title: How to set up logging on dask distributed workers?
body: <p>After upgrading of dask distributed to version 1.15.0 my logging stopped working.</p>
  
  <p>I've used logging.config.dictConfig to initialize python logging facilities, and previously these settings propagated to all workers. But after upgrade it doesn't work anymore.</p>
  
  <p>If I do dictConfig right before every log call on every worker it works but it's not a proper solution.</p>
  
  <p>So the question is how it initialize logging on every worker before my computation graph starts executing and do it only once per worker?</p>
  
  <p><strong>UPDATE:</strong></p>
  
  <p>This hack worked on a dummy example but didn't make a difference on my system:</p>
  
  <pre><code>def init_logging():
     # logging initializing happens here
     ...
  
  client = distributed.Client()
  client.map(lambda _: init_logging, client.ncores())
  </code></pre>
  
  <p><strong>UPDATE 2:</strong></p>
  
  <p>After digging through documentation this fixed the problem:</p>
  
  <pre><code>client.run(init_logging)
  </code></pre>
  
  <p>So the question now is: Is this a proper way to solve this problem?</p>