1. COSC 1306—COMPUTER SCIENCE AND PROGRAMMING PYTHON LISTS Jehan-François Pâris jfparis@uh.edu

2. Introduction Lists are sequences of items –separated by commas –enclosed in square brackets ("[…]") Examples – [ 1, 2, 3,4,5] – ['Alice', 'Bob', 'Carol', Dean'] – ['Alice', 'freshman', [100, 90, 70]]

3. Usages Group together similar objects –Lists of people, courses, exams –Vectors and matrices of algebra and physics Store records –Contact list entry ['Bill', 713-555-1234, 'bill.tran@ xyx.com'] –Anything else

4. Operations Access the elements of a list –Individual elements –Slices Modify its elements Insert elements –Anywhere Remove elements

5. Lists >>> mylist = [11, 12, 13, 14, 'done'] >>> mylist [11, 12, 13, 14, 'done'] >>> print(mylist) [11, 12, 13, 14, 'done'] >>> mylist[0] 11 – We can access individual elements

6. List slices >>> mylist[0:1] [11] –Two observations A list slice is a list mylist[0:1] starts with list[0] but stops before mylist [1]

7. More list slices >>> mylist[0:2] [11, 12] –Includes mylist[0] and mylist[1] >>> mylist[0:] [11, 12, 13, 14, 'done'] – The whole list >>> mylist[1:] [12, 13, 14, 'done']

8. More list slices >>> mylist[-1:] ['done'] A list slice is a list >>> mylist[-1] 'done' Not the same thing!

9. An example a = [10, 20, 30, 40, 50] 1020503040 a designates the whole list a[4] a[1] a[2]a[0]a[3]

10. Lists in geometry (I) Consider a point A in the Cartesian plane –It has two coordinates x A and y A A xAxA yAyA

11. Lists in geometry (II) We will represent each point in the Cartesian plane by a list a with two elements such that – a[0] represents x A – a[1] represents y A Can now speak of the origin as point [0, 0]

12. Distance between two points The distance between two points A and B is the square root of –( A x – B x ) 2 + ( A y – B y ) 2 Pythagora's theorema

13. Why? xAxA yAyA A xBxB yByB B

14. Function computing this distance >>> def distance( a, b) : """ Cartesian distance between a and b ""“ import math return math.sqrt((a[0] - b[0])**2 + (a[1] - b[1])**2)

15. Function computing this distance >>> origin = [0, 0] >>> a = [1, 1] >>> distance(origin, a) 1.4142135623730951 >>>

16. Lists in physics (I) Speed, accelerations can be expressed by vectors In Cartesian plane force F has two components – F x and F y We will represent each force F by a list f with two elements such that – f[0] represents F x – f[1] represents F y

17. Lists in geometry (II) F FxFx FyFy θ

18. Absolute value of a force >>> def vecmodule(f) """ Module of a two-dimensional vector ""“ import math return math.sqrt(f[0]**2 + f[1]**2) >>> vecmodule([0,2]) 2.0 >>> vecmodule([3,4]) 5.0

19. Adding two vectors (I) [0, 2] + [0, 3] [0, 2, 0, 3] –Not what we want –+ operator concatenates lists

20. Adding two vectors (I) x y F G F+G GxGx FxFx GyGy FyFy

21. Adding two vectors (III) >>> def vecadd(f, g) : """ adds two two-dimensional vectors ""“ return [f[0] + g[0], f[1] + g[1]] >>> vecadd([0, 2], [0, 3]) [0, 5] – A function can return a list

22. Multiplying two vectors Which product? –Dot product returns a scalar –Cross product returns a vector –Applies to three-dimensional spaces

23. Dot product def dotproduct (f, g): “”” dot product of two two-dimensional vectors ""“ return f[0]*g[0] + f[1]*g[1] >>> dotproduct([1,0], [2, 2]) 2

24. List of lists (I) >>> a = [[1, 2], [3, 1]] >>> a [[1, 2], [3, 1]] >>> a[0] [1, 2] >>> a[1][1] 1

25. List of lists (II) Can be used to represent matrices () a 00 a 01 a 00 a01a01

26. Sorting lists >>> mylist = [11, 12, 13, 14, 'done'] >>> mylist.sort() Traceback (most recent call last): File " ", line 1, in mylist.sort() TypeError: unorderable types: str() < int() – Cannot compare apples and oranges

27. Sorting lists of strings >>> namelist = ['Alice', 'Carol', 'Bob'] >>> namelist.sort() >>> print(namelist) ['Alice', 'Bob', 'Carol'] namelist.sort() is a method applied to the list namelist – In-place sort

28. Sorting lists of numbers >>> newlist = [0, -1, +1, -2, +2] >>> newlist.sort() >>> print(newlist) [-2, -1, 0, 1, 2] In-place sort

29. Sorting into a new list >>> newlist = [0, -1, +1, -2, +2] >>> sortedlist= sorted(newlist) >>> print(newlist) [0, -1, 1, -2, 2] >>> print(sortedlist) [-2, -1, 0, 1, 2] –sorted(…) is a conventional Python function that returns a new list

30. Modifying the elements of a list >>> mylist = [11, 12, 13, 14, 'done'] >>> mylist[-1] = 'finished' >>> mylist [11, 12, 13, 14, 'finished'] >>> mylist[0:4] = ['XI', 'XII', 'XIII', 'XIV'] >>> mylist ['XI', 'XII', 'XIII', 'XIV', 'finished']

31. Lists of lists (I) >>> listoflists = [[17.5, "1306"], [13, "6360"]] >>> listoflists.sort() >>> print(listoflists) [[13, '6360'], [17.5, '1306']] >>> listoflists[0] [13, '6360'] >>> listoflists[1] [17.5, '1306']

32. Lists of lists (II) >>> listoflists[0][0] 13 >>> listoflists[1][1] '1306' >>> listoflists[0][1] ='6360 quiz' >>> listoflists [[13, '6360 quiz'], [17.5, '1306']]

33. Adding elements to a list >>> mylist = [11, 12, 13, 14, 'finished'] >>> mylist.append('Not yet!') >>> mylist [11, 12, 13, 14, 'finished', 'Not yet!']

34. Adding elements to a list (I) >>> mylist = [11, 12, 13, 14, 'finished'] >>> mylist.append('Not yet!') >>> mylist [11, 12, 13, 14, 'finished', 'Not yet!']

35. Adding elements to a list (II) >>> listoflists = [[13, '6360 quiz'], [17.5, '1306']] >>> listoflists.append([15.3, 'ABET']) >>> listoflists [[13, '6360 quiz'], [17.5, '1306'], [15.3, 'ABET']] Appending means adding at the end.

36. Adding elements inside a list (I) >>> mylist = [11, 12, 13, 14, 'finished'] >>> mylist.insert(0, 10) >>> mylist [10, 11, 12, 13, 14, 'finished'] >>> mylist.insert(5, 15) >>> mylist [10, 11, 12, 13, 14, 15, 'finished']

37. Adding elements inside a list (II) >>> mylist = [11, 12, 13, 14, 'finished'] >>> mylist.insert(0, 10) >>> mylist [10, 11, 12, 13, 14, 'finished'] >>> mylist.insert(5, 15) >>> mylist [10, 11, 12, 13, 14, 15, 'finished']

38. Adding elements inside a list (III) mylist.insert(index, item) – index specifies element before which the new item should be inserted mylist.insert(0, item) inserts the new item before the first element mylist.insert(1, item) inserts the new item before the second element and after the first one

39. Example (I) a = [10, 20, 30, 40, 50] 1020503040 a designates the whole list a[4]a[1]a[2] a[0] a[3]

40. Example (II) Where to insert 25 and keep the list sorted? 1020503040 a a[4]a[1]a[2] a[0] a[3]

41. Example (III) Where to insert 25 and keep the list sorted? 1020503040 a a[4]a[1]a[2] a[0] a[3] 25

42. Example (IV) We do – a.insert(2, 25) after a[1] and before a[2]

43. Let us check >>> a = [10, 20, 30, 40, 50] >>> a.insert(2,25) >>> a [10, 20, 25, 30, 40, 50]

44. Example (V) Where to insert 55 and keep the list sorted? 1020503040 a a[4]a[1]a[2] a[0] a[3]

45. Example (VI) Where to insert 55 and keep the list sorted? 1020503040 a a[4]a[1]a[2] a[0] a[3] 55

46. Example (VII) We must insert –After a[4] – Before no other element We act as if a[5] existed – a.insert(5, 55) It works! Same as a.append(55)

47. Let us check >>> a = [10, 20, 30, 40, 50] >>> a.insert(5, 55) >>> a [10, 20, 30, 40, 50, 55]

48. Let us make it a bit easier len(list) –returns the length of a list Same as number of its elements Equal to index of last element plus one We could have written – a.insert(len(a), 55) Same as a.append(55)

49. Removing items One by one thislist.pop(i) –removes thislist[i] from thislist –returns the removed element thislist.pop( ) –removes the last element from thislist –returns the removed element

50. Examples (I) >>> mylist = [11, 22, 33, 44, 55, 66] >>> mylist.pop(0) 11 >>> mylist [22, 33, 44, 55, 66]

51. Examples (II) >>> mylist.pop() 66 >>> mylist [22, 33, 44, 55] >>> mylist.pop(2) 44 >>> mylist [22, 33, 55]

52. Sum: one more useful function >>> list = [10, 20,20] >>> sum(list) 50 >>> list = ['Alice', ' and ', 'Bob'] >>> sum(list) –Does not work! Would get same results with tuples

53. Initializing lists Use list comprehensions >>> [ 0 for n in range(0, 9)] [0, 0, 0, 0, 0, 0, 0, 0, 0] >>> [n for n in range (1,11)] [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> [2*n+1 for n in range(0, 6)] [1, 3, 5, 7, 9, 11]

54. Warning! The for n clause is essential [0 in range(0, 10)] [True] – Because 0 is in range(0, 10)

55. More comprehensions >>> [ c for c in 'COSC 1306'] ['C', 'O', 'S', 'C', ' ', ‘1', '3', '0', '6'] >>> names = ['Alice', 'bob', 'carol'] >>> cap_names =[n.capitalize() for n in names] >>> names ['Alice', 'Bob', 'Carol'] >>> cap_names ['Alice', 'bob', 'carol']

56. An equivalence [2*n+1 for n in range(0, 6)] [1, 3, 5, 7, 9, 11] is same as a = [ ] for n in range(0,6) : a.append(2*n + 1)

57. Filtered comprehensions >>> a = [11, 22, 33, 44, 55] >>> b = [ n for n in a if n%2 == 0] >>> b [22, 44] >>> c = [n//11 for n in a if n > 20] >>> c [2, 3, 4, 5] A very powerful tool !

58. Making things more complicated >>> from random import uniform >>> >>> def gilligan(k):... return 4 * sum([1 for c in [uniform(0,1)**2+uniform(0,1)**2 for _ in range(k)] if c < 1]) / float(k)... >>> gilligan(100000) 3.13396 I did not write this code float(..) required by 2.7.2

59. Understanding the function (I) My friend used two comprehensions [uniform(0,1)**2+uniform(0,1)**2 for _ in range(k)] –creates a list containing k instances of uniform(0,1)**2+uniform(0,1)**2 – the underscore ('_') denotes the last evaluated expression

60. Understanding the function (II) [1 for c in […] if c < 1] –creates a list containing a 1 for each value in c such that c < 1 –each entry of the new list represents one dart that felt into the circle

61. Understanding the function (III) The last step is summing the contents of the outer list sum([1 for c in […] if c < 1]) –returns total number of darts each entry of the new list represents one dart that felt into the circle

62. Programming styles My friend's programming style favors conciseness over clarity I prefer clarity –Code should be so dumb that anyone could understand it without any effort Our definitions of clarity shift over time –What appears obscure to us today will appear trivial once we are familiar with the language

63. The for statement (I) for i in range(low, high): –Repeats high – low times –For all integer values of i between low and hi – 1 – low  i < hi

64. Example >>> for i in range(1, 5) : print ('Iteration %s' %i) Iteration 1 Iteration 2 Iteration 3 Iteration 4 5 is NOT in range(1, 5)

65. Observation If you want to execute a loop n times, use – for i in range(0,5) – for i in range (1, 6) – for i in range (2, 7) – …

66. The for statement (II) for i in a : –a must be a list –Repeats len(a) times –For all elements of a – for names in [‘Alice’, ‘Bob’, ‘Carol’]

67. Example (I) >>> names = ['Alice', 'Bob', 'Carol'] >>> for name in names : print('Hi ' + name + '!') Hi Alice! Hi Bob! Hi Carol! >>>

68. Example (II): better dot product def dotproduct(a, b) : if len(a) != len(b) : print("We must raise an exception!") return "Error" product = 0 for i in range(0, len(a)) product += a[i]*b[i] return product

69. Membership Can test membership in a list – a in alist returns True is a is in alist and False otherwise Will use it in if statements – if a in alist :

70. Example (I) >>> def ismember (a, list) : if a in alist : return '%s in %s' %(str(a), str(list)) else : return '%s NOT in %s' %(str(a), str(list))

71. Example (II) >>> ismember('Bob', ['Alice', 'Carol']) "Bob NOT in ['Alice', 'Carol']" >>> ismember('Alice', ['Alice', 'Carol']) "Alice in ['Alice', 'Carol']"

72. Copying/Saving a list >>> a = ["Alice", "Bob", "Carol"] >>> saved = a >>> a.pop(0) 'Alice' >>> a ['Bob', 'Carol'] >>> saved ['Bob', 'Carol'] We did not save anything!

73. Mutable and immutable quantities By default, Python quantities are immutable – Each time you modify them, you create a new value Expensive solution that works as we expect it

74. Mutable and immutable quantities Python lists are mutable – They can be modified in place – a = [1, 5, 3] can be sorted without making a new copy of the list Much cheaper solution – Can cause surprises!

75. How Python implements variables A Python variable contains the address of its current value a = 5 a 5

76. How Python implements variables A Python variable contains the address of its current value a = 5 b = a a 5 b

77. How Python implements variables A Python variable contains the address of its current value a = 5 b = a a = a +1 a 5 b 6

78. How Python implements variables This work as we expected –We saved the old value of a into be before modifying it People write – a = 5 # initial value – b = a # save initial value – a = a +1 # increment

79. A big surprise >>> a = [11, 33, 22] >>> b = a >>> b [11, 33, 22] >>> a.sort() >>> a [11, 22, 33] >>> b [11, 22, 33] The old value of a was not saved!

80. What happened (I) >>> a = [11, 33, 22] >>> b = a >>> b [11, 33, 22] a [11, 33, 22] b

81. What happened (II) >>> a = [11, 33, 22] >>> b = a >>> b [11, 33, 22] >>> a.sort() >>> a [11, 22, 33] >>> b [11, 22, 33] a [11,22, 33] b

82. Why this mess? Making lists immutable would have made Python much slower Conflict between ease of use and efficiency –This time efficiency won! Because efficiency penalty would have been very big

83. How to copy a list Copy a slice containing the whole list >>> a = [11, 33, 22] >>> b = a[0:len(a)] >>> a.sort() >>> a [11, 22, 33] >>> b [11, 33, 22] Silly but it works!