Introduction to Python

Overview

Teaching: 10 min
Exercises: 5 min

Questions

• What is Python?

• How do I get it to do things?

Objectives

• Start up the IPython interpreter

• Write your first code

What is Python?

Python is a general purpose programming language which means that it wasn’t designed to solve a particular problem or group of problems (like R or Matlab) but any problem you can think of to solve on a computer. Consequently, you can use Python to do almost anything from analyze data to running computer systems to creating games.

Though comprised of fairly basic syntax (i.e. the grammer of the commands you give it) it is incredibly powerful. It is relatively easy to pick up as well and thanks to a very large and growing set of external modules (or blocks of code) written by other programmers, you can do complicated things quickly and easily.

One of the reasons for this power is that it is (to a certain degree) an interpreted language. This means that the code you type gets translated into instructions the computer can understand as Python reads it. There is not a separate optimisation or ‘compilation’ step to create your executable/binary before you can run your code like there is with some other languages like C++. This allows the language to be very dynamic but does have the drawback of being slower than others. However, there are many ways Python has of overcoming these drawbacks and you will almost certainly never notice a problem!

Getting Started

Jupyter Notebook

The “Setup” section covers the instructions about how to start Jupyter and create a Python 3 notebook. After doing this, you should be presented with a screen similar to this:

A jupyter notebook is built up of ‘cells’ - one is created by default to start with. These cells are where you write code (indicated by the In prompt) or Markdown text if the cell type is changed using the dropdown on the menu bar (currently ‘code’ is selected).

You can add cells using the ‘+’ button or the menus. To run code in a cell, you can use the ‘Run’ button or hold down shift and press the ‘Enter’ key. Output is displayed underneath.

Jupyter notebooks can do an awful lot more and you’re welcome to explore them in more detail but this should get you started!

IPython

The IPython interpreter acts like the Shell but for Python commands. In other words, when you type your instructions at the prompt and press enter, it will be run straight away.

Python is run just like any other program from a shell prompt - by typing it’s name. If you haven’t already, you can start up the intrepreter by typing the following:

$ ipython

Python 3.6.5 |Anaconda, Inc.| (default, Apr 26 2018, 08:42:37) 
Type 'copyright', 'credits' or 'license' for more information
IPython 6.4.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: 

Note that the output will vary depending on your computer and how you’ve got Python installed.

Python vs. IPython

You may be wondering why you type ipython to run the Python interpreter rather than just python. This does also work but this is a much more basic interpreter than IPython that doesn’t have tab completion, syntax highlighting, etc. If you ever need an interactive Python prompt, IPython is the best option!

To quit out, you can do one of the following:

• Use Ctrl-D - it will ask for confirmation if you want to quit
• type the command exit
• type the command quit

This will then drop you back to the shell prompt you were at before.

Getting Python to do something

Now we can start Python, we can try to get it do something by giving it a command.

We shall start by getting Python to print something. This is very basic but will be invaluable going forward:

print("Hello World")

If all is well, you should see:

Hello World

So what did we just do? We typed in a python statement that was interpreted by Python and acted on when we pressed enter or ran the cell. It interpreted this as ‘call the function print with the argument "Hello World". It went away, ran the appropriate code and returned.

But what does the print function do? In this case, it’s fairly self-expanatory but if you wanted to know more you can use the help function:

help(print)

Help on built-in function print in module builtins:

print(...)
    print(value, ..., sep=' ', end='\n', file=sys.stdout, flush=False)
    
    Prints the values to a stream, or to sys.stdout by default.
    Optional keyword arguments:
    file:  a file-like object (stream); defaults to the current sys.stdout.
    sep:   string inserted between values, default a space.
    end:   string appended after the last value, default a newline.
    flush: whether to forcibly flush the stream.

If in IPython, You can press q to quit out of the editor this opened in (less if you’re interested!). In addition, IPython also has shell-like behaviour in that you can use the up arrow to go to previous commands that you’ve run. In Jupyter, you obviously don’t need that functionality as you can just go back to previous cells, edit them and re-run the cells.

In either IPython or Jupyter, you can also press Tab to auto-complete a function or variable name:

pri [Tab]

print

Exploring Tab Completion

The Tab completion functionality will also suggest the commands you mean if several match and also show the arguments a function might take.

Give this a try by doing:

pr [Tab]
print( [Tab]

What happens if you press Tab multiple times?

An important thing to remember whenever programming in Python though is that the code is case sensitive. This means that print is completely different and unrelated to Print. To show this, type the following:

Print("Hello World")

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-1-82ee0b7fee85> in <module>()
----> 1 Print("Hello World")

NameError: name 'Print' is not defined

As you can see, Python didn’t know what Print was so showed an error (a NameError in this case).

Key Points

• Python is a general purpose programming language that allows you to get a computer to do almost anything

• Generally, Python implementations are interpreted rather than compiled

• It is particularly useful at analysing data

• The ipython interpreter can use tab completion and keeps a history of the commands you run

• In Jupyter, you write your Python code in ‘cells’ which you can then run to see the output

• Use Ctrl-D to exist an IPython session

• Python code is case sensitive