Remove trailing commas to avoid black expanding code

From black 20.8b0's changelog:

```
re-implemented support for explicit trailing commas: now it works
consistently within any bracket pair, including nested structures (#1288
and duplicates)
```

We have lots of trailing commas throughout our source code and it causes
changes like this:

```
-    print('Brambox: %r, %r' % (brambox.__version__, brambox.__file__,))
+    print(
+        'Brambox: %r, %r'
+        % (
+            brambox.__version__,
+            brambox.__file__,
+        )
+    )
```

which adds lots of lines for no reason.  There are more extreme cases that make
the code less readable after black reformats the code.  The only way to avoid
this is to remove trailing commas.

_dev/super_setup_old.py

@@ -1036,7 +1036,7 @@ def move_wildme(wbia_rman, fmt):
                     if origin_user not in remotes:
                         # first add a remote that is the original origin
                         origin_url = origin['url']
-                        print('  * Create remote %r: %r' % (origin_user, origin_url,))
+                        print('  * Create remote %r: %r' % (origin_user, origin_url))
                         gitrepo.create_remote(origin_user, origin_url)
                     # change origin to use wildme url
                     gitorigin = gitrepo.remote('origin')

super_setup.py

@@ -556,7 +556,7 @@ def ensure(repo, dry=False):
         # Print some status
         repo.debug(
             ' * branch = {} -> {}'.format(
-                repo.pygit.active_branch.name, repo.pygit.active_branch.tracking_branch(),
+                repo.pygit.active_branch.name, repo.pygit.active_branch.tracking_branch()
             )
         )
 

wbia/__main__.py

@@ -51,11 +51,11 @@ def smoke_test():  # nocover
 
     import brambox
 
-    print('Brambox: %r, %r' % (brambox.__version__, brambox.__file__,))
+    print('Brambox: %r, %r' % (brambox.__version__, brambox.__file__))
 
     import lightnet
 
-    print('Lightnet: %r, %r' % (lightnet.__version__, lightnet.__file__,))
+    print('Lightnet: %r, %r' % (lightnet.__version__, lightnet.__file__))
 
 
 def run_wbia():

wbia/_wbia_object.py

@@ -273,16 +273,19 @@ def expand_closure_source(funcname, func):
             source = '    %s = %s' % (alias, attrname)
             explicit_lines.append(source)
 
-        explicit_source = '\n'.join(
-            [
-                'from wbia import _wbia_object',
-                '',
-                '',
-                'class _%s_base_class(_wbia_object.ObjectList1D):',
-                '    __needs_inject__ = False',
-                '',
-            ]
-        ) % (objname,)
+        explicit_source = (
+            '\n'.join(
+                [
+                    'from wbia import _wbia_object',
+                    '',
+                    '',
+                    'class _%s_base_class(_wbia_object.ObjectList1D):',
+                    '    __needs_inject__ = False',
+                    '',
+                ]
+            )
+            % (objname,)
+        )
         explicit_source += '\n'.join(explicit_lines)
         explicit_fname = '_autogen_%s_base.py' % (objname,)
         from os.path import dirname, join

wbia/algo/detect/azure.py

@@ -87,7 +87,7 @@ def _detect(gpath, prediction_project, prediction_iteration, prediction_model):
     with open(gpath, 'rb') as image_file:
         data = image_file.read()
 
-    prediction_url = DETECTION_URL % (prediction_project, prediction_iteration,)
+    prediction_url = DETECTION_URL % (prediction_project, prediction_iteration)
     prediction_header = DETECTION_HEADER.copy()
     prediction_header['Prediction-Key'] = prediction_model
     response = requests.post(url=prediction_url, data=data, headers=prediction_header)

wbia/algo/detect/canonical.py

@@ -161,7 +161,7 @@ def __getitem__(self, index):
         if self.target_transform is not None:
             target = self.target_transform(target)
 
-        result = (sample, target,) if self.targets else (sample,)
+        result = (sample, target) if self.targets else (sample,)
         return result
 
     def __len__(self):
@@ -182,7 +182,7 @@ def __repr__(self):
 
 
 def finetune(
-    model, dataloaders, optimizer, scheduler, device, num_epochs=128, under=1.0, over=1.0,
+    model, dataloaders, optimizer, scheduler, device, num_epochs=128, under=1.0, over=1.0
 ):
     phases = ['train', 'val']
 
@@ -367,7 +367,7 @@ def visualize_augmentations(dataset, augmentation, tag, num=20):
     import matplotlib.pyplot as plt
 
     samples = dataset.samples
-    logger.info('Dataset %r has %d samples' % (tag, len(samples),))
+    logger.info('Dataset %r has %d samples' % (tag, len(samples)))
 
     index_list = list(range(len(samples)))
     random.shuffle(index_list)
@@ -452,7 +452,7 @@ def train(data_path, output_path, batch_size=32):
     # Initialize the model for this run
     model = torchvision.models.densenet201(pretrained=True)
     num_ftrs = model.classifier.in_features
-    model.classifier = nn.Sequential(nn.Dropout(0.5), nn.Linear(num_ftrs, 4),)
+    model.classifier = nn.Sequential(nn.Dropout(0.5), nn.Linear(num_ftrs, 4))
 
     # Send the model to GPU
     model = model.to(device)
@@ -521,7 +521,7 @@ def test_single(filepath_list, weights_path, batch_size=512):
     # Initialize the model for this run
     model = torchvision.models.densenet201()
     num_ftrs = model.classifier.in_features
-    model.classifier = nn.Sequential(nn.Dropout(0.5), nn.Linear(num_ftrs, 4),)
+    model.classifier = nn.Sequential(nn.Dropout(0.5), nn.Linear(num_ftrs, 4))
 
     model.load_state_dict(state)
 

wbia/algo/detect/densenet.py

@@ -109,7 +109,7 @@ def __init__(self, blur=True, flip=False, rotate=10, shear=10, **kwargs):
                 sequence += [
                     iaa.PiecewiseAffine(scale=(0.0005, 0.005)),
                     iaa.Affine(
-                        rotate=(-rotate, rotate), shear=(-shear, shear), mode='symmetric',
+                        rotate=(-rotate, rotate), shear=(-shear, shear), mode='symmetric'
                     ),
                     iaa.Grayscale(alpha=(0.0, 0.5)),
                 ]
@@ -168,7 +168,7 @@ def __init__(self, filepaths, targets=None, transform=None, target_transform=Non
 
         self.targets = targets is not None
 
-        args = (filepaths, targets,) if self.targets else (filepaths,)
+        args = (filepaths, targets) if self.targets else (filepaths,)
         self.samples = list(zip(*args))
 
         if self.targets:
@@ -204,7 +204,7 @@ def __getitem__(self, index):
         if self.target_transform is not None:
             target = self.target_transform(target)
 
-        result = (sample, target,) if self.targets else (sample,)
+        result = (sample, target) if self.targets else (sample,)
 
         return result
 
@@ -391,7 +391,7 @@ def visualize_augmentations(dataset, augmentation, tag, num_per_class=10, **kwar
 
     samples = dataset.samples
     flags = np.array(ut.take_column(samples, 1))
-    logger.info('Dataset %r has %d samples' % (tag, len(flags),))
+    logger.info('Dataset %r has %d samples' % (tag, len(flags)))
 
     indices = []
     for flag in set(flags):
@@ -771,7 +771,7 @@ def test(
 
     logger.info(
         'Using weights in the ensemble, index %r: %s '
-        % (ensemble_index, ut.repr3(weights_path_list),)
+        % (ensemble_index, ut.repr3(weights_path_list))
     )
     result_list = test_ensemble(
         gpath_list,

wbia/algo/detect/orientation.py

@@ -62,7 +62,7 @@ def __init__(self, blur=True, flip=False, rotate=10, shear=10, **kwargs):
                 sequence += [
                     iaa.PiecewiseAffine(scale=(0.0005, 0.005)),
                     iaa.Affine(
-                        rotate=(-rotate, rotate), shear=(-shear, shear), mode='symmetric',
+                        rotate=(-rotate, rotate), shear=(-shear, shear), mode='symmetric'
                     ),
                     iaa.Grayscale(alpha=(0.0, 0.5)),
                 ]
@@ -121,7 +121,7 @@ def __init__(self, filepaths, targets=None, transform=None, target_transform=Non
 
         self.targets = targets is not None
 
-        args = (filepaths, targets,) if self.targets else (filepaths,)
+        args = (filepaths, targets) if self.targets else (filepaths,)
         self.samples = list(zip(*args))
 
         if self.targets:
@@ -157,7 +157,7 @@ def __getitem__(self, index):
         if self.target_transform is not None:
             target = self.target_transform(target)
 
-        result = (sample, target,) if self.targets else (sample,)
+        result = (sample, target) if self.targets else (sample,)
 
         return result
 
@@ -344,7 +344,7 @@ def visualize_augmentations(dataset, augmentation, tag, num_per_class=10, **kwar
 
     samples = dataset.samples
     flags = np.array(ut.take_column(samples, 1))
-    logger.info('Dataset %r has %d samples' % (tag, len(flags),))
+    logger.info('Dataset %r has %d samples' % (tag, len(flags)))
 
     indices = []
     for flag in set(flags):
@@ -722,7 +722,7 @@ def test(
 
     logger.info(
         'Using weights in the ensemble, index %r: %s '
-        % (ensemble_index, ut.repr3(weights_path_list),)
+        % (ensemble_index, ut.repr3(weights_path_list))
     )
     result_list = test_ensemble(
         gpath_list,

wbia/algo/detect/randomforest.py

@@ -46,7 +46,7 @@ def train_gid_list(
     """
     logger.info(
         '[randomforest.train()] training with %d gids and species=%r'
-        % (len(gid_list), species,)
+        % (len(gid_list), species)
     )
     if trees_path is None and species is not None:
         trees_path = join(ibs.get_cachedir(), 'trees', species)
@@ -298,7 +298,7 @@ def detect(ibs, gpath_list, tree_path_list, **kwargs):
     if verbose:
         logger.info(
             '[randomforest.detect()] Detecting with %d trees with scale_list=%r'
-            % (len(tree_path_list), kwargs['scale_list'],)
+            % (len(tree_path_list), kwargs['scale_list'])
         )
 
     # Run detection

wbia/algo/graph/core.py

@@ -686,7 +686,7 @@ def connected_component_status(infr):
         num_inconsistent = len(infr.recovery_ccs)
         num_names_max = infr.pos_graph.number_of_components()
 
-        status = dict(num_names_max=num_names_max, num_inconsistent=num_inconsistent,)
+        status = dict(num_names_max=num_names_max, num_inconsistent=num_inconsistent)
         infr.print('done checking status', 3)
         return status
 

wbia/algo/graph/mixin_dynamic.py

@@ -1146,7 +1146,7 @@ def _set_pos_redun_flag(infr, nid, flag):
             infr.remove_internal_priority(cc)
             if infr.params['inference.update_attrs']:
                 infr.set_edge_attrs(
-                    'inferred_state', ut.dzip(nxu.edges_inside(infr.graph, cc), ['same']),
+                    'inferred_state', ut.dzip(nxu.edges_inside(infr.graph, cc), ['same'])
                 )
         else:
             if was_pos_redun:
@@ -1491,7 +1491,7 @@ def categorize_edges(infr, graph=None, ne_to_edges=None):
         # Find edges internal to inconsistent PCCs
         incon_internal = {
             nid: union(
-                ne_to_edges[key][(nid, nid)] for key in (POSTV, NEGTV,) + UNINFERABLE
+                ne_to_edges[key][(nid, nid)] for key in (POSTV, NEGTV) + UNINFERABLE
             )
             for nid in incon_internal_nids
         }

wbia/algo/graph/mixin_viz.py

@@ -448,7 +448,7 @@ def get_any(dict_, keys, default=None):
         reviewed_width = 2.0
         if highlight_reviews:
             nx.set_edge_attributes(
-                graph, name='linewidth', values=ut.dzip(reviewed_edges, [reviewed_width]),
+                graph, name='linewidth', values=ut.dzip(reviewed_edges, [reviewed_width])
             )
             nx.set_edge_attributes(
                 graph,

wbia/algo/graph/mixin_wbia.py

@@ -1194,7 +1194,8 @@ def fix_annotmatch_to_undirected_upper(ibs):
 
         df4 = df3[~pd.isnull(df3[ed_key])]
         ibs.set_annotmatch_evidence_decision(
-            df4.annotmatch_rowid, [None if pd.isnull(x) else int(x) for x in df4[ed_key]],
+            df4.annotmatch_rowid,
+            [None if pd.isnull(x) else int(x) for x in df4[ed_key]],
         )
         ibs.set_annotmatch_tag_text(
             df4.annotmatch_rowid, df4.annotmatch_tag_text.tolist()

wbia/algo/graph/nx_dynamic_graph.py

@@ -12,7 +12,7 @@
 class GraphHelperMixin(ut.NiceRepr):
     def __nice__(self):
         return 'nNodes={}, nEdges={}'.format(
-            self.number_of_nodes(), self.number_of_edges(),
+            self.number_of_nodes(), self.number_of_edges()
         )
 
     def has_nodes(self, nodes):
@@ -181,7 +181,7 @@ def clear(self):
 
     def __nice__(self):
         return 'nNodes={}, nEdges={}, nCCs={}'.format(
-            self.number_of_nodes(), self.number_of_edges(), self.number_of_components(),
+            self.number_of_nodes(), self.number_of_edges(), self.number_of_components()
         )
 
     def number_of_components(self):

wbia/algo/hots/_pipeline_helpers.py

@@ -218,7 +218,7 @@ def testdata_pre_sver(defaultdb='PZ_MTEST', qaid_list=None, daid_list=None):
 
 
 def testdata_post_sver(
-    defaultdb='PZ_MTEST', qaid_list=None, daid_list=None, codename='vsmany', cfgdict=None,
+    defaultdb='PZ_MTEST', qaid_list=None, daid_list=None, codename='vsmany', cfgdict=None
 ):
     """
     >>> from wbia.algo.hots._pipeline_helpers import *  # NOQA

wbia/algo/hots/chip_match.py

@@ -138,9 +138,12 @@ def safe_check_nested_lens_eq(arr1, arr2):
     else:
         safe_check_lens_eq(arr1, arr2, 'outer lengths do not correspond')
         for count, (x, y) in enumerate(zip(arr1, arr2)):
-            assert len(x) == len(y), (
-                'inner lengths at position=%r do not correspond (%r != %r)'
-                % (count, len(x), len(y),)
+            assert len(x) == len(
+                y
+            ), 'inner lengths at position=%r do not correspond (%r != %r)' % (
+                count,
+                len(x),
+                len(y),
             )
 
 
@@ -522,7 +525,7 @@ def ishow_single_annotmatch(cm, qreq_, aid2=None, **kwargs):
         }
         if aid2 is None:
             aid2 = cm.get_top_aids(ntop=1)[0]
-        logger.info('[cm] ishow_single_annotmatch aids(%s, %s)' % (cm.qaid, aid2,))
+        logger.info('[cm] ishow_single_annotmatch aids(%s, %s)' % (cm.qaid, aid2))
         kwshow.update(**kwargs)
         try:
             inter = interact_matches.MatchInteraction(
@@ -1187,9 +1190,7 @@ def summarize(cm, qreq_):
                     cminfo_dict[key] = annot_df[prop].iloc[idx]
 
         cminfo_dict.update(
-            dict(
-                gt_aid=cminfo_dict['gt_annot_daid'], gf_aid=cminfo_dict['gf_annot_daid'],
-            )
+            dict(gt_aid=cminfo_dict['gt_annot_daid'], gf_aid=cminfo_dict['gf_annot_daid'])
         )
         del cminfo_dict['gt_annot_daid']
         del cminfo_dict['gf_annot_daid']
@@ -1851,7 +1852,7 @@ def varinfo(varname, onlyrepr=False, canshowrepr=True, cm=cm, varcolor='yellow')
                     varinfo_list += [
                         # '    %s varinfo(%s):' % (symbol, varname,),
                         '    %s %s = <not shown!>'
-                        % (symbol, varname,),
+                        % (symbol, varname)
                     ]
                 varinfo_list += ['          len = %r' % (len(varval),)]
                 if depth != len(varval):

wbia/algo/hots/neighbor_index_cache.py

@@ -311,7 +311,7 @@ def request_wbia_nnindexer(qreq_, verbose=True, **kwargs):
 
 
 def request_augmented_wbia_nnindexer(
-    qreq_, daid_list, verbose=True, use_memcache=True, force_rebuild=False, memtrack=None,
+    qreq_, daid_list, verbose=True, use_memcache=True, force_rebuild=False, memtrack=None
 ):
     r"""
     DO NOT USE. THIS FUNCTION CAN CURRENTLY CAUSE A SEGFAULT

wbia/algo/hots/scoring.py

@@ -48,7 +48,7 @@ def score_chipmatch_list(qreq_, cm_list, score_method, progkw=None):
         progkw = dict(freq=1, time_thresh=30.0, adjust=True)
     lbl = 'scoring %s' % (score_method)
     # Choose the appropriate scoring mechanism
-    logger.info('[scoring] score %d chipmatches with %s' % (len(cm_list), score_method,))
+    logger.info('[scoring] score %d chipmatches with %s' % (len(cm_list), score_method))
     if score_method == 'sumamech':
         for cm in ut.ProgressIter(cm_list, lbl=lbl, **progkw):
             cm.score_name_sumamech(qreq_)

wbia/algo/preproc/preproc_image.py

@@ -90,7 +90,7 @@ def islocal(gpath):
                 _, ext = splitext(filename)
                 # base = filename
                 base = ut.random_nonce(16)
-                suffix = '.%s%s' % (base, ext,)
+                suffix = '.%s%s' % (base, ext)
                 temp_file, temp_filepath = tempfile.mkstemp(suffix=suffix)
                 args = (
                     gpath,
@@ -120,7 +120,7 @@ def islocal(gpath):
                         scheme = urlsplit(uri_, allow_fragments=False).scheme
                         uri_ = uri_.strip('%s://' % (scheme,))
                         uri_path = urlquote(uri_.encode('utf8'))
-                        uri_ = '%s://%s' % (scheme, uri_path,)
+                        uri_ = '%s://%s' % (scheme, uri_path)
                         # six.moves.urllib.request.urlretrieve(uri_, filename=temp_filepath)
                         response = requests.get(uri_, stream=True, allow_redirects=True)
                         assert (
@@ -158,7 +158,7 @@ def islocal(gpath):
             #                          warn.line)
             #     warnstr = warnings.formatwarning
             #     logger.info(warnstr)
-            logger.info('%d warnings issued by %r' % (len(w), gpath,))
+            logger.info('%d warnings issued by %r' % (len(w), gpath))
     # Parse out the data
     width, height = pil_img.size  # Read width, height
     time, lat, lon, orient = parse_exif(pil_img)  # Read exif tags

wbia/algo/smk/inverted_index.py

@@ -200,7 +200,7 @@ def render_inverted_vocab_word(inva, wx, ibs, fnum=None):
 
         # Stack them together
         solidbar = np.zeros(
-            (patch_img.shape[0], int(patch_img.shape[1] * 0.1), 3), dtype=patch_img.dtype,
+            (patch_img.shape[0], int(patch_img.shape[1] * 0.1), 3), dtype=patch_img.dtype
         )
         border_color = (100, 10, 10)  # bgr, darkblue
         if ut.is_float(solidbar):