> This a very heavy install. It's fetching tons of things that I have not
> used. Not sure what they are, but seems like trashing my system.
>
Yes, unfortunately Conda is an unbearably big dependency (over 1.xxx Gb)
that sneaks in via un-suspicious packages. A dependency this big should
never install without a strict user consent. Docs explain how to avoid it
but don't find the explanation clear. I had to declare this
ENV["JUPYTER"]="C:/programs/WinPython-3.5.2.2_64/python-3.5.2.amd64/Scripts/jupyter"
to really prevent a Conda installation
>
> On Wednesday, September 28, 2016 at 4:30:32 AM UTC+8, Cedric St-Jean wrote:
>>
>> Yeah, it's because of IJulia, sorry about that. I need it to support
>> autoreloading. I could split the package in two, but it's small enough
>> already that it doesn't feel like the right call.
>>
>> One day we'll get conditional imports...
>>
>> On Tue, Sep 27, 2016 at 4:14 PM, Daniel Carrera <dcar...@gmail.com>
>> wrote:
>>
>>> Thanks! You are a savior!
>>>
>>> Here is something odd: when I installed it with Pkg.clone(...) my Julia
>>> decided that it also had to update Conda and install Jupyter. Is this some
>>> weird quirk of my setup. I notice that you import IJulia, so I guess that
>>> has something to do with it. It's not a big deal; I just thought it was
>>> weird to see the package manager installing stuff like Qt, fontconfig, SSL,
>>> and libxml just to clobber include().
>>>
>>> But other than that, it works fabulously. Thank you so much!
>>>
>>> Cheers,
>>> Daniel.
>>>
>>>
>>>
>>> On 27 September 2016 at 21:45, Cedric St-Jean <cedric...@gmail.com>
>>> wrote:
>>>
>>>> I wrote a work-around earlier today:
>>>>
>>>> Pkg.clone("git://github.com/cstjean/ClobberingReload.jl.git")
>>>>
>>>> using ClobberingReload: sinclude # silent include
>>>> sinclude("foo.jl") # no redefinition warnings
>>>>
>>>>
>>>> It's fresh off the press, so please file an issue if you encounter a
>>>> problem. It calls `include` under the hood; there's no magic involved. I
>>>> just intercept STDERR and remove the redefinition warnings.
>>>>
>>>> On Tuesday, September 27, 2016 at 3:13:00 PM UTC-4, Andrew wrote:
>>>>>
>>>>> It seems like a lot of people are complaining about this. Is there
>>>>> some way to suppress method overwritten warnings for an include()
>>>>> statement? Perhaps a keyword like include("foo.jl", quietly = true)?
>>>>>
>>>>> On Tuesday, September 27, 2016 at 1:56:27 PM UTC-4, Daniel Carrera
>>>>> wrote:
>>>>>>
>>>>>> Hello,
>>>>>>
>>>>>> I'm not sure when I upgraded, but I am using Julia 0.5 and now it
>>>>>> complains every time I redefine a method, which is basically all the
>>>>>> time.
>>>>>> When I'm developing ideas I usually have a file with a script that I
>>>>>> modify
>>>>>> and reload all the time:
>>>>>>
>>>>>> julia> include("foo.jl");
>>>>>>
>>>>>> ... see the results, edit file ...
>>>>>>
>>>>>> julia> include("foo.jl");
>>>>>>
>>>>>> ... see the results, edit file ...
>>>>>> julia> include("foo.jl");
>>>>>>
>>>>>> ... see the results, edit file ...
>>>>>>
>>>>>>
>>>>>> And so on. This is what I do most of the time. But now every time I
>>>>>> `include("foo.jl")` I get warnings for every method that has been
>>>>>> redefined
>>>>>> (which is all of them):
>>>>>>
>>>>>> julia> include("foo.jl");
>>>>>>
>>>>>> WARNING: Method definition (::Type{Main.Line})(Float64, Float64) in
>>>>>> module Main at /home/daniel/Data/Science/Thesis/SI.jl:4 overwritten at
>>>>>> /home/daniel/Data/Science/Thesis/SI.jl:4.
>>>>>> WARNING: Method definition (::Type{Main.Line})(Any, Any) in module
>>>>>> Main at /home/daniel/Data/Science/Thesis/SI.jl:4 overwritten at
>>>>>> /home/daniel/Data/Science/Thesis/SI.jl:4.
>>>>>> WARNING: Method definition new_line(Any, Any, Any) in module Main at
>>>>>> /home/daniel/Data/Science/Thesis/SI.jl:8 overwritten at
>>>>>> /home/daniel/Data/Science/Thesis/SI.jl:8.
>>>>>>
>>>>>>
>>>>>> Is there a way that this can be fixed? How can I recover Julia's
>>>>>> earlier behaviour? This is very irritating, and I don't think it makes
>>>>>> sense for a functional language like Julia. If I wrote a method as a
>>>>>> variable assignment (e.g. "foo = x -> 2*x") Julia wouldn't complain.
>>>>>>
>>>>>>
>>>>>> Thanks for the help,
>>>>>> Daniel.
>>>>>>
>>>>>
>>>
>>
