103 lines
3.4 KiB
Python
103 lines
3.4 KiB
Python
import pandas as pd
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from datetime import datetime, timedelta
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import holidays
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import os
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from pathlib import Path
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import random
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import csv
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# Define date range
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start_date = datetime(2023, 1, 1)
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end_date = datetime(2023, 12, 31)
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# Austrian public holidays
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at_holidays = holidays.country_holidays('AT', years=[2023])
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# Exclude dates in external CSV-defined ranges
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exclude_ranges_path = Path.home() / 'Documents' / 'zisco' / 'exclude_ranges.csv'
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exclude_ranges = []
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if exclude_ranges_path.exists():
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with open(exclude_ranges_path, newline='') as csvfile:
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reader = csv.reader(csvfile)
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for row in reader:
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try:
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start = datetime.strptime(row[0], '%Y-%m-%d')
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end = datetime.strptime(row[1], '%Y-%m-%d')
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exclude_ranges.append((start, end))
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except Exception:
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continue
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def is_in_exclude_ranges(date):
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for start, end in exclude_ranges:
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if start <= date <= end:
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return True
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return False
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# Generate all dates in range
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dates = []
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current = start_date
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while current <= end_date:
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if current.weekday() in [1, 3]: # 1=Tuesday, 3=Thursday
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if current not in at_holidays and not is_in_exclude_ranges(current):
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dates.append((current, "Wien"))
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current += timedelta(days=1)
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# Add meetings from separate CSV file
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meetings_path = Path.home() / 'Documents' / 'zisco' / 'meetings_2023.csv'
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meetings = []
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if meetings_path.exists():
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with open(meetings_path, newline='') as csvfile:
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reader = csv.reader(csvfile)
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for row in reader:
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try:
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date = datetime.strptime(row[1], '%d.%m.%Y')
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ziel = row[3]
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#if date not in at_holidays and not is_in_exclude_ranges(date):
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if not is_in_exclude_ranges(date):
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meetings.append((date, ziel))
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except Exception:
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continue
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# Combine dates and meetings, ensuring no duplicates
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# all_entries = dates+meetings
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# all_entries.sort()
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# Combine and remove duplicates (as tuples to deduplicate)
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all_entries = list({tuple(row) for row in meetings + dates})
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# Sort by date (index 0)
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all_entries.sort(key=lambda x: x[0])
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df = pd.DataFrame({
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'Datum': [d.strftime('%Y-%m-%d') for d, _ in all_entries],
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'Ziel': [z for _, z in all_entries],
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'Zweck': ['Besprechung'] * len(all_entries),
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'Std.': [random.randint(3, 7) for _ in all_entries],
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'Inland': [''] * len(all_entries),
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'Ausland': [''] * len(all_entries),
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'Tage': [''] * len(all_entries),
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'INLAND': [''] * len(all_entries),
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'AUSLAND': [''] * len(all_entries)
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})
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# df = pd.DataFrame({
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# 'Datum': [d.strftime('%Y-%m-%d') for d in dates],
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# 'Ziel': ['Wien'] * len(dates),
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# 'Zweck': ['Besprechung'] * len(dates),
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# 'Std.': [random.randint(3, 9) for _ in dates],
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# 'Inland': [''] * len(dates),
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# 'Ausland': [''] * len(dates),
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# 'Tage': [''] * len(dates),
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# 'INLAND': [''] * len(dates),
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# 'AUSLAND': [''] * len(dates)
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# })
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headers = [['', '', '', '', '', '', '', 'Taggeld', 'Nächtigungen'],
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['Datum', 'Ziel', 'Zweck', 'Std.', 'Inland', 'Ausland', 'Tage', 'Inland', 'Ausland']]
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multi_header = pd.MultiIndex.from_arrays(headers)
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df.columns = multi_header
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documents_dir = Path.home() / 'Documents'
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csv_path = documents_dir / 'zisco' / 'travel_schedule.csv'
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os.makedirs(csv_path.parent, exist_ok=True)
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df.to_csv(csv_path, index=False) |