172 lines
4.7 KiB
Python
172 lines
4.7 KiB
Python
from pathlib import Path
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from datetime import datetime
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from collections import Counter
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from functools import reduce
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import re
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import string
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import sys
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from common import parse_foods_file
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foods, recipes = parse_foods_file()
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if len(sys.argv) > 1:
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value, name = sys.argv[1:]
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value = float(value.removesuffix('g'))
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if name in recipes:
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food = recipes[name]
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if value == 0.0:
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value = food['TOTAL']
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food = {k: v*(value/food['TOTAL']) for k,v in food.items()}
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elif name in foods:
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if value == 0.0:
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value = 100
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food = {k: v*(value/100.0) for k,v in foods[name].items()}
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else:
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breakpoint()
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print(f'ERROR: Invalid diet entry: {content}')
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from pprint import pprint
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pprint(food)
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exit(0)
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entry_re = re.compile(r'^(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}) ', re.MULTILINE)
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diet_re = re.compile(r'@diet (\d+g) ([a-zA-Z]+)')
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total_entries = 0
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total_words = 0
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word_frequency = Counter()
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total_csv = [['day', 'entries', 'words']]
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daily_csv = [['day', 'entries', 'words', 'calories', 'carbs', 'fat', 'protein',
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'sugar']]
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entry_csv = [['timestamp', 'words']]
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words_csv = [['word', 'count']]
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diet_csv = [[
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'timestamp', 'name', 'grams', 'calories', 'carbs', 'fat', 'protein',
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'saturated_fat', 'sugar', 'fiber'
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]]
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output = open('diet', 'w')
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for fpath in sorted((Path.home() / 'workspace' / 'journal').glob('*.md')):
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day = fpath.stem
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header, *tmp = entry_re.split(fpath.read_text())
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entries = list(zip(tmp[::2], tmp[1::2]))
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daily_entries = len(entries)
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daily_words = 0
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daily_calories = 0.0
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daily_protein = 0.0
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daily_carbs = 0.0
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daily_fat = 0.0
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daily_sugar = 0.0
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output.write(f'-- {day}\n')
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for (timestamp, content) in sorted(entries, key=lambda x: x[0]):
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ts_str = timestamp
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timestamp = int(datetime.strptime(timestamp, '%Y-%m-%d %H:%M:%S').timestamp())
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content = '\n'.join(
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part.replace('\n', ' ')
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for part in content.split('\n\n')
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)
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for diet in diet_re.finditer(content):
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value, name = diet.groups()
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output.write(f'{ts_str} {name} {value}\n')
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value = float(value.removesuffix('g'))
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if name in recipes:
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food = recipes[name]
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if value == 0.0:
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value = food['TOTAL']
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food = {k: v*(value/food['TOTAL']) for k,v in food.items()}
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elif name in foods:
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if value == 0.0:
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value = 100
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food = {k: v*(value/100.0) for k,v in foods[name].items()}
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else:
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breakpoint()
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print(f'ERROR: Invalid diet entry: {content}')
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continue
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diet_csv.append((
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timestamp,
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name,
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value,
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round(food.get('Energy', 0.0), 2),
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round(food.get('Carbs', 0.0), 2),
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round(food.get('Fat', 0.0), 2),
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round(food.get('Protein', 0.0), 2),
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round(food.get('SaturatedFat', 0.0), 2),
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round(food.get('Sugar', 0.0), 2),
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round(food.get('Fiber', 0.0), 2),
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))
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daily_calories += food.get('Energy', 0.0)
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daily_protein += food.get('Protein', 0.0)
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daily_fat += food.get('Fat', 0.0)
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daily_carbs += food.get('Carbs', 0.0)
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daily_sugar += food.get('Sugar', 0.0)
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words = ''.join(
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c if c in string.ascii_letters+"'" else ' '
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for c in content.lower()
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).split()
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word_frequency.update(words)
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entry_words = len(words)
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daily_words += entry_words
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entry_csv.append([timestamp, entry_words])
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daily_macros = daily_protein + daily_fat + daily_carbs
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daily_csv.append([
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day,
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daily_entries,
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daily_words,
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round(daily_calories, 2),
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round(100 * (daily_carbs / daily_macros) if daily_carbs else 0, 2),
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round(100 * (daily_fat / daily_macros) if daily_fat else 0, 2),
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round(100 * (daily_protein / daily_macros) if daily_protein else 0, 2),
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round(daily_protein, 2),
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round(daily_sugar, 2)
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])
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total_entries += daily_entries
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total_words += daily_words
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total_csv.append([day, total_entries, total_words])
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words_csv += word_frequency.most_common()
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def write_csv(fname, csv):
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with open(fname, 'w') as fp:
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fp.write('\n'.join(','.join(str(x) for x in row) for row in csv))
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write_csv('total.csv', total_csv)
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write_csv('daily.csv', daily_csv)
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write_csv('entry.csv', entry_csv)
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write_csv('words.csv', words_csv)
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write_csv('diet.csv', diet_csv)
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