Python Graph Analysis Expert

Graph Modeling in Python

Strong familiarity with mathematical graph structures (adjacency lists/matrices)

Experience with recursive algorithms (BFS/DFS implementations without loops)

Use of provided modules (graphs.py, digraphs.py) over third-party libraries

Algorithmic Analysis

Implementation of:

Shortest path algorithms

Constraint satisfaction problems

Interval graph coloring

Flow network analysis

Data Handling

Efficient parsing of CSV-based rail network data (not big data, but requires careful modeling)

Set/dictionary operations for fast lookups in graph traversals

Key Mathematical Concepts

Graph diameter calculation

Bipartite matching

Flow network bottleneck analysis

Predicate logic for constraint validation

Project-Specific Constraints

Loop-free implementations (recursion/comprehensions only)

Adherence to strict I/O formats from test cases

Avoidance of external libraries beyond csv, itertools, functools, and course-provided modules