Add whiteboard link for optimizing last week's assignment

This reverts commit 8d50900eaa.

assignments/python-packages/python-packages.md

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+## Overview
+
+Create a program which creates a topological ordering of Python packages.
+See this [starter template](https://gitea.bchen.dev/brendan/python-packages-starter)

notes-and-examples/2026.08.20/exercise2.py

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+# See the overview from 2026.07.31.
+# Note: I added Anaheim to the sample graph here. The solution should work
+# appropriately with either graph.
+
+sample_graph = {
+    'Santa Ana': {
+        'Los Angeles': 5,
+        'Anaheim': 3,
+        'Palm Springs': 50
+    },
+    'Anaheim': {
+        'Los Angeles': 2,
+        'Santa Ana': 3
+    },
+    'Los Angeles': {
+        'Anaheim': 2,
+        '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/2026.08.20/overview.md

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+## Outline
+
+We're working on exercise 2 from [2026.07.31](../2026.07.31/overview.md).
+The exercise and starter file is included again below for convenience.
+
+In a *weighted* road network, return all possible paths that a car can take to
+reach point A to point B. For each path, also sum up the total weight that
+taking that path requires.
+
+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 `possible_paths("Santa Ana", "San Francisco")`
+should yield the return below.
+
+```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", "San Francisco"],
+        30
+    ),
+    (
+        ["Santa Ana", "Palm Springs", "San Francisco"],
+        80
+    )
+]
+```

notes-and-examples/2026.08.27/overview.md

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+## Overview
+
+We'll go over exercise 2 from [last week](../2026.08.20/overview.md), as well as
+a new topic: [topological sort](./topological_sort.md). Try to complete the 
+exercise from the document.

notes-and-examples/2026.08.27/topological_sort.md

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+## Class ordering
+
+These are some classes for Chapman University, for
+the [computer science program](https://catalog.chapman.edu/preview_program.php?catoid=33&poid=6408&print).
+
+![An ordering of classes for Chapman University.](./classes.png)
+
+This is a *directed acyclic graph*, or DAG.
+
+- Directed: edges point from one node to another, not necessarily the other way around
+- Acyclic: there are no *cycles* in the graph
+
+We say that a class is a *prerequisite* or a *dependency* of another class
+if we need to take it before that other class. So, we need to take CPSC 230
+before CPSC 231, for example.
+
+Could you come up with something like this for your school?
+
+## The algorithm
+
+If you were to come up with a list of classes, such that the list of classes
+is in the order which you need to take them, what would that look like?
+
+This order is what we're trying to achieve with the topological sort
+algorithm. Note that there can be multiple correct solutions.
+
+By the way, [here is a link to the whiteboard](https://excalidraw.com/#json=69478-DnuxlMCcyaOkazP,I_-nOWaO9m0wJkAFfqt9JA).
+
+## The exercise
+
+Let's write the algorithm. First, test it against the Chapman classes, then
+put in your classes and see how it fares against that.

notes-and-examples/2026.08.27/topological_sort.py

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+from collections import deque
+# double-ended queue, this may be helpful
+# see the docs: https://docs.python.org/3/library/collections.html#collections.deque
+
+classes = {
+    'CPSC 230': {'CPSC 231'},
+    'CPSC 231': {'CPSC 350', 'CPSC 330'},
+    'CPSC 350': {'CPSC 380', 'CPSC 408', 'CPSC 406'},
+    'CPSC 330': {'CPSC 351'},
+    'CPSC 351': set(),
+    'ENGR 101': set(),
+    'CPSC 380': set(),
+    'CPSC 406': set(),
+    'CPSC 408': set()
+}
+
+def topological_sort(adjacency_list: dict[str, set[str]]):
+    # return the sorted ordering ['CPSC 230', 'ENGR 101', 'CPSC 231', ...]
+    return []
+
+print(topological_sort(classes))

notes-and-examples/2026.08.27/topological_sort_solution.py

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+from collections import deque
+
+# This is a solution which uses DFS to trace the paths; there
+# are other solutions as well
+
+classes = {
+    'CPSC 230': {'CPSC 231'},
+    'CPSC 231': {'CPSC 350', 'CPSC 330'},
+    'CPSC 350': {'CPSC 380', 'CPSC 408', 'CPSC 406'},
+    'CPSC 330': {'CPSC 351'},
+    'CPSC 351': set(),
+    'ENGR 101': set(),
+    'CPSC 380': set(),
+    'CPSC 406': set(),
+    'CPSC 408': set()
+}
+
+
+def topological_sort(adjacency_list: dict[str, set[str]]):
+    result = deque()
+    visited = set()
+
+    def dfs(current: str, visited_in_traversal=None):
+        if visited_in_traversal is None:
+            visited_in_traversal = set()
+        if current in visited:
+            return
+        if current in visited_in_traversal:
+            raise ValueError("Graph has a cycle")
+
+        visited_in_traversal.add(current)
+
+        for neighbor in adjacency_list[current]:
+            dfs(neighbor, visited_in_traversal)
+
+        # to trace the reverse path, use .append
+        result.appendleft(current)
+        visited.add(current)
+
+    for node in adjacency_list.keys():
+        if node not in visited:
+            dfs(node)
+
+    return result
+
+
+print(topological_sort(classes))

notes-and-examples/2026.09.04/overview.md

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+## Overview
+
+We will go over the exercise from last week and start on [Python Packages](https://gitea.bchen.dev/brendan/python-packages-starter),
+a new assignment. For reference, this assignment is also in the Assignments section.
+
+Whiteboard for optimizing last week's assignment: https://excalidraw.com/#json=rd-1CkdxA2AMpQsiVOQkY,t7-KayQW3DntCDkXVktEJQ
+