This is the 34th edition of the Haskell Communities and Activities Report. This report has 148 entries, 5 more than in the previous edition. Of these, 39 projects have received substantial updates and 18 entries are completely new. As usual, fresh entries – either completely new or old entries which have been revived after a short temporarily disappearance – are formatted using a blue background, while updated entries have a header with a blue background.
Since my goal is to keep only entries which are under active development (defined as receiving an update in a 3-editions sliding window), contributions from May 2015 and before have been completely removed, excepting those related to user groups and communities. However, they can be resurfaced in the next edition, should a new update be sent for them. For the 30th edition, for example, we had around 20 new entries which resurfaced.
A call for new HCAR entries and updates to existing ones will be issued on the Haskell mailing lists in late September/early October.
Now enjoy the current report and see what other Haskellers have been up to lately. Any feedback is very welcome, as always.
Mihai Maruseac, LeapYear Technologies Inc., US
<hcar at haskell.org>
PS: For this edition, I would like to thank Robin Bate Boerop for mentioning HCAR in his talk at BayHac. A few of the new entries are the result of his announcement.
|Report by:||Herbert Valerio Riedel|
|Participants:||Andres Löh, Antonio Nikishaev, Austin Seipp, Carlos Camarao de Figueiredo, Carter Schonwald, David Luposchainsky, Henk-Jan van Tuyl, Henrik Nilsson, Herbert Valerio Riedel, Iavor Diatchki, John Wiegley, JoséManuel Calderon Trilla, Jurriaan Hage, Lennart Augustsson, M Farkas-Dyck, Mario Blazevic, Nicolas Wu, Richard Eisenberg, Vitaly Bragilevsky, Wren Romano|
Haskell’ is an ongoing process to produce revisions to the Haskell standard, incorporating mature language extensions and well-understood modifications to the language. New revisions of the language are expected once per year.
The goal of the Haskell Language committee together with the Core Libraries Committee is to work towards a new Haskell 2020 Language Report. The Haskell Prime Process relies on everyone in the community to help by contributing proposals which the committee will then evaluate and, if suitable, help formalise for inclusion. Everyone interested in participating is also invited to join the haskell-prime mailing list.
Four years (or rather ~3.5 years) from now may seem like a long time. However, given the magnitude of the task at hand, to discuss, formalise, and implement proposed extensions (taking into account the recently enacted three-release-policy) to the Haskell Report, the process shouldn’t be rushed. Consequently, this may even turn out to be a tight schedule after all. However, it’s not excluded there may be an interim revision of the Haskell Report before 2020.
Based on this schedule, GHC 8.8 (likely to be released early 2020) would be the first GHC release to feature Haskell 2020 compliance. Prior GHC releases may be able to provide varying degree of conformance to drafts of the upcoming Haskell 2020 Report.
The Haskell Language 2020 committee starts out with 20 members which contribute a diversified skill-set. These initial members also represent the Haskell community from the perspective of practitioners, implementers, educators, and researchers.
The Haskell 2020 committee is a language committee; it will focus its efforts on specifying the Haskell language itself. Responsibility for the libraries laid out in the Report is left to the Core Libraries Committee (CLC). Incidentally, the CLC still has an available seat; if you would like to contribute to the Haskell 2020 Core Libraries you are encouraged to apply for this opening.
Haskellers is a site designed to promote Haskell as a language for use in the real world by being a central meeting place for the myriad talented Haskell developers out there. It allows users to create profiles complete with skill sets and packages authored and gives employers a central place to find Haskell professionals.
Haskellers is a web site in maintenance mode. No new features are being added, though the site remains active with many new accounts and job postings continuing. If you have specific feature requests, feel free to send them in (especially with pull requests!).
Haskellers remains a site intended for all members of the Haskell community, from professionals with 15 years experience to people just getting into the language.
The collection of various Haskell mini tutorials and assorted small projects (http://okmij.org/ftp/Haskell/) has received a manifold addition centered on Type Equality and Overlapping Instances.
We describe several forms of testing two types for equality, and asserting that two types are equal or not equal. The predicates differ in how they compare type variables, whether they allow wildcards, etc.
Overlapping instances are so practically appealing because they express the common pattern of adding a special case to an existing set of overloaded functions. We illustrate the pattern on a real-life example of optimizing a generic library. The example demonstrates the conflict between two practically useful features, overlapping instances and associated data types.
Overlapping instances are controversial because they straddle a contradiction. They embody “negation as failure”: the general type class instance is chosen for the given type only when all more specific instances failed to match the type. Negation-as-failure presupposes closed world, or a fixed set of instances. However, type classes are open: the user may add more instances at any time, in the same or different modules.
We describe type-level representation of types: essentially type-level Typeable. The library lets us check if two types are equal or dis-equal, and compare them by shape. We may use wildcards in type comparisons.
The library exhibits type-level conditional and higher-order type families such as |Member| (which takes a type-level equality predicate as an argument).
|Report by:||Michael Snoyman|
|Participants:||Edward Kmett, Simon Peyton Jones and others|
The School of Haskell has been available since early 2013. It’s main two functions are to be an education resource for anyone looking to learn Haskell and as a sharing resources for anyone who has built a valuable tutorial. The School of Haskell contains tutorials, courses, and articles created by both the Haskell community and the developers at FP Complete. Courses are available for all levels of developers.
School of Haskell has been open sourced, and is available from its own domain name (schoolofhaskell.com). In addition, the underlying engine powering interactive code snippets, ide-backend, has also been released as open source.
Currently 3150 tutorials have been created and 441 have been officially published. Some of the most visited tutorials are Text Manipulation, Attoparsec, Learning Haskell at the SOH, Introduction to Haskell - Haskell Basics, and A Little Lens Starter Tutorial. Over the past year the School of Haskell has averaged about 16k visitors a month.
All Haskell programmers are encouraged to visit the School of Haskell and to contribute their ideas and projects. This is another opportunity to showcase the virtues of Haskell and the sophistication and high level thinking of the Haskell community.
|Report by:||Manuel M. T. Chakravarty|
|Status:||Work in progress with eight published chapters|
Learning Haskell is a new Haskell tutorial that integrates text and screencasts to combine in-depth explanations with the hands-on experience of live coding. It is aimed at people who are new to Haskell and functional programming. Learning Haskell does not assume previous programming expertise, but it is structured such that an experienced programmer who is new to functional programming will also find it engaging.
Learning Haskell combines perfectly with the Haskell for Mac programming environment, but it also includes instructions on working with a conventional command-line Haskell installation. It is a free resource that should benefit anyone who wants to learn Haskell.
Learning Haskell is still work in progress with eight chapters already available. The current material covers all the basics, including higher-order functions and algebraic data types. Learning Haskell is approachable and fun – it includes topics such as illustrating various recursive structures using fractal graphics, such as this fractal tree.
Further chapters will be made available as we complete them.
The book is divided into two parts. Part I introduces the basic concepts of pure programming in Haskell and is structured around the core features of the language, such as types, functions, list comprehensions, recursion and higher-order functions. Part II covers impure programming and a range of more advanced topics, such as monads, parsing, foldable types, lazy evaluation and reasoning about programs. The book contains many extended programming examples, and each chapter includes suggestions for further reading and a series of exercises. The appendices provide solutions to selected exercises, and a summary of some of the most commonly used definitions from the Haskell standard prelude.
The book is an extensively revised and expanded version of the first edition. It has been extended with new chapters that cover more advanced aspects of Haskell, new examples and exercises to further reinforce the concepts being introduced, and solutions to selected exercises. The remaining material has been completely reworked in response to changes in the language and feedback from readers. The new edition uses the Glasgow Haskell Compiler (GHC), and is fully compatible with the latest version of the language, including recent changes concerning applicative, monadic, foldable and traversable types.
|Report by:||Chris Allen|
|Status:||Content complete, in final editing|
Haskell Programming is a book that aims to get people from the barest basics to being well-grounded in enough intermediate Haskell concepts that they can self-learn what would be typically required to use Haskell in production or to begin investigating the theory and design of Haskell independently. We’re writing this book because many have found learning Haskell to be difficult, but it doesn’t have to be. What particularly contributes to the good results we’ve been getting has been an aggressive focus on effective pedagogy and extensive testing with reviewers as well as feedback from readers. My coauthor Julie Moronuki is a linguist who’d never programmed before learning Haskell and authoring the book with me.
Haskell Programming is currently content complete and is approximately 1,200 pages long in the v0.12.0 release. The book is available for sale during the early access, which includes the 1.0 release of the book in PDF. We’re still editing the material. We expect to release the final version of the book this winter.
|Report by:||Jeremy Singer|
|Status:||Third run of a six-week online Haskell course has just completed|
The School of Computing Science at the University of Glasgow has partnered with the FutureLearn platform to deliver a six week massive open online course (MOOC) entitled Functional Programming in Haskell. The course goes through the basics of the Haskell language, using short videos, an online REPL, multiple choice quizzes and articles.
The third run of the course began on 1 Apr 2018. Around 1500 people signed up for the course, 70%of whom actively engaged with the materials. The most engaging aspect of the activity is the comradely atmosphere in the discussion forums.
The course is in a steady state, running two times per year in April and September. Visit our site to register your interest.
We are continuously refining the learning materials, based on learner feedback from the course. We presented some initial experiences at the Trends in Functional Programming in Education 2017 conference.
2018 saw GHC’s first release under its new accelerated release schedule. GHC 8.4.1 contained improvements in GHC’s standard libraries, code generation, and hundreds of bug fixes. Our focus is now turned to the next major release of the 8.0 series, GHC 8.6.1.
Significantly improved Windows support with a new I/O manager, long file path compatibility and dynamic linking support (Tamar Christina).
Since the launch of the GHC proposals process (https://github.com/ghc-proposals/ghc-proposals), over 128 proposals have been created, 41 have been submitted to the committee and 19 have been accepted. These are:
GHC is lucky to have a large number of volunteer contributors.
As always, if you are interested in contributing to any facet of GHC, be it the runtime system, type-checker, documentation, simplifier, or anything in between, please come speak to us either on IRC (#ghc on irc.freeenode.net) or email@example.com. Happy Haskelling!
Helium is a compiler that supports a substantial subset of Haskell 98 (but, e.g., n+k patterns are missing). Type classes are restricted to a number of built-in type classes and all instances are derived. The advantage of Helium is that it generates novice friendly error feedback, including domain specific type error diagnosis by means of specialized type rules. Helium and its associated packages are available from Hackage. Install it by running cabal install helium. You should also cabal install lvmrun on which it dynamically depends for running the compiled code.
Currently Helium is at version 1.8.1. The major change with respect to 1.8 is that Helium is again well-integrated with the Hint programming environment that Arie Middelkoop wrote in Java. The jar-file for Hint can be found on the Helium website, which is located at http://www.cs.uu.nl/wiki/Helium. This website also explains in detail what Helium is about, what it offers, and what we plan to do in the near and far future.
A student has added parsing and static checking for type class and instance definitions to the language, but type inferencing and code generating still need to be added. Completing support for type classes is the second thing on our agenda, the first thing being making updates to the documentation of the workings of Helium on the website.
|Report by:||Jens Petersen|
|Participants:||Elliott Sales de Andrade, Robert-AndréMauchin|
The Fedora Haskell SIG works to provide good Haskell support in the Fedora Project Linux distribution.
For the Fedora 28 release on 1st May, ghc was updated to 8.2.2 and packages to Stackage LTS 10 versions. Also the shared dynamic libraries now live in system libdir. Over 30 new packages were added to Fedora 28. We use the cabal-rpm packaging tool to create and update Haskell packages, and fedora-haskell-tools to rebuild them.
For the next release we plan to update to LTS 11, and also to do some packaging changes to subpackage haddock documentation for libraries.
A Fedora Copr repo is available for ghc-8.4.2.
If you are interested in Fedora Haskell packaging, please join our mailing-list and the Freenode #fedora-haskell channel. You can also follow @fedorahaskell for occasional updates.
The Debian Haskell Group aims to provide an optimal Haskell experience to users of the Debian GNU/Linux distribution and derived distributions such as Ubuntu. We try to follow the Haskell Platform versions for the core packages and package a wide range of other useful libraries and programs. At the time of writing, we maintain 1077 source packages.
A system of virtual package names and dependencies, based on the ABI hashes, guarantees that a system upgrade will leave all installed libraries usable. Most libraries are also optionally available with profiling enabled and the documentation packages register with the system-wide index.
The current stable Debian release (“strech”) provides GHC 8.0.1. In Debian unstable and testing (“buster”, the next release) we ship GHC 8.0.2. GHC 8.2 is staged in “experimental”.
Debian users benefit from the Haskell ecosystem on 22 architecture/kernel combinations, including the non-Linux-ports KFreeBSD and Hurd.
|Report by:||Joachim Breitner|
|Participants:||Antal Spector-Zabusky, Stephanie Weirich|
The hs-to-coq tool, written by Antal Spector-Zabusky, Joachim Breitner and Stephanie Weirich, translates a large subset of Haskell into Gallina, the programming langauge of the proof assistant Coq. The translation process is configurable and allows the user to stub out low-level features, to map Haskell types and functions to corresponding existing Coq types and functions and to declare termination arguments. It has been used to verify a large subset of Haskell’s containers library.
|Report by:||Ulf Norell|
|Participants:||Ulf Norell, Nils Anders Danielsson, Andreas Abel, Jesper Cockx, Makoto Takeyama, Stevan Andjelkovic, Jean-Philippe Bernardy, James Chapman, Dominique Devriese, Peter Divianszki, Fredrik Nordvall Forsberg, Olle Fredriksson, Daniel Gustafsson, Alan Jeffrey, Fredrik Lindblad, Guilhem Moulin, Nicolas Pouillard, Andrés Sicard-Ramirez and many others|
Agda is a dependently typed functional programming language (developed using Haskell). A central feature of Agda is inductive families, i.e., GADTs which can be indexed by values and not just types. The language also supports coinductive types, parameterized modules, and mixfix operators, and comes with an interactive interface—the type checker can assist you in the development of your code.
A lot of work remains in order for Agda to become a full-fledged programming language (good libraries, mature compilers, documentation, etc.), but already in its current state it can provide lots of value as a platform for research and experiments in dependently typed programming.
Release of Agda 2.5.4 is planned for early summer 2018 with a number of new features:
The Agda Wiki: http://wiki.portal.chalmers.se/agda/
|Report by:||Ben Lippmeier|
|Participants:||Ben Lippmeier, Jacob Stanley|
|Status:||experimental, active development|
The Disciplined Disciple Compiler (DDC) is a research compiler used to investigate program transformation in the presence of computational effects. It compiles a family of strict functional core languages and supports region and effect typing. This extra information provides a handle on the operational behaviour of code that isn’t available in other languages. Programs can be written in either a pure/functional or effectful/imperative style, and one of our goals is to provide both styles coherently in the same language.
DDC v0.5.1 was released in late October, and is in "working alpha" state. The main new features are:
We are currently working on a new indexed binary format for interface files, as re-parsing interface files is currently a bottleneck. The file format is to be provided by the Shimmer project, which has been split out into a separate repo.
I am working on an ambitious update to GHC that will bring full dependent types to the language. In GHC 8, the Core language and type inference have already been updated according to the description in our ICFP’13 paper . Accordingly, all type-level constructs are simultaneously kind-level constructs, as there is no distinction between types and kinds. Specifically, GADTs and type families are promotable to kinds. At this point, I conjecture that any construct writable in those other dependently-typed languages will be expressible in Haskell through the use of singletons.
Building on this prior work, I have written my dissertation on incorporating proper dependent types in Haskell . I have yet to have the time to start genuine work on the implementation, but I plan to do so starting summer 2017.
Here is a sneak preview of what will be possible with dependent types, although much more is possible, too!
data Vec :: * -> Integer -> * ^^ where
Nil :: Vec a 0
(:::) :: a -> Vec a n -> Vec a (1 !+ n)
replicate :: pi n. forall a. a -> Vec a n
replicate ^^ @0 _ = Nil
replicate x = x ::: replicate x
Of course, the design here (especially for the proper dependent types) is preliminary, and input is encouraged.
The generics-sop (“sop” is for “sum of products”) package is a library for datatype-generic programming in Haskell, in the spirit of GHC’s built-in DeriveGeneric construct and the generic-deriving package.
Datatypes are represented using a structurally isomorphic representation that can be used to define functions that work automatically for a large class of datatypes (comparisons, traversals, translations, and more). In contrast with the previously existing libraries, generics-sop does not use the full power of current GHC type system extensions to model datatypes as an n-ary sum (choice) between the constructors, and the arguments of each constructor as an n-ary product (sequence, i.e., heterogeneous lists). The library comes with several powerful combinators that work on n-ary sums and products, allowing to define generic functions in a very concise and compositional style.
The current release is 0.2.0.0.
A new talk from ZuriHack 2016 is available on Youtube. The most interesting upcoming feature is probably type-level metadata, making use of the fact that GHC 8 now offers type-level metadata for the built-in generics. While the feature is in principle implemented, there are still a few open questions about what representation would be most convenient to work with in practice. Help or opinions are welcome!
|Report by:||Jan Bracker|
|Participants:||Jan Bracker and Henrik Nilsson|
|Status:||Experimental fully working version|
The supermonad package provides a unified way to represent different monadic and applicative notions. In other words, it provides a way to use standard and generalized monads and applicative functors (with additional indices or constraints) without having to manually disambiguate which notion is referred to in every context. This allows the reuse of code, such as standard library functions, across all of the notions.
To achieve this, the library splits the monad and applicative type classes such that they are general enough to allow instances for all of the generalized notions and then aids constraint checking through a GHC plugin to ensure that everything type checks properly. Due to the plugin the library can only be used with GHC.
If you are interested in using the library, we have a few examples of different size in the repository to show how it can be utilized. The generated Haddock documentation also has full coverage and can be seen on the libraries Hackage page.
The project had its first release shortly before ICFP and the Haskell Symposium 2016. Since then we have added support for applicative functors in addition to monads.
We are working on a comprehensive paper that covers all aspects of the project and its theoretical foundations. The paper is submitted to the Journal of Functional Programming.
If you are interested in contributing, found a bug or have a suggestion to improve the project we are happy to hear from you in person, by email or over the projects bug tracker on GitHub.
The outcome of the compile-time evaluation of type families is currently inscrutable to the running program. tyfam-witnesses is a new minimal library that utilises Template Haskell to obtain the necessary artifacts for running the clauses of closed type families at execution time. By pattern matching on the outcome all the type-level equalities can be recovered.
For each closed type family in a series of declarations, witnesses adds a GADT mirroring its clauses, and a reification function that runs it given indexed TypeReps. Here is a usage example:
gets accompanied with
and a runner (or reifier)
Pattern matching on the result of the latter guides the GHC type checker and allows writing recursive functions that evaluate to an ElimRefl v f, which would otherwise get stuck.
The library has been introduced at the Regensburg Haskell Meetup (→6.8) and other conferences in Oct. 2017.
You can find it on hackage, grab it with cabal install tyfam-witnesses, be reminded however, that GHC v8.2 is a prerequisite for its usage.
I am interested in possible further uses and am waiting for encouragement in resolving the two remaining restrictions.
Cabal is the standard packaging system for Haskell software. It specifies a standard way in which Haskell libraries and applications can be packaged so that it is easy for consumers to use them, or re-package them, regardless of the Haskell implementation or installation platform.
cabal-install is the command line interface for the Cabal and Hackage system. It provides a command line program cabal which has sub-commands for installing and managing Haskell packages.
We’ve recently produced new point releases of Cabal/cabal-install from the 1.24 branch. Among other things, Cabal 184.108.40.206 includes a fix necessary to make soon-to-be-released GHC 8.0.2 work on macOS Sierra.
Almost 1500 commits were made to the master branch by 53 different contributors since the 1.24 release. Among the highlights are:
The next Cabal/cabal-install versions will be released either in early 2017, or simultaneously with GHC 8.2 (April/May 2017). Our main focus at this stage is getting the new-build feature to the state where it can be enabled by default, but there are many other areas of Cabal that need work.
We would like to encourage people considering contributing to take a look at the bug tracker on GitHub and the Wiki, take part in discussions on tickets and pull requests, or submit their own. The bug tracker is reasonably well maintained and it should be relatively clear to new contributors what is in need of attention and which tasks are considered relatively easy. For more in-depth discussion there is also the cabal-devel mailing list.
Stack is a modern, cross-platform build tool for Haskell code. It is intended for Haskellers both new and experienced.
Stack handles the management of your toolchain (including GHC - the Glasgow Haskell Compiler - and, for Windows users, MSYS), building and registering libraries, building build tool dependencies, and more. While it can use existing tools on your system, Stack has the capacity to be your one-stop shop for all Haskell tooling you need.
The primary design point is reproducible builds. If you run stack build today, you should get the same result running stack build tomorrow. There are some cases that can break that rule (changes in your operating system configuration, for example), but, overall, Stack follows this design philosophy closely. To make this a simple process, Stack uses curated package sets called snapshots.
Stack has also been designed from the ground up to be user friendly, with an intuitive, discoverable command line interface.
Since its first release in June 2015, many people are using it as their primary Haskell build tool, both commercially and as hobbyists. New features and refinements are continually being added, with regular new releases.
Binaries and installers/packages are available for common operating systems to make it easy to get started. Download it at http://haskellstack.org/.
Stackage began in November 2012 with the mission of making it possible to build stable, vetted sets of packages. The overall goal was to make the Cabal experience better. Five years into the project, a lot of progress has been made and now it includes both Stackage and the Stackage Server. To date, there are over 1900 packages available in Stackage. The official site is https://www.stackage.org.
The Stackage project consists of many different components, linked to from the Stackage Github repository https://github.com/fpco/stackage#readme. These include:
There are dozens of individual maintainers for packages in Stackage. Overall Stackage curation is handled by the “Stackage curator” team, which consists of Michael Snoyman, Adam Bergmark, Dan Burton, Jens Petersen, Luke Murphy, Chris Dornan, and Mihai Maruseac.
Stackage provides a well-tested set of packages for end users to develop on, a rigorous continuous-integration system for the package ecosystem, some basic guidelines to package authors on minimal package compatibility, and even a testing ground for new versions of GHC. Stackage has helped encourage package authors to keep compatibility with a wider range of dependencies as well, benefiting not just Stackage users, but Haskell developers in general.
If you’ve written some code that you’re actively maintaining, don’t hesitate to get it in Stackage. You’ll be widening the potential audience of users for your code by getting your package into Stackage, and you’ll get some helpful feedback from the automated builds so that users can more reliably build your code.
Since the last HCAR, we have moved Stackage Nightly to GHC 8.4.1, as well as released LTS 10 and 11 based on GHC 8.2.2.
A browser plugin (currently supported for Firefox/Google Chrome) to automatically redirect Haddock documentation on Hackage to corresponding Stackage pages, when the request is via search engines like Google/Bing etc. For the case where the package hasn’t been added yet to Stackage, no redirect will be made and the Hackage documentation will be available. This plugin also tries to guess when the user would want to go to a Hackage page instead of the Stackage one and tries to do the right thing there.
Pier is a command-line tool for building Haskell projects. It is similar in purpose to Stack (→4.2.2); it uses *.cabal files to configure individual packages, a top-level YAML file to configure the whole project, and Stackage (→4.2.3) to get consistent sets of package dependencies. However, Pier attempts to address some of Stack’s limitations by exploring a different approach:
Pier is still experimental, but is already able to build most the packages in Stackage (specifically, 90%of the more than 2600 packages in lts-10.3) as well as itself (i.e., pier build pier). Notably, packages with custom Setup scripts are not yet supported.
Future plans include: adding more commands such as pier repl; improving the usability around the output file store (for example, garbage collection); and exposing the internal library that Pier uses for hermetic build steps and immutable outputs.
packcheck uniformly, consistently builds and comprehensively sanity tests a Haskell package across build tools (stack/cabal) and across all platforms (Linux/MacOS/Windows). You do not need to be familiar with any of the build tools to use it.
packcheck provides a universal CI/build script packcheck.sh and config files designed such that you can just copy over the .travis.yml and appveyor.yml files provided with packcheck to your package repository and your package is CI ready. You can replicate the same testing on your local machine, just copy packcheck.sh to your local machine, put it in your PATH, and run it from your package directory:
This is a utility to install Haskell programs on a system using stack. Although stack does have an install command, it only copies binaries. Sometimes more is needed, other files and some directory structure. hsinstall tries to install the binaries, the LICENSE file and also the resources directory if it finds one.
Installations can be performed in one of two directory structures. FHS, or the Filesystem Hierarchy Standard (most UNIX-like systems) and what I call “bundle” which is a portable directory for the app and all of its files. They look like this:
There are two parts to hsinstall that are intended to work together. The first part is a Haskell shell script, util/install.hs. Take a copy of this script and check it into a project you’re working on. This will be your installation script. Running the script with the –help switch will explain the options. Near the top of the script are default values for these options that should be tuned to what your project needs.
The other part of hsinstall is a library. The install script will try to install a resources directory if it finds one. the HSInstall library can then be used in your code to locate the resources at runtime.
Note that you only need the library if your software has data files it needs to locate at runtime in the installation directories. Many programs don’t have this requirement and can ignore the library altogether.
Source code is available on darcshub, Hackage and Stackage
A Yesod scaffolding site with Postgres backend. It provides a JSON API backend as a separate subsite. The primary purpose of this repository is to use Yesod as a API server backend and do the frontend development using a tool like React or Angular. The current code includes a basic example using React and Babel which is bundled finally by webpack and added in the handler getHomeR in a type safe manner.
The future work is to make it compatible with yesod-1.6 and then integrate it as part of yesod-scaffold and make it as part of stack template.
Using the Haskell Cloud builder, existing Haskell projects can be uploaded, built, and run from the cloud with minimal changes. A choice of pre-installed frameworks is available - see the Wiki for details.
Darcs is a distributed revision control system written in Haskell. In Darcs, every copy of your source code is a full repository, which allows for full operation in a disconnected environment, and also allows anyone with read access to a Darcs repository to easily create their own branch and modify it with the full power of Darcs’ revision control. Darcs is based on an underlying theory of patches, which allows for safe reordering and merging of patches even in complex scenarios. For all its power, Darcs remains a very easy to use tool for every day use because it follows the principle of keeping simple things simple.
Darcs 2.14.0 was released on April 2018. It features a better support of non-ASCII encodings by default, an improved display of patch dependencies, per-file conflict marking, a more efficient annotate command, and better shell completion.
SFC and donationsDarcs is free software licensed under the GNU GPL (version 2 or greater). Darcs is a proud member of the Software Freedom Conservancy, a US tax-exempt 501(c)(3) organization. We accept donations at http://darcs.net/donations.html.
git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space.
As well as integrating with the git command-line tools, git-annex includes a graphical app which can be used to keep a folder synchronized between computers. This is implemented as a local webapp using yesod and warp.
git-annex runs on Linux, OSX and other Unixes, and has been ported to Windows. There is also an incomplete but somewhat usable port to Android.
Five years into its development, git-annex has a wide user community. It is being used by organizations for purposes as varied as keeping remote Brazilian communities in touch and managing Neurological imaging data. It is available in a number of Linux distributions, in OSX Homebrew, and is one of the most downloaded utilities on Hackage. It was my first Haskell program.
At this point, my goals for git-annex are to continue to improve its foundations, while at the same time keeping up with the constant flood of suggestions from its user community, which range from adding support for storing files on more cloud storage platforms (around 20 are already supported), to improving its usability for new and non technically inclined users, to scaling better to support Big Data, to improving its support for creating metadata driven views of files in a git repository.
At some point I’d also like to split off any one of a half-dozen general-purpose Haskell libraries that have grown up inside the git-annex source tree.
|Report by:||Maarten Faddegon|
Hoed is a tracer and debugger for the programming language Haskell.
To locate a defect with Hoed you annotate suspected functions and compile as usual. Then you run your program, information about the annotated functions is collected. Finally you connect to a debugging session using a console.
With Hoed you can list and search observed functions applied to argument values and the result values. Hoed also provides algorithmic debugging. An algorithmic debugger finds defects in programs by systematic search. The programmer directs the search by answering a series of yes/no questions about the correctness of specific function applications and their results. Hoed also allows the use of (QuickCheck-style) properties to answer automatically some of the questions arising during algorithmic debugging, and to replace others by simpler questions.
Let us consider the following program, a defective implementation of a parity function with a test property.
Using the property-based test tool QuickCheck we find the counter example 1 for our property.
Hoed can help us determine which function is defective. We annotate the functions |isOdd|, |isEven|, |plusOne| and |mod2| as follows:
To reduce the number of questions the programmer has to answer, we added a new mode Assisted Algorithmic Debugging. In this mode (QuickCheck) properties already present in program code for property-based testing can be used to automatically judge computation statements
The tool ghc-vis visualizes live Haskell data structures in GHCi. Since it does not force the evaluation of the values under inspection it is possible to see Haskell’s lazy evaluation and sharing in action while you interact with the data.
Ghc-vis supports two styles: A linear rendering similar to GHCi’s :print, and a graph-based view where closures in memory are nodes and pointers between them are edges. In the following GHCi session a partially evaluated list of fibonacci numbers is visualized:
At this point the visualization can be used interactively: To evaluate a thunk, simply click on it and immediately see the effects. You can even evaluate thunks which are normally not reachable by regular Haskell code.
Ghc-vis can also be used as a library and in combination with GHCi’s debugger.
The library ghc-heap-view provides means to inspect the GHC’s heap and analyze the actual layout of Haskell objects in memory. This allows you to investigate memory consumption, sharing and lazy evaluation.
This means that the actual layout of Haskell objects in memory can be analyzed. You can investigate sharing as well as lazy evaluation using ghc-heap-view.
The package also provides the GHCi command :printHeap, which is similar to the debuggers’ :print command but is able to show more closures and their sharing behaviour:
The graphical tool ghc-vis (→4.4.2) builds on ghc-heap-view.
Since version 0.5.10, ghc-heap-view supports GHC 8.2. There is ongoing work that might merge this functionality into GHC proper.
Hat is a source-level tracer for Haskell. Hat gives access to detailed, otherwise invisible information about a computation.
Hat helps locating errors in programs. Furthermore, it is useful for understanding how a (correct) program works, especially for teaching and program maintenance. Hat is not a time or space profiler. Hat can be used for programs that terminate normally, that terminate with an error message or that terminate when interrupted by the programmer.
You trace a program with Hat by following these steps:
Hat is distributed as a package on Hackage that contains all Hat tools and tracing versions of standard libraries. Hat 2.9.4 works with recent versions of the Glasgow Haskell compiler for Haskell programs that are written in Haskell 98 plus a few language extensions such as multi-parameter type classes and functional dependencies.
Although Hat is distributed as a cabal package that can be installed with stack, it currently does not support working with stack projects; instead it provides an old-fashioned build tool hat-make.
Note that all modules of a traced program have to be transformed, including trusted libraries (transformed in trusted mode). For portability all viewing tools have a textual interface; however, many tools require an ANSI terminal and thus run on Unix / Linux / OS X, but not on Windows.
In the longer term we intend to transfer the lightweight tracing technology that we use in Hoed (→4.4.1) also to Hat.
Carefully crafted Haskell libraries are often set up to trigger a specific cascade of optimization. Stream fusion as found in the text and vector libraries is a good example, as are generic programming libraries like generic-lens. The inspection-testing library allows developers to assert that certian transformations indeed happen at compile time, and check these assertions automatically.
For example, the following test file ensures that GHC’s optimizer removes the call to fmap in lhs:
|Report by:||Rudy Braquehais|
|Status:||Actively maintained, v0.7.0|
LeanCheck is an enumerative property-based testing library with a very small core of only 180 lines of code. Its enumeration is size-bounded so the number of tests is easier to control than with SmallCheck.
It is used like so:
LeanCheck has support for higher-order properties (those taking functions as arguments). For example:
LeanCheck works on properties whose argument types are instances of the Listable typeclass. It is very easy to define Listable instances for user-defined types. For example, take “Hutton’s Razor”:
LeanCheck is available on Hackage under a BSD3-style license. All you need to do to get it is:
The latest version (v0.7.0) includes functions to compute statistics of Listable instances.
|Report by:||Rudy Braquehais|
|Status:||Actively maintained, v0.3.1|
Extrapolate is a property-based testing library capable of reporting generalized counter-examples to properties. Extrapolate works on top of LeanCheck (→4.5.2).
Here is an example:
The above property about nub not only fails for the list [0,0] but also for any list that has repeated elements.
The generalization of failing cases informs the programmer more fully and more immediately what characterizes failures. This information helps the programmer to locate more confidently and more rapidly the causes of failure in their program.
Extrapolate’s generalization of counter-examples is similar to SmartCheck’s. However, when generalizing, Extrapolate allows for repeated variables and side-conditions.
Extrapolate is available on Hackage under a BSD3-style license. All you need to do to get it is:
The latest version (v0.3.1) uses Speculate (→4.5.4) to avoid testing equivalent conditions improving results and performance.
|Report by:||Rudy Braquehais|
|Status:||Actively maintained, v0.3.2|
Speculate is a library that uses testing to automatically discover and conjecture properties about Haskell functions. Those properties can contribute to understanding, documentation, validation, design refinement and regression testing.
The following example shows how to use Speculate to discover properties about addition and multiplication:
Speculate can even discover properties about higher-order functions. For example, it discovers the following properties about map, id and (.) (cf. eg/fun.hs):
Speculate is similar to QuickSpec, but uses a different algorithm to produce inequalities and conditional equations. See the documentation for further details and examples.
The latest version (v0.3.2) includes significant performance improvements. It also includes improvements in documentation, examples and API.
Speculate is available on Hackage under a BSD3-style license. All you need to do to get it is:
More often than not, testing software consumes a large portion of the development budget, however we frequently see cases where unit and integration tests fail to uncover critical errors that appear once the software is deployed. Most testing techniques revolve around specifying a collection of execution sequences that check the expected against the actual behavior. A problem with this is that the number of possible execution sequences is huge, and therefore only a very small portion of these would be covered by test cases that are specified as a sequence of steps. The second problem is that, with the goal of increasing coverage and prevent regression bugs a large number of test cases is written, which eats up the development budget.
Model-based testing is a technique for writing tests, where a model of the system behavior is made a a high-level of abstraction, and then the system-under test is tested against this the expected behavior as specified by the model. Model-based testing relies on different algorithms for generating test cases from models, which allows to achieve a much higher test coverage than standard testing techniques, while requiring only a fraction of the code.
TorXakis is such a model-based testing tool, that has been used to verify large scale systems in well-know high tech companies. This tool is entirely written in Haskell, and its code is available on Github under a BSD3 license.
Since July last year, a lot of effort was put into taking TorXakis from a prototype to an industrial grade tool. Some of the improvements made include:
In addition, there is ongoing work in a new command line interface and a new compiler for the TorXakis language.
A year is almost gone, and there are a lot of interesting challenges ahead to make TorXakis a tool that can be used in production, so we welcome the contributions of anybody interested in the topic.
Haskell for Mac is an easy-to-use, innovative programming environment and learning platform for Haskell on OS X. It includes its own Haskell distribution and requires no further set up. It features interactive Haskell playgrounds to explore and experiment with code. Playground code is not only type-checked, but also executed while you type, which leads to a fast turn around during debugging or experimenting with new code.
Integrated environment. Haskell for Mac integrates everything needed to start writing Haskell code, including an editor with syntax highlighting and smart identifier completion. Haskell for Mac creates Haskell projects based on standard Cabal specifications for compatibility with the rest of the Haskell ecosystem. It includes the Glasgow Haskell Compiler (GHC) and over 200 of the most popular packages of LTS Haskell package sets. Matching command line tools and extra packages can be installed, too.
Type directed development. Haskell for Mac uses GHC’s support for deferred type errors so that you can still execute playground code in the face of type errors. This is convenient during refactoring to test changes, while some code still hasn’t been adapted to new signatures. Moreover, you can use type holes to stub out missing pieces of code, while still being able to run code. The system will also report the types expected for holes and the types of the available bindings.
Interactive HTML, graphics &games. Haskell for Mac comes with support for web programming, network programming, graphics programming, animations, and much more. Interactively generate web pages, charts, animations, or even games (with the OS X SpriteKit support). Graphics are also live and change as you modify the program code.
The screenshot below is from the development of a Flappy Bird clone in Haskell. Watch the Haskell for Mac developer live code Flappy Bird in Haskell in 20min at the end of the Compose :: Melbourne 2016 keynote at https://speakerdeck.com/mchakravarty/playing-with-graphics-and-animations-in-haskell. You can find more information about writing games in Haskell in this blog post: http://blog.haskellformac.com/blog/writing-games-in-haskell-with-spritekit.
Haskell for Mac has recently gained auto-completion of identifiers, taking into account the current module’s imports. It now also features a graphical package installer for LTS Haskell and support for GHC 8. Moreover, a new type class, @Presentable@, enables custom rendering of user-defined data types using images, HTML, and even animations.
Haskell for Mac is available for purchase from the Mac App Store. Just search for "Haskell", or visit our website for a direct link. We are always available for questions or feedback at firstname.lastname@example.org.
The Haskell for Mac website: http://haskellformac.com
|Report by:||Chris Allen|
|Participants:||Alan Zimmerman, Moritz Kiefer, Michael Sloan, Gracjan Polak, Daniel Gröber, others welcome|
|Status:||Open source, just beginning|
haskell-ide-engine is a backend for driving the sort of features programmers expect out of IDE environments. haskell-ide-engine is a project to unify tooling efforts into something different text editors, and indeed IDEs as well, could use to avoid duplication of effort.
There is basic support for getting type information and refactoring, more features including type errors, linting and reformatting are planned. People who are familiar with a particular part of the chain can focus their efforts there, knowing that the other parts will be handled by other components of the backend. Integration for Emacs and Leksah is available and should support the current features of the backend. Work has started on a Language Server Protocol transport, for use in VS Code. haskell-ide-engine also has a REST API with Swagger UI. Inspiration is being taken from the work the Idris community has done toward an interactive editing environment as well.
Help is very much needed and wanted so if this is a problem that interests you, please pitch in! This is not a project just for a small inner circle. Anyone who wants to will be added to the project on github, address your request to @alanz.
|Report by:||Heinrich Apfelmus|
|Status:||available, active development|
HyperHaskell is a graphical Haskell interpreter, not unlike GHCi, but hopefully more awesome. You use worksheets to enter expressions and evaluate them. Results are displayed graphically using HTML.
HyperHaskell is intended to be easy to install. It is cross-platform and should run on Linux, Mac and Windows. Internally, it uses the GHC API to interpret Haskell programs, and the graphical front-end is built on the Electron framework. HyperHaskell is open source.
HyperHaskell’s main attraction is a Display class that supersedes the good old Show class. The result looks like this:
HyperHaskell is currently Level alpha. The latest stable release is 0.1.0.2. Compared to the previous report, no new release has been made, but basic features are working. It is now possible to interpret statements in the IO monad and to bind variables, greatly enhancing the usefulness of the interpreter.
Support for the Nix package manager has been implemented by Rodney Lorrimar. I am looking for help in setting up binary releases on the Windows platform!
Programming a computer usually involves writing a program text in a particular language, a “verbal” activity. But computers can also be instructed by gestures, say, a mouse click, which is a “nonverbal” activity. The long term goal of HyperHaskell is to blur the lines between programming “verbally” and “nonverbally” in Haskell. This begins with an interpreter that has graphical representations for values, but also includes editing a program text while it’s running (“live coding”) and interactive representations of values (e.g. “tangible values”). This territory is still largely uncharted from a purely functional perspective, probably due to a lack of easily installed graphical facilities. It is my hope that HyperHaskell may provide a common ground for exploration and experimentation in this direction, in particular by offering the Display class which may, perhaps one day, replace our good old Show class.
A simple form of live coding is planned for Level beta, and I am experimenting with interactive music programming.
CodeWorld is a web-based educational programming environment using Haskell, and appropriate for all ages. It provides a simple mathematical model for geometric figures, animations, and interactive and multi-player games. The language scales between a graphical block-based language for primary students, a simplified variant of Haskell, and the full-fledged Haskell language for older students and universities. In addition to the tools, CodeWorld also provides learning resources for teachers and independent learners. CodeWorld is actively used for Haskell programming classes and activities, by universities, primary and secondary schools, and non-profit organizations and programs.
In the summer of 2017, CodeWorld hosted four students through the Summer of Haskell program to work on improving debugging tools, error messages, collaborative coding experiences, and exporting projects to video and mobile applications. Some contributions are still being merged. Other recent changes include the addition of a model for simple multi-player networked games and QuickCheck support for the full Haskell mode. Simultaneously, we’ve been busy developing a packaged curriculum for early secondary students, ages 11-14, using functional programming as a framework for creative mathematics.
CodeWorld is freely available. The hosted web site at http://code.world is open to the public. Source code for the project is available under the Apache license. Teaching materials and resources are released as they are completed under a Creative Commons license.
|Report by:||Ivan Kristo|
|Participants:||Robin Palotai, Kristoffer Søholm|
|Status:||stable, actively developed|
Haskell Indexer is a Kythe extension for working with Haskell source code. Kythe is language-agnostic ecosystem for building tools that work with code. An example is code search with cross-reference support: https://cs.chromium.org/. Haskell Indexer makes it possible to use Kythe-based tools with Haskell. With Haskell Indexer it’s possible to list all use-sites of any given function (get reverse-references) and explore the code without any IDE setup.
A portion of GHC and Stackage is indexed and available at http://stuff.codereview.me/.
Haskell Indexer is in active use and development. As of today, it’s possible to get it from GitHub – the Hackage release is work in progress. The future plans include improving the cross-reference support, adding cross-language linking with C and better handling of Template Haskell.
Brittany is a Haskell source code formatting tool that tries to produce consistent, neat, and concise layouting while preserving comments and user-provided formatting (e.g. newlines). In particular brittany..
The project is not finished in two important aspects:
Brittany is based on ghc-exactprint and the ghc parser. It requires ghc-8.*, and is available on Hackage and on Stackage.
The project welcomes contribution for any desired, yet missing features.
The design/implementation of this project has been captured in several documents you can find in the project’s repository.
IHaskell is a Haskell kernel for the Jupyter project, and it is usable through various Jupyter frontends, such as the console and the notebook. It is an interactive shell similar to GHCi, and it provides features such as syntax highlighting, autocompletion, multi-line input cells, integrated documentation, rich output visualisation, and more. It integrates with HLint to provide style and formatting suggestions, and notebooks can be exported as Literate Haskell or Markdown.
An example IHaskell notebook looks like this:
IHaskell currently supports GHC 8.0, 8.2, and 8.4, and older releases have support back to GHC 7.6. It can be installed on Linux and macOS. Windows is currently not supported. Installation via Cabal, Stack, and Nix is supported, and the recently announced mybinder.org can also be used to host IHaskell notebooks.
IHaskell is open source, and the project homepage is at https://github.com/gibiansky/IHaskell.
Doc Browser is an API documentation browser written in Haskell and QML.
It is a native desktop app, with offline supports for Hoogle, DevDocs’ docset and Dash’s docset.
It is under development, but the GUI is suitable for daily use.
The Incredible Proof Machine is a visual interactive theorem prover: Create proofs of theorems in propositional, predicate or other, custom defined logics simply by placing blocks on a canvas and connecting them. You can think of it as Simulink mangled by the Curry-Howard isomorphism.
It is also an addictive and puzzling game, I have been told.
Exference is a tool aimed at supporting developers writing Haskell code by generating expressions from a type, e.g.
The algorithm does a proof search specialized to the Haskell type system. In contrast to Djinn, the well known tool with the same general purpose, Exference supports a larger subset of the Haskell type system - most prominently type classes. The cost of this feature is that Exference makes no promise regarding termination (because the problem becomes an undecidable one; a draft of a proof can be found in the pdf below). Of course the implementation applies a time-out.
There are two primary use-cases for Exference:
The current implementation is functional and works well. The most important aspect that still could use improvement is the performance, but it would probably take a slightly improved approach for the core algorithm (and thus a major rewrite of this project) to make significant gains.
The project is actively maintained; apart from occasional bug-fixing and general maintenance/refactoring there are no major new features planned currently.
Try it out by on IRC(freenode): exferenceBot is in #haskell and #exference.
|Report by:||Jurriaan Hage|
|Participants:||Brian Vermeer, Gerben Verburg|
Holmes is a tool for detecting plagiarism in Haskell programs. A prototype implementation was made by Brian Vermeer under supervision of Jurriaan Hage, in order to determine which heuristics work well. This implementation could deal only with Helium programs. We found that a token stream based comparison and Moss style fingerprinting work well enough, if you remove template code and dead code before the comparison. Since we compute the control flow graphs anyway, we decided to also keep some form of similarity checking of control-flow graphs (particularly, to be able to deal with certain refactorings).
In November 2010, Gerben Verburg started to reimplement Holmes keeping only the heuristics we figured were useful, basing that implementation on haskell-src-exts. A large scale empirical validation has been made, and the results are good. We have found quite a bit of plagiarism in a collection of about 2200 submissions, including a substantial number in which refactoring was used to mask the plagiarism. A paper has been written, which has been presented at CSERC’13, and should become available in the ACM Digital Library.
The tool will be made available through Hackage at some point, but before that happens it can already be obtained on request from Jurriaan Hage.
<J.Hage at uu.nl>
|Report by:||Bastiaan Heeren|
|Participants:||Johan Jeuring, Alex Gerdes, Josje Lodder, Hieke Keuning|
|Status:||experimental, active development|
Ideas (Interactive Domain-specific Exercise Assistants) is a joint research project between the Open University of the Netherlands and Utrecht University. The project’s goal is to use software and compiler technology to build state-of-the-art components for intelligent tutoring systems (ITS), learning environments, and applied games. The ‘ideas’ software package provides a generic framework for constructing the expert knowledge module (also known as a domain reasoner) for an ITS or learning environment. Domain knowledge is offered as a set of feedback services that are used by external tools such as the digital mathematical environment (first/left screenshot) and the Math-Bridge system. Over the last ten years, we have developed several domain reasoners based on this framework, including reasoners for mathematics, linear algebra, statistics, propositional logic, for learning Haskell (the Ask-Elle programming tutor) and evaluating Haskell expressions and evaluating microcontroller I/O expressions, and for practicing communication skills (the serious game Communicate!, second/right screenshot).
We have continued working on the domain reasoners that are used by our programming tutors. The Ask-Elle functional programming tutor lets you practice introductory functional programming exercises in Haskell. We have extended this tutor with QuickCheck properties for testing the correctness of student programs, and for the generation of counterexamples. We have analysed the usage of the tutor to find out how many student submissions are correctly diagnosed as right or wrong.
We have started with the Advise-Me project (Automatic Diagnostics with Intermediate Steps in Mathematics Education), which is a Strategic Partnership in EU’s Erasmus+ programme. In this project we develop innovative technology for calculating detailed diagnostics in mathematics education, for domains such as ‘Numbers’ and ‘Relationships’. The technology is offered as an open, reusable set of feedback and assessment services. The diagnostic information is calculated automatically based on the analysis of intermediate steps.
We are continuing our research in various directions. We are investigating feedback generation for axiomatic proofs for propositional logic. We also want to add student models to our framework and use these to make the tutors more adaptive, and develop authoring tools to simplify the creation of domain reasoners.
The library for developing domain reasoners with feedback services is available as a Cabal source package. The latest release has support for constructing constraint-based tutors, besides the model-tracing tutors based on problem-solving procedures that are expressed in an extensible domain-specific language. We have written a tutorial on how to make your own domain reasoner with this library.
The Basic Haskell Cheat Sheet is a reference sheet with reminders of the most common Haskell features and functions condensed in two pages.
It covers a subset of the standard prelude, including examples of:
It does not aim to teach readers how to use the language, but simply remind readers of syntax, functions or caveats. It can be useful both to newcomers and oldtimers of the Haskell language.
Contributions are welcome, just submit a “pull request” on GitHub. Note the hard limit of two pages: to add something, something else should be removed.
|Report by:||Patrik Jansson|
|Participants:||Cezar Ionescu, Daniel Heurlin, Daniel Schoepe|
“Domain Specific Languages of Mathematics” is a project at Chalmers and UGOT which lead to a new BSc level course of the same name, including accompanying material for learning and applying classical mathematics (mainly basics of real and complex analysis). The main idea is to encourage the students to approach mathematical domains from a functional programming perspective: to identify the main functions and types involved and, when necessary, to introduce new abstractions; to give calculational proofs; to pay attention to the syntax of the mathematical expressions; and, finally, to organize the resulting functions and types in domain-specific languages.
The third instance of the course was carried out Jan–March 2018 in Gothenburg and the course material is available on github. The lecture notes have been collected in an informal “book” during the last six months; contributions and ideas are welcome!
Just two example to give a feeling for the contents:
Given the definition of “h : A -> is a homomorphism from
Op : A->A->A to op : B->B->B”:
H2(h, Op, op) = ∀ x. ∀ y. h (Op x y) == op (h x) (h y)
Then H2(exp,(+),(·)) says that ex+y == ex·ey for all x and y.
A somewhat longer example (two tweets):
See also the HCAR entry “Learn you a Physics” (→4.8.5) by a group of BSc students.
|Report by:||Erik Sjöström|
|Participants:||Oskar Lundström, Johan Johansson, Björn Werner|
Learn You A Physics is the result of a BSc project at Chalmers (supervised by P. Jansson) where the goal is to create an introductory learning material for physics aimed at programmers with a basic understanding of Haskell.
It does this by identifying key areas in physics with a well defined scope, for example dimensional analysis or single particle mechanics, and develops a domain specific language around each of these areas.
The implementation of these DSL’s are the meat of the learning material with accompanying text to explain every step and how it relates to the physics of that specific area.
The text is written in such a way as to be as non-frightening as possible, and to only require a beginner knowledge in Haskell. Inspiration is taken from Learn you a Haskell for Great Good and the project DSLsofMath (→4.8.4) at Chalmers and University of Gothenburg.
This tool by Ralf Hinze and Andres Löh is a preprocessor that transforms literate Haskell or Agda code into LaTeX documents. The output is highly customizable by means of formatting directives that are interpreted by lhs2TeX. Other directives allow the selective inclusion of program fragments, so that multiple versions of a program and/or document can be produced from a common source. The input is parsed using a liberal parser that can interpret many languages with a Haskell-like syntax.
The program is stable and can take on large documents.
The current version is 1.19 and has been released in April 2015. Development repository and bug tracker are on GitHub. The tool is mostly in plain maintenance mode, although there are still vague plans for a complete rewrite of lhs2TeX, hopefully cleaning up the internals and making the functionality of lhs2TeX available as a library.
Unicode strings need to be converted to a normalized form using the Unicode Character Database before they can be compared for equivalence. unicode-transforms is a pure Haskell implementation of Unicode normalization. The alternative is the text-icu package which provides this functionality as Haskell bindings to the ICU C++ implementation. unicode-transforms supports all forms of normalization (NFC/NFD/NFKC/NFKD) and supports the latest version of the Unicode standard (Unicode 9).
One of the goals of unicode-transforms was high performance. We have successfully achieved this goal for decompose (NFD/NFKD) forms, achieving performance close to, and in one benchmark even better than the C++ implementation (i.e. the text-icu package). Compose (NFC/NFKC) implementation is not yet optimized, and though the performance of compose is decent it is not at par with the C++ implementation. This is still open for anyone looking for a challenge to beat C++.
This library can potentially be integrated with the text package allowing us to keep text in a standard normalized form by default, thus freeing the Haskell programmers from worrying about explicit normalization. The library is available on Hackage under BSD3 license.
This rapid software development tool json-autotype interprets JSON data and converts them into Haskell module with data type declarations.
The generated declarations use automatically derived Aeson class instances to read and write data directly from/to JSON strings, and facilitate interaction with growing number of large JSON APIs.
Generated parser can be immediately tested on an input data:
The software can be installed directly from Hackage.
It uses sophisticated union type unification, and robustly interprets most ambiguities using clever typing.
The tool has reached maturity this year, and thanks to automated testing procedures it seems to robustly infer types for all JSON inputs considered valid by Aeson.
The tool now supports Elm output, and plans to support all members of Haskell family of languages.
The author welcomes comments and suggestions at <mjgajda at gmail.com>.
Ginger is a Haskell implementation of the Jinja2 HTML template language. Unlike most existing Haskell templating solutions, Ginger expands templates at run-time, not compile time; this is a deliberate design decision, intended to support a typical rapid-cycle web development workflow. Also unlike most existing Haskell HTML DSLs, Ginger is completely unaware of the DOM, and does not enforce well-formed HTML. Just like Jinja2, however, it does distinguish HTML source and raw values at the type level, meaning that HTML encoding is automatic and (mostly) transparent, avoiding the most common source of XSS vulnerabilities. For a quick impression of what Ginger syntax looks like:
All the important features of Jinja2 have been implemented, and the library is fully usable for production work. Some features of the original Jinja2 have been left out because the author considers them Pythonisms; others are missing simply because they haven’t been implemented yet. Additionally, some features have been added that are missing in Jinja2, such as lambdas, being able to use macros as functions or filters, ‘do‘ expressions, output indenting constructs, and “script mode”, switching Ginger into a syntax that is closer to a unityped scripting language than a template language.
Improvement that haven’t made it yet include TemplateHaskell support (which would allow programmers to compile Ginger templates directly into the binary, and perform template compilation at compile time rather than runtime), a built-in caching mechanism, and more configuration options. Contributions of any kind are very welcome.
WAI (Web Application Interface) is an application interface between web applications and handlers in Haskell. The Application data type is defined as follows:
That is, a WAI application takes two arguments: a Request and a function to send a Response. So, the typical behavior of WAI application is processing a request, generating a response and passing the response to the function.
Historically speaking, this interface made possible to develop handlers other than HTTP. The WAI applications can run through FastCGI (wai-handler-fastcgi), run as stand-alone (wai-handler-webkit), etc. But the most popular handler is based on HTTP, of course. The major HTTP handler for WAI is Warp which now provides both HTTP/1.1 and HTTP/2. TLS (warp-tls) is also available. New transports such as WebSocket (wai-websocket) and Event Source (wai-extra) can be implemented, too.
It is possible to develop WAI applications directly. For instance, Hoogle and Mighttpd2 take this way. However, you may want to use web application frameworks such as Apiary, MFlow, rest, Servant, Scotty, Spock, Yesod, etc.
WAI also provides Middleware:
WAI middleware can inspect and transform a request, for example by automatically gzipping a response or logging a request (wai-extra).
Since the last HCAR, WAI started using Builder of ByteString instead of Builder of blaze-builder. Because they are identical, no backward compatibility issue happens.
Warp is a high performance, easy to deploy HTTP handler for WAI (→4.10.1). Its supports both HTTP/1.1 and HTTP/2.
Since the last HCAR, no major changes were made.
|Report by:||Michael Snoyman|
|Participants:||Greg Weber, Luite Stegeman, Felipe Lessa|
Yesod is a traditional MVC RESTful framework. By applying Haskell’s strengths to this paradigm, Yesod helps users create highly scalable web applications.
Performance scalability comes from the amazing GHC compiler and runtime. GHC provides fast code and built-in event-based asynchronous IO.
But Yesod is even more focused on scalable development. The key to achieving this is applying Haskell’s type-safety to an otherwise traditional MVC REST web framework.
Of course type-safety guarantees against typos or the wrong type in a function. But Yesod cranks this up a notch to guarantee common web application errors won’t occur.
When type safety conflicts with programmer productivity, Yesod is not afraid to use Haskell’s most advanced features of Template Haskell and quasi-quoting to provide easier development for its users. In particular, these are used for declarative routing, declarative schemas, and compile-time templates.
MVC stands for model-view-controller. The preferred library for models is Persistent (→4.11.1). Views can be handled by the Shakespeare family of compile-time template languages. This includes Hamlet, which takes the tedium out of HTML. Both of these libraries are optional, and you can use any Haskell alternative. Controllers are invoked through declarative routing and can return different representations of a resource (html, json, etc).
Yesod is broken up into many smaller projects and leverages Wai (→4.10.1) to communicate with the server. This means that many of the powerful features of Yesod can be used in different web development stacks that use WAI such as Scotty and Servant.
Since the last HCAR, we’ve released version 1.6, the first breaking version of Yesod since September 2014. Most code will continue to work unchanged, but improvements have been added to Yesod’s monad transformer implementation, as well as adding some long-awaited cleanups.
The Yesod team is quite happy with the current level of stability in Yesod. Since the 1.0 release, Yesod has maintained a high level of API stability, and we intend to continue this tradition. Future directions for Yesod are now largely driven by community input and patches. We’ve been making progress on the goal of easier client-side interaction, and have high-level interaction with languages like Fay, TypeScript, and CoffeScript. GHCJS support is in the works.
The Yesod site (http://www.yesodweb.com/) is a great place for information. It has code examples, screencasts, the Yesod blog and — most importantly — a book on Yesod.
|Report by:||Doug Beardsley|
|Participants:||Gregory Collins, Greg Hale, and others|
The Snap Framework is a web application framework built from the ground up for speed, reliability, stability, and ease of use. The project’s goal is to be a cohesive high-level platform for web development that leverages the power and expressiveness of Haskell to make building websites quick and easy.
Snap continues to see active use in industry and continued support from the development team. If you would like to contribute, get a question answered, or just keep up with the latest activity, stop by the #snapframework IRC channel on Freenode.
MFlow is a Web framework of the kind of other functional, stateful frameworks like WASH, Seaside, Ocsigen or Racket. MFlow does not use continuation passing properly, but a backtracking monad that permits the synchronization of browser and server and error tracing. This monad is on top of another “Workflow” monad that adds effects for logging and recovery of process/session state. In addition, MFlow is RESTful. Any GET page in the flow can be pointed to with a REST URL.
A paper describing the MFlow internals has been published in The Monad Reader issue 23.
The PureScript language features Haskell-like syntax, type classes with functional dependencies, rank-n types, and row polymorphism with a form of polymorphic labels.
The PureScript compiler can be downloaded from purescript.org, or compiled from source from Hackage.
Sprinkles is a “zero programming web development framework”, intended for building content-centric server-site websites in a declarative fashion.
As such, Sprinkles sits in a unique position in between static site generators such as Jekyll, Hakyll, etc., and fully dynamic CMS solutions like Ghost, WordPress, etc.
A Sprinkles website consists of a project file in YAML format, a set of templates (using Ginger, a Haskell implementation of the Jinja HTML template language), and static files such as stylesheets, images, and client-side scripts. Data can be loaded from SQL databases, local files, HTTP, or local shell scripts, and Sprinkles supports a wide range of input formats, including JSON, YAML, HTML, Markdown, LaTeX, and even DOCX. The heart of a project file is a list of routes, each specifying a list of backend data sources to query, the output of which then gets bound to a template variable.
Unlike a static site generator, Sprinkles generates its HTML output on the fly, so there is no build step, you just deploy your updated project files to the server, restart the Sprinkles process, and your new site is live. Unlike a classic CMS, however, there is no admin area; instead, you manage your data externally.
This approach has a few advantages, most notably, it makes Sprinkles more secure, because no admin area is exposed that could be exploited to escalate from compromising the public-facing part to gain write access; write access is implemented separately, via separate channels (typically an SSH connection).
Various workflows are possible, e.g.:
Sprinkles comes with a built-in Warp server, and this is the preferred deployment option, but CGI, SCGI and FastCGI are also supported. A “bake” mode has been added recently that turns Sprinkles into a static site generator, so a Jekyll-style workflow is now also possible.
The nginx-haskell-module allows using typed Haskell handlers from within custom Nginx configurations. It provides several Nginx directives that correspond to where Haskell code is applied and what kind of task it solves:
Here, “a string-like result” is an umbrella term for various Haskell string-like implementations like String and ByteString, perhaps wrapped inside IO Monad. Typed Haskell handlers give a strong guarantee that underlying code will cause no IO specific side effects thus making sure that Nginx will not stop working due to unpredictably long-running IO code, which is extremely crucial for this popular web server.
On the other hand, when effectful code is desirable, it can be declared with directive haskell_run_async, which runs Haskell code asynchronously and won’t stop the Nginx world. Moreover, the module provides directive haskell_run_service for running custom asynchronous “services” that are not bound to requests: this makes it possible to program interesting solutions like Nginx-specific service discovery (see a reference to an advanced example below). An asynchronous service results are available in request-specific Nginx configuration areas (e.g. location) via an Nginx variable that holds a string, which, on a deeper level, may wrap a typed data (or JSON, or other representations).
Basically, a service results variable is stored in a worker-specific memory, but with directive haskell_service_var_in_shm it gets its place in a shared memory and becomes available from all Nginx workers. In conjunction with directive haskell_service_var_update_callback, this allows programming custom ad-hoc solutions when a Haskell service’s results are needed in another Nginx module. On the Github project page there is an advanced example dynamicUpstreams that implements such an approach.
Starting from version 1.4.0 of the module, services that share their results in shared memory become shared themselves. This means that only one worker process really runs a shared service, while services on the other workers wait on locks until the active worker exits or dies.
Starting from version 1.8.0 of the module, services can be managed by custom hooks declared with directive haskell_service_hook. With the hooks, it is possible to build custom APIs for managing services of arbitrary complexity. A similar directive haskell_service_update_hook allows for writing C plugins that run in a worker’s main thread upon every update from the service. To access internal Nginx global data in a plugin, the Haskell module provides several opaque pointers, in particular ngxCyclePtr, ngxUpstreamMainConfPtr, and ngxCachedTimePtr.
The module provides other two directives haskell_var_nocacheable and haskell_var_compensate_uri_changes that make Nginx error_page redirections almost Turing-complete. It is achieved by letting them loop without limits on number of cycles (by the second directive) and ensuring that loop-specific variables get updated between iterations (by the first directive). The technique of Turing-complete error_page redirections is used in an advanced example labeledMediaRouting.
Haskell implementation of popular Perl template processing system.
Perl Template Toolkit is mainly used for web development.
This port includes such features as:
In the next release it is planned to include support for custom methods, filters and functions in templates.
Since the last HCAR, persistent has mostly experienced bug fixes, including recent fixes and increased backend support for the new flexible primary key type.
Haskell has many different database bindings available, but most provide few useful static guarantees. Persistent uses knowledge of the data schema to provide a type-safe interface to the database. Persistent is designed to work across different databases, currently working on Sqlite, PostgreSQL, MongoDB, MySQL, Redis, and ZooKeeper.
Persistent provides a high-level query interface that works against all backends.
selectList [ PersonFirstName ==. "Simon",
PersonLastName ==. "Jones"] 
The result of this will be a list of Haskell records.
Persistent can also be used to write type-safe query libraries that are specific. esqueleto is a library for writing arbitrary SQL queries that is built on Persistent.
Persistent is in a stable, feature complete state. Future plans are only to increase its ease for the places where it can be easily used:
Persistent users may also be interested in Groundhog, a similar project.
Persistent is recommended to Yesod (→4.10.3) users. However, there is nothing particular to Yesod or even web development about it. You can have a type-safe, productive way to store data for any kind of Haskell project.
The squeal-postgresql package is a library providing a deep embedding of PostgreSQL in Haskell. Squeal makes use of lots of features and ideas in Haskell such as:
The point is not to use them in particularly new ways, but for very practical purposes. DataKinds are used to embed the SQL type and schema system into Haskell. OverloadedLabels are used to refer to tables and columns. Indexed monads are used to track changing schema types. Generics are used to easily marshal data between Haskell product and record types and SQL parameter and row types. GADTs are used for joins, aliased expressions, heterogeneous lists and more.
However, in spite of these perhaps being formidable sounding concepts, it is much easier to learn them when there is a familiar pattern you can use, and that’s SQL. I believe that if a Haskeller knows SQL, then Squeal can be a gateway to learning these concepts. That’s because Squeal tries to be (mostly) faithful to SQL.
If the Squeal expressions are basically SQL, then why not just use SQL? Squeal adds strong, static typing and decomposability, which helps to develop and maintain an application. Change your schema and the compiler will tell you where you must change your queries and manipulations. Queries and manipulations with common subparts can be factored for reusability. You can even write typed schema migration definitions using Squeal.
Squeal is still experimental and I would love to get some real users and contributors. Send me bug reports and feature requests. There are still many missing features that I have plans to include.
Since the last HCAR, Squeal has released version 0.2.1. This is a minor update over version 0.2 which was released late March. The difference between these two versions is solving an issue where alias identifiers could conflict with reserved words in PostgreSQL. To fix the issue, alias identifiers are now quoted. Thanks to Petter Rasmussen for the fix.
The version 0.2 was released March 26th and has the following changes:
Bringing SQL constraints to the type level means that more of the schema is statically known. In version 0.1 column constraints – which boil down to having ‘DEFAULT‘ or not – were at the type level, but they were confusingly named.
The :=> type operator is intended to helpfully connote a constraint relation. It’s also used for table constraints which are new in version 0.2:
Another change in the constraint system was the removal of column constraints from query and manipulation results, as result columns don’t support a notion of DEFAULT. This necessitates a distinction between TableTypes which have both column and table constraints and RelationTypes which have neither.
Migrations are a hot topic and many people have requested this feature. From version 0.2, Squeal adds support for linear, invertible migrations. That is, a migration is a named, invertible, schema-tracking computation:
And, Migrations can be put together in an “aligned” list:
These aligned lists are free categories and might look familiar from the reflections without remorse technique, which uses their cousins, aligned sequences.
In the context of migration, they allow one to chain new migrations as a schema evolves over time. Migrations’ execution is tracked in an auxiliary migrations table. Migration lists can then be run or rewinded.
Regarding aliases, in Squeal 0.1, we had different typeclasses HasColumn and HasTable to indicate that a table has a column or that a schema has a table. In Squeal 0.2 this has been unified to a single typeclass,
Support for array types has been added to Squeal 0.2 through the ’PGfixarray and ’PGvararray PGTypes. Array values can be constructed using the ‘array‘ function and can be encoded from and decoded to Haskell Vectors.
Squeal 0.2 provides a monad transformer PoolPQ that’s an instance of MonadPQ. The resource-pool library is leveraged to provide striped pools of Connections. PoolPQ should be a drop in replacement for running Manipulations and Querys with PQ.
Squeal 0.2 supports a simple transaction control language. A computation in MonadPQ can be called transactionally with different levels of isolation. Additionally, a schema changing computation, a data definition, can be run in a transaction. Running a computation in a transaction means that all SQL statements will be rolled back if an exception is encountered.
The above changes required major and minor changes to Squeal DSL functions. Please consult the documentation.
|Report by:||Kei Hibino|
|Participants:||Shohei Murayama, Shohei Yasutake, Sho Kuroda and Kazu Yamamoto|
Haskell Relational Record (HRR) is open-source libraries which provides a pragmatic embedded domain specific language to generate SQL. It supports a large part of the SQL standard which includes outer joins and aggregations with type safety, and also supports pragmatic but type-unsafe features like placeholder, correlation and direct SQL embedding interfaces. Direct SQL embedding interfaces allow database-system-dependent SQL code fragments.
HRR also provides template-haskell which generates record types and relation types definitions from relational-database schemas. Supported schemes of relational-database engines are PostgreSQL, MySQL, SQLite, IBM DB2, Microsoft SQL Server and OracleSQL.
HRR is publicly developed on github since 2013, and its release is publicly announced to Haskell community in December 2014. HRR has been in use at Asahi Net (Internet Service Provider in Japan) since March 2013, and more than three years of production use demonstrates its stability and usability. HRR is actively developed, and technical support is provided in Haskell-jp (→6.13).
YeshQL is a library to bridge the Haskell / SQL gap by implementing a quasi-quoter that allows programmers to write SQL queries in plain SQL, adding metainformation as structured SQL comments. The latter allows the quasi-quoter to generate a type-safe API for these queries. YeshQL uses HDBC for the database backends, but doesn’t depend on any particular HDBC driver.
The approach was stolen from the YesQL library for Clojure, and adapted to be more idiomatic in Haskell.
An example code snippet might look like this:
Contributions of any kind are more than welcome.
|Report by:||Nikos Karagiannidis|
|Status:||Stable, active development|
DBFunctor is a library for Functional Data Management of tabular data. What does this mean?
It means that whenever you have a data analysis/preparation/transformation task and you want to do it with Haskell type-safe code, that you enjoy, love and trust so much, now you can!
Moreover, whenever you have a data set in plain CSV files and you want to write a Haskell application that needs to analyze these data by queries, or apply any data transformations on them; you no longer need to install a database, import the files into the database and then use some Haskell library, in order to query the data in the database. You can query and transform the data stored in the CSV files in-place, within your Haskell application; generating new CSV files whenever you wish, by using the DBFunctor package and the powerful Embedded Domain Specific Language – called Julius – that comes with it.
ETL stands for Extract Transform and Load and is the standard technology for accomplishing data management tasks in Data Warehouses / Data Marts and in general for preparing data for any analytic purposes (Ad hoc queries, data exploration/data analysis, Reporting and Business Intelligence, feeding Machine Learning algorithms, etc.). ELT is a newer variation of ETL and means that the data are first Loaded into their final destination and then the data Transformation runs in-place (as opposed to running at a separate staging area on possibly a different server)).
DBFunctor should be used whenever data manipulation/transformation tasks over tabular data must be performed and we wish to perform them with Haskell code, yielding all the well-known (to Haskellers) benefits from doing that.
DBFunctor provides an in-memory data structure called RTable, which implements the concept of a Relational Table (which, simply put, is a set of tuples) and all relevant relational algebra operations (selection, projection, inner join, outer joins, aggregations, group by, set operations etc.).
Moreover, it implements the concepts of Column Mapping (for deriving new columns based on existing ones – by splitting, merging, or with any other possible combination using a lambda expression or a function to define the new value) and that of the ETL Mapping, which is the equivalent of a “mapping” in an ETL tool (like Informatica, Talend, Oracle Data Integrator, SSIS, Pentaho, etc.). With this powerful construct, one can build arbitrary complex data pipelines, which can enable any type of data transformations and all these by writing Haskell code.
With the term “tabular data” we mean any type of data that can be mapped to an RTable (e.g., CSV (any delimiter), DB Table/Query, JSON etc). Essentially, for a Haskell data type a to be “tabular”, one must implement the following functions:
These two functions implement the “logic” of transforming data type a to/from an RTable based on specific RTable Metadata, which specify the column names and data types of the RTable, as well as (optionally) the primary key constraint, and/or alternative unique constraints (i.e., similar information provided with a CREATE TABLE statement in SQL).
By implementing these two functions, data type a essentially becomes an instance of the type class RTabular and thus can be transformed with the DBFunctor package. Currently, we have implemented a CSV data type (based one the [Cassava](https://github.com/haskell-hvr/cassava) library), in order to enable data transformations over CSV files.
Apart from supporting other “tabular” data types (e.g., database tables/queries) our ultimate goal is, eventually to make DBFunctor the first declarative library for ETL/ELT, by exploiting the virtues of functional programming and Haskell strong type system in particular.
Here we use “declarative” in the same sense that SQL is a declarative language for querying data. You only have to state what data you want to be returned and you don’t care about how this will be accomplished – the DBMS engine does this for you behind the scenes.
In the same manner, ideally, one should only need to code the desired data transformation from a source schema to a target schema, as well as all the data integrity constraints and business rules that should hold after the transformation and not having to define all the individual steps for implementing the transformation, as it is the common practice today. This will yield tremendous benefits compared to common ETL challenges faced today and change the way we build data transformation flows. Just to name a few:
The above is inspired by the theoretical work on Categorical Databases by David Spivak.
|Report by:||Andrey Mokhov|
|Participants:||Arseniy Alekseyev, Neil Mitchell|
|Status:||usable, active development|
Alga is a library for algebraic manipulation of graphs in Haskell. The underlying theory is presented here.
Consider the following data type, which is defined in the top-level module Algebra.Graph of the library:
data Graph a = Empty
| Vertex a
| Overlay (Graph a) (Graph a)
| Connect (Graph a) (Graph a)
We can give the following semantics to the constructors in terms of the pair (V,E) of vertices and edges:
This figure shows examples of graph construction, where + and * stand for Overlay and Connect.
We can give an algebraic semantics to the graph construction primitives by defining the type class:
class Graph g where
type Vertex g
empty :: g
vertex :: Vertex g -> g
overlay :: g -> g -> g
connect :: g -> g -> g
Instances of the type class obey the following laws:
This algebraic structure corresponds to unlabelled directed graphs: every expression represents a graph, and every graph can be represented by an expression. The library defines several law-abiding instances and polymorphic graph manipulation functions.
The library is documented, tested and usable. It is under active development, so the API is subject to change.
JudyGraph is a graph library that can handle very dense graphs with a million edges per node. As the name suggests, the library is based on Judy arrays, which is a very fast and memory efficient key-value storage. The properties of this key-value storage guided the development in that node and edge data had to be compressed into 32 bit values with typeclasses. The lowest bits of the edge are used to enumerate several edges with the same property (which is encoded in the higher bits). The documentation of Judy Arrays promises very little CPU cache misses when only the lowest bits are used successively. Another trick to squeeze edge data into 32 bit is to interpret an edge differently depending on the node index of the origin node. Depending on the range in which the index is the edge is interpreted differently.
The library was developed as an alternative for the Neo4j graph database. That’s why it also has a query language that resembles Cypher:
Last year at Hal Leipzig, I showed that storing the ghc-core code of 1000s of libraries in a graph could be of great help for Haskell tooling. The goal is a function search engine that can get better search results by using PageRank. It should also be possible to click together little programs, once a function is picked. The doc folder contains the slides of this talk.
Currently the library is targeted to load a large graph from csv-files (that fits into memory) and to achieve fast queries and do some post processing like adding or updating edges, but no deletion. The future plan is to implement persistence, get ACID guarantees and implement missing Cypher commands. I would be glad for hints.
The conduit package is one of the most popular approaches to solving the streaming data problem in Haskell. It provides a composable, resource-safe, and constant memory solution to many common problems. With the well developed conduit ecosystem around it, you can easily deal with a variety of data sources (files, memory, HTTP, TCP), file formats (XML, YAML, JSON, CSV), advanced abstractions around parallel processing and concurrency, and have access to a wide range of helpful library functions to choose from.
Since the last HCAR, conduit has had a new major release, version 1.3. The changes include:
This results in a simpler core, more consistent API, and a more batteries-included experience in the conduit library itself.
Under the surface, conduit makes use of coroutines and an inlined free monad transformer approach to allow for a high level of flexibility in conduit composition. This is as opposed to other approaches, like list-t or stream fusion, which trade in some of that flexibility for performance. Some of these ideas were explored in http://www.yesodweb.com/blog/2016/02/first-class-stream-fusion. The end result is that, for most I/O based applications, conduit provides a great trade-off. For fully CPU-bound operations, you’ll likely want to consider using something less flexible but higher performance.
Conduit is intended to be a replacement to usage of lazy I/O in Haskell code, allowing us to work on large data sets, ensure resources are cleaned up promptly, and retain composable programs. Please see the aforementioned tutorial for many examples of how this works.
The conduit package is designed to work well with the resourcet package, which allows for guaranteeing resource finalization in continuation-based monads. This is one of the main simplifications that conduit achieved versus previous streaming approaches, such as the enumerator package and other left-fold iterator approaches.
There is a rich ecosystem of libraries available to be used with conduit, including cryptography, network communications, serialization, XML processing, and more.
Many conduit libraries are available via Hackage, Stackage Nightly, and LTS Haskell (just search for the word conduit). The main repository includes a tutorial on using the package (https://github.com/snoyberg/conduit#readme).
Conduit includes a stream fusion framework for optimizing away intermediate data creation. Unfortunately, these optimizations do not always trigger due to problems with rewrite rule firing. There is some consideration around making this stream fusion a first-class entity that developers can rely upon. See http://www.yesodweb.com/blog/2016/02/first-class-stream-fusion and https://github.com/snoyberg/foreach.
The transactional trie is a contention-free hash map for Software Transactional Memory (STM). It is based on the lock-free concurrent hash trie.
“Contention-free” means that it will never cause spurious conflicts between STM transactions operating on different elements of the map at the same time. Compared to simply putting a |HashMap| into a |TVar|, it is up to 8x faster and uses 10x less memory.
A non-blocking concurrent map implementation based on the lock-free concurrent hash trie (aka Ctrie).
A hash trie is a tree whose leaves store key-value bindings and whose nodes are implemented as arrays. The concurrent trie extends the hash trie by adding indirection nodes above every array node. Indirection nodes have the property that they stay in the trie even if the nodes above or below them change. When inserting an element into the trie, instead of directly modifying an array node, an updated copy of the array node is created and an atomic compare-and-swap operation on the indirection node is used to switch out the old array node for the new one. If the compare-and-swap operation fails, the insert is retried from the beginning. This simple scheme, where indirection nodes act as barriers for concurrent modification, ensures that there are no lost updates or race conditions of any kind, while keeping all operations completely lock-free.
A more thorough discussion, including proofs of linearizability and lock- freedom, can be found in the papers by Prokopec et al.
The Random Access Zipper (RAZ) is a data structure for representing sequences with efficient indexing and edits.
The paper introducting it (with an implementation in OCaml) reported performance that is competitive with the more common Finger Tree structure.
I have translated it in Haskell, and started implementing the same interface as Data.Sequence from containers in Data.Raz.Sequence.
I reproduced the benchmarks from the paper as well as those of containers. On average, Haskell’s raz is slightly slower than OCaml’s, but faster than containers for many operations.
The Data.Raz.Sequence module remains to be finished to fully match Data.Sequence.
There are certainly lots of optimizations opportunities.
Raz requires randomness, which results in some awkward types in Haskell on the one hand (or, internal (ab)use of unsafePerformIO to implement a pure interface), but this explicitness can be informative on the other hand, though I am not yet certain how that information may be usefully exploited.
The generic-random library automatically derives random generators for most datatypes. It can be used in testing for example, in particular to define instances of QuickCheck’s Arbitrary.
The module Generic.Random.Generic leverages GHC.Generics to handle common boilerplate in instances of Arbitrary for simple datatypes.
However, for recursive datatypes, a naive generator is likely to have problematic issues: non-termination, inconveniently biased distributions (too large, too small, too full). Generic.Random.Data derives Boltzmann samplers, introduced by Duchon et al. (2004). They produce finite values of a given type and about a given size (the number of constructors) in linear time; the distribution is uniform when conditioned to a fixed size: two values with the same size occur with the same probability. An implementation can now be found in the boltzmann-samplers library (it has been split out of generic-random).
Slowness of Boltzmann samplersI found out that the FEAT library, which can derive random generators for the same class of datatypes producing values of a given size exactly and uniformly distributed, has much better performance as well.
A more detailed explanation can be found at https://github.com/Lysxia/generic-random/issues/6.
In theory, Boltzmann samplers have the better asymptotic complexity, but they come with an overhead that appears hard to get rid of; boltzmann-samplers only catches up to FEAT on data sizes that seem too large to be practical (thousands of constructors).
Due to that, I have lost some motivation to go forward with boltzmann-samplers. I still remain open to discussion and suggestions.
Generic and applicative interfaceIn spite of the above issues, I’ve started a rework of boltzmann-samplers using GHC.Generics rather than SYB, and a more general way to obtain generators from an applicative specification.
The branch can currently be found at: https://github.com/Lysxia/boltzmann-samplers/tree/generics.
ADPfusion provides a low-level domain-specific language (DSL) for the formulation of dynamic programs with emphasis on computational biology and linguistics. We follow ideas established in algebraic dynamic programming (ADP) where a problem is separated into a grammar defining the search space and one or more algebras that score and select elements of the search space. The DSL has been designed with performance and a high level of abstraction in mind.
ADPfusion grammars are abstract over the type of terminal and syntactic symbols. Thus it is possible to use the same notation for problems over different input types. We directly support grammars over strings, sets (with boundaries, if necessary), trees, as well as profile hidden Markov models, and profile stochastic context-free grammars. Linear, context-free and multiple context-free languages are supported, where linear languages can be asymptotically more efficient both in time and space. ADPfusion is extendable by the user without having to modify the core library. This allows users of the library to support novel input types, as well as domain-specific index structures. Currently, ADPfusion, as a core library, provides support for linear string-based grammars. All above-mentioned variants are provided as extension packages and can serve as a guideline on how to expand the capabilities of ADPfusion.
As an example of ADPfusion in practice, consider a grammar that recognizes palindromes. Given the non-terminal p, as well as parsers for single characters c and the empty input e, the production rule for palindromes can be formulated as p ->c p c || e.
The corresponding ADPfusion code is similar:
We need a number of combinators as “glue” and additional evaluation functions f, g, and h. With f c1 p c2 = p && (c1=c2) scoring a candidate, g e = True, and h xs = or xs determining if the current substring is palindromic.
This effectively turns the grammar into a memo-function that then yields the optimal solution via a call to axiom p. Backtracking for co- and sub-optimal solutions is provided as well. The backtracking machinery is derived automatically and requires the user to only provide a set of pretty-printing evaluation functions.
As of now, code written in ADPfusion achieves performance close to hand-optimized C, and outperforms similar approaches (Haskell-based ADP, GAPC producing C++) thanks to stream fusion. The figure shows running times for the Nussinov algorithm.
The entry on generalized Algebraic Dynamic Programming (→4.12.9) provides information on the associated high-level environment for the development of dynamic programs.
|Report by:||Christian Höner zu Siederdissen|
|Participants:||Sarah J. Berkemer|
|Status:||usable, active development|
Generalized Algebraic Dynamic Programming (gADP) provides a solution for high-level dynamic programs. We treat the formal grammars underlying each DP algorithm as an algebraic object which allows us to calculate with them. gADP covers dynamic programming problems of various kinds: (i) we include linear, context-free, and multiple context-free languages (ii) over sequences, trees, sets, and profile stochastic structures (profile HMMs and profile SCFGs); and (iii) provide abstract algebras to combine grammars in novel ways.
Below, we describe the highlights our system offers in more detail:
We have developed a theory of algebraic operations over linear and context-free grammars. This theory allows us to combine simple “atomic” grammars to create more complex ones.
With the compiler that accompanies our theory, we make it easy to experiment with grammars and their products. Atomic grammars are user-defined and the algebraic operations on the atomic grammars are embedded in a rigorous mathematical framework.
Our immediate applications are problems in computational biology and linguistics. In these domains, algorithms that combine structural features on individual inputs (or tapes) with an alignment or structure between tapes are becoming more commonplace. Our theory will simplify building grammar-based applications by dealing with the intrinsic complexity of these algorithms.
We provide multiple types of output. LaTeX is available to those users who prefer to manually write the resulting grammars. Alternatively, Haskell modules can be created. TemplateHaskell and QuasiQuoting machinery is also available turning this framework into a fully usable embedded domain-specific language. The DSL or Haskell module use ADPfusion (→4.12.8) with multitape extensions, delivering “close-to-C” performance.
Most dynamic programming frameworks we are aware of deal with problems over sequence data. There are, however, many dynamic programming solutions to problems that are inherently non-sequence like. Hamiltonian path problems, finding optimal paths through a graph while visiting each node, are a well-studied example.
We have extended our formal grammar library to deal with problems that can not be encoded via linear data types. This provides the user of our framework with two benefits, easy encoding of problems based on set-like inputs and construction of dynamic programming solutions. On a more general level, the extension of ADPfusion and the formal grammars library shows how to encode new classes of problems that are now gaining traction and are being studied.
If, say, the user wants to calculate the shortest Hamiltonian path through all nodes of a graph, then the grammar for this problem is:
which states that a path s is either extended by a node n, or that a path is started by having just a first, single node n. Functions f and g evaluate the cost of moving to the new node. gADP has notions of sets with interfaces (here: for s) that provide the needed functionality for stating that all nodes in s have been visited with a final visited node from which an edge to n is to be taken.
Tree grammars are important for the analysis of structured data common in linguistics and bioinformatics. Consider two parse trees for English and German (from: Berkemer et al. General Reforestation: Parsing Trees and Forests) and the node matching probabilities we gain when trying to align the two trees:
We can create the parse trees themselves with a normal context-free language on sequences. We can also compare the two sentences with, say, a Needleman-Wunsch style sequence alignment algorithm. However, this approach ignores the fact that parse trees encode grammatical structure inherent to languages. The comparison of sentences in English or German should be on the level of the structured parse tree, not the unstructured sequence of words.
Our extension of ADPfusion (→4.12.8) to forests as inputs allows us to deal with a variety of problems in complete analogy to sequence-based dynamic programming. This extension fully includes grammar products, and automatic outside grammars.
Our third contribution to high-level and efficient dynamic programming is the ability to automatically construct Outside algorithms given an Inside algorithm. The combination of an Inside algorithm and its corresponding Outside algorithm allow the developer to answer refined questions for the ensemble of all (suboptimal) solutions.
The image below depicts one such automatically created grammar that parses a string from the Outside in. T and C are non-terminal symbols of the Outside grammar; the production rules also make use of the S and B non-terminals of the Inside version.
One can, for example, not only ask for the most efficient path through all cities on a map, but also answer which path between two cities is the most frequented one, given all possible travel routes. In networks, this allows one to determine paths that are chosen with high likelihood.
In both, linguistics and bioinformatics, a number of problems exist that can only be described with formal languages that are more powerful than context-free languages, but often have the form of two or more interleaved context-free languages (say: anbncn). In RNA biology, pseudoknotted structures can be modelled in this way, while in linguistics, we can model languages with crossing dependencies.
ADPfusion and the generalized Algebraic Dynamic Programming methodology have been extended to handle these kinds of grammars.
|Report by:||Christian Höner zu Siederdissen|
|Participants:||Maria Beatriz Walter Costa|
|Status:||usable, active development|
Here, we showcase an application developed using generalized Algebraic Dynamic Programming (→4.12.9).
Joint work with Maria Beatriz Walter Costa, Dan Tulpan, Peter F. Stadler, and Katja Nowick.
The MutationOrder program tries to solve the following problem: We are given two RNA input sequences: (i) an ancestral sequence, and (ii) an extant sequence which is related to the ancestral sequence but has undergone a number of mutations (that are typically thought of to be beneficial).
We now have to determine the most likely order in which single nucleotide mutations happened between two RNA sequences. The algorithm that answers this question is a variant of the travelling salesman problem. First, we need to keep track of all the mutations (nodes or “cities”) previously visited, instead of just the two nodes indicating the most recent and current change as these modify the cost of the current change. Second, it is biologically possible that one or more hidden nodes – corresponding to mutations and backmutations were visited. This in turns leads to a multi-stage histomorphism problem we solve with our algorithm.
|Report by:||Olle Fredriksson|
|Participants:||Spiros Boosalis, Oleg Grenrus, Tero Keinänen|
Earley is a parsing library that can parse all context-free grammars, including tricky ones for example with left-recursion. The grammars are specified in applicative style.
A new feature in the Earley library is language generation. Given a grammar and a list of allowed input tokens, Earley can generate the members of the language that the grammar generates. The following example shows the language generated by a Roman numerals grammar limited to the tokens ’V’, ’I’, and ’X’.
language (generator romanNumeralsGrammar "VIX")
|Report by:||Micha J. Gajda|
|Participants:||Micha Gajda, Kevin Cheung, Guru Devanla, and others|
Discussion in the DataHaskell community suggested that we need an extensive effort to make it easier to parse different file formats, and hasten the setup of DataHaskell projects.
Currently we have json-autotype (→4.9.3), and Frames library that autodetect file format, generate appropriate type description, and the parser.
We expanded our efforts to build type providers with xml-typelift library written by Kevin Cheung with advice of Michal - it generates type descriptions.
We also started building type-provider tool that will catalog the existing parsers for common file formats, and automaticaly generate import code. Prototype is available in GitHub repository.
Transient is a monad/applicative/Alternative with batteries included that brings the power of high level effects in order to reduce the learning curve and make the Haskell programmer productive. Effects include event handling/reactive, backtracking, extensible state, indeterminism, concurrency, parallelism, thread control and distributed computing, publish/subscribe and client/server side web programming among others.
All effects can be combined while maintaining algebraic and monadic composability using standard applicative, alternative and monadic combinators.
What is new in this report is:
Future work: Relay communications, Programmer-defined serialization, Server side HTML rendering
Streamly is a natural extension of Haskell lists to monadic streaming with concurrent composition:
You can fold streams concurrently.
Streams support nested and concurrent looping constructs. For example, to compute each square and the sum of squares concurrently:
The following example recursively lists a directory tree concurrently. To see the elegance of the API, just remove runStream and the asyncly combinator and the code now becomes regular IO monad code.
There is much more to Streamly, please see the tutorial included in the package, and the streaming-benchmarks (→4.12.15) repository on github for performance comparison. There is a lot left to do; contributions are needed and welcome.
There are quite a few Haskell streaming libraries providing streaming IO functionality. Apart from the difference in user level APIs they also use different design philosophies and the underlying stream or stream processor types. It is interesting to know how the different approaches compare with each other in terms of performance on micro-benchmarks. In addition to helping users in choosing a library, comparative performance measurement can also provide an insight into the strengths and weaknesses of the design approaches which can in turn help in choosing the best approach when building a new library. It can also help in finding performance issues and improving these libraries.
streaming-benchmarks package provides a common framework to fairly measure and compare the performance of the various monadic streaming libraries including vector, streamly (→4.12.14), streaming, pipes, conduit, machines and drinkery. The library also provides performance measurement of pure data structures like list and vector for a comparison with the monadic ones. The benchmarking code is pretty modular and new streaming libraries can be added easily. The figures in this section show some of the benchmarks, please see the README in the streaming-benchmarks GitHub repository for more details.
A word of caution for end users, these are micro benchmarks and whether they are significant for a particular use case in a macro setting depends on the contribution of the micro-benchmark cost to the overall performance of the application.
The proto-lens library provides an API for protocol buffers, a language-independent binary file format. Cabal (→4.2.1) and Stack (→4.2.2) projects can use proto-lens to autogenerate Haskell source bindings from the original protocol buffer specifications.
The library uses modern Haskell language and library patterns for simpler and safer code, including:
Version 0.3.0.0 of the library was recently released; it includes usability improvements to the API and generating prisms for "oneof" fields (sum types). Ongoing work includes better integration with gRPC and improving the type error messages.
|Report by:||Jost Berthold and Rita Loogen|
|Participants:||Rita Loogen, Lukas Schiller (Marburg), Jost Berthold (Sydney), Florian Fey (Münster), Yolanda Ortega-Mallén, Mercedes Hidalgo, Fernando Rubio, Alberto de la Encina (Madrid)|
Eden extends Haskell with a small set of syntactic constructs for explicit process specification and creation, including automatic process communication (via head-strict lazy lists) and synchronization. Higher-level coordination is achieved by defining skeletons, ranging from a simple parallel map to sophisticated master-worker schemes. Eden’s interface includes the concept of Remote Data, which provides implicit stream communication channels between processes to compose skeletons and define arbitrary communication topologies. A PA-monad enables the eager execution of user defined sequences of Parallel Actions in Eden.
Standard reference:Rita Loogen, Yolanda Ortega-Mallén, and Ricardo Peña: Parallel Functional Programming in Eden, JFP 15(3), 2005, pages 431–475.
Tutorial:Rita Loogen: Eden - Parallel Functional Programming in Haskell, in: V. Zsok, Z. Horvath, and R. Plasmeijer (Eds.): CEFP 2011, Springer LNCS 7241, 2012, pp. 142-206. (see also: www.mathematik.uni-marburg.de/~eden/?content=cefp)
Eden is currently implemented by modifications to the Glasgow-Haskell Compiler GHC, extending its runtime system to use multiple communicating instances with independent heap management. The implementation supports MPI (or PVM) in cluster environments, and a shared memory mode solely based on OS support (Windows/Linux) on multicore platforms. Source code of the modified GHC is available from http://github.com/jberthold/ghc; there are Eden variants of every major/minor GHC version since 2008, which can be built using only the usual GHC build tools (and MPI if desired).
Building on this runtime support, the Haskell package edenmodules defines the language, and edenskels provides a library of parallel skeletons. The Eden libraries are available via Hackage and from http://hex.mathematik.uni-marburg.de:8080/.
As an alternative, a library-only implementation of Eden was recently developed by Florian Fey. This implementation uses the network-fancy package for networking, and the packman package for serialising Haskell heap objects.
If you want to use Eden, we will be happy to provide support, and delighted to receive your contributions to its implementation — please contact us via github or e-mail.
The Eden trace viewer tool EdenTV provides a visualisation of Eden program runs. Visual post-mortem activity profiles are produced for processing elements (machines), Eden processes and threads, including message traffic. EdenTV is written in Haskell and is freely available on hackage. It can also display thread views of GHC eventlogs.
A second trace viewer tool is Eden-Tracelab, by Bastian Reitemeier. It can visualise larger trace files by using an external database. See brtmr.de/2015/10/17/introducing-eden-tracelab.html.
The Eden skeleton library contains various skeletons for parallel processing, including parallel maps, workpools, divide-and-conquer, and common process topologies. Take a look on the Eden pages or the haddock documentation on hackage for an overview.
Eden’s simple API of explicit processes with implicit communication enables rapid prototyping for parallel programs at both the skeleton/library and the application level. A range of research has investigated Eden skeletons library optimisations and refinements. Eden has been used to solve optimisation problems in continuous domains. This has been done by defining parallel skeletons dealing with different bioinspired metaheuristics, such as Particle Swarm Optimization, Differential Evolution, and Artificial Bee Colony.
|Report by:||Kei Davis|
|Participants:||Dean Prichard, David Ringo, Loren Anderson, Jacob Marks|
The main project goal is the demonstration of a light-weight, higher-order, polymorphic, pure functional language implementation in which we can experiment with automatic parallelization strategies, varying degrees of default function and constructor strictness, and lightweight instrumentation.
We do not consider speculative or eager evaluation, but do plan to infer strictness by program analysis, so potential parallelism is dictated by the specified degree of default strictness, language constructs for parallelism, and program analysis.
Our approach is similar to that of the Intel Labs Haskell Research Compiler: we use GHC as a front-end to generate STG, then exit to our own back-end compiler; additionally, we have native Mini-Haskell and STG front-ends. As in their case we do not attempt to use the GHC runtime. Our implementation is light-weight in that we are not attempting to support or recreate the vast functionality of GHC and its runtime. This approach is also similar to Don Stewart’s except that we generate C instead of Java.
Currently we have a fully functioning serial implementation and a primitive proof-of-design parallel implementation. The most recent major development was the bridge between GHC and our system. Thus we can now compile and run Haskell programs with simple primitive and algebraic data types using GHC or our own mini-Haskell front-end.
Additionally, we have developed a new strictness analysis technique that is currently being implemented.
We are currently developing a more realistic parallel runtime, and writing up and implementing the new strictness analysis technique.
If you are a United States citizen or permanent resident alien studying computer science or mathematics at the undergraduate level, or are a recent graduate, with strong interests in Haskell programming, compiler/runtime development, and pursuing a spring, fall, or summer internship at Los Alamos National Laboratory, USA, this could be for you.
We don’t expect applicants to necessarily already be highly accomplished Haskell programmers—such an internship is expected to be a combination of further developing your programming/Haskell skills and putting them to good use. If you’re already a strong C hacker we could use that too.
The application process requires a bit of work so don’t leave
enquiries until the last day/month. Dates for terms beyond summer 2018 are
best guesses based on prior years.
|Fall 2018||OPEN NOW||May 31 2018|
|Spring 2019||July 2018||Oct 2018|
|Summer 2019||Oct 2018||Jan 2019|
Email same address as above for the Trends in Functional Programming 2016 paper about this project.
Intern Loren Anderson did an interesting Haskell exercise while here for this mathematics paper.
A common problem with concurrent programs is that output to the console has to be buffered or otherwise dealt with to avoid multiple threads writing over top of one-another. This is particularly a problem for progress displays, and the output of external processes. The concurrent-output library aims to be a simple solution to this problem.
It includes support for multiple console regions, which different threads can update independently. Rather than the complexity of using a library such as ncurses to lay out the screen, concurrent-output’s regions are compositional; it acts as a kind of miniature tiling window manager. This makes it easy to generate progress displays similar to those used by apt or docker.
STM is used extensively in the implementation, which simplified what would have otherwise been a mess of nested locks. This made concurrent-output extensible using STM transactions. See this blog post.
Concurrent-output is used by git-annex, propellor, and xdcc and patches have been developed to make both shake and stack use it.
Deja Fu is a concurrency testing tool for Haskell built on top of the “concurrency” library, which provides a typeclass abstraction over a large subset of the “base” concurrency API, such as:
In the last six months, in addition to the usual stream of bugfixes and performance improvements, dejafu has: overhauled the API, throwing out many confusingly similar functions; implemented a snapshotting mechanism, to avoid redundancy in test cases with some nontrivial set-up work; gained support for simplifying execution traces; and switched to using a more convenient record-based approach for configuration.
The set of languages to choose from for mobile development is limited to those languages that can target those ecosystems.
There have been ongoing efforts to make Haskell a viable choice for Mobile Development for many years, via the path of cross compilation.
A major obstacle for cross compilation with Haskell is Template Haskell. Up until recently Template Haskell was available only for stage2 compilers, while cross compilers are stage1. One notable exception is GHCJS, which had Template Haskell support quite some time already via an out of process Template Haskell solution. With the addition of -fexternal-interpreter via iserv in recent GHCs, which implements a very similar system, it is possible to add TH support to stage1 cross compilers.
With the addition of linker for mach-o/aarch64, elf/aarch64, and improvements to the elf/armv7 linker in GHC, as well as a proxy mechanism that allows GHC to communicate with a remote iserv on a different host it is now possible to compile large chunks of TH code with cross compilers targeting supported linker platforms. File and Process IO pose interesting problems.
The necessary changes to GHC are all under review and will hopefully make it into GHC 8.4 in time.
There are some additional challenges in the Haskell ecosystem (e.g. cabal is not very cross compilation aware) that need to be addressed before Haskell for Mobile works out of the box.
A periodically force-pushed snapshot of the GHC HEAD plus the open differentials is available, as well as build scripts that build ghc for iOS and Android using a custom toolchain, derived from the ghc-ios-scripts. GHCSlave apps for iOS and Android that wrap iserv.
Further information covering the ongoing development will be published at https://medium.com/@zw3rk.
haskus-system is a system programming framework directly on top of the Linux kernel system calls. It doesn’t rely on usual interfaces (e.g., libc, libdrm, libinput, X11, wayland, etc.) to communicate with the kernel. Everything is done in Haskell.
Notable changes since the last HCAR:
The source code is freely available (BSD3 license).
Haskino is a Haskell development environment for programming the Arduino microcontroller boards in a high level functional language instead of the low level C language normally used.
This work started with Levent Erkok’s hArduino package. The original version of Haskino, extended hArduino by applying the concepts of the strong remote monad design pattern to provide a more efficient way of communicating, and generalizing the controls over the remote execution. In addition, it added a deep embedding, control structures, an expression language, and a redesigned firmware interpreter to enable standalone software for the Arduino to be developed using the full power of Haskell.
The current version of Haskino continues to build on this work. Haskino is now able to directly generate C programs from our Arduino Monad. This allows the same monadic program to be quickly developed and prototyped with the interpreter, then compiled to C for more efficient operation. In addition, we have added scheduling capability with lightweight threads and semaphores for inter-thread synchronization.
The development has been active over the past year. A paper was published at PADL 2016 for original version, and there is a paper accepted for presentation at TFP 2016 for the new scheduled and compiled version.
The STM32-Zombie project turns a STM32Fxxx micro controller into a Haskell programmable and flexible IO peripheral of your PC. The STM32Fxxx micro controller family features a variety of powerful IO peripherals like GPIO ports, USART, SPI, I2C, USB, ADC, timers, real time clock, etc. and STM32-Zombie allows a Haskell program to control the complete set of built-in micro controller peripherals.
The project is called STM32-Zombie because it shuts down the controllers brain (the ARM CPU) and turns it into a remote controlled zombie. It works without any c-code, cross-compiler tool-chain, or firmware. The STM32Fxxx peripherals use memory mapped control registers and the on-chip-debugging interface of the controller allows Haskell to access all of the controllers address space and registers. With help of the DMA controller even hard-real-time applications, like high-frequency sampling or generating of high-frequency output patterns, are possible.
Minimal hardware requirements, for trying out this project, are a mini STM32F103 breakout board and a STLink V2 USB dongle simulator. Both parts are available for less then $2 each. My test setup are mini STM32F103 breakout boards. I have not tested the library with other members of the STM32Fxxx family but the library is probably a good starting point for work on other STM32Fxxx controllers.
The cabal package contains examples for LED blinking, serial port, SPI, high-frequency ADC sampling, control of WS1228B RGB LED strips, and more.
The library uses the naming conventions of the ST-Microelectronics STM32F10x Firmware Library and provides a mid-level abstraction of the hardware.
While access to all of the peripherals is possible, the abstraction layer is still work-in-progress and does not cover all of the peripherals yet.
Comments, suggestions, experience reports, and patches are welcome. The project is open to any kind of contribution.
This library provides common numerical analysis functionality, without requiring any external bindings. It is not optimized for performance yet, but it serves as an experimental platform for scientific computation in a purely functional setting.
Currently it offers :
The initial motivation for this was on one hand the lack of native Haskell tools for numerical computation, and on the other a curiosity to reimagine scientific computing through a functional lens.
The implementation relies on nested IntMap’s from containers.
Currently, a new backend based on accelerate is under development, along with a generalized interface based on typeclasses, which will allow to decouple algorithms from datastructures. Eventually, the accelerate-based backend and interface will be provided as two distinct packages, and sparse-linear-algebra will import from both and provide a new reference implementation.
A usage tutorial on the major functionality is available in the README file, and all interface functions are commented throughout the Haddock documentation.
sparse-linear-algebra is freely available on Hackage under the terms of a GPL-3 license; development is tracked on GitHub, and all suggestions and contributions are very much welcome.
Aivika is a collection of open-source simulation libraries written in Haskell. It is mainly focused on discrete event simulation but has a partial support of system dynamics and agent-based modeling too.
A key idea is that many simulation activities can be modeled based on abstract computations such as monads, streams and arrows. The computations are composing units, which we can construct simulation models from and then run.
Aivika consists of a few packages. The basic package introduces the simulation computations. There are other packages that allow automating simulation experiments. They can save the simulation results in files, plot charts and histograms, collect the statistics summary and so on. There are also packages for distributed parallel simulation and nested simulation based on the generalized version of Aivika.
The core of Aivika is quite stable and well-tested. The libraries work on Linux, OS X and Windows. They are licensed under BSD3 and available on Hackage.
There are plans to find new application fields for the libraries. The core libraries solve a very general task and definitely can be applied to other fields too.
Haskell’s Float and Double types are often used for floating-point arithmetic, but sometimes they should not be. Although the Haskell Language Report does not require it, these types are typically implemented using a binary floating-point representation, and consequently do not always have an exact correspondence with the way we write a value using decimal notation. For example, the value 0.1 cannot be represented exactly as a binary floating-point value, because there is no integer solution to make c ×2q = 10-1.
This can lead to subtle errors in computations, as well as the attendant grief and frustration when our programs fail to meet user expectations. It is why Mike Cowlishaw, editor of the IEEE 754 standard for floating-point arithmetic, writes: “While suitable for many purposes, binary floating-point arithmetic should not be used for financial, commercial, and user-centric applications or web services because the decimal data used in these applications cannot be represented exactly using binary floating-point.”
Mike Cowlishaw has an entire section of his website devoted to General Decimal Arithmetic (URL below), including a complete specification that describes the decimal arithmetic included in the updated IEEE 754-2008 standard. Decimal floating-point arithmetic works just like its binary cousin, except it uses a radix value of 10 internally instead of 2. This allows decimal floating-point values to be represented exactly; there is a one-to-one correspondence between the way a value is written in decimal notation and the way it is represented internally. Consequently there are fewer surprises when performing arithmetic with such values.
The decimal-arithmetic package is being developed to provide a Haskell implementation of the General Decimal Arithmetic specification. It offers a versatile Decimal type constructor that is parameterized with both a precision and a rounding algorithm; all arithmetic using this type will be restricted to the given precision, using the given rounding algorithm whenever the result of a computation exceeds the precision.
Several type aliases are provided as a convenience. For example, Decimal64 is a decimal floating-point type with 16 digits of precision (comparable to Double) that rounds half even. It is special because it also has a Binary instance with a 64-bit encoded representation using the decimal64 interchange format. Similar types Decimal32 (cf. Float) and Decimal128 are also provided.
All the usual numeric, fractional, real, and floating-point type classes have been fully implemented, allowing decimal types to be used as drop-in substitutes for Float and Double. In addition, a low-level arithmetic monad is provided within which primitive operations can be performed with complete control over the outcome of exceptional conditions such as inexact results or division by zero.
The package is currently in a usable state; extensive testing is encouraged. While the package includes a moderate test suite, future work will focus on ensuring the implementation passes all of the test cases provided on Mike Cowlishaw’s website.
wxHaskell 0.93.0.0 development is in progress, with, amongst others, an adaptation to Cabal 2.0. A cabal.project file is added to the GitHub repository and the test sets are converted to Cabal packages, to be able to compile everything with the experimental command "cabal new-build all". Preparations have been made for the wxWidgets 3.1 binding, but more work is needed for this.
New project participants are welcome.
wxHaskell is a portable and native GUI library for Haskell. The goal of the project is to provide an industrial strength GUI library for Haskell, but without the burden of developing (and maintaining) one ourselves.
wxHaskell is therefore built on top of wxWidgets: a comprehensive C++ library that is portable across all major GUI platforms; including GTK, Windows, X11, and MacOS X. Furthermore, it is a mature library (in development since 1992) that supports a wide range of widgets with the native look-and-feel.
A screen printout of a sample wxHaskell program:
Threepenny-gui is a framework for writing graphical user interfaces (GUI) that uses the web browser as a display. Features include:
You can download the library from Hackage or Stackage and use it right away to write that cheap GUI you need for your project. Here a screenshot from the example code:
For a collection of real world applications that use the library, have a look at the gallery on the homepage.
The latest release is version 0.8.2.0. I would like to thank co-maintainer Simon Jakobi for his diligent and timely releases.
Compared to the previous report, several small additions to the API have been made, the documentation has been improved, and compatibility with the latest GHC versions has been ensured. Moreover, I given a tutorial about the library on HaL 2017, and the slides are now available in the source repository.
The library is still in flux, API changes are likely in future versions.
In the future, I hope to improve the functional reactive programming (FRP) aspects of the framework, for instance by using the reactive-banana library as a basis. (→4.17.2)
Yampa (Github: http://git.io/vTvxQ, Hackage: http://goo.gl/JGwycF), is a Functional Reactive Programming implementation in the form of a EDSL to define Signal Functions, that is, transformations of input signals into output signals (aka. behaviours in other FRP dialects).
Yampa systems are defined as combinations of Signal Functions. Yampa includes combinators to create constant signals, apply pointwise (or time-wise) transformations, access the running time, introduce delays and create loopbacks (carrying present output as future input). Systems can be dynamic: their structure can be changed using switching combinators, which apply a different signal function at some point in the future. Combinators that deal with collections enable adding, removing, altering, pausing and unpausing signal functions at will.
A suitable thinking model for FRP in Yampa is that of signal processing, in which components (signal functions) transform signals based on their present value and a component’s internal state. Components can, therefore, be serialized, applied in parallel, etc. Yampa’s signal functions implement the Arrow and ArrowLoop typeclasses, making it possible to use both arrow notation and arrow combinators.
Yampa combinators guarantee causality: the value of an output signal at a time t can only depend on values of input signals at times [0,t]. Efficiency is provided by limiting history only to the immediate past, and letting signals functions explicitly carry state for the future. Unlike other implementations of FRP, Yampa enforces a strict separation of effects and pure transformations: all IO code must exist outside Signal Functions, making systems easier to reason about and debug.
Yampa has been used to create both free/open-source and commercial games. Examples of the former include Frag (http://goo.gl/8bfSmz), a basic reimplementation of the Quake III Arena engine in Haskell, and Haskanoid (http://git.io/v8eq3), an arkanoid game featuring SDL graphics and sound with Wiimote &Kinect support, which works on Windows, Linux, Mac, Android, iOS and web browsers (thanks to GHCJS). Examples of the latter include Keera Studios (→5.2)’ Magic Cookies!, a Haskell puzzle board game for iOS and Android available on iTunes (https://goo.gl/6gB6sb) and Google Play (https://goo.gl/0A8z6i).
Guerric Chupin (ENSTA ParisTech), under the supervision of Henrik Nilsson (Functional Programming Lab, University of Nottingham (→6.6)) has developed Arpeggigon (→4.18.4) (https://gitlab.com/chupin/arpeggigon), an interactive cellular automaton for composing groove-based music. The aim was to evaluate two reactive but complementary frameworks for implementing interactive time-aware applications. Arpeggigon uses Yampa for music generation, Gtk2HS for Graphical User Interface, jack for handling MIDI I/O, and Keera Hails to implement a declarative MVC architecture, based on Reactive Values and Relations (RVRs). The results have been written up in an application paper, Funky Grooves: Declarative Programming of Full-Fledged Musical Applications, presented at PADL 2017. The code and an extended version of the paper are publicly available (https://gitlab.com/chupin/arpeggigon). Arpeggigon has also been demonstrated at FARM 2017, the Haskell eXchange 2017, and Haskell in Leipzig 2017.
Yampa is under active development, with many Haskellers participating and sending their contributions. Recent releases have featured a cleaner API and new Signal Function combinators. The most recent version, released this year, includes full documentation. Our github repository includes development branches with features that have been used to extend Yampa for custom games. Some of these features have been presented in the paper “Back to the Future: time travel in FRP”, presented at the Haskell Symposium 2017, and will be included in future versions. Yampa will now be extended with testing and debugging features, which allow us to express temporal assertions about FRP systems using Temporal Logic, and to use QuickCheck to test those properties, as described in the paper “Testing and Debugging Functional Reactive Programming”, presented at ICFP 2017.
Extensions to Arrowized Functional Reactive Programming are an active research topic. Last year we published, together with Manuel Bärenz, a monadic arrowized reactive framework called Dunai (https://git.io/vXsw1), and a minimal FRP implementation called BearRiver. BearRiver provides all the core features of Yampa, as well as additional extensions. We have demonstrated the usefulness of our approach and the compatibility with existing Yampa games by using BearRiver to compile and execute the Haskanoid and Magic Cookies! for Android without changing the code of such games. These games are also available for iOS and other platforms.
The Functional Programming Laboratory at the University of Nottingham (→6.6) is working on other extensions to make Yampa more general and modular, increase performance, enable new use cases and address existing limitations. To collaborate with our research, please contact Ivan Perez (email@example.com) and Henrik Nilsson (firstname.lastname@example.org).
There are several other channels that anyone can use to reach other Yampa users and implementors, including a mailing list and the #yampa IRC channel on freenode. We are also active on Haskell Caféand the facebook group Programming Haskell, and subscribe to the Yampa keyword on StackOverflow. We encourage all Haskellers to participate on Yampa’s development by opening issues on our Github page (http://git.io/vTvxQ), adding improvements, creating tutorials and examples, and using Yampa in their next amazing Haskell games. We thank the kind users who have already sent us their contributions.
Reactive-banana is a library for functional reactive programming (FRP). FRP offers an elegant and concise way to express interactive programs such as graphical user interfaces, animations, computer music or robot controllers. It promises to avoid the spaghetti code that is all too common in traditional approaches to GUI programming.
The goal of the library is to provide a solid foundation.
The library is meant to be used in conjunction with existing libraries that are specific to your problem domain. For instance, you can hook it into any event-based GUI framework, like wxHaskell or Gtk2Hs. Several helper packages like reactive-banana-wx provide a small amount of glue code that can make life easier.
The latest release is version 220.127.116.11. Thanks to the efforts of our co-maintainer Oliver Charles, the library is available on Stackage. (→4.2.3) The library API is stable and feature complete.
Several other improvements have been suggested on the issue tracker, most notably renaming the Event type to Events, as the plural provides a more apt description of the semantics of this type.
|Report by:||Jonathan Thaler|
|Status:||Experimental, active development|
Agent-Based Simulation (ABS) is a methodology in which a system is simulated in a bottom-up approach by modelling the micro interactions of its constituting parts, called agents, out of which the global macro system behaviour emerges. So far mainly object-oriented techniques and languages have been used in ABS. We investigate how ABS can be implemented in a pure functional language like Haskell. We build on the concept of Functional Reactive Programming and Monadic Stream Functions for which we use the library Dunai.
It is of most importance to us to keep our code pure - except from the reactive main-loop all our code is pure and does not make use of the IO Monad. This guarantees us reproducibility of the simulation already at compile time because no external sources of non-determinism can influence the computations. We claim that, in contrast to traditional object-oriented languages, this representation is conceptually cleaner and opens the way to formally reason about ABS. For an introduction into the concepts behind functional reactive ABS we refer to our paper, submitted for Haskell Symposium 2018: https://github.com/thalerjonathan/phd/blob/master/public/purefunctionalepidemics/pfe.pdf.
We implemented the library chimera for this purpose which implements all concepts (and more) described in the paper. As use-cases we also implemented a number of various well known ABS models e.g. Schelling Segregation, Sugarscape, Agent_Zero. The code is freely available but not stable as it currently serves for prototyping for gaining insights into the problems faced when implementing ABS in Haskell. The plan is to release the final implementation at the end of the PhD as a stable and full-featured library on Hackage.
If you are interested in the on-going research please contact Jonathan Thaler (email@example.com).
The diagrams framework provides an embedded domain-specific language for declarative drawing. The overall vision is for diagrams to become a viable alternative to DSLs like MetaPost or Asymptote, but with the advantages of being declarative—describing what to draw, not how to draw it—and embedded—putting the entire power of Haskell (and Hackage) at the service of diagram creation. There is always more to be done, but diagrams is already quite fully-featured, with a comprehensive user manual and a growing set of tutorials, a large collection of primitive shapes and attributes, many different modes of composition, paths, cubic splines, images, text, arbitrary monoidal annotations, named subdiagrams, and more.
Work on diagrams has slowed considerably since the release of diagrams 1.4 in October 2016, due to time constraints of the main developers. However, work on diagrams 2.0 is slowly but steadily progressing, targeting a release during the summer of 2018. Updates will include:
There is plenty of exciting work to be done; new contributors are welcome! Diagrams has developed an encouraging, responsive, and fun developer community, and makes for a great opportunity to learn and hack on some “real-world” Haskell code. Because of its size, generality, and enthusiastic embrace of advanced type system features, diagrams can be intimidating to would-be users and contributors; however, we are actively working on new documentation and resources to help combat this. For more information on ways to contribute and how to get started, see the Contributing page on the diagrams wiki: http://haskell.org/haskellwiki/Diagrams/Contributing, or come hang out in the #diagrams IRC channel on freenode.
The csound-expression is a Haskell framework for electronic music production. It’s based on very efficient and feature rich software synthesizer Csound. The Csound is a programming language for music production. With CE we can generate the Csound code out of high-level functional description. The project is available on Hackage and can be installed with cabal.
The new version 5.3 is out. Let’s look at the new features.
The project was updated to compile with new GHC 8.4.x. Also it was tested on previous compilers down to 7.8. So the CE should compile across 7.8 to 8.4 GHC compilers.
The library was updated to support latest Csound stable release 6.10. There are many new DSP algorithms available with this update. Among them there are many great filters like emulation of Korg 35 analog filter, or emulation of Roland TB-303 resonant filter, zero-delay feedback filters. You can find them at the module Csound.Air.Filter.
This release features new effects useful for guitars. Like emulation of Roland Space echo (function tapeEcho or magnus) and ambient guitar effect (ambiEnv, ambiGuitar). The Space echo simulates behaviour of magnetic tape delay. Ambient guitar detects strike attacks in the audio signal and smoothes them down, so that they sound like pads.
New addition is built in BPM synchronization. User can set global BPM with function setBpm. Then it’s possible to use functions that synchronize Hzs (function syn) and seconds (function takt) to global BPM. It’s useful to align delay times and LFO rates with global BPM. Also module csound-sampler was updated to respond to changes in global BPM.
There are some additions to improve usability of the library like adding new instances for rendering to Csound files. Like rendering functions with arbitrary number of inputs and outputs and rendering of functions augmented with UIs.
Also documentation, examples and tutorial were updated for recent changes.
New useful functions: brown for brownian noise, resizeGui for scaling GUIs window size.
You can listen to the music that was made with Haskell and the library csound-expression:
The library is available on Github and Hackage. See the packages csound-expression, csound-sampler and csound-catalog.
|Report by:||Jeroen Bransen|
|Participants:||W. Bas de Haas, José Pedro Magalhães, Dion ten Heggeler, Tijmen Ruizendaal, Gijs Bekenkamp, Hendrik Vincent Koops|
Chordify is a music player that extracts chords from musical sources like Youtube, Deezer, Soundcloud, or your own files, and shows you which chord to play when. The aim of Chordify is to make state-of-the-art music technology accessible to a broader audience. Our interface is designed to be simple: everyone who can hold a musical instrument should be able to use it.
Behind the scenes, we have a chord extraction pipeline that is written in Haskell with some bindings to C libraries. We use Kiss FFT for computing audio features, which give information about the frequencies in the audio signal. These features are the inputs for a deep convolutional neural network that is trained and evaluated with bindings to the Tensorflow library. Finally a Hidden Markov Model, which is also trained on datasets of audio with manually annotated chords, is used to pick the final chord for each beat. This model encapsulates the rules of tonal harmony.
We have a distributed backend based on Cloud Haskell, allowing us to easily scale up when the demand increases. Our library currently contains about 6.5 million songs, and about 7,500 new songs are Chordified every day. We have also released an iOS app that allows iPhone and iPad users to interface with our technology more easily, and an Android version is being developed.
Chordify is a proud user of Haskell, but we have also encountered some problems and limitations of the language and the libraries. These include:
|Report by:||Henrik Nilsson|
|Participants:||Henrik Nilsson, Guerric Chupin, Jin Zhan|
|Status:||Experimental: working but not yet feature complete|
The Arpeggigon is a Functional Reactive Musical Automaton developed by Henrik Nilsson and summer interns Guerric Chupin and Jin Zhan. The work took place in the Functional Programming Laboratory, University of Nottingham (→6.6), which Guerric now has joined as a PhD student.
The Arpeggigon was developed as a case study for evaluating the combination of two reactive but complementary frameworks for implementing interactive time-aware applications: (FRP) as embodied by Yampa and Reactive Values and Relations (RVR). Hybrid (mixed continuous and discrete time) aspects were of particular interest.
We choose a musical application as music is a domain with hybrid temporal aspects at its core. The goal was to develop a full-fledged application in terms of look and feel and interoperability with standard MIDI software and hardware as would be found in a studio setting. To that end, we opted for using the standard GUI framework GTK+ for the user interface and the Jack framework for MIDI connectivity. Additionally, we wanted an application that is interesting and fun in its own right.
The Arpeggigon was inspired by the hardware reacTogon: a “chain reactive performance arpeggiator”. It’s essentially a cellular automaton based around the Harmonic Table: a way to arrange musical notes on a hexagonal grid. Play heads bounce between tokens arranged on the hexagonal grid. Whenever a play head hits a token, a note corresponding to the position of the token on the grid is played. The picture below shows what the Arpeggigon looks like:
The case study demonstrates that FRP in combination with RVR is a compelling combination for building this kind of applications. FRP, in the synchronous dataflow tradition, aligns with the temporal and declarative nature of music, while RVR allows declarative interfacing with external components as needed for full-fledged musical applications.
The results have been written up in an application paper, “Funky Grooves: Declarative Programming of Full-Fledged Musical Applications”, that was presented at PADL 2017. There is also an extended technical report version and videos as well as slides from talks (PADL, FARM, Haskell eXchange, etc).
The code is publicly available on GitLab.
The next steps are to make the Arpeggigon more feature complete and to improve its interoperability in the context of a MIDI studio by improving its timing.
Gifcurry is an open source video to GIF maker written in Haskell. Powered by the core library, Gifcurry has both a command-line and graphical user interface. Features include a video preview, seeking, trimming, croping, text overlays with font selection, setting the width and output quality, and saving the results as a GIF or video. Platforms supported include Linux and macOS.
Gifcurry is actively maintained and continuously improved. A two year old project, Gifcurry has had 17 releases at the time of this writing. The most recent version was released in April of 2018.
Gifcurry’s source is on GitHub and Hackage. Linux users can download and install Gifcurry via the Arch User Repository, Snapcraft, AppImageHub, or the GitHub releases page. There is a convenient build script for macOS users and a Homebrew package is planned.
Future improvements include being able to add multiple text overlays and having them show in the video preview. Currently, Gifcurry allows you to add two text overlays (one for the top and bottom) that last the entire duration. Instead, you’ll be able to add as many as you wish, specifying the start time, duration, font, and location for each.
Movie Monad is an open source desktop video player written in Haskell. Its run-time dependencies include GTK+ and GStreamer. To interface with GTK+ and GStreamer, Movie Monad uses the haskell-gi bindings. Features include the usual playback and volume controls, full screen mode, subtitle support, variable speed playback, and a command line interface. Users can play both local and remote files from the web.
While there already exists a wide array of video players, there is still room for Movie Monad with its intuitive interface and unobtrusive feature set. Movie Monad falls somewhere between mpv’s minimalism and VLC’s verbosity. The main reason for the project’s existence, however, is to showcase Haskell’s capabilities of targeting the desktop by using Haskell to build a nontrivial, multimedia GUI application.
Movie Monad’s source is on GitHub and Hackage. Linux users can download and install Movie Monad via the Arch User Repository, Flathub, Snapcraft, AppImageHub, GNOME Software, or the GitHub releases page. There is a convenient build script for macOS users and a Homebrew package is planned.
Two new features are planned for Movie Monad. In addition to browsing through local files, Movie Monad will support browsing through podcast feeds. The other planned feature involves image recognition allowing users to search through a video much like they would a text document. If you see a feature Movie Monad should have, be sure to leave your feedback on the GitHub issues page.
Nomyx is a unique game where you can change the rules of the game itself, while playing it! In fact, changing the rules is the goal of the game. Changing a rule is considered as a move. The players can submit new rules or modify existing ones, thus completely changing the behavior of the game through time. The rules are managed and interpreted by the computer. They must be written in the Nomyx language, based on Haskell. This is the first complete implementation of a Nomic game on a computer.
At the beginning, the initial rules are describing:
The V1.0 has been released!
The game has been presented in Zurihac 2017, where we playing several live matches. A lot of learning material is available, including videos, a tutorial, a FAQ, and API documentation.
If you like Nomyx, you can help! There is a development mailing list (check the website).
EtaMOO is a new, experimental MOO server implementation written in Haskell. MOOs are network accessible, multi-user, programmable, interactive systems well suited to the construction of text-based adventure games, conferencing systems, and other collaborative software. The design of EtaMOO is modeled closely after LambdaMOO, perhaps the most widely used implementation of MOO to date.
Unlike LambdaMOO which is a single-threaded server, EtaMOO seeks to offer a fully multi-threaded environment, including concurrent execution of MOO tasks. To retain backward compatibility with the general MOO code expectation of single-threaded semantics, EtaMOO makes extensive use of software transactional memory (STM) to resolve possible conflicts among simultaneously running MOO tasks.
EtaMOO fully implements the MOO programming language as specified for the latest version of the LambdaMOO server, with the aim of offering drop-in compatibility. Several enhancements are also planned to be introduced over time, such as support for 64-bit MOO integers, Unicode MOO strings, and others.
Recent development has brought the project to a largely usable state. A major advancement was made by integrating the vcache library from Hackage for persistent storage — a pairing that worked especially well given EtaMOO’s existing use of STM. Consequently, EtaMOO now has a native binary database backing with continuous checkpointing and instantaneous crash recovery. Furthermore, EtaMOO takes advantage of vcache’s automatic value cache with implicit structure sharing, so the entire MOO database need not be held in memory at once, and duplicate values (such as object properties) are stored only once in persistent storage.
Further development has incorporated optional support for the lightweight object WAIF data type as originally described and implemented for the LambdaMOO server. The vcache library was especially useful in implementing the persistent shared WAIF references for EtaMOO.
Future EtaMOO development will focus on feature parity with the LambdaMOO server, full Unicode support, and several additional novel features.
Latest development of EtaMOO can be seen on GitHub, with periodic releases also being made available through Hackage.
I made a Tetris in Haskell, while learning the basics of the language, in order to gain some hands-on experience, and also to convince myself that Haskell is a practical language that’s worth the time investment and the steep learning curve.
I am now convinced that that is the case. In fact, I’m amazed at how concise and readable Haskell code can be, and I can already acknowledge Haskell as a tool for productivity, predictability and reliability, which are without a doubt, properties most software developers could benefit from.
I have documented this experience as a series of thoughts from the point of view of a beginner, in the form of a blog post titled “Tetris in Haskell in a Weekend”
I also documented the project’s evolution in small increments as a git repository that might be of interest to other beginners. The repository can be accessed via github, and contributions are welcome
Barbarossa is a UCI chess engine written completely in Haskell. UCI is one of the two most used protocols used in the computer chess scene to communicate between a chess GUI and a chess engine. This way it is possible to write just the chess engine, which then works with any chess GUI.
I started in 2009 to write a chess engine under the name Abulafia. In 2012 I decided to rewrite the evaluation and search parts of the engine under the new name, Barbarossa.
My motivation was to demonstrate that even in a domain in which the raw speed of a program is very important, as it is in computer chess, it is possible to write competitive software with Haskell. The speed of Barbarossa (measured in searched nodes per second) is still far behind comparable engines written in C or C++. Nevertheless Barbarossa can compete with many engines - as it can be seen on the CCRL rating lists, where is it currently listed with a strength of about 2200 ELO.
Barbarossa uses a few techniques which are well known in the computer chess scene:
I still have a lot of ideas which could improve the strength of the engine, some of which address a higher speed of the calculations, and some, new chess related features, which may reduce the search tree.
The engine is open source and is published on github. The last released version is Barbarossa v0.4.0 from December 2016.
The Ravensburger Tiptoi pen is an interactive toy for kids aged 4 to 10 that uses OiD technology to react when pointed at the objects on Ravensburger’s Tiptoi books, games, puzzles and other toys. It is programmed via binary files in a proprietary, undocumented data format.
We have reverse engineered the format, and created a tool to analyze these files and generate our own. This program, called tttool, is implemented in Haskell, which turned out to be a good choice: Thanks to Haskell’s platform independence, we can easily serve users on Linux, Windows and OS X.
The implementation makes use of some nice Haskell idioms such as a monad that, while parsing a binary, creates a hierarchical description of it and a writer monad that uses lazyness and MonadFix to reference positions in the file “before” these are determined.
Asteroids is a Haskell version of the known game with the same name. It was developed as learning project.
The main aim of the game is to score the highest score by shooting the coming asteroids while avoiding them and remembering that the player only has three spaceships.
The implementation simulates the space physics and follows the original rules. In addition, we added a multi-player system to invite friends to join the campaign.
Our team found it a good opportunity to develop this using Haskell. By using lazy evaluation techniques we were able to provide a stable framerate.
hledger is a set of cross-platform tools (and Haskell libraries) for tracking money, time, or any other commodity, using double-entry accounting and a simple future-proof text file format.
It is an enhanced, well-documented reimplementation of plain text accounting in Haskell, inspired by John Wiegley’s Ledger program.
hledger aims to be a reliable and practical tool for daily use, and provides command-line, curses-style, and web interfaces.
hledger is released under GNU GPLv3+.
Project activity has been continuous since our last update in November 2016.
Some notable developments:
hledger is available from the hledger.org website, Github, Hackage, or Stackage. It is packaged for a number of systems (Windows, Homebrew, most GNU/Linux distros, NixOS, Sandstorm..) and buildable on other systems supporting GHC (freeBSD, openBSD..).
Gipeda is a tool that presents data from your program’s benchmark suite (or any other source), with nice tables and shiny graphs. Its name is an abbreviation for “Git performance dashboard” and highlights that it is aware of git, with its DAG of commits.
Gipeda powers the GHC performance dashboard at http://perf.haskell.org, but it builds on Shake and creates static files, so that hosting a gipeda site is easily possible.
The program arbtt, the automatic rule-based time tracker, allows you to investigate how you spend your time, without having to manually specify what you are doing. arbtt records what windows are open and active, and provides you with a powerful rule-based language to afterwards categorize your work. And it comes with documentation!
The program works on Linux, Windows, and MacOS X.
Propellor is a configuration management system for Linux that is configured using Haskell. It fills a similar role as Puppet, Chef, or Ansible, but using Haskell instead of the ad-hoc configuration language typical of such software. Propellor is somewhat inspired by the functional configuration management of NixOS.
A simple configuration of a web server in Propellor looks like this:
webServer :: Host
webServer = host "webserver.example.com"
& ipv4 "18.104.22.168"
& staticSiteDeployedTo "/var/www"
`requires` Apt.serviceInstalledRunning "apache2"
staticSiteDeployedTo :: FilePath -> Property DebianLike
There have been many benefits to using Haskell for configuring and building Propellor, but the most striking are the many ways that the type system can be used to help ensure that Propellor deploys correct and consistent systems. Beyond typical static type benefits, GADTs and type families have proven useful. For details, see the blog.
An eventual goal is for Propellor to use type level programming to detect at compile time when a host has eg, multiple servers configured that would fight over the same port. Moving system administration toward using types to prove correctness properties of the system.
Propellor recently has been extended to support FreeBSD, and this led to Propellor properties including information about the supported OSes in their types. That was implemented using singletons to represent the OS, and functions over type level lists. For details, see this blog post.
Propellor has also been extended to be able to create bootable disk images. This allows it to not only configure existing Linux systems, but manage their entire installation process.
The leapseconds-announced library provides an easy to use static LeapSecondMap with the leap seconds announced at library release time. It is intended as a quick-and-dirty leap second solution for one-off analyses concerned only with the past and present (i.e. up until the next as of yet unannounced leap second), or for applications which can afford to be recompiled against an updated library as often as every six months.
Version 2017.1 of leapseconds-announced was released to support the change from LeapSecondTable to LeapSecondMap in time-1.7. It contains all leap seconds up to 2017-01-01. A new version will be uploaded if/when the IERS announces a new leap second.
|Report by:||Tim Matthews|
|Status:||experimental, actively developed|
clr-haskell is a project to enable the use of code within the common language runtime (.NET / Mono / CoreCLR) from GHC Haskell.
This project provides 2 primary flavours for a developer to interop between the CLR &Haskell:
The Haskeller’s strongly typed flavour. Takes advantage of the latest GHC extensions to provide a way of encoding an OO type system within the Haskell type system.
The .NET dev’s inline flavour. Provides the ability to call directly into valid C#/ F#syntax via quasi-quoted template Haskell.
|Report by:||Dino Morelli|
|Status:||stable, actively developed|
This project is the server-side software for Kitchen Snitch, a mobile application that provides health inspection scores, currently for the Raleigh-Durham area in NC, USA. The data can be accessed on maps along with inspection details, directions and more.
The back-end software provides a REST API for mobile clients and runs services to perform regular inspection data acquisition and maintenance.
Kitchen Snitch has been in development for over a year and is running on AWS. The mobile client and server were released for public use in April of 2016 after a beta-test period.
Some screenshots of the Android client software in action:
Getting Kitchen Snitch:
The Haskell server source code is available on darcshub at the URLs below.
FRTrader is a functional reactive bitcoin trading bot. It uses the reactive-banana FRP library and currently has bindings to the GDAX bitcoin exchange. The bot uses as a multi-threaded architecture that makes it easy to plug in extra exchanges and to trade on multiple exchanges simultaneously.
The code is available on github.
The following talk recorded at BayHac 2017 explains the design rationale and the use of FRP in trading.
We welcome contributions and hope to add bindings to other exchanges soon. Also, feel free to make a huge trading profit! Enjoy!
Hapoid is an Portable Object Translation file Linter for Bahasa Indonesia.
Currently, this project is a prototype but it will continue to be developed.
Hanum is an OpenStreetMap dynamic attributes linter with custom presets.
Some contributors to OSM may just want to fix wrong attributes on the OSM data. This means that they might not want to see any path or shape of the data. This linter thus acts as a library which allows data validation and creating new editors for OSM.
The linter filters error, thus reducing possible conflicts when submitting data to OSM. To further enhance the capabilities, custom presets and rules can be created for each individual country.
In Indonesia, especially in Kalimantan there are many areas where OSM has invalid data. For example, SMAN 1 Bintang Ara, which is a senior high school, shows on OSM as having a |school:type_idn| attribute of |elementary school|. Furthermore, it also lacks an address attribute.
A similar example is found in Papua: there are locations where the |admin_level| attribute is not a number as it should be, as well as areas where |addr:full| has invalid formatting.
With Hanum, we can define custom rules and use these presets to improve data quality.
shell-conduit allows writing shell scripts with conduit. It uses template Haskell to bring all the executables in the PATH as top level functions which can be used to launch them as a process.
tldr is a command line client for the TLDR pages. The TLDR pages are a community effort to simplify the beloved man pages with practical examples.
Compared to the previous version, the new verion works in Windows and doesn’t do eager cloning. Also default completion support has been added from optparse-applicative. The new-format branch contains changes for the new syntax of TLDR pages and will be merged with master whenever the upstream changes are finalized and merged.
pprjam is a reference manager for academics that allows you to organize your library of papers, add tags and notes, and create “ppr stacks” (like a playlist for references) to share with your colleagues. More collaboration features are planned for business (paid) users. The feature I’m really excited about, however, is what I call the “ppr trail” which uses a graph database to show, for any given paper, all of it’s citations and everything that cites it; this would allow you to explore the history of an idea by following the trail of publications over time with just a few clicks.
The first beta prototype has been deployed and is in active development. Production (i.e. usable) version is planned for the end of Q2. I heavily use Yesod for the web stuff and pandoc-citeproc for dealing with citation formats. Deployment is handled with NixOS.
Well-Typed is a Haskell services company. We provide commercial support for Haskell as a development platform, including consulting services, training, bespoke software development and technical support. For more information, please take a look at our website or drop us an e-mail at <info at well-typed.com>.
One of our main responsibilities is maintenance and release management for GHC (→3.1), thanks to support from several companies including Microsoft Research. Our full-time GHC team is led by Ben Gamari. If your company is interested in supporting work on GHC, either by contributing to the general maintenance pool or funding work on specific issues, please get in touch with us. We are also able to provide technical support with toolchain issues such as non-standard GHC configurations.
Through our work for IOHK we have recently been contributing significantly to the development of the Cardano cryptocurrency, which is implemented in Haskell. Cardano has been in the top 10 cryptocurrencies by market cap since December 2017. We are applying formal methods and related “semi-formal” techniques to achieve higher assurance and improved code quality in future iterations of the cryptocurrency (including everything from QuickCheck-compatible designs to developing formalized process calculi in Isabelle).
We endeavour to make our work available as open source software wherever possible, and contribute back to existing projects we use. Recently our contributions have included:
We are looking forward to the next Haskell eXchange in London from 11–12th October 2018, and we are planning another free Hackathon on 13th October. Together with Skills Matter, we will be offering public Haskell training courses in London around the Haskell eXchange (8th–10th, 15th–16th October). Registration is now open for both the courses and eXchange, so if you would like to come, register now!
We are always looking for new clients and projects, so if you have something we could help you with, or even would just like to tell us about your use of Haskell, please drop us an e-mail.
Keera Studios Ltd. is a Haskell development studio that focuses on games and mobile apps for both iOS and Android.
Last year, we completed a set of development tools for mobile Haskell games that enables compiling, testing, packaging and deploying mobile games with no effort. Our framework is versatile enough to accomodate not only games, but also mobile apps using standard widget toolkits available on mobile platforms, in order to provide a natural look and feel.
Our development toolkit if based on two tools, Andronaut and Curiosity, that provide, respectively, Android and iOS application templates and compile, package, sign and upload Haskell games and mobile apps to online stores. They have been designed to be trivial use, both during development and in CI servers: each tool downloads GHC pre-compiled for each target, as well as other SDKs and tools needed for mobile platforms. We use Travis CI to compile, package, sign and automatically upload our games to Google Play for Android (and tweet when a major release is out!). When developing locally, Andronaut and Curiosity maximize caching, and are able to recompile a mobile app and deploy it to a phone (connected via USB) in less than 45 seconds, or to the online store in less than one minute.
We top our development framework with a novel tool for testing and debugging mobile games: Haskell Titan (Testing Infrastructure for Temporal AbstractioNs). Haskell Titan is designed to take advantage of Haskell’s referential transparency to deliver fully reproducible game runs that can be saved, replayed, paused, played backwards, modified and debugged. Our GUI tool communicates with the game running on a phone or a computer, and uses Temporal Logic to specify game assertions. Players can record a game run with minimal overhead and send it over the internet to our servers, which we can use to reproduce bugs deterministically on the same architecture. Our tool also integrates well with QuickCheck, which we use to test game assertions and find counterexamples. Effectively, we can see QuickCheck play.
We have published Magic Cookies!, the first commercial game for iOS and Android written in Haskell, available on iTunes (https://goo.gl/6gB6sb) and on Google Play (https://goo.gl/cM1tD8). Currently holding a 4.9/5 star review, Magic Cookies! been in the Top 100 of paid board games on Google Play US, and Top 125 in the European Union, number 7 for paid braingames in Taiwan, number 15 in Italy, and Top 50 in 110 countries.
We have developed a breakout clone that runs on Windows, Linux, Mac, iOS, Android and Web (http://goo.gl/53pK2x), using hardware acceleration and parallelism. This game has been released on Google Play for Android, is distributed pre-compiled for Ubuntu via Launchpad, and can be played directly on the browser, compiled via GHCJS. The desktop version additionally supports Nintendo Wiimotes and Kinect. Thanks to many volunteer Haskellers, this game has seen updated documentation, better support for all OSs, and now includes 9 new levels.
We are currently developing three arcade games for both Android and iOS. Soon we will release the first version of a game internally called ‘npuzzles’, a sliding block puzzle game with classic levels, as well as levels with altered or novel rules designed to surprise, challenge and engage the player. This game is the first built from scratch using our SAGE infrastructure (detailed below), and serves as a well documented game-programming teaching source using Haskell, functional reactive programming (Yampa), SAGE, and our standard game structure, to show how easy and clear Haskell desktop and mobile games can be. The second game is Escape, and has been designed to challenge user’s ability to track multiple objects moving simultaneously in different directions. The third one, codenamed pang-a-lambda, is inspired by the classic Super Pang and takes advantage of newer developments in the FRP implementation Yampa to include declarative physics simulations and time transformations, including the possibility of reversing time.
We are also producing a visual interactive game about the war in Ukraine, which depicts the everyday life of people affected by the war, in an effort to raise awareness about the current state of affairs, how people are being treated and what they have lost. This game invites the player to see the human side of people who remain invisible to their own society, only to become an unnamed shield standing at the conflict line. On the basis of this game, our company has been accepted in Facebook’s acceleration programme for new apps and startups FbStart, and being granted thousands of dollars in digital goods and services for support and advertising.
This year we have completed the first version of our Simple Arcade Game Engine (SAGE), which hides tedious details from the developer. SAGE provides solutions for aspects common to many games, like asset management, 2D drawings, interactive widgets and positioning, and input devices (mouse, keyboard, touchscreen, accelerometers, wiimote and kinect), different game screens (splash screen, menus, level selection), preferences, saving and restoring the game state, and basic 2D physics and collisions. SAGE works for mobile and desktop and supports multiple backends, like SDL and SDL2, and hiding the details from the developer. The first game released with SAGE will be npuzzles, and we are currently porting other games to this new framework before their release.
In previous years we also developed GALE, a DSL for graphic adventures, together with an engine and a basic IDE that allows non-programmers to create their own 2D graphic adventure games without any knowledge of programming. Supported features include multiple character states and animations, multiple scenes and layers, movement bitmasks (used for shortest-path calculation), luggage, conversations, sound effects, background music, and a customizable UI. The IDE takes care of asset management, generating a fully portable game with all the necessary files. The engine is multiplatform, working seamlessly on Linux, Windows, Android and iOS. This work has been described in the paper “GALE: A functional Graphic Adventure Library and Engine”, presented at FARM 2017.
We have also started the Haskell Game Programming project (http://git.io/vlxtJ), which contains documentation and multiple examples of multimedia, access to gaming hardware, physics and game concepts. We have developed a battery of Haskell mobile demos, covering SDL multimedia (including demos for multi-touch and accelerometers), communication with Java via C/C++, Facebook/Twitter status sharing, access to each mobile ecosystem (for instance, to use Android built-in shared preferences storage system, or for in-app payments), and use to native mobile widgets on Android and iOS.
All of this proves that Haskell truly is a viable option for professional game and app development, for both mobile and desktop. Our novel testing and debugging tools show that Haskell can, in certain respects, be more suitable than other languages for game and app programming, especially for (heterogeneous) mobile devices. In combination with our samples and our compilation, packaging and deployment tool, we have a complete, pain-free mobile app development suite.
Our GUI applications are created using Keera Hails, our open-source reactive programming library (http://git.io/vTvXg). Keera Hails provides integration with GTK+, network sockets, files, FRP Yampa signal functions and other external resources. Keera Hails is straightforward to adapt to new platforms, and we have shown reactive Haskell applications that work on iOS, Android, Windows, Linux, Mac and Web/DOM (using each platform’s default widget system), just by choosing different backends (https://goo.gl/nFUA2u). We have used Keera Hails for our Graphic Adventure IDE, the open-source posture monitor Keera Posture (http://git.io/vTvXy), as well as multiple other commercial and open-source applications. Guerric Chupin (ENSTA ParisTech) and Henrik Nilsson (University of Nottingham (→6.6)) have also published Arpeggigon (→4.18.4) (https://gitlab.com/chupin/arpeggigon), an interactive cellular automaton for composing groove-based music, which combines the FRP implementation Yampa and Keera Hails. Their results have been written up in an application paper, Funky Grooves: Declarative Programming of Full-Fledged Musical Applications, presented at PADL 2017, and demonstrated at FARM 2017, the Haskell eXchange 2017, and Haskell in Leipzig 2017.
Videos and details of our work are published regularly on Facebook (https://fb.me/keerastudios), on Twitter (https://www.twitter.com/keerastudios), and on our company website (http://www.keera.co.uk). If you want to use Haskell in your next game, desktop or mobile application, or to receive more information, please contact us at <keera at keera.co.uk>.
McMaster Computer Science Outreach visits schools in Ontario, Canada to teach basic Computer Science topics and discuss the impacts of the Information Revolution, teaching children from six to sixteen, using Elm for the programming portion of our programming. Elm looks a lot like Haskell, but does not have user-definable type classes and is strict. We presented a paper about our tools and curriculum at TFPIE 2017, https://www.cs.kent.ac.uk/people/staff/sjt/TFPIE2017/TFPIE_2017/Programme.html.
We would like to thank Google for igniteCS funding, which allowed us to run seven-week workshops in schools in high-needs schools. Many of their contributions are in our Hall of Fame: http://outreach.mcmaster.ca/menu/fame.html.
|Report by:||Marco Zocca|
|Participants:||Nikita Tchayka, Mahdi Dibaiee, |
John Vial, Stefan Dresselhaus,
and many others
The DataHaskell community was initiated in September 2016 as a gathering place for scientific computing, machine learning and data science practitioners and Haskell programmers; we observe a growing interest in using functional composition, domain-specific languages and type inference for implementing robust and reusable data processing pipelines.
DataHaskell revolves around a Gitter chatroom and a GitHub organization. The community is slowly but steadily growing; new interested people join the chatroom discussion (which now counts more than 230 unique users) every few days, and 20 or so are active on an average week.
After an informal survey we concluded that large part of our userbase seems to be lacking most:
The notebook-IDE situation has improved, thanks for example to an updated iHaskell and the new, native Haskell.do editor. Dataframes are a more subtle topic, that require domain-specific optimizations, and we are also actively working on that after adopting the analyze package.
Some of us met in person at ZuriHac (Zurich) and ICFP 2017 (Oxford). An informal DataHaskell workshop took place on Saturday 9, 2017 at ICFP, during which a series of lightning talks showed various applications of the current state of the library ecosystem, e.g. rendering mathematics-heavy code on Hackage, high-performance numerical computing, probabilistic EDSLs and notebook usage for exploratory data analysis.
The workshop was well-received and we are evaluating various options for upcoming meetings, e.g. to be hosted at either functional programming or data science conferences.
We cherish the open and multidisciplinary nature of our community, and welcome all new users and contributions.
There are many different courses on functional programming – mostly taught in Haskell – at Eötvös Lorand University, Faculty of Informatics. Currently, we are offering the following courses in that regard:
In addition to these, there is also a Haskell-related course, Type Systems of Programming Languages, taught for Hungarian master’s students in Software Technology. This course gives a more formal introduction to the basics and mechanics of type systems applied in many statically-typed functional languages.
For teaching some of the courses mentioned above, we have been using an interactive online evaluation and testing system, called ActiveHs. It contains several dozens of systematized exercises, and through that, some of our course materials are available there in English as well.
Our homebrew online assignment management system, "BE-AD" keeps working on for the fourth semester starting from this September. The BE-AD system is implemented almost entirely in Haskell, based on the Snap web framework and Bootstrap. Its goal to help the lecturers with scheduling course assignments and tests, and it can automatically check the submitted solutions as an option. It currently has over 700 users and it provides support for 12 courses at the department, including all that are related to functional programming. This is still in an alpha status yet so it is not available on Hackage as of yet, only on GitHub, but so far it has been performing well, especially in combination with ActiveHs.
|Report by:||Nils Dallmeyer|
Semantics of Functional Programming Languages. Extended call-by-need lambda calculi model the semantics of Haskell. We analyze the semantics of those calculi with a special focus on the correctness of program analyses and program transformations. In our recent research, we use Haskell to develop automated tools to show correctness of program transformations, where the method is syntax-oriented and computes so-called forking and commuting diagrams by a combination of several unification algorithms that operate on a meta-representation of the language expressions and transformations.
We therefore developed variants of unification on the meta-representation: An expressive variant that covers all the specifics of normal-order reduction rules. Others are extensions of nominal unification with built-in alpha-equivalence: one variant can deal with recursive lets, the second one permits variable-variables, and a third one permits context-variables and a meta-form of distinct-variable-conditions.
Improvements In recent research we analyzed whether program transformations are optimizations, i.e. whether they improve the time and/or space resource behavior. We showed that common subexpression elimination is an improvement, also under polymorphic typing. We developed methods for better reasoning about improvements in the presence of sharing, i.e. in call-by-need calculi. We also developed a simulation-based method to validate time-improvements respecting the sharing structure. We showed for different transformations that they are space improvements and developed a tool for specific space analyses.
Concurrency We analyzed a higher-order functional language with concurrent threads, monadic IO, MVars and concurrent futures which models Concurrent Haskell and proved that this language conservatively extends the purely functional core of Haskell. In a similar program calculus we proved correctness of a highly concurrent implementation of Software Transactional Memory (STM) and developed an alternative implementation of STM Haskell which performs quite early conflict detection. Moreover we developed an algorithm that optimizes concurrent programs w.r.t. space and analyzed the impact on complexity of synchronization requirements.
Grammar based compression This research topic focuses on algorithms on grammar compressed data like strings, matrices, and terms. We implemented several algorithms as a Haskell library.
The Functional Programming group at Kent is a subgroup of the Programming Languages and Systems Group of the School of Computing. We are a group of staff and students with shared interests in functional programming. While our work is not limited to Haskell – we use for example also Erlang and ML – Haskell provides a major focus and common language for teaching and research.
Our members pursue a variety of Haskell-related projects, several of which are reported in other sections of this report. In September Joanna Sharrad joined us as a new PhD student to work with Meng Wang and Olaf Chitil on type error debugging. For her undergraduate work on delta debugging of type errors she already won the second place in the Student Research Competition at ICFP 2017. Stephen Adams is working on advanced refactoring of Haskell programs, extending HaRe. Andreas Reuleaux is building in Haskell a refactoring tool for a dependently typed functional language. Maarten Faddegon built the lightweight tracer and algorithmic debugger Hoed for real-world Haskell programs and successfully defended his PhD thesis. Olaf Chitil develops these ideas on tracing further, with a small prototype tracer HatLight for a subset of Haskell and the aim of developing the Haskell tracer Hat further. Dominic Orchard is working on co-effectful programming and applying verification in computational science. He also develops tools in Haskell for analysing, refactoring and verifying Fortran programs. Meng Wang is working on lenses, bidirectional transformation and property-based testing (QuickCheck). Together with last years visitor Colin Runciman from the University of York, Stefan Kahrs is working on minimising regular expressions, implemented in Haskell. Scott Owens is working on verified compilers for the (strict) functional language CakeML. Simon Thompson, Scott Owens, Hugo Férée and Reuben Rowe are working on an EPSRC project on trustworthy refactoring. They are studying refactoring for CakeML and OCaml, informed by their previous work for Haskell and Erlang.
We are always looking for more PhD students. We are particularly keen to recruit students interested in programming tools for verification, compilation, tracing, refactoring, type checking and any useful feedback for a programmer. The school and university have support for strong candidates: more details at http://www.cs.kent.ac.uk/pg or contact any of us individually by email.
We are also keen to attract researchers to Kent to work with us. There are many opportunities for research funding that could be taken up at Kent, as shown in the website http://www.kent.ac.uk/researchservices/sciences/fellowships/index.html. Please let us know if you’re interested in applying for one of these, and we’ll be happy to work with you on this.
Finally, if you would like to visit Kent, either to give a seminar if you’re passing through London or the UK, or to stay for a longer period, please let us know.
Functional Programming continues at KU and the Computer Systems Design Laboratory in ITTC! The System Level Design Group (lead by Perry Alexander) and the Functional Programming Group (lead by Andrew Gill) together form the core functional programming initiative at KU. All the Haskell related KU projects are now focused on use-cases for the remote monad design pattern. One example is the Haskino Project (→4.14.3).
The Functional Programming Group: http://www.ittc.ku.edu/csdl/fpg
|Report by:||Jennifer Hackett, Martin Handley|
The School of Computer Science at the University of Nottingham is home to the Functional Programming Laboratory, a research group focused on all theoretical and practical aspects of functional programming, together with related topics such as type theory and category theory. The lab is led by Thorsten Altenkirch and Graham Hutton, with Henrik Nilsson and Venanzio Capretta as academic staff. In addition, we currently have three post-doctoral researchers, eight postgraduate students and one intern.
Our interests are wide-ranging, including:
The Functional Programming Lab is currently home to an EPSRC grant on reasoning about the efficiency of programs. Jennifer Hackett and Graham Hutton are currently preparing a paper for ICFP that presents a cost-aware parametricity theorem that produces free theorems that can be used to reason about time costs, alongside another paper exploring an approach to reasoning about efficiency based on metric spaces. Also, Martin Handley and Graham Hutton have developed a tool that will assist programmers to reason inequationally about the cost behaviour of their programs. A paper on this tool has been submitted to the upcoming European Symposium on Programming.
Jan Bracker and Henrik Nilsson are working on unifying generalizations of monads and applicative functors. Their work has produced the supermonads library (→4.1.3) which offers a unified way to work with these generalized notions in Haskell (details in the independent entry). In addition to the practical support of these notions they are also exploring the theoretical foundations of said notions in category theory. Future work may involve generalizing arrows as well.
Functional Reactive Programming (FRP) remains an active part of our research. Henrik Nilsson and Ivan Perez have worked on monadic FRP, FRP extensions such as time transformations, property-based testing and debugging for FRP, Reactive Values and Relations (RVR). We have also worked on applications of these technologies; e.g., to games and music. In particular, together with summer interns Guerric Chupin and Jin Zhan, we developed the Arpeggigon (→4.18.4), a Functional Reactive Musical Automaton, as a substantial test case for FRP and RVR that is also an interesting and fun application in its own right. This has led to a number of publications and talks (PADL, ICFP, Haskell Symposium, FARM, London Haskell Meetup, Haskell eXchange, Haskell in Leipzig) as well as open source software releases. The Yampa (→4.17.1) FRP implementation is also actively being maintained.
The lab plays an active role in teaching, with Haskell playing an important role in many of the modules offered. Modules include: Programming, Programming Paradigms, Advanced Functional Programming, Machines and Their Languages, Compilers, Introduction to Formal Reasoning, Advanced Algorithms and Data Structures, Languages and Computation and Foundations of Programming.
Every Friday afternoon we hold the FP Café, an informal meeting where we hold whiteboard discussions on current activities, general business or anything that sounds interesting. Visitors are welcome: if you want to come along (perhaps even to give a talk yourself), please contact us!
The lab plays a leading role in the Midlands Graduate School in the Foundations of Computing Science.
|Report by:||Erik de Castro Lopo|
|Participants:||Ben Lippmeier, Shane Stephens, and others|
We are a seminar and social group for people in Sydney, Australia, interested in Functional Programming and related fields. Members of the group include users of Haskell, Ocaml, LISP, Scala, F#, Scheme and others. We have 10 meetings per year (Feb–Nov) and meet on the fourth Wednesday of each month. We regularly get 40–50 attendees, with a 70/30 industry/research split. Talks this year have included material on compilers, theorem proving, type systems, Haskell web programming, dynamic programming, Scala and more. We usually have about 90 mins of talks, starting at 6:30pm. All welcome.
Since autumn 2014 Haskellers in Regensburg, Bavaria, Germany have been meeting roughly once per month to socialize and discuss Haskell-related topics.
We usually have dinner first and then move on to have a talk. Topics vary quite a bit, from introductory to advanced, from theoretical to practical, and we have been looking at other languages such as Scala or dependently typed languages as well.
There are typically between 5 and 15 attendees, and we often get visitors from Munich and Nürnberg.
New members are always welcome, whether they are Haskell beginners or experts. If you are living in the area or are visiting, please join! Meetings are announced a few weeks in advance on our meetup page: http://www.meetup.com/Regensburg-Haskell-Meetup/.
Since March 2015 haskellistas, scalafists, lambdroids, and other fans of functional programming languages in Augsburg, Bavaria, Germany have been meeting every four weeks in the OpenLab, Augsburg’s hacker space. Usually there are ten to twenty attendees.
At each meeting, there are typically two to three talks on a wide range of topics of interest to Haskell programmers, such as latest news from the Kmettiverse and introductions to the category-theoretic background of freer monads. Afterwards we have stimulating discussions while dining together.
From time to time we offer free workshops to introduce new programmers to the joy of Haskell.
Newcomers are always welcome! Recordings of our talks are available at http://www.curry-club-augsburg.de/.
Born in Summer 2015, the Italian Haskell Group is an effort to advocate functional programming and share our passion for Haskell through real-life meetings, discussion groups and community projects.
There have been 3 meetups (in Milan, Bologna and Florence), our plans to continue with a quarterly schedule. Anyone from the experienced hacker to the functionally curious newbie is welcome; during the rest of the year you can join us on our irc/mumble channel for haskell-related discussions and activities.
RuHaskell is the Russian-speaking community of haskellers. We have a website with Haskell-related articles, a podcast, a subreddit and some Gitter chats including one for novice haskellers specially. We also organize mini-conferences about twice a year in Moscow, Russia. The 4th mini-conference has taken place in the April, 2017.
Since 2012 the NY Haskell Users Group has been hosting monthly Haskell talks and the occasional hackathon. Over fifteen-hundred members are registered on Meetup for the group, and talk attendence ranges between sixty to one hundred and twenty. NYHUG has also been organizing, on and off, beginner-oriented hangouts where people can assemble and study and learn together. And as of recently, NYHUG has also been the home base for organizing a Haskell Programming from First Principles study group, as well as an active Slack channel where ongoing discussion for the reading group takes place.
In 2015, the NY Haskell organizers launched the Compose Conference, which was held again in 2016, with a sibling “Compose::Melbourne” conference being held in 2016 as well. Compose is a cross-language conference for functional programmers, focused on strongly-typed functional languages such as Haskell, OCaml, F#, and SML. It aims to be both practical and educational, among other things providing opportunity for researchers to present the more applicable elements of their work to a wide audience of professional and hobbyist functional programmers. It is our hope to continue Compose and also to extend it to sibling conferences in other geographic areas as well sharing similar goals and format.
Japan Haskell User Group (a.k.a Haskell-jp) is a Haskellers’ community group in Japan, established at April 2017.
Since it began, we have tried various activities to help Haskellers discuss, collect, learn, and deliver any information related to Haskell.
Today we have two major updates since the last HCAR:
Thanks to Fumiaki Kinoshita (https://github.com/fumieval) and the voters in Haskell-jp, we got a brand-new, nice, and more Japanese logo. It’s nicknamed “Sakulambda”, after its motif, sakura and the lambda character.
All you have to do is send a pull request to the Haskell-jp repository with your article written in Markdown format.
We will review the rendered article as well as its source code, and deploy it by merging on master.
These features are implemented by Circle CI’s build artifacts and Travis CI’s automatic deployment.
|Report by:||Yasuaki Kudo|
Tokyo Haskell Meetup is a group that meets mostly every month in Tokyo. English is the dominant language and we enjoy casual and lively discussions of Haskell and Functional Languages, (and others including Philosophy, Politics, Business, etc.), while helping each other learn Haskell. Our members proficiency in Haskell is very diverse – from the beginners (such as myself) to the experts.
Functional programmers are rare to find in Indonesia, especially for Haskell where they are less than 30 from hundreds of thousands programmers that the country has.
I started a functional programming group at Telkom University. My goal is to create a great community of functional programmers starting from university.
<wisnu at nurcahyo.me>
Haskell-serbia is website for the Haskell user group in Serbia.
The idea is to organize meetups, write tutorials and generally spread the Haskell programming language in Serbia.
It is in active development and website is up and running.
There are plans to add fresh new look to website, customize user profile pages, write more tutorials and generally get more people involved.