feat: Add Processing Opex functionality
- Introduced OpexValidationError for handling validation errors in processing opex calculations. - Implemented ProjectProcessingOpexRepository and ScenarioProcessingOpexRepository for managing project and scenario-level processing opex snapshots. - Enhanced UnitOfWork to include repositories for processing opex. - Updated sidebar navigation and scenario detail templates to include links to the new Processing Opex Planner. - Created a new template for the Processing Opex Planner with form handling for input components and parameters. - Developed integration tests for processing opex calculations, covering HTML and JSON flows, including validation for currency mismatches and unsupported frequencies. - Added unit tests for the calculation logic, ensuring correct handling of various scenarios and edge cases.
This commit is contained in:
@@ -3,9 +3,14 @@
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from __future__ import annotations
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from collections import defaultdict
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from statistics import fmean
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from services.currency import CurrencyValidationError, normalise_currency
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from services.exceptions import CapexValidationError, ProfitabilityValidationError
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from services.exceptions import (
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CapexValidationError,
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OpexValidationError,
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ProfitabilityValidationError,
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)
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from services.financial import (
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CashFlow,
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ConvergenceError,
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@@ -24,6 +29,14 @@ from schemas.calculations import (
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CapexTotals,
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CapexTimelineEntry,
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CashFlowEntry,
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ProcessingOpexCalculationRequest,
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ProcessingOpexCalculationResult,
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ProcessingOpexCategoryBreakdown,
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ProcessingOpexComponentInput,
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ProcessingOpexMetrics,
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ProcessingOpexParameters,
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ProcessingOpexTotals,
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ProcessingOpexTimelineEntry,
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ProfitabilityCalculationRequest,
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ProfitabilityCalculationResult,
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ProfitabilityCosts,
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@@ -31,6 +44,15 @@ from schemas.calculations import (
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)
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_FREQUENCY_MULTIPLIER = {
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"daily": 365,
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"weekly": 52,
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"monthly": 12,
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"quarterly": 4,
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"annually": 1,
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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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@@ -332,4 +354,183 @@ def calculate_initial_capex(
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)
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__all__ = ["calculate_profitability", "calculate_initial_capex"]
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def calculate_processing_opex(
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request: ProcessingOpexCalculationRequest,
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) -> ProcessingOpexCalculationResult:
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"""Aggregate processing opex components into annual totals and timeline."""
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if not request.components:
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raise OpexValidationError(
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"At least one processing opex component is required for calculation.",
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["components"],
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)
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parameters: ProcessingOpexParameters = request.parameters
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base_currency = parameters.currency_code
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if base_currency:
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try:
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base_currency = normalise_currency(base_currency)
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except CurrencyValidationError as exc:
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raise OpexValidationError(
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str(exc), ["parameters.currency_code"]
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) from exc
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evaluation_horizon = parameters.evaluation_horizon_years or 1
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if evaluation_horizon <= 0:
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raise OpexValidationError(
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"Evaluation horizon must be at least 1 year.",
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["parameters.evaluation_horizon_years"],
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)
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escalation_pct = float(parameters.escalation_pct or 0.0)
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apply_escalation = bool(parameters.apply_escalation)
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category_totals: dict[str, float] = defaultdict(float)
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timeline_totals: dict[int, float] = defaultdict(float)
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timeline_escalated: dict[int, float] = defaultdict(float)
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normalised_components: list[ProcessingOpexComponentInput] = []
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max_period_end = evaluation_horizon
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for index, component in enumerate(request.components):
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frequency = component.frequency.lower()
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multiplier = _FREQUENCY_MULTIPLIER.get(frequency)
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if multiplier is None:
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raise OpexValidationError(
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f"Unsupported frequency '{component.frequency}'.",
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[f"components[{index}].frequency"],
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)
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unit_cost = float(component.unit_cost)
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quantity = float(component.quantity)
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annual_cost = unit_cost * quantity * multiplier
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period_start = component.period_start or 1
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period_end = component.period_end or evaluation_horizon
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if period_end < period_start:
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raise OpexValidationError(
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(
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"Component period_end must be greater than or equal to "
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"period_start."
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),
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[f"components[{index}].period_end"],
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)
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max_period_end = max(max_period_end, period_end)
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component_currency = component.currency
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if component_currency:
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try:
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component_currency = normalise_currency(component_currency)
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except CurrencyValidationError as exc:
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raise OpexValidationError(
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str(exc), [f"components[{index}].currency"]
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) from exc
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if base_currency is None and component_currency:
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base_currency = component_currency
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elif (
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base_currency is not None
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and component_currency is not None
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and component_currency != base_currency
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):
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raise OpexValidationError(
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(
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"Component currency does not match the global currency. "
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f"Expected {base_currency}, got {component_currency}."
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),
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[f"components[{index}].currency"],
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)
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category_totals[component.category] += annual_cost
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for period in range(period_start, period_end + 1):
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timeline_totals[period] += annual_cost
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normalised_components.append(
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ProcessingOpexComponentInput(
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id=component.id,
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name=component.name,
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category=component.category,
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unit_cost=unit_cost,
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quantity=quantity,
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frequency=frequency,
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currency=component_currency,
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period_start=period_start,
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period_end=period_end,
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notes=component.notes,
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)
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)
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evaluation_horizon = max(evaluation_horizon, max_period_end)
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try:
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currency = normalise_currency(base_currency) if base_currency else None
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except CurrencyValidationError as exc:
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raise OpexValidationError(
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str(exc), ["parameters.currency_code"]
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) from exc
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timeline_entries: list[ProcessingOpexTimelineEntry] = []
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escalated_values: list[float] = []
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overall_annual = timeline_totals.get(1, 0.0)
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escalated_total = 0.0
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for period in range(1, evaluation_horizon + 1):
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base_cost = timeline_totals.get(period, 0.0)
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if apply_escalation:
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factor = (1 + escalation_pct / 100.0) ** (period - 1)
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else:
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factor = 1.0
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escalated_cost = base_cost * factor
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timeline_escalated[period] = escalated_cost
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escalated_total += escalated_cost
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timeline_entries.append(
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ProcessingOpexTimelineEntry(
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period=period,
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base_cost=base_cost,
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escalated_cost=escalated_cost if apply_escalation else None,
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)
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)
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escalated_values.append(escalated_cost)
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category_breakdowns: list[ProcessingOpexCategoryBreakdown] = []
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total_base = sum(category_totals.values())
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for category, total in sorted(category_totals.items()):
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share = (total / total_base * 100.0) if total_base else None
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category_breakdowns.append(
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ProcessingOpexCategoryBreakdown(
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category=category,
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annual_cost=total,
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share=share,
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)
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)
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metrics = ProcessingOpexMetrics(
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annual_average=fmean(escalated_values) if escalated_values else None,
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cost_per_ton=None,
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)
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totals = ProcessingOpexTotals(
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overall_annual=overall_annual,
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escalated_total=escalated_total if apply_escalation else None,
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escalation_pct=escalation_pct if apply_escalation else None,
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by_category=category_breakdowns,
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)
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return ProcessingOpexCalculationResult(
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totals=totals,
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timeline=timeline_entries,
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metrics=metrics,
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components=normalised_components,
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parameters=parameters,
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options=request.options,
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currency=currency,
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)
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__all__ = [
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"calculate_profitability",
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"calculate_initial_capex",
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"calculate_processing_opex",
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]
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