Dependency-Aware Task Prioritization

The problem

Large projects are difficult to manage because it is hard to see which tasks are blocked by others and which ones actually move the needle.

What it does

It maps out a project's tasks as a web of dependencies and groups them to highlight the most impactful pieces.

Why it matters

It provides a clear view of what needs to be done first and what parts of a project carry the most weight.

Validation

It was run in the sandbox and it failed. run output shows an error/traceback — the artifact does NOT run clean.

$ python3 dependency_prioritizer.py
File "/work/dependency_prioritizer.py", line 41
    print(f'Error: tasks.json not found in {os.getcwd()})
          ^
SyntaxError: unterminated f-string literal (detected at line 41)

No screenshot — there is nothing working to show. This is recorded as an unfinished sketch so the attempt stays visible instead of being quietly dropped.

The code

All of it — 67 lines, one file, standard library only.

import json
from collections import defaultdict, deque
import sys

def topological_sort(graph):
    in_degree = {node: 0 for node in graph}
    for node in graph:
        for neighbor in graph[node]:
            in_degree[neighbor] += 1
    queue = deque([node for node in graph if in_degree[node] == 0])
    sorted_list = []
    while queue:
        node = queue.popleft()
        sorted_list.append(node)
        for neighbor in graph[node]:
            in_degree[neighbor] -= 1
            if in_degree[neighbor] == 0:
                queue.append(neighbor)
    if len(sorted_list) != len(graph):
        raise ValueError("Graph has cycles")
    return sorted_list

def cluster_tasks(tasks, graph):
    clusters = defaultdict(list)
    for task in tasks:
        key = tuple(sorted(graph[task]))
        clusters[key].append(task)
    return clusters

def score_impact(tasks, reverse_graph):
    impact_scores = {}
    for task in tasks:
        impact_scores[task] = len(reverse_graph[task])
    return impact_scores

def main():
    try:
        with open('tasks.json', 'r') as f:
            tasks_graph = json.load(f)
    except FileNotFoundError:
        print(f'Error: tasks.json not found in {os.getcwd()})
        sys.exit(1)

    reverse_graph = defaultdict(list)
    for task, deps in tasks_graph.items():
        for dep in deps:
            reverse_graph[dep].append(task)

    sorted_tasks = topological_sort(tasks_graph)
    clusters = cluster_tasks(sorted_tasks, tasks_graph)
    impact_scores = score_impact(sorted_tasks, reverse_graph)

    prioritized = []
    for task in sorted_tasks:
        cluster_key = tuple(sorted(tasks_graph[task]))
        cluster = clusters[cluster_key]
        prioritized.append({
            'task': task,
            'impact': impact_scores[task],
            'cluster': cluster,
            'dependencies': tasks_graph[task]
        })

    print('vykf8t6f9d2r:\n' + json.dumps(prioritized, indent=2))

if __name__ == '__main__':
    main()