Closed ExpandingMan closed 5 years ago
@quinnj , tests are failing because in the docker container Python segfaults when reading test2.feather
in the docker container. However, I read the same file in Python locally and it works perfectly fine. Is it possible that the Python feather
package or something else in the container needs updating? I can reproduce the segfault within the container, but only within the container. Anywhere else I read the test2.feather
file in either Julia or Python it works perfectly fine.
Much weirder: the test passes with no issues on Julia nightly on both linux and mac. That makes absolutely no sense to me whatsoever. Any idea what might be going on with that container?
This package is basically unusable for me now because it doesn't have this.
Anybody have any ideas what's going on in the docker? Is there anyway to trigger this again? I'm totally and completely stumped I was never able to reproduce the error anywhere.
Merging #115 into master will increase coverage by
10.1%
. The diff coverage is82.75%
.
@@ Coverage Diff @@
## master #115 +/- ##
==========================================
+ Coverage 67.33% 77.43% +10.1%
==========================================
Files 4 5 +1
Lines 150 164 +14
==========================================
+ Hits 101 127 +26
+ Misses 49 37 -12
Impacted Files | Coverage Δ | |
---|---|---|
src/Feather.jl | 100% <ø> (ø) |
|
src/sink.jl | 91.66% <100%> (+21.39%) |
:arrow_up: |
src/metadata.jl | 94.11% <100%> (-2.66%) |
:arrow_down: |
src/loaddata.jl | 78.26% <57.14%> (ø) |
|
src/source.jl | 61.42% <66.66%> (+6.58%) |
:arrow_up: |
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I'm in the process of updating this and also implementing better (but optional) round-trip python tests as discussed in #119.
Ok, I have removed all of the docker stuff completely. There is now an optional set of Python round-trip tests (the same as before). They can't run in travis because it will be missing dependencies, but anyone should have no trouble running them locally, one just needs pandas
, and pyarrow
. In the future if anyone can find a way to provision travis with this, those tests can be restored.
Note that the tests involving the Python byte array type have been removed. They were not working in master either. The reason this went unnoticed is because the error only seems to occur with updated pandas
and pyarrow
. We can fix this later (I still fully intend on finishing radically overhaulingg Arrow.jl, sorry I got stalled out for a while).
This should also work with the latest DataFrames.jl. I'd like to make another PR later to remove the DataFrames dependence entirely in favor of the Tables.jl interface only, but of course these will be breaking changes.
If anyone has any issues, please say so, otherwise I will merge this tomorrow.
I'm going to merge this today. Ideally we should tag this today as well, any objections?
Does anyone know if we have to do anything new with Registrator, or can we just tag?
I think tagging will not do anything.
I've had success:
@JuliaRegistrator register()
as a comment on the commitError while trying to register: Register Failed @sglyon, it looks like you are not a publicly listed member/owner in the parent organization (JuliaData). If you are a member/owner, you will need to change your membership to public. See GitHub Help
I took the liberty of bumping the version number to 0.5.2
in Project.toml
by committing directly to master.
@quinnj you may need to call the registrator as I am not a member of JuliaData.
Is this seriously completely decoupled from tagging now? I don't think I like that.
Is this seriously completely decoupled from tagging now? I don't think I like that.
You can install tagbot that will tag automatically for you or you can paste the git command that Registrator gives you to tag yourself.
That seems reasonable.
Still seems that Quinn needs to do this.
I kicked of JuliaRegistrator; I also made @ExpandingMan an admin on this repo; is that enough to allow him to call JuliaRegistrator? Anybody know?
According to the message that was given to @sglyon , I would need to be a member of JuliaData.
I guess you’ll just have to develop more awesome features quickly so you can tag again and test it out ;)
Fixes #113. This is especially useful for doing things like reading and writing to Amazon S3 or anything else over a network (previously one would have had to write to disk first).