This warning was happening to dependent packages on R CMD check.
The problem is due to delayedAssign; it appears this can't be used safely, at least not to define package-level symbols that contain S4 or reference class objects.
If you call this in a package's .R file:
`delayedAssign("hello", stop("boom"))`
but don't refer to "hello" anywhere, when you run R CMD check on a dependent package you'll see the error.
If the expression needs the methods package (like Context$new()), you'll get an error unless the dependent package itself depends on methods.
setTimeout() is necessary for uiOutput(); we need to wait for a short while before typesetting math, otherwise two bad things can happen:
1. a math expression may be rendered twice (static output)
2. it is not rendered at all (dynamic ui output)
so the compromise is to typeset math after a short while when the document is ready; 200 ms is an arbitrary choice here
I always thought dots and colons were illegal in HTML ID attributes,
but I was wrong. They are legal and because they are commonly used
in identifier names in R, Shiny users often like to use them. Worse,
Shiny gave no warnings when using dots and only a pretty advanced
subset of functionality would NOT work when using dots, causing
everyone to think they were fully supported in Shiny.
This commit ought to bring reality in line with perception. It turns
out that jQuery has an escaping scheme in its queries that allow us
to support dots after all. As long as we are always careful to
surround IDs with $escape when putting them in a query, we'll be in
good shape.
Colons will probably still cause problems at the moment because we
use colons internally to separate input type from input name. But
we've never seen users try to use colon in IDs before, so we can
wait to fix it until that becomes a problem.
the cause:
normalize('foo', '/') => C:/foo
normalize('foo/', '/') => C:/foo/
under Windows. For unix, the trailing slash will always be removed in normalizePath()
let's make the number of bins reactive instead; now it is very clear what the slider really controls
a histogram with different number of bins also serves as a good demo of the property of histograms (small bins --> small variance + large bias)
