pyhf v0.7.0 released

[pyhf announcements]

Dear pyhf users,

We're happy to announce that pyhf v0.7.0 is out now on PyPI and Conda-forge! This is a minor release with new features and some API breaking changes. Thank you to everyone who tested the release candidates as your feedback was quite helpful. As always please read the full release notes carefully while updating your code to use the new release. Below we list the most important points from the release notes.

* All backends are now fully compatible and tested with Python 3.10.

* The pyhf.tensorlib.poisson API now allows for the expected rate parameter lam to be 0 in the case that the observed events n is 0 given that the limit is well defined.

* pyhf.readxml.parse now supports reading of XML configurations with absolute paths. To support this, pyhf xlm2json now has a -v/--mount option.

* Support for model specifications without a parameter of interest defined is added.

* The pyhf.parameters.paramsets classes suggested_fixed attribute behavior has been updated. To access the behavior used in pyhf v0.6.x use the suggested_fixed_as_bool attribute.

* pyhf.pdf._ModelConfig.par_names is changed to be a property attribute.

* The order of model parameters is now sorted by model parameter name.

* Support for writing user custom modifiers is added.

* Performance in pyhf.readxml is increased by improvements to pyhf.readxml.import_root_histogram.

* pyhf.contrib.utils.download is now more robust to different target file types.

* Schema validation now allows for both list and pyhf.tensorlib objects to exist in the model specification.

* There is now a Pyodide instance embedded in the pyhf docs. Try running pyhf natively in your web browser when you visit the docs!

Development work on v0.8.0 has already started and we will be releasing v0.7.x patch releases for any bugs as needed. Please report back to us any questions or problems you run into with the v0.7.0 API through the recommended channels!

Best,
The pyhf dev team (Lukas, Matthew, and Giordon)