remove large files

.github/workflows/test.yml

@@ -1,59 +0,0 @@
-name: Test
-
-on:
-  push:
-    branches: [ main ]
-  pull_request:
-    branches: [ main, staging-* ]
-  workflow_dispatch:
-
-jobs:
-  build:
-    runs-on: ${{ matrix.os }}
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ['3.10']
-        os: [ubuntu-latest]  # , macos-latest]
-
-    steps:
-      - uses: actions/checkout@v2
-      - name: Ubuntu cache
-        uses: actions/cache@v1
-        if: startsWith(matrix.os, 'ubuntu')
-        with:
-          path: ~/.cache/pip
-          key:
-            ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/pyproject.toml') }}
-          restore-keys: |
-            ${{ matrix.os }}-${{ matrix.python-version }}-
-
-      - name: macOS cache
-        uses: actions/cache@v1
-        if: startsWith(matrix.os, 'macOS')
-        with:
-          path: ~/Library/Caches/pip
-          key:
-            ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/pyproject.toml') }}
-          restore-keys: |
-            ${{ matrix.os }}-${{ matrix.python-version }}-
-
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v1
-        with:
-          python-version: ${{ matrix.python-version }}
-
-      - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install -e .[dev]
-
-      - name: Generate databases
-        run: python cities/utils/csv_to_db_pipeline.py
-
-      - name: Test
-        run: python -m pytest tests/
-
-      - name: Test Notebooks
-        run: |
-            ./scripts/test_notebooks.sh

.gitignore

@@ -23,3 +23,8 @@ tests/.coverage
 .vscode/launch.json
 data/sql/counties_database.db
 data/sql/msa_database.db
+docs/experimental_notebooks/zoning/interactions_preds.dill
+docs/experimental_notebooks/zoning/population_preds.dill
+docs/experimental_notebooks/zoning/waic_dict_7.pkl
+docs/experimental_notebooks/zoning/waic_dict_13.pkl
+docs/experimental_notebooks/zoning/waic_dict_14.pkl

build/.env

@@ -0,0 +1,10 @@
+GOOGLE_CLOUD_PROJECT=cities-429602
+GOOGLE_CLOUD_BUCKET=minneapolis-basis
+
+ENV=dev
+INSTANCE_CONNECTION_NAME=cities-429602:us-central1:cities-devel
+DB_SEARCH_PATH=dev,public
+HOST=34.123.100.76
+SCHEMA=minneapolis
+DATABASE=cities
+DB_USERNAME=postgres

build/Dockerfile

@@ -0,0 +1,10 @@
+FROM python:3
+
+WORKDIR /usr/src/app
+
+COPY requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+CMD [ "python", "main.py" ]

build/api/Dockerfile

@@ -0,0 +1,10 @@
+FROM python:3
+
+WORKDIR /usr/src/app
+
+COPY requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+CMD [ "python", "main.py" ]

build/api/main.py

@@ -0,0 +1,235 @@
+import os
+
+from typing import Annotated
+
+from dotenv import load_dotenv
+from fastapi import FastAPI, Depends, Query
+from fastapi.middleware.gzip import GZipMiddleware
+import uvicorn
+
+import psycopg2
+from psycopg2.pool import ThreadedConnectionPool
+
+load_dotenv()
+
+ENV = os.getenv("ENV")
+USERNAME = os.getenv("DB_USERNAME")
+PASSWORD = os.getenv("PASSWORD")
+HOST = os.getenv("HOST")
+DATABASE = os.getenv("DATABASE")
+DB_SEARCH_PATH = os.getenv("DB_SEARCH_PATH")
+INSTANCE_CONNECTION_NAME = os.getenv("INSTANCE_CONNECTION_NAME")
+
+app = FastAPI()
+
+if ENV == "dev":
+    from fastapi.middleware.cors import CORSMiddleware
+
+    origins = [
+        "http://localhost",
+        "http://localhost:5000",
+    ]
+    app.add_middleware(CORSMiddleware, allow_origins=origins, allow_credentials=True)
+
+app.add_middleware(GZipMiddleware, minimum_size=1000, compresslevel=5)
+
+
+if ENV == "dev":
+    host = HOST
+else:
+    host = f"/cloudsql/{INSTANCE_CONNECTION_NAME}"
+
+pool = ThreadedConnectionPool(
+    1,
+    10,
+    user=USERNAME,
+    password=PASSWORD,
+    host=HOST,
+    database=DATABASE,
+    options=f"-csearch_path={DB_SEARCH_PATH}",
+)
+
+
+def get_db() -> psycopg2.extensions.connection:
+    db = pool.getconn()
+    try:
+        yield db
+    finally:
+        pool.putconn(db)
+
+
+predictor = None
+
+
+def get_predictor(db: psycopg2.extensions.connection = Depends(get_db)):
+    from cities.deployment.tracts_minneapolis.predict import TractsModelPredictor
+
+    global predictor
+    if predictor is None:
+        predictor = TractsModelPredictor(db)
+    return predictor
+
+
+Limit = Annotated[float, Query(ge=0, le=1)]
+Radius = Annotated[float, Query(ge=0)]
+Year = Annotated[int, Query(ge=2000, le=2030)]
+
+
+@app.middleware("http")
+async def add_cache_control_header(request, call_next):
+    response = await call_next(request)
+    response.headers["Cache-Control"] = "public, max-age=300"
+    return response
+
+
+if ENV == "dev":
+
+    @app.middleware("http")
+    async def add_acess_control_header(request, call_next):
+        response = await call_next(request)
+        response.headers["Access-Control-Allow-Origin"] = "*"
+        return response
+
+
+@app.get("/demographics")
+async def read_demographics(
+    category: Annotated[str, Query(max_length=100)], db=Depends(get_db)
+):
+    with db.cursor() as cur:
+        cur.execute(
+            """
+            select tract_id, "2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019", "2020", "2021", "2022"
+            from api__demographics where description = %s
+            """,
+            (category,),
+        )
+        return [[desc[0] for desc in cur.description]] + cur.fetchall()
+
+
+@app.get("/census-tracts")
+async def read_census_tracts(year: Year, db=Depends(get_db)):
+    with db.cursor() as cur:
+        cur.execute("select * from api__census_tracts where year_ = %s", (year,))
+        row = cur.fetchone()
+
+    return row[1] if row is not None else None
+
+
+@app.get("/high-frequency-transit-lines")
+async def read_high_frequency_transit_lines(year: Year, db=Depends(get_db)):
+    with db.cursor() as cur:
+        cur.execute(
+            """
+            select line_geom_json
+            from api__high_frequency_transit_lines
+            where '%s-01-01'::date <@ valid
+            """,
+            (year,),
+        )
+        row = cur.fetchone()
+
+    return row[0] if row is not None else None
+
+
+@app.get("/high-frequency-transit-stops")
+async def read_high_frequency_transit_stops(year: Year, db=Depends(get_db)):
+    with db.cursor() as cur:
+        cur.execute(
+            """
+            select stop_geom_json
+            from api__high_frequency_transit_lines
+            where '%s-01-01'::date <@ valid
+            """,
+            (year,),
+        )
+        row = cur.fetchone()
+
+    return row[0] if row is not None else None
+
+
+@app.get("/yellow-zone")
+async def read_yellow_zone(
+    year: Year, line_radius: Radius, stop_radius: Radius, db=Depends(get_db)
+):
+    with db.cursor() as cur:
+        cur.execute(
+            """
+            select
+              st_asgeojson(st_transform(st_union(st_buffer(line_geom, %s, 'quad_segs=4'), st_buffer(stop_geom, %s, 'quad_segs=4')), 4269))::json
+            from api__high_frequency_transit_lines
+            where '%s-01-01'::date <@ valid
+            """,
+            (line_radius, stop_radius, year),
+        )
+        row = cur.fetchone()
+
+    if row is None:
+        return None
+
+    return {
+        "type": "FeatureCollection",
+        "features": [
+            {"type": "Feature", "properties": {"id": "0"}, "geometry": row[0]}
+        ],
+    }
+
+
+@app.get("/blue-zone")
+async def read_blue_zone(year: Year, radius: Radius, db=Depends(get_db)):
+    with db.cursor() as cur:
+        cur.execute(
+            """
+            select st_asgeojson(st_transform(st_buffer(line_geom, %s, 'quad_segs=4'), 4269))::json
+            from api__high_frequency_transit_lines
+            where '%s-01-01'::date <@ valid
+            """,
+            (radius, year),
+        )
+        row = cur.fetchone()
+
+    if row is None:
+        return None
+
+    return {
+        "type": "FeatureCollection",
+        "features": [
+            {"type": "Feature", "properties": {"id": "0"}, "geometry": row[0]}
+        ],
+    }
+
+
+@app.get("/predict")
+async def read_predict(
+    blue_zone_radius: Radius,
+    yellow_zone_line_radius: Radius,
+    yellow_zone_stop_radius: Radius,
+    blue_zone_limit: Limit,
+    yellow_zone_limit: Limit,
+    year: Year,
+    db=Depends(get_db),
+    predictor=Depends(get_predictor),
+):
+    result = predictor.predict_cumulative(
+        db,
+        intervention=(
+            {
+                "radius_blue": blue_zone_radius,
+                "limit_blue": blue_zone_limit,
+                "radius_yellow_line": yellow_zone_line_radius,
+                "radius_yellow_stop": yellow_zone_stop_radius,
+                "limit_yellow": yellow_zone_limit,
+                "reform_year": year,
+            }
+        ),
+    )
+    return {
+        "census_tracts": [str(t) for t in result["census_tracts"]],
+        "housing_units_factual": [t.item() for t in result["housing_units_factual"]],
+        "housing_units_counterfactual": [
+            t.tolist() for t in result["housing_units_counterfactual"]
+        ],
+    }
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=int(os.getenv("PORT", 8000)))