
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    "## What is *Python*?\n",
    "\n",
    "- Python is a *dynamic, interpreted* general purpose programming language initially created by Guido van Rossum in 1991\n",
    "- It is a powerful language that supports several popular programming paradigms:\n",
    "    - procedural\n",
    "    - object-oriented\n",
    "    - functional\n",
    "- Python is widely used in bioinformatics and scientific computing, as well as many other academic areas and in industry too\n",
    "- Python is available on all popular operating systems\n",
    "    - Mac\n",
    "    - Windows\n",
    "    - Linux"
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    "## The Python programming language\n",
    "\n",
    "- Python is considered to come with \"batteries included\" and the <a href=\"https://docs.python.org/3.5/library/\">standard library</a> (some of which we will see in this course) provides built-in support for lots of common tasks:\n",
    "    - numerical & mathematical functions \n",
    "    - interacting with files and the operating system\n",
    "    - ...\n",
    "\n",
    "- There is also a wide range of external libraries for areas not covered in the standard library, such as [Matplotlib](http://matplotlib.org/) the Python plotting library and the [BioPython](http://biopython.org/) Library which provides tools for bioinformatics - we look at this later"
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    "## Getting started\n",
    "\n",
    "- Python is an *interpreted* language, this means that your computer does not run Python code natively, but instead we run our code using the Python interpreter\n",
    "- There are three ways in which you can run Python code:\n",
    "    - Directly typing **commands into the interpreter**: *Good for experimenting with the language, and for some interactive work*\n",
    "    - Using a **Jupyter notebook**: *Great for experimenting with the language, and for sharing and learning*\n",
    "    - Typing code **into a file** and then telling the interpreter to run the code from this file: *Good for larger programs, and when you want to run the same code repeatedly*\n"
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    "## How to start the Python interpreter?\n",
    "\n",
    "On a Mac or Linux machine you should start a terminal and then just type the command `python3`.\n",
    "<center><img src=\"img/python_shell.png\"></center>"
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    "## How to run Python code from a file?\n",
    "\n",
    "Running Python code is as simple as opening a Terminal window and typing the command `python3` followed by the name of the script.\n",
    "\n",
    "```bash\n",
    "python3 scripts/hello.py\n",
    "```\n",
    "<center><img src=\"img/python_run_code.png\"></center>"
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    "## What is a Jupyter notebook?\n",
    "\n",
    "<img src=\"http://jupyter.org/assets/nav_logo.svg\">\n",
    "\n",
    "- The [Jupyter Notebook](http://jupyter.org/) is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. \n",
    "\n",
    "- Jupyter provides a rich architecture for interactive data science and scientific computing with: \n",
    "    - Over 40 programming languages such as Python, R, Julia and Scala.\n",
    "    - A browser-based notebook with support for code, rich text, math expressions, plots and other rich media.\n",
    "    - Support for interactive data visualization.\n",
    "    - Easy to use tools for parallel computing."
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   "source": [
    "## How to install Jupyter on your own computer?\n",
    "\n",
    "<img src=\"http://jupyter.org/assets/nav_logo.svg\">\n",
    "\n",
    "- We recommend using a virtual environment after having installed [Python 3](https://www.python.org/).\n",
    "```bash\n",
    "python3 -m venv venv\n",
    "source venv/bin/activate # activate your virtual environment\n",
    "pip install jupyter\n",
    "```\n",
    "\n",
    "- Start the notebook server from the command line:\n",
    "```\n",
    "jupyter notebook\n",
    "```\n",
    "- You should see the notebook home page open in your web browser.\n"
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    "## How to run python in a Jupyter notebook?\n",
    "\n",
    "<img src=\"http://jupyter.org/assets/nav_logo.svg\">\n",
    "\n",
    "- See [Jupyter Notebook Basics](http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb)\n",
    "\n",
    "\n",
    "- Go to our notebook for the fist session: [python_functions_and_modules_1](python_fm_1.ipynb)"
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