augray
augray
Right now when submitting k8s jobs, it happens from the clients (either from the resolver in detached mode, or from a user machine in non-detached mode). We should put this...
We already support this for lists: ``` @sematic.func def pipeline() -> typing.List[int]: return [foo(), bar()] ``` where `foo` and `bar` are Sematic funcs (thus returning futures). We should also support...
We should support abstract base classes as type annotations for sematic functions, but we currently do not.
You can hit weird cases that behave in unexpected ways when you try to compare futures: ``` @sematic.func def pipeline() -> str: if some_sematic_func() == 1: return "Yay!" else: return...
Ideally this would work: ```python @dataclass class Foo: foo: int @sematic.func def make_foo(i: int) -> Foo: return Foo(foo=i) @sematic.func def get_int(foo: Foo) -> int: return make_foo(42).foo ``` But it doesn't...
We should explain what's supported and what's not, as well as the functionality you get when using these types.
- Mention that installing postgres is a pre-req (actually that's true for "real" users as well) - description of how to run bazel tests - instructions on installing standard version...
Right now there's no way to tell in the UI who created a particular execution. We should add some capability to do that.
There are URLs that will take you to a pipeline, but not to an individual execution of one. When people are sharing executions with one another, they will likely want...
datetime is a common type in python that we should probably have a good visualization for