Sourcery refactored master branch #1

sourcery-ai · 2022-03-21T00:13:45Z

Branch master refactored by Sourcery.

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sourcery-ai · 2022-03-21T00:13:47Z

expand_mnist.py

@@ -11,6 +11,7 @@

 """



Lines 36-40 refactored with the following changes:

Replace manual loop counter with call to enumerate (convert-to-enumerate)

This removes the following comments ( why? ):

# counter

sourcery-ai · 2022-03-21T00:13:47Z

mnist_svm.py

    num_correct = sum(int(a == y) for a, y in zip(predictions, test_data[1]))
    print("Baseline classifier using an SVM.")
-    print(str(num_correct) + " of " + str(len(test_data[1])) + " values correct.")
+    print(f'{str(num_correct)} of {len(test_data[1])} values correct.')


Function svm_baseline refactored with the following changes:

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Remove unnecessary calls to str() from formatted values in f-strings (remove-str-from-fstring)

sourcery-ai · 2022-03-21T00:13:47Z

network.py

-                print("Epoch {} : {} / {}".format(j,self.evaluate(test_data),n_test))
+                print(f"Epoch {j} : {self.evaluate(test_data)} / {n_test}")
            else:
-                print("Epoch {} complete".format(j))
+                print(f"Epoch {j} complete")


Function Network.SGD refactored with the following changes:

Replace call to format with f-string. (use-fstring-for-formatting)

sourcery-ai · 2022-03-21T00:13:47Z

network2.py

-            print("Epoch %s training complete" % j)
+            print(f"Epoch {j} training complete")

            if monitor_training_cost:
                cost = self.total_cost(training_data, lmbda)
                training_cost.append(cost)
-                print("Cost on training data: {}".format(cost))
+                print(f"Cost on training data: {cost}")
            if monitor_training_accuracy:
                accuracy = self.accuracy(training_data, convert=True)
                training_accuracy.append(accuracy)
-                print("Accuracy on training data: {} / {}".format(accuracy, n))
+                print(f"Accuracy on training data: {accuracy} / {n}")
            if monitor_evaluation_cost:
                cost = self.total_cost(evaluation_data, lmbda, convert=True)
                evaluation_cost.append(cost)
-                print("Cost on evaluation data: {}".format(cost))
+                print(f"Cost on evaluation data: {cost}")
            if monitor_evaluation_accuracy:
                accuracy = self.accuracy(evaluation_data)
                evaluation_accuracy.append(accuracy)
-                print("Accuracy on evaluation data: {} / {}".format(self.accuracy(evaluation_data), n_data))
+                print(
+                    f"Accuracy on evaluation data: {self.accuracy(evaluation_data)} / {n_data}"
+                )
+


Function Network.SGD refactored with the following changes:

Replace interpolated string formatting with f-string (replace-interpolation-with-fstring)

Replace call to format with f-string. (use-fstring-for-formatting)

sourcery-ai · 2022-03-21T00:13:48Z

network2.py

-        result_accuracy = sum(int(x == y) for (x, y) in results)
-        return result_accuracy
+        return sum(int(x == y) for (x, y) in results)


Function Network.accuracy refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

sourcery-ai · 2022-03-21T00:13:48Z

network2.py

-        f = open(filename, "w")
-        json.dump(data, f)
-        f.close()
+        with open(filename, "w") as f:
+            json.dump(data, f)


Function Network.save refactored with the following changes:

Use with when opening file to ensure closure (ensure-file-closed)

sourcery-ai · 2022-03-21T00:13:48Z

network2.py

-    f = open(filename, "r")
-    data = json.load(f)
-    f.close()
+    with open(filename, "r") as f:
+        data = json.load(f)


Function load refactored with the following changes:

Use with when opening file to ensure closure (ensure-file-closed)

sourcery-ai · 2022-03-21T00:13:48Z

network3.py


        # define the (regularized) cost function, symbolic gradients, and updates
-        l2_norm_squared = sum([(layer.w**2).sum() for layer in self.layers])
+        l2_norm_squared = sum((layer.w**2).sum() for layer in self.layers)


Function Network.SGD refactored with the following changes:

Replace unneeded comprehension with generator (comprehension-to-generator)

sourcery-ai · 2022-03-21T00:13:48Z

test.py

-    for i in range(iters):
+    for _ in range(iters):
        r = f()
    t1 = time.time()
    print("Looping %d times took %f seconds" % (iters, t1 - t0))
-    print("Result is %s" % (r,))
+    print(f"Result is {r}")


Function testTheano refactored with the following changes:

Replace unused for index with underscore (for-index-underscore)

Replace interpolated string formatting with f-string (replace-interpolation-with-fstring)

sourcery-ai · 2022-03-21T00:13:57Z

Sourcery Code Quality Report

❌ Merging this PR will decrease code quality in the affected files by 0.03%.

Quality metrics	Before	After	Change
Complexity	5.75 ⭐	5.75 ⭐	0.00
Method Length	63.91 🙂	63.91 🙂	0.00
Working memory	11.93 😞	11.93 😞	0.00
Quality	61.08% 🙂	61.05% 🙂	-0.03% 👎

Other metrics	Before	After	Change
Lines	1037	1036	-1

Changed files	Quality Before	Quality After	Quality Change
expand_mnist.py	32.97% 😞	32.97% 😞	0.00%
mnist_svm.py	84.31% ⭐	84.55% ⭐	0.24% 👍
network.py	67.60% 🙂	67.44% 🙂	-0.16% 👎
network2.py	58.59% 🙂	58.07% 🙂	-0.52% 👎
network3.py	61.59% 🙂	61.59% 🙂	0.00%
test.py	71.84% 🙂	71.84% 🙂	0.00%

Here are some functions in these files that still need a tune-up:

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
network3.py	Network.SGD	18 🙂	409 ⛔	21 ⛔	21.65% ⛔	Try splitting into smaller methods. Extract out complex expressions
network2.py	Network.SGD	21 😞	244 ⛔	23 ⛔	23.20% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
network.py	Network.backprop	2 ⭐	170 😞	12 😞	55.30% 🙂	Try splitting into smaller methods. Extract out complex expressions
network2.py	Network.backprop	2 ⭐	168 😞	12 😞	55.49% 🙂	Try splitting into smaller methods. Extract out complex expressions
network2.py	Network.update_mini_batch	1 ⭐	127 😞	14 😞	57.91% 🙂	Try splitting into smaller methods. Extract out complex expressions

Legend and Explanation

The emojis denote the absolute quality of the code:

⭐ excellent
🙂 good
😞 poor
⛔ very poor

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!

'Refactored by Sourcery'

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sourcery-ai bot requested a review from brucew2099 March 21, 2022 00:13

sourcery-ai bot commented Mar 21, 2022

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Sourcery refactored master branch #1

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