""" Seed a realistic RUFORUM IILMP log frame with indicators and targets, then populate actual data points from live grant/award data. Run: python manage.py seed_mel_targets Run with clear: python manage.py seed_mel_targets --clear """ from __future__ import annotations from datetime import date from decimal import Decimal from django.contrib.auth import get_user_model from django.core.management.base import BaseCommand from django.utils.text import slugify User = get_user_model() LOGFRAME_SLUG = "ruforum-iilmp-strategic-plan-2024-2028" # Indicator definitions: (code, name, unit, calc, target_2024, target_2025, target_2026) INDICATORS = [ # ── Scholarships ──────────────────────────────────────────────────── { "code": "SCH-001", "name": "Number of MSc scholarships awarded annually", "unit": "scholarships", "level": "output", "outcome_title": "Strengthened human capacity in agricultural sciences", "target_2024": 10, "target_2025": 20, "target_2026": 30, "source_module": "rims", "call_type": "scholarship", }, { "code": "SCH-002", "name": "% of scholarship awardees who are female", "unit": "%", "level": "output", "outcome_title": "Strengthened human capacity in agricultural sciences", "target_2024": 40, "target_2025": 45, "target_2026": 50, "source_module": "rims", "call_type": "scholarship", "is_gender": True, }, { "code": "SCH-003", "name": "Number of African countries represented in scholarship cohort", "unit": "countries", "level": "output", "outcome_title": "Strengthened human capacity in agricultural sciences", "target_2024": 5, "target_2025": 8, "target_2026": 12, "source_module": "rims", "call_type": "scholarship", "is_countries": True, }, { "code": "SCH-004", "name": "% of scholarship awardees with a declared disability", "unit": "%", "level": "output", "outcome_title": "Strengthened human capacity in agricultural sciences", "target_2024": 5, "target_2025": 8, "target_2026": 10, "source_module": "rims", "call_type": "scholarship", "is_disability": True, }, # ── Research Grants ────────────────────────────────────────────────── { "code": "RG-001", "name": "Number of research grants awarded annually", "unit": "grants", "level": "output", "outcome_title": "Increased agricultural research and innovation", "target_2024": 5, "target_2025": 10, "target_2026": 15, "source_module": "rims", "call_type": "grant", }, { "code": "RG-002", "name": "% of research grant principal investigators who are female", "unit": "%", "level": "output", "outcome_title": "Increased agricultural research and innovation", "target_2024": 30, "target_2025": 35, "target_2026": 40, "source_module": "rims", "call_type": "grant", "is_gender": True, }, { "code": "RG-003", "name": "Number of countries with active research grantees", "unit": "countries", "level": "output", "outcome_title": "Increased agricultural research and innovation", "target_2024": 4, "target_2025": 7, "target_2026": 10, "source_module": "rims", "call_type": "grant", "is_countries": True, }, # ── Fellowships ────────────────────────────────────────────────────── { "code": "FEL-001", "name": "Number of fellowships awarded annually", "unit": "fellowships", "level": "output", "outcome_title": "Enhanced leadership and professional development", "target_2024": 8, "target_2025": 15, "target_2026": 20, "source_module": "rims", "call_type": "fellowship", }, { "code": "FEL-002", "name": "% of fellowship awardees who are female", "unit": "%", "level": "output", "outcome_title": "Enhanced leadership and professional development", "target_2024": 40, "target_2025": 45, "target_2026": 50, "source_module": "rims", "call_type": "fellowship", "is_gender": True, }, # ── Cross-cutting ──────────────────────────────────────────────────── { "code": "CC-001", "name": "Total number of African countries reached across all programmes", "unit": "countries", "level": "outcome", "outcome_title": "Broad and inclusive African programme reach", "target_2024": 10, "target_2025": 15, "target_2026": 20, "source_module": "rims", "call_type": None, "is_countries": True, "cross_cutting": True, }, { "code": "CC-002", "name": "Total awards made across all programme types", "unit": "awards", "level": "outcome", "outcome_title": "Broad and inclusive African programme reach", "target_2024": 23, "target_2025": 45, "target_2026": 65, "source_module": "rims", "call_type": None, "cross_cutting": True, }, { "code": "CC-003", "name": "Overall % of awardees who are female across all programmes", "unit": "%", "level": "outcome", "outcome_title": "Broad and inclusive African programme reach", "target_2024": 38, "target_2025": 42, "target_2026": 48, "source_module": "rims", "call_type": None, "is_gender": True, "cross_cutting": True, }, { "code": "CC-004", "name": "Total number of awardees with declared disability", "unit": "people", "level": "outcome", "outcome_title": "Broad and inclusive African programme reach", "target_2024": 3, "target_2025": 6, "target_2026": 10, "source_module": "rims", "call_type": None, "is_disability": True, "cross_cutting": True, }, ] class Command(BaseCommand): help = "Seed RUFORUM IILMP MEL results framework, indicators, targets and actual data points" def add_arguments(self, parser): parser.add_argument("--clear", action="store_true", help="Delete the seeded log frame and recreate") def handle(self, *args, **options): from apps.mel.indicators.models import ( DataPoint, Indicator, IndicatorFrequency, IndicatorTarget, IndicatorType, LogFrame, LogFrameLevel, LogFrameRow, ) from apps.rims.grants.models import Application, GrantCall from apps.core.countries import to_country_name if options["clear"]: LogFrame.objects.filter(slug=LOGFRAME_SLUG).delete() self.stdout.write(self.style.WARNING("Cleared seeded log frame.")) if LogFrame.objects.filter(slug=LOGFRAME_SLUG).exists(): self.stdout.write(self.style.WARNING( "Log frame already exists. Run --clear first to recreate." )) # Still refresh data points self._refresh_data_points() return director = User.objects.filter(role="program_director").first() today = date.today() # ── Create log frame ────────────────────────────────────────────── lf = LogFrame.objects.create( name="RUFORUM IILMP Strategic Plan 2024–2028", slug=LOGFRAME_SLUG, description=( "Integrated IILMP programme log frame covering scholarships, " "research grants, and fellowships across sub-Saharan Africa." ), programme="IILMP", owner=director, period_start=date(2024, 1, 1), period_end=date(2028, 12, 31), status="active", ) self.stdout.write(f" LogFrame: {lf.name}") # ── Impact row ──────────────────────────────────────────────────── impact = LogFrameRow.objects.create( logframe=lf, level=LogFrameLevel.IMPACT, title="Improved agricultural productivity and food security across Africa through strengthened human capital and research", order=0, ) # ── Outcome rows (unique titles) ────────────────────────────────── outcome_map = {} outcome_titles = list(dict.fromkeys( ind["outcome_title"] for ind in INDICATORS )) for i, title in enumerate(outcome_titles): row = LogFrameRow.objects.create( logframe=lf, parent=impact, level=LogFrameLevel.OUTCOME, title=title, order=i, ) outcome_map[title] = row self.stdout.write(f" Outcome: {title}") # ── Output rows + indicators ────────────────────────────────────── output_map = {} for ind_def in INDICATORS: outcome_row = outcome_map[ind_def["outcome_title"]] level = ind_def.get("level", "output") if level == "output": output_title = f"Output: {ind_def['outcome_title']}" if output_title not in output_map: out_row = LogFrameRow.objects.create( logframe=lf, parent=outcome_row, level=LogFrameLevel.OUTPUT, title=output_title, order=0, ) output_map[output_title] = out_row parent_row = output_map[output_title] else: parent_row = outcome_row indicator = Indicator.objects.create( logframe_row=parent_row, code=ind_def["code"], name=ind_def["name"], unit=ind_def["unit"], indicator_type=IndicatorType.QUANTITATIVE, calculation_method=f"Computed from RIMS grants module — source_module: rims", data_source="RIMS grants pipeline (awards, applications, profiles)", frequency=IndicatorFrequency.ANNUAL, source_module="rims", responsible=director, is_active=True, ) self.stdout.write(f" Indicator [{indicator.code}]: {indicator.name}") # Create targets for 2024, 2025, 2026 for year, target_val in [ (2024, ind_def["target_2024"]), (2025, ind_def["target_2025"]), (2026, ind_def["target_2026"]), ]: IndicatorTarget.objects.create( indicator=indicator, period_label=f"FY{year}", period_start=date(year, 1, 1), period_end=date(year, 12, 31), target_value=Decimal(str(target_val)), original_target_value=Decimal(str(target_val)), ) self.stdout.write(self.style.SUCCESS(" Targets created.")) self._refresh_data_points() def _refresh_data_points(self): """Compute actual values from live grant data and write DataPoints.""" from apps.mel.indicators.models import ( DataPoint, Indicator, IndicatorTarget, ) from apps.rims.grants.models import Application, GrantCall from django.db.models import Count from django.utils import timezone self.stdout.write(" Computing actual data points from grants data...") awarded_apps = Application.objects.filter( status=Application.Status.AWARDED ).select_related("scholarship_profile", "call") current_year = date.today().year period_label = f"FY{current_year}" def get_or_create_dp(indicator, target, value): DataPoint.objects.update_or_create( indicator=indicator, period_label=period_label, source_module="rims", source_event="seed_mel_targets", defaults={ "value": Decimal(str(round(value, 2))), "target": target, "status": "verified", "qualitative_note": f"Auto-computed from RIMS grants data on {date.today()}", } ) for indicator in Indicator.objects.filter(source_module="rims"): target = IndicatorTarget.objects.filter( indicator=indicator, period_label=period_label, ).first() if not target: continue code = indicator.code ind_def = next((i for i in INDICATORS if i["code"] == code), None) if not ind_def: continue call_type = ind_def.get("call_type") cross_cutting = ind_def.get("cross_cutting", False) if call_type: qs = awarded_apps.filter(call__call_type=call_type) else: qs = awarded_apps total = qs.count() if ind_def.get("is_gender"): female = qs.filter(scholarship_profile__gender="female").count() value = round(female / total * 100, 1) if total else 0 elif ind_def.get("is_countries"): value = float( qs.exclude(scholarship_profile__country_of_origin="") .exclude(scholarship_profile__isnull=True) .values_list("scholarship_profile__country_of_origin", flat=True) .distinct().count() ) elif ind_def.get("is_disability"): if indicator.unit == "%": dis = qs.filter(scholarship_profile__have_physical_disability=True).count() value = round(dis / total * 100, 1) if total else 0 else: value = float(qs.filter(scholarship_profile__have_physical_disability=True).count()) else: value = float(total) get_or_create_dp(indicator, target, value) self.stdout.write( f" [{code}] {indicator.name[:40]}... → actual: {value} / target: {target.target_value}" ) self.stdout.write(self.style.SUCCESS(" Data points refreshed."))