File upload From pc in colab.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled12.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOm3KE5hAmy9zeMTfjbxpiA",
      "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/github/Minhaz78/Machine-Learning-Practice/blob/main/File%20upload%20From%20pc%20in%20colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# :**File upload From pc in colab** 🥰::::\\:::::::"
      ],
      "metadata": {
        "id": "DodwXaVjNiq4"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 113
        },
        "id": "yxyPObZRJrnc",
        "outputId": "a415a395-a946-49b6-820f-80a0bae4da11"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-e5fa5039-2b0e-4d25-a323-102df6044218\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-e5fa5039-2b0e-4d25-a323-102df6044218\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving piramid.c to piramid.c\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'piramid.c': b'#include<stdio.h>\\r\\n#include<conio.h>\\r\\nint main()\\r\\n{\\r\\n    /*this code is making a piramid.*/\\r\\n    int n,p,i,j,x; //declare the value\\r\\n    scanf(\"%d\",&n);\\r\\n    for(p=1;p<=n;p++)\\r\\n    {\\r\\n        x=n-p;\\r\\n        for(i=1;i<=x;i++) //this is for loop.\\r\\n        {\\r\\n            printf(\" \"); //print the output\\r\\n        }\\r\\n        for(j=1;j<=p;j++)\\r\\n        {\\r\\n            printf(\"#\");\\r\\n        }\\r\\n        printf(\"\\\\n\"); //this is new line\\r\\n    }\\r\\n\\r\\n}\\r\\n'}"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ],
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ]
    }
  ]
}