What is Python?#

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

Tip

See also the Python home page for further information.

Executing Python code#

You can execute Python code interactively by starting the interpreter like with the command python3 and test it with any python command such as:

print('hello')
hello

You can also put the print("hello") line in a file (hello.py) and execute it as a Python script with python3 hello.py or python3 -i hello.py to enter interactive mode after the file is executed.

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#

Supported Python 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
print('the whole dictionary:', d)
print('one entry of the dictionary:', d['p'])
the whole dictionary: {'s': 0, 'p': 1, 'd': 2}
one entry of the dictionary: 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]
print('the whole list:', l)
print('one list element:', l[1])
print('negative index:', l[-2])
the whole list: [1, ('gg', 7), 'hmm', 1.2]
one list element: ('gg', 7)
negative index: 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')
print('the original, changed list:', a)
print('the second list:', b)
the original, changed list: ['q', 'w', 'e']
the second list: ['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
print('the first number:', c)
print('the second number:', d)

e = d
e += 1
print('second and third number:', (d, e))
the first number: 42
the second number: 47
second and third number: (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


print(f(5))
print(f(5, n=8))
36
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)
print(a.c)
print(a.get_c())
print(a.m(3))
7
7
21

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

Importing modules#

There are several ways to import modules (either .py files in your working directory or packages that are installed in your python environment). For example:

import numpy; numpy.linspace(1, 10, num=5)

and

import numpy as np; np.linspace(1, 10, num=5)

and

from numpy import linspace; linspace(1, 10, num=5)

all yield the same result.

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