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MIT License
Copyright (c) 2024 Stephen Waits <steve@waits.net>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
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# Monte Carlo Project Scheduler (mcps)
Monte Carlo Project Scheduler (mcps) is a command-line tool that runs Monte
Carlo simulations on project schedules to estimate completion times and effort
required. It helps project managers and engineers gain a better understanding of
potential project risks and timelines by providing a probabilistic analysis of
schedule durations and total work effort.
## Features
- **Simulate Project Schedules**: Run multiple simulations to estimate the
probability distribution of project completion times and total work effort.
- **Customizable Inputs**: Accepts project schedules in YAML or JSON formats,
with options to override certain parameters like the number of workers or the
number of iterations.
- **Visual Output**: Generates an ASCII-based cumulative distribution function
(CDF) graph, providing an easy-to-understand visualization of the simulation
results.
## Installation
### Prerequisites
- **Rust**: You'll need to have Rust installed on your system to build the
project. You can install Rust using `rustup`:
```bash
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
```
### Building from Source
- Clone and build the repository:
```bash
git clone <git@git.sr.ht>:~swaits/mcps
cd mcps
cargo build --release
```
The binary will be available at `target/release/mcps`.
## Usage
Once you have built the tool, you can use it by providing a project schedule
file in YAML or JSON format.
### Basic Usage
```bash
./mcps example.yaml -i 100000 -w 10
```
This command runs the Monte Carlo simulation on the example.yaml schedule file
with 100,000 iterations and overrides the number of workers to 10.
### Command-Line Options
- `-i, --iterations <iterations>`: Specify the number of iterations to run. Must be at least 100. Default is 50,000.
- `-w, --workers <num_workers>`: Override the number of workers specified in the schedule file.
- `-v, --version`: Print version information.
- `-h, --help`: Print help information.
### Schedule File Format
The tool accepts schedule files in YAML or JSON format. Below is an example of the YAML format:
```yaml
num_workers: 5 # for the purpose of scheduling simulation
estimate_confidence: 0.80 # confidence actuals will fall inside estimate bounds
tasks:
- id: DesignPhase
min_time: 1.5 # 1.5 days
max_time: 3.5 # 3.5 days
dependencies: []
- id: ImplementationPhase
min_time: 2.25 # 2.25 days
max_time: 4.75 # 4.75 days
dependencies: [DesignPhase]
```
### Example Output
The tool generates an ASCII-based cumulative distribution function (CDF) graph,
which visually represents the distribution of project durations and effort:
![example output of mcps](./assets/output.png)
## Project Details
### Contributing
Contributions are welcome! If you'd like to contribute, please fork the
repository and make changes as you'd like. Pull requests are warmly welcomed.
### Issues
If you encounter any issues with the tool, feel free to open an issue on the repository.
### Acknowledgments
This tool was developed by Stephen Waits. Contributions and suggestions are
always welcome!
### License
This project is licensed under the MIT License. See the LICENSE file for details.
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