Sourcery refactored master branch #1
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| if self.line_before_msg: | ||
| _stdout.write("\n") | ||
| _stdout.write(self.preambule + " ... " + s) | ||
| _stdout.write(f"{self.preambule} ... {s}") |
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Function PreambuleStream.write_msg refactored with the following changes:
- Use f-string instead of string concatenation [×2] (
use-fstring-for-concatenation)
| def getDescription(test): | ||
| doc_first_line = test.shortDescription() | ||
| if doc_first_line: | ||
| if doc_first_line := test.shortDescription(): |
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Function QuietTestResult.getDescription refactored with the following changes:
- Use named expression to simplify assignment and conditional (
use-named-expression)
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| print("%s: %s" % (flavour,self.getDescription(test))) | ||
| print(f"{flavour}: {self.getDescription(test)}") | ||
| print(self.separator2) | ||
| print("%s" % err) | ||
| print(f"{err}") |
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Function QuietTestResult.printErrorList refactored with the following changes:
- Replace interpolated string formatting with f-string [×2] (
replace-interpolation-with-fstring)
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| INSTALL_REQUIRES = sorted(set( | ||
| line.partition('#')[0].strip() | ||
| for file in (os.path.join(os.path.dirname(__file__), file) | ||
| for file in requirements) | ||
| for line in open(file) | ||
| ) - {''}) | ||
| INSTALL_REQUIRES = sorted( | ||
| ( | ||
| { | ||
| line.partition('#')[0].strip() | ||
| for file in ( | ||
| os.path.join(os.path.dirname(__file__), file) | ||
| for file in requirements | ||
| ) | ||
| for line in open(file) | ||
| } | ||
| - {''} | ||
| ) | ||
| ) |
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Lines 87-92 refactored with the following changes:
- Replace list(), dict() or set() with comprehension (
collection-builtin-to-comprehension)
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| FULLVERSION += '.dev0+' + GIT_REVISION[:7] | ||
| FULLVERSION += f'.dev0+{GIT_REVISION[:7]}' |
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Function write_version_py refactored with the following changes:
- Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| return super().__repr__() + ' # params=' + repr(self.params) | ||
| return f'{super().__repr__()} # params={repr(self.params)}' |
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Function SklModel.__repr__ refactored with the following changes:
- Use f-string instead of string concatenation [×2] (
use-fstring-for-concatenation)
| ) | ||
| # first argument is 'self' | ||
| assert spec[0] == "self" | ||
| return {name: values[name] for name in spec[1:] if name in values} |
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Function SklLearner._get_sklparams refactored with the following changes:
- Swap if/else branches (
swap-if-else-branches) - Remove unnecessary else after guard condition (
remove-unnecessary-else) - Inline variable that is immediately returned (
inline-immediately-returned-variable)
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| def __call__(self, data, ret=Model.Value): | ||
| if isinstance(data, Table): | ||
| with data.force_unlocked(data.X): | ||
| return super().__call__(data, ret) | ||
| else: | ||
| if not isinstance(data, Table): | ||
| return super().__call__(data, ret) | ||
| with data.force_unlocked(data.X): | ||
| return super().__call__(data, ret) |
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Function CatGBModel.__call__ refactored with the following changes:
- Swap if/else branches (
swap-if-else-branches) - Remove unnecessary else after guard condition (
remove-unnecessary-else)
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| return super().__repr__() + ' # params=' + repr(self.params) | ||
| return f'{super().__repr__()} # params={repr(self.params)}' |
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Function CatGBModel.__repr__ refactored with the following changes:
- Use f-string instead of string concatenation [×2] (
use-fstring-for-concatenation)
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| vals = [attr.values[j] for j in sorted(child.condition)] | ||
| if not vals: | ||
| child.description = "(unreachable)" | ||
| if vals := [attr.values[j] for j in sorted(child.condition)]: | ||
| child.description = ( | ||
| vals[0] | ||
| if len(vals) == 1 | ||
| else f'{", ".join(vals[:-1])} or {vals[-1]}' | ||
| ) | ||
| else: | ||
| child.description = vals[0] if len(vals) == 1 else \ | ||
| "{} or {}".format(", ".join(vals[:-1]), vals[-1]) |
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Function MappedDiscreteNode._set_child_descriptions refactored with the following changes:
- Use named expression to simplify assignment and conditional (
use-named-expression) - Swap if/else branches (
swap-if-else-branches) - Replace call to format with f-string (
use-fstring-for-formatting)
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| child.description = \ | ||
| "{} {}".format("≤>"[child_idx], attr.str_val(threshold)) | ||
| child.description = f'{"≤>"[child_idx]} {attr.str_val(threshold)}' |
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Function NumericNode._set_child_descriptions refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting)
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| else: | ||
| sums = np.sum(predictions, axis=1) | ||
| # This can't happen because nodes with 0 instances are prohibited | ||
| # zeros = (sums == 0) | ||
| # predictions[zeros] = 1 | ||
| # sums[zeros] = predictions.shape[1] | ||
| return predictions / sums[:, np.newaxis] | ||
| sums = np.sum(predictions, axis=1) | ||
| # This can't happen because nodes with 0 instances are prohibited | ||
| # zeros = (sums == 0) | ||
| # predictions[zeros] = 1 | ||
| # sums[zeros] = predictions.shape[1] | ||
| return predictions / sums[:, np.newaxis] |
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Function TreeModel.predict refactored with the following changes:
- Remove unnecessary else after guard condition (
remove-unnecessary-else)
| def get_indices(self, nodes): | ||
| subsets = [node.subset for node in nodes] | ||
| if subsets: | ||
| if subsets := [node.subset for node in nodes]: |
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Function TreeModel.get_indices refactored with the following changes:
- Use named expression to simplify assignment and conditional (
use-named-expression)
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| rules.append("{} > {}".format(name, attr.repr_val(lower))) | ||
| rules.append(f"{name} > {attr.repr_val(lower)}") | ||
| elif lower is None: | ||
| rules.append("{} ≤ {}".format(name, attr.repr_val(upper))) | ||
| rules.append(f"{name} ≤ {attr.repr_val(upper)}") | ||
| else: | ||
| rules.append("{} < {} ≤ {}".format( | ||
| attr.repr_val(lower), name, attr.repr_val(upper))) | ||
| rules.append(f"{attr.repr_val(lower)} < {name} ≤ {attr.repr_val(upper)}") | ||
| else: | ||
| rules.append("{}: {}".format(name, node.description)) | ||
| rules.append(f"{name}: {node.description}") |
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Function TreeModel.rule refactored with the following changes:
- Replace call to format with f-string [×4] (
use-fstring-for-formatting)
| 'old behavior' | ||
| """ | ||
| alternative = ('; Instead, use ' + obj) if isinstance(obj, str) else '' | ||
| alternative = f'; Instead, use {obj}' if isinstance(obj, str) else '' |
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Function deprecated refactored with the following changes:
- Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| if ret == Model.Value: | ||
| return vals | ||
| else: | ||
| return vals, cal_probs | ||
| return vals if ret == Model.Value else (vals, cal_probs) |
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Function CalibratedClassifier.__call__ refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp)
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| calibrators = [fitter.fit(cls_probs, ytrue) | ||
| for cls_idx, cls_probs in enumerate(probabilities.T)] | ||
| calibrators = [fitter.fit(cls_probs, ytrue) for cls_probs in probabilities.T] |
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Function CalibratedLearner.get_model refactored with the following changes:
- Remove unnecessary calls to
enumeratewhen the index is not used (remove-unused-enumerate)
| solver = "liblinear" | ||
| else: | ||
| solver = "lbfgs" | ||
| solver = "liblinear" if penalty == "l1" else "lbfgs" |
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Function LogisticRegressionLearner._initialize_wrapped refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp)
|
|
||
| def __str__(self): | ||
| return 'ConstantModel {}'.format(self.dist) | ||
| return f'ConstantModel {self.dist}' |
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Function ConstantModel.__str__ refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting)
| y *= x.sum() / y.sum() | ||
| lrs = 2 * (x * np.log(x/y)).sum() | ||
| return lrs | ||
| return 2 * (x * np.log(x/y)).sum() |
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Function likelihood_ratio_statistic refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
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| p_cond = dist_sum / p_dist_sum | ||
| if tc is not None: | ||
| p_cond = dist_sum / p_dist_sum | ||
| # p_cond = dist[tc] / p_dist[tc] | ||
| p_true_positive = dist[tc] / dist_sum | ||
| p_class = p_dist[tc] / p_dist_sum | ||
| else: | ||
| # generality of the rule | ||
| p_cond = dist_sum / p_dist_sum |
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Function WeightedRelativeAccuracyEvaluator.evaluate_rule refactored with the following changes:
- Hoist repeated code outside conditional statement (
hoist-statement-from-if)
This removes the following comments ( why? ):
# generality of the rule
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| # remove redundant selectors | ||
| possible_selectors = [smh for smh in possible_selectors if | ||
| smh not in existing_selectors] | ||
|
|
||
| return possible_selectors | ||
| return [smh for smh in possible_selectors if smh not in existing_selectors] |
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Function TopDownSearchStrategy.find_new_selectors refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
This removes the following comments ( why? ):
# remove redundant selectors
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| attributes = self.domain.attributes | ||
| class_var = self.domain.class_var | ||
|
|
||
| if self.selectors: | ||
| attributes = self.domain.attributes |
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Function Rule.__str__ refactored with the following changes:
- Move assignments closer to their usage (
move-assign) - Use f-string instead of string concatenation [×2] (
use-fstring-for-concatenation) - Replace call to format with f-string (
use-fstring-for-formatting)
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| if not rule_list or rule_list and rule_list[-1].length > 0: | ||
| if not rule_list or rule_list[-1].length > 0: |
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Function CN2Learner.fit_storage refactored with the following changes:
- Remove redundant conditional (
remove-redundant-if)
| if len(data.domain.class_vars) != 1: | ||
| n_cls = len(data.domain.class_vars) | ||
| raise ValueError("Number of classes should be 1: {}".format(n_cls)) | ||
| raise ValueError(f"Number of classes should be 1: {n_cls}") |
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Function SimpleTreeModel.__init__ refactored with the following changes:
- Replace call to format with f-string [×2] (
use-fstring-for-formatting)
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| depths = {} | ||
| depths[cluster] = 0 | ||
| depths = {cluster: 0} | ||
| for cluster in preorder(cluster): | ||
| cl_depth = depths[cluster] | ||
| depths.update(dict.fromkeys(cluster.branches, cl_depth + 1)) | ||
| depths |= dict.fromkeys(cluster.branches, cl_depth + 1) |
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Function cluster_depths refactored with the following changes:
- Merge dictionary assignment with declaration (
merge-dict-assign) - Merge dictionary updates via the union operator (
dict-assign-update-to-union)
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| indices.update(chain.from_iterable( | ||
| ((var, -1-idx), (var.name, -1-idx), (-1-idx, -1-idx)) | ||
| for idx, var in enumerate(self.metas))) | ||
| indices |= chain.from_iterable( | ||
| ((var, -1 - idx), (var.name, -1 - idx), (-1 - idx, -1 - idx)) | ||
| for idx, var in enumerate(self.metas) | ||
| ) |
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Function Domain._ensure_indices refactored with the following changes:
- Merge dictionary updates via the union operator (
dict-assign-update-to-union)
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| return base if not places \ | ||
| else "{} {:0{}}".format(base, index + 1, places) | ||
| return "{} {:0{}}".format(base, index + 1, places) if places else base |
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Function Domain.from_numpy refactored with the following changes:
- Swap if/else branches of if expression to remove negation (
swap-if-expression)
| myvar = self.variables[index] | ||
| else: | ||
| myvar = self.metas[-1 - index] | ||
| myvar = self.variables[index] if index >= 0 else self.metas[-1 - index] |
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Function Domain._get_equivalent refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp)
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| if index >= 0: | ||
| return self.variables[index] | ||
| else: | ||
| return self.metas[-1 - index] | ||
| return self.variables[index] if index >= 0 else self.metas[-1 - index] |
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Function Domain.__getitem__ refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp)
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Sourcery Code Quality Report✅ Merging this PR will increase code quality in the affected files by 0.01%.
Here are some functions in these files that still need a tune-up:
Legend and ExplanationThe emojis denote the absolute quality of the code:
The 👍 and 👎 indicate whether the quality has improved or gotten worse with this pull request. Please see our documentation here for details on how these metrics are calculated. We are actively working on this report - lots more documentation and extra metrics to come! Help us improve this quality report! |
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