Global parameters

[varvara-l]

There are some configuration parameters in the system that different functions and classes can require any time (for example, a special directory for temporary files, the number of processors the system can use).
It's sometimes inconvenient to pass them to functions, so there should be a list of global variables which are seen from everywhere. But I don't know what is a good way to do it in python.

[chrishokamp]

for now we should use the conf.yaml file for this. That's already what
we're doing with the workers: param in yaml.

I think we want to avoid globals because that's a code smell (especially in
python). If a component needs a parameter from the config, like the tmp/
directory path, then it needs to be initialized with that parameter,
probably with a sensible default in most cases.

So, for the alignment model, it should be initialized with a tmp/ dir
location, and it should probably delete the alignment files by default once
we're finished using them.

In the future, the user should be able to name the tmp/ dir after the
experiment, so that different experiment configurations can be stored in
different directories.

On Thu, Jan 15, 2015 at 3:26 PM, varvara-l notifications@github.com wrote:

There are some configuration parameters in the system that different
functions and classes can require any time (for example, a special
directory for temporary files, the number of processors the system can
use).
It's sometimes inconvenient to pass them to functions, so there should be
a list of global variables which are seen from everywhere. But I don't know
what is a good way to do it in python.

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#5.

[varvara-l]

All global parameters should be defined in the config and passed to functions that need them. There won't be any global parameters seen from everywhere.