Popular Haskell Packages: Q2 2010 report

Here is some data on downloads of Haskell libraries and apps on Hackage, for the first half of 2010.

The Hackage dependency graph

Hackage is the central repository of open source Haskell libraries and tools. Once they install the Haskell Platform, users get more libraries from Hackage, via “cabal install”.

Headlines

May was the most popular month for Hackage ever, breaking 150k downloads in a single month for the first time.

The 2000th Haskell package was released on April 16.

Total downloads on Hackage since 2006 have passed 2.4 million, with 780 thousand downloads in 2010 so far (double the total from the same time in 2009).

Totals

Total cabal packages: 2182. (+ 208 in Q2).

Total contributing developers: 575 (42 new developers in Q2)

90 day moving average: 12 packages per day uploaded.

Total downloads from Hackage 2007-present: 2.42 million

Average monthly downloads in 2010: 130 thousand.

Top of the Pops

The top 15 most popular libraries in the first half of 2010 were:

  1. HTTP
  2. parsec (+1)
  3. zlib (-1)
  4. binary (+1)
  5. network (+2)
  6. utf8-string (-2)
  7. Cabal (+1)
  8. QuickCheck (-2)
  9. mtl (+1)
  10. haskell-src-exts (-1)
  11. regex-base
  12. deepseq (+6)
  13. ghc-paths (+2)
  14. hslogger (+6)
  15. regex-posix (-2)

Top 15 most popular applications in the first half of 2010:

  1. cabal-install
  2. xmonad
  3. haddock (+1)
  4. cpphs (-1)
  5. happy
  6. darcs (+1)
  7. alex (+1)
  8. hscolour (-2)
  9. pandoc
  10. hlint
  11. leksah
  12. xmobar
  13. yi
  14. hint
  15. agda

Honorable Mentions

  • The Galois xml library was more popular in the first half of 2010 than HaXml, dethroning HaXml for the first time.
  • text has made it into the top 30 libraries
  • HDBC continues to be the most popular database library
  • vector has almost surpassed array in downloads (array is part of the Haskell Platform though)
  • wxHaskell is still more popular than gtk2hs on Hackage,  though gtk2hs has almost caught up.

You can read all the 2010 data for your favorite packages, and ranked by 2010 popularity.

Top Libraries by Category

  • Networking: HTTP, network, network-bytestring, curl
  • Parsing: parsec, polyparse, attoparsec
  • Compression: zlib, zip-archive
  • Binary formats: binary, cereal
  • Text formats: utf8-string, text, dataenc
  • Markup: pandoc, xhtml, tagsoup, html
  • JSON: json
  • Atom/RSS: feed
  • XML: xml, HaXml, hexpat
  • Web services:  happstack, snap
  • GUIs: wxHaskell, gtk2hs
  • Graphics: SDL, cairo, gd
  • Templates: HStringTemplate
  • Testing: QuickCheck, HUnit, testpack, hpc
  • Control: mtl, transformers, monads-fd
  • Languages: haskell-src-exts, haskell-src, HJavaScript
  • Regexes: regex-{base,posix,compat,tdfa}, pcre-light
  • Logging: hslogger
  • Generics: uniplate, syb-with-class, syb
  • 3D: OpenGL
  • Edit history: haskeline
  • Concurrency and parallelism: parallel, stm
  • Databases: HDBC
  • Arrays: array, vector, hmatrix
  • Hashing: pureMD5, SHA
  • Data structures: containers, fingertree, dlist
  • Science:  statistics
  • Benchmarking: criterion
  • Storage: hs3

Is there anything else you see in the data?

Open Source Bridge Talk: Multicore Haskell Now

In June I had the opportunity to talk about approaches to parallel programming in Haskell at Open Source Bridge: “a new conference for developers working with open source technologies and for people interested in learning the open source way.”

Here are the slides (::PDF), and the source that accompanied the tutorial:

The abstract for  the session:

Haskell is a functional language built for parallel and concurrent programming. You can take an off-the-shelf copy of GHC and write high performance parallel programs right now. This tutorial will teach you how to exploit parallelism through Haskell on your commodity multicore machine, to make your code faster. We will introduce key parallel programming models, as implemented in Haskell, including:

  • semi-explicit parallelism via sparks
  • explicit parallelism via threads and shared memory
  • software transactional memory

and look at how to build faster programs using these abstractions. We will also look at the engineering considerations when writing parallel programs, and the tools Haskell provides for debugging and reasoning about parallel programs.

This is a hands on tutorial session: bring your laptops, there will be code!