Download Introducing Python Part I

Tutorials Applied Visualizaton
Summer Term 2009
Part II - Introducing Python
Introducing Python
Python
Simple, flexible, easy to learn
Extendible
Used in a vast variety of commercial and open
source products
•
•
•
•
It has nothing to do with reptiles
• The name actually comes from
“Monty Python’s Flying Circus”
Computer Graphics Group
Friedrich-Alexander Universität Erlangen - Nürnberg
Introducing Python
Python
•
If you already know a programming language
such as C or C++ there will be some things you
need to get used to
• High-level data types allow to express complex
operations in a single statement
• Statement grouping is done by indentation
instead of beginning and ending brackets
• No variable or argument declarations are
necessary
Introducing Python
An informal introduction
Invoking the interpreter
•
Last login: Tue May 5 10:43:28 on ttys000
[13:51:28] machine:~ $ python
•
Ensure that the Python binary is in your PATH
/usr/local/bin - Commonly on *nix machines
• C:\Python2X\ - Commonly on Windows machines
•
Introducing Python
An informal introduction
•
Invoking the interpreter
Introducing Python
An informal introduction
•
>>> # this is the first comment
... SPAM=1
# a second comment
>>>
# and a third
... STRING="#this is not a comment"
>>>
>>> print SPAM
1
>>> print STRING
#this is not a comment
Introducing Python
An informal introduction
•
Using Python as a calculator
>>>
>>>
>>>
>>>
900
>>>
>>>
>>>
0
>>>
0
>>>
0
•
Using Python as a calculator
>>>
4
>>>
5
>>>
>>>
2
>>>
-3
Python 2.5.1 (r251:54863, Jan 17 2008, 19:35:17)
[GCC 4.0.1 (Apple Inc. build 5465)] on darwin
Type "help", "copyright", "credits" or "license" for
more information.
•
2+2
(50-5*6)/4 # and a comment
7/3
7/-3
Note that integer division returns the floor of the
result
Introducing Python
An informal introduction
•
However, variables must be “defined”
Assigned to some value before being used
!
w = 20
h = 5*9
w*h
>>> n
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'n' is not defined
>>>
x = y = z = 0
x
y
z
No declaration for variables!
•
Note how Python will tell you when something is
wrong
Introducing Python
An informal introduction
•
However, variables must be “defined”
! Assigned to some value before being used
Introducing Python
An informal introduction
•
Using Python as a calculator
• Built in operators
>>> n = 7
>>> n
7
>>>
•
Introducing Python
An informal introduction
•
Using Python as a calculator
• Python has full floating point support
>>> 3 * 3.75 / 1.5
7.5
>>> 7.0 / 2
3.5
>>>
•
Note how the argument types determine the
result type
+
-
*
/
%
**
>>
<<
&
|
^
~
All binary except ~
Introducing Python
An informal introduction
•
Using Python as a calculator
• There even are complex numbers
>>>
>>> 1j * 1J
(-1+0j)
>>> 1j * complex(0,1)
(-1+0j)
>>> 3+1j*3
(3+3j)
>>> (1+2j)/(1+1j)
(1.5+0.5j)
>>>
//
Introducing Python
An informal introduction
•
Using Python as a calculator
• There even are complex numbers
Introducing Python
An informal introduction
•
>>>
>>> a=1.5+0.5j
>>> a.real
1.5
>>> a.imag
0.5
>>>
Introducing Python
An informal introduction
•
Using Python as a calculator
• The variable _
>>>
>>> tax = 12.5 / 100
>>> price = 100.50
>>> price * tax
12.5625
>>> price + _
113.0625
>>> round(_, 2)
113.06
>>>
Using Python as a calculator
• Conversions
>>> b = 1.5
>>> c = 2
>>> int(b)
1
>>> float(c)
2.0
>>> float(a)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: can't convert complex to float; use abs(z)
>>> abs(a)
1.5811388300841898
>>>
Introducing Python
An informal introduction
•
Strings
>>> 'hello world'
'hello world'
>>> "hello world"
'hello world'
>>> 'hey, it\'s python'
"hey, it's python"
>>>
Introducing Python
An informal introduction
•
Strings (escaping long lines)
Introducing Python
An informal introduction
•
Strings (triple quotes)
>>>
>>>
...
...
...
...
>>> test = "Hello, this is a long \
... string, expanding over several lines.\
... \n \
... "
>>> print test
Hello, this is a long string, expanding over several lines.
print """
Hello, this is a multi
line
test string
"""
Hello, this is a multi
line
test string
>>>
Introducing Python
An informal introduction
•
Strings (concatenation / repetition)
>>> test = "Hello " + " VTK " + " class!"
>>> print test
Hello VTK class!
>>> greeting = "Hello"
>>>
>>> test = greeting*3 + " VTK class!"
>>> print test
HelloHelloHello VTK class!
>>>
Introducing Python
An informal introduction
•
Strings (subscription / slicing)
>>> word = "Hello"
>>> word[4]
'o'
>>> word[0:2]
'He'
>>> word[2:4]
'll'
>>> word[:2]
'He'
>>> word[2:]
'llo'
>>>
Introducing Python
An informal introduction
•
Strings are constant in Python
Introducing Python
An informal introduction
•
>>> 'X' + word[1:]
'Xello'
>>>
>>>
>>> "Mo" + word[4]
'Moo'
>>>
>>> word[0] = 'X' # OOPS!
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'str' object does not support item assignment
Introducing Python
An informal introduction
•
Negative subscripts
>>> word[-1]
'o'
>>> word[-2]
'l'
>>> word[-2:]
'lo'
>>> word[:-2]
'Hel'
>>>
>>> len(word)
5
You can create new strings, however
Introducing Python
An informal introduction
•
Slices and indexing
H
E
L
L
O
0
1
2
3
4
-5
-4
-3
-2
-1
1
:
3
-4
:
-2
Introducing Python
An informal introduction
•
Introducing Python
Python data types
Strings - Odds and Ends
•
>>> word = u"Hello" # This is a Unicode string now
>>> print word
Hello
•
>>> test = r"This is a raw string.\nNote how the escape
character stays."
>>> print test
This is a raw string.\nNote how the escape character stays.
>>>
>>> word = ur"Hello\n" # Unicode raw
>>> print word
Hello\n
>>>
Introducing Python
Python data types - Lists
•
Expressed as list of comma separated values
between square brackets
>>>
>>> alist = [ 'spam', 123, 'eggs', 22.56, 'x']
>>> alist
['spam', 123, 'eggs', 22.559999999999999, 'x']
>>>
•
•
Items can have different types
Can even contain lists (dictionaries, tuples,...)
>>>
>>> a = [ 1, 'test', [ 2, 4 ], 3]
>>> a
[1, 'test', [2, 4], 3]
>>>
•
Python has a number of compound data types
Used to group together other values
• Lists
• Dictionaries
• Tuples
• Sets
The most versatile is the List
Introducing Python
Python data types - Lists
•
Lists can be indexed just like strings
• In fact, strings are just immutable lists
>>> print a
[1, 'test', [2, 4], 3]
>>>
>>> a[0]
1
>>> a[3]
3
>>> a[-2]
[2, 4]
>>> a[-3]
'test'
>>>
Introducing Python
Python data types - Lists
•
Lists can be indexed just like strings
• In fact, strings are just immutable lists
Introducing Python
Python data types - Lists
•
>>> a[1:-1]
['test', [2, 4]]
>>> a[3:]
[3]
>>> a[:2]
[1, 'test']
>>>
>>> a[:2] + ['moo', 2*2]
[1, 'test', 'moo', 4]
>>> 3*a[:3] + ['moo', 2*2]
[1, 'test', [2, 4], 1, 'test', [2, 4], 1, 'test', [2, 4],
'moo', 4]
>>>
Introducing Python
Python data types - Lists
•
Lists can be indexed just like strings
• Assignment to slices is also possible
>>>
[1,
>>>
>>>
[1,
>>>
>>>
[1,
>>>
>>>
[]
>>>
a
'testtesttest', [256, 4], 3]
a[1:3] = [2,3,4,5]
a
2, 3, 4, 5, 3]
a[-1:] = []
a
2, 3, 4, 5]
a[:] = []
a
Lists can be indexed just like strings
• Unlike strings, you can change list items
>>>
[1,
>>>
>>>
[1,
>>>
>>>
>>>
[1,
>>>
a
'test', [2, 4], 3]
a[1] = 3*a[1]
a
'testtesttest', [2, 4], 3]
a[2][0] = 256
a
'testtesttest', [256, 4], 3]
Introducing Python
Python data types - Lists
•
Lists can be indexed just like strings
• Assignment to slices is also possible
>>>
>>> a = ['a', 'b', 'd','e']
>>> a
['a', 'b', 'd', 'e']
>>> a[2:2] = ['c']
>>> a
['a', 'b', 'c', 'd', 'e']
>>>
Introducing Python
Python data types - Lists
•
Lists can be indexed just like strings
• Assignment to slices is also possible
Introducing Python
Python data types - Lists
•
>>>
>>>
>>>
[1,
>>>
>>>
[1,
>>>
>>>
[1,
>>>
>>>
>>> b = a[:]
>>> b
['a', 'b', 'c', 'd', 'e']
>>>
>>> len(b)
5
>>>
>>> b[len(b)-1]
'e'
>>>
Introducing Python
Python data types - Lists
•
Methods of lists
>>> list.remove(4)
>>> list
[1, 2, 2.5, 3, 5, 6]
>>> list.pop(1)
2
>>> list
[1, 2.5, 3, 5, 6]
>>>
>>> list.index(3)
2
>>> list.index(10)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: list.index(x): x not in list
>>> 10 in list
False
Methods of lists
list = [1,2,3]
list.append(4)
list
2, 3, 4]
list.insert(2, 2.5)
list
2, 2.5, 3, 4]
list.extend([5,6])
list
2, 2.5, 3, 4, 5, 6]
Introducing Python
Python data types - Lists
•
Methods of lists
>>>
>>>
3
>>>
>>>
>>>
[0,
>>>
>>>
>>>
[9,
>>>
list = [3,2,6,4,8,9,0,1,4,5,4]
list.count(4)
list.sort()
list
1, 2, 3, 4, 4, 4, 5, 6, 8, 9]
list.reverse()
list
8, 6, 5, 4, 4, 4, 3, 2, 1, 0]
Introducing Python
Python data types - Lists
•
Introducing Python
Python data types - Tuples
Methods of lists
• Note the difference between append and extend
>>>
>>>
>>>
[1,
>>>
>>>
[1,
>>>
>>> t = ("a", 3, "c")
>>> t
('a', 3, 'c')
>>>
>>> t2 = 1, 'a', 3
>>> t2
(1, 'a', 3)
>>>
list = [1,2,3]
list.extend([4,5])
list
2, 3, 4, 5]
list.append([6,7])
list
2, 3, 4, 5, [6, 7]]
•
•
•
•
Introducing Python
Python data types - Tuples
>>> empty = ()
>>> single = "single",
>>>
>>> empty
()
>>> single
('single',)
>>>
•
•
•
You cannot change elements in tuples
Tuples are faster than lists
Tuples can be converted into lists and vice-versa
(tuple and list functions)
Are defined like lists, but () are used instead of []
Can use the same indexing methods as lists
There are no methods on tuples (like append)
You can index tuples like lists ([] operator)
Introducing Python
Python data types - Tuples
•
Packing and Unpacking
>>>
>>>
(1,
>>>
>>>
1
>>>
2
>>>
3
•
>>>
t = 1,2,3
t
2, 3)
x,y,z = t
x
y
z
Introducing Python
Python data types - Sets
A set is an unordered collection with no
duplicates
•
>>> list = [ 1, 2, 3, 5, 6, 6, 1, 1, 3 ]
>>> set(list)
set([1, 2, 3, 5, 6])
>>>
Introducing Python
Python data types - Dictionaries
A collection of key - value pairs
•
•
•
•
•
Enclosed in {}, Form: key:value
Keys can be strings and numbers or tuples, if they
consists only of strings and numbers
In other words: keys must be immutable
Values can be any type
Introducing Python
Python data types - Dictionaries
•
A collection of key - value pairs
>>> a_dict
{ 1:"hello",
"a_value", "a_number":33.23 }
• =Enclosed
in {},"a_key":
Form: key:value
>>> a_dict
•
Keys
can 'a_value',
be strings 'a_number':
and numbers
or tuples, if they
{1: 'hello',
'a_key':
33.229999999999997}
>>> a_dict[1]
consists only of strings and numbers
'hello'
•
In other words: keys must be immutable
>>> a_dict["a_number"]
33.229999999999997
>>> a_dict["new_key"] = 42
>>> a_dict
{1: 'hello', 'new_key': 42, 'a_key': 'a_value', 'a_number':
33.229999999999997}
>>> a_dict["UnknownKey"]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError: 'UnknownKey'
>>>
Introducing Python
Python data types - The del statement
•
del can be used with lists and dictionaries
>>> a_dict
{1: 'hello', 'new_key': 42, 'a_key': 'a_value'}
>>> del a_dict["a_key"]
>>> a_dict
{1: 'hello', 'new_key': 42}
>>>
>>> list = [ 'a', 'b', 2,3,4]
>>> list
['a', 'b', 2, 3, 4]
>>> del list[2]
>>> list
['a', 'b', 3, 4]
>>> del list[len(list)-1]
>>> list
['a', 'b', 3]
>>>
Introducing Python
Python data types - odds and ends
•
You can always create empty lists and
dictionaries
>>> test1 = []
>>> test2 = {}
>>> test1
[]
>>> test2
{}
>>> test2["akey"] = 10
>>> test1.append(2)
>>> test1
[2]
>>> test2
{'akey': 10}
>>>
Introducing Python
Writing scripts
•
•
•
•
Usually you won’t use the interpreter directly
Create a simple text file to keep your code
By convention, these have the ending .py
Invoke the interpreter supplying your file
machine:~user$ cat test.py
greeting = "Hello " + " VTK " + " class!"
print greeting
machine:~user$ python test.py
Hello VTK class!
machine:~user$
Introducing Python
Writing scripts
•
You can pass command line parameters
[23:42:55] lyra:examples $ cat cmdline.py
import sys
print sys.argv
[23:43:00] lyra:examples $
[23:42:54] lyra:examples $ python cmdline.py 4 83 hello
['cmdline.py', '4', '83', 'hello']
Introducing Python
First steps towards programming
•
Of course, you can use Python for more
complicated tasks than adding two and two
together
>>> a, b = 0, 1
>>> while b < 10:
...
print b
...
a, b = b, a+b
...
1
1
2
3
5
8
>>>
Introducing Python
First steps towards programming
•
Note some details
• Multiple assignment for a and b
• The while loop
•
First steps towards programming
•
•
Loops the body until the condition (b < 10) is False
# If block
if COND:
stmnt
elif OTHERCOND:
stmnt
elif EVENOTHERCOND:
stmnt
else:
stmnt
Intendation is Pythons way of grouping statements
Introducing Python
First steps towards programming
Control Flow - while and if
>>> a, b = 0, 1
>>> while b < 10:
...
if b == 3:
...
print "WOW, b is ", b
...
else:
...
print b,
...
a, b = b, a+b
...
1 1 2 WOW, b is 3
5 8
>>>
Control Flow - while and if
# While loop
while COND:
stmnt
stmnt
The body of the loop is indented
•
•
Introducing Python
Note the behavior of the print statement
# OPTIONAL
# OPTIONAL
# OPTIONAL
Introducing Python
First steps towards programming
•
Conditional operators
<
>
<=
>=
==
!=
#
#
#
#
#
#
Lower than
Greater than
Lower or equal
Greater or equal
Equal
Not equal
and # Logical and
or # Logical or
not # Logical not
•
•
# REQUIRED
•
•
A COND is anything that evaluates to True or False
Interpreted as False are: False, None, numeric zero
of all types, empty strings and containers.
All other values are interpreted as True
Introducing Python
First steps towards programming
•
Control Flow - for
Introducing Python
First steps towards programming
•
>>>
>>> a = [ 'a', 'moo', 'vtk', 'class' ]
>>> for x in a:
...
print x, len(x)
...
a 1
moo 3
vtk 3
class 5
>>>
•
•
First steps towards programming
•
>>>
[0,
>>>
[4,
>>>
[4,
>>>
>>>
...
...
0 1
>>>
This differs from what you might be used to
There is no iterating over an arithmetic
progression of values
Introducing Python
Control Flow - for
• It is not safe to modify the sequence beeing
iterated over - but you can also trick a little
>>> for v in a[:]: # Makes a copy(!) of the list!
...
if len(v) == 3:
...
a.insert(a.index(v)+1, 'moo')
...
>>> a
['fooo', 'bar', 'moo', 'foobar']
>>>
Control Flow - for
• range() does the trick
range(10)
1, 2, 3, 4, 5, 6, 7, 8, 9]
range(4,10)
5, 6, 7, 8, 9]
range(4,10,2)
6, 8]
for i in range(10):
print i,
2 3 4 5 6 7 8 9
Introducing Python
First steps towards programming
•
break, continue, and else on loops
• break breaks out of the smallest enclosing for
or while loop
• continue continues with the next iteration of
the loop
• Loop statements may have an else clause
•
•
Executed when the loop terminates normally
Not executed when the loop is terminated by
break
Introducing Python
First steps towards programming
•
break, continue, and else on loops
Introducing Python
First steps towards programming
•
>>> for n in range(2,10):
...
for x in range(2, n):
...
if n % x == 0:
...
print n, " = ", x, '*', n/x
...
break
...
else:
...
print n, " is prime number"
...
2 is prime number
3 is prime number
4 = 2 * 2
5 is prime number
6 = 2 * 3
7 is prime number
8 = 2 * 4
9 = 3 * 3
>>>
Introducing Python
First steps towards programming
•
Defining functions
>>> def fib(n):
...
""" Print a Fibonacci series up to n. """
...
a, b = 0, 1
...
while b < n:
...
print b,
...
a, b = b, a + b
...
>>>
>>> fib(2000)
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
>>>
pass
• The pass statement does nothing
• It can be used when a statement is required
syntactically, but the program requires no action
>>> def foo():
...
pass
...
>>>
Introducing Python
First steps towards programming
•
Defining functions
• def introduces a function definition
• Must be followed by function name and
parenthesized list of formal parameters
• The statements that form the function body start
on the next line and must be intended
• The first statement of the function can optionally
be a string literal, the docstring
Introducing Python
First steps towards programming
•
Defining functions
• A definition actually introduces only a symbolic
name
Introducing Python
First steps towards programming
•
Defining functions
• A function always returns a value
>>> print fib(0)
None
>>>
>>> fib
<function fib at 0x24c430>
>>> f = fib
>>> f(2000)
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
>>>
Introducing Python
First steps towards programming
•
Defining functions
• Fibonacci variant returning a list
Introducing Python
First steps towards programming
•
Defining functions
• Local and global function variables
>>> def fib2(n):
...
result = [] # Local variable to the function
...
a, b = 0, 1
...
while b < n:
...
result.append(b)
...
a, b = b, a + b
...
return result
...
>>> fib2(2000)
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377,
610, 987, 1597]
>>>
•
A function can also return multiple values!
>>>
>>>
>>>
...
...
...
>>>
5
>>>
10
>>>
•
i = 10
def f():
i = 5
print i
f()
print i
Variables are defined local to the function body
Introducing Python
First steps towards programming
•
Defining functions
• Local and global function variables
>>> def f():
...
print z
...
>>> f()
Traceback (most recent
File "<stdin>", line
File "<stdin>", line
NameError: global name
>>>
•
•
Function arguments
• Default values
>>> def example(a = 1, b = ‘Hello’, c = [])
Default values are evaluated only once, that is
at the point of definition, e.g.
>>>
...
...
...
>>>
[1]
>>>
[1,
>>>
[1,
def f(a, L=[]):
L.append(a)
return L
print f(1)
print f(2)
2]
print f(3)
2, 3]
Defining functions
• Local and global function variables
>>>
>>>
>>>
...
...
...
...
>>>
10
>>>
25
>>>
25
>>>
If the variable is not defined within the function, it
will be searched in global scope
First steps towards programming
•
First steps towards programming
call last):
1, in <module>
2, in f
'z' is not defined
Introducing Python
•
Introducing Python
x = 10
def f():
global x
x = 25
print x
# global fetches var from global scope
x
f()
x
Introducing Python
First steps towards programming
•
Function arguments
• You probably wanted this
>>>
...
...
...
...
...
>>>
[1]
>>>
[2]
>>>
[3]
>>>
def f(a, L=None):
if L is None:
L = []
L.append(a)
return L
print f(1)
print f(2)
print f(3)
Introducing Python
First steps towards programming
•
Function arguments
• Keyword arguments
Introducing Python
First steps towards programming
•
Function arguments
• Keyword arguments
def parrot(voltage, state='a stiff', action='voom'):
print "-- This parrot wouldn't", action,
print "if you put", voltage, "volts through it."
print "-- It's", state, "!"
•
Could be called in any of the following ways
parrot(1000)
parrot(action = 'VOOOOOM', voltage = 1000000)
parrot('a thousand', state = 'pushing up the daisies')
parrot('a million', 'bereft of life', 'jump')
Introducing Python
First steps towards programming
•
def parrot(voltage, state='a stiff', action='voom'):
print "-- This parrot wouldn't", action,
print "if you put", voltage, "volts through it."
print "-- It's", state, "!"
Function arguments
• Dictionary arguments
>>> def foo(a = 0, **myargs):
...
for k, v in myargs.iteritems():
...
print k, "=", v
...
>>> foo(name1='arg1', name2 = 20, anothername=[2,4,'a'])
anothername = [2, 4, 'a']
name2 = 20
name1 = arg1
>>>
•
But those would all be invalid
parrot()
parrot(voltage=5.0, 'dead')
parrot(110, voltage=220)
parrot(actor='John Cleese')
#
#
#
#
required argument missing
non-keyword argument following keyword
duplicate value for argument
unknown keyword
Introducing Python
First steps towards programming
•
Function arguments
• Arbitrary non-keyword arguments
>>> def foo2(*thearguments):
...
print thearguments
...
>>> foo2(22, 30, 'foo', (1,2))
(22, 30, 'foo', (1, 2))
>>>
•
•
Can be combined with **argument type, but *
must come first!
Of course, regular arguments can also be there,
but they must also precede * and ** forms!
Introducing Python
First steps towards programming
•
Function arguments
• Unpacking - another powerful feature
>>> def example(a, b, c):
...
print a, " ", b, " ", c
...
>>> list = [ 'Hello', 'VTK', 'class']
>>>
>>> example(*list)
Hello
VTK
class
>>>
Introducing Python
First steps towards programming
•
The docstring (won’t forget that... ;)
>>> def foo3():
...
""" This is a rather simple function. """
...
pass
...
>>> foo3()
>>> print foo3.__doc__
This is a rather simple function.
>>>
Introducing Python
First steps towards programming
•
Function arguments
• Unpacking - another powerful feature
>>> def example2(greeting, topic, towhom):
...
print greeting, topic, towhom
...
>>> dict = { "greeting":"Hello", "topic":"VTK", "towhom":"class" }
>>>
>>> example2(**dict)
Hello VTK class
>>>
Introducing Python
First steps towards programming
•
The docstring (won’t forget that... ;)
• Try it on an internal function
>>> print range.__doc__
range([start,] stop[, step]) -> list of integers
Return a list containing an arithmetic progression of
integers.
range(i, j) returns [i, i+1, i+2, ..., j-1]; start (!)
defaults to 0.
When step is given, it specifies the increment (or
decrement).
For example, range(4) returns [0, 1, 2, 3]. The end point
is omitted!
These are exactly the valid indices for a list of 4
elements.
>>>
Introducing Python
Modules
•
•
•
•
A module is a collection of Python statements
and functions
A modules filename is the modules name with
a .py appended
You can use existing modules by importing from
them
You can also create your own modules
• Just put your functions into a .py file use that by
importing
Introducing Python
Modules
•
Using a module is done by importing it
>>> cos (2.0)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'cos' is not defined
>>> import math
>>> math.cos(2.0)
-0.41614683654714241
>>> cos (2.0)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'cos' is not defined
•
import only includes the module namespace
Introducing Python
Modules
•
Examples of often used modules
• sys - python system functions
• os - operating system specific functions
• time - timing functions
• math - math functions
• vtk - VTK bindings
• tkinter - Tk bindings
•
And a whole lot of more (‘Batteries included’)
Introducing Python
Modules
•
To get rid of the module tag either import only a
single function or all (*) functions
>>> from math import cos
>>> cos(2.0)
-0.41614683654714241
>>> sin(2.0)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'sin' is not defined
>>> from math import *
>>> sin(2.0)
0.90929742682568171
>>>
Introducing Python
Modules
•
Listing the contents of a module
>>> import math
>>>
>>> dir(math)
['__doc__', '__file__', '__name__', 'acos', 'asin',
'atan', 'atan2', 'ceil', 'cos', 'cosh', 'degrees', 'e',
'exp', 'fabs', 'floor', 'fmod', 'frexp', 'hypot',
'ldexp', 'log', 'log10', 'modf', 'pi', 'pow',
'radians', 'sin', 'sinh', 'sqrt', 'tan', 'tanh']
>>>
•
Modules can contain sub-modules!