Retrieving Your Completed Files


When a Job has been completed, the output data from that job is made available to download. A user can download the data by using the Conductor Downloader tool. The Downloader can operate in one of two modes: Manual(Explicit mode) or Automatic (Daemon mode)


The frames of a job can be manually downloaded via a shell command:

conductor downloader --job_id <jobid>
For example:
conductor downloader --job_id 00014

A job can be safely downloaded multiple times, either manually or automatically without creating conflict.


A job's data can be automatically downloaded by running the Downloader in daemon mode. As each Task completes, the downloader daemon will download it to your local disk. The directory that the files are downloaded to is dictated by the path specified in the Job’s output path. 

To start the downloader in daemon mode:

conductor downloader

Conductor recommends running stand-alone upload and download daemons on a dedicated box. This allows resources to be offloaded from artists machines so they can be more productive. 

Deploying the daemons requires a working conductor install or the following docker setup. 

You need to make sure that you configure "local_upload": False in your config.yml so artist boxes do not upload directly. 

Note: you can export CONDUCTOR_DEVELOPMENT=1 if you would like debug output


Docker is the preferred mechanism to deploy the daemons since it allows us to package the entire runtime environment, but this is not a requirement. You can skip this step if you would like.

Instructions for installing docker can be found here.

In order to run the public conductor docker image, you need to specify the following options:

Export account name:

    -e CONDUCTOR_ACCOUNT=my_account_name

share one or more directories. 

     -v /Volumes:/Volumes
     -v /home:/home

you need to make sure that you share all of the directories that include dependencies for renders. 

To make this easier, we recommend setting up an alias, like:

     alias conductor_docker=''docker run -it \
     -v /Volumes/af:/Volumes/af
     -v /Users:/Users
     -e CONDUCTOR_ACCOUNT=mystudio