Python - Lecture 2 Fixed

8/9/2019 Python - Lecture 2 Fixed

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Python

67557Lecture 2

CS.HUJIFall 2014 -ה"תשע

Dr. Arie Schlesinger


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Containers of data

Motivation: keep data and processing

tools ‘close by’,

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Some classifications

• Simple objects, ףס נ ק ריפל םינתינ :ל

int, float, bool (non iterable)

• Containers of objects : (iterable)

str, list, tuple, range, set, frozenset, dict…

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Order• Sequences: ordered Containers

• A sequence is a container whose elements are ordered

and can be accessed by their position index, starting

from 0. Example, the 1st element in the string:

>>> s=‘abc’ >>> s[0]

‘a’

• Containers: strings, lists, tuples, range,..

• Not Sequences-unordered Containers

- Can not index their elements: sets, frozensets, dictionaries11/8/2014 10:37:29 PM 4


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Freedom

• Mutable: list, set, dictionary

- Contents can be changed :

- add , remove, change elements.

• Immutable: strings, tuples, frozenset, range

- No changes can be made

(Not containers: int, float, bool )

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l


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The two titles every containerholds

there are more

• Sequence, Mutable: list

• Sequence, Immutable: string, tuple, range

• Not sequence, Mutable : set, dictionary

• Not sequence, Immutable : frozenset

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What about the titles of thenon containers ?

• No Sequence, Immutable : int, float, bool

(no order, no freedom to change)

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sequences

strings, lists, tuples, range

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SequencesTuples

Contain 0 or more items of mixed types, including othercontainers – Immutable

Strings

Contain a seq of 0 or more single chars – Immutable

Lists

Contain a seq of 0 or more items of mixed types, includingother containers – Mutable

Ranges

Contain a seq of 0 or more ordered integers ! - immutable11/8/2014 10:37:29 PM 9


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Similar Syntax

•The three sequences types : tuples, strings, andlists, have similar syntax and functionality

Therefore most operations on all sequences, can be

demonstrated on one seq, to illustrate the others

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Sequences• Tuples : defined using parentheses, and commas.

>>> tup = (12, 'bcd', 3.45, (1,2), 'efg')

• Lists : defined using square brackets, and commas.

>>> liz = ["bcd", 23, 3.23, 12]

• Strings are defined using quotes (", ', or """).

>>> st = "abc"

>>> st = 'abc'

>>> st = """an exampleof a multi-line string that uses triple quotes."""

• Empty seq: [], (), ''

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Sequence indexing

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Indexing• You can access individual elements of a tuple, list, or string

using square bracket indexing notation, ( 0 based…)>>> tup = (12, ‘bcd’, 3.45, (1,2), ‘efg’)

>>> tup[1] # 2nd element in the tuple.

‘bcd’

>>> liz = [“bcd”, 23, 3.23, 12]

>>> liz[1] # 2nd element in the list.

23

>>> st = “bcd”

>>> st[1] # 2nd char in string.

‘c’

The index is an expression that evaluates to

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Positive and negative indices

>>> tup = (12, ‘bcd’, 3.45, (1,2), ‘efg’)

• Positive index: count from the left , starting with 0.

>>> tup[1]‘bcd’

• Negative index:count from right , starting with the lastelement, represented by index: -1

>>> tup[-3] # the 3rd from the end

3.4511/8/2014 10:37:29 PM 14


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Sequence slicing

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Slicing>>> tup = (12, ‘bcd’, 3.45, (1,2), ‘efg’)

>>> t[1:4]

(‘bcd’, 3.45, (1,2))

• Return a same-class-container, with a subset of the

original members.• It starts copying from the first index, and stops

copying before the second index.

• negative indices can be used :

>>> t[1:-1]

(‘bcd’, 3.45, (1,2))

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Slicing defaults

>>> tup = (12, ‘bcd’, 3.45, (1,2), ‘efg’)

• Without a first index, it starts from position 0:

>>> t[:2]

(12, ‘bcd’)

• Without the second index, it starts at the first index

until end of the container.

>>> t[2:](3.45, (1,2), ‘efg’)

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What indexing, and slicing return

Strings return strings:

Indexing: returns the one-char string at index pos.

Slicing : returns the substring specified (a new string)

Lists, tuples return:

Indexing: returns the element at index positionSlicing : returns a new seq as specified

(element can be simple or compound: int,string, list ,…)

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indexing slicing doc

http://docs.python.org/2/library/stdtypes.html#

sequence-types-list-tuple-range

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Copying the Whole Sequence• [:] makes a copy of an entire sequence.

>>> tup[:](12, ‘bcd’, 3.45, (1,2), ‘efg’)

>>> list1=[1,[2,3],4]• Two diff names of one seq:

>>> list2 = list1 # 2 names refer to 1 ref

# NEW: Changing one affects both Shallow copy : Two diff names of two diff seq

>>> list3 = list1[:]

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The ‘in’ Operator

•membership test , returns True or False :

>>> t = [1, 2, 4, 5]

>>> 3 in t

False>>> 4 in t

True

>>> 4 not in t

False

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Membership for strings• tests for substrings of 1 or more adjacent chars

>>> a = 'abcde'>>> 'c' in a

True

>>> 'cd' in a

True

>>> 'ac' in a

False

• Careful: the in keyword is also used in the syntax of for loopsand list comprehensions.11/8/2014 10:37:29 PM 22


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The + Operator• The + operator produces a new tuple, list, or

string whose value is the concatenation of itsarguments.

>>> (1, 2, 3) + (4, 5, 6)

(1, 2, 3, 4, 5, 6)>>> [1, 2, 3] + [4, 5, 6]

[1, 2, 3, 4, 5, 6]

>>> “The” + “ ” + “Beatles”

‘The Beatles’

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Mutability:

Tuples vs. Lists

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T l I t bl


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Tuples: Immutable

>>> tup = (12, ‘bcd’, 3.45, (1,2), ‘efg’)

>>> tup[2] = 2…TypeError: object doesn't support item assignment

You can’t change a tuple.

You can make a fresh tuple and assign its

reference to a previously used name.

>>> tup = (12, ‘bcd’, 2, (1,2), ‘efg’)

After the assignment, tup is now the name of the new

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Lists: Mutable• Lists are mutable: it is possible to change their

content (strings are immutable)

• Assign to a legal position:

>>> liz = [‘abc’, 12, 4.34, 23]

>>> liz[1] = 35 # assignment

>>> liz[‘abc’, 35, 4.34, 23]

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More examples

>>> myList

[1, 'a', -2.7]

>>> myList[0]='Iosi'

>>> myList

['Iosi', 'a', -2.7]

• We can change lists in place.

• myList is still the name of the same container

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Assignment to slices…1

• Assignment to slices can even change the size of

the list or clear it entirely:

>>> letters =['a’,'b’,'c’,'d’,'e’,'f’,'g']

# replace some values

>>> letters[2:5] = ['C', 'D', 'E']

>>> letters

['a', 'b', 'C', 'D', 'E', 'f', 'g']

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Assignment to slices…2# now remove them

>>> letters[2:5] = []>>> letters

['a', 'b', 'f', 'g']

# clear the list by replacing all the elements with anempty list

>>> letters[:] = []

>>> letters[]

([] is the ‘destroyer tool’)

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len() works with all sequences

>>> letters = ['a', 'b', 'c', 'd']

>>> len(letters)

4

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nesting lists


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nesting lists

• Create lists containing other lists:

>>> a = ['a', 'b', 'c']>>> n = [1, 2, 3]

>>> x = [a, n]

>>> x[['a', 'b', 'c'], [1, 2, 3]]

>>> x[0]

['a', 'b', 'c'] # list a>>> x[0][1]

'b'

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For your lists Only 1


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For your lists Only..1

>>> liz1 = [1, 1, 3, 4, 5]>>> liz1.append(‘x’) # a method of lists

>>> liz1

[1, 1, 3, 4, 5, ‘x’]

>>> liz1.insert(2, ‘y’)

>>>liz1 [1, 1, ‘y’, 3, 4, 5, ‘x’]

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The extend method vs the


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The extend method vs theoperator +

• + creates a fresh list (with a new memoryreference)

• extend operates on liz1 in place.

>>> liz1.extend([9, 8, 7])

>>> liz1

[1, 2, ‘i’, 3, 4, 5, ‘a’, 9, 8, 7]

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Append

>>> x = [1, 2, 3]

>>> x.append([4, 5])

>>> x # appends its arg packed as it comes

[1, 2, 3, [4, 5]]

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Extend

>>> x = [1, 2, 3]

>>> x.extend([4, 5])

>>> x # extend unpacks its arg

[1, 2, 3, 4, 5]

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For your lists Only ..2

>>> liz4 = [‘a’, ‘b’, ‘c’, ‘b’]

>>> liz4.index(‘b’)

1

>>> liz4.count(‘b’)

2

>>> liz4.remove(‘b’)

>>> liz4[‘a’, ‘c’, ‘b’]

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For your lists Only ..3>>> li = [5, 2, 6, 8]

>>> li.reverse() # reverse the list in place>>> li

[8, 6, 2, 5]

>>> li.sort() # sort the list in place

>>> li

[2, 5, 6, 8]

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Tuples vs. Lists

• Lists can be modified, and they have lots of

handy operations we can perform on them.

• Tuples are immutable and have fewer

features.

• To convert between tuples and lists use the

list() and tuple() functions:

>>> li = list(tu)>>> tu = tuple(li)

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M li t() t l ()


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More on list(),tuple() • list(iterable), tuple(iterable) are constructors that

decompose their arg and create a list/tuple from itselements:

>>> list('abc')

['a', 'b', 'c']

>>> list([1,2])

[1, 2]

>>> list((11,22))

[11, 22]

>>> list(12)

…TypeError: 'int' object is not iterable

(other types have similar constructors: set(), dict()…

which decompose some iterable and use its elems)


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The magic of tuples


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The Magic of Tuples

>>> a=(1,2)

>>> b=1,2 # a tuple without parens

>>> a

(1, 2)

>>> b

(1, 2)

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From Tuples Unpacking to Swap

>>> x,y=(1,2) # tuple unpacking>>> x

1

>>> y

2

>>> x,y=11,22 # also tuple unpacking

>>> x

11

>>> y

22

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Swap

>>> x,y=y,x # swap is a tuple unpacking !!>>> x

22

>>> y11

>>> x,y # just writing like that, creates a tuple(22,11)

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From Swap de luxe to .. Fibonacci

>>> a=0; b=1

>>> for i in range(5):

a, b = b, a+b

print b,

1 2 3 5 8

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The range() Function

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http://docs.python.org/3/library/stdtypes.html%23rangehttp://docs.python.org/3/library/stdtypes.html%23range


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range,xrange• The built-in function range([i,]j [,step])

creates an object that represents a range of integersk such that i


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‘Les Iterables’

Iterable: An object(container)

capable of returning its

members one at a time.

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Wh i it bl ?


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Who is iterable?

• all sequence types (like list, str, tuple, range)

• some non-sequence types like set,

frozenset, dict, file objects,

• Can be used in a for loop and in other places

where sequences are employed

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http://docs.python.org/3/library/stdtypes.html%23listhttp://docs.python.org/3/library/stdtypes.html%23strhttp://docs.python.org/3/library/stdtypes.html%23tuplehttp://docs.python.org/3/library/stdtypes.html%23dicthttp://docs.python.org/3/glossary.html%23term-file-objecthttp://docs.python.org/3/reference/compound_stmts.html%23forhttp://docs.python.org/3/reference/compound_stmts.html%23forhttp://docs.python.org/3/glossary.html%23term-file-objecthttp://docs.python.org/3/library/stdtypes.html%23dicthttp://docs.python.org/3/library/stdtypes.html%23tuplehttp://docs.python.org/3/library/stdtypes.html%23strhttp://docs.python.org/3/library/stdtypes.html%23list


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Iterators

• An iterator represents a stream of data

• the built-in function iter(),

- takes an iterable object as argument- returns an iterator for the object. ( 'של' )

• to get successive items in the stream.

- use the built-in function next()

- is good for one pass over the set of values.

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Iterator examples

http://docs.python.org/3/library/functions.html%23iterhttp://docs.python.org/3/library/functions.html%23nexthttp://docs.python.org/3/library/functions.html%23nexthttp://docs.python.org/3/library/functions.html%23iter


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Iterator examples>>> s='abc' # s is iterable

>>> its=iter(s) # iter(s) creates an iterator to s

>>> its.next() # next(its) returns the next item in s

'a'

>>> its.next()

'b'>>> its.next()

'c’

>>> its.next() # iterator is exausted - no more elements

…Error…StopIteration

To do it again repeat(refill) its=iter(…)

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References and Copies

About assignments


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About assignments

• Magic integers (יור ק ע ):-5

256 ..singletons)

>>> x=256

>>> y=256

>>> print id(x),id(y)

28190492 28190492


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Noיור ק ע for floats

>>> x=256.0

>>> y=256.0


36792004 36791924

nor for ints out of


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nor for ints out of[-5 …256]

>>> x=257

>>> y=257


11733080 28387720

Reference alias


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Reference, alias

• When a program makes an assignment suchas a = b, a new reference to b is created.

>>> b = 257

>>> a = b

>>> print id(a), id(b)

28387672 28387672

>>> a is b # are the ids equal ?True

>>> a==b # are the values equal ?

True


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What abo t fo st i gs?

http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413


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What aboutיור ק ע for strings?

>>> x='a'

>>> y='a'


20008472 20008472

>>> x='ojuwriuwrvpiurvpibpihv'

>>> y='ojuwriuwrvpiurvpibpihv'>>> print id(x),id(y)

32475184 32475184

A d h t b t li t t l

http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413http://moodle.cs.huji.ac.il/cs13/mod/forum/discuss.php?d=6413


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And what about lists, or tuples

>>> x=[1,2,3]

>>> y=[1,2,3]


32502248 32489384

>>> x=(1,2,3)

>>> y=(1,2,3)>>> print id(x),id(y)

32503248 32502368


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Mutable objects behaviour

• The behavior is different for mutable objects such as lists and

dictionaries. Example:

>>> a = [1,2,3,4]

>>> b = a # b is a reference to a

>>> b is a

True

>>> a == b

True

Changes in an ‘alias’ copy


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Changes in an alias copy

>>> b[2] = -100 # Change an element in b

>>> a # Notice how a also changed

[1, 2, -100, 4]

>>> b

[1, 2, -100, 4]

>>> a is b

True

>>> a==b

True

What about real copies


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What about real copies

•Here a and b refer to the same object, so a changemade to the obj thru one of the vars is seen thru theother.

We need copies that can be changed without changing

the original: not a new reference

shallow , deep copies


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shallow , deep copies• There are 2 diff types of copy operations for container

objects, such as lists and dictionaries: shallow copy,

deep copy.

• A shallow copy:

- creates a new object

- fills it with references to the items contained in the originalobject . Example:

>>> a = [ 1, 2, [3,4] ]

>>> b = list(a)

# Create a shallow copy of a.

>>> b is a

False

Shallow copies ‘merits’


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Shallow copies merits

>>> b.append(100) # Append element to b.

>>> b[1, 2, [3, 4], 100]

>>> a # Notice that a is unchanged[1, 2, [3, 4]]

>>> b[2][0] = -100 # Modify an element inside b

>>> b

[1, 2, [-100, 4], 100]

>>> a # Notice the change inside a

[1, 2, [-100, 4]]

How it works


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How it works

• In this case, a and b are separate list objects, but

the elements they contain are shared.

• Therefore, a modification to one of the elements

of a also modifies an element of b, as shown.

• A deep copy creates a new object and recursively

copies all the objects it contains.

• There is no built-in operation to create deep

copies of objects.

copy.deepcopy()


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copy deepcopy()

• The copy.deepcopy() function in copy module doesit, example:

>>> import copy

>>> a = [1, 2, [3, 4]]

>>> b = copy.deepcopy(a)

>>> print a is b, a==b # False, True

>>> b[2][0] = -100

>>> b

[1, 2, [-100, 4]]

>>> a

[1, 2, [3, 4]] # a is not changed(problems: when some element recursively points to itself)


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Three ways to shallow

• Each of the follows produces a shallow copy of

iterable x:

y=list(x)

y=x[:]

y=copy.copy(x)


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First class objects

First-Class Objects


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j

• All objects in Python are“first class”,

meaning that:

- all objects that can be named by an identifier,

have equal status.

- all objects that can be named, can be treated

as data.

First class Example


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pA simple dictionary with two values:

items = { 'number' : 42

'text' : "Hello World"}

Let’s add some ‘special’ items to this dictionary.

items["func"] = abs # Add the abs() functionimport math

items["mod"] = math # Add a module

items["error"] = ValueError # Add an exception type

nums = [1,2,3,4]

items["append"] = nums.append # Add a meth of another object

First class example


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First class example

• The items dictionary contains: a function, a module, an

exception, and a method of another object .

• Use the keys as the prev items, Example:

>>> items["func"](-5) # Executes abs(-5)

5

>>> items["mod"].sqrt(9) # Executes math.sqrt(9)

3.0

>>>try:

x = int("Iosi")

except items["error"] as e: # Same as except ValueError as e

print "Couldn't convert"

Couldn't convert

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First class Example cont.

>>> items["append"](‘Ety’)

>>> nums

[1, 2, 3, 4, ‘Ety’]

•Writing very compact code is possible because

everything in Python is first-class.

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Another First class example

• Given a line of text such as:

"Iosi, 1, 3.14, Malka"

let’s convert it into a list of elements with the right

type-conversion.

- create a list of types (which are first-class objects)

- execute a few simple list processing operations:

C


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Cont. >>> line = "Iosi, 1, 3.14, Malka"

>>> field_types = [str, int, float, str]

>>> raw_fields = line.split(',')

>>> fields = [ty(val) for ty,val in

zip(field_types,raw_fields)]

>>> fields

['Iosi', 1, 3.14, 'Malka']


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Aliasing function names

Did you know ?


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Did you know ?

You can bind a name to a ‘known respectable’

function, and use it instead :

>>> Iosi=len

>>> Iosi('abc')3

>>> Ety = type

>>> Ety(2)

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Write your functions


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y>>> def mySquare(x) : # function declaration

return x*x

>>> mySquare(7) # function call

49

>>> def mySquarePlusAnything(x,anything):

return x*x+mySquare(anything)

>>> mySquarePlusAnything(6,4) # function call

50

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elsei ng with the loops

In python

Loops (for,while)may havean else part

Else and the loops


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Else and the loops

• The else clause of a loop is executed only if :

- the loop ends naturally, or if

- the loop did not start/execute at all.

• If the loop is un-naturally terminated by a

break statement (or by some exception),

- the else clause is skipped.

Why: As a simple signal of what happened in the

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else example

while value < limit:

if value == x:

print "Found it!"

break

value+=y

else: # see the else indentationprint ”x it’s not there ! "

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Python - Lecture 2 Fixed