DSA Study Plan

Your brief

Begin with contracts, scans and array costs. Then compare ordering methods and the structures that support different access patterns. Move to tree invariants and graph representations before weighted routes, spanning forests and residual flow. Finish with greedy counterexamples, reusable subproblems and bounded exact optimization. Keep the original fixture, expected result and a short explanation of the preconditions alongside every saved source.

Run the code

Select Try in playground to load this complete source into the existing Python editor. It does not run automatically; choose Run when ready. These examples use only the Python standard library and small fictional inputs. They do not need database services, extra packages or personal files.

For local work, save the complete source as study-plan.py and run python study-plan.py. The local review uses Python 3.12.14; the browser uses the existing Pyodide 0.27.7 runtime. Keep inputs small, respect explicit table/tour budgets and account for recursion limits before increasing a fixture’s size.

Worked solution

checks = [
    ("scan", [7, 4, 6], 4),
    ("empty", [], 4),
    ("first position", [4, 7], 4),
]
def locate(values, target):
    return next((index for index, value in enumerate(values) if value == target), None)

for label, values, target in checks:
    print(label, locate(values, target))

scan 1
empty None
first position 0

Time, space and assumptions

This small test collection scans each supplied sequence once. For a larger review, report fixture counts and input bounds instead of calling an unbounded collection of tests constant-time.

Extend and test

Deliver one route project, one subset project and a report listing independent oracles, boundary cases, exact versions and any untested scale or input conditions.