Parametric and Logical Types for Model-Driven Engineering
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Typescript Language Specification
TypeScript Language Specification Version 1.8 January, 2016 Microsoft is making this Specification available under the Open Web Foundation Final Specification Agreement Version 1.0 ("OWF 1.0") as of October 1, 2012. The OWF 1.0 is available at http://www.openwebfoundation.org/legal/the-owf-1-0-agreements/owfa-1-0. TypeScript is a trademark of Microsoft Corporation. Table of Contents 1 Introduction ................................................................................................................................................................................... 1 1.1 Ambient Declarations ..................................................................................................................................................... 3 1.2 Function Types .................................................................................................................................................................. 3 1.3 Object Types ...................................................................................................................................................................... 4 1.4 Structural Subtyping ....................................................................................................................................................... 6 1.5 Contextual Typing ............................................................................................................................................................ 7 1.6 Classes ................................................................................................................................................................................. -
A System of Constructor Classes: Overloading and Implicit Higher-Order Polymorphism
A system of constructor classes: overloading and implicit higher-order polymorphism Mark P. Jones Yale University, Department of Computer Science, P.O. Box 2158 Yale Station, New Haven, CT 06520-2158. [email protected] Abstract range of other data types, as illustrated by the following examples: This paper describes a flexible type system which combines overloading and higher-order polymorphism in an implicitly data Tree a = Leaf a | Tree a :ˆ: Tree a typed language using a system of constructor classes – a mapTree :: (a → b) → (Tree a → Tree b) natural generalization of type classes in Haskell. mapTree f (Leaf x) = Leaf (f x) We present a wide range of examples which demonstrate mapTree f (l :ˆ: r) = mapTree f l :ˆ: mapTree f r the usefulness of such a system. In particular, we show how data Opt a = Just a | Nothing constructor classes can be used to support the use of monads mapOpt :: (a → b) → (Opt a → Opt b) in a functional language. mapOpt f (Just x) = Just (f x) The underlying type system permits higher-order polymor- mapOpt f Nothing = Nothing phism but retains many of many of the attractive features that have made the use of Hindley/Milner type systems so Each of these functions has a similar type to that of the popular. In particular, there is an effective algorithm which original map and also satisfies the functor laws given above. can be used to calculate principal types without the need for With this in mind, it seems a shame that we have to use explicit type or kind annotations. -
Design and Implementation of Generics for the .NET Common Language Runtime
Design and Implementation of Generics for the .NET Common Language Runtime Andrew Kennedy Don Syme Microsoft Research, Cambridge, U.K. fakeÒÒ¸d×ÝÑeg@ÑicÖÓ×ÓfغcÓÑ Abstract cally through an interface definition language, or IDL) that is nec- essary for language interoperation. The Microsoft .NET Common Language Runtime provides a This paper describes the design and implementation of support shared type system, intermediate language and dynamic execution for parametric polymorphism in the CLR. In its initial release, the environment for the implementation and inter-operation of multiple CLR has no support for polymorphism, an omission shared by the source languages. In this paper we extend it with direct support for JVM. Of course, it is always possible to “compile away” polymor- parametric polymorphism (also known as generics), describing the phism by translation, as has been demonstrated in a number of ex- design through examples written in an extended version of the C# tensions to Java [14, 4, 6, 13, 2, 16] that require no change to the programming language, and explaining aspects of implementation JVM, and in compilers for polymorphic languages that target the by reference to a prototype extension to the runtime. JVM or CLR (MLj [3], Haskell, Eiffel, Mercury). However, such Our design is very expressive, supporting parameterized types, systems inevitably suffer drawbacks of some kind, whether through polymorphic static, instance and virtual methods, “F-bounded” source language restrictions (disallowing primitive type instanti- type parameters, instantiation at pointer and value types, polymor- ations to enable a simple erasure-based translation, as in GJ and phic recursion, and exact run-time types. -
Python Programming
Python Programming Wikibooks.org June 22, 2012 On the 28th of April 2012 the contents of the English as well as German Wikibooks and Wikipedia projects were licensed under Creative Commons Attribution-ShareAlike 3.0 Unported license. An URI to this license is given in the list of figures on page 149. If this document is a derived work from the contents of one of these projects and the content was still licensed by the project under this license at the time of derivation this document has to be licensed under the same, a similar or a compatible license, as stated in section 4b of the license. The list of contributors is included in chapter Contributors on page 143. The licenses GPL, LGPL and GFDL are included in chapter Licenses on page 153, since this book and/or parts of it may or may not be licensed under one or more of these licenses, and thus require inclusion of these licenses. The licenses of the figures are given in the list of figures on page 149. This PDF was generated by the LATEX typesetting software. The LATEX source code is included as an attachment (source.7z.txt) in this PDF file. To extract the source from the PDF file, we recommend the use of http://www.pdflabs.com/tools/pdftk-the-pdf-toolkit/ utility or clicking the paper clip attachment symbol on the lower left of your PDF Viewer, selecting Save Attachment. After extracting it from the PDF file you have to rename it to source.7z. To uncompress the resulting archive we recommend the use of http://www.7-zip.org/. -
Refinement Types for ML
Refinement Types for ML Tim Freeman Frank Pfenning [email protected] [email protected] School of Computer Science School of Computer Science Carnegie Mellon University Carnegie Mellon University Pittsburgh, Pennsylvania 15213-3890 Pittsburgh, Pennsylvania 15213-3890 Abstract tended to the full Standard ML language. To see the opportunity to improve ML’s type system, We describe a refinement of ML’s type system allow- consider the following function which returns the last ing the specification of recursively defined subtypes of cons cell in a list: user-defined datatypes. The resulting system of refine- ment types preserves desirable properties of ML such as datatype α list = nil | cons of α * α list decidability of type inference, while at the same time fun lastcons (last as cons(hd,nil)) = last allowing more errors to be detected at compile-time. | lastcons (cons(hd,tl)) = lastcons tl The type system combines abstract interpretation with We know that this function will be undefined when ideas from the intersection type discipline, but remains called on an empty list, so we would like to obtain a closely tied to ML in that refinement types are given type error at compile-time when lastcons is called with only to programs which are already well-typed in ML. an argument of nil. Using refinement types this can be achieved, thus preventing runtime errors which could be 1 Introduction caught at compile-time. Similarly, we would like to be able to write code such as Standard ML [MTH90] is a practical programming lan- case lastcons y of guage with higher-order functions, polymorphic types, cons(x,nil) => print x and a well-developed module system. -
Parametric Polymorphism Parametric Polymorphism
Parametric Polymorphism Parametric Polymorphism • is a way to make a language more expressive, while still maintaining full static type-safety (every Haskell expression has a type, and types are all checked at compile-time; programs with type errors will not even compile) • using parametric polymorphism, a function or a data type can be written generically so that it can handle values identically without depending on their type • such functions and data types are called generic functions and generic datatypes Polymorphism in Haskell • Two kinds of polymorphism in Haskell – parametric and ad hoc (coming later!) • Both kinds involve type variables, standing for arbitrary types. • Easy to spot because they start with lower case letters • Usually we just use one letter on its own, e.g. a, b, c • When we use a polymorphic function we will usually do so at a specific type, called an instance. The process is called instantiation. Identity function Consider the identity function: id x = x Prelude> :t id id :: a -> a It does not do anything with the input other than returning it, therefore it places no constraints on the input's type. Prelude> :t id id :: a -> a Prelude> id 3 3 Prelude> id "hello" "hello" Prelude> id 'c' 'c' Polymorphic datatypes • The identity function is the simplest possible polymorphic function but not very interesting • Most useful polymorphic functions involve polymorphic types • Notation – write the name(s) of the type variable(s) used to the left of the = symbol Maybe data Maybe a = Nothing | Just a • a is the type variable • When we instantiate a to something, e.g. -
CSE 307: Principles of Programming Languages Classes and Inheritance
OOP Introduction Type & Subtype Inheritance Overloading and Overriding CSE 307: Principles of Programming Languages Classes and Inheritance R. Sekar 1 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Topics 1. OOP Introduction 3. Inheritance 2. Type & Subtype 4. Overloading and Overriding 2 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Section 1 OOP Introduction 3 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding OOP (Object Oriented Programming) So far the languages that we encountered treat data and computation separately. In OOP, the data and computation are combined into an “object”. 4 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Benefits of OOP more convenient: collects related information together, rather than distributing it. Example: C++ iostream class collects all I/O related operations together into one central place. Contrast with C I/O library, which consists of many distinct functions such as getchar, printf, scanf, sscanf, etc. centralizes and regulates access to data. If there is an error that corrupts object data, we need to look for the error only within its class Contrast with C programs, where access/modification code is distributed throughout the program 5 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Benefits of OOP (Continued) Promotes reuse. by separating interface from implementation. We can replace the implementation of an object without changing client code. Contrast with C, where the implementation of a data structure such as a linked list is integrated into the client code by permitting extension of new objects via inheritance. Inheritance allows a new class to reuse the features of an existing class. -
INF 102 CONCEPTS of PROG. LANGS Type Systems
INF 102 CONCEPTS OF PROG. LANGS Type Systems Instructors: James Jones Copyright © Instructors. What is a Data Type? • A type is a collection of computational entities that share some common property • Programming languages are designed to help programmers organize computational constructs and use them correctly. Many programming languages organize data and computations into collections called types. • Some examples of types are: o the type Int of integers o the type (Int→Int) of functions from integers to integers Why do we need them? • Consider “untyped” universes: • Bit string in computer memory • λ-expressions in λ calculus • Sets in set theory • “untyped” = there’s only 1 type • Types arise naturally to categorize objects according to patterns of use • E.g. all integer numbers have same set of applicable operations Use of Types • Identifying and preventing meaningless errors in the program o Compile-time checking o Run-time checking • Program Organization and documentation o Separate types for separate concepts o Indicates intended use declared identifiers • Supports Optimization o Short integers require fewer bits o Access record component by known offset Type Errors • A type error occurs when a computational entity, such as a function or a data value, is used in a manner that is inconsistent with the concept it represents • Languages represent values as sequences of bits. A "type error" occurs when a bit sequence written for one type is used as a bit sequence for another type • A simple example can be assigning a string to an integer -
Lecture Slides
Outline Meta-Classes Guy Wiener Introduction AOP Classes Generation 1 Introduction Meta-Classes in Python Logging 2 Meta-Classes in Python Delegation Meta-Classes vs. Traditional OOP 3 Meta-Classes vs. Traditional OOP Outline Meta-Classes Guy Wiener Introduction AOP Classes Generation 1 Introduction Meta-Classes in Python Logging 2 Meta-Classes in Python Delegation Meta-Classes vs. Traditional OOP 3 Meta-Classes vs. Traditional OOP What is Meta-Programming? Meta-Classes Definition Guy Wiener Meta-Program A program that: Introduction AOP Classes One of its inputs is a program Generation (possibly itself) Meta-Classes in Python Its output is a program Logging Delegation Meta-Classes vs. Traditional OOP Meta-Programs Nowadays Meta-Classes Guy Wiener Introduction AOP Classes Generation Compilers Meta-Classes in Python Code Generators Logging Delegation Model-Driven Development Meta-Classes vs. Traditional Templates OOP Syntactic macros (Lisp-like) Meta-Classes The Problem With Static Programming Meta-Classes Guy Wiener Introduction AOP Classes Generation Meta-Classes How to share features between classes and class hierarchies? in Python Logging Share static attributes Delegation Meta-Classes Force classes to adhere to the same protocol vs. Traditional OOP Share code between similar methods Meta-Classes Meta-Classes Guy Wiener Introduction AOP Classes Definition Generation Meta-Classes in Python Meta-Class A class that creates classes Logging Delegation Objects that are instances of the same class Meta-Classes share the same behavior vs. Traditional OOP Classes that are instances of the same meta-class share the same behavior Meta-Classes Meta-Classes Guy Wiener Introduction AOP Classes Definition Generation Meta-Classes in Python Meta-Class A class that creates classes Logging Delegation Objects that are instances of the same class Meta-Classes share the same behavior vs. -
Parametric Polymorphism (Generics) 30 April 2018 Lecturer: Andrew Myers
CS 4120/5120 Lecture 36 Parametric Polymorphism (Generics) 30 April 2018 Lecturer: Andrew Myers Parametric polymorphism, also known as generics, is a programming language feature with implications for compiler design. The word polymorphism in general means that a value or other entity that can have more than one type. We have already talked about subtype polymorphism, in which a value of one type can act like another (super)type. Subtyping places constraints on how we implemented objects. In parametric polymorphism, the ability for something to have more than one “shape” is by introducing a type parameter. A typical motivation for parametric polymorphism is to support generic collection libraries such as the Java Collection Framework. Prior to the introduction of parametric polymorphism, all that code could know about the contents of a Set or Map was that it contained Objects. This led to code that was clumsy and not type-safe. With parametric polymorphism, we can apply a parameterized type such as Map to particular types: a Map String, Point maps Strings to Points. We can also parameterize procedures (functions, methods) withh respect to types.i Using Xi-like syntax, we might write a is_member method that can look up elements in a map: contains K, V (c: Map K, V , k: K): Value { ... } Map K, V h m i h i ...h i p: Point = contains String, Point (m, "Hello") h i Although Map is sometimes called a parameterized type or a generic type , it isn’t really a type; it is a type-level function that maps a pair of types to a new type. -
Polymorphism
Polymorphism A closer look at types.... Chap 8 polymorphism º comes from Greek meaning ‘many forms’ In programming: Def: A function or operator is polymorphic if it has at least two possible types. Polymorphism i) OverloaDing Def: An overloaDeD function name or operator is one that has at least two Definitions, all of Different types. Example: In Java the ‘+’ operator is overloaDeD. String s = “abc” + “def”; +: String * String ® String int i = 3 + 5; +: int * int ® int Polymorphism Example: Java allows user DefineD polymorphism with overloaDeD function names. bool f (char a, char b) { return a == b; f : char * char ® bool } bool f (int a, int b) { f : int * int ® bool return a == b; } Note: ML Does not allow function overloaDing Polymorphism ii) Parameter Coercion Def: An implicit type conversion is calleD a coercion. Coercions usually exploit the type-subtype relationship because a wiDening type conversion from subtype to supertype is always DeemeD safe ® a compiler can insert these automatically ® type coercions. Example: type coercion in Java Double x; x = 2; the value 2 is coerceD from int to Double by the compiler Polymorphism Parameter coercion is an implicit type conversion on parameters. Parameter coercion makes writing programs easier – one function can be applieD to many subtypes. Example: Java voiD f (Double a) { ... } int Ì double float Ì double short Ì double all legal types that can be passeD to function ‘f’. byte Ì double char Ì double Note: ML Does not perform type coercion (ML has no notion of subtype). Polymorphism iii) Parametric Polymorphism Def: A function exhibits parametric polymorphism if it has a type that contains one or more type variables. -
Marshmallow-Annotations Documentation Release 2.4.1
marshmallow-annotations Documentation Release 2.4.1 Alec Nikolas Reiter Jan 28, 2021 Contents 1 Installation 3 2 Content 5 Index 21 i ii marshmallow-annotations Documentation, Release 2.4.1 Version 2.4.1 (Change Log) marshmallow-annotations allows you to create marshmallow schema from classes with annotations on them: # music.py from typing import List class Album: id: int name: str def __init__(self, id: int, name: str): self.id= id self.name= name class Artist: id: int name: str albums: List[Album] def __init__(self, id: int, name: str, albums: List[Album]): self.id= id self.name= name self.albums= albums # schema.py from marshmallow_annotations import AnnotationSchema from.music import Album, Artist class AlbumScheme(AnnotationSchema): class Meta: target= Album register_as_scheme= True class ArtistScheme(AnnotationSchema): class Meta: target= Artist register_as_scheme= True scheme= ArtistScheme() scheme.dump( Artist( id=1, name="Abominable Putridity", albums=[ Album( id=1, name="The Anomalies of Artificial Origin" ) ] ) ) #{ # "albums": [ #{ # "id": 1, (continues on next page) Contents 1 marshmallow-annotations Documentation, Release 2.4.1 (continued from previous page) # "name": "The Anomalies of Artificial Origin" #} # ], # "id": 1, # "name": "Abominable Putridity" #} 2 Contents CHAPTER 1 Installation marshmallow-annotations is available on pypi and installable with: pip install marshmallow-annotations marshmallow-annotations supports Python 3.6+ and marshmallow 2.x.x Note: If you are install marshmallow-annotations outside of a virtual environment, consider installing with pip install --user marshmallow-annotations rather than using sudo or adminstrator privileges to avoid installing it into your system Python. 3 marshmallow-annotations Documentation, Release 2.4.1 4 Chapter 1. Installation CHAPTER 2 Content 2.1 Quickstart This guide will walk you through the basics of using marshmallow-annotations.