[522] black formatting

monocongo · Sep 19, 2023 · e20eb3e · e20eb3e
1 parent ead6196
commit e20eb3e
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Showing 18 changed files with 1,710 additions and 1,776 deletions.
diff --git a/docs/conf.py b/docs/conf.py
@@ -18,7 +18,7 @@
 import toml
 
 # since our source files are under a src folder we need to add that as our first path
-sys.path.insert(0, os.path.abspath('../src'))
+sys.path.insert(0, os.path.abspath("../src"))
 
 # -- Project information -----------------------------------------------------
 
@@ -29,10 +29,10 @@
 pyproject = toml.load("../pyproject.toml")
 
 # get the full release version, including alpha/beta/rc tags
-release = pyproject['tool']['poetry']['version']
+release = pyproject["tool"]["poetry"]["version"]
 
 # get the major.minor version
-version = '.'.join(release.split('.')[:2])
+version = ".".join(release.split(".")[:2])
 
 # -- General configuration ---------------------------------------------------
 
@@ -149,9 +149,7 @@
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [
-    (master_doc, "climate_indices", "climate_indices Documentation", [author], 1)
-]
+man_pages = [(master_doc, "climate_indices", "climate_indices Documentation", [author], 1)]
 
 
 # -- Options for Texinfo output ----------------------------------------------

diff --git a/notebooks/concurrent_shared_memory_example.ipynb b/notebooks/concurrent_shared_memory_example.ipynb
@@ -22,7 +22,7 @@
    "outputs": [],
    "source": [
     "# create a large array of random values\n",
-    "random = np.random.rand(400,400,1200)"
+    "random = np.random.rand(400, 400, 1200)"
    ]
   },
   {
@@ -34,7 +34,7 @@
     "# create a shared memory array for the input and result arrays, copying the original input data\n",
     "shm_random = shared_memory.SharedMemory(create=True, size=random.data.nbytes)\n",
     "shared_random = np.ndarray(random.shape, dtype=random.dtype, buffer=shm_random.buf)\n",
-    "shared_random[:,:,:] = random[:,:,:]\n",
+    "shared_random[:, :, :] = random[:, :, :]\n",
     "shm_name_random = shm_random.name\n",
     "\n",
     "shm_result = shared_memory.SharedMemory(create=True, size=random.data.nbytes)\n",
@@ -61,12 +61,21 @@
     "def shm_add_average(\n",
     "    arguments: Dict,\n",
     "):\n",
-    "    existing_shm_input = shared_memory.SharedMemory(name=arguments['shm_name_input'])\n",
-    "    shm_ary_input = np.ndarray(shape=arguments['shape'], dtype=arguments['dtype'], buffer=existing_shm_input.buf)\n",
-    "    existing_shm_result = shared_memory.SharedMemory(name=arguments['shm_name_result'])\n",
-    "    shm_ary_result = np.ndarray(shape=arguments['shape'], dtype=arguments['dtype'], buffer=existing_shm_result.buf)\n",
-    "    shm_ary_result[arguments['lat_index'], arguments['lon_index']] = \\\n",
-    "        add_average(shm_ary_input[arguments['lat_index'], arguments['lon_index']])"
+    "    existing_shm_input = shared_memory.SharedMemory(name=arguments[\"shm_name_input\"])\n",
+    "    shm_ary_input = np.ndarray(\n",
+    "        shape=arguments[\"shape\"],\n",
+    "        dtype=arguments[\"dtype\"],\n",
+    "        buffer=existing_shm_input.buf,\n",
+    "    )\n",
+    "    existing_shm_result = shared_memory.SharedMemory(name=arguments[\"shm_name_result\"])\n",
+    "    shm_ary_result = np.ndarray(\n",
+    "        shape=arguments[\"shape\"],\n",
+    "        dtype=arguments[\"dtype\"],\n",
+    "        buffer=existing_shm_result.buf,\n",
+    "    )\n",
+    "    shm_ary_result[arguments[\"lat_index\"], arguments[\"lon_index\"]] = add_average(\n",
+    "        shm_ary_input[arguments[\"lat_index\"], arguments[\"lon_index\"]]\n",
+    "    )"
    ]
   },
   {
@@ -88,20 +97,18 @@
     "arguments_list = []\n",
     "for lat_index in range(shared_random.shape[0]):\n",
     "    for lon_index in range(shared_random.shape[1]):\n",
-    "\n",
     "        arguments = {\n",
-    "            'lat_index': lat_index,\n",
-    "            'lon_index': lon_index,\n",
-    "            'shm_name_input': shm_name_random,\n",
-    "            'shm_name_result': shm_name_result,\n",
-    "            'dtype': shared_random.dtype,\n",
-    "            'shape': shared_random.shape\n",
+    "            \"lat_index\": lat_index,\n",
+    "            \"lon_index\": lon_index,\n",
+    "            \"shm_name_input\": shm_name_random,\n",
+    "            \"shm_name_result\": shm_name_result,\n",
+    "            \"dtype\": shared_random.dtype,\n",
+    "            \"shape\": shared_random.shape,\n",
     "        }\n",
     "        arguments_list.append(arguments)\n",
     "\n",
     "# use a ProcessPoolExecutor to download the images in parallel\n",
     "with concurrent.futures.ProcessPoolExecutor(max_workers=cpu_count()) as executor:\n",
-    "\n",
     "    # use the executor to map the download function to the iterable of arguments\n",
     "    executor.map(shm_add_average, arguments_list)"
    ]