PyCharm grand repo wide reformat with black formatter

app/spotify_explicit/process.py

@@ -9,13 +9,11 @@ import numpy as np
 
 # Gets all files in tracks folder, returns them in parsed JSON
 def get_files():
-    folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'tracks')
+    folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), "tracks")
     files = []
     for file in os.listdir(folder):
         with open(os.path.join(os.path.join(folder, file))) as file:
-            files.append(
-                json.load(file)
-            )
+            files.append(json.load(file))
     return files
 
 
@@ -23,17 +21,17 @@ def get_files():
 def combine_files(files):
     items = []
     for file in files:
-        items.extend(file['items'])
+        items.extend(file["items"])
     return items
 
 
 # Prints the data in a interesting format
 def print_data(data):
     for i, item in enumerate(data):
-        date = dateutil.parser.parse(item['added_at'])
-        explicit = '!' if item['track']['explicit'] else ' '
-        track_name = item['track']['name']
-        artists = ' & '.join(artist['name'] for artist in item['track']['artists'])
+        date = dateutil.parser.parse(item["added_at"])
+        explicit = "!" if item["track"]["explicit"] else " "
+        track_name = item["track"]["name"]
+        artists = " & ".join(artist["name"] for artist in item["track"]["artists"])
         print('[{}] {} "{}" by {}'.format(date, explicit, track_name, artists))
 
 
@@ -41,10 +39,10 @@ def process_data(data):
     # Process the data by Month/Year, then by Clean/Explicit
     scores = {}
     for item in data:
-        date = dateutil.parser.parse(item['added_at']).strftime('%b %Y')
+        date = dateutil.parser.parse(item["added_at"]).strftime("%b %Y")
         if date not in scores.keys():
             scores[date] = [0, 0]
-        scores[date][1 if item['track']['explicit'] else 0] += 1
+        scores[date][1 if item["track"]["explicit"] else 0] += 1
 
     # Create simplified arrays for each piece of data
     months = list(scores.keys())[::-1]
@@ -54,7 +52,7 @@ def process_data(data):
         explicit.append(item[1])
 
     # Done processing date properly, start plotting work
-    logging.info('Processed data, creating plot from data')
+    logging.info("Processed data, creating plot from data")
     # Weird numpy stuff
     n = len(scores.values())
     ind = np.arange(n)
@@ -63,33 +61,35 @@ def process_data(data):
     plt.figure(figsize=(10.0, 6.0))
     # Stacked Bars
     p1 = plt.bar(ind, explicit, width)
-    p2 = plt.bar(ind, clean, width, bottom=explicit)  # bottom= just has the bar sit on top of the explicit
+    p2 = plt.bar(
+        ind, clean, width, bottom=explicit
+    )  # bottom= just has the bar sit on top of the explicit
     # Plot labeling
-    plt.title('Song Count by Clean/Explicit')
-    plt.ylabel('Song Count')
-    plt.xlabel('Month')
+    plt.title("Song Count by Clean/Explicit")
+    plt.ylabel("Song Count")
+    plt.xlabel("Month")
     plt.xticks(ind, months, rotation=270)  # Rotation 90 will have the
-    plt.legend((p1[0], p2[0]), ('Explicit', 'Clean'))
+    plt.legend((p1[0], p2[0]), ("Explicit", "Clean"))
     fig = plt.gcf()  # Magic to save to image and then show
 
     # Save the figure, overwriting anything in your way
-    logging.info('Saving the figure to the \'export\' folder')
-    export_folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'export')
+    logging.info("Saving the figure to the 'export' folder")
+    export_folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), "export")
     if not os.path.exists(export_folder):
         os.makedirs(export_folder)
     plt.tight_layout()
     fig.savefig(
         os.path.join(
             export_folder,
-            'export'
+            "export"
             # datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')
         ),
         dpi=100,
-        quality=95
+        quality=95,
     )
 
-    # Finally show the figure to 
-    logging.info('Showing plot to User')
+    # Finally show the figure to
+    logging.info("Showing plot to User")
     # plt.show()
 
     # Copy the figure to your clipboard to paste in Excel
@@ -101,10 +101,17 @@ def process_data(data):
 # Will paste into Excel very easily
 def copy(months, clean, explicit):
     from pyperclip import copy
-    top = 'Period\tClean\tExplicit\n'
-    copy(top + '\n'.join([
-        f'{item[0]}\t{item[1]}\t{item[2]}' for item in zip(months, clean, explicit)
-    ]))
+
+    top = "Period\tClean\tExplicit\n"
+    copy(
+        top
+        + "\n".join(
+            [
+                f"{item[0]}\t{item[1]}\t{item[2]}"
+                for item in zip(months, clean, explicit)
+            ]
+        )
+    )
 
 
 def main():
@@ -114,7 +121,10 @@ def main():
     logging.info(f"Read and parse {len(files)} track files")
     logging.info("Combining into single track file for ease of access")
     data = combine_files(files)
-    data.sort(key=lambda item: dateutil.parser.parse(item['added_at']).timestamp(), reverse=True)
-    logging.info(f'File combined with {len(data)} items')
-    logging.info('Processing file...')
+    data.sort(
+        key=lambda item: dateutil.parser.parse(item["added_at"]).timestamp(),
+        reverse=True,
+    )
+    logging.info(f"File combined with {len(data)} items")
+    logging.info("Processing file...")
     process_data(data)