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63 lines
1.6 KiB
63 lines
1.6 KiB
import csv
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import arrow
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import os
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import collections
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import json
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import re
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import matplotlib
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ref_time = arrow.get()
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data_dir = '/Users/fluffy/Library/Mobile Documents/iCloud~com~ifunography~HealthExport/Documents/'
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start_time, _ = ref_time.shift(days=-30).span('day')
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_, end_time = ref_time.span('day', bounds='[]')
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metrics = collections.defaultdict(list)
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def filter(date):
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if date >= start_time and date < end_time:
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return date
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return None
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def scan_dir(path):
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for file in os.scandir(path):
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if file.is_dir():
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scan_dir(file.path)
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elif file.is_file():
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scan_file(file)
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def scan_file(file):
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match = re.match(r'HealthAutoExport-([0-9\-]+)\.json', file.name)
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if not match:
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return
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file_date = arrow.get(match[1])
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if filter(file_date):
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file_data = json.load(open(file.path,'r'))
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scan_metrics(file_data['data']['metrics'])
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def get_value(item):
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if 'qty' in item:
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return item['qty']
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elif 'Avg' in item:
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return item['Avg']
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elif 'asleep' in item:
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print(item)
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return None
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else:
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raise KeyError(f"unknown format; keys: {item.keys()}")
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def scan_metrics(data):
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for metric in data:
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if len(data):
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sink = metrics[metric['name']]
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for item in metric['data']:
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if when := filter(arrow.get(item['date'], 'YYYY-MM-DD HH:mm:ss Z')):
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sink.append((when, item))
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scan_dir(data_dir)
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metrics = {k:sorted(v,key=lambda i:i[0]) for k,v in metrics.items() if len(v)}
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for key,vals in metrics.items():
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print(key,len(vals))
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