Bump numpy from 1.15.1 to 1.22.0

[dependabot]

Bumps numpy from 1.15.1 to 1.22.0.

Release notes

Sourced from numpy's releases.

v1.22.0

NumPy 1.22.0 Release Notes

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

• Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
• A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
• NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
• New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
• A new configurable allocator for use by downstream projects.

These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

Expired deprecations

Deprecated numeric style dtype strings have been removed

Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

(gh-19539)

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

(gh-19615)

... (truncated)

Commits

• 4adc87d Merge pull request #20685 from charris/prepare-for-1.22.0-release
• fd66547 REL: Prepare for the NumPy 1.22.0 release.
• 125304b wip
• c283859 Merge pull request #20682 from charris/backport-20416
• 5399c03 Merge pull request #20681 from charris/backport-20954
• f9c45f8 Merge pull request #20680 from charris/backport-20663
• 794b36f Update armccompiler.py
• d93b14e Update test_public_api.py
• 7662c07 Update init.py
• 311ab52 Update armccompiler.py
• Additional commits viewable in compare view

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[JonathanPorta]

PR Review

Summary

This PR bumps numpy in the prebuilt Lambda dependency bundle from 1.15.1 to 1.22.0. That target version is incompatible with this repo's declared build runtime: the Dockerfile builds Python 3.6, while NumPy 1.22 dropped Python 3.6/3.7 support.

Findings

• Severity: Blocking
• Location: prebuilt-requirements.txt and Dockerfile
• Problem: numpy==1.22.0 cannot be installed for the Python 3.6 Lambda build target used by this repo.
• Why it matters: The prebuilt artifact is assembled inside a Python 3.6 Lambda build image. With this pin, the Docker build/package path cannot resolve a compatible NumPy wheel, so the Lambda dependency bundle cannot be produced as configured.
• Suggested fix: Close this stale dependabot PR. If the project remains on Python 3.6, use a NumPy version that still supports cp36 and validate it with the full native stack. If the goal is to move to NumPy 1.22+, update the Lambda runtime/build image first and refresh SciPy/scikit-image/OpenCV together.

Test / Verification Notes

I inspected the PR diff, prebuilt-requirements.txt, Dockerfile, and the packaging Makefile. I ran a targeted runtime compatibility check: pip download --only-binary=:all: --platform manylinux2010_x86_64 --python-version 36 --implementation cp --abi cp36m 'numpy==1.22.0'. Pip reports no matching distribution and lists 1.19.5 as the newest available cp36-compatible NumPy in that query. I did not run the full Docker build because dependency resolution already fails for the repo's runtime target.

Overall Recommendation

Needs changes before merge.