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:
2025-11-13 09:26:57 +01:00
parent 1240b08740
commit 1feae7ff85
16 changed files with 1931 additions and 11 deletions

View File

@@ -3,9 +3,14 @@
from __future__ import annotations
from collections import defaultdict
from statistics import fmean
from services.currency import CurrencyValidationError, normalise_currency
from services.exceptions import CapexValidationError, ProfitabilityValidationError
from services.exceptions import (
CapexValidationError,
OpexValidationError,
ProfitabilityValidationError,
)
from services.financial import (
CashFlow,
ConvergenceError,
@@ -24,6 +29,14 @@ from schemas.calculations import (
CapexTotals,
CapexTimelineEntry,
CashFlowEntry,
ProcessingOpexCalculationRequest,
ProcessingOpexCalculationResult,
ProcessingOpexCategoryBreakdown,
ProcessingOpexComponentInput,
ProcessingOpexMetrics,
ProcessingOpexParameters,
ProcessingOpexTotals,
ProcessingOpexTimelineEntry,
ProfitabilityCalculationRequest,
ProfitabilityCalculationResult,
ProfitabilityCosts,
@@ -31,6 +44,15 @@ from schemas.calculations import (
)
_FREQUENCY_MULTIPLIER = {
"daily": 365,
"weekly": 52,
"monthly": 12,
"quarterly": 4,
"annually": 1,
}
def _build_pricing_input(
request: ProfitabilityCalculationRequest,
) -> PricingInput:
@@ -332,4 +354,183 @@ def calculate_initial_capex(
)
__all__ = ["calculate_profitability", "calculate_initial_capex"]
def calculate_processing_opex(
request: ProcessingOpexCalculationRequest,
) -> ProcessingOpexCalculationResult:
"""Aggregate processing opex components into annual totals and timeline."""
if not request.components:
raise OpexValidationError(
"At least one processing opex component is required for calculation.",
["components"],
)
parameters: ProcessingOpexParameters = request.parameters
base_currency = parameters.currency_code
if base_currency:
try:
base_currency = normalise_currency(base_currency)
except CurrencyValidationError as exc:
raise OpexValidationError(
str(exc), ["parameters.currency_code"]
) from exc
evaluation_horizon = parameters.evaluation_horizon_years or 1
if evaluation_horizon <= 0:
raise OpexValidationError(
"Evaluation horizon must be at least 1 year.",
["parameters.evaluation_horizon_years"],
)
escalation_pct = float(parameters.escalation_pct or 0.0)
apply_escalation = bool(parameters.apply_escalation)
category_totals: dict[str, float] = defaultdict(float)
timeline_totals: dict[int, float] = defaultdict(float)
timeline_escalated: dict[int, float] = defaultdict(float)
normalised_components: list[ProcessingOpexComponentInput] = []
max_period_end = evaluation_horizon
for index, component in enumerate(request.components):
frequency = component.frequency.lower()
multiplier = _FREQUENCY_MULTIPLIER.get(frequency)
if multiplier is None:
raise OpexValidationError(
f"Unsupported frequency '{component.frequency}'.",
[f"components[{index}].frequency"],
)
unit_cost = float(component.unit_cost)
quantity = float(component.quantity)
annual_cost = unit_cost * quantity * multiplier
period_start = component.period_start or 1
period_end = component.period_end or evaluation_horizon
if period_end < period_start:
raise OpexValidationError(
(
"Component period_end must be greater than or equal to "
"period_start."
),
[f"components[{index}].period_end"],
)
max_period_end = max(max_period_end, period_end)
component_currency = component.currency
if component_currency:
try:
component_currency = normalise_currency(component_currency)
except CurrencyValidationError as exc:
raise OpexValidationError(
str(exc), [f"components[{index}].currency"]
) from exc
if base_currency is None and component_currency:
base_currency = component_currency
elif (
base_currency is not None
and component_currency is not None
and component_currency != base_currency
):
raise OpexValidationError(
(
"Component currency does not match the global currency. "
f"Expected {base_currency}, got {component_currency}."
),
[f"components[{index}].currency"],
)
category_totals[component.category] += annual_cost
for period in range(period_start, period_end + 1):
timeline_totals[period] += annual_cost
normalised_components.append(
ProcessingOpexComponentInput(
id=component.id,
name=component.name,
category=component.category,
unit_cost=unit_cost,
quantity=quantity,
frequency=frequency,
currency=component_currency,
period_start=period_start,
period_end=period_end,
notes=component.notes,
)
)
evaluation_horizon = max(evaluation_horizon, max_period_end)
try:
currency = normalise_currency(base_currency) if base_currency else None
except CurrencyValidationError as exc:
raise OpexValidationError(
str(exc), ["parameters.currency_code"]
) from exc
timeline_entries: list[ProcessingOpexTimelineEntry] = []
escalated_values: list[float] = []
overall_annual = timeline_totals.get(1, 0.0)
escalated_total = 0.0
for period in range(1, evaluation_horizon + 1):
base_cost = timeline_totals.get(period, 0.0)
if apply_escalation:
factor = (1 + escalation_pct / 100.0) ** (period - 1)
else:
factor = 1.0
escalated_cost = base_cost * factor
timeline_escalated[period] = escalated_cost
escalated_total += escalated_cost
timeline_entries.append(
ProcessingOpexTimelineEntry(
period=period,
base_cost=base_cost,
escalated_cost=escalated_cost if apply_escalation else None,
)
)
escalated_values.append(escalated_cost)
category_breakdowns: list[ProcessingOpexCategoryBreakdown] = []
total_base = sum(category_totals.values())
for category, total in sorted(category_totals.items()):
share = (total / total_base * 100.0) if total_base else None
category_breakdowns.append(
ProcessingOpexCategoryBreakdown(
category=category,
annual_cost=total,
share=share,
)
)
metrics = ProcessingOpexMetrics(
annual_average=fmean(escalated_values) if escalated_values else None,
cost_per_ton=None,
)
totals = ProcessingOpexTotals(
overall_annual=overall_annual,
escalated_total=escalated_total if apply_escalation else None,
escalation_pct=escalation_pct if apply_escalation else None,
by_category=category_breakdowns,
)
return ProcessingOpexCalculationResult(
totals=totals,
timeline=timeline_entries,
metrics=metrics,
components=normalised_components,
parameters=parameters,
options=request.options,
currency=currency,
)
__all__ = [
"calculate_profitability",
"calculate_initial_capex",
"calculate_processing_opex",
]