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solutions/system_design/social_graph/README.md
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@ -63,7 +63,7 @@ Handy conversion guide:
Without the constraint of millions of users (vertices) and billions of friend relationships (edges), we could solve this unweighted shortest path task with a general BFS approach: Without the constraint of millions of users (vertices) and billions of friend relationships (edges), we could solve this unweighted shortest path task with a general BFS approach:
```python ```python
class Graph(Graph): class Graph():
def shortest_path(self, source, dest): def shortest_path(self, source, dest):
if source is None or dest is None: if source is None or dest is None:
@ -97,6 +97,19 @@ class Graph(Graph):
prev_node_keys[adj_node.key] = prev_node.key prev_node_keys[adj_node.key] = prev_node.key
adj_node.visit_state = State.visited adj_node.visit_state = State.visited
return None return None
"""
obj = Graph()
a = Obj("a")
b = Obj("b")
c = Obj("c")
d = Obj("d")
a.adj_nodes = {"b":b, "c":c}
b.adj_nodes = {"a":a}
c.adj_nodes = {"a":a, "d":d}
d.adj_nodes = {"c":c}
print(obj.shortest_path(a, d))
"""
``` ```
We won't be able to fit all users on the same machine, we'll need to [shard](https://github.com/donnemartin/system-design-primer#sharding) users across **Person Servers** and access them with a **Lookup Service**. We won't be able to fit all users on the same machine, we'll need to [shard](https://github.com/donnemartin/system-design-primer#sharding) users across **Person Servers** and access them with a **Lookup Service**.