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What is Haskell?

In Haskell, every expression has a type that is determined at compile time. It is essential for the types in function applications to match correctly; if they do not, the compiler will reject the code. This rigorous type system not only ensures correctness but also acts as a framework for defining program structure. Each function in Haskell operates under the principles of mathematical functions, which makes them fundamentally "pure." Even in the case of side-effecting IO operations, these are merely specifications of actions to be executed, produced by pure functions. Haskell avoids the use of statements or commands; it focuses instead on expressions that cannot change variables—either local or global—and cannot alter states like time or randomness. Although it is not mandatory to specify every type within a Haskell program, types can be inferred through a process known as bidirectional unification. Programmers also have the freedom to explicitly declare types when necessary or to ask the compiler to provide them for clarity, thus improving documentation. This level of flexibility empowers Haskell developers to maintain a balance between type safety and user-friendliness while fostering an environment conducive to robust software development. Overall, Haskell's design encourages clarity and precision in programming practices.

What is AMPL?

AMPL is a powerful and intuitive modeling language crafted for articulating and solving complex optimization problems. It empowers users to formulate mathematical models with a syntax akin to algebraic expressions, which facilitates a clear and efficient representation of variables, objectives, and constraints. The language supports a wide array of problem types, encompassing linear programming, nonlinear programming, and mixed-integer programming, among others. One of AMPL's notable strengths lies in its ability to separate models from data, offering both flexibility and scalability for large-scale optimization challenges. Moreover, the platform seamlessly integrates with various solvers, including both commercial and open-source options, allowing users to choose the most appropriate solver for their specific needs. In addition, AMPL is compatible with several operating systems, such as Windows, macOS, and Linux, and offers a variety of licensing options to meet diverse user requirements. This adaptability and user-centric design render AMPL an outstanding option for both individuals and organizations engaged in tackling sophisticated optimization tasks. Its extensive features and capabilities ensure that users are well-equipped to handle a broad spectrum of optimization scenarios.

Media

Media

Integrations Supported

Apache NetBeans
AskCodi
CodePal
CodeRunner
CodeSession
Cody
Echidna
FreeBSD
Helix Editor
Lapce
PaizaCloud
Python
RunCode
Sonatype Nexus Repository
Sublime Text
SwapCode AI
TextMate
WebTranslateIt.com
jEdit

Integrations Supported

Apache NetBeans
AskCodi
CodePal
CodeRunner
CodeSession
Cody
Echidna
FreeBSD
Helix Editor
Lapce
PaizaCloud
Python
RunCode
Sonatype Nexus Repository
Sublime Text
SwapCode AI
TextMate
WebTranslateIt.com
jEdit

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

$3,000 per year
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Haskell

Company Website

www.haskell.org

Company Facts

Organization Name

AMPL

Date Founded

2002

Company Location

United States

Company Website

ampl.com/products/ampl/

Categories and Features

Categories and Features

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