Matthew Dowle is working on a fast CSV reader for data.table. Here is test data case generated in R along with some timings:
require(data.table)
n=1e6
DT = data.table( a=sample(1:1000,n,replace=TRUE),
b=sample(1:1000,n,replace=TRUE),
c=rnorm(n),
d=sample(c("foo","bar","baz","qux","quux"),n,replace=TRUE),
This list was originally authored by a friend who has been learning programming for some time (tuningmind)
Note: Many books may be available from a nearby public library. Check there as well!
These two are about the best I've seen for starting from scratch:
Prerequisites:
Software components used:
So you managed to break Julia. Congratulations! Collected here are some general procedures you can undergo for common symptoms encountered when something goes awry. Including the information from these debugging steps can greatly help the maintainers when tracking down a segfault or trying to figure out why your script is running slower than expected.
If you've been directed to this page, find the symptom that best matches what you're experiencing and follow the instructions to generate the debugging information requested. Table of symptoms:
| #Python/pypy | |
| import math | |
| def smallestdivisall(n): | |
| for i in xrange(1, math.factorial(n)+1): | |
| for j in xrange(1, n+1): | |
| if i % j != 0: | |
| break | |
| elif j == n: | |
| return i | |
| It is a rite of passage to post one's successful build instructions for OpenCV on a Mac | |
| after you've tried all the other conflicting instructions out there and still failed. | |
| brew failed for me (was this because I could never get a happy brew doctor situation? | |
| I'll never know). macports? nope. build-from-source recipes? I didn't find one that | |
| worked for me. | |
| Here's what did work to build OpenCV 2.4.5 from the distribution tarball using cmake, | |
| on Mac OSX 10.8.4, linked to an anaconda installation rather than the system python. | |
| It is a mashup of various bits of advice out there. If you're already comfortable with | |
| build/install from source, all you need to read is the cmake invocation in step 3 and |
| /* Experimental typographically tinkered IJulia stylesheet | |
| * Copyright © 2013 Jiahao Chen <jiahao@mit.edu> | |
| * MIT License | |
| * | |
| * To use, place in ~/.ipython/profile_julia/static/custom/custom.css | |
| * and refresh IJulia | |
| * | |
| * Based on suggestions from practicaltypography.com | |
| */ |
So you managed to break Julia. Congratulations! Collected here are some general procedures you can undergo for common symptoms encountered when something goes awry. Including the information from these debugging steps can greatly help the maintainers when tracking down a segfault or trying to figure out why your script is running slower than expected.
If you've been directed to this page, find the symptom that best matches what you're experiencing and follow the instructions to generate the debugging information requested. Table of symptoms:
| # Fortran-like array with arbitrary starting indices | |
| # | |
| # usage: | |
| # | |
| # julia> include("FArray.jl") | |
| # size (generic function with 51 methods) | |
| # | |
| # julia> y = FArray(Float64, -1:1, -7:7, -128:512, -5:5, -1:1, -3:3, -2:2, -1:1); | |
| # | |
| # julia> y[-1,-7,-128,-5,-1,-3,-2,-1] = 14 |
| # Repeat an operation n times, e.g. | |
| # @dotimes 100 println("hi") | |
| macro dotimes(n, body) | |
| quote | |
| for i = 1:$(esc(n)) | |
| $(esc(body)) | |
| end | |
| end | |
| end |
