This is probably a newbie question... but is it possible to show the definition of a (user defined) function? While debugging/optimizing it is convenient to quickly see how a certain function was programmed.
Thanks in advance.
You can use the #edit macro, which is supposed to take you to the definition of a method, similarly to how the #which macro which shows the file and line # where that particular method was defined, for example:
julia> #which push!(CDFBuf(),"foo")
push!{T<:CDF.CDFBuf}(buff::T, x) at /d/base/DA/DA.jl:105
julia> #which search("foobar","foo")
search(s::AbstractString, t::AbstractString) at strings/search.jl:146
Note that methods that are part of Julia will show a path relative to the julia source directory "base".
While this is not an automatic feature available with Julia in general (as pointed out by Stefan), if you add docstrings when you define your initial function, you can always use the help?> prompt to query this docstring. For example
julia> """mytestfunction(a::Int, b)""" function mytestfunction(a::Int, b)
return true
This attaches the docstring "mytestfunction(a::Int, b)" to the function mytestfunction(a::Int, b). Once this is defined, you can then use the Julia help prompt (by typing ? at the REPL), to query this documentation.
help?> mytestfunction
mytestfunction(a::Int, b)
Related
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.
Given a function object f, how do I find:
Function's name.
Module(s) of its method(s)?
In Julia 0.4 I was able to find name using f.env.name, but no tips for module. For Julia 0.5 I wasn't able to find any of two.
Name is easy: Symbol(f) or string(f) if you want a string
Module is, as you know going to be per method (i.e per type signature).
methods(f) with return a method table that prints out all the methods and where they are, in terms of files.
You can do [meth.module for meth in methods(f)] to get there modules
So to use an example, the collect function.
julia> using DataStructures #so we have some non-Base definitions
julia> Symbol(collect)
:collect
julia> methods(collect)
# 5 methods for generic function "collect":
collect(r::Range) at range.jl:813
collect{T}(::Type{T}, itr) at array.jl:211
collect(itr::Base.Generator) at array.jl:265
collect{T}(q::DataStructures.Deque{T}) at /home/ubuntu/.julia/v0.5/DataStructures/src/deque.jl:170
collect(itr) at array.jl:236
julia> [meth.module for meth in methods(collect)]
5-element Array{Module,1}:
Base
Base
Base
DataStructures
Base
julia> first(methods(collect, (Deque,))).module
DataStructures
#oxinabox's answer is correct. To add, typeof(f).name.mt.name is the v0.5 replacement for f.env.name. That can be useful to avoid the . that occurs when just applying string to a function introduced in a non-stdlib module. There also exists Base.function_name(f) which is probably less likely to break when the Julia version changes.
To get the module that a function (type) is introduced in, rather than the modules of individual methods, there's typeof(f).name.module, or the probably-better version, Base.function_module(f). The module of the method table is probably the same; that can be obtained through typeof(f).name.mt.module.
Note that f.env in v0.4 is a direct equivalent of typeof(f).name.mt, so on v0.4 the same f.env.name and f.env.module apply.
In Julia 1.x the commands are:
Base.nameof
Base.parentmodule
Since this two methods are exported, also nameof and parentmodule works.
Not exactly the answer but closely related: you can find the file name and line number of f using functionloc(f)
How do you find out where a macro is from in Julia. I'm looking at someone's code and they're using an #debug("string") macro. There are no using statements in the particular file that would tell me where it's loaded from, so I assume it's loaded form somewhere else in the code.
I might guess at the debug module for Julia, but it doesn't seem like it's being used that way, it seems like it's being used more for logging, so I'm a bit unsure of how to track it down through the code.
A macro location can be obtained using the #which macro, this is a feature introduced in 0.5.
julia> #which #printf("%0.2f", 1/3)
#printf(args...) at printf.jl:1178
Similar to #which, you can use #edit to open the source file and #functionloc to get the function location programmatically.
You can go to help mode in the Julia repl by keyboard shortcut shfit+?
help?> #debug
No documentation found.
#debug is a macro.
# 1 method for macro "#debug":
#debug(msg...) at /home/guo/.julia/v0.5/Logging/src/logging_macros.jl:11
I guess the marco #debug is probably from the package Logging.jl.
In Julia, is there any way to get the name of a passed to a function?
x = 10
function myfunc(a)
# do something here
end
assert(myfunc(x) == "x")
Do I need to use macros or is there a native method that provides introspection?
You can grab the variable name with a macro:
julia> macro mymacro(arg)
string(arg)
end
julia> #mymacro(x)
"x"
julia> #assert(#mymacro(x) == "x")
but as others have said, I'm not sure why you'd need that.
Macros operate on the AST (code tree) during compile time, and the x is passed into the macro as the Symbol :x. You can turn a Symbol into a string and vice versa. Macros replace code with code, so the #mymacro(x) is simply pulled out and replaced with string(:x).
Ok, contradicting myself: technically this is possible in a very hacky way, under one (fairly limiting) condition: the function name must have only one method signature. The idea is very similar the answers to such questions for Python. Before the demo, I must emphasize that these are internal compiler details and are subject to change. Briefly:
julia> function foo(x)
bt = backtrace()
fobj = eval(current_module(), symbol(Profile.lookup(bt[3]).func))
Base.arg_decl_parts(fobj.env.defs)[2][1][1]
end
foo (generic function with 1 method)
julia> foo(1)
"x"
Let me re-emphasize that this is a bad idea, and should not be used for anything! (well, except for backtrace display). This is basically "stupid compiler tricks", but I'm showing it because it can be kind of educational to play with these objects, and the explanation does lead to a more useful answer to the clarifying comment by #ejang.
Explanation:
bt = backtrace() generates a ... backtrace ... from the current position. bt is an array of pointers, where each pointer is the address of a frame in the current call stack.
Profile.lookup(bt[3]) returns a LineInfo object with the function name (and several other details about each frame). Note that bt[1] and bt[2] are in the backtrace-generation function itself, so we need to go further up the stack to get the caller.
Profile.lookup(...).func returns the function name (the symbol :foo)
eval(current_module(), Profile.lookup(...)) returns the function object associated with the name :foo in the current_module(). If we modify the definition of function foo to return fobj, then note the equivalence to the foo object in the REPL:
julia> function foo(x)
bt = backtrace()
fobj = eval(current_module(), symbol(Profile.lookup(bt[3]).func))
end
foo (generic function with 1 method)
julia> foo(1) == foo
true
fobj.env.defs returns the first Method entry from the MethodTable for foo/fobj
Base.decl_arg_parts is a helper function (defined in methodshow.jl) that extracts argument information from a given Method.
the rest of the indexing drills down to the name of the argument.
Regarding the restriction that the function have only one method signature, the reason is that multiple signatures will all be listed (see defs.next) in the MethodTable. As far as I know there is no currently exposed interface to get the specific method associated with a given frame address. (as an exercise for the advanced reader: one way to do this would be to modify the address lookup functionality in jl_getFunctionInfo to also return the mangled function name, which could then be re-associated with the specific method invocation; however, I don't think we currently store a reverse mapping from mangled name -> Method).
Note also that (1) backtraces are slow (2) there is no notion of "function-local" eval in Julia, so even if one has the variable name, I believe it would be impossible to actually access the variable (and the compiler may completely elide local variables, unused or otherwise, put them in a register, etc.)
As for the IDE-style introspection use mentioned in the comments: foo.env.defs as shown above is one place to start for "object introspection". From the debugging side, Gallium.jl can inspect DWARF local variable info in a given frame. Finally, JuliaParser.jl is a pure-Julia implementation of the Julia parser that is actively used in several IDEs to introspect code blocks at a high level.
Another method is to use the function's vinfo. Here is an example:
function test(argx::Int64)
vinfo = code_lowered(test,(Int64,))
string(vinfo[1].args[1][1])
end
test (generic function with 1 method)
julia> test(10)
"argx"
The above depends on knowing the signature of the function, but this is a non-issue if it is coded within the function itself (otherwise some macro magic could be needed).
Problem
I read in an array of strings from a file.
julia> file = open("word-pairs.txt");
julia> lines = readlines(file);
But Julia doesn't know that they're strings.
julia> typeof(lines)
Array{Any,1}
Question
Can I tell Julia this somehow?
Is it possible to insert type information onto a computed result?
It would be helpful to know the context where this is an issue, because there might be a better way to express what you need - or there could be a subtle bug somewhere.
Can I tell Julia this somehow?
No, because the readlines function explicitly creates an Any array (a = {}): https://github.com/JuliaLang/julia/blob/master/base/io.jl#L230
Is it possible to insert type information onto a computed result?
You can convert the array:
r = convert(Array{ASCIIString,1}, w)
Or, create your own readstrings function based on the link above, but using ASCIIString[] for the collection array instead of {}.
Isaiah is right about the limits of readlines. More generally, often you can say
n = length(A)::Int
when generic type inference fails but you can guarantee the type in your particular case.
As of 0.3.4:
julia> typeof(lines)
Array{Union(ASCIIString,UTF8String),1}
I just wanted to warn against:
convert(Array{ASCIIString,1}, lines)
that can fail (for non-ASCII) while I guess, in this case nothing needs to be done, this should work:
convert(Array{UTF8String,1}, lines)