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# What is Python?

This section will give a very brief introduction to the Python language.

See also

- The Python home page.

- Python Recipes.

- Try a Python quick reference card or a different reference card.

## Executing Python code

You can execute Python code interactively by starting the interpreter like this:

    $ python3
    >>> print('hello')
    hello

You can also put the `print('hello')` line in a file (`hello.py`) and execute it as a Python script:

    $ python3 hello.py
    hello

Or like this:

    $ python3 -i hello.py
    hello
    >>> print('hi!')
    hi!

Finally, you can put `#!/usr/bin/env python3` in the first line of the `hello.py` file, make it executable (`chmod +x hello.py`) and execute it like any other executable.

Tip

For a better interactive experience, consider ipython.

## Types

Python has the following predefined types:

type | description | example
--- | --- | ---
`bool` | boolean | `False`
`int` | integer | `117`
`float` | floating point number | `1.78`
`complex` | complex number | `0.5 + 2.0j`
`str` | string | `'abc'`
`tuple` | tuple | `(1, 'hmm', 2.0)`
`list` | list | `[1, 'hmm', 2.0]`
`dict` | dictionary | `{'a': 7.0, 23: True}`

A `dict` object is mapping from keys to values:

    >>> d = {'s': 0, 'p': 1}
    >>> d['d'] = 2
    >>> d
    {'p': 1, 'd': 2, 's': 0}
    >>> d['p']
    1

In this example all keys are strings and all values are integers. Types can be freely mixed in the same dictionary; any type can be used as a value and most types can be used as keys (mutable objects cannot be keys).

A `list` object is an ordered collection of arbitrary objects:

    >>> l = [1, ('gg', 7), 'hmm', 1.2]
    >>> l[1]
    ('gg', 7)
    >>>
    >>> l
    [1, ('gg', 7), 'hmm', 1.2]
    >>> l[-2]
    'hmm'

Indexing a list with negative numbers counts from the end of the list, so element -2 is the second last.

A `tuple` behaves like a `list` - except that it can’t be modified in place. Objects of types `list` and `dict` are mutable - all the other types listed in the table are immutable, which means that once an object has been created, it can not change. Tuples can therefore be used as dictionary keys, lists cannot.

Note

List and dictionary objects can change. Variables in Python are references to objects - think of the = operator as a “naming operator”, not as an assignment operator. This is demonstrated here:

    >>> a = ['q', 'w']
    >>> b = a
    >>> a.append('e')
    >>> a
    ['q', 'w', 'e']
    >>> b
    ['q', 'w', 'e']

The line b = a gives a new name to the array, and both names now refer to the same list.

However, often a new object is created and named at the same time, in this example the number 42 is not modified, a new number 47 is created and given the name `d`. And later, `e` is a name for the number 47, but then a new number 48 is created, and `e` now refers to that number:

    >>> c = 42
    >>> d = c + 5
    >>> c
    42
    >>> d
    47
    >>> e = d
    >>> e += 1
    >>> (d, e)
    (47, 48)

Note

Another very important type is the `ndarray` type described here: Numeric arrays in Python. It is an array type for efficient numerics, and is heavily used in ASE.

## Loops

A loop in Python can be done like this:

    >>> things = ['a', 7]
    >>> for x in things:
    ...     print(x)
    ...
    a
    7

The `things` object could be any sequence. Strings, tuples, lists, dictionaries, ndarrays and files are sequences. Try looping over some of these types.

Often you need to loop over a range of numbers:

    >>> for i in range(5):
    ...     print(i, i*i)
    ...
    0 0
    1 1
    2 4
    3 9
    4 16

## Functions and classes

A function is defined like this:

    >>> def f(x, m=2, n=1):
    ...     y =  x + n
    ...     return y**m
    ...
    >>> f(5)
    36
    >>> f(5, n=8)
    169

Here `f` is a function, `x` is an argument, `m` and `n` are keywords with default values `2` and `1` and `y` is a variable.

A class is defined like this:

    >>> class A:
    ...     def __init__(self, b):
    ...         self.c = b
    ...     def m(self, x):
    ...         return self.c * x
    ...     def get_c(self):
    ...         return self.c

You can think of a class as a template for creating user defined objects. The `__init__()` function is called a constructor, it is being called when objects of this type are being created.

In the class `A` `__init__` is a constructor, `c` is an attribute and `m` and `get_c` are methods.

    >>> a = A(7)
    >>> a.c
    7
    >>> a.get_c()
    7
    >>> a.m(3)
    21

Here we make an instance (or object) `a` of type `A`.

## Importing modules

If you put the definitions of the function `f` and the class `C` in a file `stuff.py`, then you can use that code from another piece of code:

    from stuff import f, C
    print(f(1, 2))
    print(C(1).m(2))

or:

    import stuff
    print(stuff.f(1, 2)(
    print(stuff.C(1).m(2))

or:

    import stuff as st
    print(st.f(1, 2))
    print(st.C(1).m(2))

Python will look for `stuff.py` in these directories:

1. current working directory

2. directories listed in your `PYTHONPATH`

3. Python’s own system directory (typically `/usr/lib/pythonX.Y`)

and import the first one found.