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apache / arrow / 6c6754aa5fb840466dfd618ca5b6ae7ca72ebbfa
commit6c6754aa5fb840466dfd618ca5b6ae7ca72ebbfa[log] [tgz]
authorSutou Kouhei <kou@clear-code.com>Mon Dec 09 06:23:46 2019 +0900
committerSutou Kouhei <kou@clear-code.com>Mon Dec 09 06:23:46 2019 +0900
tree6046215a351573d03b4f7beb428494e0a485f1e9
parent7102d7eeef60fd0fb4fb7b06ed092d63db961b15 [diff]
ARROW-6920: [Packaging] Build python 3.8 wheels

adds python3.8 wheels

as far as I can tell python3.8 isn't available for Conda yet (https://github.com/conda-forge/python-feedstock/pull/274), so that's will have to be added later

Closes #5685 from sjhewitt/arrow-6920 and squashes the following commits:

feac49470 <Sutou Kouhei> Add a TODO comment
908a39648 <Sutou Kouhei> Check Docker version for debug
43833a3da <Sutou Kouhei> Add Python 3.8 support to package metadata
f3f9bfad9 <Krisztián Szűcs> Install tensorflow for 32 bit unicode width py27
cd9ae83b1 <Sutou Kouhei> Install TensorFlow for Python 2.7 manually
5293f2bf7 <Sutou Kouhei> Pin base image and remove needless virtualenvs
344eecd71 <Sutou Kouhei> Use apache/arrow-dev again
99cad413d <Sutou Kouhei> Use the uploaded image
f0c8e6927 <Sutou Kouhei> Link to libpython only on Windows
260fa7930 <Sutou Kouhei> Add a missing empty line
52761b413 <Sutou Kouhei> libpython.so may not exist
5e5977eb3 <Sutou Kouhei> Don't link to other Python libraries on non Windows
e047d54d6 <Sutou Kouhei> Don't use local function
10dac6741 <Terence D. Honles> move plasma subprocesses to top level functions
da300ac20 <Sutou Kouhei> Don't use TTY
c4526d87f <Sutou Kouhei> Use more recent numpy
7ace0cb03 <Sutou Kouhei> Ensure using the latest image
655f88c45 <Sutou Kouhei> Use Azure Pipelines instead of Travis CI
2ef6213fc <Sutou Kouhei> Use "call conda.bat activate/deactivate"
1c8427ea4 <Sutou Kouhei> Use conda without call
99251eaba <Sutou Kouhei> Use "conda activate/deactivate"
f403b6fe3 <Sutou Kouhei> Use the latest multibuild
c81884017 <Sutou Kouhei> Remove m suffix
e9f14087f <Sutou Kouhei> Set up Python 3.8
2ab67322b <Simon Hewitt> ARROW-6920:  Build python 3.8 wheels

Lead-authored-by: Sutou Kouhei <kou@clear-code.com>
Co-authored-by: Terence D. Honles <terence@honles.com>
Co-authored-by: Krisztián Szűcs <szucs.krisztian@gmail.com>
Co-authored-by: Simon Hewitt <si@sjhewitt.co.uk>
Signed-off-by: Sutou Kouhei <kou@clear-code.com>
18 files changed
tree: 6046215a351573d03b4f7beb428494e0a485f1e9
  1. .github/
  2. c_glib/
  3. ci/
  4. cpp/
  5. csharp/
  6. dev/
  7. docs/
  8. format/
  9. go/
  10. integration/
  11. java/
  12. js/
  13. matlab/
  14. python/
  15. r/
  16. ruby/
  17. rust/
  18. testing
  19. .clang-format
  20. .clang-tidy
  21. .clang-tidy-ignore
  22. .dir-locals.el
  23. .dockerignore
  24. .env
  25. .gitattributes
  26. .gitignore
  27. .gitmodules
  28. .hadolint.yaml
  29. .pre-commit-config.yaml
  30. .readthedocs.yml
  31. appveyor.yml
  32. CHANGELOG.md
  33. cmake-format.py
  34. CODE_OF_CONDUCT.md
  35. CONTRIBUTING.md
  36. docker-compose.yml
  37. header
  38. LICENSE.txt
  39. Makefile.docker
  40. NOTICE.txt
  41. README.md
  42. run-cmake-format.py
README.md

Apache Arrow

Build Status Coverage Status Fuzzit Status License Twitter Follow

Powering In-Memory Analytics

Apache Arrow is a development platform for in-memory analytics. It contains a set of technologies that enable big data systems to process and move data fast.

Major components of the project include:

Arrow is an Apache Software Foundation project. Learn more at arrow.apache.org.

What's in the Arrow libraries?

The reference Arrow libraries contain a number of distinct software components:

  • Columnar vector and table-like containers (similar to data frames) supporting flat or nested types
  • Fast, language agnostic metadata messaging layer (using Google's Flatbuffers library)
  • Reference-counted off-heap buffer memory management, for zero-copy memory sharing and handling memory-mapped files
  • IO interfaces to local and remote filesystems
  • Self-describing binary wire formats (streaming and batch/file-like) for remote procedure calls (RPC) and interprocess communication (IPC)
  • Integration tests for verifying binary compatibility between the implementations (e.g. sending data from Java to C++)
  • Conversions to and from other in-memory data structures

How to Contribute

Please read our latest project contribution guide.

Getting involved

Even if you do not plan to contribute to Apache Arrow itself or Arrow integrations in other projects, we'd be happy to have you involved: