supply-roster-optimization / src /config /optimization_config.py

Upload folder using huggingface_hub

ffa1f50 verified about 1 year ago

18.1 kB

import pandas as pd
import src.preprocess.transform as transformed_data
import datetime
from datetime import timedelta
import src.preprocess.extract as extract
from src.config.constants import ShiftType, LineType, KitLevel, DefaultConfig

# Re-import all the packages
import importlib

# Reload modules to get latest changes - REMOVED to prevent infinite loops
# importlib.reload(extract)
# importlib.reload(transformed_data)  # Uncomment if needed


def get_date_span():
    """Get date span from streamlit session state, or return default"""
    try:
        import streamlit as st
        if hasattr(st, 'session_state'):
            # Get from session state without printing (avoid spam)
            if 'start_date' in st.session_state and 'planning_days' in st.session_state:
                from datetime import datetime, timedelta
                start_date = datetime.combine(st.session_state.start_date, datetime.min.time())
                planning_days = st.session_state.planning_days
                end_date = start_date + timedelta(days=planning_days - 1)
                date_span = list(range(1, planning_days + 1))
                return date_span, start_date, end_date
    except:
        pass
    
    # Default values - no printing to avoid spam
    from datetime import datetime
    return list(range(1, 6)), datetime(2025, 7, 7), datetime(2025, 7, 11)


# Only call get_date_span() when explicitly needed - avoid module-level execution
# DATE_SPAN, start_date, end_date = get_date_span()  # REMOVED - called dynamically instead
DATE_SPAN = None
start_date = None
end_date = None

def get_product_list():
    """Get filtered product list without printing spam"""
    try:
        from src.demand_filtering import DemandFilter
        filter_instance = DemandFilter()
        filter_instance.load_data(force_reload=True)
        return filter_instance.get_filtered_product_list()
    except:
        # Fallback: get from session state start_date
        date_span, start_date, end_date = get_date_span()
        return transformed_data.get_released_product_list(start_date)


def get_employee_type_list():
    """Get employee type list from session state or default"""
    try:
        import streamlit as st
        if hasattr(st, 'session_state') and 'selected_employee_types' in st.session_state:
            return st.session_state.selected_employee_types
    except:
        pass
    
    # Default: load from data files
    employee_type_list = extract.read_employee_data()
    return employee_type_list["employment_type"].unique().tolist()

        
def get_shift_list():
    """Get shift list from session state or default"""
    try:
        import streamlit as st
        if hasattr(st, 'session_state') and 'selected_shifts' in st.session_state:
            return st.session_state.selected_shifts
    except:
        pass
    
    # Default: load from data files
    shift_list = extract.get_shift_info()
    return shift_list["id"].unique().tolist()

# Evening shift activation mode - define early to avoid circular dependency
# Options:
#   "normal" - Only use regular shift (1) and overtime shift (3) - NO evening shift
#   "activate_evening" - Allow evening shift (2) when demand is too high or cost-effective
#   "always_available" - Evening shift always available as option
EVENING_SHIFT_MODE = "normal"  # Default: only regular + overtime

# Evening shift activation threshold
# If demand cannot be met with regular + overtime, suggest evening shift activation
EVENING_SHIFT_DEMAND_THRESHOLD = 0.9  # Activate if regular+overtime capacity < 90% of demand

#Where?
def get_active_shift_list():
    """
    Get the list of active shifts based on EVENING_SHIFT_MODE setting.
    """
    all_shifts = get_shift_list()
    
    if EVENING_SHIFT_MODE == "normal":
        # Only regular and overtime shifts - NO evening shift
        active_shifts = [s for s in all_shifts if s in ShiftType.REGULAR_AND_OVERTIME]
        print(f"[SHIFT MODE] Normal mode: Using shifts {active_shifts} (Regular + Overtime only, NO evening)")
        
    elif EVENING_SHIFT_MODE == "activate_evening":
        # All shifts including evening (2)
        active_shifts = list(all_shifts)
        print(f"[SHIFT MODE] Evening activated: Using all shifts {active_shifts}")
        
    elif EVENING_SHIFT_MODE == "always_available":
        # All shifts always available
        active_shifts = list(all_shifts)
        print(f"[SHIFT MODE] Always available: Using all shifts {active_shifts}")
        
    else:
        # Default to normal mode
        active_shifts = [s for s in all_shifts if s in ShiftType.REGULAR_AND_OVERTIME]
        print(f"[SHIFT MODE] Unknown mode '{EVENING_SHIFT_MODE}', defaulting to normal: {active_shifts}")
    
    return active_shifts

# DO NOT load at import time - always call get_active_shift_list() dynamically
# SHIFT_LIST = get_active_shift_list()  # REMOVED - was causing stale data!

#where?
def get_line_list():
    """Get line list - try from streamlit session state first, then from data files"""
    try:
        # Try to get from streamlit session state (from Dataset Metadata page)
        import streamlit as st
        if hasattr(st, 'session_state') and 'selected_lines' in st.session_state:
            print(f"Using lines from Dataset Metadata page: {st.session_state.selected_lines}")
            return st.session_state.selected_lines
    except Exception as e:
        print(f"Could not get lines from streamlit session: {e}")
    
    # Default: load from data files
    print(f"Loading line list from data files")
    line_df = extract.read_packaging_line_data()
    line_list = line_df["id"].unique().tolist()
    return line_list

# DO NOT load at import time - always call get_line_list() dynamically
# LINE_LIST = get_line_list()  # REMOVED - was causing stale data!

#where?
def get_kit_line_match():
    kit_line_match = extract.read_kit_line_match_data()
    kit_line_match_dict = kit_line_match.set_index("kit_name")["line_type"].to_dict()
    
    # Create line name to ID mapping
    line_name_to_id = {
        "long line": LineType.LONG_LINE,
        "mini load": LineType.MINI_LOAD,
        "miniload": LineType.MINI_LOAD,     # Alternative naming (no space)
        "Long_line": LineType.LONG_LINE,    # Alternative naming
        "Mini_load": LineType.MINI_LOAD,    # Alternative naming
    }
    
    # Convert string line names to numeric IDs
    converted_dict = {}
    for kit, line_name in kit_line_match_dict.items():
        if isinstance(line_name, str) and line_name.strip():
            # Convert string names to numeric IDs
            line_id = line_name_to_id.get(line_name.strip(), None)
            if line_id is not None:
                converted_dict[kit] = line_id
            else:
                print(f"Warning: Unknown line type '{line_name}' for kit {kit}")
                # Default to long line if unknown
                converted_dict[kit] = LineType.LONG_LINE
        elif isinstance(line_name, (int, float)) and not pd.isna(line_name):
            # Already numeric
            converted_dict[kit] = int(line_name)
        else:
            # Missing or empty line type - skip (no production needed for non-standalone masters)
            pass  # Don't add to converted_dict - these kits won't have line assignments
            
    return converted_dict

KIT_LINE_MATCH_DICT = get_kit_line_match()


def get_line_cnt_per_type():
    try:
        # Try to get from streamlit session state (from config page)
        import streamlit as st
        if hasattr(st, 'session_state') and 'line_counts' in st.session_state:
            print(f"Using line counts from config page: {st.session_state.line_counts}")
            return st.session_state.line_counts
    except Exception as e:
        print(f"Could not get line counts from streamlit session: {e}")
    
    print(f"Loading default line count values from data files")
    line_df = extract.read_packaging_line_data()
    line_cnt_per_type = line_df.set_index("id")["line_count"].to_dict()
    print("line cnt per type", line_cnt_per_type)
    return line_cnt_per_type

# DO NOT load at import time - always call get_line_cnt_per_type() dynamically
# LINE_CNT_PER_TYPE = get_line_cnt_per_type()  # REMOVED - was causing stale data!

#where?
def get_demand_dictionary(force_reload=False):
    """
    Get filtered demand dictionary. 
    IMPORTANT: This dynamically loads data to reflect current Streamlit configs/dates.
    """
    try:
        # Always get fresh filtered demand to reflect current configs
        from src.demand_filtering import DemandFilter
        filter_instance = DemandFilter()
        
        # Force reload data to pick up new dates/configs
        filter_instance.load_data(force_reload=True)
        
        demand_dictionary = filter_instance.get_filtered_demand_dictionary()
        print(f"📈 FRESH FILTERED DEMAND: {len(demand_dictionary)} products with total demand {sum(demand_dictionary.values())}")
        print(f"🔄 LOADED DYNAMICALLY: Reflects current Streamlit configs")
        return demand_dictionary
    except Exception as e:
        print(f"Error loading dynamic demand dictionary: {e}")
        raise Exception("Demand dictionary not found with error:"+str(e))

# DO NOT load at import time - always call get_demand_dictionary() dynamically
# DEMAND_DICTIONARY = get_demand_dictionary()  # REMOVED - was causing stale data!

#delete as already using default cost rates
def get_cost_list_per_emp_shift():
    try:
        # Try to get from streamlit session state (from config page)
        import streamlit as st
        if hasattr(st, 'session_state') and 'cost_list_per_emp_shift' in st.session_state:
            print(f"Using cost list from config page: {st.session_state.cost_list_per_emp_shift}")
            return st.session_state.cost_list_per_emp_shift
    except Exception as e:
        print(f"Could not get cost list from streamlit session: {e}")
    
    print(f"Loading default cost values")
    # Default hourly rates - Important: multiple employment types with different costs
    return DefaultConfig.DEFAULT_COST_RATES

def shift_code_to_name():
    return ShiftType.get_all_names()

def line_code_to_name():
    """Convert line type IDs to readable names"""
    return LineType.get_all_names()

# DO NOT load at import time - always call get_cost_list_per_emp_shift() dynamically
# COST_LIST_PER_EMP_SHIFT = get_cost_list_per_emp_shift()  # REMOVED - was causing stale data!
        


# COST_LIST_PER_EMP_SHIFT = {  # WH_Workforce_Hourly_Pay_Scale
#     "Fixed": {1: 0, 2: 22, 3: 18},
#     "Humanizer": {1: 10, 2: 10, 3: 10},
# }






#where to put?
def get_team_requirements(product_list=None):
    """
    Extract team requirements from Kits Calculation CSV.
    Returns dictionary with employee type as key and product requirements as nested dict.
    """
    if product_list is None:
        product_list = get_product_list()  # Get fresh product list
        

    kits_df = extract.read_personnel_requirement_data()

    team_req_dict = {
        "UNICEF Fixed term": {},
        "Humanizer": {}
    }
    
    # Process each product in the product list
    for product in product_list:
        print("product",product)
        print(f"Processing team requirements for product: {product}")
        product_data = kits_df[kits_df['Kit'] == product]
        print("product_data",product_data)
        if not product_data.empty:
            # Extract Humanizer and UNICEF staff requirements
            humanizer_req = product_data["Humanizer"].iloc[0]
            unicef_req = product_data["UNICEF staff"].iloc[0]
            
            # Convert to int (data is already cleaned in extract function)
            team_req_dict["Humanizer"][product] = int(humanizer_req)
            team_req_dict["UNICEF Fixed term"][product] = int(unicef_req)
        else:
            print(f"Warning: Product {product} not found in Kits Calculation data, setting requirements to 0")
            
    
    return team_req_dict



def get_max_employee_per_type_on_day():
    try:
        # Try to get from streamlit session state (from config page)
        import streamlit as st
        if hasattr(st, 'session_state') and 'max_employee_per_type_on_day' in st.session_state:
            print(f"Using max employee counts from config page: {st.session_state.max_employee_per_type_on_day}")
            return st.session_state.max_employee_per_type_on_day
    except Exception as e:
        print(f"Could not get max employee counts from streamlit session: {e}")
    
    print(f"Loading default max employee values")
    # Get date span dynamically if not available
    if DATE_SPAN is None:
        date_span, _, _ = get_date_span()
    else:
        date_span = DATE_SPAN
    
    max_employee_per_type_on_day = {
        "UNICEF Fixed term": {
            t: 8 for t in date_span
        },
        "Humanizer": {
            t: 10 for t in date_span
        }
    }
    return max_employee_per_type_on_day


# Keep the constant for backward compatibility, but use function instead
MAX_HOUR_PER_PERSON_PER_DAY = 14  # legal standard
def get_max_hour_per_shift_per_person():
    """Get max hours per shift per person from session state or default"""
    try:
        import streamlit as st
        if hasattr(st, 'session_state'):
            # Build from individual session state values
            max_hours = {
                ShiftType.REGULAR: st.session_state.get('max_hours_shift_1', DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON[ShiftType.REGULAR]),
                ShiftType.EVENING: st.session_state.get('max_hours_shift_2', DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON[ShiftType.EVENING]),
                ShiftType.OVERTIME: st.session_state.get('max_hours_shift_3', DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON[ShiftType.OVERTIME])
            }
            return max_hours
    except Exception as e:
        print(f"Could not get max hours per shift from session: {e}")
    
    # Fallback to default
    return DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON



# Keep these complex getters that access DefaultConfig or have complex logic:
def get_evening_shift_demand_threshold():
    """Get evening shift demand threshold from session state or default"""
    try:
        import streamlit as st
        if hasattr(st, 'session_state'):
            return st.session_state.get('evening_shift_threshold', DefaultConfig.EVENING_SHIFT_DEMAND_THRESHOLD)
    except Exception as e:
        print(f"Could not get evening shift threshold from session: {e}")
    
    # Fallback to default
    return DefaultConfig.EVENING_SHIFT_DEMAND_THRESHOLD


# ---- Kit Hierarchy for Production Ordering ----
def get_kit_hierarchy_data():
    kit_levels, dependencies, priority_order = extract.get_production_order_data()
    
    return kit_levels, dependencies, priority_order

KIT_LEVELS, KIT_DEPENDENCIES, PRODUCTION_PRIORITY_ORDER = get_kit_hierarchy_data()
print(f"Kit Hierarchy loaded: {len(KIT_LEVELS)} kits, Priority order: {len(PRODUCTION_PRIORITY_ORDER)} items")

def get_kit_levels():
    """Get kit levels lazily - returns {kit_id: level} where 0=prepack, 1=subkit, 2=master"""
    kit_levels, _, _ = get_kit_hierarchy_data()
    return kit_levels

def get_kit_dependencies():
    """Get kit dependencies lazily - returns {kit_id: [dependency_list]}"""
    _, dependencies, _ = get_kit_hierarchy_data()
    return dependencies

def get_max_parallel_workers():
    """Get max parallel workers from session state or default"""
    try:
        import streamlit as st
        if hasattr(st, 'session_state'):
            # Build from individual session state values
            max_parallel_workers = {
                LineType.LONG_LINE: st.session_state.get('max_parallel_workers_long_line', DefaultConfig.MAX_PARALLEL_WORKERS_LONG_LINE),
                LineType.MINI_LOAD: st.session_state.get('max_parallel_workers_mini_load', DefaultConfig.MAX_PARALLEL_WORKERS_MINI_LOAD)
            }
            return max_parallel_workers
    except Exception as e:
        print(f"Could not get max parallel workers from session: {e}")
    
    # Fallback to default
    return {
        LineType.LONG_LINE: DefaultConfig.MAX_PARALLEL_WORKERS_LONG_LINE,
        LineType.MINI_LOAD: DefaultConfig.MAX_PARALLEL_WORKERS_MINI_LOAD
    }



def get_fixed_min_unicef_per_day():
    """
    Get fixed minimum UNICEF employees per day - try from streamlit session state first, then default
    This ensures a minimum number of UNICEF fixed-term staff are present every working day
    """
    try:
        import streamlit as st
        if hasattr(st, 'session_state') and 'fixed_min_unicef_per_day' in st.session_state:
            print(f"Using fixed minimum UNICEF per day from config page: {st.session_state.fixed_min_unicef_per_day}")
            return st.session_state.fixed_min_unicef_per_day
    except ImportError:
        pass 
    
    # Fallback to default configuration
    return DefaultConfig.FIXED_MIN_UNICEF_PER_DAY


def get_payment_mode_config():
    """
    Get payment mode configuration - try from streamlit session state first, then default values
    Payment modes:
    - "bulk": If employee works any hours in shift, pay for full shift hours
    - "partial": Pay only for actual hours worked
    """
    try:
        # Try to get from streamlit session state (from Dataset Metadata page)
        import streamlit as st
        if hasattr(st, 'session_state') and 'payment_mode_config' in st.session_state:
            print(f"Using payment mode config from streamlit session: {st.session_state.payment_mode_config}")
            return st.session_state.payment_mode_config
    except Exception as e:
        print(f"Could not get payment mode config from streamlit session: {e}")
    
    # Default payment mode configuration
    print(f"Loading default payment mode configuration")
    payment_mode_config = DefaultConfig.PAYMENT_MODE_CONFIG
    
    return payment_mode_config


print("✅ Module-level configuration functions defined (variables initialized dynamically)")

	import pandas as pd
	import src.preprocess.transform as transformed_data
	import datetime
	from datetime import timedelta
	import src.preprocess.extract as extract
	from src.config.constants import ShiftType, LineType, KitLevel, DefaultConfig

	# Re-import all the packages
	import importlib

	# Reload modules to get latest changes - REMOVED to prevent infinite loops
	# importlib.reload(extract)
	# importlib.reload(transformed_data) # Uncomment if needed


	def get_date_span():
	"""Get date span from streamlit session state, or return default"""
	try:
	import streamlit as st
	if hasattr(st, 'session_state'):
	# Get from session state without printing (avoid spam)
	if 'start_date' in st.session_state and 'planning_days' in st.session_state:
	from datetime import datetime, timedelta
	start_date = datetime.combine(st.session_state.start_date, datetime.min.time())
	planning_days = st.session_state.planning_days
	end_date = start_date + timedelta(days=planning_days - 1)
	date_span = list(range(1, planning_days + 1))
	return date_span, start_date, end_date
	except:
	pass

	# Default values - no printing to avoid spam
	from datetime import datetime
	return list(range(1, 6)), datetime(2025, 7, 7), datetime(2025, 7, 11)


	# Only call get_date_span() when explicitly needed - avoid module-level execution
	# DATE_SPAN, start_date, end_date = get_date_span() # REMOVED - called dynamically instead
	DATE_SPAN = None
	start_date = None
	end_date = None

	def get_product_list():
	"""Get filtered product list without printing spam"""
	try:
	from src.demand_filtering import DemandFilter
	filter_instance = DemandFilter()
	filter_instance.load_data(force_reload=True)
	return filter_instance.get_filtered_product_list()
	except:
	# Fallback: get from session state start_date
	date_span, start_date, end_date = get_date_span()
	return transformed_data.get_released_product_list(start_date)


	def get_employee_type_list():
	"""Get employee type list from session state or default"""
	try:
	import streamlit as st
	if hasattr(st, 'session_state') and 'selected_employee_types' in st.session_state:
	return st.session_state.selected_employee_types
	except:
	pass

	# Default: load from data files
	employee_type_list = extract.read_employee_data()
	return employee_type_list["employment_type"].unique().tolist()


	def get_shift_list():
	"""Get shift list from session state or default"""
	try:
	import streamlit as st
	if hasattr(st, 'session_state') and 'selected_shifts' in st.session_state:
	return st.session_state.selected_shifts
	except:
	pass

	# Default: load from data files
	shift_list = extract.get_shift_info()
	return shift_list["id"].unique().tolist()

	# Evening shift activation mode - define early to avoid circular dependency
	# Options:
	# "normal" - Only use regular shift (1) and overtime shift (3) - NO evening shift
	# "activate_evening" - Allow evening shift (2) when demand is too high or cost-effective
	# "always_available" - Evening shift always available as option
	EVENING_SHIFT_MODE = "normal" # Default: only regular + overtime

	# Evening shift activation threshold
	# If demand cannot be met with regular + overtime, suggest evening shift activation
	EVENING_SHIFT_DEMAND_THRESHOLD = 0.9 # Activate if regular+overtime capacity < 90% of demand

	#Where?
	def get_active_shift_list():
	"""
	Get the list of active shifts based on EVENING_SHIFT_MODE setting.
	"""
	all_shifts = get_shift_list()

	if EVENING_SHIFT_MODE == "normal":
	# Only regular and overtime shifts - NO evening shift
	active_shifts = [s for s in all_shifts if s in ShiftType.REGULAR_AND_OVERTIME]
	print(f"[SHIFT MODE] Normal mode: Using shifts {active_shifts} (Regular + Overtime only, NO evening)")

	elif EVENING_SHIFT_MODE == "activate_evening":
	# All shifts including evening (2)
	active_shifts = list(all_shifts)
	print(f"[SHIFT MODE] Evening activated: Using all shifts {active_shifts}")

	elif EVENING_SHIFT_MODE == "always_available":
	# All shifts always available
	active_shifts = list(all_shifts)
	print(f"[SHIFT MODE] Always available: Using all shifts {active_shifts}")

	else:
	# Default to normal mode
	active_shifts = [s for s in all_shifts if s in ShiftType.REGULAR_AND_OVERTIME]
	print(f"[SHIFT MODE] Unknown mode '{EVENING_SHIFT_MODE}', defaulting to normal: {active_shifts}")

	return active_shifts

	# DO NOT load at import time - always call get_active_shift_list() dynamically
	# SHIFT_LIST = get_active_shift_list() # REMOVED - was causing stale data!

	#where?
	def get_line_list():
	"""Get line list - try from streamlit session state first, then from data files"""
	try:
	# Try to get from streamlit session state (from Dataset Metadata page)
	import streamlit as st
	if hasattr(st, 'session_state') and 'selected_lines' in st.session_state:
	print(f"Using lines from Dataset Metadata page: {st.session_state.selected_lines}")
	return st.session_state.selected_lines
	except Exception as e:
	print(f"Could not get lines from streamlit session: {e}")

	# Default: load from data files
	print(f"Loading line list from data files")
	line_df = extract.read_packaging_line_data()
	line_list = line_df["id"].unique().tolist()
	return line_list

	# DO NOT load at import time - always call get_line_list() dynamically
	# LINE_LIST = get_line_list() # REMOVED - was causing stale data!

	#where?
	def get_kit_line_match():
	kit_line_match = extract.read_kit_line_match_data()
	kit_line_match_dict = kit_line_match.set_index("kit_name")["line_type"].to_dict()

	# Create line name to ID mapping
	line_name_to_id = {
	"long line": LineType.LONG_LINE,
	"mini load": LineType.MINI_LOAD,
	"miniload": LineType.MINI_LOAD, # Alternative naming (no space)
	"Long_line": LineType.LONG_LINE, # Alternative naming
	"Mini_load": LineType.MINI_LOAD, # Alternative naming
	}

	# Convert string line names to numeric IDs
	converted_dict = {}
	for kit, line_name in kit_line_match_dict.items():
	if isinstance(line_name, str) and line_name.strip():
	# Convert string names to numeric IDs
	line_id = line_name_to_id.get(line_name.strip(), None)
	if line_id is not None:
	converted_dict[kit] = line_id
	else:
	print(f"Warning: Unknown line type '{line_name}' for kit {kit}")
	# Default to long line if unknown
	converted_dict[kit] = LineType.LONG_LINE
	elif isinstance(line_name, (int, float)) and not pd.isna(line_name):
	# Already numeric
	converted_dict[kit] = int(line_name)
	else:
	# Missing or empty line type - skip (no production needed for non-standalone masters)
	pass # Don't add to converted_dict - these kits won't have line assignments

	return converted_dict

	KIT_LINE_MATCH_DICT = get_kit_line_match()


	def get_line_cnt_per_type():
	try:
	# Try to get from streamlit session state (from config page)
	import streamlit as st
	if hasattr(st, 'session_state') and 'line_counts' in st.session_state:
	print(f"Using line counts from config page: {st.session_state.line_counts}")
	return st.session_state.line_counts
	except Exception as e:
	print(f"Could not get line counts from streamlit session: {e}")

	print(f"Loading default line count values from data files")
	line_df = extract.read_packaging_line_data()
	line_cnt_per_type = line_df.set_index("id")["line_count"].to_dict()
	print("line cnt per type", line_cnt_per_type)
	return line_cnt_per_type

	# DO NOT load at import time - always call get_line_cnt_per_type() dynamically
	# LINE_CNT_PER_TYPE = get_line_cnt_per_type() # REMOVED - was causing stale data!

	#where?
	def get_demand_dictionary(force_reload=False):
	"""
	Get filtered demand dictionary.
	IMPORTANT: This dynamically loads data to reflect current Streamlit configs/dates.
	"""
	try:
	# Always get fresh filtered demand to reflect current configs
	from src.demand_filtering import DemandFilter
	filter_instance = DemandFilter()

	# Force reload data to pick up new dates/configs
	filter_instance.load_data(force_reload=True)

	demand_dictionary = filter_instance.get_filtered_demand_dictionary()
	print(f"📈 FRESH FILTERED DEMAND: {len(demand_dictionary)} products with total demand {sum(demand_dictionary.values())}")
	print(f"🔄 LOADED DYNAMICALLY: Reflects current Streamlit configs")
	return demand_dictionary
	except Exception as e:
	print(f"Error loading dynamic demand dictionary: {e}")
	raise Exception("Demand dictionary not found with error:"+str(e))

	# DO NOT load at import time - always call get_demand_dictionary() dynamically
	# DEMAND_DICTIONARY = get_demand_dictionary() # REMOVED - was causing stale data!

	#delete as already using default cost rates
	def get_cost_list_per_emp_shift():
	try:
	# Try to get from streamlit session state (from config page)
	import streamlit as st
	if hasattr(st, 'session_state') and 'cost_list_per_emp_shift' in st.session_state:
	print(f"Using cost list from config page: {st.session_state.cost_list_per_emp_shift}")
	return st.session_state.cost_list_per_emp_shift
	except Exception as e:
	print(f"Could not get cost list from streamlit session: {e}")

	print(f"Loading default cost values")
	# Default hourly rates - Important: multiple employment types with different costs
	return DefaultConfig.DEFAULT_COST_RATES

	def shift_code_to_name():
	return ShiftType.get_all_names()

	def line_code_to_name():
	"""Convert line type IDs to readable names"""
	return LineType.get_all_names()

	# DO NOT load at import time - always call get_cost_list_per_emp_shift() dynamically
	# COST_LIST_PER_EMP_SHIFT = get_cost_list_per_emp_shift() # REMOVED - was causing stale data!



	# COST_LIST_PER_EMP_SHIFT = { # WH_Workforce_Hourly_Pay_Scale
	# "Fixed": {1: 0, 2: 22, 3: 18},
	# "Humanizer": {1: 10, 2: 10, 3: 10},
	# }






	#where to put?
	def get_team_requirements(product_list=None):
	"""
	Extract team requirements from Kits Calculation CSV.
	Returns dictionary with employee type as key and product requirements as nested dict.
	"""
	if product_list is None:
	product_list = get_product_list() # Get fresh product list


	kits_df = extract.read_personnel_requirement_data()

	team_req_dict = {
	"UNICEF Fixed term": {},
	"Humanizer": {}
	}

	# Process each product in the product list
	for product in product_list:
	print("product",product)
	print(f"Processing team requirements for product: {product}")
	product_data = kits_df[kits_df['Kit'] == product]
	print("product_data",product_data)
	if not product_data.empty:
	# Extract Humanizer and UNICEF staff requirements
	humanizer_req = product_data["Humanizer"].iloc[0]
	unicef_req = product_data["UNICEF staff"].iloc[0]

	# Convert to int (data is already cleaned in extract function)
	team_req_dict["Humanizer"][product] = int(humanizer_req)
	team_req_dict["UNICEF Fixed term"][product] = int(unicef_req)
	else:
	print(f"Warning: Product {product} not found in Kits Calculation data, setting requirements to 0")


	return team_req_dict



	def get_max_employee_per_type_on_day():
	try:
	# Try to get from streamlit session state (from config page)
	import streamlit as st
	if hasattr(st, 'session_state') and 'max_employee_per_type_on_day' in st.session_state:
	print(f"Using max employee counts from config page: {st.session_state.max_employee_per_type_on_day}")
	return st.session_state.max_employee_per_type_on_day
	except Exception as e:
	print(f"Could not get max employee counts from streamlit session: {e}")

	print(f"Loading default max employee values")
	# Get date span dynamically if not available
	if DATE_SPAN is None:
	date_span, _, _ = get_date_span()
	else:
	date_span = DATE_SPAN

	max_employee_per_type_on_day = {
	"UNICEF Fixed term": {
	t: 8 for t in date_span
	},
	"Humanizer": {
	t: 10 for t in date_span
	}
	}
	return max_employee_per_type_on_day


	# Keep the constant for backward compatibility, but use function instead
	MAX_HOUR_PER_PERSON_PER_DAY = 14 # legal standard
	def get_max_hour_per_shift_per_person():
	"""Get max hours per shift per person from session state or default"""
	try:
	import streamlit as st
	if hasattr(st, 'session_state'):
	# Build from individual session state values
	max_hours = {
	ShiftType.REGULAR: st.session_state.get('max_hours_shift_1', DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON[ShiftType.REGULAR]),
	ShiftType.EVENING: st.session_state.get('max_hours_shift_2', DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON[ShiftType.EVENING]),
	ShiftType.OVERTIME: st.session_state.get('max_hours_shift_3', DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON[ShiftType.OVERTIME])
	}
	return max_hours
	except Exception as e:
	print(f"Could not get max hours per shift from session: {e}")

	# Fallback to default
	return DefaultConfig.MAX_HOUR_PER_SHIFT_PER_PERSON



	# Keep these complex getters that access DefaultConfig or have complex logic:
	def get_evening_shift_demand_threshold():
	"""Get evening shift demand threshold from session state or default"""
	try:
	import streamlit as st
	if hasattr(st, 'session_state'):
	return st.session_state.get('evening_shift_threshold', DefaultConfig.EVENING_SHIFT_DEMAND_THRESHOLD)
	except Exception as e:
	print(f"Could not get evening shift threshold from session: {e}")

	# Fallback to default
	return DefaultConfig.EVENING_SHIFT_DEMAND_THRESHOLD


	# ---- Kit Hierarchy for Production Ordering ----
	def get_kit_hierarchy_data():
	kit_levels, dependencies, priority_order = extract.get_production_order_data()

	return kit_levels, dependencies, priority_order

	KIT_LEVELS, KIT_DEPENDENCIES, PRODUCTION_PRIORITY_ORDER = get_kit_hierarchy_data()
	print(f"Kit Hierarchy loaded: {len(KIT_LEVELS)} kits, Priority order: {len(PRODUCTION_PRIORITY_ORDER)} items")

	def get_kit_levels():
	"""Get kit levels lazily - returns {kit_id: level} where 0=prepack, 1=subkit, 2=master"""
	kit_levels, _, _ = get_kit_hierarchy_data()
	return kit_levels

	def get_kit_dependencies():
	"""Get kit dependencies lazily - returns {kit_id: [dependency_list]}"""
	_, dependencies, _ = get_kit_hierarchy_data()
	return dependencies

	def get_max_parallel_workers():
	"""Get max parallel workers from session state or default"""
	try:
	import streamlit as st
	if hasattr(st, 'session_state'):
	# Build from individual session state values
	max_parallel_workers = {
	LineType.LONG_LINE: st.session_state.get('max_parallel_workers_long_line', DefaultConfig.MAX_PARALLEL_WORKERS_LONG_LINE),
	LineType.MINI_LOAD: st.session_state.get('max_parallel_workers_mini_load', DefaultConfig.MAX_PARALLEL_WORKERS_MINI_LOAD)
	}
	return max_parallel_workers
	except Exception as e:
	print(f"Could not get max parallel workers from session: {e}")

	# Fallback to default
	return {
	LineType.LONG_LINE: DefaultConfig.MAX_PARALLEL_WORKERS_LONG_LINE,
	LineType.MINI_LOAD: DefaultConfig.MAX_PARALLEL_WORKERS_MINI_LOAD
	}



	def get_fixed_min_unicef_per_day():
	"""
	Get fixed minimum UNICEF employees per day - try from streamlit session state first, then default
	This ensures a minimum number of UNICEF fixed-term staff are present every working day
	"""
	try:
	import streamlit as st
	if hasattr(st, 'session_state') and 'fixed_min_unicef_per_day' in st.session_state:
	print(f"Using fixed minimum UNICEF per day from config page: {st.session_state.fixed_min_unicef_per_day}")
	return st.session_state.fixed_min_unicef_per_day
	except ImportError:
	pass

	# Fallback to default configuration
	return DefaultConfig.FIXED_MIN_UNICEF_PER_DAY


	def get_payment_mode_config():
	"""
	Get payment mode configuration - try from streamlit session state first, then default values
	Payment modes:
	- "bulk": If employee works any hours in shift, pay for full shift hours
	- "partial": Pay only for actual hours worked
	"""
	try:
	# Try to get from streamlit session state (from Dataset Metadata page)
	import streamlit as st
	if hasattr(st, 'session_state') and 'payment_mode_config' in st.session_state:
	print(f"Using payment mode config from streamlit session: {st.session_state.payment_mode_config}")
	return st.session_state.payment_mode_config
	except Exception as e:
	print(f"Could not get payment mode config from streamlit session: {e}")

	# Default payment mode configuration
	print(f"Loading default payment mode configuration")
	payment_mode_config = DefaultConfig.PAYMENT_MODE_CONFIG

	return payment_mode_config


	print("✅ Module-level configuration functions defined (variables initialized dynamically)")