- Data-Haskell - Haskell.org

ANN closed-intervals-0.1
by Olaf Klinke 24 Mar '21

24 Mar '21

Dear Cafe, I am pleased to announce the first release of closed-intervals [1], a package for querying and manipulating collections of closed intervals in totally ordered types. Other packages exist which either deal with a single interval type [2,4] or provide an interval type class [3]. Having both closed, open and half-open intervals makes the interface complicated, however. The focus of closed-intervals is on intervals including both end-points and is intended to be used on records with length or duration information. My use cases are mostly sequences of annotated time intervals [*], parsed from time-stamped data. Against these sequences overlap-, coverage- and intersection queries are run using single intervals as query. The package contains many doctests. Testing builds on Henning Thielemann's doctest-extract [5] and doctest-exitcode-io [6] packages. closed-intervals is, after provenience [7], the second package in an effort to open-source my employer's entire Haskell codebase. We will gradually publish from general to problem-specific. Cheers, Olaf [1] https://hackage.haskell.org/package/closed-intervals [2] https://hackage.haskell.org/package/data-interval [3] https://hackage.haskell.org/package/IntervalMap [4] https://hackage.haskell.org/package/intervals [5] https://hackage.haskell.org/package/doctest-extract [6] https://hackage.haskell.org/package/doctest-exitcode-io [7] https://hackage.haskell.org/package/provenience [*] Since time types are fine-grained and a time point is an idealized concept, the question of end-point inclusion is not that relevant for time intervals. We do distinguish between intersection in end-points and proper intersection, though.

1 0

FHPNC'19 Deadline Extension and 2nd Call for Papers
by Marco Zocca 09 May '19

09 May '19

We are happy to extend the submission deadline to the 2019 ACM SIGPLAN Functional High Performance and Numerical Computing Workshop until Saturday, May 25, 2019, 12 PM AoE ("anywhere on Earth", i.e. UTC-6). Marco Zocca and Dominic Steinitz FHPNC'19 Organizing Committee ================================= 2nd Call for Papers (Extended Abstracts and Full Papers) ACM SIGPLAN Workshop on Functional High-Performance and Numerical Computing (FHPNC), Berlin, August 18, 2019 Satellite event of the 24th ACM SIGPLAN International Conference on Functional Programming (ICFP 2019) 18 - 23 August, 2019 Homepage : https://icfp19.sigplan.org/home/FHPNC-2019#Call-for-Papers The ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing aims to bring together researchers and practitioners exploring or employing the use of functional or declarative programming languages or techniques in scientific computing, and specifically in the domains of high-performance computing and numerical programming. The purpose of the meeting is to enable sharing of results, experiences, and novel ideas about how high-level, declarative techniques can help make high-performance, distributed/parallel, or numerically-intensive code dealing with computationally challenging problems easier to write, read, maintain, or portable to new hardware architectures. Areas of interest include, but are not limited to: * relevant compiler technologies * runtime systems (including fault tolerance mechanisms and those supporting distributed or parallel computation) * domain-specific languages (embedded or standalone) * type systems * formal methods * software libraries (e.g. for exact or interval arithmetic). ## Submission details Submissions should fall into one of two categories: * Regular research papers (up to 12 pages) * Extended abstracts (1 - 2 pages) The bibliography will not be counted against the page limits for either category. Regular research papers are expected to present novel and interesting research results, and will be included in the formal proceedings. Extended abstracts should report work in progress that the authors would like to present at the workshop; they will be evaluated primarily for relevance and interest. Extended abstracts will be distributed to workshop attendees but will not be published in the formal proceedings. We welcome submissions from PC members (with the exception of the PC Chair), but these submissions will be held to a higher standard. Submission is handled through the HotCRP site. All submissions should be in portable document format (PDF) and formatted using the ACM SIGPLAN style guidelines. Submissions written with LaTeX are required to use the ‘acmart’ format and the two-column ‘sigplan’ subformat (not to be confused with the one-column ‘acmlarge’ subformat!). Extended Abstracts must be submitted with the label ‘Extended abstract’ clearly in the title. ## Publication The proceedings of FHPNC 2019 will be published in the ACM Digital Library. ## Related links * Author Information and LaTeX templates : http://www.sigplan.org/Resources/Author/ * Attendee Code of Conduct: http://www.sigplan.org/Resources/Policies/CodeOfConduct/

1 0

[CfP] Functional High-Performance and Numerical Computing 2019
by Marco Zocca 11 Apr '19

11 Apr '19

===================================================== Call for Papers (Extended Abstracts and Full Papers) ACM SIGPLAN Workshop on Functional High-Performance and Numerical Computing (FHPNC), Berlin, August 18, 2019 Satellite event of the 24th ACM SIGPLAN International Conference on Functional Programming (ICFP 2019) 18 - 23 August, 2019 ===================================================== https://icfp19.sigplan.org/home/FHPNC-2019#Call-for-Papers The ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing aims to bring together researchers and practitioners exploring or employing the use of functional or declarative programming languages or techniques in scientific computing, and specifically in the domains of high-performance computing and numerical programming. The purpose of the meeting is to enable sharing of results, experiences, and novel ideas about how high-level, declarative techniques can help make high-performance, distributed/parallel, or numerically-intensive code dealing with computationally challenging problems easier to write, read, maintain, or portable to new hardware architectures. Areas of interest include, but are not limited to: * relevant compiler technologies * runtime systems (including fault tolerance mechanisms and those supporting distributed or parallel computation) * domain-specific languages (embedded or standalone) * type systems * formal methods * software libraries (e.g. for exact or interval arithmetic). ## Submission details Submissions should fall into one of two categories: * Regular research papers (up to 12 pages) * Extended abstracts (1 - 2 pages) The bibliography will not be counted against the page limits for either category. Regular research papers are expected to present novel and interesting research results, and will be included in the formal proceedings. Extended abstracts should report work in progress that the authors would like to present at the workshop; they will be evaluated primarily for relevance and interest. Extended abstracts will be distributed to workshop attendees but will not be published in the formal proceedings. We welcome submissions from PC members (with the exception of the PC Chair), but these submissions will be held to a higher standard. Submission is handled through the HotCRP site. All submissions should be in portable document format (PDF) and formatted using the ACM SIGPLAN style guidelines. Submissions written with LaTeX are required to use the ‘acmart’ format and the two-column ‘sigplan’ subformat (not to be confused with the one-column ‘acmlarge’ subformat!). Extended Abstracts must be submitted with the label ‘Extended abstract’ clearly in the title. ## Publication The proceedings of FHPNC 2019 will be published in the ACM Digital Library. ## Related links * Author Information and LaTeX templates : http://www.sigplan.org/Resources/Author/ * Attendee Code of Conduct: http://www.sigplan.org/Resources/Policies/CodeOfConduct/

1 0

DataHaskell Newsletter #1, June 2018
by Marco Zocca 17 Jun '18

17 Jun '18

Hi all, I'd like to share with you a few of the things that happened during the past months on and around DataHaskell (DH), and a summary of the current state of things. Time permitting, this will become a regular newsletter, with the idea to keep up to date those who don't usually hang out on our Gitter chatroom [1]. ---------------------------------------------------------------------------------------------------------------- * Outreach activities and related meetings ICFP 2017 : Early September 2017 we had an hour-long lunch mini-workshop at ICFP during which a few people presented how they use Haskell in their numerical and data-crunching work. Mostly positive opinions, as well as a "contrarian" viewpoint (from an expert practitioner) who lamented the low-performance of native Haskell numerical code (e.g. the large memory footprint of boxed data). Michal Gajda presented how he uses IHaskell for interactive data exploration (btw, it's a thing and you can try it today!), Trevor McDonell introduced Accelerate (the high-performance array library that can target CUDA GPUs), Adam Scibior presented `monad-bayes` and Praveen Narayan presented `hakaru` (two probabilistic progamming laguages embedded in Haskell). ZuriHac 2018 : community bonding mostly (read: no hacking was done). Received more feedback of the usual sort "how do I do X in Haskell?" "I was expecting a more advanced state of machine learning capabilities in Haskell", etc. There may or may not be a set of Haskell bindings for Apache Arrow in the works, stay tuned! ICFP 2018 : There will be two very interesting workshops (FHPC, functional programming in high-performance computing and NPFL, numerical programming in functional languages), for those who will be attending the conference. One of the workshop chairs of NPFL is Dominic Steinitz of Tweag, author of the excellent idontgetoutmuch.wordpress.com blog. ---------------------------------------------------------------------------------------------------------------- * DH survey On April 5 I've published a survey [2], that tried to gauge the community interest and pain points related to doing "data science" in our beloved language. The survey is still open but I won't be collecting data anymore (70 people have taken the questionnaire and 62 have completed it), and I've scraped and formatted the dataset (you can find it at https://github.com/DataHaskell/surveys) Some of the free text answers are particularly interesting. I don't have much time currently to create the plots and publish a blog post about it, but it would be a Good Thing to have, if anyone wants to step up. The project backbone is ready for new contributors! ---------------------------------------------------------------------------------------------------------------- * Contributors wanted : External projects At regular intervals, new exciting projects appear and it's becoming quite hard to keep track of everything that's happening in this area. I'd like to highlight here a few that are seeing significant activity as of late and have large impact potential. ** General-purpose (e.g. numerics-related) `numhask` [3] is an experiment at replacing the numerical typeclasses of `base`, in particular those related to `Num`, in favor of a finer-grained and more principled hierarchy. It is already available and receiving quite a bit of attention recently, but there still are a number of areas that could use some help, for example property checking, test coverage, the `accelerate` bindings, etc. ** Data science `boke-hs` [4] : a native Haskell interface to generate Bokeh plots. The project was mostly developed during the ZuriHac weekend; currently it's functional and you can create line plots with it, but helping out with the domain mapping would be a very valuable contribution. In particular, the library emits JSON blobs that are interpreted in the browser by BokehJS ; "domain mapping" means creating the Haskell data that will serialize into JSON appropriately. A currently-unnamed library for linking databases and Haskell dataframes. This is Gagandeep Bhatia's ongoing Summer of Haskell project, and you can find a writeup and links to his current work (which uses `beam` as a database binding library and `Frames` as type-safe in-memory representation) here: https://www.gagandeepbhatia.com/blog/ . `haskell.do` [5] : a native Haskell notebook/interactive editor/IDE for the browser. The project started well, has a website and a few initial releases, but currently needs some love to achieve its full potential. Interactive development with visual feedback is a crucial part of data science work, and contributions to this project will be very valuable. ** Machine learning `hasktorch` [6] is in developer beta ! This is a set of Haskell bindings for `torch` (the deep learning C library), and comes wrapped in a typed interface that provide statically-checked vector dimensions, and the like. ** Probabilistic programming languages `deanie` [7] is a probabilistic EDSL. Currently it's lacking code for its general-purpose inference engine (see https://github.com/jtobin/deanie/blob/master/lib/Deanie/Inference/Comonadic…) The implementation technique is related to "Co-Free for interpreters" as shown in [8]. ---------------------------------------------------------------------------------------------------------------- * Contributors wanted : DataHaskell internal projects We do have a few projects set up that could use some collaborators. If you are willing to contribute to any of these, please open a ticket on the project issue tracker and the maintainers will be in touch shortly. * `type-providers` : a unified code generation library for accessing structured data in a type-safe way : https://github.com/DataHaskell/type-providers . Michal Gajda is willing to mentor a student who wants to translate his own `json-autotype` to a new library that can generate type-safe code for XML, and can be queried in-memory via Frames. Contributing to this library will likely require some knowledge of Template Haskell. * A fork of the venerable `statistics` library, that separates the dense linear algebra library as a standalone library : https://github.com/DataHaskell/statistics . There is currently a PR to the upstream library (https://github.com/bos/statistics/pull/143) longer-term plans include giving it a typeclass-based interface, for example based on `numhask`. * `numhask-linear-algebra` : this is a longer shot at unifying native linear algebra libraries under a single typeclass representation, as provided by `numhask` (project at https://github.com/DataHaskell/numhask-linear-algebra ). This is something that's currently unavailable in the Haskell ecosystem and will be a highly relevant contribution to many. ---------------------------------------------------------------------------------------------------------------- * DataHaskell internal administration In addition to helping out with the survey blogpost, some help in the following areas would be much appreciated ** Knowledge base : testers wanted ! The knowledge base ( http://www.datahaskell.org/docs/community/current-environment.html ) is a growing curated collection of libraries for doing data science-related tasks; anything from manipulating storable data to statistical inference. It's pretty useful as it is, but I think the entries should be annotated with additional information, such as the degree of completeness and developer- and user-friendliness. For this, some help in testing out the libraries and reporting back would be very useful. Ultimately, it would be very useful to contribute such an assessment back to the "state of the ecosystem" document [9], which is highly visible but not so much up to date on the data-science related things. ** Maintainers wanted ! Currently, Nikita and I are the only owners of the github organization. It would be great if additional people stepped up for "tending the garden", e.g. keeping track of issue tickets, filling out the documentation, lending a hand on the gitter channel to address newcomers' issues, etc. Historically, data science and numerical computing have been underserved niches of the Haskell ecosystem, and while things are steadily improving, together we can bring about this change soon ! ---------------------------------------------------------------------------------------------------------------- That's it for now, I hope you enjoyed this Newsletter; don't hesitate to share your thoughts either here or on our Gitter chatroom! [1] Marco github.com/ocramz ---------------------------------------------------------------------------------------------------------------- References : [1] DH Gitter chatroom : https://gitter.im/dataHaskell/Lobby [2] DH user survey April 2018: https://www.surveymonkey.com/r/3FBBJWR [3] numhask : github.com/tonyday567/numhask [4] boke-hs , native Haskell bindings for Bokeh : https://github.com/ahaym/boke-hs [5] HaskellDO, the interactive Haskell editor: http://haskell.do/ , https://github.com/theam/haskell-do [6] hasktorch, the Haskell bindings to Torch : https://github.com/hasktorch/hasktorch [7] deanie , probabilistic programming language : https://github.com/jtobin/deanie [8] "Free for DSLs, co-free for interpreters" http://dlaing.org/cofun/posts/free_and_cofree.html [9] State of the Haskell ecosystem : https://github.com/Gabriel439/post-rfc/blob/master/sotu.md

1 0

DataHaskell User Survey
by Marco Zocca 05 Apr '18

05 Apr '18

Dear all, the community around datahaskell.org has been slowly but steadily growing since its inception in 2016, and with it the diversity of its members. Its mission is to provide a home for data science and numerical computation students and practitioners who would like to use Haskell in their work and explorations. In order to best represent and serve the community, we'd like to know it in the first place, which is why we have prepared this little questionnaire (10 questions, which should take around 5 minutes to complete): https://www.surveymonkey.com/r/3FBBJWR No personal data are required and the results will only be published in aggregate form at a later stage. The raw data will only be stored and used for producing the aggregate report, after which it will be deleted. Thank you in advance for your time; Best, Marco Zocca github.com/ocramz hackage.haskell.org/user/ocramz

1 0

Numerical / Data Special Interest Group at ICFP'17
by Marco Zocca 28 Aug '17

28 Aug '17

Dear all, thanks to the ICFP organisers and to D.Steinitz (https://idontgetoutmuch.wordpress.com/) we will have a late-minute workshop on the numerical and data-related Haskell at ICFP'17 (Oxford) on Saturday 9th September in the slot 12:30 - 14:00. Looking forward to meeting you all there; Best, Marco Zocca https://github.com/ocramz

1 0

DataHaskell impromptu workshop at ICFP'17 ?
by Marco Zocca 16 Aug '17

16 Aug '17

Dear all, among those that will attend the last three days of ICFP (i.e. the Haskell symposium and CUFP), are there people who would be interested in meeting to discuss possible future directions for the DataHaskell project? Looking forward to your feedback; Best, Marco

2 1

Exploring the Titanic dataset with Haskell
by Nikita Tchayka 07 Mar '17

07 Mar '17

Hello dataHaskell! I'd like to inaugurate our mailing list by showing something that I'm working on for our documentation site. After checking some notebooks in Kaggle, this notebook <https://www.kaggle.com/mrisdal/titanic/exploring-survival-on-the-titanic> by Megan Risdal really caught my eye. It looks really complete and also, accomplishes a lot of tasks ranging from easy ones as simple feature engineering by extracting titles from the names, to more complex ones like applying a Random Forest. It also includes visualization, which is cool too. I'm currently working on porting it to Haskell, so we can see what's missing and what's there. I'm using Eric Conlon's (@ejconlon) Analyze library, and even though its still young, I absolutely love it. It allows easy CSV loading and there are no name clashes like in Frames, nor you have to define your datatypes first as in Cassava. The notebook itself can be found here <https://github.com/NickSeagull/ex01-exploring-titanic/blob/master/src/Lib.hs>, it's in a repo in my Github and it can be loaded in HaskellDO, although right now I'm using Vim + Stack REPL, until error highlighting is implemented. Cheers -- nikita tchayka . software craftsman { nickseagull.github.io }

1 0