Initial full-stack test version

README.md

@@ -0,0 +1,205 @@
+# Zesty.ai engineering test (full-stack)
+
+## Background
+
+Full-stack engineers at Zesty.ai develop our web applications end-to-end, working with modern front-end frameworks, APIs 
+(ours and third parties'), and many kinds of data and imagery.
+
+This test is an opportunity for you to demonstrate your comfort with developing both an API and a UI, similar to a 
+day-to-day project you might encounter working on our team.
+
+## Assignment
+
+Your goal is to create a full-stack web application that allows developers to search for and retrieve information about 
+real estate properties. Using your language(s) and framework(s) of choice, you will need to create a front-end and
+back-end for your application and connect to the provided PostgreSQL database.
+
+Your application should include some required features, and may also include optional features. Implementing required 
+features is expected to take around 4 hours. If you feel like implementing optional features, you may spend more than 4 
+hours. Pick whichever optional features you think you can do best.
+
+Note that some features are more difficult than others, and you will be evaluated on more than just the number of
+features completed. Quality is preferred over quantity. Design, organize, and comment your code as you would a typical 
+production project. Be prepared to discuss decisions you made.
+
+### Required features
+
+* **List all properties:** Display, in a tabular format, all properties and their geographic location (longitude and 
+  latitude).
+
+* **Property detail page:** Show detailed information about a given property, including its image, geographic location, 
+  and statistics (if applicable).
+
+* **Containerization:** Include Docker image(s) of your application when submitting your final code.
+
+### Optional features
+
+* **Search by coordinates:** Prompt the user for a longitude, latitude, and search radius (default 10000 meters) and 
+  display, in a tabular format, the results of the search, including the properties' geographic location (longitude and 
+  latitude).
+
+* **Map view:** Using the 
+  [Google Maps JavaScript API](https://developers.google.com/maps/documentation/javascript/overview), display a map 
+  centered around either the user's current location, or an address they enter. Display a marker on the map for each 
+  property. Clicking on a marker should reveal an 
+  [Info Window](https://developers.google.com/maps/documentation/javascript/examples/infowindow-simple) with key 
+  property information.
+
+* **Save for later:** Allow users to save properties from the List, Search, Detail, and/or Map pages and visit their 
+  list of saved properties.
+
+* **Image overlays:** Add polygonal overlays to property images to represent either the parcel, building, or both 
+  (`parcel_geo` and `buildings_geo` fields in the database).
+
+* **Statistics:** Calculate geographic data about all properties within a given distance from a reference property. 
+  Take *propertyId* and *distance* (in meters) as inputs. The API should return the following:
+  * parcel area (meters squared)
+  * buildings areas (array, meters squared)
+  * buildings distances to center (array, meters).  Distance to center is the distance from the building to the 
+    `geocode_geo` field in the property table.
+  * zone density (percentage).  Create a "zone" geography, which is a buffer of *distance* meters around the 
+    `geocode_geo` point. Then, calculate the percentage of that zone geography which has buildings in it.
+
+## Setup
+### Development environment requirements
+
+You will need to install [Docker](https://www.docker.com/products/docker-desktop) and 
+[`docker-compose`](https://docs.docker.com/compose/install/) to run the example database.
+
+### Database startup
+From the repo root folder, run `docker-compose up -d` to start the PostgreSQL database needed for this example. The 
+database server will be exposed on port **5555**. If this port is not available on your computer, feel free to change 
+the port in the `docker-compose.yml` file.
+
+In the test database, there is a single table called `properties` (with 5 sample rows), where each row represents a 
+property or address. There are three geography<sup>*</sup> fields and one field with an image URL pointing to an image on [Google Cloud Storage](https://cloud.google.com/storage/).
+
+<sup>*</sup> *If you are not familiar with [PostgreSQL](https://www.postgresql.org/) or [PostGIS](https://postgis.net/), you may need to read up beforehand.*
+
+### API reference
+
+The API you will be implementing for this project must follow the following API specification.
+
+Note that some endpoints and parameters only apply to optional features.
+
+#### GET /display/:*id*?(overlay=yes(&parcel=:*parcelColor*)(&building=:*buildingColor*))
+
+*Fetches and displays property tile by ID. Optionally overlays parcel and building geometries on tile.*
+
+`example: GET localhost:1235/display/f853874999424ad2a5b6f37af6b56610?overlay=yes&building=green&parcel=orange`
+
+###### Request Parameters
+
+- "id" |
+  description: Property ID |
+  type: string |
+  required: true |
+  validation: length greater than 0
+
+- "overlay" |
+  description: Overlays parcel and building geometries on tile |
+  type: string |
+  required: false |
+  validation: enum("yes")
+
+- "parcel" |
+  description: Indicated building overlay color |
+  type: string |
+  required: false |
+  validation: enum(~<color>~) ex. "red", "green", "orange"
+
+- "building" |
+  description: Indicates building overlay color |
+  type: string |
+  required: false |
+  validation: enum(~<color>~) ex. "red", "green", "orange"
+
+###### Response
+
+JPEG image
+
+#### GET /properties
+
+*Lists all properties.*
+
+`example: GET localhost:1235/properties`
+
+###### Response
+
+JSON array of property objects
+
+#### POST /find
+
+*Finds properties within X meters away from provided geojson point.*
+
+`example: POST localhost:1235/find`
+
+###### Request Body
+
+- geojson object with x-distance property
+
+```
+''    example:
+''
+''    {
+''     "type": "Feature",
+''      "geometry": {
+''        "type": "Point",
+''        "coordinates": [-80.0782213, 26.8849731]
+''      },
+''      "x-distance": 1755000
+''    }
+```
+
+###### Response
+
+JSON array of property IDs
+
+#### GET /statistics/:*id*?distance=:*distance*
+
+*Returns various statistics for parcels and buildings found X meters around the requested property*
+
+`example: GET localhost:1235/statistics/f853874999424ad2a5b6f37af6b56610?distance=1755000`
+
+###### Request Parameters
+
+- "id" |
+  description: Property ID |
+  type: string |
+  required: true |
+  validation: length greater than 0
+
+- "distance" |
+  description: Buffer distance |
+  type: integer |
+  required: true |
+  validation: greater than 0
+
+###### Response
+
+JSON array including
+
+- "parcel_area_sqm" |
+  description: Total area of the property's parcel, in square meters |
+  type: float
+
+- "building_area_sqm" |
+  description: Total area of buildings inside the property's parcel, in square meters |
+  type: float
+
+- "building_distances_m" |
+  description: Array of [distance, from the centroid of the property, to the centroid of each building, in meters] |
+  type: List[float]
+
+- "zone_density" |
+  description: Array of [density of each building's area as a ratio to parcel area, dimensionless] |
+  type: List[float]
+
+
+## Submission instructions
+
+Send us your completed application's code by email, or create and give us access to a new private GitHub repository.
+
+Include instructions on how to run your app, and a list of what features you implemented. Add any comments or things you 
+want the reviewer to consider when looking at your submission. You don't need to be too detailed, as there will likely 
+be a review done with you where you can explain what you've done.

docker-compose.yml

@@ -0,0 +1,17 @@
+version: '3'
+
+services:
+  postgres:
+    image: mdillon/postgis:9.6
+    restart: always
+    ports:
+      - "5555:5432"
+    environment:
+      POSTGRES_USER: postgres
+      POSTGRES_PASSWORD: engineTest888
+      POSTGRES_DB: zesty
+    volumes:
+      - ./init-db/:/docker-entrypoint-initdb.d/
+      - pg-data:/var/lib/postgresql/data
+volumes:
+  pg-data:

init-db/01-setup.sql

@@ -0,0 +1,12 @@
+CREATE EXTENSION IF NOT EXISTS postgis;
+CREATE EXTENSION IF NOT EXISTS postgis_topology;
+
+CREATE TABLE IF NOT EXISTS public.properties (
+     id varchar(100) NOT NULL,
+     geocode_geo geography NULL,
+     parcel_geo geography NULL,
+     building_geo geography NULL,
+     image_bounds float8[] NULL,
+     image_url text NULL,
+     CONSTRAINT properties_pk PRIMARY KEY (id)
+);

init-db/02-create_test_data.sql

@@ -0,0 +1,26 @@
+TRUNCATE TABLE properties;
+
+INSERT INTO properties (id,  geocode_geo, parcel_geo, building_geo, image_bounds, image_url)
+VALUES ('f1650f2a99824f349643ad234abff6a2','0101000020E61000003A765089EB6F52C0F0259EFD92754440','0103000020E61000000100000005000000AF4B76DEE76F52C0459326408E75444061F49A1CED6F52C02E558CBA8A7544403C8D9280EF6F52C022948A1893754440B0201019EA6F52C0DF48C98696754440AF4B76DEE76F52C0459326408E754440','0103000020E6100000010000000700000004E78C28ED6F52C0250516C094754440B08C0DDDEC6F52C0A9177C9A937544409259BDC3ED6F52C0A35A4414937544409373620FED6F52C0A4C2D8429075444023827170E96F52C0EB3A54539275444076C24B70EA6F52C066C0594A9675444004E78C28ED6F52C0250516C094754440',
+        '{-73.74917015433311, 40.91823163691108, -73.74833196401596, 40.918865008051775}',
+        'https://storage.googleapis.com/engineering-test/images/f1650f2a99824f349643ad234abff6a2.tif');
+
+INSERT INTO properties (id,  geocode_geo, parcel_geo, building_geo, image_bounds, image_url)
+VALUES ('f853874999424ad2a5b6f37af6b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
+        '{-80.08276484906673, 26.324465748554815, -80.08192665874958, 26.325217013939653}',
+        'https://storage.googleapis.com/engineering-test/images/f853874999424ad2a5b6f37af6b56610.tif');
+
+INSERT INTO properties (id,  geocode_geo, parcel_geo, building_geo, image_bounds, image_url)
+VALUES ('3290ec7dd190478aab124f6f2f32bdd7','0101000020E61000007056E993010554C0F956DA988DE23A40','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','0103000020E6100000010000000B0000009AEC9FA7010554C059F8FA5A97E23A400A2C8029030554C0BD55D7A19AE23A40D93F4F03060554C007B5DFDA89E23A403F53AF5B040554C08081204086E23A40F8A6E9B3030554C0E99B340D8AE23A40942F6821010554C08D63247B84E23A4036751E15FF0454C06F675F7990E23A40FA28232E000554C0A93121E692E23A40172829B0000554C0C8B260E28FE23A40E198654F020554C0AFEE586C93E23A409AEC9FA7010554C059F8FA5A97E23A40',
+        '{-80.07864028215408, 26.88459934588957, -80.07780209183693, 26.885346941040712}',
+        'https://storage.googleapis.com/engineering-test/images/3290ec7dd190478aab124f6f2f32bdd7.tif');
+
+INSERT INTO properties (id,  geocode_geo, parcel_geo, building_geo, image_bounds, image_url)
+VALUES ('5e25c841f0ca47ac8215b5fd0076259a','0101000020E61000005840FC5731E955C0BE1F6DD223F64440','0103000020E610000001000000090000001206174930E955C04D88728721F64440023E3E4C32E955C08720957B21F64440CDC1025532E955C0EDEEA59E23F64440C45E785D32E955C042CAB5C125F64440D5863D6632E955C0BBBC50E427F644402F363C6130E955C0091459F027F64440CBD2305930E955C08F0D9ACD25F6444000EB235130E955C0B10787AA23F644401206174930E955C04D88728721F64440','0103000020E610000001000000050000007383A10E2BE955C06971C63027F644402E90A0F831E955C0878A71FE26F644408D98D9E731E955C09CC58B8521F64440D28BDAFD2AE955C0AD307DAF21F644407383A10E2BE955C06971C63027F64440',
+        '{-87.64405556023121, 41.92265629567588, -87.64321736991405, 41.92327994592767}',
+        'https://storage.googleapis.com/engineering-test/images/5e25c841f0ca47ac8215b5fd0076259a.tif');
+
+INSERT INTO properties (id,  geocode_geo, parcel_geo, building_geo, image_bounds, image_url)
+VALUES ('622088210a6f43fca2a1824e8610df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
+        '{-80.07419116795063, 26.386429931549575, -80.07335297763348, 26.387180794346914}',
+        'https://storage.googleapis.com/engineering-test/images/622088210a6f43fca2a1824e8610df03.tif');