Merge pull request #664 from ipython/pre-commit-ci-update-config

[pre-commit.ci] pre-commit autoupdate

Author: minrk

.pre-commit-config.yaml

@@ -7,12 +7,12 @@ repos:
           - --py36-plus
         exclude: setupbase.py
   - repo: https://github.com/asottile/reorder_python_imports
-    rev: v2.6.0
+    rev: v2.7.1
     hooks:
       - id: reorder-python-imports
         exclude: setupbase.py
   - repo: https://github.com/psf/black
-    rev: 21.12b0
+    rev: 22.1.0
     hooks:
       - id: black
         exclude: setupbase.py
@@ -32,7 +32,7 @@ repos:
       - id: check-executables-have-shebangs
       - id: requirements-txt-fixer
   - repo: https://github.com/pre-commit/mirrors-eslint
-    rev: v8.7.0
+    rev: v8.8.0
     hooks:
       - id: eslint
         files: \.[jt]sx?$ # *.js, *.jsx, *.ts and *.tsx

benchmarks/profiling/profiling_code.py

@@ -54,13 +54,13 @@ def run_profiling(selected_profiling_task, selected_view):
 
     if selected_profiling_task == 'many_empty_tasks':
         for x in range(1, 5):
-            profile_many_empty_tasks(view, 10 ** x)
+            profile_many_empty_tasks(view, 10**x)
     elif selected_profiling_task == 'many_empty_tasks_non_blocking':
         for x in range(1, 5):
-            profile_many_empty_tasks(view, 10 ** x, block=False)
+            profile_many_empty_tasks(view, 10**x, block=False)
     elif selected_profiling_task == 'tasks_with_large_data':
         for x in range(1, 8):
-            profile_tasks_with_large_data(view, 10 ** x)
+            profile_tasks_with_large_data(view, 10**x)
     # elif selected_profiling_task == 'echo_many_arguments':
     #     for i in range(100):
     #         for number_of_arguments in ((2 ** x) - 1 for x in range(1, 9)):

docs/source/examples/wave2D/wavesolver.py

@@ -111,10 +111,10 @@ def __init__(
         xv = x[:, newaxis]  # for vectorized expressions with f(xv,yv)
         yv = y[newaxis, :]  # -- " --
         if dt <= 0:
-            dt = (1 / float(c)) * (1 / sqrt(1 / dx ** 2 + 1 / dy ** 2))  # max time step
+            dt = (1 / float(c)) * (1 / sqrt(1 / dx**2 + 1 / dy**2))  # max time step
         Cx2 = (c * dt / dx) ** 2
         Cy2 = (c * dt / dy) ** 2
-        dt2 = dt ** 2  # help variables
+        dt2 = dt**2  # help variables
 
         u = zeros((nx + 1, ny + 1))  # solution array
         u_1 = u.copy()  # solution at t-dt
@@ -216,10 +216,10 @@ def solve(self, tstop, dt=-1, user_action=None, verbose=False, final_test=False)
         xv = x[:, newaxis]  # for vectorized expressions with f(xv,yv)
         yv = y[newaxis, :]  # -- " --
         if dt <= 0:
-            dt = (1 / float(c)) * (1 / sqrt(1 / dx ** 2 + 1 / dy ** 2))  # max time step
+            dt = (1 / float(c)) * (1 / sqrt(1 / dx**2 + 1 / dy**2))  # max time step
         Cx2 = (c * dt / dx) ** 2
         Cy2 = (c * dt / dy) ** 2
-        dt2 = dt ** 2  # help variables
+        dt2 = dt**2  # help variables
         # id for the four possible neighbor subdomains
         lower_x_neigh = partitioner.lower_neighbors[0]
         upper_x_neigh = partitioner.upper_neighbors[0]

ipyparallel/controller/app.py

@@ -332,7 +332,7 @@ def _use_threads_changed(self, change):
 
     @default('number_of_leaf_schedulers')
     def get_number_of_leaf_schedulers(self):
-        return 2 ** self.broadcast_scheduler_depth
+        return 2**self.broadcast_scheduler_depth
 
     @default('number_of_broadcast_schedulers')
     def get_number_of_broadcast_schedulers(self):
@@ -812,7 +812,7 @@ def init_hub(self):
         broadcast_ids = []  # '0', '00', '01', '001', etc.
         # always a leading 0 for the root node
         for d in range(1, self.broadcast_scheduler_depth + 1):
-            for i in range(2 ** d):
+            for i in range(2**d):
                 broadcast_ids.append(format(i, f"0{d + 1}b"))
         self.internal_info = {
             'interface': internal_interface,

ipyparallel/controller/broadcast_scheduler.py

@@ -49,7 +49,7 @@ def send_to_targets(self, msg, original_msg_id, targets, idents, is_coalescing):
     def send_to_sub_schedulers(
         self, msg, original_msg_id, targets, idents, is_coalescing
     ):
-        trunc = 2 ** self.max_depth
+        trunc = 2**self.max_depth
         fmt = f"0{self.max_depth + 1}b"
 
         # assign targets to sub-schedulers based on binary path

ipyparallel/controller/dictdb.py

@@ -112,7 +112,7 @@ class DictDB(BaseDB):
     _buffer_bytes = Integer(0)  # running total of the bytes in the DB
 
     size_limit = Integer(
-        1024 ** 3,
+        1024**3,
         config=True,
         help="""The maximum total size (in bytes) of the buffers stored in the db
 

ipyparallel/tests/test_lbview.py

@@ -26,7 +26,7 @@ def test_z_crash(self):
 
     def test_map(self):
         def f(x):
-            return x ** 2
+            return x**2
 
         data = list(range(16))
         ar = self.view.map_async(f, data)
@@ -36,7 +36,7 @@ def f(x):
 
     def test_map_generator(self):
         def f(x):
-            return x ** 2
+            return x**2
 
         data = list(range(16))
         ar = self.view.map_async(f, iter(data))
@@ -77,13 +77,13 @@ def f(x, y):
 
     def test_map_unordered(self):
         def f(x):
-            return x ** 2
+            return x**2
 
         def slow_f(x):
             import time
 
             time.sleep(0.05 * x)
-            return x ** 2
+            return x**2
 
         data = list(range(16, 0, -1))
         reference = list(map(f, data))
@@ -101,13 +101,13 @@ def slow_f(x):
 
     def test_map_ordered(self):
         def f(x):
-            return x ** 2
+            return x**2
 
         def slow_f(x):
             import time
 
             time.sleep(0.05 * x)
-            return x ** 2
+            return x**2
 
         data = list(range(16, 0, -1))
         reference = list(map(f, data))

ipyparallel/tests/test_view.py

@@ -294,7 +294,7 @@ def test_push_pull_recarray(self):
         R = numpy.array(
             [
                 (1, 'hi', 0.0),
-                (2 ** 30, 'there', 2.5),
+                (2**30, 'there', 2.5),
                 (-99999, 'world', -12345.6789),
             ],
             [('n', int), ('s', '|S10'), ('f', float)],
@@ -331,7 +331,7 @@ def test_map(self):
         view = self.client[:]
 
         def f(x):
-            return x ** 2
+            return x**2
 
         data = list(range(16))
         ar = view.map_async(f, data)