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Diff for: web/pandas/pdeps/0010-required-pyarrow-dependency.md

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# PDEP-10: PyArrow as a required dependency for default string inference implementation
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- Created: 17 April 2023 (updated May 8, 2024)
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- Status: Rejected
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- Created: 17 April 2023
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- Status: Accepted
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- Discussion: [#52711](https://github.com/pandas-dev/pandas/pull/52711)
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[#52509](https://github.com/pandas-dev/pandas/issues/52509)
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- Author: [Matthew Roeschke](https://github.com/mroeschke)
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[Patrick Hoefler](https://github.com/phofl)
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- Revision: 2
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- Revision: 1
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# Note
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This PDEP was originally accepted on May 8, 2023. However, after reviewing feedback posted
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on the feedback issue [#54466](https://github.com/pandas-dev/pandas/issues/54466), we, the members of
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the core team, have not decided with moving forward with this PDEP for pandas 3.0.
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The primary reasons for rejecting this PDEP are twofold:
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1) Requiring pyarrow as a dependency causes installation problems.
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- Pyarrow does not fit or has a hard time fitting in space-constrained environments
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such as AWS Lambda and WASM, due to its large size of around ~40 MB for a compiled wheel
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(which is larger than pandas' own wheel sizes)
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- Installation of pyarrow is not possible on some platforms. We provide support for some
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less widely used platforms such as Alpine Linux (and there is third party support for pandas in
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pyodide, a WASM distribution of pandas), both of which pyarrow does not provide wheels for.
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While both of these reasons are mentioned in the drawbacks section of this PDEP, at the time of the writing
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of the PDEP, we underestimated the impact this would have on users, and also downstream developers.
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2) Many of the benefits presented in this PDEP can be materialized even with payrrow as an optional dependency.
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For example, as detailed in PDEP-14, it is possible to create a new string data type with the same semantics
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as our current default object string data type, but that allows users to experience faster performance and memory savings
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compared to the object strings.
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While we've decided to not move forward with requiring pyarrow in pandas 3.0, the rejection of this PDEP
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does not mean that we are abandoning pyarrow support and integration in pandas. We, as the core team, still believe
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that adopting support for pyarrow arrays and data types in more of pandas will lead to greater interoperability with the
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ecosystem and better performance for users. Furthermore, a lot of the drawbacks, such as the large installation size of pyarrow
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and the lack of support for certain platforms, can be solved, and potential solutions have been proposed for them, allowing us
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to potentially revisit this decision in the future.
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However, at this point in time, it is clear that we are not ready to require pyarrow
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as a dependency in pandas.
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This PDEP is superseded by PDEP-15.
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## Abstract
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