First-Class Subtypes
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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. -
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. -
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. -
Open WATCOM Programmer's Guide
this document downloaded from... Use of this document the wings of subject to the terms and conditions as flight in an age stated on the website. of adventure for more downloads visit our other sites Positive Infinity and vulcanhammer.net chet-aero.com Watcom FORTRAN 77 Programmer's Guide Version 1.8 Notice of Copyright Copyright 2002-2008 the Open Watcom Contributors. Portions Copyright 1984-2002 Sybase, Inc. and its subsidiaries. All rights reserved. Any part of this publication may be reproduced, transmitted, or translated in any form or by any means, electronic, mechanical, manual, optical, or otherwise, without the prior written permission of anyone. For more information please visit http://www.openwatcom.org/ Portions of this manual are reprinted with permission from Tenberry Software, Inc. ii Preface The Watcom FORTRAN 77 Programmer's Guide includes the following major components: · DOS Programming Guide · The DOS/4GW DOS Extender · Windows 3.x Programming Guide · Windows NT Programming Guide · OS/2 Programming Guide · Novell NLM Programming Guide · Mixed Language Programming · Common Problems Acknowledgements This book was produced with the Watcom GML electronic publishing system, a software tool developed by WATCOM. In this system, writers use an ASCII text editor to create source files containing text annotated with tags. These tags label the structural elements of the document, such as chapters, sections, paragraphs, and lists. The Watcom GML software, which runs on a variety of operating systems, interprets the tags to format the text into a form such as you see here. Writers can produce output for a variety of printers, including laser printers, using separately specified layout directives for such things as font selection, column width and height, number of columns, etc. -
COMPILING FUNCTIONAL PROGRAMMING CONSTRUCTS to a LOGIC ENGINE by Harvey Abramson and Peter Ludemann Technical Report 86-24 November 1986
COMPILING FUNCTIONAL PROGRAMMING CONSTRUCTS TO A LOGIC ENGINE by Harvey Abramson and Peter Ludemann Technical Report 86-24 November 1986 Compiling Functional Programming Constructs to a Logic Engine Harvey Abramson t and Peter Ltidemann:I: Department of Computer Science University of British Columbia Vancouver, B.C., Canada V6T 1W5 Copyright © 1986 Abstract In this paper we consider how various constructs used in functional programming can be efficiently translated to code for a Prolog engine (designed by Ltidemann) similar in spirit but not identical to the Warren machine. It turns out that this Prolog engine which contains a delay mechanism designed to permit co routining and sound implementation of negation is sufficient to handle all common functional programming constructs; indeed, such a machine has about the same efficiency as a machine designed specifically for a functional programming language. This machine has been fully implemented. t Present address: Department of Computer Science, Bristol University, Bristol, England . f Present address: IBM Canada Ltd., 1 Park Centre, 895 Don Mills Road, North York, Ontario, Canada M3C 1W3 The proposals for combining the two paradigms Compiling Functional Programming have been roughly classified in [BoGi86] as being Constructs to a Logic Engine either functional plus logic or logic plus functional. Harvey Abramson t and Peter Ltidemanni In the former approach, invertibility, nondeterminism Department of Computer Science and unification are added to some higher order functional language; in the latter approach, first-order University of British Columbia functions are added to a first-order logic with an Vancouver, B.C., Canada V6T lWS equality theory. We do not take any position as to Copyright© 1986 which approach is best, but since a logic machine already deals with unification, nondeterminism and invertibility, we have taken, from an implementation Abstract viewpoint, the logic plus functional approach. -
Parameter Passing, Generics, Exceptions
Lecture 9: Parameter Passing, Generics and Polymorphism, Exceptions COMP 524 Programming Language Concepts Stephen Olivier February 12, 2008 Based on notes by A. Block, N. Fisher, F. Hernandez-Campos, and D. Stotts The University of North Carolina at Chapel Hill Parameter Passing •Pass-by-value: Input parameter •Pass-by-result: Output parameter •Pass-by-value-result: Input/output parameter •Pass-by-reference: Input/output parameter, no copy •Pass-by-name: Effectively textual substitution The University of North Carolina at Chapel Hill 2 Pass-by-value int m=8, i=5; foo(m); print m; # print 8 proc foo(int b){ b = b+5; } The University of North Carolina at Chapel Hill 3 Pass-by-reference int m=8; foo(m); print m; # print 13 proc foo(int b){ b = b+5; } The University of North Carolina at Chapel Hill 4 Pass-by-value-result int m=8; foo(m); print m; # print 13 proc foo(int b){ b = b+5; } The University of North Carolina at Chapel Hill 5 Pass-by-name •Arguments passed by name are re-evaluated in the caller’s referencing environment every time they are used. •They are implemented using a hidden-subroutine, known as a thunk. •This is a costly parameter passing mechanism. •Think of it as an in-line substitution (subroutine code put in-line at point of call, with parameters substituted). •Or, actual parameters substituted textually in the subroutine body for the formulas. The University of North Carolina at Chapel Hill 6 Pass-by-name array A[1..100] of int; array A[1..100] of int; int i=5; int i=5; foo(A[i], i); foo(A[i]); print A[i]; #print A[6]=7 -
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. -
Programming Languages
◦ ◦◦◦ TECHNISCHE UNIVERSITAT¨ MUNCHEN¨ ◦◦◦◦ ◦ ◦ ◦◦◦ ◦◦◦◦ ¨ ¨ ◦ ◦◦ FAKULTAT FUR INFORMATIK Programming Languages Multiple Inheritance Dr. Axel Simon and Dr. Michael Petter Winter term 2012 Multiple Inheritance 1 / 29 Outline Inheritance Principles 1 Interface Inheritance 2 Implementation Inheritance 3 Liskov Substition Principle and Shapes C++ Object Heap Layout 1 Basics 2 Single-Inheritance Excursion: Linearization 3 Virtual Methods 1 Ambiguous common parents 2 Principles of Linearization C++ Multiple Parents Heap Layout 3 Linearization algorithm 1 Multiple-Inheritance 2 Virtual Methods 3 Common Parents Discussion & Learning Outcomes Multiple Inheritance 2 / 29 “Wouldn’t it be nice to inherit from several parents?” Multiple Inheritance Inheritance Principles 3 / 29 Interface vs. Implementation inheritance The classic motivation for inheritance is implementation inheritance Code reusage Child specializes parents, replacing particular methods with custom ones Parent acts as library of common behaviours Implemented in languages like C++ or Lisp Code sharing in interface inheritance inverts this relation Behaviour contract Child provides methods, with signatures predetermined by the parent Parent acts as generic code frame with room for customization Implemented in languages like Java or C# Multiple Inheritance Inheritance Principles 4 / 29 Interface Inheritance DropDownList refresh() ActionObserver MyDDL changed() changed() Multiple Inheritance Inheritance Principles 5 / 29 Implementation inheritance PowerShovel FrontLoader actuate() actuate() -
Codata in Action
Codata in Action Paul Downen1, Zachary Sullivan1, Zena M. Ariola1, and Simon Peyton Jones2 1 University of Oregon, Eugene, USA?? [email protected], [email protected], [email protected] 2 Microsoft Research, Cambridge, UK [email protected] Abstract. Computer scientists are well-versed in dealing with data struc- tures. The same cannot be said about their dual: codata. Even though codata is pervasive in category theory, universal algebra, and logic, the use of codata for programming has been mainly relegated to represent- ing infinite objects and processes. Our goal is to demonstrate the ben- efits of codata as a general-purpose programming abstraction indepen- dent of any specific language: eager or lazy, statically or dynamically typed, and functional or object-oriented. While codata is not featured in many programming languages today, we show how codata can be eas- ily adopted and implemented by offering simple inter-compilation tech- niques between data and codata. We believe codata is a common ground between the functional and object-oriented paradigms; ultimately, we hope to utilize the Curry-Howard isomorphism to further bridge the gap. Keywords: codata · lambda-calculi · encodings · Curry-Howard · func- tion programming · object-oriented programming 1 Introduction Functional programming enjoys a beautiful connection to logic, known as the Curry-Howard correspondence, or proofs as programs principle [22]; results and notions about a language are translated to those about proofs, and vice-versa [17]. In addition to expressing computation as proof transformations, this con- nection is also fruitful for education: everybody would understand that the as- sumption \an x is zero" does not mean \every x is zero," which in turn explains the subtle typing rules for polymorphism in programs. -
Fun with Phantom Types 5 R
The Fun of Programming Oege de Moor, Jeremy Gibbons and Geraint Jones macmillan.eps Contents Fun with phantom types 5 R. Hinze Fun with phantom types R. Hinze Haskell is renowned for its many extensions to the Hindley-Milner type system (type classes, polymorphic recursion, rank-n types, existential types, functional dependencies—just to name a few). In this chapter we look at yet another exten- sion. I can hear you groaning but this is quite a mild extension and one that fits nicely within the Hindley-Milner framework. Of course, whenever you add a new feature to a language, you should throw out an existing one (especially if the lan- guage at hand is named after a logician). Now, for this chapter we abandon type classes—judge for yourself how well we get along without Haskell’s most beloved feature. 1 Introducing phantom types Suppose you want to embed a programming language, say, a simple expression language in Haskell. Since you are a firm believer of static typing, you would like your embedded language to be statically typed, as well. This requirement rules out a simple Term data type as this choice would allow us to freely mix terms of different types. The next idea is to parameterize the Term type so that Term t comprises only terms of type t. The different compartments of Term are then inhabited by declaring constructors of the appropriate types (we confine ourselves to a few basic operations): Zero :: Term Int Succ, Pred :: Term Int → Term Int IsZero :: Term Int → Term Bool If :: ∀a .