io19-demo-2-interoperability.ipynb

io19-demo-2-interoperability.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "io19-demo-2-interoperability.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "swift",
      "display_name": "Swift"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/rakesh4real/8057c3e4a6a556e7f16fae05e4bac66f/io19-demo-2-interoperability.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xSYmKIt59Zt3",
        "colab_type": "text"
      },
      "source": [
        "**Credits:** Google I/O 19 "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3WKd4UjLASm0",
        "colab_type": "text"
      },
      "source": [
        "#Interoperability\n",
        "\n",
        "## 1. Import from Python"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4dsTWOz7ADgB",
        "colab_type": "code",
        "outputId": "4fe6b1a1-c44b-426e-df80-c83ae03c25c6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "import Python\n",
        "Python.version"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3.6.8 (default, Oct  7 2019, 12:59:55) \n",
              "[GCC 8.3.0]\n"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AHxl-3uQAZ0l",
        "colab_type": "code",
        "outputId": "8031fd08-a78c-4225-b14b-5c4b000d2e73",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "let np = Python.import(\"numpy\")\n",
        "let plt = Python.import(\"matplotlib.pyplot\")\n",
        "\n",
        "// Also enable Jupyter's display capabilities\n",
        "%include \"EnableIPythonDisplay.swift\"\n",
        "IPythonDisplay.shell.enable_matplotlib(\"inline\")"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('inline', 'module://ipykernel.pylab.backend_inline')\n"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YCSlByHIAfLT",
        "colab_type": "code",
        "outputId": "d21902c3-2e4f-468d-ead6-8006cb98e3d8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "let x = np.linspace(0, 10, 100)\n",
        "\n",
        "plt.plot(x, np.sin(x))\n",
        "plt.plot(x, np.cos(x))\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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MgpSSzScrmZ8YTkSAj+MOHJUKEcmQv9Fxx3QhS9Ki8fE0sXkULpEdSoHF0Cs6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\nc87FnCcC55yLuf8BDOwAxhPWBvgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "None\n"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pmn3t-zkA2l0",
        "colab_type": "text"
      },
      "source": [
        "## 2. C Interoperability"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LmKS4AnJAjeh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import Glibc"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_PmkdeghA7cb",
        "colab_type": "code",
        "outputId": "ccd03e24-197d-4d0c-971f-8545afdbeef3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "let address = malloc(32)!\n",
        "let string = address.bindMemory(to: CChar.self, capacity: 32)\n",
        "\n",
        "strcpy(string, \"This looks more friendly than C itself!\")\n",
        "puts(string)\n",
        "\n",
        "free(address)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "This looks more friendly than C itself!\r\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}