While working on https://github.com/pybind/pybind11/pull/4674 I came to realize that this include is not needed here.

Note however that the pybind11/cast.h changes under https://github.com/pybind/pybind11/pull/4601 are still needed, therefore pybind11_abseil still requires current pybind11 master.

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Make `absl::Time` from-python conversion (almost) identical to a Google-internal implementation under absl/python.

Note that the unit tests are unchanged (in the entire Google codebase).

The remaining very subtle differences between `type_caster<absl::Time>::load()` and the corresponding from-python conversion under absl/python are related to the pybind11 two-pass overload resolution feature that does not exist in PyCLIF.

As a side-effect, this change removes long-obsolete remnants of Python 2 support.

PiperOrigin-RevId: 529457660

Add support for `absl::InfiniteFuture`, `absl::InfinitePast`, matching established Google-internal conventions under absl/python.

Also replace floating-point arithmetic in the handling of microseconds with integer arithmetic, to sidestep subtle round-off issues. See the source code comment in the new `internal::GetTimestampMicrosFromDateTimeObj()` function for details.

PiperOrigin-RevId: 529169464

This conversion muddles the concepts of

* a particular point of time in a day, **independent of a particular date**, and

* a particular date + time.

This conversion was added only recently, but after more consideration, that was a mistake.

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For compatibility with Google-internal Clif_PyObjAs/From implementations.

This is to support the PyCLIF-pybind11 integration.

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Civil Time Unit conversions compatibility between pybind11_abseil & Google-internal Clif_PyObjAs/From implementations.

This is to support the PyCLIF-pybind11 integration.

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The file doesn't exist, and using the exported target causes downstream errors.

For one, TensorFlow's license checker errors on these non-existing LICENSE files

PiperOrigin-RevId: 500257122

This change replaces references to a number of deprecated NumPy type aliases (np.bool, np.int, np.float, np.complex, np.object, np.str) with their recommended replacement (bool, int, float, complex, object, str).

NumPy 1.24 drops the deprecated aliases, so we must remove uses before updating NumPy.

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To enable (limited) testing of `@pybind11_abseil:status` without the `@pybind11_abseil/tests:status_example_test` dependency.

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This change supports the PyCLIF-pybind11 integration.

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This change supports the PyCLIF-pybind11 integration.

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For interoperability with other Python binding systems (e.g. SWIG).

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Current motivation: Testing after https://github.com/pybind/pybind11_bazel/pull/46 was merged.

Convert pybind11_bazel dependency to FLOATING (we own it).

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Preparation for enabling presubmit UBSAN testing.

UBSAN error fixed by this CL:

```
SUMMARY: UndefinedBehaviorSanitizer: nullptr-with-nonzero-offset third_party/pybind11_abseil/tests/status_example.cc:111:66 in
```
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Make pybind11_abseil `StatusNotOk.__str__` compatible with long-established Google-internal behavior.

For example:

* Old: `INTERNAL: GetMemoryInfo error`
* New: `GetMemoryInfo error [INTERNAL]`

This behavior change is likely to only affect asserts in test code.

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Changes behavior of code introduced with https://github.com/pybind/pybind11_abseil/commit/4b5def2c2cdb16e9e099ed521acb03445cf44c3f on May 31, 2022, motivated by Google-internal developments.

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Before this change, `__repr__` is identical to `__str__`. There are countless articles on the web explaining the expected difference, for example:

* https://www.tutorialspoint.com/str-vs-repr-in-python

Quoting "Key differences":

* str(): Make object readable; Generate output to end user
* repr(): Required code that reproduces object; Generate output for developer

"Required code that reproduces object" is impractical for `Status`, mainly because there is not good way to concisely include the payload, but even just the `.message()` can potentially be very long. Therefore it is best to simply use the default `__repr__`, as is the case for the vast majority of types of significant complexity.

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