Thursday, September 15, 2016

August 2016 1HaskellADay 1Liners

  • August 20th, 2016: maybeify :: (a, Maybe b) -> Maybe (a, b)
    Define maybeify. Snaps for elegance.
    • Hardy Jones @st58 sequence
    • Bruno @Brun0Cad mapM id
    • Thomas D @tthomasdd {-# LANGUAGE TupleSections #-}
      mabeify (x,mY) = maybe Nothing (return . (x,)) mY
    • Андреев Кирилл @nonaem00 import "category-extras" Control.Functor.Strong
      maybeify = uncurry strength
    • bazzargh @bazzargh I can't beat 'sequence', but: uncurry (fmap.(,))
    • Nick @crazy_fizruk distribute (from Data.Distributive)

Thursday, September 1, 2016

August 2016 1HaskellADay Problems and Solutions

August 2016


  • August 25th, 2016: Today's #haskell exercise looks at historical prices of #bitcoin
    Today's #haskell solution is worth $180k ... five years ago. I wonder what it will be worth 5 years hence? 
  • August 23rd, 2016: Enough diving into the node's data, let's look at the structure of the related nodes for today's #haskell problem. The structure of tweets and related data for today's #haskell solution 
  • August 22nd, 2016: Today's #haskell problem is parsing twitter hashtags and a bit of data fingerprinting/exploration of same. BOOM! Today's #haskell solution analyzes hashtags twitter-users ('tweeps') use
  • August 19th, 2016: For today's #haskell exercise we look at unique users in a set of twitter graph-JSONToday's #haskell solution gives us a list of users, then their tweets, from twitter graph-JSON data 
  • August 18th, 2016: For today's #haskell problem we extract and reify URLs from twitter graph-JSON. Today's #haskell solution extract URLs from twitter data as easily as looking up the URLs in a JSON map.
  • August 17th, 2016: For today's #haskell problem we explore the relationships from and to tweets and their related data. Today's #haskell solution relates data to tweets extracted from graph-JSON 
  • August 16th, 2016: For today's #haskell exercise we begin converting nodes in a graph to more specific types (Tweets are up first). We create some JSON Value-extractors and with those find the tweets in graph JSON in today's #Haskell solution 
  • August 15th, 2016: Today's #haskell exercise looks at twitter data as labeled/typed nodes and relations in JSON  

    Okay! For today's #haskell solution we discover our node and relation types in twitter data-as-graphs JSON! 
  • August 10th, 2016: Today's #Haskell problem we look at the big data-problem: getting a grasp of large indices of tweets in graph JSON. Today's #Haskell solution time-stamps and gives 'small-data' indices to tweets from graph JSON 
  • August 9th, 2016: For today's #haskell problem we extract the tweets from rows of graph data encoded in JSON. Today's #Haskell solution extracts the tweets from graph JSON and does some simple queries
  • August 8th, 2016: For today's #haskell problem we look at reading in the graph of a twitter-feed as JSON and just a bit of parsing. We leverage the Cypher library for today's #haskell solution to look at 100 rows of tweets encoded as JSON 
  • August 5th, 2016: Today's #Haskell problem we go for the Big Kahuna: solving a Kakuro puzzle
    Okay, we have a #Haskell solution ... finally ... maybe. The solver took too long, so I solved it myself faster :/ 
  • August 4th, 2016: Today's #Haskell exercise looks at (simple) constraints of unknown values for a sum-solverToday's #Haskell solution also uses QBits to solve constrained unknowns 
  • August 3rd, 2016: Today's #haskell problem provides the cheatsheet: "What are the unique 4-number sums to 27?" We round-trip the Set category for today's #haskell solution
  • August 2nd, 2016: Today's #haskell exercise looks at solving our sums when we know some of the numbers alreadyQBits actually work nicely for today's #Haskell solution 
  • August 1st, 2016: For today's #Haskell exercise we play the 'Numbers Game.' The #haskell solution is a guarded combine >>= permute in the [Int]-domain. I like the Kleisli category; ICYMI.