Welcome to MathLingua

MathLingua is a language for easily creating a collection of mathematical knowledge, including definitions, theorems, axioms, and conjectures, in a format designed to be easy and fun to read and write.

Existing languages such as Lean, Coq, and others require their users to have deep knowledge of their underlying frameworks (such as the Calculus of Constructions) to express mathematical statements directly in those frameworks.

The goal of MathLingua, on the other hand, is to allow one to express mathematical concepts in a higher level language that focuses on what a statement means instead of how it is represented in a logical framework.

MathLingua then handles the details of how to express a statement in an underlying logical framework.

This is similar to how mathematics is expressed in literature, where theorems and definitions are described in a higher level natural language. For example, the following illustrates how a Monoid is defined in MathLingua:

Defines: M := (X, *, e)
. 'X is \set'
. '* is \function:on{X, X}to{X}'
. 'X in X'
. [associativity]
  forAll: x, y, z
  where: 'x, y, z in X'
  then: 'x * (y * z) = (x * y) * z'
. [identity]
  forAll: x
  where: 'x in X'
  . 'e * x = x'
  . 'x * e = x'

Notice how the syntax of MathLingua allows one to think of a Monoid as a tuple of objects with certain properties. Contrast this with how a Monoid could be described in the Calculus of Constructions as a type consisting of fields of different types (corresponding to the components of the Monoid) and proofs of the various properties of those fields.

MathLingua’s approach allows one to describe what a Monoid is while, under the hood, MathLingua handles how to express a Monoid in a logical framework such as the Calculus of Constructions.

Note: MathLingua is still a work in progress and is in the early stages of development.

Relationship to Existing Languages

Simply put, MathLingua is not designed to replace existing languages. Instead, MathLingua is a way to more easily express mathematical knowledge that transpiles down to existing languages such as Lean. Mathematicians can then focus on what a mathematical statement means instead of how it is encoded in a logical framework.

Compared to existing languages such that Lean, Coq, and others, MathLingua can be viewed as a higher level language whereas those languages can be viewed as lower level languages.

That is, Lean can be thought of as a lower level language similar to assembly language in computer science whereas MathLingua can be viewed as a higher level language language such as C, C++, or Java.

Then, just as in computer science as one can express an algorithm in both assembly language and C, the meaning of the algorithm can be easier to understand when written in C, whereas how the algorithm is implemented in particular hardware is more clear in assembly language.

Similarly, lower level languages such as Lean allow one to express how a mathematical concept is expressed in the Calculus of Constructions, MathLingua, like C, helps makes the meaning of the concept more clear.

Lean, Coq, and others are great languages, but can have a steep learning curve and require one to view mathematical knowledge from a type theory perspective. MathLingua is designed to have a gradual learning curve that can be easily used by mathematicians.

Design Principles

MathLingua is being created with the following principles in mind:

  • MathLingua provides a way to express Mathematical concepts in a way that is familiar to mathematicians without having to know advanced type theory.
  • It is designed to have a gradual learning curve.
  • It is focused on being easy to read and understand rather than expressing concepts with a small number of characters.
  • Metadata is a core feature. All concepts can have descriptions of the importance of the concept and how it relates to other concepts as well as links to related books, articles, and other documents.
  • Concepts are designed to be able to be read independently. You do not need to know what file a concept is defined in to understand it.
  • One does not need to express mathematical knowledge directly in an framework such as the calculus of constructions.
  • All types of concepts such as functions, sets, spaces, and others are represented consistently.

Note that these principles directly address some of the issues with existing languages and frameworks such as Lean, Coq, Metamath, and others that have a steep learning curve and multiple ways to express the same concept which can make it difficult to learn, understand, and grow mathematical knowledge expressed in those frameworks.

Non Goals

MathLingua is not intended to replace existing languages such as Lean, Coq, Metamath, or others. Instead, it is meant to be used with those languages by transpiling to them and using them as the underlying formal framework.


The following shows how to describe an even integer:

Defines: n
where: 'n is \integer'
. exists: k
  where: 'k is \integer'
  suchThat: 'n = 2*k'

A mathematical structure such as a group can be described as:

Defines: G := (X, *, e)
. 'X is \set'
. '* is \function:on{X, X}to{X}'
. 'e in X'
. forAll: x, y, z
  where: 'x, y, x in X'
  then: 'x * (y * z) = (x * y) * z'
. forAll: x
  where: 'x in X'
  . 'x * e = x'
  . 'e * x = x'
. forAll: x
  where: 'x in X'
  . exists: y
    where: 'y in X'
    . 'x * y = e'
    . 'y * x = e'

The following shows how to express Fermat’s Last Theorem:

given: n
. 'n is \integer'
. 'n > 2'
. not:
  . exists: x, y, z
    where: 'x, y, z is \integer'
    . 'x \neq 0'
    . 'y \neq 0'
    . 'z \neq 0'
    . 'x^n + y^n = z^n'

A piecewise defined function, such as the Heaviside function can be described as:

Defines: f(x)
where: 'f is \function:on{\reals}to{\reals}'
. piecewise:
  when: 'x < 0'
  then: 'f(x) := 0'
  when: 'x > 0'
  then: 'f(x) := 1'
  else: 'f(x) := 1/2'

The set of even integers can be expressed as:

Defines: X
where: 'X is \set'
. given: x
  where: 'x is \integer'
  all: 'x'
  suchThat: 'x is \even'


MathLingua started as a language for describing the structure of mathematical statements to build a database of knowledge where one could search for mathematical concepts based on their structure.

Since then, responding to valuable user feedback, MathLingua has moved to being a high level language to help formally define a collection of mathematical knowledge.

Currently, the MathLingua parser has been implemented in Kotlin, has unit and smoke tests, and does some AST validation. However, more validation work needs to be done. That is, parsing MathLingua source code into an AST for further processing is in good shape.

However, work has just started on taking that AST and transpiling it to lower level languages. The first target for such a transpilation is Lean.

Furthermore, since MathLingua initially started as a language for only describing the structure of mathematical statements, much work is still needed on developing the aspects of the language that allow proofs of theorems to be encoded in MathLingua.

The rough project roadmap is as follows:

  • Developing the infrastructure for transpiling MathLingua statements to Lean. This approach will use sorry for all proofs.
  • Allowing proofs for theorems to be directly encoded in an underlying language while the statement of the theorem is in MathLingua.
  • Developing the proof aspects of the MathLingua so that proves can be directly expressed in MathLingua.
  • Translating existing theorems encoded in the underlying language into MathLingua and ensuring the proves remain valid.

Note: MathLingua is a personal project that is being worked on in the author’s spare time.

Helping Out

If you would like to help out, reach out to DominicKramer@gmail.com or open a pull request at https://github.com/DominicKramer/mathlingua.

Assistance in trying the language, testing and exploring the best ways to express MathLingua code in Lean, and writing documentation are some ways to help, but any feedback or help is greatly appreciated.

About the Author

MathLingua is being developed by Dr. Dominic Kramer a mathematician, computer scientist, and senior software engineer. Dominic received his PhD in pure mathematics from Iowa State University and his research interests include the intersection of mathematics and computer science, in particular the foundations of mathematics, type theory, and language design.

He is particularly interested in how the design and structure of languages assists in the development of concepts in those languages and the tradeoffs needed to make a language powerful yet easy to learn and master.

Dominic has industry experience in the useage of type systems in huge software projects and deeply enjoys not just the beauty of mathematics, but helping others learn explore and discover mathematics.

He hopes MathLingua will help many more people learn and discover this beauty of mathematics.