from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module. –

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module. –

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but

from A as a separate step). It can even be combined with a : to extract both diagonals from the two pages at the same time: julia> A[CartesianIndex.(axes(A, 1), axes(A, 2)), 1] 4-element Vector{Int64}: skipping as many elements as there are in a single column (5). Similarly, jumping between the two "pages" (in the third dimension) requires skipping 5*7 == 35 elements. The strides of this array is the – Interfaces for Julia packages are typically described using docstrings, README.md, static web pages, ... • Some developers choose not to export all symbols required to use their package/module, but