Add new overview + exercise files + update last week's examples

notes-and-examples/2026.07.31/overview.md

@@ -32,7 +32,7 @@ with 2nd-degree connections in the second inner list, and so forth.
 Your algorithm should take a starting person and a *maximum N*, such that your
 algorithm does not return connections past the maximum Nth connection.
 
-Example: `nthDegreeConnections(Mallory, 2)` would return the following lists
+Example: `nth_degree_connections(Mallory, 2)` would return the following lists
 in a list:
 
 - `[Carol, Grace]`: 1st-degree connections
@@ -55,15 +55,27 @@ Your algorithm should take the starting and ending points, and return a list
 of tuples. Each tuple should contain the traversal from point A to point B,
 followed by the total weight.
 
-In this fictitious graph, calling `possiblePaths("Santa Ana", "San Francisco")`
+In this fictitious graph, calling `possible_paths("Santa Ana", "San Francisco")`
 should yield the return below. Which path is better?
 
 ```python
 graph = {
-    "Santa Ana": [("Los Angeles", 5), ("Palm Springs", 50)],
-    "Los Angeles": [("San Francisco", 25), ("Santa Ana", 5)],
-    "Palm Springs": [("San Francisco", 30), ("Santa Ana", 50)],
-    "San Francisco": [("Los Angeles", 25), ("Palm Springs", 30)]
+    'Santa Ana': {
+        'Los Angeles': 5,
+        'Palm Springs': 50
+    },
+    'Los Angeles': {
+        'San Francisco': 25,
+        'Santa Ana': 5
+    },
+    'Palm Springs': {
+        'San Francisco': 30,
+        'Santa Ana': 50
+    },
+    'San Francisco': {
+        'Los Angeles': 25,
+        'Palm Springs': 30
+    } 
 }
 ```
 

notes-and-examples/2026.08.04/exercise1.py

@@ -0,0 +1,28 @@
+# see the overview from 2026.07.31
+
+sample_graph = {
+    'Alice': set(['Bob', 'Carol']),
+    'Bob': set(['Alice', 'Dave']),
+    'Carol': set(['Alice', 'Eve', 'Mallory']),
+    'Dave': set(['Frank', 'Eve', 'Bob']),
+    'Eve': set(['Carol', 'Grace', 'Dave']),
+    'Frank': set(['Dave', 'Heidi']),
+    'Grace': set(['Eve', 'Ivan', 'Mallory']),
+    'Heidi': set(['Frank', 'Ivan']),
+    'Ivan': set(['Heidi', 'Grace']),
+    'Mallory': set(['Carol', 'Grace'])
+}
+
+def nth_degree_connections(
+    graph: dict[str, set[str]],
+    starting_vertex: str,
+    max_n: int
+):
+    # TODO
+    pass
+
+print(nth_degree_connections(sample_graph, 'Mallory', 2))
+print(nth_degree_connections(sample_graph, 'Alice', 4))
+print(nth_degree_connections(sample_graph, 'Ivan', 1))
+print(nth_degree_connections(sample_graph, 'Grace', 0))
+print(nth_degree_connections(sample_graph, 'Carol', 100))

notes-and-examples/2026.08.04/exercise2.py

@@ -0,0 +1,26 @@
+# see the overview from 2026.07.31
+
+sample_graph = {
+    'Santa Ana': {
+        'Los Angeles': 5,
+        'Palm Springs': 50
+    },
+    'Los Angeles': {
+        'San Francisco': 25,
+        'Santa Ana': 5
+    },
+    'Palm Springs': {
+        'San Francisco': 30,
+        'Santa Ana': 50
+    },
+    'San Francisco': {
+        'Los Angeles': 25,
+        'Palm Springs': 30
+    } 
+}
+
+def possible_paths(start: str, end: str):
+    # TODO
+    pass
+
+print(possible_paths('Santa Ana', 'San Francisco'))

notes-and-examples/2026.08.04/overview.md

@@ -0,0 +1,3 @@
+## Outline
+
+Let's work on the exercises from [last week](../2026.07.31/overview.md).