Add a plot to the website

.gitignore

@@ -167,3 +167,4 @@ cython_debug/
 #.idea/
 
 .env
+.DS_Store

Makefile

@@ -24,18 +24,14 @@ build: ## Build wheel file using poetry
 	@echo "🚀 Creating wheel file"
 	@poetry build
 
-.PHONY: docs-test
-docs-test: ## Test if documentation can be built without warnings or errors
-	@poetry run mkdocs build -s
-
-.PHONY: docs
-docs: ## Build and serve the documentation
-	@poetry run mkdocs serve
-
 .PHONY: serve
-serve: ## Serve API with uvicorn
+serve: ## Serve API with uvicorn in development mode
 	@poetry run uvicorn pypi_scout.api.main:app --reload
 
+.PHONY: frontend
+frontend: ## Serve frontend in development mode
+	@cd frontend; npm run dev
+
 .PHONY: help
 help:
 	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-20s\033[0m %s\n", $$1, $$2}'

frontend/app/components/InfoBox.tsx

@@ -24,7 +24,7 @@ const InfoBox: React.FC<InfoBoxProps> = ({ infoBoxVisible }) => {
         packages on PyPI, which includes all packages with at least ~100
         downloads per week. The results are then scored based on their
         similarity to the query and their number of weekly downloads, and the
-        best results are displayed in the table below.
+        best results are displayed in the plot and table above.
       </p>
     </div>
   );

frontend/app/components/ScatterPlot.tsx

@@ -0,0 +1,278 @@
+import React from "react";
+import { Scatter } from "react-chartjs-2";
+import {
+  Chart,
+  Tooltip,
+  Legend,
+  PointElement,
+  LinearScale,
+  Title,
+  LogarithmicScale,
+  CategoryScale,
+} from "chart.js";
+
+Chart.register(
+  Tooltip,
+  Legend,
+  PointElement,
+  LinearScale,
+  Title,
+  LogarithmicScale,
+  CategoryScale,
+);
+
+interface Match {
+  name: string;
+  similarity: number;
+  weekly_downloads: number;
+  summary: string;
+}
+
+interface ScatterPlotProps {
+  results: Match[];
+}
+
+const getColor = (
+  similarity: number,
+  downloads: number,
+  minSim: number,
+  maxSim: number,
+  minLogDownloads: number,
+  maxLogDownloads: number,
+) => {
+  const baseColor = [54, 162, 235]; // Blue
+  const highlightColor = [255, 99, 132]; // Red
+
+  const normalizedSimilarity = (similarity - minSim) / (maxSim - minSim);
+  const normalizedDownloads =
+    (Math.log10(downloads) - minLogDownloads) /
+    (maxLogDownloads - minLogDownloads);
+
+  const weight = Math.min(
+    ((normalizedSimilarity + normalizedDownloads) / 2) * 1.5,
+    1,
+  );
+
+  const color = baseColor.map((base, index) =>
+    Math.round(base + weight * (highlightColor[index] - base)),
+  );
+
+  return `rgba(${color.join(",")}, 0.8)`;
+};
+
+const getPointSize = (
+  similarity: number,
+  downloads: number,
+  minSim: number,
+  maxSim: number,
+  minLogDownloads: number,
+  maxLogDownloads: number,
+) => {
+  const normalizedSimilarity = (similarity - minSim) / (maxSim - minSim);
+  const normalizedDownloads =
+    (Math.log10(downloads) - minLogDownloads) /
+    (maxLogDownloads - minLogDownloads);
+
+  const minSize = 2;
+  const size = Math.min(
+    (normalizedSimilarity + normalizedDownloads) * 10 + minSize,
+    25,
+  );
+  return size;
+};
+
+const ScatterPlot: React.FC<ScatterPlotProps> = ({ results }) => {
+  const similarities = results.map((result) => result.similarity);
+  const downloads = results.map((result) => result.weekly_downloads);
+  const logDownloads = downloads.map((download) => Math.log10(download));
+
+  const minSim = Math.min(...similarities);
+  const maxSim = Math.max(...similarities);
+  const minLogDownloads = Math.min(...logDownloads);
+  const maxLogDownloads = Math.max(...logDownloads);
+
+  const data = {
+    datasets: [
+      {
+        label: "Packages",
+        data: results.map((result) => ({
+          x: result.similarity,
+          y: result.weekly_downloads,
+          name: result.name,
+          summary: result.summary,
+          link: `https://pypi.org/project/${result.name}/`,
+        })),
+        backgroundColor: results.map((result) =>
+          getColor(
+            result.similarity,
+            result.weekly_downloads,
+            minSim,
+            maxSim,
+            minLogDownloads,
+            maxLogDownloads,
+          ),
+        ),
+        borderColor: results.map((result) =>
+          getColor(
+            result.similarity,
+            result.weekly_downloads,
+            minSim,
+            maxSim,
+            minLogDownloads,
+            maxLogDownloads,
+          ),
+        ),
+        pointRadius: results.map((result) =>
+          getPointSize(
+            result.similarity,
+            result.weekly_downloads,
+            minSim,
+            maxSim,
+            minLogDownloads,
+            maxLogDownloads,
+          ),
+        ),
+        hoverBackgroundColor: results.map((result) =>
+          getColor(
+            result.similarity,
+            result.weekly_downloads,
+            minSim,
+            maxSim,
+            minLogDownloads,
+            maxLogDownloads,
+          ),
+        ),
+        hoverBorderColor: results.map((result) =>
+          getColor(
+            result.similarity,
+            result.weekly_downloads,
+            minSim,
+            maxSim,
+            minLogDownloads,
+            maxLogDownloads,
+          ),
+        ),
+        pointHoverRadius: 15,
+      },
+    ],
+  };
+
+  const options = {
+    responsive: true,
+    maintainAspectRatio: false,
+    plugins: {
+      tooltip: {
+        callbacks: {
+          title: (context: any) => {
+            const dataPoint = context[0].raw;
+            return dataPoint.name;
+          },
+          beforeLabel: (context: any) => {
+            const dataPoint = context.raw;
+            return dataPoint.summary;
+          },
+          label: () => "",
+          afterLabel: (context: any) => {
+            const dataPoint = context.raw;
+            return `\nWeekly downloads: ${dataPoint.y.toLocaleString()}`;
+          },
+        },
+        titleFont: { size: 16, weight: "bold" },
+        bodyFont: { size: 14 },
+        footerFont: { size: 12 },
+        displayColors: false,
+        backgroundColor: "rgba(0, 0, 0, 0.8)",
+        padding: 10,
+        bodySpacing: 4,
+        titleAlign: "left",
+        bodyAlign: "left",
+        footerAlign: "left",
+      },
+      legend: {
+        display: false,
+      },
+    },
+    scales: {
+      x: {
+        title: {
+          display: true,
+          text: "Similarity",
+          color: "#FFFFFF",
+          font: {
+            size: 24,
+          },
+        },
+        ticks: {
+          color: "#FFFFFF",
+        },
+      },
+      y: {
+        title: {
+          display: true,
+          text: "Weekly Downloads",
+          color: "#FFFFFF",
+          font: {
+            size: 24,
+          },
+        },
+        ticks: {
+          callback: function (value: any) {
+            return value.toLocaleString();
+          },
+          color: "#FFFFFF",
+          maxTicksLimit: 5,
+        },
+        type: "logarithmic",
+      },
+    },
+    onClick: (event: any, elements: any) => {
+      if (elements.length > 0) {
+        const elementIndex = elements[0].index;
+        const datasetIndex = elements[0].datasetIndex;
+        const link = data.datasets[datasetIndex].data[elementIndex].link;
+        window.open(link, "_blank");
+      }
+    },
+    onHover: (event: any, elements: any) => {
+      event.native.target.style.cursor = elements[0] ? "pointer" : "default";
+    },
+    elements: {
+      point: {
+        hoverRadius: 15,
+      },
+    },
+  };
+
+  const plugins = [
+    {
+      id: "customLabels",
+      afterDatasetsDraw: (chart: any) => {
+        const ctx = chart.ctx;
+        chart.data.datasets.forEach((dataset: any) => {
+          dataset.data.forEach((dataPoint: any, index: number) => {
+            const { x, y } = chart
+              .getDatasetMeta(0)
+              .data[index].tooltipPosition();
+            ctx.fillStyle = "white";
+            ctx.textAlign = "center";
+            ctx.fillText(dataPoint.name, x, y - 10);
+          });
+        });
+      },
+    },
+  ];
+
+  return (
+    <div className="overflow-auto w-full flex flex-col items-center">
+      <h2 className="text-center text-white mb-4">
+        Click a package to go to PyPI
+      </h2>
+      <hr className="border-gray-500 mb-4 w-full" />
+      <div className="w-full h-[600px]">
+        <Scatter data={data} options={options} plugins={plugins} />
+      </div>
+    </div>
+  );
+};
+
+export default ScatterPlot;

frontend/app/components/ToggleSwitch.tsx

@@ -0,0 +1,42 @@
+import React from "react";
+
+interface ToggleSwitchProps {
+  option1: string;
+  option2: string;
+  selectedOption: string;
+  onToggle: (option: string) => void;
+}
+
+const ToggleSwitch: React.FC<ToggleSwitchProps> = ({
+  option1,
+  option2,
+  selectedOption,
+  onToggle,
+}) => {
+  return (
+    <div className="flex space-x-4 bg-sky-800 p-2 rounded-lg shadow-md">
+      <button
+        className={`px-4 py-2 rounded ${
+          selectedOption === option1
+            ? "bg-white text-sky-900"
+            : " bg-sky-950 text-white"
+        }`}
+        onClick={() => onToggle(option1)}
+      >
+        {option1}
+      </button>
+      <button
+        className={`px-4 py-2 rounded ${
+          selectedOption === option2
+            ? "bg-white text-sky-900"
+            : " bg-sky-950 text-white"
+        }`}
+        onClick={() => onToggle(option2)}
+      >
+        {option2}
+      </button>
+    </div>
+  );
+};
+
+export default ToggleSwitch;