1. LET’S TALK ABOUT
ruby

2. Ian Bishop
@ianbishop

3. Ruby is

4. Ruby is
simple in appearance,

5. Ruby is
simple in appearance,
but is very complex inside,

6. Ruby is
simple in appearance,
but is very complex inside,
just like our human body

7. Ruby is
simple in appearance,
but is very complex inside,
just like our human body
- Yukihiro “matz” Matsumoto

8. philosophy

9. principle of
least surprise

10. principle of least surprise
array.length
string.length()
collection.size()

11. principle of least surprise
array.length
string.length()
collection.size()
array.length
string.length
collection.length

12. features

13. everything is an object
5.times do
print “Everyone loves ruby!”
end

14. everything is an object
5.times

15. everything is a message
/abc/ === “abc” “abc” === /abc/
=> true => false

16. everything is a message
/abc/ === “abc”
=> true

17. everything is a message
/abc/
/abc/

18. everything is a message
/abc/
/abc/.send

19. everything is a message
/abc/ ===
/abc/.send(:===

20. everything is a message
/abc/ === “abc”
/abc/.send(:===, “abc”)

21. everything is a message
/abc/ === “abc”
=> true
/abc/.send(:===, “abc”)
=> true

22. everything is a message
/abc/ === “abc” “abc” === /abc/
=> true => false

23. everything is a message
case “HELLO”
when /^[a-z]*$/
“lowercase”
when /^[A-Z]*$/
“uppercase”
end
=> “uppercase”

24. everything is a message
case “HELLO”
when “hello”
“lowercase”
when “HELLO”
“uppercase”
end
=> “uppercase”

25. everything is a message
/abc/ === “abc” “abc” === /abc/
=> true => false

26. dynamic runtime
a = [1,2,3]
a.first
=> 1
a.second
NoMethodError: Undefined method
‘second’ for [1, 2, 3]:Array

27. dynamic runtime
class Array
def second
if self.length > 1
return self[1]
end
nil
end
end

28. dynamic runtime
a = [1,2,3]
a.first
=> 1
a.second

29. dynamic runtime
a = [1,2,3]
a.first
=> 1
a.second
=> 2

31. DEALING WITH
data

34. using collections
a = [1,2,3]

35. using collections
a = [1,2,3,“meow”]

36. using collections
a.each do |x|
puts x
end
1
2
3
meow

37. using collections
a.each

38. using collections
a.each do |x|
end

39. using collections
a.each do |x|
puts x
end

40. using collections
a.each do |x|
puts x
end
1
2
3
meow

41. .each
Iterate over elements in a collection

42. .map
Iterate over elements in a collection,
returning a new collection of
elements of the same size

43. using map
a = [1,2,3]

44. using map
a = [1,2,3]
a.map

45. using map
a = [1,2,3]
a.map do |x|
end

46. using map
a = [1,2,3]
a.map do |x|
2 * x
end

47. using map
a = [1,2,3]
a.map do |x|
return 2 * x
end

48. using map
a = [1,2,3]
a.map do |x|
2 * x
end

49. using map
a = [1,2,3]
a.map do |x|
2 * x
end
=> [2,4,6]

50. .map
Iterate over elements in a collection,
returning a new collection of
elements of the same size

51. .select
Iterate over elements in a collection,
returning elements which match a
specified criteria

52. using select
a = [1,2,3]

53. using select
a = [1,2,3]
a.select

54. using select
a = [1,2,3]
a.select do |x|
end

55. using select
a = [1,2,3]
a.select do |x|
x.odd?
end

56. using select
a = [1,2,3]
a.select do |x|
x.odd?
end
=> [1,3]

57. .select
Iterate over elements in a collection,
returning elements which match a
specified criteria

58. .reduce
Combines all elements in a collection
using a binary operation, returning
an accumulator value.

59. using reduce
a = [1,2,3]

60. using reduce
a = (1..100)

61. using reduce
a = (1..100)
a.reduce

62. using reduce
a = (1..100)
a.reduce do |sum, x|
end

63. using reduce
a = (1..100)
a.reduce do |sum, x|
sum + x
end

64. using reduce
a = (1..100)
a.reduce do |sum, x|
sum + x
end
=> 5050

65. .reduce
Combines all elements in a collection
using a binary operation, returning
an accumulator value.

66. .reduce
Combines all elements in a collection
using a binary operation, returning
an accumulator value.

67. using reduce (again)
a = (1..100)
a.reduce

68. using reduce (again)
a = (1..100)
a.reduce(:*)

69. using reduce (again)
a = (1..100)
a.reduce(:*)
=>9332621544394415268169923885626670049
071596826438162146859296389521759999322
991560894146397615651828625369792082722
37582511852109168640000000000000…

70. SOLVING
HARDER
PROBLEMS

71. generating poker hands

72. building a deck of cards
suits = %w(S C H D)

73. building a deck of cards
suits = %w(S C H D)
=> [“S”, “C”, “H”, “D”]

74. building a deck of cards
suits = %w(S C H D)
=> [“S”, “C”, “H”, “D”]
“S C H D”.split /s+/
=> [“S”, “C”, “H”, “D”]

75. building a deck of cards
suits = %w(S C H D)
faces =

76. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a

77. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)

78. [1, 2, 3]
[“a”, “b”, “c”]

79. [1, 2, 3]
x
[“a”, “b”, “c”]

80. cross product
[1, “a”], [1, “b”], [1, “c”],
[2, “a”], [2, “b”], [2, “c”],
[3, “a”], [3, “b”], [3, “c”]

81. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces)

82. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces)
=> [[“S”, 2], [“S”, 3], …, [“S”, “A”],
[“C”, 1], …, [“C”, “A”], …]

83. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces)
=> [“S2”, “S3”, …, “SA”, “C1”, …, “C2”,
…]

84. join(sep=$,) -> str
Returns a string created by converting each element
of the array to a string, seperated by sep.
[ “a”, “b”, “c”].join
=> “abc”
[ “a”, “b”, “c”].join(“-”)
=> “a-b-c”

85. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces)
deck = deck.map do |pair|
pair.join
end

86. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces)
deck.map! do |pair|
pair.join
end

87. building a deck of cards
.map!

88. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces)
deck.map! do |pair|
pair.join
end

89. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces)
deck.map! { |pair| pair.join }

90. building a deck of cards
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces).map(&:join)

91. generating poker hands
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces).map(&:join)

92. sample(n) -> new_ary
Choose n random elements from the array.
The elements are chosen by using random
and unique indices in order to ensure that an
element doesn’t repeat itself unless the array
already contained duplicate elements.

93. generating poker hands
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces).map(&:join)
deck.sample(5)

94. generating poker hands
suits = %w(S C H D)
faces = (2..10).to_a + %w(J Q K A)
deck = suits.product(faces).map(&:join)
deck.sample(5)
=> [“C2”, “D5”, “S7”, “D8”, “C8”]

95. LET’S TALK ABOUT
MAP REDUCE

96. LET’S TALK ABOUT
©
MAP REDUCE

97. Count of URL Access Frequency
The map function processes logs of web page
requests and outputs <URL, 1>. The reduce
function adds together all values for the same
URL and emits a <URL, total count> pair.
from Introduction to Parallel Programming and MapReduce (Google)

98. counting url access frequency
log

99. counting url access frequency
log
=> [“example.com”, “google.com”,
“userevents.com”, “unb.ca”,
“frederictonug.net”, ..]

100. Count of URL Access Frequency
The map function processes logs of web page
requests and outputs <URL, 1>. The reduce
function adds together all values for the same
URL and emits a <URL, total count> pair.
from Introduction to Parallel Programming and MapReduce (Google)

101. generate count pairs
count_pairs = log.map do |url|
[url, 1]
end

102. Count of URL Access Frequency
The map function processes logs of web page
requests and outputs <URL, 1>. The reduce
function adds together all values for the same URL
and emits a <URL, total count> pair.
from Introduction to Parallel Programming and MapReduce (Google)

103. BUT FIRST

104. Collection of key-value
pairs.
Similar to an array, except
indexing is done via unique
keys.

105. brief introduction to hashes
my_hash = { :abc => 5, “def” => 9 }

106. brief introduction to hashes
my_hash = { :abc => 5, “def” => 9 }
my_hash[:abc]

107. brief introduction to hashes
my_hash = { :abc => 5, “def” => 9 }
my_hash[:abc]
=> 5

108. brief introduction to hashes
my_hash = { :abc => 5, “def” => 9 }
my_hash[:abc]
=> 5
my_hash[“def”] = 14

109. brief introduction to hashes
my_hash = { :abc => 5, “def” => 9 }
my_hash[:abc]
=> 5
my_hash[“def”] = 14
=> { :abc => 5, “def” => 14 }

110. Count of URL Access Frequency
The map function processes logs of web page
requests and outputs <URL, 1>. The reduce
function adds together all values for the same URL
and emits a <URL, total count> pair.
from Introduction to Parallel Programming and MapReduce (Google)

111. combining count pairs
count_pairs.reduce

112. combining count pairs
count_pairs.reduce({})

113. combining count pairs
count_pairs.reduce({}) do |hash, pair|
end

114. combining count pairs
count_pairs.reduce({}) do |hash, pair|
url, count = pair
end

115. combining count pairs
count_pairs.reduce({}) do |hash, pair|
url, count = pair
if hash.has_key? url
hash[url] += count
end

116. combining count pairs
count_pairs.reduce({}) do |hash, pair|
url, count = pair
if hash.has_key? url
hash[url] += count
else
hash[url] = count
end
end

117. combining count pairs
count_pairs.reduce({}) do |hash, pair|
url, count = pair
if hash.has_key? url
hash[url] += count
else
hash[url] = count
end
hash
end

118. counting url access frequency
log = [“example.com”, “google.com”,
“example.com”, “unb.ca”]

119. counting url access frequency
log = [“example.com”, “google.com”,
“example.com”, “unb.ca”]
=> { “example.com” => 2,
“google.com” => 1,
“unb.ca” => 1 }