properly add in spotify_explicit portion

app/spotify_explicit/process.py

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+import os
+import sys
+import json
+import logging
+import datetime
+import collections
+import numpy as np
+import dateutil.parser
+import PIL.Image as Image
+import matplotlib.pyplot as plt
+
+# Gets all files in tracks folder, returns them in parsed JSON
+def get_files():
+    folder = os.path.join(sys.path[0], '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)
+            )
+    return files
+
+# Simple function to combine a bunch of items from different files
+def combine_files(files):
+    items = []
+    for file in files:
+        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'])
+        print('[{}] {} "{}" by {}'.format(date, explicit, track_name, artists))
+
+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')
+        if date not in scores.keys():
+            scores[date] = [0, 0]
+        scores[date][1 if item['track']['explicit'] else 0] += 1
+    
+    # Create simplified arrays for each piece of data
+    months = list(scores.keys())[::-1]
+    clean, explicit = [], []
+    for item in list(scores.values())[::-1]:
+        clean.append(item[0])
+        explicit.append(item[1])
+
+    # Done processing date properly, start plotting work
+    logging.info('Processed data, creating plot from data')
+    # Weird numpy stuff
+    n = len(scores.values())
+    ind = np.arange(n)
+    width = 0.55
+    # Resizer figuresize to be 2.0 wider
+    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
+    # Plot labeling
+    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'))
+    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(sys.path[0], 'export')
+    if not os.path.exists(export_folder):
+        os.makedirs(export_folder)
+    plt.tight_layout()
+    fig.savefig(
+        os.path.join(
+            export_folder,
+            'export'
+            # datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')
+        ),
+        dpi=100,
+        quality=95
+    )
+    
+    # Finally show the figure to 
+    logging.info('Showing plot to User')
+    # plt.show()
+
+    # Copy the figure to your clipboard to paste in Excel
+    # logging.info('Copying the plot data to clipboard')
+    # copy(months, clean, explicit)
+
+# Simple method for exporting data to a table like format
+# 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)
+    ]))
+
+def main():
+    # logging.basicConfig(level=logging.INFO)
+    logging.info("Reading track files")
+    files = get_files()
+    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...')
+    process_data(data)