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Merged
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Jun 19, 2025
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Create deployment to be used in the blog #1

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339 changes: 339 additions & 0 deletions content/3rd-party-libs.ipynb
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{
"metadata": {
"kernelspec": {
"name": "xcpp23",
"display_name": "C++23",
"language": "cpp"
},
"language_info": {
"codemirror_mode": "text/x-c++src",
"file_extension": ".cpp",
"mimetype": "text/x-c++src",
"name": "C++",
"version": "23"
}
},
"nbformat_minor": 5,
"nbformat": 4,
"cells": [
{
"id": "472d1671-a068-4ce5-afae-076586f0b1b3",
"cell_type": "markdown",
"source": "<center>\n <h1>Interactive Demos of C++ Libraries in the Browser</h1>\n <h3>Powered by Xeus-Cpp-Lite and WebAssembly</h3>\n</center>\n\nThis notebook demonstrates several powerful C++ libraries running entirely in the browser using **xeus-cpp-lite**. The examples span symbolic computation, numerical analysis, interactive visualization, and more — all compiled to WebAssembly and ready to run in a JupyterLite environment.\n\n**Featured libraries:**\n\n1. **Scientific Computation (Symbolic & Numeric)**: `boost`, `symengine`, `openblas`\n2. **Array based Computation through Xtensor-stack**: `xtl`, `xtensor`, `xsimd`, `xtensor-blas`\n3. **Interactive Widgets**: `xwidgets`, `xcanvas`\n4. **Utilities & Miscellaneous**: `nlohmann_json`, and others",
"metadata": {}
},
{
"id": "c5f00d53-7cc9-43fb-82c7-c69b631e7b92",
"cell_type": "markdown",
"source": "## Scientific Computation (Symbolic & Numeric)\n\nLet’s begin with powerful C++ libraries for symbolic math, high-precision arithmetic, and efficient numerical computation using BLAS and LAPACK routines.",
"metadata": {}
},
{
"id": "7ef2ba09-bcc8-41e2-b503-3b21e60fdd3e",
"cell_type": "code",
"source": "#include <boost/multiprecision/cpp_int.hpp>\nusing namespace boost::multiprecision;\nusing namespace std;\n\nint128_t boost_product(long long A, long long B)\n{\n int128_t ans = (int128_t)A * B;\n return ans;\n}\n\nlong long first = 98745636214564698;\nlong long second = 7459874565236544789;\ncout << \"Product of \" << first << \" * \" << second << \" = \\n\"\n << boost_product(first, second);",
"metadata": {
"trusted": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "Product of 98745636214564698 * 7459874565236544789 = \n736630060025131838840151335215258722"
}
],
"execution_count": 1
},
{
"id": "d8e235a1-5d41-43f8-8908-9f76b4c6c1d7",
"cell_type": "code",
"source": "#include <symengine/expression.h>\n\nusing namespace SymEngine;\n\nExpression x(\"x\");\nauto ex = pow(x + sqrt(Expression(2)), 6);",
"metadata": {
"trusted": true
},
"outputs": [],
"execution_count": 2
},
{
"id": "82912670-8abf-4364-8bfb-b55e206fb153",
"cell_type": "code",
"source": "#include <xcpp/xdisplay.hpp>\nxcpp::display(ex);",
"metadata": {
"trusted": true
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/latex": "$\\left(x + \\sqrt{2}\\right)^6$",
"text/plain": "(x + sqrt(2))**6"
},
"metadata": {}
}
],
"execution_count": 3
},
{
"id": "f738315b-f1ed-48b8-ae71-250b3667c694",
"cell_type": "code",
"source": "auto expanded_ex = expand(ex);\nxcpp::display(expanded_ex);",
"metadata": {
"trusted": true
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/latex": "$8 + 24 \\sqrt{2} x + 40 \\sqrt{2} x^3 + 6 \\sqrt{2} x^5 + 60 x^2 + 30 x^4 + x^6$",
"text/plain": "8 + 24*sqrt(2)*x + 40*sqrt(2)*x**3 + 6*sqrt(2)*x**5 + 60*x**2 + 30*x**4 + x**6"
},
"metadata": {}
}
],
"execution_count": 4
},
{
"id": "f25ec9b7-951e-4494-b932-64d71a601127",
"cell_type": "code",
"source": "#include <iostream>\n#include <iomanip>\n\ntypedef int INTEGER;\ntypedef double DOUBLE;\n\nextern \"C\" {\n int dgetrf_(const INTEGER* m, const INTEGER* n, DOUBLE* a,\n const INTEGER* lda, INTEGER* ipiv, INTEGER* info);\n}\n\nconst INTEGER m = 3, n = 3, lda = 3;\nDOUBLE A[9] = {\n 1.0, 2.0, 3.0,\n 4.0, 5.0, 6.0,\n 7.0, 8.0, 10.0\n}; // Column-major layout\n\nINTEGER ipiv[3];\nINTEGER info;\n\ndgetrf_(&m, &n, A, &lda, ipiv, &info);\n\n// Output\nstd::cout << std::fixed << std::setprecision(6);\nstd::cout << \"LU Decomposition (OpenBLAS dgetrf_)\\n\";\nstd::cout << \"info: \" << info << \"\\n\\n\";\n\nstd::cout << \"Factorized Matrix (A after dgetrf_):\\n\";\nfor (int i = 0; i < m; ++i) {\n for (int j = 0; j < n; ++j)\n std::cout << std::setw(10) << A[i + j * lda];\n std::cout << \"\\n\";\n}\n\nstd::cout << \"\\nPivot Indices:\\n\";\nfor (int i = 0; i < std::min(m, n); ++i)\n std::cout << ipiv[i] << \" \";\nstd::cout << \"\\n\";\n",
"metadata": {
"trusted": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "LU Decomposition (OpenBLAS dgetrf_)\ninfo: 0\n\nFactorized Matrix (A after dgetrf_):\n 3.000000 6.000000 10.000000\n 0.333333 2.000000 3.666667\n 0.666667 0.500000 -0.500000\n\nPivot Indices:\n3 3 3 \n"
}
],
"execution_count": 5
},
{
"id": "6b7e64a2-546c-47a7-b4ed-95e98febd785",
"cell_type": "markdown",
"source": "## Array based Computation through Xtensor-stack\n\nExplore NumPy-style array computing in C++ with Xtensor, Xtensor-BLAS, and Xsimd — enabling high-performance numerical and SIMD-accelerated workflows.",
"metadata": {}
},
{
"id": "6496d5e7-d1e5-4437-be87-bb26b48ce735",
"cell_type": "code",
"source": "#include \"xtensor/containers/xarray.hpp\"\n#include \"xtensor/io/xio.hpp\"\n#include \"xtensor/views/xview.hpp\"\n\nxt::xarray<double> arr1 = {{1.0, 2.0, 3.0}, {2.0, 5.0, 7.0}, {2.0, 5.0, 7.0}};\nxt::xarray<double> arr2{5.0, 6.0, 7.0};\n\nxcpp::display(xt::view(arr1, 1) + arr2);",
"metadata": {
"trusted": true
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": "<table style='border-style:solid;border-width:1px;'><tbody><tr><td style='font-family:monospace;' title='0'><pre> 7.</pre></td></tr><tr><td style='font-family:monospace;' title='1'><pre> 11.</pre></td></tr><tr><td style='font-family:monospace;' title='2'><pre> 14.</pre></td></tr></tbody></table>"
},
"metadata": {}
}
],
"execution_count": 6
},
{
"id": "c748227d-4083-4c19-8f07-a449d41e67fe",
"cell_type": "code",
"source": "xt::xarray<int> arr = {1, 2, 3, 4, 5, 6, 7, 8, 9};\narr.reshape({3, 3});\n\nxcpp::display(arr);",
"metadata": {
"trusted": true
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": "<table style='border-style:solid;border-width:1px;'><tbody><tr><td style='font-family:monospace;' title='(0, 0)'><pre>1</pre></td><td style='font-family:monospace;' title='(0, 1)'><pre>2</pre></td><td style='font-family:monospace;' title='(0, 2)'><pre>3</pre></td></tr><tr><td style='font-family:monospace;' title='(1, 0)'><pre>4</pre></td><td style='font-family:monospace;' title='(1, 1)'><pre>5</pre></td><td style='font-family:monospace;' title='(1, 2)'><pre>6</pre></td></tr><tr><td style='font-family:monospace;' title='(2, 0)'><pre>7</pre></td><td style='font-family:monospace;' title='(2, 1)'><pre>8</pre></td><td style='font-family:monospace;' title='(2, 2)'><pre>9</pre></td></tr></tbody></table>"
},
"metadata": {}
}
],
"execution_count": 7
},
{
"id": "74298554-9964-4633-bff3-e67d03a1797d",
"cell_type": "code",
"source": "#include <iostream>\n#include \"xtensor-blas/xlinalg.hpp\"\n\nxt::xtensor<double, 2> M = {{1.5, 0.5}, {0.7, 1.0}};",
"metadata": {
"trusted": true
},
"outputs": [],
"execution_count": 8
},
{
"id": "22dadb84-d39e-4028-a919-febd64f4a60d",
"cell_type": "code",
"source": "std::cout << \"Matrix rank: \" << xt::linalg::matrix_rank(M) << std::endl;\nstd::cout << \"Matrix inverse: \" << std::endl;\nxcpp::display(xt::linalg::inv(M));\nstd::cout << \"Eigen values: \" << std::endl;\nxcpp::display(xt::linalg::eigvals(M));",
"metadata": {
"trusted": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "Matrix rank: 2\nMatrix inverse: \n"
},
{
"output_type": "display_data",
"data": {
"text/html": "<table style='border-style:solid;border-width:1px;'><tbody><tr><td style='font-family:monospace;' title='(0, 0)'><pre> 0.869565</pre></td><td style='font-family:monospace;' title='(0, 1)'><pre>-0.434783</pre></td></tr><tr><td style='font-family:monospace;' title='(1, 0)'><pre>-0.608696</pre></td><td style='font-family:monospace;' title='(1, 1)'><pre> 1.304348</pre></td></tr></tbody></table>"
},
"metadata": {}
},
{
"name": "stdout",
"output_type": "stream",
"text": "Eigen values: \n"
},
{
"output_type": "display_data",
"data": {
"text/html": "<table style='border-style:solid;border-width:1px;'><tbody><tr><td style='font-family:monospace;' title='0'><pre> 1.892262+0.i</pre></td></tr><tr><td style='font-family:monospace;' title='1'><pre> 0.607738+0.i</pre></td></tr></tbody></table>"
},
"metadata": {}
}
],
"execution_count": 9
},
{
"id": "d8e9e9e7-5def-4d77-b459-afb8002282ae",
"cell_type": "code",
"source": "#include <xsimd/xsimd.hpp>\n\nnamespace xs = xsimd;\n\n// Define two SIMD float vectors using the wasm backend\nxs::batch<float, xs::wasm> X = {1.2f, 3.4f, 5.6f, 7.8f};\nxs::batch<float, xs::wasm> Y = {2.1f, 4.3f, 6.5f, 8.7f};\n\n// Perform SIMD addition\nxs::batch<float, xs::wasm> Z = X + Y;\n\n// Print the result\nstd::cout << Z << std::endl;",
"metadata": {
"trusted": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "(3.300000, 7.700000, 12.100000, 16.500000)\n"
}
],
"execution_count": 10
},
{
"id": "0f0978c4-7ec4-4615-894a-c6558503d851",
"cell_type": "markdown",
"source": "## Interactive Widgets\n\nBuild rich, interactive UI components in C++ using xwidgets and xcanvas, seamlessly integrated with the Jupyter frontend.",
"metadata": {}
},
{
"id": "2ce27d4d-43f7-464c-a611-5400c3cdb735",
"cell_type": "code",
"source": "#include <xwidgets/xslider.hpp>\n\nxw::slider<double> slider;",
"metadata": {
"trusted": true
},
"outputs": [],
"execution_count": 11
},
{
"id": "36b1b0f7-00d9-47bf-8543-985e27088d07",
"cell_type": "code",
"source": "slider.value = 20;\nslider.max = 40;\nslider.style().handle_color = \"blue\";\nslider.orientation = \"vertical\";\nslider.description = \"A slider\";",
"metadata": {
"trusted": true
},
"outputs": [],
"execution_count": 12
},
{
"id": "b2647bb5-0c2e-4f12-b0ed-0c0f5c7ed65c",
"cell_type": "code",
"source": "// Need to re-run this to see the slider being displayed\nxcpp::display(slider);",
"metadata": {
"trusted": true
},
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "07f19b34aac74f97947e4e9b068ebe5f",
"version_major": 2,
"version_minor": 1
},
"text/plain": "A Jupyter widget with unique id: 07f19b34aac74f97947e4e9b068ebe5f"
},
"metadata": {}
}
],
"execution_count": 13
},
{
"id": "0f3e4dcb-5d9f-479b-b568-8d7625683946",
"cell_type": "code",
"source": "#include <sstream>\n#include \"xcanvas/xcanvas.hpp\"\n\nauto canvas = xc::canvas().initialize()\n .width(300)\n .height(300)\n .finalize();",
"metadata": {
"trusted": true
},
"outputs": [],
"execution_count": 14
},
{
"id": "1eed2b39-b632-440c-9d3d-c8d377bc504c",
"cell_type": "code",
"source": "canvas.shadow_offset_x = 0;\ncanvas.shadow_offset_y = 0;\ncanvas.shadow_blur = 0;\n\nfor (std::size_t i = 0; i < 200; i++)\n{\n std::stringstream color;\n color << \"rgb(200, \" << 200 - i << \", \" << i << \")\";\n canvas.fill_style = color.str();\n canvas.fill_rect(0, 0, 200, 200 - i);\n}",
"metadata": {
"trusted": true
},
"outputs": [],
"execution_count": 15
},
{
"id": "4d1797e5-3ce1-4737-9561-a87a7e82cce1",
"cell_type": "code",
"source": "// Need to re-run this to see the canvas being displayed\nxcpp::display(canvas);",
"metadata": {
"trusted": true
},
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "e34c45cc453240cebac33426cd7c448d",
"version_major": 2,
"version_minor": 1
},
"text/plain": "A Jupyter widget with unique id: e34c45cc453240cebac33426cd7c448d"
},
"metadata": {}
}
],
"execution_count": 16
},
{
"id": "d26a70d2-9dc6-4ca0-b974-2cfd4249a8a7",
"cell_type": "markdown",
"source": "## Miscallaneous\n\nFeel free to explore other useful C++ libraries in the browser, like nlohmann_json, pugixml, xtl etc",
"metadata": {}
},
{
"id": "e1fdb4b5-384a-42a1-80c1-ba2bcd515e01",
"cell_type": "code",
"source": "#include \"nlohmann/json.hpp\"\n\nnlohmann::json jsonObject;\n\njsonObject[\"name\"] = \"John Doe\";\njsonObject[\"age\"] = 30;\njsonObject[\"is_student\"] = false;\njsonObject[\"skills\"] = {\"C++\", \"Python\", \"JavaScript\"};\n\nstd::cout << jsonObject.dump(4) << std::endl;",
"metadata": {
"trusted": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "{\n \"age\": 30,\n \"is_student\": false,\n \"name\": \"John Doe\",\n \"skills\": [\n \"C++\",\n \"Python\",\n \"JavaScript\"\n ]\n}\n"
}
],
"execution_count": 17
},
{
"id": "ed69c0cd-c65a-47d7-9ee2-13502953e876",
"cell_type": "code",
"source": "",
"metadata": {
"trusted": true
},
"outputs": [],
"execution_count": null
}
]
}
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