Unique method of processing API data supporting wide variety of data types and multiple/singular formats without data duplication
A computer-implemented approach is described that includes receiving a mass price computation request for a plurality of deals involving a plurality of vehicles. The request includes a data structure configured to store input values, and a tri-value field configured to store a tri-value, the tri-value being one of a first value, a second value, or a third value, the first value indicating a single computation is requested using the input values, the second value indicating a limited set of combinatorial calculations to be calculated using the input values, and the third value indicating a full set of combinatorial calculations using the input values. The approach further causes computing of each of the plurality of deals based on the data structure, and outputting results to a user device based on the mass price computation request.
1 . A computer-implemented method comprising:
receiving a mass price computation request for a plurality of deals involving a plurality of vehicles, the mass price computation request including a data structure configured to store input values, the data structure including a tri-value field configured to store a tri-value, the tri-value being one of a first value, a second value, or a third value, the first value indicating a single computation is requested using the input values, the second value indicating a limited set of combinatorial calculations to be calculated using the input values, and the third value indicating a full set of combinatorial calculations using the input values;
causing computing of each of the plurality of deals based on the data structure, wherein the computing includes:
computing using a first sub-process a risk score for each vehicle-deal requested in a multidimensional vehicle-deal request,
causing using a second sub-process a set of pre-pricing derived variables to be computed across a network using first asynchronous parallel thread processing by a first plurality of micro-services servers,
packaging computing, as part of the causing using the second sub-process, of the set of pre-pricing derived variables into one or more asynchronous threads for execution by the first plurality of micro-services servers in the network,
computing using a third sub-process a respective price for each vehicle-deal requested in the multidimensional vehicle-deal request, and
causing, using a fourth sub-process and based on each respective price, a set of post-pricing derived variables to be computed across the network using second asynchronous parallel thread processing by a second plurality of micro-services servers,
packaging computing, as part of the causing using the fourth sub-process, of the set of post-pricing derived variables into one or more asynchronous threads for execution by the second plurality of micro-services servers in the network; and
outputting results to a user device based on the mass price computation request.
2 . The method of claim 1 , wherein a type of input values includes one of Integer, IntegerArray, double, doubleArray, String, StringArray, Map, Boolean, and Calendar.
3 . The method of claim 1 , wherein the data structure is a text file or an encoded file.
4 . The method of claim 1 , wherein at least one of the input values is associated with a credit policy.
5 . The method of claim 1 , wherein at least one of the input values is associated with a dealer involved with the plurality of vehicles.
6 . The method of claim 1 , wherein at least one of the input values is associated with a financial computation.
7 . The method of claim 1 , wherein the causing computing includes causing computing of one or more output values to form the results.
8 . The method of claim 1 , wherein receiving the mass price computation request includes receiving the mass price computation request via an application programming interface.
9 . The method of claim 1 , wherein the data structure is further configured to store updated input values.
10 . The method of claim 1 , wherein the data structure is further configured to store a version number for a parameter associated with at least one of the input values.
11 . A non-transitory machine-readable storage medium that provides instructions that, if executed by at least one computing device, are configurable to cause said at least one computing device to perform operations comprising:
receiving a mass price computation request for a plurality of deals involving a plurality of vehicles, the mass price computation request including a data structure configured to store input values, the data structure including a tri-value field configured to store a tri-value, the tri-value being one of a first value, a second value, or a third value, the first value indicating a single computation is requested using the input values, the second value indicating a limited set of combinatorial calculations to be calculated using the input values, and the third value indicating a full set of combinatorial calculations using the input values,
computing the plurality of deals involving the plurality of vehicles based on the data structure, wherein the computing includes:
computing using a first sub-process a risk score for each vehicle-deal requested in a multidimensional vehicle-deal request,
causing using a second sub-process a set of pre-pricing derived variables to be computed across a network using first asynchronous parallel thread processing by a first plurality of micro-services servers,
packaging computing, as part of the causing using the second sub-process, of the set of pre-pricing derived variables into one or more asynchronous threads for execution by the first plurality of micro-services servers in the network,
computing using a third sub-process a respective price for each vehicle-deal requested in the multidimensional vehicle-deal request, and
causing, using a fourth sub-process and based on each respective price, a set of post-pricing derived variables to be computed across the network using second asynchronous parallel thread processing by a second plurality of micro-services servers,
packaging computing, as part of the causing using the fourth sub-process, of the set of post-pricing derived variables into one or more asynchronous threads for execution by the second plurality of micro-services servers in the network; and
causes outputting of results to a user device based on the mass price computation request.
12 . The non-transitory machine-readable storage medium of claim 11 , wherein a type of input values includes one of Integer, IntegerArray, double, doubleArray, String, StringArray, Map, Boolean, and Calendar.
13 . The non-transitory machine-readable storage medium of claim 11 , wherein the data structure is a text file or an encoded file.
14 . The non-transitory machine-readable storage medium of claim 11 , wherein at least one of the input values is associated with a credit policy.
15 . The non-transitory machine-readable storage medium of claim 11 , wherein at least one of the input values is associated with a dealer involved with the plurality of vehicles.
16 . The non-transitory machine-readable storage medium of claim 11 , wherein at least one of the input values is associated with a financial computation.
17 . The non-transitory machine-readable storage medium of claim 11 , wherein the causing computing includes causing computing of one or more output values to form the results.
18 . The non-transitory machine-readable storage medium of claim 11 , wherein receiving the mass price computation request includes receiving the mass price computation request via an application programming interface.
19 . The non-transitory machine-readable storage medium of claim 11 , wherein the data structure is further configured to store updated input values.
20 . The non-transitory machine-readable storage medium of claim 11 , wherein the data structure is further configured to store a version number for a parameter associated with at least one of the input values.