Let's Talk About Ruby

An introductory talk given about Ruby for the Fredericton Developers User Group on October 24th, 2012.

Transcript

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” => true “abc” === /abc/ => 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” => true “abc” === /abc/ => 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” => true “abc” === /abc/ => 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. [1, “a”], [1, “b”], [1, “c”], [2, “a”], [2, “b”], [2, “c”], [3, “a”], [3, “b”], [3, “c”] cross product
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 }