spark-instrumented-optimizer/python/pyspark/cloudpickle/__init__.py
HyukjinKwon d6322bf70c [SPARK-33983][PYTHON] Update cloudpickle to v1.6.0
### What changes were proposed in this pull request?

This PR proposes to upgrade cloudpickle from 1.5.0 to 1.6.0.
It virtually contains one fix:

4510be850d

From a cursory look, this isn't a regression, and not even properly supported in Python:

```python
>>> import pickle
>>> pickle.dumps({}.keys())
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: cannot pickle 'dict_keys' object
```

So it seems fine not to backport.

### Why are the changes needed?

To leverage bug fixes from the cloudpickle upstream.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Jenkins build and GitHub actions build will test it out.

Closes #31007 from HyukjinKwon/cloudpickle-upgrade.

Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-04 10:36:31 -08:00

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Python

from __future__ import absolute_import
from pyspark.cloudpickle.cloudpickle import * # noqa
from pyspark.cloudpickle.cloudpickle_fast import CloudPickler, dumps, dump # noqa
# Conform to the convention used by python serialization libraries, which
# expose their Pickler subclass at top-level under the "Pickler" name.
Pickler = CloudPickler
__version__ = '1.6.0'