This application is designed to query a database to find the best price for a rental location by season. It uses Angular 4 for the front end and a back end employing Node/Express to provide data from a PostgreSQL database. The communication between the front and back end is mediated by a REST API.

The requirements for this project only asked to show the car at each location with the best price for a season. Instead, I decided to show all the available cars ordered by price since most customers do not choose a rental car solely based on price.

Also, the same car make may ne displayed multiple times in the best-price query if there are multiple cars of the same make available for a particular location in the inventory. The inventory Id is shown in the best-price query results table to confirm that the query is not displaying duplicate data.

The database contains five tables:

• location - holds one record per location
• car - holds one record for each car make
• inventory - holds a record for every car in a location's inventory. Has a one-to-many relationship with the location table
• season - holds one record for each location's season. Also has a one-to-many relation with the location table.
• price - holds a price record for every location, car and season.

The full database schema DDL can be found in the Readme.md file in the node-car-rental folder.

The amount of time available to do this project caused me to simplify a few things:

• Data was loaded into the database to allow best price querying of four locations. Further development of the application would allow data entry by an employee.
• The availability of cars in the inventory was determined by the is_rented field in the inventory table. Normally, the inventory would be linked to a transaction table which would indicate cars in the inventory rented or reserved by customers using the rental date and return date.
• Seasonal choices are shown on the front end by a drop-down to select a month. Each location had only two contiguous seasons based on months of the year. Further development of this application should require a more realistic segregation of seasons.

See the Readme.md file in each folder for how to setup the application's front and back end.