Alexandr Kurilin from Front Row Education recently wrote an article about their usage of Haskell for the Commercial Haskell Special Interest Group. I asked his permission to post that article to our blog as well.The mission
Front Row Education was founded to change the way math education is done in a modern day classroom. In the web universe we have all sorts of great tools for tracking, analyzing and incentivising user behavior: complex analytics, rich data visualizations, a/b testing, studying usage patterns over time, cohort analysis, gamification etc. We figured: instead of using the above to have granny click on more ads, let's make these powerful techniques available to teachers, parents and school administrators to make math education more engaging and effective.
Front Row allows schools to track student progress over time, identify areas of struggle, learn how to address them, all the while encouraging more quality practice. Learning math this way becomes a interactive and compelling experience, providing immediate feedback and adjusting content with every answer. As students practice, they generate rich data that school staff uses to continuously course-correct and fill in the gaps.
Numerous experiments from past years show that making Front Row a regular part of a math classroom leads to improved conceptual understanding, a lower rate of students falling behind, and improved scores on state tests. As of today Front Row helps over a million students in their regular math practice, and has been used in over 30% of US K-8 schools.Our journey to Haskell
As of today Front Row uses Haskell for anything that needs to run on a server machine that is more complex than a 20 line ruby script. This includes most web services, cron-driven mailers, command-line support tools, applications for processing and validating content created by our teachers and more. We've been using Haskell actively in production since 2014.
At the time of the switch we were already familiar with the functional programming world. The central piece to the Front Row system is the JSON API used by both the student and teacher web experiences. I wrote the first version of the API in 2013 in Clojure on top of the Ring/Compojure micro-framework. At the time I didn't have plans for the API to grow to serve the kind of size and traffic we see today: it was mostly a way for me to really dive into functional programming and understanding design challenges that other popular frameworks had to come across.
Building your own framework is a fantastic learning experience, but it is also a significant commitment: without investing a ton of time and effort into the framework, you'll end up with something very bare-bones and hard to turn it into a production quality, fully-featured application. It takes innumerable iterations to make a framework extensible, modular and well maintained with a team of 1-3 developers, busy with dozens other tasks that a fast-moving startup demands.
Clojure at the time didn't offer any alternatives as far as web frameworks were concerned, and we were already starting to see the inherent critical weakness behind building large modular systems in dynamically typed languages: refactoring is a serious pain and something you will avoid at all costs because it's hard to ensure you're not breaking anything. It's not that bad if you have ONE codebase that doesn't have dependencies, but once you get into two digits you're in for a bad time.
Switching to Haskell and the Yesod framework seemed like a natural step forward: a strongly typed, purely functional, highly expressive language that would finally allow refactoring and moving fast to be painless. On top of it, a beautifully designed, extensible web framework with years of polish, one of the best high-performance web servers in the industry, extreme attention to type safety, and an all-star team of OSS contributors supporting it.
Moving from Clojure to Haskell didn't feel like a massive jump: a lot of concepts translate pretty closely, although Haskell offers a much richer vocabulary than just maps and vecs. Monads, type classes, IO etc. eventually clicked, and it was smooth sailing after that.Advantages of using Haskell
Where does Haskell fit into all of this you say? As the development team of a small early stage edtech startup, we have two main goals:
- Iterate as fast as possible on new educational concepts, business model experiments and user feedback. Basically, crank out as much code as possible while keeping the quality bar very high.
- Stretch our runway, be conservative with our very limited resources
Haskell fits in pretty well with both of goals.Static typing
First of all, static typing is essential when it comes to keeping the system always in a working state. Coming from a dynamically typed universe, it's surprising how much time you can save on writing unit tests, because you are getting more certainty from the compiler: no more null exceptions, no type mismatches in function calls, no more forgetting about dealing with the empty list case etc. A whole class of pesky, incredibly common and banal bugs is eliminated from your work: you now have more bandwidth to worry about implementing user stories instead of obsessing that your application doesn't blow up due to sloppy oversight.
I still remember one of my biggest Haskell/Yesod "aha" moments: not only does Yesod make sure that routes in your HTML are type-safe, but even image files linked in tags are verified to exist on disk by the compiler. No .jpg, no build, it's that simple. It's a level of guarantee that dramatically increases your confidence in the code at barely any cost.Modularity
Modularity is another big one. We have a central module at the bottom of every one of our web applications, APIs, tools and cron binaries. This module wraps the database entities and the SQL logic necessary to access them. It also provides a lot of common shared functionality that should not be implemented more than once. Since the schema changes very aggressively, we need a way to make sure our applications are updated ASAP, we can't wait for things to blow up in production. Updating our entity definitions in that one module prevents every application built on top of it from compiling again until the change is dealt with.
No more API call mismatches, no more using an old schema, no more apps running against an old deprecated version that can lead to breaking the db state. As many others have stated, Haskell is the first language out there that feels like it manages to achieve true modularity: purity and defining what context a function is allowed to run in ensure that a library call can lead to no surprises. Testing side-effect free functions is much simpler than continuously dealing with system state.Efficiency
Regarding the second point, why would Haskell stretch your runway? Simple. You're writing fewer bugs, you're reusing more code, new developers are causing less damage, and you have more room to deal with technical debt before it bites you. Purity and static types allow a team to aggressively refactor the codebase without having to worry that they might have forgotten to update something: a combination of a light layer of spec-style tests and a very picky compiler provide you with most of what you need to make refactoring a non-issue. More refactoring = more long-term productivity, higher team morale, more pride in one's work. Doing the same with a Ruby is as fun as pulling teeth.
All of the above adds up to needing fewer developers, as less time is spent on maintenance, which ultimately equals a higher chance of your company getting somewhere thanks to the more frequent iterations. The more stuff you try, the more likely you are to find or expand that business mechanic that will carry your business forward.Trouble in paradise
This is not to say that things aren't all perfect though, and there's still plenty of room for improvement in the ecosystem.Building
Build times, especially once the whole constellation of Yesod and Persistent packages are brought into the mix, are not insignificant. It still takes a good 5-10 min to build our larger web application on our beefiest machines. There are optimizations that can be made in this space which we haven't adopted yet, such as caching already build object files to avoid having to re-compile them every time, so I'm confident this will be a non-issue in the nearby future, but it's still worth being aware of. GHC works hard, you need to provide it with enough juice or time to let it do its job.Testing
The testing frameworks out there are still fairly spartan from the developer experience standpoint. If you test Yesod with hspec, the premier BDD library for Haskell, there's currently no way to insert a bunch of rows into the database during fixtures and pass the results into the individual test cases. You have to wrap each test case in additional function calls to pull that off, adding more boilerplate to your tests.
Additionally, it's not possible to find out which one of your specific test cases failed when checking for multiple conditions within the same "it" block. This means that if you need to check the state of the system after an HTTP request, you have no clue which one of the checks failed.
Fortunately the developer(s) behind these libraries are responsive and happy to look into improvements. At the very least they're glad to point other developers in the right direction towards a PR.
This has in general been my experience with the Haskell community: things aren't perfect, but folks are always looking for a way to improve the ecosystem and want Haskell to be the best language to develop in. People are trying to carve out their little slice of paradise, and are willing to put in the hard work to make it happen.Docs
Documentation is still not quite there and the initial onboarding of new developers is still rough. There are only so many snippets to Google for, compared to e.g. Ruby and Python. A lot of documentation is very barebones and requires diving straight into the source, which is fine for a proficient Haskeller, but not for an already terrified beginner.
Many times I've witnessed senior developers get very frustrated when something wouldn't compile for hours and they couldn't find any help to move forward: be prepared to assist them before they get too grumpy. Some projects are better about it than other: Yesod and Persistent have extensive documentation and the FPComplete crew have numerous tutorials out there to help. New books come out once in a while with fresher snippets: the time-tested Real World Haskell is now fairly outdated, but the more recent Beginning Haskell is perfectly relevant. Many channels on IRC are available: #haskell-beginners, #haskell and #yesod, although sometimes it can take work to get the answer you're looking for. More than once I heard the comment that documentation seems to be written by wizards for other wizards, and if you're a lowly initiate, you will have a rough time.
I've personally had the privilege to help all of our developers skill up in Haskell and Yesod, and I've become a huge believer in the power of having someone more experienced guide you along the way. What took me several months of learning, mostly by myself, now takes our developers a couple of weeks of quality coaching. It took me a while to grok monads, type classes, type families etc., however, properly guided developers can figure it out in a matter of hours. Having a good teacher on your team will speed adoption within the organization immensely.Strength in numbers
We once experienced a very frustrating issue that got us thinking about our full commitment to Haskell as a company.
When we switched our main API to Yesod (a full rewrite), we almost immediately ran into the issue the API would burn up close to 95% of available CPU on whatever AWS EC2 instance it was hosted on. We upgraded machines, just to see if we could cheat our way out of fixing this by throwing money at the problem, and even with a $600/mo 16 core box, the API still managed to flood all of the available cores with barely any traffic hitting it. I personally spent a good week banging my head against it: was it resource contention? Was it a really big oversight in one of my handlers? Was it misconfiguration? Was it something about the EC2 environment? Why doesn't this reproducing AT ALL under profiling? Was it our database connection pooling? I threw a lot of screenshots and code samples at the community both on Google Groups and IRC: nobody else had ever seen anything like it. Uh oh.. All the while customer support requests are pouring in, teachers are aggravated, the team is looking at the devs and "their latest shiny toy", tapping their collective foot.
This is the part where picking exotic tooling for your stack can be a dangerous beast: "given enough eyeballs, all bugs are shallow", and when only a dozen teams out there are using your libraries at your scale, you are on your own when it comes to fixing issues. With Rails, there's enough volume of developers that there will be enough projects of every scale to burn-in your tool of choice. That's simply not the case with Haskell's usage numbers.
What this means is that if you're planning to bet the farm on Haskell, you need to be ready and comfortable with the idea that you might have to get your hands dirty, might be the first person to figure out a solution to the problem you're seeing. This requirement is pretty much non-existent in .NET / ruby / python at al. Start small, start simple, let the tooling grow on you as you gain experience. Start with tools that aren't mission critical until you're more confident.However..
It bears mentioning that the above concerns are being actively addressed by the community and the state of things is rapidly improving:
- Cabal, the Haskell package manager, was a real pain to work with just a few years ago and "cabal hell" is still part of Haskell vernacular. However, with sandboxes and consistent version snapshots provided by FPComplete as Stackage LTS, that problem has been mostly resolved.
- Build times are slow, but the community is coming up with improvements such as halcyon that should alleviate things considerably.
- Docs have gotten dramatically better over the past couple of years. There's been a big push towards keeping fresh, community-maintained, easy-to-follow and beginner-friendly instructions such as those provided by Chris Allen's Learn Haskell. We now even have IRC channels tailored specifically for beginners, e.g. #haskell-beginners . Today newcomers become more productive much faster than they did a few years ago.
- The community has been recently doing a better job at outreach and we've seen many new developers come make Haskell a permanent part of their toolbox. With more participants, tools get more fully-featured and more maintained.
It's a very exciting time in the history of computing to jump on the Haskell train. Yes, the community is tiny and one might get little hand-holding compared to more popular ecosystems, however Haskell offers obvious benefits to software teams who can power through the initial pain period.
Today Haskell offers some of the best tools around for delivering quality software quickly and reliably, minimizing maintenance cost while maximizing developer enjoyment. To me Haskell is that dream of "developer happiness" that we were promised many years ago by the Ruby community: I can write beautiful, short, expressive and readable code that will perform phenomenally and stand the test of time and continuous change. What more can I ask for?
Pycket: A Tracing JIT For a Functional Language
Spenser Bauman, Carl Friedrich Bolz, Robert Hirschfeld, Vasily Krilichev, Tobias Pape, Jeremy Siek, and Sam Tobin-Hochstadt
We present Pycket, a high-performance tracing JIT compiler for Racket. Pycket supports a wide variety of the sophisticated features in Racket such as contracts, continuations, classes, structures, dynamic binding, and more. On average, over a standard suite of benchmarks, Pycket outperforms existing compilers, both Racket’s JIT and other highly-optimizing Scheme compilers. Further, Pycket provides much better performance for proxies than existing systems, dramatically reducing the overhead of contracts and gradual typing. We validate this claim with performance evaluation on multiple existing benchmark suites.
The Pycket implementation is of independent interest as an application of the RPython meta-tracing framework (originally created for PyPy), which automatically generates tracing JIT compilers from interpreters. Prior work on meta-tracing focuses on bytecode interpreters, whereas Pycket is a high-level interpreter based on the CEK abstract machine and operates directly on abstract syntax trees. Pycket supports proper tail calls and first-class continuations. In the setting of a functional language, where recursion and higher-order functions are more prevalent than explicit loops, the most significant performance challenge for a tracing JIT is identifying which control flows constitute a loop -- we discuss two strategies for identifying loops and measure their impact.
Per the post title, I want to expand my knowledge and tool set for Haskell source code analysis. For example, lines of code, average line width, number of functions, is error or undefined called, etc. I'm looking to track how my source code is changing over time for a project I'm working on. What are my options?submitted by aflott
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Hi : ) I'm a newcomer to Haskell and sometimes I need basic help that I cannot find on stackoverflow - plus I do not have a formal CS-background so certain things that might be obvious to more experienced people are totally over my head.
Is there anyone that was already planning on learning Haskell on their own over the summer who would like to make a learning-team with me? Either over the Internet or in person : )
------ EDIT -----
Thanks everyone for the great number of answers : ) I think that given that I am already working on a personal project while doing the Learn You a Haskell readings and exercises, the easiest way to work on this is going to be the #haskell IRC channel - so hop on it and let's code together !submitted by teachmesomehaskell
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Unison - a next-generation programming platform, by Paul Chiusano:
- Programs are edited in a (browser-based) semantic editor which guarantees programs are well-formed and typecheck by construction
- The codebase is a purely functional data structure
- The program is a UI, and UI interaction is programming
- Persistent data sources must be accessible via a high-level, typed API
An interesting project mentioned in a comment a few weeks ago, it now has its own website and a more descriptive abstract overview explaining it's core premises.
Previous posts on Paul's blog are also of interest, and some feature videos demonstrating some aspects of Unison.
The workshop is aimed at beginners. So, even if you haven't dabbled in functional programming or Haskell, it is totally fine. If you are an experienced Haskell developer, it'll be great to have you there to help us out and catch up. Please do drop by !
You can register to the workshop here.submitted by arkhamist
For those of you who have past or current experience using a lisp--be it Scheme, Common Lisp, Clojure, or another--what is your experience using that lisp in comparison to and contrast with Haskell?
This is an extremely broad question, so if I were forced to more specificity I might ask some of the following:
- What types of projects do you find more suited to one language over the other?
- How does the prototyping experience differ for you in each?
- How abour the debugging experience?
- Are there significant differences in library availability?
- What differences do you find within the communities?
- How does your workflow differ?
- How readable/maintainable is the average code to the average skilled lisper/haskeller?
- Have you experienced significant differenes when collaborating in each?
Really, though, any and all experiences and input will be much appreciated.submitted by xelxebar
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If the integers from 1 to 999,999,999 are written as words, sorted alphabetically, and concatenated, what is the 51 billionth letter?
With the following approach, my program ran for over 8 hours without terminating:findFiftyOneBillion :: Char findFiftyOneBillion = findCharAtIndex fiftyOneBillion findCharAtIndex :: Integer -> Char findCharAtIndex idx = head . drop' (idx - 1) . concat . sort . map integerToWord $ [1..999999999] drop' :: Integer -> [a] -> [a] -- omitted integerToWord :: Integer -> String -- omitted
In the problem description, I don't see an upper time bound for how long it should take to solve this problem.
However, I'm highly confident that my approach is not the best way.
Can someone please give me a hint to solve this problem?
Thankssubmitted by kevin_meredith
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This has been a long time coming. My heartfelt thanks to both the ghc and debian developers who got it there. I only wish I hadn't failed in my attempt to get this version of ghc into Debian last fall, in time for the recent release.submitted by joeyh
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