Note
Go to the end to download the full example code.
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#
Type |
Description |
Example |
---|---|---|
|
Boolean |
|
|
Integer |
|
|
Floating point number |
|
|
Complex number |
|
|
String |
|
|
Tuple |
|
|
List |
|
|
Dictionary |
|
A dict object is mapping from keys to values:
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:
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:
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:
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:
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:
0 0
1 1
2 4
3 9
4 16
Functions and classes#
A function is defined like this:
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:
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.