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Refactor various components
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18
samples/sample_program/build.gradle
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18
samples/sample_program/build.gradle
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@@ -0,0 +1,18 @@
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plugins {
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id 'application'
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}
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java {
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modularity.inferModulePath = true
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sourceCompatibility = JavaVersion.VERSION_17
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targetCompatibility = JavaVersion.VERSION_17
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}
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repositories {
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mavenCentral()
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}
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dependencies {
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implementation project(':api')
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implementation project(':core')
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}
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@@ -0,0 +1,30 @@
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package io.xpipe.sample;
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import io.xpipe.api.DataSource;
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import io.xpipe.api.DataTable;
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import io.xpipe.core.data.node.TupleNode;
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import java.util.Comparator;
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public class HomePricesSample {
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private static DataTable homePricesTable;
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public static void main(String[] args) {
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var resource = HomePricesSample.class.getResource("homes.csv");
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// Creates a wrapped data source using the url.
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// Note that while this is possible, it is not recommended as
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// all queries are routed through the XPipe client anyway.
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// It allows us however to bundle the data with this sample program.
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homePricesTable = DataSource.wrap(resource).asTable();
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System.out.println("The highest selling house entry is: " + getHighestSellingHouse());
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}
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private static TupleNode getHighestSellingHouse() {
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return homePricesTable.stream()
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.min(Comparator.comparingInt(t -> t.forKey("Sell").asInt()))
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.get();
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}
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}
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3
samples/sample_program/src/main/java/module-info.java
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3
samples/sample_program/src/main/java/module-info.java
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@@ -0,0 +1,3 @@
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module io.xpipe.sample {
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requires io.xpipe.api;
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}
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@@ -0,0 +1,52 @@
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"Sell", "List", "Living", "Rooms", "Beds", "Baths", "Age", "Acres", "Taxes"
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142, 160, 28, 10, 5, 3, 60, 0.28, 3167
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175, 180, 18, 8, 4, 1, 12, 0.43, 4033
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129, 132, 13, 6, 3, 1, 41, 0.33, 1471
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138, 140, 17, 7, 3, 1, 22, 0.46, 3204
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232, 240, 25, 8, 4, 3, 5, 2.05, 3613
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135, 140, 18, 7, 4, 3, 9, 0.57, 3028
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150, 160, 20, 8, 4, 3, 18, 4.00, 3131
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207, 225, 22, 8, 4, 2, 16, 2.22, 5158
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271, 285, 30, 10, 5, 2, 30, 0.53, 5702
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89, 90, 10, 5, 3, 1, 43, 0.30, 2054
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153, 157, 22, 8, 3, 3, 18, 0.38, 4127
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87, 90, 16, 7, 3, 1, 50, 0.65, 1445
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234, 238, 25, 8, 4, 2, 2, 1.61, 2087
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106, 116, 20, 8, 4, 1, 13, 0.22, 2818
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175, 180, 22, 8, 4, 2, 15, 2.06, 3917
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165, 170, 17, 8, 4, 2, 33, 0.46, 2220
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166, 170, 23, 9, 4, 2, 37, 0.27, 3498
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136, 140, 19, 7, 3, 1, 22, 0.63, 3607
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148, 160, 17, 7, 3, 2, 13, 0.36, 3648
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151, 153, 19, 8, 4, 2, 24, 0.34, 3561
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180, 190, 24, 9, 4, 2, 10, 1.55, 4681
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293, 305, 26, 8, 4, 3, 6, 0.46, 7088
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167, 170, 20, 9, 4, 2, 46, 0.46, 3482
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190, 193, 22, 9, 5, 2, 37, 0.48, 3920
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184, 190, 21, 9, 5, 2, 27, 1.30, 4162
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157, 165, 20, 8, 4, 2, 7, 0.30, 3785
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110, 115, 16, 8, 4, 1, 26, 0.29, 3103
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135, 145, 18, 7, 4, 1, 35, 0.43, 3363
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567, 625, 64, 11, 4, 4, 4, 0.85, 12192
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180, 185, 20, 8, 4, 2, 11, 1.00, 3831
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183, 188, 17, 7, 3, 2, 16, 3.00, 3564
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185, 193, 20, 9, 3, 2, 56, 6.49, 3765
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152, 155, 17, 8, 4, 1, 33, 0.70, 3361
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148, 153, 13, 6, 3, 2, 22, 0.39, 3950
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152, 159, 15, 7, 3, 1, 25, 0.59, 3055
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146, 150, 16, 7, 3, 1, 31, 0.36, 2950
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170, 190, 24, 10, 3, 2, 33, 0.57, 3346
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127, 130, 20, 8, 4, 1, 65, 0.40, 3334
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265, 270, 36, 10, 6, 3, 33, 1.20, 5853
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157, 163, 18, 8, 4, 2, 12, 1.13, 3982
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128, 135, 17, 9, 4, 1, 25, 0.52, 3374
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110, 120, 15, 8, 4, 2, 11, 0.59, 3119
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123, 130, 18, 8, 4, 2, 43, 0.39, 3268
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212, 230, 39, 12, 5, 3, 202, 4.29, 3648
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145, 145, 18, 8, 4, 2, 44, 0.22, 2783
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129, 135, 10, 6, 3, 1, 15, 1.00, 2438
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143, 145, 21, 7, 4, 2, 10, 1.20, 3529
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247, 252, 29, 9, 4, 2, 4, 1.25, 4626
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111, 120, 15, 8, 3, 1, 97, 1.11, 3205
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133, 145, 26, 7, 3, 1, 42, 0.36, 3059
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