diff --git a/docs/make.jl b/docs/make.jl
index d6774c32f6..c0ebaad576 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -29,6 +29,7 @@ makedocs(
             "tutorials/implementing.md",
             "tutorials/mathprogbase.md",
             "tutorials/bridging_constraint.md",
+            "tutorials/manipulating_expressions.md",
         ],
         "Manual" => [
             "manual/standard_form.md",
diff --git a/docs/src/submodules/Utilities/reference.md b/docs/src/submodules/Utilities/reference.md
index 25054cc243..e2d64d0b83 100644
--- a/docs/src/submodules/Utilities/reference.md
+++ b/docs/src/submodules/Utilities/reference.md
@@ -157,6 +157,8 @@ The following functions can be used to manipulate functions with basic algebra:
 
 ```@docs
 Utilities.scalar_type
+Utilities.scalarize
+Utilities.eachscalar
 Utilities.promote_operation
 Utilities.operate
 Utilities.operate!
diff --git a/docs/src/tutorials/manipulating_expressions.md b/docs/src/tutorials/manipulating_expressions.md
new file mode 100644
index 0000000000..3efe0abbc2
--- /dev/null
+++ b/docs/src/tutorials/manipulating_expressions.md
@@ -0,0 +1,142 @@
+```@meta
+CurrentModule = MathOptInterface
+DocTestSetup = quote
+    using MathOptInterface
+    const MOI = MathOptInterface
+end
+DocTestFilters = [r"MathOptInterface|MOI"]
+```
+
+# Manipulating expressions
+
+This guide highlights a syntactically appealing way to build expressions at the
+MOI level, but also to look at their contents. It may be especially useful
+when writing models or bridge code.
+
+## Creating functions
+
+This section details the ways to create functions with MathOptInterface.
+
+### Creating scalar affine functions
+
+The simplest scalar function is simply a variable: 
+
+```jldoctest expr; setup=:(model = MOI.Utilities.CachingOptimizer(MOI.Utilities.Model{Float64}(), MOI.Utilities.AUTOMATIC); )
+julia> x = MOI.add_variable(model) # Create the variable x
+MathOptInterface.VariableIndex(1)
+julia> f1 = MOI.SingleVariable(x) # A function with the single variable x
+MathOptInterface.SingleVariable(MathOptInterface.VariableIndex(1))
+```
+
+This type of function is extremely simple; to express more complex functions, 
+other types must be used. For instance, a [`ScalarAffineFunction`](@ref) is a
+sum of linear terms (a factor times a variable) and a constant. Such an object
+can be built using the standard constructor: 
+
+```jldoctest expr
+julia> f2 = MOI.ScalarAffineFunction([MOI.ScalarAffineTerm(1, x)], 2) # x + 2
+MathOptInterface.ScalarAffineFunction{Int64}(MathOptInterface.ScalarAffineTerm{Int64}[ScalarAffineTerm{Int64}(1, VariableIndex(1))], 2)
+```
+
+However, you can also use operators to build the same scalar function: 
+
+```jldoctest expr
+julia> f2 = MOI.SingleVariable(x) + 2 # x + 2
+MathOptInterface.ScalarAffineFunction{Int64}(MathOptInterface.ScalarAffineTerm{Int64}[ScalarAffineTerm{Int64}(1, VariableIndex(1))], 2)
+```
+
+### Creating scalar quadratic functions
+
+Scalar quadratic functions are stored in [`ScalarQuadraticFunction`](@ref) 
+objects, in a way that is highly similar to scalar affine functions. You can
+obtain a quadratic function as a product of affine functions: 
+
+```jldoctest expr
+julia> f3 = 1 * MOI.SingleVariable(x) * MOI.SingleVariable(x) # x²
+MathOptInterface.ScalarQuadraticFunction{Int64}(MathOptInterface.ScalarQuadraticTerm{Int64}[ScalarQuadraticTerm{Int64}(2, VariableIndex(1), VariableIndex(1))], MathOptInterface.ScalarAffineTerm{Int64}[], 0)
+julia> f4 = f2 * f2 # (x + 2)²
+MathOptInterface.ScalarQuadraticFunction{Int64}(MathOptInterface.ScalarQuadraticTerm{Int64}[ScalarQuadraticTerm{Int64}(2, VariableIndex(1), VariableIndex(1))], MathOptInterface.ScalarAffineTerm{Int64}[ScalarAffineTerm{Int64}(2, VariableIndex(1)), ScalarAffineTerm{Int64}(2, VariableIndex(1))], 4)
+julia> f4 = f2^2 # (x + 2)² too
+MathOptInterface.ScalarQuadraticFunction{Int64}(MathOptInterface.ScalarQuadraticTerm{Int64}[ScalarQuadraticTerm{Int64}(2, VariableIndex(1), VariableIndex(1))], MathOptInterface.ScalarAffineTerm{Int64}[ScalarAffineTerm{Int64}(2, VariableIndex(1)), ScalarAffineTerm{Int64}(2, VariableIndex(1))], 4)
+```
+
+### Creating vector functions
+
+A vector function is a function with several values, irrespective of the number
+of input variables. Similarly to scalar functions, there are three main types 
+of vector functions: [`VectorOfVariables`](@ref), 
+[`VectorAffineFunction`](@ref), and [`VectorQuadraticFunction`](@ref).
+
+The easiest way to create a vector function is to stack several scalar
+functions using [`Utilities.vectorize`](@ref). It takes a vector as input,
+and the generated vector function (of the most appropriate type) has each 
+dimension corresponding to a dimension of the vector.
+
+```jldoctest expr
+julia> f5 = MOI.Utilities.vectorize([f2, 2 * f2])
+MathOptInterface.VectorAffineFunction{Int64}(MathOptInterface.VectorAffineTerm{Int64}[VectorAffineTerm{Int64}(1, ScalarAffineTerm{Int64}(1, VariableIndex(1))), VectorAffineTerm{Int64}(2, ScalarAffineTerm{Int64}(2, VariableIndex(1)))], [2, 4])
+```
+
+!!! warning
+    [`Utilities.vectorize`](@ref) only takes a vector of similar scalar 
+    functions: you cannot mix [`SingleVariable`](@ref) and 
+    [`ScalarAffineFunction`](@ref), for instance. In practice, it means that 
+    `Utilities.vectorize([f1, f2])` does not work; you should rather use 
+    `Utilities.vectorize([1 * f1, f2])` instead to only have 
+    [`ScalarAffineFunction`](@ref) objects.
+
+## Canonicalizing functions
+
+In more advanced use cases, you might need to ensure that a function is 
+"canonical". Functions are stored as an array of terms, but there is no check
+that these terms are redundant: a [`ScalarAffineFunction`](@ref) object might
+have two terms with the same variable, like `x + x + 1`. These terms could be
+merged without changing the semantics of the function: `2x + 1`. 
+
+Working with these objects might be cumbersome. Canonicalization helps maintain 
+redundancy to zero. 
+
+[`Utilities.is_canonical`](@ref) checks whether a function is already in its 
+canonical form:
+
+```jldoctest expr
+julia> MOI.Utilities.is_canonical(f2 + f2) # (x + 2) + (x + 2) is stored as x + x + 4
+false
+```
+
+[`Utilities.canonical`](@ref) returns the equivalent canonical version of the 
+function:
+
+```jldoctest expr
+julia> MOI.Utilities.canonical(f2 + f2) # Returns 2x + 4
+MathOptInterface.ScalarAffineFunction{Int64}(MathOptInterface.ScalarAffineTerm{Int64}[ScalarAffineTerm{Int64}(2, VariableIndex(1))], 4)
+```
+
+## Exploring functions
+
+At some point, you might need to dig into a function, for instance to map it 
+into solver constructs.
+
+### Vector functions
+
+[`Utilities.scalarize`](@ref) returns a vector of scalar functions from a
+vector function:
+
+```jldoctest expr
+julia> MOI.Utilities.scalarize(f5) # Returns a vector [f2, 2 * f2].
+2-element Array{MathOptInterface.ScalarAffineFunction{Int64},1}:
+ MathOptInterface.ScalarAffineFunction{Int64}(MathOptInterface.ScalarAffineTerm{Int64}[ScalarAffineTerm{Int64}(1, VariableIndex(1))], 2)
+ MathOptInterface.ScalarAffineFunction{Int64}(MathOptInterface.ScalarAffineTerm{Int64}[ScalarAffineTerm{Int64}(2, VariableIndex(1))], 4)
+```
+
+!!! note
+    [`Utilities.eachscalar`](@ref) returns an iterator on the dimensions, which
+    serves the same purpose as [`Utilities.scalarize`](@ref).
+
+[`output_dimension`](@ref) returns the number of dimensions of the 
+output of a function:
+
+```jldoctest expr
+julia> MOI.output_dimension(f5)
+2
+```
diff --git a/src/Utilities/functions.jl b/src/Utilities/functions.jl
index a3f63d0ab2..8d9bf8f880 100644
--- a/src/Utilities/functions.jl
+++ b/src/Utilities/functions.jl
@@ -492,7 +492,20 @@ function ScalarFunctionIterator(f::MOI.VectorQuadraticFunction)
     )
 end
 
+"""
+    eachscalar(f::MOI.AbstractVectorFunction)
+
+Returns an iterator for the scalar components of the vector function.
+
+See also [`scalarize`](@ref).
+"""
 eachscalar(f::MOI.AbstractVectorFunction) = ScalarFunctionIterator(f)
+
+"""
+    eachscalar(f::MOI.AbstractVector)
+
+Returns an iterator for the scalar components of the vector.
+"""
 eachscalar(f::AbstractVector) = f
 
 function Base.iterate(it::ScalarFunctionIterator, state = 1)
@@ -3067,12 +3080,26 @@ function operate(
     return MOI.VectorQuadraticFunction(quadratic_terms, affine_terms, constant)
 end
 
-# Similar to `eachscalar` but faster, see
-# https://github.com/jump-dev/MathOptInterface.jl/issues/418
+"""
+    scalarize(func::MOI.VectorOfVariables, ignore_constants::Bool = false)
+
+Returns a vector of scalar functions making up the vector function in the form
+of a `Vector{MOI.SingleVariable}`.
+
+See also [`eachscalar`](@ref).
+"""
 function scalarize(f::MOI.VectorOfVariables, ignore_constants::Bool = false)
     return MOI.SingleVariable.(f.variables)
 end
 
+"""
+    scalarize(func::MOI.VectorAffineFunction{T}, ignore_constants::Bool = false)
+
+Returns a vector of scalar functions making up the vector function in the form
+of a `Vector{MOI.ScalarAffineFunction{T}}`.
+
+See also [`eachscalar`](@ref).
+"""
 function scalarize(
     f::MOI.VectorAffineFunction{T},
     ignore_constants::Bool = false,
@@ -3092,6 +3119,14 @@ function scalarize(
     return functions
 end
 
+"""
+    scalarize(func::MOI.VectorQuadraticFunction{T}, ignore_constants::Bool = false)
+
+Returns a vector of scalar functions making up the vector function in the form
+of a `Vector{MOI.ScalarQuadraticFunction{T}}`.
+
+See also [`eachscalar`](@ref).
+"""
 function scalarize(
     f::MOI.VectorQuadraticFunction{T},
     ignore_constants::Bool = false,