# Distributed, packages, and race condition in pre-compiling

**URL:** <https://discourse.julialang.org/t/distributed-packages-and-race-condition-in-pre-compiling/43340>\
**Category:** General Usage\
**Tags:** package, parallel, distributed\
**Created:** [July 19, 2020, 4:55pm UTC](https://discourse.julialang.org/t/distributed-packages-and-race-condition-in-pre-compiling/43340 "2020-07-19T16:55:28Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![torgo](https://avatars.discourse-cdn.com/v4/letter/t/94ad74/32.png) [@torgo](https://discourse.julialang.org/u/torgo)\
**Post date:** [July 19, 2020, 4:55pm UTC](https://discourse.julialang.org/t/distributed-packages-and-race-condition-in-pre-compiling/43340/1 "2020-07-19T16:55:28Z")

</div>

I am having a problem that I think is represented well by this [StackExchange question discussion.](https://stackoverflow.com/questions/55410326/module-does-not-support-precompilation-but-is-imported-by-a-module-that-does)  
As far as I understand that discussion, one needs to be careful when using Distributed to balance two issues:

1. Each worker needs to be able to see all of the necessary code.
2. If packages need to be pre-compiled, then one could run into a race condition if each worker tries to compile.

I was running into this problem with a more complicated set of code, so I decided to try to make a simple example to understand the issues.

One solution suggested in the StackExchange post is to do something like this:

```julia
using Distributed
using DataFrames
@everywhere using DataFrames

```

with the idea (as I understand it), that the first `using` will result in pre-compilation in serial, and then the `@everywhere using` will load the code onto each worker.  
I have verified that this works as expected for me.

However, suppose now that instead of `DataFrames`, I want to load my very simple module called `Run`:

```julia
# Run.jl
module Run

function runsims()
    println("hello!")
end

end

```

I start a Julia process with no options and run this code:

```julia
using Distributed
using Run
@everywhere using Run

```

No problems.

However, if I start with `julia -p 1` and try to run the same code, I get this error after `using Run`:

```julia
ERROR: On worker 2:
ArgumentError: Package Run not found in current path:
- Run `import Pkg; Pkg.add("Run")` to install the Run package.

```

Why does this error occur?  
If I try this:

```julia
using Distributed
Pkg.add("Run")
using Run
@everywhere using Run

```

then I also get an error:

```julia
ERROR: LoadError: The following package names could not be resolved:
 * Run (not found in project, manifest or registry)
Please specify by known `name=uuid`.

```

Am I just using modules in the wrong way?  
I have not had problems with this type of approach until trying to parallelize with Distributed.

---

<div class="post-metadata">

**Author:** ![torgo](https://avatars.discourse-cdn.com/v4/letter/t/94ad74/32.png) [@torgo](https://discourse.julialang.org/u/torgo)\
**Post date:** [July 19, 2020, 5:35pm UTC](https://discourse.julialang.org/t/distributed-packages-and-race-condition-in-pre-compiling/43340/2 "2020-07-19T17:35:51Z")

</div>

Forgot something: All of this is premised on me having added the current working directory to `LOAD_PATH`:

```julia
push!(LOAD_PATH, ".")

```