Pert-Interactive.py

import math
import pandas as pd
from graphviz import Digraph

def pert(tasks, dependencies):
    task_data={}
    #Calculate the expected time, variance and standard deviation of each task
    for task, times in tasks.items():
        O, P, M = times
        expected_time = (O + M*4 + P)/6
        variance = ((P-O)**2)/36
        standard_deviation = math.sqrt(variance)
        # Convert to float and round to two
        float(expected_time)
        float(variance)
        float(standard_deviation)
        expected_time = round(expected_time, 2)
        variance = round(variance, 2)
        standard_deviation = round(standard_deviation, 2)
        # Add the task data to the currently empty dictionary
        task_data[task] = {
            "expected_time": float(expected_time),
            "variance": float(variance),
            "standard_deviation": float(standard_deviation),
            "earliest_start": 0,
            "latest_start": None,
            "earliest_finish": float(expected_time),
            "latest_finish": None,
            "slack": 0
        }


    dependencies = {key: [dep] if isinstance(dep, str) else dep for key, dep in dependencies.items()}
    #Calculate the earliest start and earliest finish of each task
    for _ in range(len(task_data)):
        for task in task_data:
            if task in dependencies:
                earliest_start = max([task_data[dep]["earliest_finish"] for dep in dependencies[task]], default=0)
                task_data[task]["earliest_start"] = earliest_start
                task_data[task]["earliest_finish"] = earliest_start + task_data[task]["expected_time"]

    project_duration = max(task_data[task]["earliest_finish"] for task in task_data)


    for task in task_data:
        task_data[task]["latest_finish"] = project_duration

    # Calculate the latest start, finish and slack of each task
    for _ in range(len(task_data)):
        for task in task_data:
            if task not in dependencies or not dependencies[task]:
                continue
            for dep in dependencies[task]:
                task_data[dep]["latest_finish"] = min(task_data[dep]["latest_finish"], task_data[task]["earliest_start"])
                task_data[dep]["latest_start"] = task_data[dep]["latest_finish"] - task_data[dep]["expected_time"]
                task_data[dep]["slack"] = task_data[dep]["latest_start"] - task_data[dep]["earliest_start"]


    return task_data


def create_pert_graph(task_data):
    dot = Digraph()

    for task, data in task_data.items():
        dot.node(task, label=f"{task}\nExpected time: {data['expected_time']} (SD: {data['standard_deviation']})")

    for task, deps in dependencies.items():
        for dep in deps:
            label = str(task_data[dep]['expected_time'])
            dot.edge(dep, task, label=label)

    return dot


#Define the tasks
tasks = {}
dependencies = {}
number_of_tasks = int(input("Enter the number of tasks you have: "))
for i in range(number_of_tasks):
    task = input("Enter the name of the task(ex: A, B): ")
    optimistic_time = float(input("Enter the optimistic time: "))
    pessimistic_time = float(input("Enter the pessimistic time: "))
    most_likely_time = float(input("Enter the most likely time: "))
    tasks[task] = [optimistic_time, pessimistic_time, most_likely_time]

# Define the dependencies of each task
for task in tasks:
    number_of_dependencies = int(input(f"Enter the number of dependencies of task {task}: "))
    dependencies[task] = []
    for i in range(number_of_dependencies):
        dependency = input(f"Enter the name of the dependency {i+1}: ")
        dependencies[task].append(dependency)

results = pert(tasks, dependencies)

pert_graph = create_pert_graph(results)
pert_graph.render("pert_graph_interactive.png")

# Print the Results
results_df = pd.DataFrame.from_dict(results, orient='index')
print(results_df)

results_df.to_csv('personal_results.csv')