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kfl/mosml

Moscow ML is a light-weight implementation of Standard ML (SML), a strict functional language widely used in teaching and research.

Standard ML ◇ compiler
★407STARS
⑂46FORKS
!49ISSUES
🏆#6,015GLOBAL RANK
🔥48DAYS TRENDING
🚀
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Momentum

+10

STARS · LAST 30 DAYS

1

PER DAY

#2

MOST-STARRED Standard ML

Window7 days30 days90 days
Stars gained+7+10+90
Per day111
Forks gained+1+3+10

mosml gained 10 stars in the last 30 days, about 1 a day, and now has 407. It is about 17 years old and has averaged roughly 24 stars a year. It ranks #2 among Standard ML repositories and #6,015 across all languages on GitHubRepo.

Trending Record

mosml has maintained a continuous presence across global trending indexes, peaking at #100. Below is the 30-day activity profile:

💡 Overview

mosml is an open-source project written in Standard ML: Moscow ML is a light-weight implementation of Standard ML (SML), a strict functional language widely used in teaching and research.

Engineered for speed, consistency, and developer ease, it solves common hurdles in compiler, programming-language, standard-ml. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Standard ML for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ git clone https://github.com/kfl/mosml.git
cd mosml

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Standard ML environment and standard tooling

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

mosml coordinates its core functionality through a modular Standard ML pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Production System Integration

Embed mosml into Standard ML backend services to handle core application logic.

CI/CD Automated Pipelines

Run automated validation, builds, and integration suites during deployments.

Developer Tooling & Workflows

Accelerate developer onboarding with pre-configured project utilities.

Open Source Extension

Fork and customize internal modules under the repository's open source license.

🚀 Getting Started

1

Install mosml using your package manager: `git clone https://github.com/kfl/mosml.git`

2

Initialize your project workspace or configuration file for mosml.

3

Import mosml into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `mosml --help` to verify successful setup.

👍 Strengths

Active community backing with 407 GitHub stars and verified adoption.
Permissive open-source distribution under the Open Source license.
Built in Standard ML for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Standard ML and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

G
GoldenCheetah/GoldenCheetah ★ 2.2K Standard ML

Performance Software for Cyclists, Runners, Triathletes and Coaches

Compare ↗

👥 Who Should Use This

Developers and engineering teams building with Standard ML, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

kfl/mosml is currently ranked #6,015 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#6,004 toastdriven/itty Python ★ 409 Compare ↗
#6,011 devops-works/binenv Go ★ 408 Compare ↗
#6,011 kubernetes-sigs/kubetest2 Go ★ 408 Compare ↗
#6,011 jgm/yst Haskell ★ 408 Compare ↗
#6,011 himmelblau-idm/himmelblau Rust ★ 408 Compare ↗
#6,015 kfl/mosml This Project Standard ML ★ 407
#6,015 Lyellr88/marm-memory Python ★ 407 Compare ↗
#6,015 technoweenie/acts_as_versioned Ruby ★ 407 Compare ↗
#6,015 github/auto-complete-element JavaScript ★ 407 Compare ↗
#6,015 yungifez/skuul PHP ★ 407 Compare ↗
#6,015 decocms/studio TypeScript ★ 407 Compare ↗

Frequently Asked Questions

What does mosml do? +

Moscow ML is a light-weight implementation of Standard ML (SML), a strict functional language widely used in teaching and research.

What language is mosml written in? +

The primary language is Standard ML. Topics include: compiler, programming-language, standard-ml.

Is mosml actively maintained? +

Yes, the last recorded push was on Jan 26, 2024 with 49 open issues being tracked.

How many stars does mosml have? +

mosml has 407 stars and 46 forks on GitHub.

How does mosml rank among GitHub repositories? +

With 407 stars, kfl/mosml is ranked #6,015 globally across all repositories tracked on GitHubRepo and #2 among Standard ML projects.

What license is mosml distributed under? +

No SPDX license identified yet. Code without a license is subject to copyright by default.

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