precompilation issue #21696 how to fix

[miguelraz]

Faced this myself, so I thought I might as well write it down for posterity's sake.
(Feel free to close.)

I was hitting this issue JuliaLang/julia#21969

I hit the same bug of
using Combinatorics - v0.4.0 or using PolynomialFactors v0.0.5
and got back

LoadError: Declaring __precompile__(true) is only allowed in module files being imported.
while loading C:\Users\miguel\.julia\v0.6\Combinatorics\src\Combinatorics.jl, in expression starting on line 1
__precompile__(::Bool) at loading.jl:335
include_from_node1(::String) at loading.jl:569
eval(::Module, ::Any) at boot.jl:235
_require(::Symbol) at loading.jl:483
require(::Symbol) at loading.jl:398
_include_from_serialized(::String) at loading.jl:157
_require_from_serialized(::Int64, ::Symbol, ::String, ::Bool) at loading.jl:200
_require_search_from_serialized(::Int64, ::Symbol, ::String, ::Bool) at loading.jl:236
_require(::Symbol) at loading.jl:434
require(::Symbol) at loading.jl:398
include_string(::String, ::String) at loading.jl:515
eval(::Module, ::Any) at boot.jl:235
(::Atom.##61#64)() at eval.jl:102
withpath(::Atom.##61#64, ::Void) at utils.jl:30
withpath(::Function, ::Void) at eval.jl:38
macro expansion at eval.jl:101 [inlined]
(::Atom.##60#63{Dict{String,Any}})() at task.jl:80

Sys info WINDOWS:

Julia Version 0.6.0-rc3.0
Commit ad290e93e4* (2017-06-07 11:53 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: AMD Athlon(tm) II X2 250 Processor
  WORD_SIZE: 64
  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Barcelona)
  LAPACK: libopenblas64_
  LIBM: libopenlibm
  LLVM: libLLVM-3.9.1 (ORCJIT, amdfam10)

I then edited my files according to these PRs
JuliaMath/Combinatorics.jl#49
jverzani/PolynomialFactors.jl#5

and using DifferentialEquations now hit this bug.

LoadError: Declaring __precompile__(true) is only allowed in module files being imported.
while loading C:\Users\miguel\.julia\v0.6\DifferentialEquations\src\DifferentialEquations.jl, in expression starting on line 1
__precompile__(::Bool) at loading.jl:335
__precompile__() at loading.jl:331
include_from_node1(::String) at loading.jl:569
eval(::Module, ::Any) at boot.jl:235
_require(::Symbol) at loading.jl:483
require(::Symbol) at loading.jl:398
include_string(::String, ::String) at loading.jl:515
eval(::Module, ::Any) at boot.jl:235
(::Atom.##61#64)() at eval.jl:102
withpath(::Atom.##61#64, ::Void) at utils.jl:30
withpath(::Function, ::Void) at eval.jl:38
macro expansion at eval.jl:101 [inlined]
(::Atom.##60#63{Dict{String,Any}})() at task.jl:80

Then, doing using StochasticDiffEq and then using DifferentialEquations seems to have worked. Thanks to @shivin9 way back in the logs for that idea and Chris for the useful PRs.

[ChrisRackauckas]

I'll leave this up so that way people venturing into v0.6-rc3 know this is a Julia issue with some solutions, but is a PITA for now. When it's fixed in Julia Base or through the other package changes, I'll close.

[miguelraz]

Seems optimal. Thanks!

[miguelraz]

This is now fixed with a Pkg.update().
Closing.