Running python code in colab from github.ipynb

running-python-code-in-colab-from-github.ipynb

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  "metadata": {
    "colab": {
      "name": "Running python code in colab from github.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyP/ZJ60SpZXabDsxlSLOjjI",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/iampramodyadav/bfba31115a95bd674007ae60fecfc69d/running-python-code-in-colab-from-github.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7sHO91F320AI"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "# Running .py file in IPython notebook cell from Git Hub\n",
        "\n",
        "Pramod Kumar Yadav (@iampramodyadav)\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WEjm4diF3bc4"
      },
      "source": [
        "## Clone the containing folder"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ceqfjZlR1v-3",
        "outputId": "235b02d5-63bb-49bd-95eb-332e552b2e21"
      },
      "source": [
        " !git clone https://github.com/iampramodyadav/FEA"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'FEA'...\n",
            "remote: Enumerating objects: 49, done.\u001b[K\n",
            "remote: Counting objects: 100% (49/49), done.\u001b[K\n",
            "remote: Compressing objects: 100% (48/48), done.\u001b[K\n",
            "remote: Total 49 (delta 12), reused 0 (delta 0), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (49/49), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DBRBINpH_7_K",
        "outputId": "9c4750d8-762e-4506-b6e0-d9eeef0c5e49"
      },
      "source": [
        "!ls FEA #list all files in FEA"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Gauss_Legendre_Quadrature.ipynb  README.md\t       test2.py\n",
            "LICENSE\t\t\t\t Shape_Function.ipynb  test.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ziERueunBzbk"
      },
      "source": [
        "## RUN .py file"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jxA7O-l-B4_E"
      },
      "source": [
        "### Method-1 ([Magic Function](http://ipython.org/ipython-doc/dev/interactive/tutorial.html#magic-functions))"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bk5rrVhF18YX"
      },
      "source": [
        "%run FEA/test.py "
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XrZfrnNx2YRe",
        "outputId": "9bbf3475-3ea0-46be-a6fb-53be662decea"
      },
      "source": [
        "print(Legendre.__doc__)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "  n: Order of polynomial\n",
            "  x: Variable\n",
            "  This function print Legendre polynomial of order n\n",
            "  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "id": "eFUWXKgb2kN2",
        "outputId": "1f5835a4-034f-418e-bbbf-0baf0692521e"
      },
      "source": [
        "x=symbols('x')\n",
        "Legendre(3,x)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/latex": "$\\displaystyle 1.66666666666667 x \\left(1.5 x^{2} - 0.5\\right) - \\frac{2 x}{3}$",
            "text/plain": [
              "1.66666666666667*x*(1.5*x**2 - 0.5) - 2*x/3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TdCkwjePAlFS"
      },
      "source": [
        "%run FEA/test2.py"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jDrpL1thAtf6",
        "outputId": "ac5039eb-51f0-48f6-d948-2eed87ecb273"
      },
      "source": [
        "z=symbols('z')\n",
        "SHAPE(2,z)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[-1.0*z*(0.5 - 0.5*z), (1.0 - 1.0*z)*(1.0*z + 1.0), 1.0*z*(0.5*z + 0.5)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5cIgGqqeB9TK"
      },
      "source": [
        "### Method-2"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mNRNyoFH4hze"
      },
      "source": [
        "!python FEA/test.py"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 38
        },
        "id": "v--DUK9W5spG",
        "outputId": "66463dde-7f1d-4b4b-cb7f-d35d50d8715c"
      },
      "source": [
        "Legendre(2,x)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/latex": "$\\displaystyle 1.5 x^{2} - 0.5$",
            "text/plain": [
              "1.5*x**2 - 0.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eJrcR1ODA48N"
      },
      "source": [
        "!python FEA/test2.py"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "09Nkr67pA40a",
        "outputId": "a1d1661c-7444-4b70-abb4-baf984c003e7"
      },
      "source": [
        "z=symbols('z')\n",
        "SHAPE(2,z)"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[-1.0*z*(0.5 - 0.5*z), (1.0 - 1.0*z)*(1.0*z + 1.0), 1.0*z*(0.5*z + 0.5)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    }
  ]
}