CLRS Notebook Examples

spytial-clrs is a Jupyter notebook collection. It implements the data structures from the CLRS algorithms textbook (Cormen, Leiserson, Rivest, Stein) with Spytial. Each notebook is organized by one CLRS chapter and covers one or more textbook structures. The notebook declares the spatial constraints that make each structure legible.

What's in it

Chapter	Structures	Notebook
6, 19	Max heap, Fibonacci heap	heaps.ipynb
10	Stacks, queues	stacksqueues.ipynb
10.2	Singly, doubly, circular linked lists	linked-lists.ipynb
11	Direct-address and chained hash tables	hash-tables.ipynb
12, 13, 14, 14.3, 18, 20	BST, red-black, order statistic, interval, B-tree, van Emde Boas	trees.ipynb
15.2	Matrix-chain memoization tables	memoization.ipynb
16.3	Huffman codes	huffman.ipynb
21.3	Disjoint-set forests (forest and set views)	disjoint-sets.ipynb
22, 22.4, 22.5, 23	Graphs, topological sort, strongly connected components, MST	graphs.ipynb

The collection also contains BDDs in simple-bdd.ipynb.

Run the notebooks

The collection can be used in three ways. No local installation is necessary beyond the notebooks themselves.

Docker (no local setup):

docker pull sidprasad/spytial-clrs:latest
docker run -p 8888:8888 sidprasad/spytial-clrs
# open http://localhost:8888

JupyterLite (in-browser, no installation): refer to the spytial-clrs README for the deployed link.

Local clone:

git clone https://github.com/sidprasad/spytial-clrs
cd spytial-clrs
pip install -r requirements.txt
jupyter notebook src/

Reading guide

Use the notebooks as a guide, based on the structure to visualize:

Notebook	Structures	Good docs topics
stacksqueues.ipynb	stacks, queues	attributes, linear structure, first tutorial examples
linked-lists.ipynb	singly, doubly, circular linked lists	field hiding, attributes, cyclic layout
heaps.ipynb	max heap, Fibonacci heap	recursive structures, alignment, richer edge styling
trees.ipynb	BST, red-black tree, order statistic tree, interval tree, B-tree, van Emde Boas tree	annotations on recursive types, grouped structures, larger gallery examples
hash-tables.ipynb	direct-address and chained hash tables	grouping, selector-heavy examples, labeled fields
graphs.ipynb	graphs, MST, SCC views	graph-like structures, grouping, alternative visual projections
disjoint-sets.ipynb	disjoint set forests	group constraints and forest layouts
memoization.ipynb	matrix-style DP tables	alignment constraints and grid-like layouts

How to use these examples

• Start with stacksqueues.ipynb or linked-lists.ipynb for an introduction to Spytial.
• Browse trees.ipynb and graphs.ipynb for more complex layouts and more advanced operation combinations.
• Use the notebook closest to the target data shape as a template for a first diagram.