schedule-constraint-parsing

name	schedule-constraint-parsing
description	Uses regular expressions to parse dates, time ranges, and durations from natural language text like meeting requests.

Schedule Constraint Parsing

This skill outlines how to use standard Python re and datetime libraries to extract specific meeting requirements (duration, dates, start/end time windows) from email bodies.

Common Regex Patterns

1. Extracting Duration

People describe duration in hours or minutes (e.g., "1.5 hour", "one-hour", "45-minute").

import re

def parse_duration(text):
    duration_min = None
    
    # Hour pattern
    hr_match = re.search(r'([\d\.]+|(?:one|two|three|half))\s*(?:hour|hr)', text, re.IGNORECASE)
    if hr_match:
        val = hr_match.group(1).lower()
        if val == 'one': hours = 1.0
        elif val == 'two': hours = 2.0
        elif val == 'half': hours = 0.5
        else: hours = float(val)
        duration_min = int(hours * 60)
        
    # Minute pattern
    min_match = re.search(r'(\d+)\s*(?:minute|min)', text, re.IGNORECASE)
    if min_match:
        duration_min = int(min_match.group(1))
        
    return duration_min

2. Extracting Time Range

Extracting available start and end boundaries (e.g., "between 10:00am to 2:00pm", "between 1:00 PM and 5:00 PM PST").

def parse_time_window(text):
    # Extracts HH:MM AM/PM pairs
    pattern = r'(\d{1,2}(?::\d{2})?\s*(?:am|pm|AM|PM)).*?(?:to|and|-)\s*(\d{1,2}(?::\d{2})?\s*(?:am|pm|AM|PM))'
    match = re.search(pattern, text)
    if match:
        start_time_str = match.group(1)
        end_time_str = match.group(2)
        return start_time_str, end_time_str
    return None, None

These simple extraction functions are excellent bases for parsing natural language scheduling intents.