>>> arr (renderDateField "date" "%B %e, %Y" "Date unknown")

renderDateField :: String  -- ^ Key in which the rendered date should be placed
                -> String  -- ^ Format to use on the date
                -> String  -- ^ Default value, in case the date cannot be parsed
                -> Page a  -- ^ Page on which this should be applied
                -> Page a  -- ^ Resulting page
renderDateField = renderDateFieldWith defaultTimeLocale

Page a -> Page a

$ ghc --make test.hs 
[1 of 1] Compiling Main             ( test.hs, test.o )

test.hs:22:17:
    Couldn't match expected type `Compiler (Page String) b0'
                with actual type `Page a0 -> Page a0'
    In the return type of a call of `renderDateField'

data Compiler a b = Compiler
    { compilerDependencies :: Reader DependencyEnvironment Dependencies
    , compilerJob          :: a -> CompilerM b
    }

hasktags -e .

import Text.Feed.Import
import Text.Feed.Query
import Data.Maybe

main = do
  rss <- parseFeedFromFile "test.rss"
  mapM_ putStrLn $ map (fromJust . getItemTitle) (getFeedItems rss)

import Text.Feed.Import
import Text.Feed.Query
import Data.Maybe
import Network.HTTP

eutils_url = "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/erss.cgi?rss_guid="
guid = "1ZQ4a7JQ6X8P3NJNZLWG_ML-XsrLQgH63A06CsXO-jG0m_iEe-"

getTitle = (take 60) . fromJust . getItemTitle
getItems = getFeedItems . fromJust . parseFeedString

main :: IO ()
main = do
  res <- simpleHTTP $ getRequest $ eutils_url ++ guid
  body <- getResponseBody res
  mapM_ putStrLn $ map getTitle $ getItems body

RMol: A Toolset for Transforming SD/Molfile structure inform
Adenosiland: Walking through adenosine receptors landscape.
Enzyme Informatics.
The Use of the R language for Medicinal Chemistry Applicatio
Similarity coefficients for binary chemoinformatics data: ov
Review on Chemogenomics approach: Interpreting antagonist ac
Immunotoxicity, Flow Cytometry and Chemoinformatics: A Revie
A Parallel Systematic-Monte Carlo Algorithm for exploring Co
Validation of drug-like inhibitors against Mycobacterium tub
Desirability-based Multi-criteria Virtual Screening of Selec
The use of glycoinformatics in glycochemistry.
Role of computational methods in pharmaceutical sciences.
High-throughput screening with a miniaturized radioligand co
Chemoinformatics: recent advances at the interfaces between 
ReactionPredictor: Prediction of Complex Chemical Reactions

import Text.Feed.Import
import Text.Feed.Query
import Data.Maybe
import Network.HTTP
import Network.Browser (browse, request)

eutils_url = "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/erss.cgi?rss_guid="
guid = "1ZQ4a7JQ6X8P3NJNZLWG_ML-XsrLQgH63A06CsXO-jG0m_iEe-"

getTitle = (take 60) . fromJust . getItemTitle
getItems = getFeedItems . fromJust . parseFeedString . rspBody

main :: IO ()
main = do
  (_, res) <- browse $ do
    request $ getRequest $ eutils_url ++ guid
  mapM_ putStrLn $ map getTitle $ getItems $ res

import Database.HDBC
import Database.HDBC.Sqlite3
import Data.Maybe

main = do
  conn <- connectSqlite3 "/Users/kzfm/blog.db"
  stmt <- prepare conn "select title from entry"
  execute stmt []
  results <- sFetchAllRows stmt
  mapM_ (putStrLn . fromJust) $ concat results

from sqlalchemy import create_engine, MetaData

db = create_engine('mysql://user:password@localhost/chembl_14?charset=utf8&use_unicode=0')
metadata = MetaData(bind=db, reflect=True)

table = metadata.tables['target_dictionary']
stmt = table.select(table.c['organism'] == 'Homo sapiens')

for r in stmt.execute():
    print r.chembl_id, r.pref_name