[Feature Request]: Add PERT (Program Evaluation and Review Technique) support with optimistic, pessimistic, and most-likely duration inputs

[prince-pokharna]

Summary

The library is named networkdiagram and the README explicitly mentions CPM/PERT in its title and description. However, the current implementation only supports CPM (Critical Path Method) with deterministic single-point durations. PERT — which uses three-point estimates (optimistic, most likely, pessimistic) to model uncertainty — is entirely unimplemented.

This is a significant gap for a library that presents itself as both CPM and PERT capable.

Problem

• CriticalPathMethod is the only class available. There is no PERTNetwork class.
• PERT duration formula t_e = (O + 4M + P) / 6 and variance σ² = ((P - O) / 6)² are not implemented anywhere.
• Users expecting PERT functionality from the library description will find it missing with no error message — just absent functionality.
• The visualization does not support displaying uncertainty ranges or variance on the network graph.

Impact

• The library misleads users with its CPM/PERT branding.
• Project managers and students using this for probabilistic scheduling have no tool support.
• Opportunity cost: PERT support would make this library significantly more useful for real-world project management scenarios.

Proposed Solution

I would like to implement a PERTNetwork class inside networkdiagram/:

class PERTActivity:
    def __init__(self, name: str, optimistic: float, most_likely: float, pessimistic: float, predecessors: list[str]):
        self.name = name
        self.optimistic = optimistic
        self.most_likely = most_likely
        self.pessimistic = pessimistic
        self.predecessors = predecessors
        self.expected_duration = (optimistic + 4 * most_likely + pessimistic) / 6
        self.variance = ((pessimistic - optimistic) / 6) ** 2

class PERTNetwork:
    def __init__(self):
        self.activities: dict[str, PERTActivity] = {}

    def add_activity(self, name, optimistic, most_likely, pessimistic, predecessors):
        self.activities[name] = PERTActivity(name, optimistic, most_likely, pessimistic, predecessors)

    def calculate_project_variance(self, critical_path: list[str]) -> float:
        return sum(self.activities[a].variance for a in critical_path if a in self.activities)

    def calculate_probability(self, target_duration: float, critical_path_duration: float, project_variance: float) -> float:
        import math
        from scipy import stats
        z = (target_duration - critical_path_duration) / math.sqrt(project_variance)
        return stats.norm.cdf(z)

I will also add PERT examples to the README and update the visualization to optionally display variance ranges on critical path nodes. Please assign this to me.

Labels: enhancement, feature, math, help wanted, GSSoC 2026

[prince-pokharna]

Hey @kathan-majithia ,
Please assign it to me under GSSoC 2026.
/assign /claim /claim-assignment