wycats

#[macro_escape];

use std::rt::task::Task;
use std::rt::local::Local;

mod libunwind;

macro_rules! run(
  ($expr:expr) => (
    {

wycats

struct Foo {
  bar: ~Bar
}

struct Bar {
  age: int
}

impl IndexMut<int,Bar> for Foo {
  fn index_mut<'a>(&'a mut self, element: &int) -> &'a mut Bar {

wycats

#[feature(macro_rules)];

#[crate_id = "skylight#0.0.1"];
#[no_uv];

#[desc = "Direwolf Agent"];
#[license = "MIT"];
use std::prelude::*;
extern mod std = "std#0.10-pre";

wycats

# Ruby 1.9.2

location = nil

Net::HTTP.start("github.com", 443, use_ssl: true) do |http|
  uri = URI.parse("https://github.com/skylightio/skylight-rust/releases/download/v0.3.0-pre.1/libskylight-x86_64-linux.a.gz")
  response = http.get(uri.request_uri)
  location = response["Location"]
end

wycats

//#set_loc(1, "examples/rust/atoi.rl");

//#set_loc(5, "examples/rust/atoi.rs");
static _atoi_actions: &'static [i8] = &[
    0,    1,    0,    1,    1
];

static _atoi_key_offsets: &'static [i8] = &[
    0,    0,    4,    6,    9

wycats

%%{
machine http_date;
write data;
}%%

#[deriving(Clone, Eq, Ord)]
pub struct HttpDate {
  year: uint,
  month: u8,
  day: u8,

wycats

define(["ember/foo", "ember/bar", "ember/baz"], function(__dependency1__, __dependency2__, __dependency3__) {
  var a = __dependency1__.a,
      b = __dependency1__.b,
      c = __dependency1__.c;

  var d = __dependency2__.d;
  var e = __dependency3__.e;
});

define(["ember/foo", "ember/bar", "ember/winkle"], function(__dependency1__, __dependency2__, __dependency3__) {

wycats

#[crate_id = "hamcrest"];

pub trait Matcher<T> {
  fn matches(&self, actual: &T) -> bool;
}

/*
 *
 * ===== Matchers =====
 *

wycats

#[crate_id = "hamcrest"];

pub trait Matcher<T> {
  fn matches(&self, actual: &T) -> bool;
}

/*
 *
 * ===== Matchers =====
 *

wycats

Response Time

There are several places that your application's response times appear in Skylight. It is important to note that we always show the 95th percentile response time, not the average. While this take significantly more computation on the backend to determine, it is a much, much better number to indicate real world performance than the average.

Averages are almost useless when thinking about web performance, and in the worst case, are actually misleading. For more information, see DHH's blog post The problem with averages. Google, Twitter, and GitHub (to name a few) all use 95th percentile numbers when tracking performance.

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