feat: Add profitability calculation schemas and service functions
- Introduced Pydantic schemas for profitability calculations in `schemas/calculations.py`. - Implemented service functions for profitability calculations in `services/calculations.py`. - Added new exception class `ProfitabilityValidationError` for handling validation errors. - Created repositories for managing project and scenario profitability snapshots. - Developed a utility script for verifying authenticated routes. - Added a new HTML template for the profitability calculator interface. - Implemented a script to fix user ID sequence in the database.
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services/calculations.py
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205
services/calculations.py
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"""Service functions for financial calculations."""
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from __future__ import annotations
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from services.currency import CurrencyValidationError, normalise_currency
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from services.exceptions import ProfitabilityValidationError
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from services.financial import (
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CashFlow,
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ConvergenceError,
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PaybackNotReachedError,
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internal_rate_of_return,
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net_present_value,
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payback_period,
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)
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from services.pricing import PricingInput, PricingMetadata, PricingResult, calculate_pricing
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from schemas.calculations import (
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CashFlowEntry,
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ProfitabilityCalculationRequest,
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ProfitabilityCalculationResult,
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ProfitabilityCosts,
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ProfitabilityMetrics,
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)
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def _build_pricing_input(
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request: ProfitabilityCalculationRequest,
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) -> PricingInput:
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"""Construct a pricing input instance including impurity overrides."""
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impurity_values: dict[str, float] = {}
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impurity_thresholds: dict[str, float] = {}
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impurity_penalties: dict[str, float] = {}
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for impurity in request.impurities:
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code = impurity.name.strip()
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if not code:
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continue
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code = code.upper()
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if impurity.value is not None:
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impurity_values[code] = float(impurity.value)
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if impurity.threshold is not None:
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impurity_thresholds[code] = float(impurity.threshold)
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if impurity.penalty is not None:
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impurity_penalties[code] = float(impurity.penalty)
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pricing_input = PricingInput(
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metal=request.metal,
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ore_tonnage=request.ore_tonnage,
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head_grade_pct=request.head_grade_pct,
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recovery_pct=request.recovery_pct,
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payable_pct=request.payable_pct,
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reference_price=request.reference_price,
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treatment_charge=request.treatment_charge,
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smelting_charge=request.smelting_charge,
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moisture_pct=request.moisture_pct,
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moisture_threshold_pct=request.moisture_threshold_pct,
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moisture_penalty_per_pct=request.moisture_penalty_per_pct,
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impurity_ppm=impurity_values,
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impurity_thresholds=impurity_thresholds,
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impurity_penalty_per_ppm=impurity_penalties,
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premiums=request.premiums,
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fx_rate=request.fx_rate,
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currency_code=request.currency_code,
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)
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return pricing_input
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def _generate_cash_flows(
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*,
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periods: int,
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net_per_period: float,
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initial_capex: float,
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) -> tuple[list[CashFlow], list[CashFlowEntry]]:
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"""Create cash flow structures for financial metric calculations."""
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cash_flow_models: list[CashFlow] = [
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CashFlow(amount=-initial_capex, period_index=0)
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]
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cash_flow_entries: list[CashFlowEntry] = [
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CashFlowEntry(
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period=0,
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revenue=0.0,
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processing_opex=0.0,
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sustaining_capex=0.0,
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net=-initial_capex,
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)
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]
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for period in range(1, periods + 1):
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cash_flow_models.append(
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CashFlow(amount=net_per_period, period_index=period))
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cash_flow_entries.append(
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CashFlowEntry(
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period=period,
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revenue=0.0,
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processing_opex=0.0,
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sustaining_capex=0.0,
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net=net_per_period,
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)
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)
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return cash_flow_models, cash_flow_entries
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def calculate_profitability(
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request: ProfitabilityCalculationRequest,
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*,
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metadata: PricingMetadata,
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) -> ProfitabilityCalculationResult:
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"""Calculate profitability metrics using pricing inputs and cost data."""
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if request.periods <= 0:
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raise ProfitabilityValidationError(
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"Evaluation periods must be at least 1.", ["periods"]
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)
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pricing_input = _build_pricing_input(request)
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try:
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pricing_result: PricingResult = calculate_pricing(
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pricing_input, metadata=metadata
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)
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except CurrencyValidationError as exc:
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raise ProfitabilityValidationError(
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str(exc), ["currency_code"]) from exc
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periods = request.periods
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revenue_total = float(pricing_result.net_revenue)
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revenue_per_period = revenue_total / periods
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processing_total = float(request.processing_opex) * periods
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sustaining_total = float(request.sustaining_capex) * periods
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initial_capex = float(request.initial_capex)
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net_per_period = (
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revenue_per_period
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- float(request.processing_opex)
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- float(request.sustaining_capex)
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)
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cash_flow_models, cash_flow_entries = _generate_cash_flows(
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periods=periods,
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net_per_period=net_per_period,
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initial_capex=initial_capex,
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)
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# Update per-period entries to include explicit costs for presentation
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for entry in cash_flow_entries[1:]:
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entry.revenue = revenue_per_period
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entry.processing_opex = float(request.processing_opex)
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entry.sustaining_capex = float(request.sustaining_capex)
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entry.net = net_per_period
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discount_rate = (request.discount_rate or 0.0) / 100.0
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npv_value = net_present_value(discount_rate, cash_flow_models)
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try:
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irr_value = internal_rate_of_return(cash_flow_models) * 100.0
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except (ValueError, ZeroDivisionError, ConvergenceError):
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irr_value = None
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try:
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payback_value = payback_period(cash_flow_models)
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except (ValueError, PaybackNotReachedError):
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payback_value = None
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total_costs = processing_total + sustaining_total + initial_capex
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total_net = revenue_total - total_costs
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if revenue_total == 0:
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margin_value = None
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else:
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margin_value = (total_net / revenue_total) * 100.0
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currency = request.currency_code or pricing_result.currency
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try:
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currency = normalise_currency(currency)
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except CurrencyValidationError as exc:
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raise ProfitabilityValidationError(
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str(exc), ["currency_code"]) from exc
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costs = ProfitabilityCosts(
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processing_opex_total=processing_total,
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sustaining_capex_total=sustaining_total,
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initial_capex=initial_capex,
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)
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metrics = ProfitabilityMetrics(
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npv=npv_value,
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irr=irr_value,
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payback_period=payback_value,
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margin=margin_value,
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)
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return ProfitabilityCalculationResult(
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pricing=pricing_result,
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costs=costs,
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metrics=metrics,
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cash_flows=cash_flow_entries,
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currency=currency,
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)
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__all__ = ["calculate_profitability"]
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