cash-flow-forecaster
Forecast project cash flow based on schedule and cost data. Generate S-curves and payment projections.
git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction /tmp/cash-flow-forecaster && cp -r /tmp/cash-flow-forecaster/1_DDC_Toolkit/Cost-Management/cash-flow-forecaster ~/.claude/skills/cash-flow-forecasterSKILL.md
# Cash Flow Forecaster
## Business Case
### Problem Statement
Poor cash flow management causes issues:
- Insufficient funds for payments
- Missed early payment discounts
- Inaccurate financial projections
- Difficulty in financing negotiations
### Solution
Generate cash flow forecasts from schedule and cost data, including S-curve projections and payment timing analysis.
### Business Value
- **Financial planning** - Accurate funding requirements
- **Vendor relations** - Timely payments
- **Financing** - Support loan draw schedules
- **Decision support** - Cash position awareness
## Technical Implementation
```python
import pandas as pd
import numpy as np
from datetime import datetime, date, timedelta
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
class CashFlowType(Enum):
"""Cash flow types."""
INFLOW = "inflow"
OUTFLOW = "outflow"
class PaymentTerms(Enum):
"""Standard payment terms."""
NET_30 = 30
NET_45 = 45
NET_60 = 60
NET_90 = 90
MILESTONE = 0
PROGRESS = 0
@dataclass
class CostItem:
"""Cost item for cash flow."""
item_id: str
description: str
total_amount: float
start_date: date
end_date: date
payment_terms: PaymentTerms
distribution: str = "linear" # linear, front_loaded, back_loaded, s_curve
retention_percent: float = 0.10
category: str = ""
@dataclass
class PaymentSchedule:
"""Scheduled payment."""
payment_id: str
item_id: str
description: str
amount: float
due_date: date
payment_type: CashFlowType
is_retention: bool = False
paid: bool = False
paid_date: Optional[date] = None
@dataclass
class CashFlowPeriod:
"""Cash flow for a period."""
period_start: date
period_end: date
inflows: float
outflows: float
net_cash_flow: float
cumulative_cash_flow: float
opening_balance: float
closing_balance: float
class CashFlowForecaster:
"""Forecast project cash flow."""
def __init__(self, project_name: str, project_start: date, project_end: date,
initial_balance: float = 0, currency: str = "USD"):
self.project_name = project_name
self.project_start = project_start
self.project_end = project_end
self.initial_balance = initial_balance
self.currency = currency
self.cost_items: List[CostItem] = []
self.revenue_items: List[CostItem] = []
self.payments: List[PaymentSchedule] = []
self._payment_counter = 0
def add_cost_item(self, item_id: str, description: str, total_amount: float,
start_date: date, end_date: date,
payment_terms: PaymentTerms = PaymentTerms.NET_30,
distribution: str = "linear",
retention: float = 0.10,
category: str = "") -> CostItem:
"""Add cost item (outflow)."""
item = CostItem(
item_id=item_id,
description=description,
total_amount=total_amount,
start_date=start_date,
end_date=end_date,
payment_terms=payment_terms,
distribution=distribution,
retention_percent=retention,
category=category
)
self.cost_items.append(item)
return item
def add_revenue_item(self, item_id: str, description: str, total_amount: float,
start_date: date, end_date: date,
payment_terms: PaymentTerms = PaymentTerms.NET_30,
distribution: str = "linear",
retention: float = 0.10) -> CostItem:
"""Add revenue item (inflow)."""
item = CostItem(
item_id=item_id,
description=description,
total_amount=total_amount,
start_date=start_date,
end_date=end_date,
payment_terms=payment_terms,
distribution=distribution,
retention_percent=retention
)
self.revenue_items.append(item)
return item
def _distribute_amount(self, total: float, start: date, end: date,
distribution: str, periods: int) -> List[float]:
"""Distribute amount over periods based on distribution type."""
if periods <= 0:
return [total]
if distribution == "linear":
return [total / periods] * periods
elif distribution == "front_loaded":
# More at the beginning
weights = [periods - i for i in range(periods)]
total_weight = sum(weights)
return [total * w / total_weight for w in weights]
elif distribution == "back_loaded":
# More at the end
weights = [i + 1 for i in range(periods)]
total_weight = sum(weights)
return [total * w / total_weight for w in weights]
elif distribution == "s_curve":
# S-curve distribution
x = np.linspace(-3, 3, periods)
weights = 1 / (1 + np.exp(-x))
weights = weights / weights.sum()
return [total * w for w in weights]
else:
return [total / periods] * periods
def generate_payment_schedule(self, period_type: str = "monthly") -> List[PaymentSchedule]:
"""Generate payment schedule from cost items."""
self.payments = []
# Process cost items (outflows)
for item in self.cost_items:
self._generate_item_payments(item, CashFlowType.OUTFLOW, period_type)
# Process revenue items (inflows)
for item in self.revenue_items:
self._generate_item_payments(item, CashFlowType.INFLOW, period_type)
return sorted(self.payments, key=lambda x: x.due_date)
def _generate_item_payments(self, item: CostItem, flow_type: CashFlowType,
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