Open Source F# Frameworks for Mac

Cross platform Neovim front-end UI, built with F# + Avalonia. Download the latest release package for your system, extract and run FVim! For Windows 7 / Vista / 8.1 / Server 2008 R2 / Server 2012 R2, use the win7-x64 package. For Windows 10, use the win-x64 package -- this version has faster startup. For macOS, it's packaged as an app bundle, unzip and drag it to your applications folder. Use a Windows FVim frontend with a WSL neovim: fvim, wsl. Multi-grid support, try Ctrl-w ge to detach a window into a separate OS window!

With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that automates the process of building best performing models for your Machine Learning scenario. All you have to do is load your data, and AutoML takes care of the rest of the model building process. ML.NET has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer.NET, and more) and have access to even more machine learning scenarios, like image classification, object detection, and more.

Capstone is a disassembly framework with the target of becoming the ultimate disasm engine for binary analysis and reversing in the security community. Created by Nguyen Anh Quynh, then developed and maintained by a small community, Capstone offers some unparalleled features. Support multiple hardware architectures: ARM, ARM64 (ARMv8), Ethereum VM, M68K, Mips, MOS65XX, PPC, Sparc, SystemZ, TMS320C64X, M680X, XCore and X86 (including X86_64). Having clean/simple/lightweight/intuitive architecture-neutral API. Provide details on disassembled instruction (called “decomposer” by others). Provide semantics of the disassembled instruction, such as list of implicit registers read & written. Implemented in pure C language, with lightweight bindings for D, Clojure, F#, Common Lisp, Visual Basic, PHP, PowerShell, Emacs, Haskell, Perl, Python, Ruby, C#, NodeJS, Java, GO, C++, OCaml, Lua, Rust, Delphi, Free Pascal & Vala (ready either in main code, or provided externally by the community).

.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks.

A functional ASP.NET Core micro web framework for building rich web applications. Giraffe is an F# micro web framework for building rich web applications. It has been heavily inspired and is similar to Suave, but has been specifically designed with ASP.NET Core in mind and can be plugged into the ASP.NET Core pipeline via middleware. Giraffe applications are composed of so called HttpHandler functions which can be thought of a mixture of Suave's WebParts and ASP.NET Core's middleware. Giraffe is intended for developers who want to build rich web applications on top of ASP.NET Core in a functional first approach. ASP.NET Core is a powerful web platform which has support by Microsoft and a huge developer community behind it and Giraffe is aimed at F# developers who want to benefit from that eco system.