Fix bug code dependencies

Makefile

@@ -2,7 +2,7 @@
 COV=pytest --cov --cov-config=pyproject.toml
 
 develop:
-	pdm install
+	pdm sync --clean
 
 black:
 	black -l 82 src _transonic_testing data_tests tests

data_tests/saved__backend__/cython/block_fluidsim.py

@@ -11,7 +11,7 @@ def rk2_step0(state_spect_n12, state_spect, tendencies_n, diss2, dt):
     #     float64[][] diss2;
     #     float dt
     # )
-    state_spect_n12[:] = (state_spect + ((dt / 2) * tendencies_n)) * diss2
+    state_spect_n12[:] = (state_spect + dt / 2 * tendencies_n) * diss2
 
 
 arguments_blocks = {

data_tests/saved__backend__/cython/blocks_type_hints.py

@@ -13,8 +13,7 @@ def block0(a, b, n):
     #     int[:] a, b;
     #     float n
     # )
-    result = ((a**2) + (b.mean() ** 3)) + n
-
+    result = a**2 + b.mean() ** 3 + n
     return result
 
 

data_tests/saved__backend__/cython/boosted_class_use_import.py

@@ -4,11 +4,11 @@
     from transonic_cl import cython
 
 import numpy as np
-from exterior_import_boost import func_import
+from __ext__MyClass2__exterior_import_boost import func_import
 
 
 def __for_method__MyClass2__myfunc(self_attr0, self_attr1, arg):
-    return ((self_attr1 + self_attr0) + np.abs(arg)) + func_import()
+    return self_attr1 + self_attr0 + np.abs(arg) + func_import()
 
 
 __code_new_method__MyClass2__myfunc = """

data_tests/saved__backend__/cython/boosted_func_use_import.py

@@ -4,7 +4,7 @@
     from transonic_cl import cython
 
 import numpy as np
-from exterior_import_boost import func_import
+from __ext__func__exterior_import_boost import func_import
 
 
 def func(a, b):

data_tests/saved__backend__/cython/class_blocks.py

@@ -20,8 +20,7 @@ def block0(a, b, n):
     # foobar
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
-
+        result += a**2 + b**3
     return result
 
 
@@ -36,8 +35,7 @@ def block1(a, b, n):
     # )
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
-
+        result += a**2 + b**3
     return result
 
 

data_tests/saved__backend__/cython/class_rec_calls.py

@@ -5,15 +5,17 @@
 
 
 def __for_method__Myclass__func(self_attr, self_attr2, arg):
-    if __for_method__Myclass__func(self_attr, self_attr2, (arg - 1)) < 1:
+    if __for_method__Myclass__func(self_attr, self_attr2, arg - 1) < 1:
         return 1
     else:
         a = __for_method__Myclass__func(
-            self_attr, self_attr2, (arg - 1)
-        ) * __for_method__Myclass__func(self_attr, self_attr2, (arg - 1))
+            self_attr, self_attr2, arg - 1
+        ) * __for_method__Myclass__func(self_attr, self_attr2, arg - 1)
         return (
-            a + ((self_attr * self_attr2) * arg)
-        ) + __for_method__Myclass__func(self_attr, self_attr2, (arg - 1))
+            a
+            + self_attr * self_attr2 * arg
+            + __for_method__Myclass__func(self_attr, self_attr2, arg - 1)
+        )
 
 
 __code_new_method__Myclass__func = """

data_tests/saved__backend__/cython/methods.py

@@ -7,8 +7,8 @@
 
 
 def __for_method__Transmitter____call__(self_arr, self_freq, inp):
-    "My docstring"
-    return ((inp * np.exp(((np.arange(len(inp)) * self_freq) * 1j))), self_arr)
+    """My docstring"""
+    return (inp * np.exp(np.arange(len(inp)) * self_freq * 1j), self_arr)
 
 
 __code_new_method__Transmitter____call__ = """

data_tests/saved__backend__/cython/row_sum_boost.py

@@ -17,12 +17,12 @@ def row_sum(arr, columns):
 def row_sum_loops(arr, columns):
     # locals type annotations are used only for Cython
     # arr.dtype not supported for memoryview
-    dtype = type(arr[(0, 0)])
+    dtype = type(arr[0, 0])
     res = np.empty(arr.shape[0], dtype=dtype)
     for i in range(arr.shape[0]):
         sum_ = dtype(0)
         for j in range(columns.shape[0]):
-            sum_ += arr[(i, columns[j])]
+            sum_ += arr[i, columns[j]]
         res[i] = sum_
     return res
 

data_tests/saved__backend__/numba/block_fluidsim.py

@@ -9,7 +9,7 @@ def rk2_step0(state_spect_n12, state_spect, tendencies_n, diss2, dt):
     #     float64[][] diss2;
     #     float dt
     # )
-    state_spect_n12[:] = (state_spect + ((dt / 2) * tendencies_n)) * diss2
+    state_spect_n12[:] = (state_spect + dt / 2 * tendencies_n) * diss2
 
 
 arguments_blocks = {

data_tests/saved__backend__/numba/blocks_type_hints.py

@@ -11,7 +11,7 @@ def block0(a, b, n):
     #     int[:] a, b;
     #     float n
     # )
-    result = ((a**2) + (b.mean() ** 3)) + n
+    result = a**2 + b.mean() ** 3 + n
     return result
 
 

data_tests/saved__backend__/numba/boosted_class_use_import.py

@@ -1,12 +1,12 @@
 # __protected__ from numba import njit
 import numpy as np
-from exterior_import_boost import func_import
+from __ext__MyClass2__exterior_import_boost import func_import
 
 # __protected__ @njit(cache=True, fastmath=True)
 
 
 def __for_method__MyClass2__myfunc(self_attr0, self_attr1, arg):
-    return ((self_attr1 + self_attr0) + np.abs(arg)) + func_import()
+    return self_attr1 + self_attr0 + np.abs(arg) + func_import()
 
 
 __code_new_method__MyClass2__myfunc = "\n\ndef new_method(self, arg):\n    return backend_func(self.attr0, self.attr1, arg)\n\n"

data_tests/saved__backend__/numba/boosted_func_use_import.py

@@ -1,6 +1,6 @@
 # __protected__ from numba import njit
 import numpy as np
-from exterior_import_boost import func_import
+from __ext__func__exterior_import_boost import func_import
 
 # __protected__ @njit(cache=True, fastmath=True)
 

data_tests/saved__backend__/numba/class_blocks.py

@@ -18,7 +18,7 @@ def block0(a, b, n):
     # foobar
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
+        result += a**2 + b**3
     return result
 
 
@@ -36,7 +36,7 @@ def block1(a, b, n):
     # )
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
+        result += a**2 + b**3
     return result
 
 

data_tests/saved__backend__/numba/class_rec_calls.py

@@ -3,15 +3,17 @@
 
 
 def __for_method__Myclass__func(self_attr, self_attr2, arg):
-    if __for_method__Myclass__func(self_attr, self_attr2, (arg - 1)) < 1:
+    if __for_method__Myclass__func(self_attr, self_attr2, arg - 1) < 1:
         return 1
     else:
         a = __for_method__Myclass__func(
-            self_attr, self_attr2, (arg - 1)
-        ) * __for_method__Myclass__func(self_attr, self_attr2, (arg - 1))
+            self_attr, self_attr2, arg - 1
+        ) * __for_method__Myclass__func(self_attr, self_attr2, arg - 1)
         return (
-            a + ((self_attr * self_attr2) * arg)
-        ) + __for_method__Myclass__func(self_attr, self_attr2, (arg - 1))
+            a
+            + self_attr * self_attr2 * arg
+            + __for_method__Myclass__func(self_attr, self_attr2, arg - 1)
+        )
 
 
 __code_new_method__Myclass__func = "\n\ndef new_method(self, arg):\n    return backend_func(self.attr, self.attr2, arg)\n\n"

data_tests/saved__backend__/numba/methods.py

@@ -5,8 +5,8 @@
 
 
 def __for_method__Transmitter____call__(self_arr, self_freq, inp):
-    "My docstring"
-    return ((inp * np.exp(((np.arange(len(inp)) * self_freq) * 1j))), self_arr)
+    """My docstring"""
+    return (inp * np.exp(np.arange(len(inp)) * self_freq * 1j), self_arr)
 
 
 __code_new_method__Transmitter____call__ = "\n\ndef new_method(self, inp):\n    return backend_func(self.arr, self.freq, inp)\n\n"

data_tests/saved__backend__/numba/row_sum_boost.py

@@ -14,12 +14,12 @@ def row_sum(arr, columns):
 def row_sum_loops(arr, columns):
     # locals type annotations are used only for Cython
     # arr.dtype not supported for memoryview
-    dtype = type(arr[(0, 0)])
+    dtype = type(arr[0, 0])
     res = np.empty(arr.shape[0], dtype=dtype)
     for i in range(arr.shape[0]):
         sum_ = dtype(0)
         for j in range(columns.shape[0]):
-            sum_ += arr[(i, columns[j])]
+            sum_ += arr[i, columns[j]]
         res[i] = sum_
     return res
 

data_tests/saved__backend__/python/block_fluidsim.py

@@ -5,7 +5,7 @@ def rk2_step0(state_spect_n12, state_spect, tendencies_n, diss2, dt):
     #     float64[][] diss2;
     #     float dt
     # )
-    state_spect_n12[:] = (state_spect + ((dt / 2) * tendencies_n)) * diss2
+    state_spect_n12[:] = (state_spect + dt / 2 * tendencies_n) * diss2
 
 
 arguments_blocks = {

data_tests/saved__backend__/python/blocks_type_hints.py

@@ -7,8 +7,7 @@ def block0(a, b, n):
     #     int[:] a, b;
     #     float n
     # )
-    result = ((a**2) + (b.mean() ** 3)) + n
-
+    result = a**2 + b.mean() ** 3 + n
     return result
 
 

data_tests/saved__backend__/python/boosted_class_use_import.py

@@ -1,9 +1,9 @@
 import numpy as np
-from exterior_import_boost import func_import
+from __ext__MyClass2__exterior_import_boost import func_import
 
 
 def __for_method__MyClass2__myfunc(self_attr0, self_attr1, arg):
-    return ((self_attr1 + self_attr0) + np.abs(arg)) + func_import()
+    return self_attr1 + self_attr0 + np.abs(arg) + func_import()
 
 
 __code_new_method__MyClass2__myfunc = """

data_tests/saved__backend__/python/boosted_func_use_import.py

@@ -1,5 +1,5 @@
 import numpy as np
-from exterior_import_boost import func_import
+from __ext__func__exterior_import_boost import func_import
 
 
 def func(a, b):

data_tests/saved__backend__/python/class_blocks.py

@@ -15,8 +15,7 @@ def block0(a, b, n):
     # foobar
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
-
+        result += a**2 + b**3
     return result
 
 
@@ -31,8 +30,7 @@ def block1(a, b, n):
     # )
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
-
+        result += a**2 + b**3
     return result
 
 

data_tests/saved__backend__/python/class_rec_calls.py

@@ -1,13 +1,15 @@
 def __for_method__Myclass__func(self_attr, self_attr2, arg):
-    if __for_method__Myclass__func(self_attr, self_attr2, (arg - 1)) < 1:
+    if __for_method__Myclass__func(self_attr, self_attr2, arg - 1) < 1:
         return 1
     else:
         a = __for_method__Myclass__func(
-            self_attr, self_attr2, (arg - 1)
-        ) * __for_method__Myclass__func(self_attr, self_attr2, (arg - 1))
+            self_attr, self_attr2, arg - 1
+        ) * __for_method__Myclass__func(self_attr, self_attr2, arg - 1)
         return (
-            a + ((self_attr * self_attr2) * arg)
-        ) + __for_method__Myclass__func(self_attr, self_attr2, (arg - 1))
+            a
+            + self_attr * self_attr2 * arg
+            + __for_method__Myclass__func(self_attr, self_attr2, arg - 1)
+        )
 
 
 __code_new_method__Myclass__func = """

data_tests/saved__backend__/python/methods.py

@@ -2,8 +2,8 @@
 
 
 def __for_method__Transmitter____call__(self_arr, self_freq, inp):
-    "My docstring"
-    return ((inp * np.exp(((np.arange(len(inp)) * self_freq) * 1j))), self_arr)
+    """My docstring"""
+    return (inp * np.exp(np.arange(len(inp)) * self_freq * 1j), self_arr)
 
 
 __code_new_method__Transmitter____call__ = """

data_tests/saved__backend__/python/row_sum_boost.py

@@ -8,12 +8,12 @@ def row_sum(arr, columns):
 def row_sum_loops(arr, columns):
     # locals type annotations are used only for Cython
     # arr.dtype not supported for memoryview
-    dtype = type(arr[(0, 0)])
+    dtype = type(arr[0, 0])
     res = np.empty(arr.shape[0], dtype=dtype)
     for i in range(arr.shape[0]):
         sum_ = dtype(0)
         for j in range(columns.shape[0]):
-            sum_ += arr[(i, columns[j])]
+            sum_ += arr[i, columns[j]]
         res[i] = sum_
     return res
 

data_tests/saved__backend__/pythran/block_fluidsim.py

@@ -5,7 +5,7 @@ def rk2_step0(state_spect_n12, state_spect, tendencies_n, diss2, dt):
     #     float64[][] diss2;
     #     float dt
     # )
-    state_spect_n12[:] = (state_spect + ((dt / 2) * tendencies_n)) * diss2
+    state_spect_n12[:] = (state_spect + dt / 2 * tendencies_n) * diss2
 
 
 arguments_blocks = {

data_tests/saved__backend__/pythran/blocks_type_hints.py

@@ -7,8 +7,7 @@ def block0(a, b, n):
     #     int[:] a, b;
     #     float n
     # )
-    result = ((a**2) + (b.mean() ** 3)) + n
-
+    result = a**2 + b.mean() ** 3 + n
     return result
 
 

data_tests/saved__backend__/pythran/boosted_class_use_import.py

@@ -3,7 +3,7 @@
 
 
 def __for_method__MyClass2__myfunc(self_attr0, self_attr1, arg):
-    return ((self_attr1 + self_attr0) + np.abs(arg)) + func_import()
+    return self_attr1 + self_attr0 + np.abs(arg) + func_import()
 
 
 __code_new_method__MyClass2__myfunc = """

data_tests/saved__backend__/pythran/class_blocks.py

@@ -15,8 +15,7 @@ def block0(a, b, n):
     # foobar
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
-
+        result += a**2 + b**3
     return result
 
 
@@ -31,8 +30,7 @@ def block1(a, b, n):
     # )
     result = np.zeros_like(a)
     for _ in range(n):
-        result += (a**2) + (b**3)
-
+        result += a**2 + b**3
     return result