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Reliafy CLI: FORM, SORM, RBDO, and Monte Carlo Simulation in Python

Reliafy CLI is a Python command-line tool for reliability analysis, reliability-based design optimization, and simulation workflows using profile-based configuration.

It supports First-Order Reliability Method (FORM), Second-Order Reliability Method (SORM), Inverse FORM, Inverse SORM, Reliability-Based Design Optimization (RBDO), Monte Carlo simulation, and Importance Sampling for rare-event probability estimation, with correlated and non-normal random-variable support via Nataf transformation.

Run outputs include reliability metrics and design points, tabulated summaries (Excel/JSON), plot reports (PDF), and pickled Matplotlib figure objects for post-processing.

The documentation is written for practical use. Method descriptions are intentionally concise, and method-specific references are consolidated in the Profile Options Reference.

New to CLI?

A CLI (command-line interface) is a way to run tools by typing commands in a terminal window.

Reliafy CLI uses this workflow because it reduces custom scripting for routine workflows, supports reproducible runs, and enables easy automation.

If you are new to terminal-based tools, start with CLI Basics for Reliafy Users for a short orientation and first-run checklist.

Pricing and Sustainability Notice

Reliafy CLI is free to use at this time. The CLI communicates with a hosted API, and the associated computation and infrastructure costs are currently funded by the developer during this early phase of operation.

To support ongoing maintenance and service delivery as usage grows, a monthly subscription of approximately $8/month is planned for a future release.

Any transition from free access to a paid subscription model will be communicated in advance. Existing users will receive clear notice before any pricing changes take effect.

Who This Tool Is For

Reliafy CLI was developed with academia in mind. The primary audience is students, instructors, and researchers working in risk and reliability, probabilistic failure analysis, and advanced probability and statistics.

Typical use cases include:

  • Courses on risk and reliability methods, structural reliability, probabilistic analysis of failure, and advanced probability and statistics.
  • Research at universities and research centers focused on reliability methods, failure analysis, code calibration and development, and related uncertainty-quantification workflows.

Recommended background readings are listed at Recommended Texts and References.

Core Workflows

Reliafy CLI provides five core reliability workflows:

Quick Start

  1. Install the CLI (and required dependencies) from PyPI:

    pip install reliafy

  2. View available commands:

    reliafy --help

  3. Copy example problems:

    reliafy examples cp

  4. Run an analysis with the default profile:

    reliafy analyze default --include-sorm --plot-rfad

Execution Model

Reliafy CLI runs computations through the hosted Reliafy API. The CLI handles local orchestration (profile loading, problem-file selection, command options, and local result saving), while the numerical reliability/design/simulation solve is executed on the API side.

Data handling and file retention

Reliafy does not retain uploaded problem modules or generated run files on the API side after a run completes. The backend uses secure deletion (srm) to remove submitted problem files and generated artifacts (such as Excel, PDF, and pickled Matplotlib files) after processing.

Main Commands

See CLI Command Overview for command behavior, usage patterns, and links to full option references for analyze, design, and simulate.

Configuration

Reliafy CLI uses YAML profile files to configure run parameters across analyze, design, and simulate, including reliability methods, plotting options (LSF/RFAD), and reporting outputs.

For profile workflows and command usage, see Profiles. For complete option keys and defaults, see Profile Options Reference.

Authentication

Reliafy CLI authenticates automatically the first time you run any command. If no valid token is found, you will be prompted to log in before the command proceeds.

For manual authentication and status checks, use reliafy user auth and reliafy user id. See Auth for full flow details and troubleshooting.

Requirements

  • Python 3.10+
  • Internet connection for API access and authentication

Getting Help

All commands support the --help flag for detailed usage information:

reliafy --help
reliafy analyze --help
reliafy profile --help

Software References

For third-party Python library citation guidance, see Software and Library References. That section separates:

  • CLI dependencies users install in their environment
  • API dependencies documented for attribution/credit only

Citing Reliafy

If you use Reliafy in journal papers, reports, theses, or other scholarly work, cite Reliafy itself. Additionally, cite the underlying reliability methods (FORM, SORM, Monte Carlo, etc.) based on relevant academic sources in your field.

Include the exact Reliafy version used in your work. For version-specific DOI citations, use the corresponding Zenodo release record.

Contact

For questions, feedback, or support, reach out at [email protected].