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Python Programming Tutorial-Page5

Refer following pages to learn complete Python language tutorial.
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List Processing

Working with lists is very common
Python is very adept at processing lists
Have already seen many examples:
>>> a = [1, 2, 3, 4, 5]
>>> sum(a)
15
>>> a[0:3]
[1, 2, 3]
>>> a * 2
[1, 2, 3, 4, 5, 1, 2, 3, 4, 5]
>>> min(a)
1
>>>

List Comprehensions


Creates a new list by applying an operation to each element of a sequence.
>>> a = [1,2,3,4,5]
>>> b = [2*x for x in a]
>>> b
[2,4,6,8,10]


A list comprehension can also filter
>>> a = [1, -5, 4, 2, -2, 10]
>>> b = [2*x for x in a if x > 0]
>>> b
[2,8,4,20]

General syntax


[expression for x in s if condition]
What it means
result = []
for x in s:
if condition:
result.append(expression)
Can be used anywhere a sequence is expected
>>> a = [1,2,3,4]
>>> sum([x*x for x in a])
30

List Comp: Examples


List comprehensions are hugely useful
Collecting the values of a specific field
stocknames = [s['name'] for s in stocks]
Performing database-like queries
a = [s for s in stocks if s['price'] > 100
and s['shares'] > 50 ]

Variable Assignment

Variables in Python are names for values
A variable name does not represent a fixed memory location into which values are stored (like C, C++, Fortran, etc.)
Assignment is just a naming operation

Variables and Values


At any time, a variable can be redefined to refer to a new value
a = 42
...
a = "Hello"
Variables are not restricted to one data type

Names, Values, Types


Names do not have a "type"--it's just a name
However, values do have an underlying type
>>> a = 42
>>> b = "Hello World"
>>> type(a)

>>> type(b)

type() function will tell you what it is
The type name is usually a function that creates or converts a value to that type

Reference Counting


Variable assignment never copies anything!
Instead, it just updates a reference count
a = 42
b = a
c = [1,2]
c.append(b)
So, different variables might be referring to the same object (check with the is operator)
>>> a is b
True

Reassignment never overwrites memory, so you normally don't notice any of the sharing
Instead, it just updates a reference count
a = 42
b = a

a = 37
When you reassign a variable, the name is just made to point to the new value.

"Copying" mutable objects such as lists and dicts is a hidden danger as explained below.

>>> a = [1,2,3,4]
>>> b = a
>>> b[2] = -10
>>> a
[1,2,-10,4]
Changes affect both variables!
Reason: Different variable names are referring to exactly the same object

Making a Copy


You have to take special steps to copy data
>>> a = [2,3,[100,101],4]
>>> b = list(a) # Make a copy
>>> a is b
False

Sometimes you need to makes a copy of an object and all objects contained within it
Use the copy module
>>> a = [2,3,[100,101],4]
>>> import copy
>>> b = copy.deepcopy(a)
>>> a[2].append(102)
>>> b[2]
[100,101]
>>>

Everything is an object


Numbers, strings, lists, functions, exceptions, classes, instances, etc...
All objects are said to be "first-class"
Meaning: All objects that can be named can be passed around as data, placed in containers, etc.,
without any restrictions.
There are no "special" kinds of objects

First Class Objects


A simple example:
>>> import math
>>> items = [abs, math, ValueError ]
>>> items
[,
,
]
>>> items[0](-45)
45

Type Checking


How to tell if an object is a specific type
if type(a) is list:
print "a is a list

if isinstance(a,list): # Preferred
print "a is a list"
Checking for one of many types
if isinstance(a,(list,tuple)):
print "a is a list or tuple"

               


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