Intro to Reactive Programming and RxJava: How to React 😮😱🤪

Approach programming in a new way by using Reactive Programming, a functional style that focuses on the flow and manipulation of data. You already know how to think imperatively, using if-statements and state variables, from your experience programming in C. We will discuss the history of Imperative and Reactive programming and compare the different styles with concrete code examples in Java. By the end of this talk you will understand when to use reactive programming and how powerful and succinct it is for data problems.

Transcript

1. Intro to Reactive Programming and RxJava: How to React Jordan Jozwiak
2. Reactive Programming Allows us to manipulate a stream of data with functions.

3. Reactive Programming Allows us to manipulate a stream of data with functions.
 (asynchronously)
4. Reactive Programming
5. Reactive Programming 1. Data streams

6. Reactive Programming 1. Data streams
 2. Functional Programming

7. Reactive Programming 1. Data streams
 2. Functional Programming
 3. Asynchronous observers
8. applications ! Retrieving data from a database and then filtering out some results based on user settings.
9. applications ! Retrieving data from a database and then filtering out some results based on user settings. 2 3 7
10. applications ! Retrieving data from a database and then filtering out some results based on user settings. ⏳
11. applications ! Retrieving data from a database and then filtering out some results based on user settings. a, b, c -> a, c
12. applications ! Retrieve data from a database and then filtering out some results based on user settings. ! Render a UI that combines data from multiple data sources ! Create a real-time model for stock prices ! Show auto-complete search results to a user ! Log data from a temperature, wind, or pressure sensor
13. Who actually uses this?
14. Who actually uses this? ! Very popular in the Android community
15. Who actually uses this? ! Very popular in the Android community ! Some usage at Google for database requests
16. Who actually uses this? ! Very popular in the Android community ! Some usage at Google for database requests ! Microsoft, Netflix, GitHub, SoundCloud, and more (see reactivex.io)
17. Reactive Programming Theory
18. Reactive Programming Theory Implementation Reactive Extensions (reactivex.io) (libraries to make normal languages reactive)
19. Reactive Programming Theory Implementation Reactive Extensions (reactivex.io) (libraries to make normal languages reactive) RxJava RxSwift RxJS …
21. 4 2 1 7 6
22. 4 2 1 7 6 filter(x -> (x % 2) == 0)
23. 4 2 1 7 6 filter(x -> (x % 2) == 0)
24. 4 2 1 7 6 filter(x -> (x % 2) == 0) 4
25. 4 2 1 7 6 filter(x -> (x % 2) == 0) 4 2
26. 4 2 1 7 6 filter(x -> (x % 2) == 0) 4 2 6
27. 4 2 1 7 6 filter(x -> (x % 2) == 0) 4 2 6
28. 4 2 1 7 6 SUBJECT subject - the stream that emits data 4 2 6
29. 4 2 6 OBSERVER observer - “subscribes to” or “consumes” data. There can be multiple observers for a single subject. 4 2 1 7 6
30. 4 2 1 7 6 filter(x -> (x % 2) == 0) 4 2 6 SUBJECT OBSERVER
31. 4 2 1 7 6 filter(x -> (x % 2) == 0) 4 2 6 SUBJECT OBSERVER 4 2 6 SERVER 2
32. 4 2 1 7 6 filter / map / count / 
 max / min / delay / ... SUBJECT OBSERVER
33. 4 2 1 7 6 some function that takes ⏳ SUBJECT OBSERVER
34. 4 2 1 7 6 some function that takes ⏳ SUBJECT OBSERVER
35. a d z a h some function that takes ⏳ SUBJECT OBSERVER
36. some function that takes ⏳ SUBJECT OBSERVER
37. ? ? ? ? ? some function that takes ⏳ ? ? ? ? SUBJECT OBSERVER
38. some function that takes ⏳ SUBJECT OBSERVER another function
39. ? ? ? ? ? some function that takes ⏳ ? ? ? ? SUBJECT OBSERVER another function ? ? ? ? ?
40. What creates the subject data stream?
41. What creates the subject data stream? ! These streams are called Observables in RxJava
42. What creates the subject data stream? ! These streams are called Observables in RxJava ! Observable.create(), fromIterable(), etc.
43. What creates the subject data stream? ! These streams are called Observables in RxJava ! Observable.create(), fromIterable(), etc. ! Retrofitting existing object-oriented design into Observable data streams can be messy
44. What creates the subject data stream? ! These streams are called Observables in RxJava ! Observable.create(), fromIterable(), etc. ! Retrofitting existing object-oriented design into Observable data streams can be messy ! Many, many open-source projects that wrap other implementations into an Rx package (an easy way to get ⭐ ⭐ ⭐ on GitHub)
45. What creates the subject data stream? ! These streams are called Observables in RxJava ! Observable.create(), fromIterable(), etc. ! Retrofitting existing object-oriented design into Observable data streams can be messy ! Many, many open-source projects that wrap other implementations into an Rx package (an easy way to get ⭐ ⭐ ⭐ on GitHub) ! github.com/zsoltk/RxAndroidLibs - 500 stars for a list of libraries
46. introduction background examples live demo wrap-up
47. What languages are you familiar with?
48. ~80 % Percent of the most popular languages are imperative 
 or multi-paradigmatic languages Source: StackOverflow Developer Survey 2018
49. What's a language paradigm?
50. What's a language paradigm? ! Computer languages resemble linguistic language
51. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures
52. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future
53. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future ◦ Vocabulary
54. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future ◦ Vocabulary ◦ Dialects
55. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future ◦ Vocabulary ◦ Dialects ! Languages are multi-faceted and evolve over time. They are often multi- paradigmatic languages.
56. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future ◦ Vocabulary ◦ Dialects ! Languages are multi-faceted and evolve over time. They are often multi- paradigmatic languages. ! Examples
57. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future ◦ Vocabulary ◦ Dialects ! Languages are multi-faceted and evolve over time. They are often multi- paradigmatic languages. ! Examples ◦ Imperative (what you’re probably used to)
58. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future ◦ Vocabulary ◦ Dialects ! Languages are multi-faceted and evolve over time. They are often multi- paradigmatic languages. ! Examples ◦ Imperative (what you’re probably used to) ◦ Reactive Programming (what we’re talking about today)
59. What's a language paradigm? ! Computer languages resemble linguistic language ◦ Grammatical structures ◦ Tenses: past, present, future ◦ Vocabulary ◦ Dialects ! Languages are multi-faceted and evolve over time. They are often multi- paradigmatic languages. ! Examples ◦ Imperative (what you’re probably used to) ◦ Reactive Programming (what we’re talking about today) ◦ Functional Programming (used in Reactive Programming)
60. Imperative vs. Functional
61. Imperative vs. Functional Imperative Programming
62. Imperative vs. Functional Imperative Programming ! Describes how the program operates
63. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program
64. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance
65. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve
66. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java
67. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java if (value % 2 == 0) { // do something }
68. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java Functional Programming if (value % 2 == 0) { // do something }
69. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java Functional Programming ! Describes what the program should accomplish if (value % 2 == 0) { // do something }
70. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java Functional Programming ! Describes what the program should accomplish ! Ideally stateless if (value % 2 == 0) { // do something }
71. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java Functional Programming ! Describes what the program should accomplish ! Ideally stateless ! Evaluate functions and create expressions instead of statements if (value % 2 == 0) { // do something }
72. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java Functional Programming ! Describes what the program should accomplish ! Ideally stateless ! Evaluate functions and create expressions instead of statements ! More difficult conceptually if (value % 2 == 0) { // do something }
73. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java Functional Programming ! Describes what the program should accomplish ! Ideally stateless ! Evaluate functions and create expressions instead of statements ! More difficult conceptually ! Examples: Scala, Haskell if (value % 2 == 0) { // do something }
74. Imperative vs. Functional Imperative Programming ! Describes how the program operates ! Uses statements to change state of the program ! Conditional statements, loops, inheritance ! Easier initial learning curve ! Examples: C, PHP, Java Functional Programming ! Describes what the program should accomplish ! Ideally stateless ! Evaluate functions and create expressions instead of statements ! More difficult conceptually ! Examples: Scala, Haskell if (value % 2 == 0) { // do something } boolean filter(int value) { return value % 2 == 0; }
75. History of Imperative Programming ! Old computers utilized vacuum tubes and very limited memory ! Programs written as step-by-step instructions ! FORTRAN introduced in 1954. Compiled, variables, complex expressions. ! 60s and 70s: COBOL, BASIC, C ! Object-oriented code grew in popularity in the 1980s. Smalltalk. C++ ! 90s: Perl, Python, Javascript, Ruby, Java
76. History of Functional Programming ! Based on lambda calculus (Church 1936) ◦ Study of computation with functions ! Lisp was developed by IBM in the 1950s ◦ LISP = LISt Processor ◦ Still in use today ◦ Only a year younger than FORTRAN ! John Backus gave a 1978 Turing Award lecture on why imperative programming is “bad” and functional programming is “good” ! 80s-00s - Object-Oriented programming dominated based on principles like encapsulation. Academics and theoreticians care about Functional Programming. ! 2010s - JavaScript made passing around functions cool again
77. Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

78. Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

79. A flow of data objects from one function to the next Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

80. Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

81. ! Functions are meant to be pure Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

82. ! Functions are meant to be pure ! All functions have an input and output data types Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

83. ! Functions are meant to be pure ! All functions have an input and output data types ! No external state is modified (no side-effects) Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

84. ! Functions are meant to be pure ! All functions have an input and output data types ! No external state is modified (no side-effects) Example:
 add(x, y) -> return x + y Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

85. Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

86. Uses the Observer pattern with Subject data sources that notify Observers Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

87. Uses the Observer pattern with Subject data sources that notify Observers Errors propagated through the flow of data Reactive Programming
 1. Data streams
 
 2. Functional programming
 
 3. Asynchronous observers

88. Reactive Programming is NOT
89. Reactive Programming is NOT ! It's own language ! React, ReactJs, ReactNative
90. RxJava
91. RxJava ! The Java library for the Reactive Extensions specification ◦ This specification is applied to other languages: RxJs, RxSwift, etc. - reactivex.io/languages
92. RxJava ! The Java library for the Reactive Extensions specification ◦ This specification is applied to other languages: RxJs, RxSwift, etc. - reactivex.io/languages ! Helpful due to complicated stream and asynchronous apis
93. RxJava ! The Java library for the Reactive Extensions specification ◦ This specification is applied to other languages: RxJs, RxSwift, etc. - reactivex.io/languages ! Helpful due to complicated stream and asynchronous apis ! Brings functional design to an object-oriented language
94. RxJava ! The Java library for the Reactive Extensions specification ◦ This specification is applied to other languages: RxJs, RxSwift, etc. - reactivex.io/languages ! Helpful due to complicated stream and asynchronous apis ! Brings functional design to an object-oriented language ! Very helpful for mobile development, which often involves asynchronously requesting data from a server, transforming it, and displaying it in the UI
95. introduction background examples live demo wrap-up
96. ... to subscribe to data Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
97. ... to subscribe to data Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
98. ... to subscribe to data Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
99. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe(new Consumer<Integer>() { @Override public void accept(Integer value) { System.out.println(value); } }); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
100. ... to subscribe to data Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Reactive new DataSource().getDataStream() .subscribe(new Consumer<Integer>() { @Override public void accept(Integer value) { System.out.println(value); } }); Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
101. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe(new Consumer<Integer>() { @Override public void accept(Integer value) { System.out.println(value); } }); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
102. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe(new Consumer<Integer>() { @Override public void accept(Integer value) { System.out.println(value); } }); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
103. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe(new Consumer<Integer>() { @Override public void accept(Integer value) { System.out.println(value); } }); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
104. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe(new Consumer<Integer>() { @Override public void accept(Integer value) { System.out.println(value); } }); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
105. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe(
 value -> System.out.println(value)
 ); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
106. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe( value -> System.out.println(value) ); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { System.out.println(value); } Output: 4, 2, 1, 7, 6, ... Data: 4, 2, 1, 7, 6, ...
107. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe( value -> updateUI(value) ); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { updateUI(value); }
108. ... to subscribe to data Reactive new DataSource().getDataStream() .subscribe( value -> saveToDatabase(value) ); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { saveToDatabase(value); }
109. ... to subscribe to data changes
110. ... to subscribe to data changes Imperative ScheduledExecutorService scheduler = // initialize Runnable runner = new Runnable() { public void run() { List<Integer> data = new DataSource().getData(); for (Integer value : data) { System.out.println(value); } } }; ScheduledFuture<?> future = // initialize scheduler.schedule(new Runnable() { public void run() { future.cancel(/* mayInterruptIfRunning */ true); } }, /* delay */ 0, TimeUnit.SECONDS);
111. ... to subscribe to data changes Imperative ScheduledExecutorService scheduler = // initialize Runnable runner = new Runnable() { public void run() { List<Integer> data = new DataSource().getData(); for (Integer value : data) { System.out.println(value); } } }; ScheduledFuture<?> future = // initialize scheduler.schedule(new Runnable() { public void run() { future.cancel(/* mayInterruptIfRunning */ true); } }, /* delay */ 0, TimeUnit.SECONDS); ???
112. ... to subscribe to data changes Imperative ScheduledExecutorService scheduler = // initialize Runnable runner = new Runnable() { public void run() { List<Integer> data = new DataSource().getData(); for (Integer value : data) { System.out.println(value); } } }; ScheduledFuture<?> future = // initialize scheduler.schedule(new Runnable() { public void run() { future.cancel(/* mayInterruptIfRunning */ true); } }, /* delay */ 0, TimeUnit.SECONDS); Reactive new DataSource().getDataStream() .subscribe( value -> System.out.println(value) );
113. ... to filter our data
114. ... to filter our data Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { if (value % 2 == 0) { System.out.println(value); } } Output: 4, 2, 6, ... Data: 4, 2, 1, 7, 6, ...
115. ... to filter our data Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { if (value % 2 == 0) { System.out.println(value); } } Output: 4, 2, 6, ... Data: 4, 2, 1, 7, 6, ...
116. ... to filter our data http://reactivex.io/documentation/operators/filter
117. ... to filter our data Reactive new DataSource().getDataStream() .filter(value -> value % 2 == 0) .subscribe(
 result -> System.out.println(result)
 ); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { if (value % 2 == 0) { System.out.println(value); } } Output: 4, 2, 6, ... Data: 4, 2, 1, 7, 6, ...
118. ... to filter our data Reactive new DataSource().getDataStream() .filter(value -> value % 2 == 0) .subscribe(
 result -> System.out.println(result)
 ); Imperative List<Integer> data = 
 new DataSource().getData(); for (Integer value : data) { if (value % 2 == 0) { System.out.println(value); } } Output: 4, 2, 6, ... Data: 4, 2, 1, 7, 6, ...
119. … to map our data Output: 8, 4, 2, 14, 12, ... Data: 4, 2, 1, 7, 6, ...
120. … to map our data Imperative List<Integer> data = new DataSource().getData(); for (Integer value : data) { int result = value * 2; System.out.println(result); } Output: 8, 4, 2, 14, 12, ... Data: 4, 2, 1, 7, 6, ...
121. ... to map our data Imperative List<Integer> data = new DataSource().getData(); for (Integer value : data) { int result = value * 2; System.out.println(result); } Output: 8, 4, 2, 14, 12, ... Data: 4, 2, 1, 7, 6, ...
122. ... to map our data http://reactivex.io/documentation/operators/map
123. ... to map our data Reactive new DataSource().getDataStream() .map(value -> value * 2) .subscribe( result -> System.out.println(result) ); Imperative List<Integer> data = new DataSource().getData(); for (Integer value : data) { int result = value * 2; System.out.println(result); } Output: 8, 4, 2, 14, 12, ... Data: 4, 2, 1, 7, 6, ...
124. ... to map our data Reactive new DataSource().getDataStream() .map(value -> value * 2) .subscribe( result -> System.out.println(result) ); Imperative List<Integer> data = new DataSource().getData(); for (Integer value : data) { int result = value * 2; System.out.println(result); } Output: 8, 4, 2, 14, 12, ... Data: 4, 2, 1, 7, 6, ...
125. ... to group our data
126. ... to group our data List<Integer> data = new DataSource().getData(); Map<String, List<Integer>> result = new HashMap<>(); String evenKey = "EVEN"; String oddKey = "ODD"; for (Integer value : data) { String key; if (value % 2 == 0) { key = evenKey; } else { key = oddKey; } result.putIfAbsent( key, new ArrayList<>()); result.get(key).add(datum); } System.out.println(result); Output: {EVEN=[4, 2, 6], ODD=[1, 7]} Data: 4, 2, 1, 7, 6
127. ... to group our data http://reactivex.io/documentation/operators/groupby
128. ... to group our data new DataSource().getDataStream() .groupBy( value -> (value % 2) == 0 ? "EVEN" : "ODD" ) .collectInto( // put our groups into a hashmap // this is actually still a little messy ) .subscribe( resultMap -> System.out.println(resultMap) ); Output: {EVEN=[4, 2, 6], ODD=[1, 7]} Data: 4, 2, 1, 7, 6
129. ... to group our data new DataSource().getDataStream() .groupBy( value -> (value % 2) == 0 ? "EVEN" : "ODD" ) .collectInto( // put our groups into a hashmap // this is actually still a little messy ) .subscribe( resultMap -> System.out.println(resultMap) ); List<Integer> data = new DataSource().getData(); Map<String, List<Integer>> result = new HashMap<>(); String evenKey = "EVEN"; String oddKey = "ODD"; for (Integer value : data) { String key; if (value % 2 == 0) { key = evenKey; } else { key = oddKey; } result.putIfAbsent( key, new ArrayList<>()); result.get(key).add(datum); } System.out.println(result); Output: {EVEN=[4, 2, 6], ODD=[1, 7]} Data: 4, 2, 1, 7, 6
130. So many more operators ! Transforming ! Buffer ! Scan ! Filtering ! Debounce ! Distinct ! First ! Last ! Take ! Min ! Combining ! Join ! Merge ! Zip ! Math ! Average ! Concat ! Max
131. Some operations can get complicated http://reactivex.io/documentation/operators/join
132. introduction background examples live demo wrap-up
133. introduction background examples live demo wrap-up
134. Reactive Programming 1. Data streams
 2. Functional Programming
 3. Asynchronous observers
135. Thanks!