Log message:
py-jsonpickle: updated to 2.0.0

v2.0.0

Major release: the serialized JSON format now preserves dictionary identity, \ 
which is a subtle change in the serialized format.
Dictionary identity is now preserved. For example, if the same dictionary \ 
appears twice in a list, the reconstituted list will now contain two references \ 
to the same dictionary.

v1.5.2

Patch release to avoid the change in behavior from the preservation of dict \ 
identity. The next release will be v2.0.0.
This relese does not include the performance improvements from v1.5.1.
Pandas DataFrame objects with multilevel columns are now supported.
Numpy 1.20 is now officially supported.
Python 3.9 is now officially supported.
Achieved a small speedup for _get_flattener by merging type checks.

v1.5.1

The performance of the unpickler was drastically improved by avoiding tag checks \ 
for basic Python types.
decode() documentation improvements.
Serialization of Pandas DataFrame objects that contain timedelta64[ns] dtypes \ 
are now supported.
Dictionary identity is now preserved. For example, if the same dictionary \ 
appears twice in a list, the reconstituted list will now contain two references \ 
to the same dictionary.
Unit tests were added to ensure that sklearn.tree.DecisionTreeClassifier objects \ 
are properly serialized.
The is_reducible() utility function used by encode() is now 4x faster! Objects \ 
that provide __getstate__(), __setstate__(), and __slots__ benefit most from \ 
these improvements.
Improved pickler flatten()/encode() performance.

v1.5.0

Previous versions of jsonpickle with make_refs=False would emit null when \ 
encountering an object it had already seen when traversing objects. All \ 
instances of the object are now serialized. While this is arguably an \ 
improvement in the vast majority of scenarios, it is a change in behavior and is \ 
thus considered a minor-level change.
Multiple enums are now serialized correctly with make_refs=False.

Log message:
textproc: Replace RMD160 checksums with BLAKE2s checksums

All checksums have been double-checked against existing RMD160 and
SHA512 hashes

Unfetchable distfiles (fetched conditionally?):
./textproc/convertlit/distinfo clit18src.zip

Log message:
textproc: Remove SHA1 hashes for distfiles

Log message:
py-jsonpickle: updated to 1.4.2

v1.4.2
* Use importlib.metadata from the stdlib on Python 3.8.
* Micro-optimize type checks to use a `set` for lookups.
* Documentation improvements.

Log message:
py-jsonpickle: updated to 1.4.1

v1.4.1
* Patch release for Python 3.8 `importlib_metadata` support.

v1.4
* Python 3.8 support.
* ``jsonpickle.encode`` now supports the standard ``indent``
  and ``separators`` arguments, and passes them through to the
  active JSON backend library.
* We now include a custom handler for `array.array` objects.
* Dict key order is preserved when pickling dictionaries on Python3.
* Improved serialization of dictionaries with non-string keys.
  Previously, using an enum that was both the key and a value in
  a dictionary could end up with incorrect references to other
  objects.  The references are now properly maintained for dicts
  with object keys that are also referenced in the dict's values.
* Improved serialization of pandas.Series objects.

v1.3
* Improved round tripping of default dicts.
* Better support for cyclical references when encoding with
  ``unpicklable=False``.

Log message:
all: migrate several HOMEPAGEs to https

pkglint --only "https instead of http" -r -F

With manual adjustments afterwards since pkglint 19.4.4 fixed a few
indentations in unrelated lines.

This mainly affects projects hosted at SourceForce, as well as
freedesktop.org, CTAN and GNU.

Log message:
py-jsonpickle: updated to 1.2

Version 1.2:

* Simplified JSON representation for __reduce__ values.

* Improved Pandas support with new handlers for more Pandas data types.

* Prevent stack overflows caused by bugs in user-defined __getstate__
  functions which cause infinite recursion.

* Improved support for objects that contain dicts with Integer keys.
  Previously, jsonpickle could not restore objects that contained
  dicts with integer keys and provided getstate only.
  These objects are now handled robustly.

* Support for encoding binary data in base85_ instead of base64 has been
  added on Python 3. Base85 produces payloads about 10% smaller than base64,
  albeit at the cost of lower throughput.  For performance and backwards
  compatibility with Python 2 the pickler uses base64 by default, but it can
  be configured to use base85 with the new use_base85 argument.

* Dynamic SQLAlchemy tables in SQLAlchemy >= 1.3 are now supported.

Log message:
py-jsonpickle: updated to 1.1

Version 1.1:
* Python 3.7 `collections.Iterator` deprecation warnings have been fixed.
* Improved Pandas support for datetime and complex numbers.

Log message:
py-jsonpickle: updated to 1.0

Version 1.0:
NOTE jsonpickle no longer supports Python2.6, or Python3 < 3.4. The \ 
officially supported Python versions are now 2.7 and 3.4+.
Improved Pandas and Numpy support.
Improved support for pickling iterators.
Better support for the stdlib json module when simplejson is not installed.
jsonpickle will now output python3-style module names when pickling builtins \ 
methods or functions.
jsonpickle will always flatten primitives, even when max_depth is reached, which \ 
avoids encoding unicode strings into their u'string' representation.
Nested classes are now supported on Python 3.
Better support for older (pre-1.9) versions of numpy

Log message:
py-jsonpickle: updated to 0.9.6

Version 0.9.6:
* Better support for SQLAlchemy
* Better support for NumPy and SciKit-Learn.
* Better support for dict sub-classes