marketStats.proto

syntax = "proto3";
package marketStats;

import "google/api/annotations.proto";
import "google/protobuf/timestamp.proto";

service MarketStats {
    rpc GetRegionHistory (GetRegionRequest) returns (GetHistoryStatsResponse) {
        option (google.api.http) = {
            get: "/v1/market/stats/history/region/{region_id}"
        };
    }

    rpc GetTypeHistory (GetTypeRequest) returns (GetHistoryStatsResponse) {
        option (google.api.http) = {
            get: "/v1/market/stats/history/type/{type_id}"
        };
    }

    rpc GetRegionTypeHistory (GetRegionTypeRequest) returns (HistoryStats) {
        option (google.api.http) = {
            get: "/v1/market/stats/history/region/{region_id}/type/{type_id}"
        };
    }
}

message GetRegionRequest {
    // Defines which region the data is fetched for
    uint64 region_id = 1;
}

message GetTypeRequest {
    // Defines which type the data is fetched for
    uint64 type_id = 1;
}

message GetRegionTypeRequest {
    // Defines which region the data is fetched for
    uint64 region_id = 1;
    // Defines which type the data is fetched for
    uint64 type_id = 2;
}

message GetHistoryStatsResponse {
    // The matching history stats
    repeated HistoryStats history_stats = 1;
}

message HistoryStats {
    // The result's region's ID
    int64 region_id = 1;
    // The result's type's ID
    int64 type_id = 2;
    // Date this dataset was fetched from the server (usually at midnight)
    google.protobuf.Timestamp generated_at = 3;
    // Latest available datapoint (usually from yesterday)
    HistoryDataPoint current_stats = 4;
    // Previous datapoint
    HistoryDataPoint previous_stats = 5;
    // Last week's *weighted* average of the average price - use this for calculations!
    double week_price_weighted_average = 6;
    // Last week's average average price (ignores volume)
    double week_price_average = 7;
    // Last week's absolute standard deviation of the average price
    double week_price_average_standard_deviation = 8;
    // Last week's absolute standard deviation of the average price, can be used for analyzing price's volatility
    double week_price_average_relative_standard_deviation = 9;
    // Last week's average daily ISK volume
    double week_isk_volume_average = 10;
    // Last week's average daily ISK volume's standard deviation
    double week_isk_volume_average_standard_deviation = 11;
    // Last week's relative daily ISK volume's standard deviation, can be used for analyzing general market's volatility
    double week_isk_volume_average_relative_standard_deviation = 12;
    // Total number of orders for that type last week
    int64 week_order_count_total = 13;
    // Average daily order count last week
    double week_order_count_average = 14;
    // Average daily order count's standard deviation last week
    double week_order_count_standard_deviation = 15;
    // Average daily order count's relative standard deviation last week, again can be used for volatility
    double week_order_count_relative_standard_deviation = 16;
    // Total number of items of that type traded last week
    int64 week_volume_total = 17;
    // Average daily items traded of that type last week
    double week_volume_average = 18;
    // Standard deviation of that value
    double week_volume_standard_deviation = 19;
    // Relative standard deviation, interesting for checking if there are non-continuous patterns (volatility)
    double week_volume_relative_standard_deviation = 20;
}

message HistoryDataPoint {
    // Date of the datapoint
    google.protobuf.Timestamp date = 1;
    // Highest price the type was traded for that day
    double highest = 2;
    // Lowest price the type was traded for that day
    double lowest = 3;
    // Average price the type was traded for that day
    double average = 4;
    // Total number of items of the type traded that day
    int64 volume = 5;
    // Total number orders for the type that day
    int64 order_count = 6;
}