<｜begin▁of▁sentence｜>### Instruction:
As a Logistics Coordinator overseeing transportation operations for a large warehouse, you're tasked with optimizing the movement of goods. You've received a shipment manifest in GML format, detailing the layout of the warehouse and the paths between different sections. Your goal is to efficiently identify sections with high traffic flow, represented as vertices with a degree greater than 3, and mark them for potential optimization. Additionally, you need to locate the first section named 'foo' to ensure its efficient handling.

To achieve this, you'll employ igraph's VertexSeq class, which allows you to traverse and manipulate vertices within the warehouse graph. Using this, you'll first select all vertices that have a degree greater than 3, indicating areas with significant activity. Then, you'll pinpoint the location of the first vertex named 'foo' to ensure it receives appropriate attention.

Finally, to visually highlight high-traffic areas, you'll set the 'color' attribute of all high-degree vertices to 'red', making them easily identifiable for further analysis and optimization. This targeted approach will streamline operations and enhance overall efficiency within the warehouse.
### Response:
import igraph as ig

# Load a graph from a file
graph = ig.Graph.Read_GML('path_to_gml_file.gml')

# Access the vertex sequence
vertices = graph.vs

# Get all vertices with degree greater than 3
high_degree_vertices = vertices.select(_degree_gt=3)

# Find the first vertex with name 'foo'
vertex_with_name_foo = vertices.find(name_eq='foo')

# Print out the names of vertices with high degree
for v in high_degree_vertices:
    print(v['name'])

# Set the attribute 'color' to 'red' for all high degree vertices
high_degree_vertices.set_attribute_values('color', 'red')
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