Coming back to this older thread, I have opened a PR with a proof of concept of the proposed protocol to convert third-party array objects to arrow: https://github.com/apache/arrow/pull/5106 In the tests, I added the protocol to pandas' nullable integer array (which is currently not supported in the from_pandas conversion) and this converts now nicely without much changes.
Are there remaining concerns about such a protocol? -- Note that the protocol is only for pandas -> arrow conversion (or other array-like objects -> arrow). The other way around (arrow -> pandas) is more complex and needs further discussion, and also involves the Arrow ExtensionTypes (as mentioned below by Wes). But I think the protocol will be useful in any case, and we can go ahead with that already (for example, not all pandas ExtensionArrays will need to map to a Arrow ExtensionType, eg the nullable integers simply map to arrow's int64 or fletcher's ExtensionArrays which just wrap a arrow array). That said, I have been working on the arrow ExtensionTypes the last days, and have been keeping an overview of the issues and needed work in this google document: https://docs.google.com/document/d/1pr9PuBfXTdlUoAgyh9zPIKDJZalDLI6GuxqblMynMM8/edit?usp=sharing (feel free to comment on it). There is also an initial PR to extend the support for defining ExtensionTypes in Python (ARROW-5610 <https://issues.apache.org/jira/browse/ARROW-5610>, https://github.com/apache/arrow/pull/5094). Joris On Fri, 17 May 2019 at 00:28, Wes McKinney <[email protected]> wrote: > hi Joris, > > Somewhat related to this, I want to also point out that we have C++ > extension types [1]. As part of this, it would also be good to define > and document a public API for users to create ExtensionArray > subclasses that can be serialized and deserialized using this > machinery. > > As a motivating example, suppose that a Java application has a special > data type that can be serialized as a Binary value in Arrow, and we > want to be able to receive this special object as a pandas > ExtensionArray column, which unboxing into a Python user space type. > > The ExtensionType can be implemented in Java, and then on the Python > side the implementation can occur either in C++ or Python. An API will > need to be defined to serializer functions for the pandas > ExtensionArray to map the pandas-space type onto the the Arrow-space > type. Does this seem like a project you might be able to help drive > forward? As a matter of sequencing, we do not yet have the capability > to interact with C++ ExtensionType in Python, so we might need to > first create callback machinery to enable Arrow extension types to be > defined in Python (that call into the C++ ExtensionType registry) > > - Wes > > [1]: > https://github.com/apache/arrow/blob/master/cpp/src/arrow/extension_type-test.cc > > On Fri, May 10, 2019 at 2:11 AM Joris Van den Bossche > <[email protected]> wrote: > > > > Op do 9 mei 2019 om 21:38 schreef Uwe L. Korn <[email protected]>: > > > > > +1 to the idea of adding a protocol to let other objects define their > way > > > to Arrow structures. For pandas.Series I would expect that they return > an > > > Arrow Column. > > > > > > For the Arrow->pandas conversion I have a bit mixed feelings. In the > > > normal Fletcher case I would expect that we don't convert anything as > we > > > represent anything from Arrow with it. > > > > > > Yes, you don't want to convert anything (apart from wrapping the arrow > > array into a FletcherArray). But how does Table.to_pandas know that? > > Maybe it doesn't need to know that. And then you might write a function > in > > fletcher to convert a pyarrow Table to a pandas DataFrame with > > fletcher-backed columns. But if you want to have this roundtrip > > automatically, without the need that each project that defines an > > ExtensionArray and wants to interact with arrow (eg in GeoPandas as well) > > needs to have his own "arrow-table-to-pandas-dataframe" converter, > pyarrow > > needs to have some notion of how to convert back to a pandas > ExtensionArray. > > > > > > > For the case where we want to restore the exact pandas DataFrame we had > > > before this will become a bit more complicated as we either would need > to > > > have all third-party libraries to support Arrow via a hook as proposed > or > > > we also define some kind of other protocol on the pandas side to > > > reconstruct ExtensionArrays from Arrow data. > > > > > > > That last one is basically what I proposed in > > > https://github.com/pandas-dev/pandas/issues/20612/#issuecomment-489649556 > > > > Thanks Antoine and Uwe for the discussion! > > > > Joris >
