'Refactored by Sourcery'

Author: Sourcery AI

source-code/cython/Classes/points_python.py

@@ -18,15 +18,15 @@ def x(self) -> float:
 
     @x.setter
     def x(self, value: float) -> None:
-        self._x = float(value)
+        self._x = value
 
     @property
     def y(self) -> float:
         return self._y
 
     @y.setter
     def y(self, value: float) -> None:
-        self._y = float(value)
+        self._y = value
 
     def __str__(self) -> str:
         return f"Point({self.x}, {self.y})"

source-code/cython/Numpy/compute_sums.py

@@ -28,7 +28,7 @@ def py_sum(a):
     for func in [array_sum.array_sum, array_sum_pure.array_sum, np.sum, py_sum]:
         total = 0.0
         start_time = timeit.default_timer()
-        for iter_nr in range(options.iter):
+        for _ in range(options.iter):
             total += func(a)
         total_time = timeit.default_timer() - start_time
         print(f'{func.__qualname__:s}: {total_time:.6f} s ({total})')

source-code/cython/Numpy/run_cythonized_sum.py

@@ -27,7 +27,7 @@ def py_sum(a):
     for func in [array_sum_pure.array_sum, py_sum]:
         total = 0.0
         start_time = timeit.default_timer()
-        for iter_nr in range(options.iter):
+        for _ in range(options.iter):
             total += func(a)
         total_time = timeit.default_timer() - start_time
         print(f'{func.__qualname__:s}: {total_time:.6f} s ({total})')

source-code/cython/Numpy/run_pure_sum.py

@@ -24,7 +24,7 @@ def py_sum(a):
     for func in [array_sum_pure.array_sum, py_sum]:
         total = 0.0
         start_time = timeit.default_timer()
-        for iter_nr in range(options.iter):
+        for _ in range(options.iter):
             total += func(a)
         total_time = timeit.default_timer() - start_time
         print(f'{func.__qualname__:s}: {total_time:.6f} s ({total})')

source-code/cython/Primes/primes_pure_malloc.py

@@ -21,6 +21,6 @@ def primes(nb_primes: cython.int):
         n += 1
 
     # Let's copy the result into a Python list:
-    result_as_list = [prime for prime in p[:len_p]]
+    result_as_list = list(p[:len_p])
     free(p)
     return result_as_list

source-code/cython/Primes/primes_pure_python.py

@@ -4,9 +4,7 @@ def primes(nb_primes: cython.int):
     i: cython.int
     p: cython.int[1000]
 
-    if nb_primes > 1000:
-        nb_primes = 1000
-
+    nb_primes = min(nb_primes, 1000)
     if not cython.compiled:  # Only if regular Python is running
         p = [0] * 1000       # Make p work almost like a C array
 
@@ -24,6 +22,4 @@ def primes(nb_primes: cython.int):
             len_p += 1
         n += 1
 
-    # Let's copy the result into a Python list:
-    result_as_list = [prime for prime in p[:len_p]]
-    return result_as_list
+    return list(p[:len_p])

source-code/cython/Primes/primes_vanilla.py

@@ -1,17 +1,16 @@
 def primes(kmax):
     p = [0]*1000
     result = []
-    if kmax > 1000:
-        kmax = 1000
+    kmax = min(kmax, 1000)
     k = 0
     n = 2
     while k < kmax:
         i = 0
         while i < k and n % p[i] != 0:
-            i = i + 1
+            i += 1
         if i == k:
             p[k] = n
-            k = k + 1
+            k += 1
             result.append(n)
         n = n + 1
     return result

source-code/numpy-scipy/fancy_indexing.py

@@ -73,7 +73,7 @@ def main():
             timings[algo].append(timeit.timeit(lambda: algo(A, B), number=1))
             print(f'{algo.__name__},{args.n},{i},{timings[algo][-1]:.6f}')
     print('summary:')
-    min_time = min([np.mean(timings[algo]) for algo in algorithms])
+    min_time = min(np.mean(timings[algo]) for algo in algorithms)
     print('  algorithm,n,repetitions,mean,std,relative')
     for algo in algorithms:
         print(f'  {algo.__name__},{args.n},{args.r},{np.mean(timings[algo]):.6f},{np.std(timings[algo]):.6f},{np.mean(timings[algo]) / min_time:.2f}')

source-code/performance/cellular_automata/cellular_automaton.py

@@ -39,9 +39,10 @@ def evolve_random(self, nr_cells, nr_generations, handler, seed=None):
         self.evolve(automaton, nr_generations, handler)
 
     def __str__(self):
-        auto_str = ''
-        for i, result in enumerate(self._rules):
-            auto_str += f'{i//4 % 2}{i//2 % 2}{i % 2} -> {result}\n'
+        auto_str = ''.join(
+            f'{i // 4 % 2}{i // 2 % 2}{i % 2} -> {result}\n'
+            for i, result in enumerate(self._rules)
+        )
         return auto_strgggg
 
 def do_nothing_handler(automaton):