parameters: (dependency_map)
return_statement: return reversed(reversed_dependency_arr)
docstring: Topologically sorts the keys of a map so that dependencies appear first.
  
    Uses Kahn's algorithm:
    https://en.wikipedia.org/wiki/Topological_sorting#Kahn's_algorithm
  
    Args:
      dependency_map: a dict mapping values to a list of dependencies (other keys
        in the map). All keys and dependencies must be hashable types.
  
    Returns:
      A sorted array of keys from dependency_map.
  
    Raises:
      CyclicDependencyError: if there is a cycle in the graph.
      ValueError: If there are values in the dependency map that are not keys in
        the map.
docstring_summary: Topologically sorts the keys of a map so that dependencies appear first.
docstring_tokens: Topologically sorts the keys of a map so that dependencies appear first .
function: def order_by_dependency(dependency_map):
    """Topologically sorts the keys of a map so that dependencies appear first.
  
    Uses Kahn's algorithm:
    https://en.wikipedia.org/wiki/Topological_sorting#Kahn's_algorithm
  
    Args:
      dependency_map: a dict mapping values to a list of dependencies (other keys
        in the map). All keys and dependencies must be hashable types.
  
    Returns:
      A sorted array of keys from dependency_map.
  
    Raises:
      CyclicDependencyError: if there is a cycle in the graph.
      ValueError: If there are values in the dependency map that are not keys in
        the map.
    """
    # Maps trackables -> trackables that depend on them. These are the edges used
    # in Kahn's algorithm.
    reverse_dependency_map = collections.defaultdict(set)
    for x, deps in dependency_map.items():
      for dep in deps:
        reverse_dependency_map[dep].add(x)
  
    # Validate that all values in the dependency map are also keys.
    unknown_keys = reverse_dependency_map.keys() - dependency_map.keys()
    if unknown_keys:
      raise ValueError("Found values in the dependency map which are not keys: "
                       f"{unknown_keys}")
  
    # Generate the list sorted by objects without dependencies -> dependencies.
    # The returned list will reverse this.
    reversed_dependency_arr = []
  
    # Prefill `to_visit` with all nodes that do not have other objects depending
    # on them.
    to_visit = [x for x in dependency_map if x not in reverse_dependency_map]
  
    while to_visit:
      x = to_visit.pop(0)
      reversed_dependency_arr.append(x)
      for dep in set(dependency_map[x]):
        edges = reverse_dependency_map[dep]
        edges.remove(x)
        if not edges:
          to_visit.append(dep)
          reverse_dependency_map.pop(dep)
  
    if reverse_dependency_map:
      leftover_dependency_map = collections.defaultdict(list)
      for dep, xs in reverse_dependency_map.items():
        for x in xs:
          leftover_dependency_map[x].append(dep)
      raise CyclicDependencyError(leftover_dependency_map)
  
    return reversed(reversed_dependency_arr)
function_tokens: def order_by_dependency ( dependency_map ) : # Maps trackables -> trackables that depend on them. These are the edges used # in Kahn's algorithm. reverse_dependency_map = collections . defaultdict ( set ) for x , deps in dependency_map . items ( ) : for dep in deps : reverse_dependency_map [ dep ] . add ( x ) # Validate that all values in the dependency map are also keys. unknown_keys = reverse_dependency_map . keys ( ) - dependency_map . keys ( ) if unknown_keys : raise ValueError ( "Found values in the dependency map which are not keys: " f"{unknown_keys}" ) # Generate the list sorted by objects without dependencies -> dependencies. # The returned list will reverse this. reversed_dependency_arr = [ ] # Prefill `to_visit` with all nodes that do not have other objects depending # on them. to_visit = [ x for x in dependency_map if x not in reverse_dependency_map ] while to_visit : x = to_visit . pop ( 0 ) reversed_dependency_arr . append ( x ) for dep in set ( dependency_map [ x ] ) : edges = reverse_dependency_map [ dep ] edges . remove ( x ) if not edges : to_visit . append ( dep ) reverse_dependency_map . pop ( dep ) if reverse_dependency_map : leftover_dependency_map = collections . defaultdict ( list ) for dep , xs in reverse_dependency_map . items ( ) : for x in xs : leftover_dependency_map [ x ] . append ( dep ) raise CyclicDependencyError ( leftover_dependency_map ) return reversed ( reversed_dependency_arr )