# Dict issue?
**URL:** https://discourse.julialang.org/t/dict-issue/42338
**Category:** General Usage
**Created:** [July 1, 2020, 3:17am UTC](https://discourse.julialang.org/t/dict-issue/42338 "2020-07-01T03:17:56Z")
**Posts on this page:** 11
**Page:** 1
### Author:  [@vinhphunguyen](https://discourse.julialang.org/u/vinhphunguyen)
#### Post date: [July 1, 2020, 3:17am UTC](https://discourse.julialang.org/t/dict-issue/42338/1 "2020-07-01T03:17:56Z")
I made a dictionary to store some inputs to a function, see below
```julia
data = Dict()
data["total_time"] = 0.3
data["time"] = 0.
data["dt"] = 1e-3
function f(data)
Tf = Float64(data["total_time"])
dtime = Float64(data["dt"] )
t = Float64(data["time"])
fric = Float64(data["friction"])
end
```
Then, I do: @code\_warntype(f), and saw this:
t::Any
Tf::Any
fric::Any
My question is why?
---
### Author:  [@jling](https://discourse.julialang.org/u/jling)
#### Post date: [July 1, 2020, 3:21am UTC](https://discourse.julialang.org/t/dict-issue/42338/2 "2020-07-01T03:21:19Z")
`%3 = Base.getindex(data, "dt")::Any`
notice your `Dict` is `{Any, Any}`
you’re converting an `Any` to `Float64`, your `Dict()` (can) contain `Any`s so compiler won’t know better until actually try converting it
replacing the first line with:
`data = Dict{String, Float64}()` would fix the instability:
```julia
Variables
#self#::Core.Compiler.Const(f, false)
data::Dict{String,Float64}
Tf::Float64
dtime::Float64
t::Float64
fric::Float64
```
---
### Author:  [@vinhphunguyen](https://discourse.julialang.org/u/vinhphunguyen)
#### Post date: [July 1, 2020, 3:25am UTC](https://discourse.julialang.org/t/dict-issue/42338/3 "2020-07-01T03:25:59Z")
> [@jling](#):
>
> Base.getindex(data, “dt”)
Thanks a lot for your prompt reply. Actually, I also stored other things in data, such as
```julia
data = Dict()
data["total_time"] = dtime#Tf
data["time"] = 0.
data["dt"] = dtime
data["friction"] = fric
data["dirichlet_grid"] = [("back", (0,0,1)),
("front",(1,1,1)),
("bottom",(1,1,1)),
("left",(1,1,1)),
("right",(1,1,1)),
] # => fix bottom nodes on X/Y/Z dir
```
That was why I went for data=Dict(). Any suggestion to have both flexibility and efficiency?
---
### Author:  [@jling](https://discourse.julialang.org/u/jling)
#### Post date: [July 1, 2020, 3:27am UTC](https://discourse.julialang.org/t/dict-issue/42338/4 "2020-07-01T03:27:02Z")
yes,
```julia
function f(data)
Tf = data["total_time"]::Float64
dtime = data["dt"]::Float64
...
end
```
something like this so they have to be `Float64` (instead of converting them)
---
### Author:  [@vinhphunguyen](https://discourse.julialang.org/u/vinhphunguyen)
#### Post date: [July 1, 2020, 3:31am UTC](https://discourse.julialang.org/t/dict-issue/42338/5 "2020-07-01T03:31:46Z")
Oh, so easy. Thanks a lot.
---
### Author:  [@vinhphunguyen](https://discourse.julialang.org/u/vinhphunguyen)
#### Post date: [July 1, 2020, 5:49am UTC](https://discourse.julialang.org/t/dict-issue/42338/6 "2020-07-01T05:49:52Z")
I am now facing another issue:
```julia
function velo_func(t)
if t < 1.5e-3
vx = 0.
vy = -50.
vz = 0.
else
vx = 50.
vy = 0.
vz = 0.
end
return (vx,vy,vz)
end
data = Dict()
data["total_time"] = dtime#Tf
data["time"] = 0.
data["dt"] = dtime
data["friction"] = fric
data["rigid_body_velo"] = Array{Tuple{Int64,Function},1}([(1,velo_func)])
```
```julia
function f(data)
rigid_solids = data["rigid_body_velo"]::Array{Tuple{Int64,Function},1}
for (s,f) in rigid_solids
solid = solids[s]
vex,vey,vez = f(t)
end
end
```
My problem is (vex, vey,vez) is recognised as Tuple(Any,ANy,Any).
Could u please help me how to make Julia knows it is Tuple(Float,Float,Float)?
---
### Author:  [@DNF](https://discourse.julialang.org/u/DNF)
#### Post date: [July 1, 2020, 6:10am UTC](https://discourse.julialang.org/t/dict-issue/42338/7 "2020-07-01T06:10:51Z")
Firstly, you are using the same name, `f`, for both the outer function and the function retrieved from the Dict. I’m not sure if that causes any problems, but it’s confusing and not a good idea, imho.
Secondly, Julia doesn’t know which function is coming out of your Dict. It just knows it’s some function, _any_ function, and therefore it cannot predict what the types of the outputs will be. It doesn’t matter that you name the outputs `vex, vey, vez`, there’s no way to know that they have anything to do with the function `velo_func`.
Will `data["rigid_body_velo"]` contain many functions or just one?
---
### Author:  [@vinhphunguyen](https://discourse.julialang.org/u/vinhphunguyen)
#### Post date: [July 1, 2020, 6:12am UTC](https://discourse.julialang.org/t/dict-issue/42338/8 "2020-07-01T06:12:46Z")
Thanks DNF. It just contains one function, but the function is problem-dependent. In other words, it is an input.
---
### Author:  [@DNF](https://discourse.julialang.org/u/DNF)
#### Post date: [July 1, 2020, 6:20am UTC](https://discourse.julialang.org/t/dict-issue/42338/9 "2020-07-01T06:20:17Z")
It might be difficult to tell the compiler which function to expect. But you can add a type assertion
```julia
(vex, vey, vez) = f(t)::Tuple{Float64, Float64, Float64}
```
(or something like that - - typing on my phone here)
> [@vinhphunguyen](#):
>
> `data["rigid_body_velo"] = Array{Tuple{Int64,Function},1}([(1,velo_func)])`
To simplify, can’t you write
```julia
data["rigid_body_velo"] = (1, velo_func)
```
?
---
### Author:  [@vinhphunguyen](https://discourse.julialang.org/u/vinhphunguyen)
#### Post date: [July 1, 2020, 6:35am UTC](https://discourse.julialang.org/t/dict-issue/42338/10 "2020-07-01T06:35:47Z")
> [@DNF](#):
>
> `::Tuple{Float64, Float64, Float64} `
Thanks again DNF. The thing is that I might have more than one tuple in data[“rigid\_body\_velo”], so in general, it must be a vector.
---
### Author:  [@DNF](https://discourse.julialang.org/u/DNF)
#### Post date: [July 1, 2020, 7:31am UTC](https://discourse.julialang.org/t/dict-issue/42338/11 "2020-07-01T07:31:24Z")
Ok, that’s what I meant when I asked if there would be only one function.
But still, I think you can just write
```julia
data["rigid_body_velo"] = [(1,velo_func), (2, other_func)] # etc.
```
No need for the complicated type info.