Zfit

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Major Features and Improvements
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last Python 3.7 version

Bug fixes and small changes
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- ``SampleData`` is not used anymore, a ``Data`` object is returned (for simple sampling). The ``create_sampler`` will still return a ``SamplerData`` object though as this differs from ``Data``.

Experimental
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- Added support on a best-effort for human-readable serialization of objects including an HS3-like representation, find a `tutorial on serialization here <https://zfit-tutorials.readthedocs.io/en/latest/tutorials/components/README.html#serialization>`_. Most built-in unbinned PDFs are supported. This is still experimental and not yet fully supported. Dumping can be performed safely, loading maybe easily breaks (also between versions), so do not rely on it yet. Everything else - apart of trying to dump - should only be used for playing around and giving feedback purposes.

Requirement changes
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- allow uproot 5 (remove previous restriction)

Thanks
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- to Johannes Lade for the amazing work on the serialization, which made this HS3 implementation possible!

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Bug fixes and small changes
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- added ``extended`` as a parameter to all PDFs: a PDF can now directly be extended without the need for
``create_extended`` (or ``set_yield``).
- ``to_pandas`` and ``from_pandas`` now also support weights as columns. Default column name is ``""``.
- add ``numpy`` and ``backend`` to options when setting the seed
- reproducibility by fixing the seed in zfit is restored, ``zfit.run.set_seed`` now also sets the seed for the backend(numpy, tensorflow, etc.) if requested (on by default)

Thanks
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- Sebastian Schmitt schmitse for reporting the bug in the non-reproducibility of the seed.

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Bug fixes and small changes
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- ``create_extended`` added ``None`` to the name, removed.
- ``SimpleConstraint`` now also takes a function that has an explicit ``params`` argument.
- add ``name`` argument to ``create_extended``.
- adding binned losses would error due to the removed ``fit_range`` argument.
- setting a global seed made the sampler return constant values, fixed (unoptimized but correct). If you ran
a fit with a global seed, you might want to rerun it.
- histogramming and limit checks failed due to a stricter Numpy check, fixed.


Thanks
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- P-H-Wagner for finding the bug in ``SimpleConstraint``.
- Dan Johnson for finding the bug in the binned loss that would fail to sum them up.
- Hanae Tilquin for spotting the bug with TensorFlows changed behavior or random states inside a tf.function,
leading to biased samples whenever a global seed was set.

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Hotfix for wrong import

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Major Features and Improvements
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- columns of unbinned ``data`` can be accessed with the obs like a mapping (like a dataframe)
- speedup builtin ``errors`` method and make it more robust

Breaking changes
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- ``Data`` can no longer be used directly as an array-like object but got mapping-like behavior.
- some old deprecated methods were removed

Bug fixes and small changes
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- improved caching speed, reduced tradeoff against memory
- yields were not added correctly in some (especially binned) PDFs and the fit would fail

Requirement changes
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- add jacobi (many thanks at HansDembinski for the package)