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{-# LANGUAGE OverloadedStrings, QuasiQuotes, ViewPatterns #-}
module Y2017.M11.D20.Exercise where
Okay, let's build our query ... IN SQL!
Grab the keywords, then, from a keyword search, return the article set.
import Data.Map (Map)
import Data.Set (Set)
import Database.PostgreSQL.Simple
import Database.PostgreSQL.Simple.SqlQQ
-- below imports available via 1HaskellADay git repository
import Data.MemoizingTable (MemoizingTable)
import Store.SQL.Connection
import Store.SQL.Util.Indexed
import Y2017.M11.D03.Exercise -- for Keyphrase
import Y2017.M11.D06.Exercise hiding (idx) -- for Score (idx, title, score)
import Y2017.M11.D07.Exercise -- for marry (map integer recommend map integer sc
import Y2017.M11.D08.Exercise -- for Recommend-type and output of JSON
import Y2017.M11.D09.Exercise -- for fetching articles (recommendations)
import Y2017.M11.D13.Exercise -- for mapping keywords to articles
import Y2017.M11.D16.Exercise -- for ranking
import Y2017.M11.D17.Exercise -- for grabbing the kws and keyphrases
-- step 1: grab the keywords
kwTable :: Connection -> IO KWtable
kwTable conn = undefined -- hint: use kwTable' to marshall the memoizing table
kwTable' :: [IxKeys] -> KWtable
kwTable' keys = undefined -- hint: see functions from D17
-- Now, with this query
filterArtsStmt :: Query
filterArtsStmt = [sql|SELECT keyword_id,article_id
FROM article_keyword
WHERE keyword_id IN ?|]
-- grab the article IDs that are the intersection of the results:
filterArts :: Connection -> KWtable -> [KeyWord] -> IO IndexedArticles
filterArts conn kws vals = undefined
-- Now, let's translate that to articles with key-phrases ... that is to say:
-- to our JSON structure we've returned before.
-- step 2: get the full articles back using fetchRecommend from the filtered
-- article Id-set.
-- step 3: get the key-phrases for article x
type KPhrMap = Map Integer [Keyphrase]
keyphrasesStmt :: Query
keyphrasesStmt =
[sql|SELECT id,strength,keyphrase FROM keyphrase WHERE id IN
(SELECT keyphrase_id FROM article_keyphrase WHERE article_id=?|]
keyphrase4 :: Connection -> Integer -> IO [IxPhrase]
keyphrase4 conn artId = undefined
-- Now we marry keywords to articles and return the ranked article set.
ranked2Score :: (ArticleId, Strength) -> Score
ranked2Score (i,s) = undefined
-- these indexed instances will be helpful marrying scores to articles:
instance Indexed Score where
idx score = undefined
instance Indexed Recommend where
idx rec = undefined
collectResult :: KeyphraseMap -> [Recommend] -> [Score] -> [Recommendation]
collectResult kphrs recs scores = undefined
-- hint: see marry and showRecs for guidance
-- What does the JSON look like for a set of articles on "trump" "election"?
-- so we need a function that from a set of keywords we return a set of
-- filtered articles.
recs :: Connection -> [KeyWord] -> IO [Recommendation]
recs conn keywords = undefined -- hint use recs' after you get a kwtable
recs' :: Connection -> [KeyWord] -> KWtable -> IO [Recommendation]
recs' conn keywords kwtable = undefined
{-- BONUS -----------------------------------------------------------------
Package all of this together as an application and from a list of keywords
return a set of JSON of the filtered articles, ranked.
main' :: [String] -> IO ()
main' keywords = undefined
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