Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

FIx intro to manual chapter on types #26312

Merged
merged 1 commit into from
Mar 3, 2018
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
7 changes: 4 additions & 3 deletions doc/src/manual/types.md
Original file line number Diff line number Diff line change
Expand Up @@ -16,10 +16,11 @@ of function arguments to be deeply integrated with the language. Method dispatch
detail in [Methods](@ref), but is rooted in the type system presented here.

The default behavior in Julia when types are omitted is to allow values to be of any type. Thus,
one can write many useful Julia programs without ever explicitly using types. When additional
one can write many useful Julia functions without ever explicitly using types. When additional
expressiveness is needed, however, it is easy to gradually introduce explicit type annotations
into previously "untyped" code. Doing so will typically increase both the performance and robustness
of these systems, and perhaps somewhat counterintuitively, often significantly simplify them.
into previously "untyped" code. Adding annotations serves three primary purposes: to take advantage
of Julia's powerful multiple-dispatch mechanism, to improve human readability, and to catch
programmer errors.

Describing Julia in the lingo of [type systems](https://en.wikipedia.org/wiki/Type_system), it
is: dynamic, nominative and parametric. Generic types can be parameterized, and the hierarchical
Expand Down