ExpandingMan

either deprecate or silence warning?

1

Hello all. I am investigating using this package exclusively since my efforts to get the new one working have been thwarted by [this issue](https://github.com/ProtonVPN/linux-cli/issues/49). I am a little worried that...

Currently FileIO seems only to work with FeatherFiles, not this package. I'd like to figure out how to deal with that when I get a chance.

Somehow an alignment error gets thrown on 32-bit systems, as has been seen on appveyor. The error was thrown on an array of `Float64` so it seems to me that...

documentation update

1

I need to write the updated documentation for the package now that it has been completely reorganized with the Arrow back-end. Coming soon!

should `mmap=false` by default on Windows?

4

I was reading the CSV.jl [documentation](https://juliadata.github.io/CSV.jl/latest/#High-level-interface-1) today and I noticed that they give a possible explanation for why `mmap=false` by default on Windows. It actually seems like a surprisingly reasonable...

slower deserialization than in python

10

Here are some results on a 366MB dataframe with mixed types... ``` INFO: Opening feather with python... 3.100129 seconds (65.20 k allocations: 2.547 MB) INFO: Opening feather with julia... 5.888453...

how do we deal with `Int32` overflows?

16

I've been reading up on what happened over on the Python side to deal with arrays with length that excedes `typemax(Int32)`. This is a problem because Arrow specifies that all...

non `Int32` categorical references

2

This issue is to discuss how we deal with categorical references that are not `Int32`. This is a violation of the Arrow [standard](https://github.com/apache/arrow/blob/master/format/Layout.md) (this is not the only suspicious thing...

`InexactError` when Int64 offset value tries to convert to Int32

2

The error occurs [here](https://github.com/JuliaData/Feather.jl/blob/master/src/Feather.jl#L361) on dataframes with sufficiently large columns. The most obvious way to fix this would be to change all of the offsets to Int64, but does the...

I'm getting a few errors when doing `Data.stream!(src, snk)` where `snk = Feather.Sink("filename.feather", Data.schema(src))` and then calling `Data.close!`. There does not seem to be a simple fix. It is really...