lmiranda
053acf6436
Add schemas, parsers, loaders, and models for Toronto neighbourhood-centric data including census profiles, crime statistics, and amenities. Schemas: - NeighbourhoodRecord, CensusRecord, CrimeRecord, CrimeType - AmenityType, AmenityRecord, AmenityCount Models: - BridgeCMHCNeighbourhood (zone-to-neighbourhood mapping with weights) - FactCensus, FactCrime, FactAmenities Parsers: - TorontoOpenDataParser (CKAN API for neighbourhoods, census, amenities) - TorontoPoliceParser (crime rates, MCI data) Loaders: - load_census_data, load_crime_data, load_amenities - build_cmhc_neighbourhood_crosswalk (PostGIS area weights) Also updates CLAUDE.md with projman plugin workflow documentation. Closes #53, #54, #55, #56, #57, #58, #59 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
107 lines
3.7 KiB
Python
107 lines
3.7 KiB
Python
"""Pydantic schemas for Toronto neighbourhood data.
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Includes schemas for neighbourhood boundaries, census profiles, and crime statistics.
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"""
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from decimal import Decimal
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from enum import Enum
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from typing import Any
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from pydantic import BaseModel, Field
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class CrimeType(str, Enum):
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"""Major crime indicator types from Toronto Police data."""
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ASSAULT = "assault"
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AUTO_THEFT = "auto_theft"
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BREAK_AND_ENTER = "break_and_enter"
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HOMICIDE = "homicide"
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ROBBERY = "robbery"
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SHOOTING = "shooting"
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THEFT_OVER = "theft_over"
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THEFT_FROM_MOTOR_VEHICLE = "theft_from_motor_vehicle"
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OTHER = "other"
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class NeighbourhoodRecord(BaseModel):
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"""Schema for Toronto neighbourhood boundary data.
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Based on City of Toronto's 158 neighbourhoods dataset.
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AREA_ID maps to neighbourhood_id for consistency with police data (Hood_ID).
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"""
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area_id: int = Field(description="AREA_ID from Toronto Open Data (1-158)")
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area_name: str = Field(max_length=100, description="Official neighbourhood name")
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area_short_code: str | None = Field(
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default=None, max_length=10, description="Short code (e.g., 'E01')"
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)
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geometry: dict[str, Any] | None = Field(
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default=None, description="GeoJSON geometry object"
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)
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model_config = {"str_strip_whitespace": True}
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class CensusRecord(BaseModel):
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"""Census profile data for a neighbourhood.
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Contains demographic and socioeconomic indicators from Statistics Canada
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census data, aggregated to the neighbourhood level.
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"""
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neighbourhood_id: int = Field(
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ge=1, le=200, description="Neighbourhood ID (AREA_ID)"
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)
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census_year: int = Field(ge=2016, le=2030, description="Census year")
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population: int | None = Field(default=None, ge=0, description="Total population")
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population_density: Decimal | None = Field(
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default=None, ge=0, description="Population per square kilometre"
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)
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median_household_income: Decimal | None = Field(
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default=None, ge=0, description="Median household income (CAD)"
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)
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average_household_income: Decimal | None = Field(
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default=None, ge=0, description="Average household income (CAD)"
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)
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unemployment_rate: Decimal | None = Field(
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default=None, ge=0, le=100, description="Unemployment rate percentage"
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)
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pct_bachelors_or_higher: Decimal | None = Field(
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default=None, ge=0, le=100, description="Percentage with bachelor's degree+"
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)
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pct_owner_occupied: Decimal | None = Field(
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default=None, ge=0, le=100, description="Percentage owner-occupied dwellings"
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)
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pct_renter_occupied: Decimal | None = Field(
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default=None, ge=0, le=100, description="Percentage renter-occupied dwellings"
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)
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median_age: Decimal | None = Field(
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default=None, ge=0, le=120, description="Median age of residents"
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)
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average_dwelling_value: Decimal | None = Field(
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default=None, ge=0, description="Average dwelling value (CAD)"
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)
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model_config = {"str_strip_whitespace": True}
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class CrimeRecord(BaseModel):
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"""Crime statistics for a neighbourhood.
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Based on Toronto Police neighbourhood crime rates data.
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Hood_ID in source data maps to neighbourhood_id (AREA_ID).
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"""
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neighbourhood_id: int = Field(
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ge=1, le=200, description="Neighbourhood ID (Hood_ID -> AREA_ID)"
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)
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year: int = Field(ge=2014, le=2030, description="Year of crime statistics")
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crime_type: CrimeType = Field(description="Type of crime (MCI category)")
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count: int = Field(ge=0, description="Number of incidents")
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rate_per_100k: Decimal | None = Field(
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default=None, ge=0, description="Rate per 100,000 population"
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)
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model_config = {"str_strip_whitespace": True}
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