METADATA

# Format: google3/devtools/metadata/metadata.proto (go/google3metadata)

name: "sb-sim"
language: PYTHON
description: "Smart Buildings Control Environment"

third_party {
  identifier {
    type: "Piper"
    value: "http://google3/third_party/py/smart_buildings"
    primary_source: true
  }

  identifier {
    type: "PyPI"
    omission_reason: "Package doesn't have an upstream repo."
  }
}

presubmit: {
  path_expression: "//depot/google3/third_party/py/smart_buildings/..."

  check_description: {
    failure_message:
      "\n"
      "CL descriptions for changes to third_party/py/smart_buildings\n"
      "must contain one or more sections delimited as follows:\n"
      "\n"
      "BEGIN_PUBLIC\n"
      "...text exposed to open source public git repo...\n"
      "END_PUBLIC\n"
      "\n"
      "If your change affects only files that you know are not "
      "opensourced, you may write something like 'Internal "
      "change'. You may not leave the section empty. \n"

    required_regexp:
      "(^|\\n)\\s*BEGIN_PUBLIC\\s*?\\n"
      "(.*\\n)*"
      "\\s*\\S+.*(\\n.*)*\\n"
      "\\s*END_PUBLIC\\s*?\\n"
    required_for_cleanup: true
  }
}

presubmit: {
  path_expression: "//depot/google3/third_party/py/smart_buildings/..."

  check_do_not_submit: {
    failure_status: ERROR
  }
  check_tabs: {
    failure_status: ERROR
  }
  check_trailing_whitespace: {
    failure_status: ERROR
  }
  check_lint: {
    action: REVIEW
    failure_status: WARNING
  }
  check_lint: {
    action: SUBMIT
    failure_status: ERROR
  }
}

presubmit: {
  include_presubmit: "//depot/google3/corp/ml/smart_buildings/METADATA"
}

exported {
  copybara {
    config_path: "//depot/google3/third_party/py/smart_buildings/copy.bara.sky"
  }
  owning_team_email: "ce-ml-team@google.com"
  path_expression: "//depot/google3/third_party/py/smart_buildings/..."
  request_url: "https://launch.corp.google.com/launch/4284362"
  remote_location: "https://github.com/google/sbsim"
  reason: OPEN_SOURCE
  description: "Open sourcing the Smart Buildings Control Simulation, Reward Function, and Custom Environment for training RL agents."
}