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c87b9bdd7d
the tracks folder was relative of the main WSGI python file due to me using my sys.path[0] method of finding the current folder the file was in, unfortunately this ends up being unreliable when put into practice
117 lines
4.0 KiB
Python
117 lines
4.0 KiB
Python
import os
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import sys
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import json
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import logging
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import datetime
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import collections
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import numpy as np
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import dateutil.parser
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import PIL.Image as Image
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import matplotlib.pyplot as plt
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# Gets all files in tracks folder, returns them in parsed JSON
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def get_files():
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folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'tracks')
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files = []
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for file in os.listdir(folder):
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with open(os.path.join(os.path.join(folder, file))) as file:
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files.append(
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json.load(file)
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)
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return files
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# Simple function to combine a bunch of items from different files
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def combine_files(files):
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items = []
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for file in files:
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items.extend(file['items'])
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return items
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# Prints the data in a interesting format
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def print_data(data):
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for i, item in enumerate(data):
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date = dateutil.parser.parse(item['added_at'])
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explicit = '!' if item['track']['explicit'] else ' '
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track_name = item['track']['name']
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artists = ' & '.join(artist['name'] for artist in item['track']['artists'])
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print('[{}] {} "{}" by {}'.format(date, explicit, track_name, artists))
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def process_data(data):
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# Process the data by Month/Year, then by Clean/Explicit
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scores = {}
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for item in data:
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date = dateutil.parser.parse(item['added_at']).strftime('%b %Y')
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if date not in scores.keys():
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scores[date] = [0, 0]
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scores[date][1 if item['track']['explicit'] else 0] += 1
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# Create simplified arrays for each piece of data
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months = list(scores.keys())[::-1]
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clean, explicit = [], []
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for item in list(scores.values())[::-1]:
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clean.append(item[0])
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explicit.append(item[1])
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# Done processing date properly, start plotting work
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logging.info('Processed data, creating plot from data')
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# Weird numpy stuff
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n = len(scores.values())
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ind = np.arange(n)
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width = 0.55
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# Resizer figuresize to be 2.0 wider
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plt.figure(figsize=(10.0, 6.0))
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# Stacked Bars
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p1 = plt.bar(ind, explicit, width)
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p2 = plt.bar(ind, clean, width, bottom=explicit) # bottom= just has the bar sit on top of the explicit
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# Plot labeling
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plt.title('Song Count by Clean/Explicit')
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plt.ylabel('Song Count')
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plt.xlabel('Month')
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plt.xticks(ind, months, rotation=270) # Rotation 90 will have the
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plt.legend((p1[0], p2[0]), ('Explicit', 'Clean'))
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fig = plt.gcf() # Magic to save to image and then show
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# Save the figure, overwriting anything in your way
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logging.info('Saving the figure to the \'export\' folder')
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export_folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'export')
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if not os.path.exists(export_folder):
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os.makedirs(export_folder)
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plt.tight_layout()
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fig.savefig(
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os.path.join(
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export_folder,
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'export'
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# datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')
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),
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dpi=100,
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quality=95
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)
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# Finally show the figure to
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logging.info('Showing plot to User')
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# plt.show()
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# Copy the figure to your clipboard to paste in Excel
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# logging.info('Copying the plot data to clipboard')
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# copy(months, clean, explicit)
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# Simple method for exporting data to a table like format
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# Will paste into Excel very easily
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def copy(months, clean, explicit):
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from pyperclip import copy
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top = 'Period\tClean\tExplicit\n'
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copy(top + '\n'.join([
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f'{item[0]}\t{item[1]}\t{item[2]}' for item in zip(months, clean, explicit)
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]))
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def main():
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# logging.basicConfig(level=logging.INFO)
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logging.info("Reading track files")
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files = get_files()
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logging.info(f"Read and parse {len(files)} track files")
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logging.info("Combining into single track file for ease of access")
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data = combine_files(files)
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data.sort(key=lambda item : dateutil.parser.parse(item['added_at']).timestamp(), reverse=True)
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logging.info(f'File combined with {len(data)} items')
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logging.info('Processing file...')
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process_data(data) |