style: Update to Black v20.8 formatting (#1048)

* Apply Black v20.8b1 formatting
   - Should be similar to format of first stable release of Black
* Update Black pre-commit hook to use rev v20.8b1
   - Using pinned revs is the recommended approach for pre-commit: psf/black#420
* Update development docs to advocate for and explain the use of pre-commit autoupdate

Author: matthewfeickert

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
 -   repo: https://github.com/psf/black
-    rev: stable
+    rev: 20.8b1
     hooks:
     - id: black
       language_version: python3

docs/development.rst

@@ -19,6 +19,15 @@ Then setup the Git pre-commit hook for `Black <https://github.com/psf/black>`__
 
     pre-commit install
 
+as the ``rev`` gets updated through time to track changes of different hooks,
+simply run
+
+.. code-block:: console
+
+    pre-commit autoupdate
+
+to have pre-commit install the new version.
+
 Testing
 -------
 

src/pyhf/cli/patchset.py

@@ -18,9 +18,7 @@ def cli():
 
 @cli.command()
 @click.argument('patchset', default='-')
-@click.option(
-    '--name', help='The name of the patch to extract.', default=None,
-)
+@click.option('--name', help='The name of the patch to extract.', default=None)
 @click.option(
     '--output-file',
     help='The location of the output json file. If not specified, prints to screen.',
@@ -64,9 +62,7 @@ def extract(patchset, name, output_file, with_metadata):
 @cli.command()
 @click.argument('background-only', default='-')
 @click.argument('patchset', default='-')
-@click.option(
-    '--name', help='The name of the patch to extract.', default=None,
-)
+@click.option('--name', help='The name of the patch to extract.', default=None)
 @click.option(
     '--output-file',
     help='The location of the output json file. If not specified, prints to screen.',

src/pyhf/cli/spec.py

@@ -346,7 +346,7 @@ def digest(workspace, algorithm, output_json):
     }
 
     if output_json:
-        output = json.dumps(digests, indent=4, sort_keys=True,)
+        output = json.dumps(digests, indent=4, sort_keys=True)
     else:
         output = '\n'.join(
             f"{hash_alg}:{digest}" for hash_alg, digest in digests.items()

src/pyhf/constraints.py

@@ -82,10 +82,10 @@ def _precompute(self):
         self.access_field = tensorlib.astensor(self._access_field, dtype='int')
 
     def has_pdf(self):
-        '''
+        """
         Returns:
             flag (`bool`): Whether the model has a Gaussian Constraint
-        '''
+        """
         return bool(self.param_viewer.index_selection)
 
     def make_pdf(self, pars):
@@ -213,10 +213,10 @@ def _precompute(self):
         self.batched_factors = tensorlib.astensor(self._batched_factors)
 
     def has_pdf(self):
-        '''
+        """
         Returns:
             flag (`bool`): Whether the model has a Gaussian Constraint
-        '''
+        """
         return bool(self.param_viewer.index_selection)
 
     def make_pdf(self, pars):

src/pyhf/modifiers/histosys.py

@@ -80,10 +80,10 @@ def _precompute(self):
             )
 
     def apply(self, pars):
-        '''
+        """
         Returns:
             modification tensor: Shape (n_modifiers, n_global_samples, n_alphas, n_global_bin)
-        '''
+        """
         if not self.param_viewer.index_selection:
             return
 

src/pyhf/modifiers/lumi.py

@@ -57,10 +57,10 @@ def _precompute(self):
         self.lumi_default = tensorlib.ones(self.lumi_mask.shape)
 
     def apply(self, pars):
-        '''
+        """
         Returns:
             modification tensor: Shape (n_modifiers, n_global_samples, n_alphas, n_global_bin)
-        '''
+        """
         if not self.param_viewer.index_selection:
             return
 

src/pyhf/modifiers/normfactor.py

@@ -58,10 +58,10 @@ def _precompute(self):
         self.normfactor_default = tensorlib.ones(self.normfactor_mask.shape)
 
     def apply(self, pars):
-        '''
+        """
         Returns:
             modification tensor: Shape (n_modifiers, n_global_samples, n_alphas, n_global_bin)
-        '''
+        """
         if not self.param_viewer.index_selection:
             return
         tensorlib, _ = get_backend()

src/pyhf/modifiers/normsys.py

@@ -81,10 +81,10 @@ def _precompute(self):
             )
 
     def apply(self, pars):
-        '''
+        """
         Returns:
             modification tensor: Shape (n_modifiers, n_global_samples, n_alphas, n_global_bin)
-        '''
+        """
         if not self.param_viewer.index_selection:
             return
 

src/pyhf/modifiers/shapefactor.py

@@ -131,10 +131,10 @@ def _precompute(self):
         self.sample_ones = tensorlib.ones(tensorlib.shape(self.shapefactor_mask)[1])
 
     def apply(self, pars):
-        '''
+        """
         Returns:
             modification tensor: Shape (n_modifiers, n_global_samples, n_alphas, n_global_bin)
-        '''
+        """
         if not self.param_viewer.index_selection:
             return