- First download
dbfpy: http://sourceforge.net/projects/dbfpy/files/latest/download?source=files - Then install:
sudo python setup.py install
To convert DBF file to CSV:
./dbf2csv database.dbf
| // this is the background code... | |
| // listen for our browerAction to be clicked | |
| chrome.browserAction.onClicked.addListener(function (tab) { | |
| // for the current tab, inject the "inject.js" file & execute it | |
| chrome.tabs.executeScript(tab.ib, { | |
| file: 'inject.js' | |
| }); | |
| }); |
| Step 0. You must have the latest & greatest version of R, and scala 2.10.1, for all of this to work. | |
| Step 1. Download and unzip the MacOS X Binary jvmr_1.0.4.tgz from here: http://cran.r-project.org/web/packages/jvmr/index.html | |
| Step 2. Create a lib folder, and copy jvmr_2.10-1.0.4.jar to that folder. | |
| Step 3. Start R | |
| Step 4. At the R console | |
| >install.packages("jvmr") |
dbfpy: http://sourceforge.net/projects/dbfpy/files/latest/download?source=filessudo python setup.py installTo convert DBF file to CSV:
./dbf2csv database.dbf
| import qualified Data.PQueue.Prio.Min as PQ | |
| import qualified Data.HashSet as Set | |
| import qualified Data.HashMap.Strict as Map | |
| import Data.Hashable (Hashable) | |
| import Data.List (foldl') | |
| import Data.Maybe (fromJust) | |
| astarSearch :: (Eq a, Hashable a) => a -> (a -> Bool) -> (a -> [(a, Int)]) -> (a -> Int) -> Maybe (Int, [a]) | |
| astarSearch startNode isGoalNode nextNodeFn heuristic = | |
| astar (PQ.singleton (heuristic startNode) (startNode, 0)) |
| macro whichs(ex) | |
| ex = expand(ex) | |
| exret = Expr(:call, :error, "expression is not a function call") | |
| if !isa(ex, Expr) | |
| # do nothing -> error | |
| elseif ex.head == :call | |
| exret = Expr(:call, :whichs, map(esc, ex.args)...) | |
| elseif ex.head == :body | |
| a1 = ex.args[1] | |
| if isa(a1, Expr) && a1.head == :call |
| // Just before switching jobs: | |
| // Add one of these. | |
| // Preferably into the same commit where you do a large merge. | |
| // | |
| // This started as a tweet with a joke of "C++ pro-tip: #define private public", | |
| // and then it quickly escalated into more and more evil suggestions. | |
| // I've tried to capture interesting suggestions here. | |
| // | |
| // Contributors: @r2d2rigo, @joeldevahl, @msinilo, @_Humus_, | |
| // @YuriyODonnell, @rygorous, @cmuratori, @mike_acton, @grumpygiant, |
| """ | |
| (C) August 2013, Mathieu Blondel | |
| # License: BSD 3 clause | |
| This is a Numba-based reimplementation of the block coordinate descent solver | |
| (without line search) described in the paper: | |
| Block Coordinate Descent Algorithms for Large-scale Sparse Multiclass | |
| Classification. Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara. | |
| Machine Learning, May 2013. |
| data Skew a = Empty | Node a (Skew a) (Skew a) | |
| singleton :: Ord a => a -> Skew a | |
| singleton x = Node x Empty Empty | |
| union :: Ord a => Skew a -> Skew a -> Skew a | |
| union t1 Empty = t1 | |
| union Emtpy t2 = t2 | |
| union t1@(Node x1 l1 r1) t2@(Node x2 l2 r2) | |
| | x1 <= x2 = Node x1 (union t2 r1) l1 |
| #!/usr/bin/env python | |
| """ | |
| Downloads and cleans up a CSV file from a Google Trends query. | |
| Usage: | |
| trends.py [email protected] google.password /path/to/filename query1 [query2 ...] | |
| Requires mechanize: | |
| pip install mechanize | |
| """ |
| {:user {:dependencies [[org.clojure/tools.namespace "0.2.3"] | |
| [spyscope "0.1.3"] | |
| [criterium "0.4.1"]] | |
| :injections [(require '(clojure.tools.namespace repl find)) | |
| ; try/catch to workaround an issue where `lein repl` outside a project dir | |
| ; will not load reader literal definitions correctly: | |
| (try (require 'spyscope.core) | |
| (catch RuntimeException e))] | |
| :plugins [[lein-pprint "1.1.1"] | |
| [lein-beanstalk "0.2.6"] |