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feat: add metrics services and aggregation engine
New modules: - spp_metrics_services: demographic dimensions and shared metric computation services built on CEL domain - spp_aggregation: unified aggregation engine with TTL-based caching, scope-based access control, and cron-managed cache cleanup
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‎spp_aggregation/__init__.py‎

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# Part of OpenSPP. See LICENSE file for full copyright and licensing details.
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from . import models

‎spp_aggregation/__manifest__.py‎

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# Part of OpenSPP. See LICENSE file for full copyright and licensing details.
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{
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"name": "OpenSPP Aggregation Engine",
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"summary": "Unified aggregation service for statistics, simulations, and GIS queries",
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"category": "OpenSPP",
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"version": "19.0.2.0.0",
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"sequence": 1,
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"author": "OpenSPP.org",
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"website": "https://github.com/OpenSPP/OpenSPP2",
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"license": "LGPL-3",
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"development_status": "Alpha",
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"maintainers": ["jeremi"],
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"depends": [
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"base",
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"spp_cel_domain",
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"spp_area",
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"spp_registry",
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"spp_security",
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"spp_metrics_services",
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],
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"data": [
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# Security
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"security/aggregation_security.xml",
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"security/ir.model.access.csv",
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# Data
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"data/cron_cache_cleanup.xml",
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# Views
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"views/aggregation_scope_views.xml",
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"views/aggregation_access_views.xml",
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"views/menu.xml",
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],
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"assets": {},
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"demo": [],
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"images": [],
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"application": False,
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"installable": True,
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"auto_install": False,
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"description": """
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OpenSPP Aggregation Engine
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==========================
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Provides a centralized aggregation service that unifies statistics computation
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across simulation, GIS API, and dashboards.
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Features
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--------
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- **Unified Scopes**: Define targeting with CEL expressions, spatial polygons,
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administrative areas, or explicit IDs
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- **Multi-dimensional Breakdown**: Group by configurable demographic dimensions
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(gender, disability, area, age group)
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- **Privacy Protection**: K-anonymity with complementary suppression prevents
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differencing attacks
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- **Access Control**: Aggregate-only access for researchers (no individual records)
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- **Distribution Statistics**: Gini coefficient, Lorenz curve, percentiles
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- **Fairness Analysis**: Parity analysis across demographic groups
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Architecture
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------------
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::
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┌─────────────────────────────────────────────────────────┐
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│ CONSUMERS │
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├─────────────┬─────────────┬─────────────┬───────────────┤
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│ Simulation │ GIS API │ QGIS Plugin │ Dashboards │
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└──────┬──────┴──────┬──────┴──────┬──────┴───────┬───────┘
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│ │ │ │
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▼ ▼ ▼ ▼
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┌─────────────────────────────────────────────────────────┐
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│ spp.aggregation.service (AbstractModel) │
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│ │
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│ compute_aggregation(scope, statistics, group_by) │
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└─────────────────────────────────────────────────────────┘
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Models
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------
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- ``spp.aggregation.scope``: Unified targeting scope (CEL, spatial, area)
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- ``spp.aggregation.access.rule``: Access control for aggregate-only users
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- ``spp.demographic.dimension``: Configurable breakdown dimensions
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Services
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--------
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- ``spp.aggregation.service``: Main computation entry point
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- ``spp.aggregation.scope.resolver``: Resolve scope to registrant IDs
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- ``spp.aggregation.cache``: TTL-based result caching
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- ``spp.metrics.distribution``: Gini, Lorenz, percentiles
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- ``spp.metrics.fairness``: Parity analysis
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- ``spp.metrics.privacy``: K-anonymity enforcement
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""",
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}

‎spp_aggregation/data/cron_cache_cleanup.xml‎

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<?xml version="1.0" encoding="utf-8"?>
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<odoo>
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<data noupdate="1">
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<!-- Cron job to clean up expired cache entries -->
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<record id="ir_cron_cache_cleanup" model="ir.cron">
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<field name="name">Aggregation: Cache Cleanup</field>
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<field name="model_id" ref="model_spp_aggregation_cache_entry"/>
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<field name="state">code</field>
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<field name="code">model.cron_cleanup_expired()</field>
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<field name="interval_number">1</field>
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<field name="interval_type">hours</field>
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<field name="active">True</field>
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</record>
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</data>
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</odoo>

‎spp_aggregation/models/__init__.py‎

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# Part of OpenSPP. See LICENSE file for full copyright and licensing details.
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from . import aggregation_scope
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from . import aggregation_access
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from . import service_scope_resolver
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from . import service_cache
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from . import statistic_registry
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from . import service_aggregation

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