SlideShare a Scribd company logo
Introducing Scala
IQSS Tech-Talk, 2013-06-27
Michael Bar-Sinai
Sunday, 4 August, 13
Based in part on Scala for the impatient, Scala for
java programmers tutorial at Typesafe.com, and Prof.
Mayer Goldberg advanced programming class in
Ben-Gurion university of the Negev, Israel
Sunday, 4 August, 13
In a Few Bullets
Developed in 2001, by Martin Odersky, EPFL Professor
Runs on the JVM (also, CLR)
Statically typed and with concise syntax
Object oriented and functional
Clean and elegant design
Strong collection framework
Expression-only, DSL friendly, advanced features
Sunday, 4 August, 13
In a Few Bullets
Developed in 2001, by Martin Odersky, EPFL Professor
Runs on the JVM (also, CLR)
Statically typed and with concise syntax
Object oriented and functional
Clean and elegant design
Strong collection framework
Expression-only, DSL friendly, advanced features
Sunday, 4 August, 13
In a Few Bullets
Developed in 2001, by Martin Odersky, EPFL Professor
Runs on the JVM (also, CLR)
Statically typed and with concise syntax
Object oriented and functional
Clean and elegant design
Strong collection framework
Expression-only, DSL friendly, advanced features
Sunday, 4 August, 13
Sunday, 4 August, 13
What is a...
Computation?
Sunday, 4 August, 13
What is a computation?
PROCEDURAL
Finite automaton working on
an infinite tape
...0 1 110101110
Sunday, 4 August, 13
What is a computation?
PROCEDURAL FUNCTIONAL
Finite automaton working on
an infinite tape
...0 1 110101110
Data flowing through a
program
f(x) /2 R
f(6) 2 R
Sunday, 4 August, 13
REPL
SEE ACCOMPANYING FILES
Sunday, 4 August, 13
List Operations
Run some binary operator on the list items and an
intermediate results
fold, reduce, scan
Concurrent: aggregate,
reduce
ndlrowolleH
Sunday, 4 August, 13
List Operations
Run some binary operator on the list items and an
intermediate results
fold, reduce, scan
Concurrent: aggregate,
reduce
ndlrowolleH
Sunday, 4 August, 13
Expressions vs. Statements
STATEMENT
if ( map contains x ) {
map(x) = computeNewX(map(x))
} else {
map(x) = computeNewX( 0 )
}
Sunday, 4 August, 13
Expressions vs. Statements
STATEMENT
EXPRESSION
if ( map contains x ) {
map(x) = computeNewX(map(x))
} else {
map(x) = computeNewX( 0 )
}
map(x) = if ( map contains x )
computeNewX( map(x) )
else
computeNewX( 0 )
Sunday, 4 August, 13
Expressions vs. Statements
STATEMENT
EXPRESSION
if ( map contains x ) {
map(x) = computeNewX(map(x))
} else {
map(x) = computeNewX( 0 )
}
map(x) = if ( map contains x )
computeNewX( map(x) )
else
computeNewX( 0 )
ACTUAL SCALA CODE
map(x) = computeNewX( map.getOrElse(x,0) )
Sunday, 4 August, 13
Class Syntax
Classes have a primary constructor that is part of
the class definition
Clients can’t distinguish between getters and
direct field access
Better privacy control
Sunday, 4 August, 13
Classes
class Person( var name:String, val id:Int ) {
! def greet = "Hello, my name is %s".format(name)
}
class Person2( name:String, val id:Int ) {
! def greet = "Hello, my name is %s".format(name)
}
class Person3( name:String, val id:Int ) {
! val greet = "Hello, my name is %s".format(name)
}
Sunday, 4 August, 13
Classes (cont.)
class Person4( aName:String, anId:Int ) {
! private val id = anId
! private[this] var pName = aName
! def name = pName
! def name_=( newName:String ) { pName = newName }
! override def toString = "[Person4 id:%d name:%s]".format(id,name)
}
Sunday, 4 August, 13
Multiple Inheritance
Would have been nice if it worked
It doesn’t
Java allowed only multiple
inheritance of interfaces
JDK8 would update this, slightly
Scala simulates multiple inheritance
using type linearization
Would have been nice if it worked
...it mostly does
A
B1
B2
C
A
B1
B2
C
Sunday, 4 August, 13
Traits
Almost like class:
Can have fields, protocols and behavior
(implementations)
Can’t have constructor parameters
Can require minimal interface from
implementing classes
Class can extend as many as needed
Types are generated at declaration point
Sunday, 4 August, 13
Objects
and the absence of static
Replace the static parts in java
Manual declaration of a runtime singletons
Classes can have “companion objects” that have
the same name
Good place for utility methods or special “apply”
methods
App trait allows script-like behavior
Sunday, 4 August, 13
Pattern Matching
Control structure that allows
switching
type inquiry
variable de-composition
Specialized Classes optimized for this
Sunday, 4 August, 13
Simple Pattern Matching
def toFuzzyStringInt( i:Int ) = i match {
! case 0 => "Nada"
! case 1 => "One"
! case 2 => "A Pair"
! case 12 => "a dozen"
! case _ if i<0 => "Less that zero"
! case _ => "%,d".format(i)
}
Sunday, 4 August, 13
Switch by Type
def prettyPrint( a:Any ) = a match {
! case i:Int => "%,d".format(i)
! case s:String => "[%s]".format(s)
! case sym:Symbol => ":%s".format(sym)
! case _ => a.toString
}
Sunday, 4 August, 13
Decomposition
First, meet the case class:
Regular class, but with immutable declared fields,
toString, equals and hashCode automatically
defined
sealed abstract class Tree
case class Sum( l:Tree, r:Tree ) extends Tree
case class Var( n:String ) extends Tree
case class Con( v:Int ) extends Tree
Sunday, 4 August, 13
Decomposition
def evalTree( t:Tree, e:Map[String,Int] ): Int =
t match {
! case Sum(l,r) => evalTree(l, e) + evalTree(r,e)
! case Var( n ) => e(n)
! case Con( i ) => i
}
Allows downcasting, accessing sub-classes fields and
varying actions based on the class of the parameter, in a
single syntactical maneuver
Sunday, 4 August, 13
... In the real world
(merged,original) match {
case ( Pass(_), ( _, _) ) => true
case ( Unfixable(_), ( _, _) ) => false
case ( Fixable(_,t,_), (t1,t2) ) => f.ld<ld(t1)+ld(t2)
}
Given two strings, we need to decide whether it is more likely that they are
two separate words or one broken word
Sunday, 4 August, 13
... In the real world
(merged,original) match {
case ( Pass(_), ( _, _) ) => true
case ( Unfixable(_), ( _, _) ) => false
case ( Fixable(_,t,_), (t1,t2) ) => f.ld<ld(t1)+ld(t2)
}
ere are two ways of constructing a software design: One way is to make it so
simple that there are obviously no deficiencies, and the other way is to make it
so complicated that there are no obvious deficiencies. e first method is far
more difficult.
-- C. A. R. Hoare, Turing Award lecture, 1980
Given two strings, we need to decide whether it is more likely that they are
two separate words or one broken word
Sunday, 4 August, 13
Option[T]
And the death of the NullPointerException
Indicates possibly missing values
Has two implementations: None and Some(t)
“Collection of at most one item”
Convention more than a language feature
Sunday, 4 August, 13
Functions as values
Creating new functions from existing ones
Powerful tool, but can get messy
Allows for DSL creation
def bind1( f:(Int,Int)=>Int, v:Int ) =
(a:Int)=>f(a,v)
Sunday, 4 August, 13
Not Covered
Creation of DSLs
Implicit conversions
Continuations
Frameworks
XML
Parsers/Combinators
Macros
Annotations
Genericity
Type System
Actors
Regular Expressions
Extractors
... many more
Sunday, 4 August, 13
Pointers
www.scala-lang.org
Typesafe.com
Scala for the Impatient, by Cay Horstmann (http://
horstmann.com/scala/)
First chapters available after registering with at Typesafe’s site
(google)
Sunday, 4 August, 13
Introducing Scala
IQSS Tech-Talk, 2013-06-27
Michael Bar-Sinai
THANKS
Sunday, 4 August, 13

More Related Content

What's hot

Babar: Knowledge Recognition, Extraction and Representation
Babar: Knowledge Recognition, Extraction and RepresentationBabar: Knowledge Recognition, Extraction and Representation
Babar: Knowledge Recognition, Extraction and Representation
Pierre de Lacaze
 
Erlang session1
Erlang session1Erlang session1
Erlang session1
mohamedsamyali
 
Category Theory in 10 Minutes
Category Theory in 10 MinutesCategory Theory in 10 Minutes
Category Theory in 10 Minutes
Jordan Parmer
 
Data Types - Premetive and Non Premetive
Data Types - Premetive and Non Premetive Data Types - Premetive and Non Premetive
Data Types - Premetive and Non Premetive
Raj Naik
 
Python - Regular Expressions
Python - Regular ExpressionsPython - Regular Expressions
Python - Regular Expressions
Mukesh Tekwani
 
Java Generics Introduction - Syntax Advantages and Pitfalls
Java Generics Introduction - Syntax Advantages and PitfallsJava Generics Introduction - Syntax Advantages and Pitfalls
Java Generics Introduction - Syntax Advantages and Pitfalls
Rakesh Waghela
 
Introduction to Category Theory for software engineers
Introduction to Category Theory for software engineersIntroduction to Category Theory for software engineers
Introduction to Category Theory for software engineers
Pranav Prakash
 
Category theory for beginners
Category theory for beginnersCategory theory for beginners
Category theory for beginners
kenbot
 
Preparation Data Structures 03 abstract data_types
Preparation Data Structures 03 abstract data_typesPreparation Data Structures 03 abstract data_types
Preparation Data Structures 03 abstract data_types
Andres Mendez-Vazquez
 
C# programming
C# programming C# programming
C# programming
umesh patil
 
Introduction to Data Structure : Pointer
Introduction to Data Structure : PointerIntroduction to Data Structure : Pointer
Introduction to Data Structure : Pointer
S P Sajjan
 
Arrays
ArraysArrays
prolog ppt
prolog pptprolog ppt
prolog ppt
sachin varun
 
What can scala puzzlers teach us
What can scala puzzlers teach usWhat can scala puzzlers teach us
What can scala puzzlers teach us
Daniel Sobral
 
Breaking down data silos with the open data protocol
Breaking down data silos with the open data protocolBreaking down data silos with the open data protocol
Breaking down data silos with the open data protocolWoodruff Solutions LLC
 
On Parameterised Types and Java Generics
On Parameterised Types and Java GenericsOn Parameterised Types and Java Generics
On Parameterised Types and Java Generics
Yann-Gaël Guéhéneuc
 
E6
E6E6
E6
lksoo
 
L04 Software Design 2
L04 Software Design 2L04 Software Design 2
L04 Software Design 2
Ólafur Andri Ragnarsson
 
Java Generics
Java GenericsJava Generics
Java Generics
jeslie
 

What's hot (20)

Algo>Abstract data type
Algo>Abstract data typeAlgo>Abstract data type
Algo>Abstract data type
 
Babar: Knowledge Recognition, Extraction and Representation
Babar: Knowledge Recognition, Extraction and RepresentationBabar: Knowledge Recognition, Extraction and Representation
Babar: Knowledge Recognition, Extraction and Representation
 
Erlang session1
Erlang session1Erlang session1
Erlang session1
 
Category Theory in 10 Minutes
Category Theory in 10 MinutesCategory Theory in 10 Minutes
Category Theory in 10 Minutes
 
Data Types - Premetive and Non Premetive
Data Types - Premetive and Non Premetive Data Types - Premetive and Non Premetive
Data Types - Premetive and Non Premetive
 
Python - Regular Expressions
Python - Regular ExpressionsPython - Regular Expressions
Python - Regular Expressions
 
Java Generics Introduction - Syntax Advantages and Pitfalls
Java Generics Introduction - Syntax Advantages and PitfallsJava Generics Introduction - Syntax Advantages and Pitfalls
Java Generics Introduction - Syntax Advantages and Pitfalls
 
Introduction to Category Theory for software engineers
Introduction to Category Theory for software engineersIntroduction to Category Theory for software engineers
Introduction to Category Theory for software engineers
 
Category theory for beginners
Category theory for beginnersCategory theory for beginners
Category theory for beginners
 
Preparation Data Structures 03 abstract data_types
Preparation Data Structures 03 abstract data_typesPreparation Data Structures 03 abstract data_types
Preparation Data Structures 03 abstract data_types
 
C# programming
C# programming C# programming
C# programming
 
Introduction to Data Structure : Pointer
Introduction to Data Structure : PointerIntroduction to Data Structure : Pointer
Introduction to Data Structure : Pointer
 
Arrays
ArraysArrays
Arrays
 
prolog ppt
prolog pptprolog ppt
prolog ppt
 
What can scala puzzlers teach us
What can scala puzzlers teach usWhat can scala puzzlers teach us
What can scala puzzlers teach us
 
Breaking down data silos with the open data protocol
Breaking down data silos with the open data protocolBreaking down data silos with the open data protocol
Breaking down data silos with the open data protocol
 
On Parameterised Types and Java Generics
On Parameterised Types and Java GenericsOn Parameterised Types and Java Generics
On Parameterised Types and Java Generics
 
E6
E6E6
E6
 
L04 Software Design 2
L04 Software Design 2L04 Software Design 2
L04 Software Design 2
 
Java Generics
Java GenericsJava Generics
Java Generics
 

Similar to Invitation to Scala

R language
R languageR language
R language
LearningTech
 
Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009
Martin Odersky
 
The Scala Programming Language
The Scala Programming LanguageThe Scala Programming Language
The Scala Programming Language
league
 
Scala - en bedre og mere effektiv Java?
Scala - en bedre og mere effektiv Java?Scala - en bedre og mere effektiv Java?
Scala - en bedre og mere effektiv Java?
Jesper Kamstrup Linnet
 
Scala introduction
Scala introductionScala introduction
Scala introduction
Yardena Meymann
 
Introduction to Scala for JCConf Taiwan
Introduction to Scala for JCConf TaiwanIntroduction to Scala for JCConf Taiwan
Introduction to Scala for JCConf Taiwan
Jimin Hsieh
 
Lambda? You Keep Using that Letter
Lambda? You Keep Using that LetterLambda? You Keep Using that Letter
Lambda? You Keep Using that Letter
Kevlin Henney
 
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот
Омские ИТ-субботники
 
Stepping Up : A Brief Intro to Scala
Stepping Up : A Brief Intro to ScalaStepping Up : A Brief Intro to Scala
Stepping Up : A Brief Intro to Scala
Derek Chen-Becker
 
Programming in Scala - Lecture Three
Programming in Scala - Lecture ThreeProgramming in Scala - Lecture Three
Programming in Scala - Lecture Three
Angelo Corsaro
 
Ajax and JavaScript Bootcamp
Ajax and JavaScript BootcampAjax and JavaScript Bootcamp
Ajax and JavaScript Bootcamp
AndreCharland
 
Data structures cs301 power point slides lecture 01
Data structures   cs301 power point slides lecture 01Data structures   cs301 power point slides lecture 01
Data structures cs301 power point slides lecture 01
shaziabibi5
 
A Brief Introduction to Scala for Java Developers
A Brief Introduction to Scala for Java DevelopersA Brief Introduction to Scala for Java Developers
A Brief Introduction to Scala for Java Developers
Miles Sabin
 
Miles Sabin Introduction To Scala For Java Developers
Miles Sabin Introduction To Scala For Java DevelopersMiles Sabin Introduction To Scala For Java Developers
Miles Sabin Introduction To Scala For Java DevelopersSkills Matter
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 
Programming in Scala: Notes
Programming in Scala: NotesProgramming in Scala: Notes
Programming in Scala: Notes
Roberto Casadei
 

Similar to Invitation to Scala (20)

R language
R languageR language
R language
 
Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009
 
The Scala Programming Language
The Scala Programming LanguageThe Scala Programming Language
The Scala Programming Language
 
Scala - en bedre og mere effektiv Java?
Scala - en bedre og mere effektiv Java?Scala - en bedre og mere effektiv Java?
Scala - en bedre og mere effektiv Java?
 
Scala introduction
Scala introductionScala introduction
Scala introduction
 
Introduction to Scala for JCConf Taiwan
Introduction to Scala for JCConf TaiwanIntroduction to Scala for JCConf Taiwan
Introduction to Scala for JCConf Taiwan
 
Effective Scala @ Jfokus
Effective Scala @ JfokusEffective Scala @ Jfokus
Effective Scala @ Jfokus
 
Lambda? You Keep Using that Letter
Lambda? You Keep Using that LetterLambda? You Keep Using that Letter
Lambda? You Keep Using that Letter
 
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборот
 
Stepping Up : A Brief Intro to Scala
Stepping Up : A Brief Intro to ScalaStepping Up : A Brief Intro to Scala
Stepping Up : A Brief Intro to Scala
 
Programming in Scala - Lecture Three
Programming in Scala - Lecture ThreeProgramming in Scala - Lecture Three
Programming in Scala - Lecture Three
 
Ajax and JavaScript Bootcamp
Ajax and JavaScript BootcampAjax and JavaScript Bootcamp
Ajax and JavaScript Bootcamp
 
Data structures cs301 power point slides lecture 01
Data structures   cs301 power point slides lecture 01Data structures   cs301 power point slides lecture 01
Data structures cs301 power point slides lecture 01
 
A Brief Introduction to Scala for Java Developers
A Brief Introduction to Scala for Java DevelopersA Brief Introduction to Scala for Java Developers
A Brief Introduction to Scala for Java Developers
 
Miles Sabin Introduction To Scala For Java Developers
Miles Sabin Introduction To Scala For Java DevelopersMiles Sabin Introduction To Scala For Java Developers
Miles Sabin Introduction To Scala For Java Developers
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 
Programming in Scala: Notes
Programming in Scala: NotesProgramming in Scala: Notes
Programming in Scala: Notes
 

More from Michael Bar-Sinai

BPjs deep dive 2019
BPjs deep dive 2019BPjs deep dive 2019
BPjs deep dive 2019
Michael Bar-Sinai
 
BPjs for IoT class
BPjs for IoT classBPjs for IoT class
BPjs for IoT class
Michael Bar-Sinai
 
Deep Dive into BPjs
Deep Dive into BPjsDeep Dive into BPjs
Deep Dive into BPjs
Michael Bar-Sinai
 
Sharing Sensitive Data With Confidence: The DataTags system
Sharing Sensitive Data With Confidence: The DataTags systemSharing Sensitive Data With Confidence: The DataTags system
Sharing Sensitive Data With Confidence: The DataTags system
Michael Bar-Sinai
 
DataTags, The Tags Toolset, and Dataverse Integration
DataTags, The Tags Toolset, and Dataverse IntegrationDataTags, The Tags Toolset, and Dataverse Integration
DataTags, The Tags Toolset, and Dataverse Integration
Michael Bar-Sinai
 
Draw More, Work Less
Draw More, Work LessDraw More, Work Less
Draw More, Work Less
Michael Bar-Sinai
 

More from Michael Bar-Sinai (6)

BPjs deep dive 2019
BPjs deep dive 2019BPjs deep dive 2019
BPjs deep dive 2019
 
BPjs for IoT class
BPjs for IoT classBPjs for IoT class
BPjs for IoT class
 
Deep Dive into BPjs
Deep Dive into BPjsDeep Dive into BPjs
Deep Dive into BPjs
 
Sharing Sensitive Data With Confidence: The DataTags system
Sharing Sensitive Data With Confidence: The DataTags systemSharing Sensitive Data With Confidence: The DataTags system
Sharing Sensitive Data With Confidence: The DataTags system
 
DataTags, The Tags Toolset, and Dataverse Integration
DataTags, The Tags Toolset, and Dataverse IntegrationDataTags, The Tags Toolset, and Dataverse Integration
DataTags, The Tags Toolset, and Dataverse Integration
 
Draw More, Work Less
Draw More, Work LessDraw More, Work Less
Draw More, Work Less
 

Recently uploaded

From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
Product School
 
Elevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object CalisthenicsElevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object Calisthenics
Dorra BARTAGUIZ
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
DianaGray10
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Tobias Schneck
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
RTTS
 
Leading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdfLeading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdf
OnBoard
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Albert Hoitingh
 
Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*
Frank van Harmelen
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
BookNet Canada
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
Guy Korland
 
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMsTo Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
Paul Groth
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
Product School
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and back
Elena Simperl
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Jeffrey Haguewood
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
KatiaHIMEUR1
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
Jemma Hussein Allen
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Prayukth K V
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
Safe Software
 

Recently uploaded (20)

From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
 
Elevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object CalisthenicsElevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object Calisthenics
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
 
Leading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdfLeading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdf
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
 
Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
 
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMsTo Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and back
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
 

Invitation to Scala

  • 1. Introducing Scala IQSS Tech-Talk, 2013-06-27 Michael Bar-Sinai Sunday, 4 August, 13
  • 2. Based in part on Scala for the impatient, Scala for java programmers tutorial at Typesafe.com, and Prof. Mayer Goldberg advanced programming class in Ben-Gurion university of the Negev, Israel Sunday, 4 August, 13
  • 3. In a Few Bullets Developed in 2001, by Martin Odersky, EPFL Professor Runs on the JVM (also, CLR) Statically typed and with concise syntax Object oriented and functional Clean and elegant design Strong collection framework Expression-only, DSL friendly, advanced features Sunday, 4 August, 13
  • 4. In a Few Bullets Developed in 2001, by Martin Odersky, EPFL Professor Runs on the JVM (also, CLR) Statically typed and with concise syntax Object oriented and functional Clean and elegant design Strong collection framework Expression-only, DSL friendly, advanced features Sunday, 4 August, 13
  • 5. In a Few Bullets Developed in 2001, by Martin Odersky, EPFL Professor Runs on the JVM (also, CLR) Statically typed and with concise syntax Object oriented and functional Clean and elegant design Strong collection framework Expression-only, DSL friendly, advanced features Sunday, 4 August, 13
  • 8. What is a computation? PROCEDURAL Finite automaton working on an infinite tape ...0 1 110101110 Sunday, 4 August, 13
  • 9. What is a computation? PROCEDURAL FUNCTIONAL Finite automaton working on an infinite tape ...0 1 110101110 Data flowing through a program f(x) /2 R f(6) 2 R Sunday, 4 August, 13
  • 11. List Operations Run some binary operator on the list items and an intermediate results fold, reduce, scan Concurrent: aggregate, reduce ndlrowolleH Sunday, 4 August, 13
  • 12. List Operations Run some binary operator on the list items and an intermediate results fold, reduce, scan Concurrent: aggregate, reduce ndlrowolleH Sunday, 4 August, 13
  • 13. Expressions vs. Statements STATEMENT if ( map contains x ) { map(x) = computeNewX(map(x)) } else { map(x) = computeNewX( 0 ) } Sunday, 4 August, 13
  • 14. Expressions vs. Statements STATEMENT EXPRESSION if ( map contains x ) { map(x) = computeNewX(map(x)) } else { map(x) = computeNewX( 0 ) } map(x) = if ( map contains x ) computeNewX( map(x) ) else computeNewX( 0 ) Sunday, 4 August, 13
  • 15. Expressions vs. Statements STATEMENT EXPRESSION if ( map contains x ) { map(x) = computeNewX(map(x)) } else { map(x) = computeNewX( 0 ) } map(x) = if ( map contains x ) computeNewX( map(x) ) else computeNewX( 0 ) ACTUAL SCALA CODE map(x) = computeNewX( map.getOrElse(x,0) ) Sunday, 4 August, 13
  • 16. Class Syntax Classes have a primary constructor that is part of the class definition Clients can’t distinguish between getters and direct field access Better privacy control Sunday, 4 August, 13
  • 17. Classes class Person( var name:String, val id:Int ) { ! def greet = "Hello, my name is %s".format(name) } class Person2( name:String, val id:Int ) { ! def greet = "Hello, my name is %s".format(name) } class Person3( name:String, val id:Int ) { ! val greet = "Hello, my name is %s".format(name) } Sunday, 4 August, 13
  • 18. Classes (cont.) class Person4( aName:String, anId:Int ) { ! private val id = anId ! private[this] var pName = aName ! def name = pName ! def name_=( newName:String ) { pName = newName } ! override def toString = "[Person4 id:%d name:%s]".format(id,name) } Sunday, 4 August, 13
  • 19. Multiple Inheritance Would have been nice if it worked It doesn’t Java allowed only multiple inheritance of interfaces JDK8 would update this, slightly Scala simulates multiple inheritance using type linearization Would have been nice if it worked ...it mostly does A B1 B2 C A B1 B2 C Sunday, 4 August, 13
  • 20. Traits Almost like class: Can have fields, protocols and behavior (implementations) Can’t have constructor parameters Can require minimal interface from implementing classes Class can extend as many as needed Types are generated at declaration point Sunday, 4 August, 13
  • 21. Objects and the absence of static Replace the static parts in java Manual declaration of a runtime singletons Classes can have “companion objects” that have the same name Good place for utility methods or special “apply” methods App trait allows script-like behavior Sunday, 4 August, 13
  • 22. Pattern Matching Control structure that allows switching type inquiry variable de-composition Specialized Classes optimized for this Sunday, 4 August, 13
  • 23. Simple Pattern Matching def toFuzzyStringInt( i:Int ) = i match { ! case 0 => "Nada" ! case 1 => "One" ! case 2 => "A Pair" ! case 12 => "a dozen" ! case _ if i<0 => "Less that zero" ! case _ => "%,d".format(i) } Sunday, 4 August, 13
  • 24. Switch by Type def prettyPrint( a:Any ) = a match { ! case i:Int => "%,d".format(i) ! case s:String => "[%s]".format(s) ! case sym:Symbol => ":%s".format(sym) ! case _ => a.toString } Sunday, 4 August, 13
  • 25. Decomposition First, meet the case class: Regular class, but with immutable declared fields, toString, equals and hashCode automatically defined sealed abstract class Tree case class Sum( l:Tree, r:Tree ) extends Tree case class Var( n:String ) extends Tree case class Con( v:Int ) extends Tree Sunday, 4 August, 13
  • 26. Decomposition def evalTree( t:Tree, e:Map[String,Int] ): Int = t match { ! case Sum(l,r) => evalTree(l, e) + evalTree(r,e) ! case Var( n ) => e(n) ! case Con( i ) => i } Allows downcasting, accessing sub-classes fields and varying actions based on the class of the parameter, in a single syntactical maneuver Sunday, 4 August, 13
  • 27. ... In the real world (merged,original) match { case ( Pass(_), ( _, _) ) => true case ( Unfixable(_), ( _, _) ) => false case ( Fixable(_,t,_), (t1,t2) ) => f.ld<ld(t1)+ld(t2) } Given two strings, we need to decide whether it is more likely that they are two separate words or one broken word Sunday, 4 August, 13
  • 28. ... In the real world (merged,original) match { case ( Pass(_), ( _, _) ) => true case ( Unfixable(_), ( _, _) ) => false case ( Fixable(_,t,_), (t1,t2) ) => f.ld<ld(t1)+ld(t2) } ere are two ways of constructing a software design: One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies. e first method is far more difficult. -- C. A. R. Hoare, Turing Award lecture, 1980 Given two strings, we need to decide whether it is more likely that they are two separate words or one broken word Sunday, 4 August, 13
  • 29. Option[T] And the death of the NullPointerException Indicates possibly missing values Has two implementations: None and Some(t) “Collection of at most one item” Convention more than a language feature Sunday, 4 August, 13
  • 30. Functions as values Creating new functions from existing ones Powerful tool, but can get messy Allows for DSL creation def bind1( f:(Int,Int)=>Int, v:Int ) = (a:Int)=>f(a,v) Sunday, 4 August, 13
  • 31. Not Covered Creation of DSLs Implicit conversions Continuations Frameworks XML Parsers/Combinators Macros Annotations Genericity Type System Actors Regular Expressions Extractors ... many more Sunday, 4 August, 13
  • 32. Pointers www.scala-lang.org Typesafe.com Scala for the Impatient, by Cay Horstmann (http:// horstmann.com/scala/) First chapters available after registering with at Typesafe’s site (google) Sunday, 4 August, 13
  • 33. Introducing Scala IQSS Tech-Talk, 2013-06-27 Michael Bar-Sinai THANKS Sunday, 4 August, 13