What is the sane way to go from a Module object to a path to the file in which it was declared?
To be precise, I am looking for the file where the keyword module occurs.
The indirect method is to find the location of the automatically defined eval method in each module.
moduleloc(mm::Module) = first(functionloc(mm.eval, (Symbol,)))
for example
moduleloc(mm::Module) = first(functionloc(mm.eval, (Symbol,)))
using DataStructures
moduleloc(DataStructures)
Outputs:
/home/oxinabox/.julia/v0.6/DataStructures/src/DataStructures.jl
This indirect method works, but it feels like a bit of a kludge.
Have I missed some inbuilt function to do this?
I will remind answered that Modules are not the same thing as packages.
Consider the existence of submodules, or even modules that are being loaded via includeing some abolute path that is outside the package directory or loadpath.
Modules simply do not store the file location where they were defined. You can see that for yourself in their definition in C. Your only hope is to look through the bindings they hold.
Methods, on the other hand, do store their file location. And eval is the one function that is defined in every single module (although not baremodules). Slightly more correct might be:
moduleloc(mm::Module) = first(functionloc(mm.eval, (Any,)))
as that more precisely mirrors the auto-defined eval method.
If you aren't looking for a programmatic way of doing it you can use the methods function.
using DataFrames
locations = methods(DataFrames.readtable).ms
It's for all methods but it's hardly difficult to find the right one unless you have an enormous number of methods that differ only in small ways.
There is now pathof:
using DataStructures
pathof(DataStructures)
"/home/ederag/.julia/packages/DataStructures/59MD0/src/DataStructures.jl"
See also: pkgdir.
pkgdir(DataStructures)
"/home/ederag/.julia/packages/DataStructures/59MD0"
Tested with julia-1.7.3
require obviously needs to perform that operation. Looking into loading.jl, I found that finding the module path has changed a bit recently: in v0.6.0, there is a function
load_hook(prefix::String, name::String, ::Void)
which you can call "manually":
julia> Base.load_hook(Pkg.dir(), "DataFrames", nothing)
"/home/philipp/.julia/v0.6/DataFrames/src/DataFrames.jl"
However, this has changed to the better in the current master; there's now a function find_package, which we can copy:
macro return_if_file(path)
quote
path = $(esc(path))
isfile(path) && return path
end
end
function find_package(name::String)
endswith(name, ".jl") && (name = chop(name, 0, 3))
for dir in [Pkg.dir(); LOAD_PATH]
dir = abspath(dir)
#return_if_file joinpath(dir, "$name.jl")
#return_if_file joinpath(dir, "$name.jl", "src", "$name.jl")
#return_if_file joinpath(dir, name, "src", "$name.jl")
end
return nothing
end
and add a little helper:
find_package(m::Module) = find_package(string(module_name(m)))
Basically, this takes Pkg.dir() and looks in the "usual locations".
Additionally, chop in v0.6.0 doesn't take these additional arguments, which we can fix by adding
chop(s::AbstractString, m, n) = SubString(s, m, endof(s)-n)
Also, if you're not on Unix, you might want to care about the definitions of isfile_casesensitive above the linked code.
And if you're not so concerned about corner cases, maybe this is enough or can serve as a basis:
function modulepath(m::Module)
name = string(module_name(m))
Pkg.dir(name, "src", "$name.jl")
end
julia> Pkg.dir("DataStructures")
"/home/liso/.julia/v0.7/DataStructures"
Edit: I now realized that you want to use Module object!
julia> m = DataStructures
julia> Pkg.dir(repr(m))
"/home/liso/.julia/v0.7/DataStructures"
Edit2: I am not sure if you are trying to find path to module or to object defined in module (I hope that parsing path from next result is easy):
julia> repr(which(DataStructures.eval, (String,)))
"eval(x) in DataStructures at /home/liso/.julia/v0.7/DataStructures/src/DataStructures.jl:3"
Related
I know this question has been asked and answered before, but none of the many answers work for me as described.
What is the procedure for reloading a module that I'm working on in Julia (1.6)?
For example, I have
module MyModule
export letters
const letters = String('A':'Z')
end
and I want the be able to load the module, make changes to letters in the module's file, and then reload the module and have those changes reflected in subsequent uses of letters. This seems simple enough, but I can't get it to work.
I've tried
include("src/MyModule.jl")
using .MyModule
but if I change the definition of letters in MyModule.jl and then
include("src/MyModule.jl")
letters doesn't change, unless I fully qualify its use each time with Main.MyModule.letters: using Main.MyModule; letters refers, for example, to the old definition.
How do I reload a module under development so that I can refer to its definitions without fully qualifying them (and without having an unqualified shadow definition always lying around)?
I would just use Revise.jl and wrap everything in functions:
module MyModule
export letters
letters(char_start, char_end) = char_start:char_end |> String
end
julia> using Revise
julia> includet("src/MyModule.jl")
julia> using .MyModule
julia> letters('l', 'p')
"lmnop"
module MyModule
export letters
letters(char_start, char_end) = char_start:char_start |> String
end
julia> letters('l', 'p')
"l"
const is for defining things that you do not want to modify, so I would not expect your original version to work as expected. Revise.jl should also throw a redefinition error if you try to change it
In general though, it's usually much nicer (and easier too!) to just put everything in a package and use the usual using/import syntax. PkgTemplates.jl is great for this
If you would like to redefine consts though, I would definitely recommend checking out Pluto.jl
I saw this example in the Julia language documentation. It uses something called Base. What is this Base?
immutable Squares
count::Int
end
Base.start(::Squares) = 1
Base.next(S::Squares, state) = (state*state, state+1)
Base.done(S::Squares, s) = s > S.count;
Base.eltype(::Type{Squares}) = Int # Note that this is defined for the type
Base.length(S::Squares) = S.count;
Base is a module which defines many of the functions, types and macros used in the Julia language. You can view the files for everything it contains here or call whos(Base) to print a list.
In fact, these functions and types (which include things like sum and Int) are so fundamental to the language that they are included in Julia's top-level scope by default.
This means that we can just use sum instead of Base.sum every time we want to use that particular function. Both names refer to the same thing:
Julia> sum === Base.sum
true
Julia> #which sum # show where the name is defined
Base
So why, you might ask, is it necessary is write things like Base.start instead of simply start?
The point is that start is just a name. We are free to rebind names in the top-level scope to anything we like. For instance start = 0 will rebind the name 'start' to the integer 0 (so that it no longer refers to Base.start).
Concentrating now on the specific example in docs, if we simply wrote start(::Squares) = 1, then we find that we have created a new function with 1 method:
Julia> start
start (generic function with 1 method)
But Julia's iterator interface (invoked using the for loop) requires us to add the new method to Base.start! We haven't done this and so we get an error if we try to iterate:
julia> for i in Squares(7)
println(i)
end
ERROR: MethodError: no method matching start(::Squares)
By updating the Base.start function instead by writing Base.start(::Squares) = 1, the iterator interface can use the method for the Squares type and iteration will work as we expect (as long as Base.done and Base.next are also extended for this type).
I'll grant that for something so fundamental, the explanation is buried a bit far down in the documentation, but http://docs.julialang.org/en/release-0.4/manual/modules/#standard-modules describes this:
There are three important standard modules: Main, Core, and Base.
Base is the standard library (the contents of base/). All modules
implicitly contain using Base, since this is needed in the vast
majority of cases.
I define an outer syntax command, imake to write some code to a file and do some other things. The intended usage is as follows:
theory Scratch
imports Complex_Main "~/Is0/IsS"
begin
imake ‹myfile›
end
The above example will write some contents to the file myfile. myfile should be a path relative to the location of the Scratch theory.
ML ‹val this_path = File.platform_path(Resources.master_directory #{theory})
I would like to be able to use the value this_path in specifying myfile. The imake command is defined in the import ~/Is0/IsS and currently looks as follows:
ML‹(*imake*)
val _ = Outer_Syntax.improper_command #{command_spec "imake"} ""
(Parse.text >>
(fn path => Toplevel.keep
(fn _ => Gc.imake path)))›
The argument is pased using Parse.text, but I need feed it the path based on the ML value this_path, which is defined later (in the Scratch theory). I searched around a lot, trying to figure out how to use something like Parse.const, but I won't be able to figure anything out any time soon.
So: It's important that I use, in some way, Resources.master_directory #{theory} in Scratch.thy, so that imake gets the folder Scratch is in, which will come from the use of #{theory} in Scratch.
If I'm belaboring the last point, it's because in the past, I wasted a lot of time getting the wrong folder, because I didn't understand how to use the command above correctly.
How can I achieve this?
Your minimal examples uses Resource.master_directory with the parameter #{theory} to define your path. #{theory} refers (statically) to the theory at the point where you write down the antiquotation. This is mostly for interactive use, when you explore stuff. For code which is used in other places, you must use the dynamically passed context and extract the theory from it.
The function Toplevel.keep you use takes a function Toplevel.state -> unit as an argument. The Toplevel.state contains a context (see chapter 1 of the Isabelle Implementation Manual), which again contains the current theory; with Toplevel.theory_of you can extract the theory from the state. For example, you could use
Toplevel.keep (fn state => writeln
(File.platform_path (Resources.master_directory (Toplevel.theory_of state))))
to define a command that prints the master_directory for your current theory.
Except in simple cases, it is very likely that you do not only need the theory, but the whole context (which you can get with Toplevel.context_of).
Use setup from preceding (parts of the) theory
In the previous section, I assumed that you always want to use the master directory. For the case where the path should be configurable, Isabelle knows the concept of configuration options.
In your case, you would need to define an configuration option before you declare your imake command
ML ‹
val imake_path = Attrib.setup_config_string #{binding imake_path}
(K path)
› (* declares an option imake_path with the value `path` as default value *)
Then, the imake command can refer to this attribute to retrieve the path via Config.get:
Toplevel.keep (fn state =>
let val path = Config.get (Toplevel.context_of state) imake_path
in ... end)
The value of imake_path can then be set in Isar (only as a string):
declare [[imake_path="/tmp"]]
or in ML, via Config.map (for updating proof contexts) or Config.map_global (for updating theories). Note that you need to feed the updated context back to the system. Isar has the command setup (takes an ML expression of type theory -> theory) for that:
setup ‹Config.map_global imake_path (K "/tmp")›
Configuration options are described in detail in the Isar Implementation Manual, section 1.1.5.
Note: This mechanism does not allow you to automatically set imake_path to the master directory for each new theory. You need to set it manually, e.g. by adding
setup ‹
Config.map imake_path
(K (File.platform_path (Resources.master_directory #{theory})))
›
at the beginning of each theory.
The more general mechanism behind configuration options is context data. For details, see section 1.1 and in particular section 1.1.4 of the Isabelle Implementation Manual). This mechanism is used in a lot of places in Isabelle; the simpset, the configuration of the simplifier, is one example for this.
I am new to Julia, so this might be trivial.
I have a function definition within a module that looks like (using URIParser):
function add!(graph::Graph,
subject::URI,
predicate::URI,
object::URI)
...
end
Outside of the module, I call:
add!(g, URIParser.URI("http://test.org/1"), URIParser.URI("http://test.org/2"), URIParser.URI("http://test.org/1"))
Which gives me this error:
ERROR: no method add!(Graph,URI,URI,URI)
in include at boot.jl:238
in include_from_node1 at loading.jl:114
at /Users/jbaran/src/RDF/src/RDF.jl:79
Weird. Because when I can see a matching signature:
julia> methods(RDF.add!)
# 4 methods for generic function "add!":
add!(graph::Graph,subject::URI,predicate::URI,object::Number) at /Users/jbaran/src/RDF/src/RDF.jl:29
add!(graph::Graph,subject::URI,predicate::URI,object::String) at /Users/jbaran/src/RDF/src/RDF.jl:36
add!(graph::Graph,subject::URI,predicate::URI,object::URI) at /Users/jbaran/src/RDF/src/RDF.jl:43
add!(graph::Graph,statement::Statement) at /Users/jbaran/src/RDF/src/RDF.jl:68
At first I thought it was my use of object::Union(...), but even when I define three functions with Number, String, and URI, I get this error.
Is there something obvious that I am missing? I am using Julia 0.2.1 x86_64-apple-darwin12.5.0, by the way.
Thanks,
Kim
This looks like you may be getting bit by the very slight difference between method extension and function shadowing.
Here's the short of it. When you write function add!(::Graph, ...); …; end;, Julia looks at just your local scope and sees if add! is defined. If it is, then it will extend that function with this new method signature. But if it's not already defined locally, then Julia creates a new local variable add! for that function.
As JMW's comment suggests, I bet that you have two independent add! functions. Base.add! and RDF.add!. In your RDF module, you're shadowing the definition of Base.add!. This is similar to how you can name a local variable pi = 3 without affecting the real Base.pi in other scopes. But in this case, you want to merge your methods with the Base.add! function and let multiple dispatch take care of the resolution.
There are two ways to get the method extension behavior:
Within your module RDF scope, say import Base: add!. This explicitly brings Base.add! into your local scope as add!, allowing method extension.
Explicitly define your methods as function Base.add!(graph::Graph, …). I like this form as it more explicitly documents your intentions to extend the Base function at the definition site.
This could definitely be better documented. There's a short reference to this in the Modules section, and there's currently a pull request that should be merged soon that will help.
I just started developing a frama-c plugin that is doing some kind of alias analysis. I'm using the Dataflow.Backwards analysis and now I have to go through the different assignment statements and collect some stuff about the lvalues.
Does frama-c provide me with 3-address code? Do I have some guarantees about the shape of the lvalue (or any memory access)? I mean, sth like in soot or wala that there is at most one field access, s.t., for a->b->c, there would be a temp variable like tmp=a->b; tmp->c;? I checked the manuals, but I couldn't find anything related to this.
No, there is no such normalization in Frama-C. If you really need it, you can first use a visitor in order to normalize the code so that it suits the requirements of your plug-in. It'd go like that:
class normalize prj: Visitor.frama_c_visitor =
object
inherit Visitor.frama_c_copy prj
method vinstr i =
match i with
| Set (lv,e) -> ...
....
end
let analyze () = ...
let run () =
let my_prj = File.create_project_from_visitor "my_project" (fun prj -> new normalize prj) in
Project.on my_prj analyze ()
The following module from Cil does probably what you want:
http://www.cs.berkeley.edu/~necula/cil/ext.html#toc26. Be aware that the type of the resulting AST is the standard Cil one. You won't be getting any help from the OCaml compiler as to which constructs can be present in the simplified AST, and which ones cannot.
Note also that this module has not been ported to Frama-C so far. You will need some minor adaptation to make it work within Frama-C.