{
  "cells": [
    {
      "metadata": {
        "id": "sGK4tJRBlE1A",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "## Setting Up\n\n* Install PyDrive Module\n* clone the colab_util gist and place `colab_util.py` to the working directory\n* clone some other git repo as example"
    },
    {
      "metadata": {
        "id": "jI85-B3WiMvo",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 2
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "outputId": "6030ecc3-8ded-4d64-b3c3-447a158850d3",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522896019248,
          "user_tz": 240,
          "elapsed": 3977,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "# !pip install -U -q PyDrive\n# !git clone https://github.com/Joshua1989/python_scientific_computing.git\n!git clone https://gist.github.com/dc7e60aa487430ea704a8cb3f2c5d6a6.git /tmp/colab_util_repo\n!mv /tmp/colab_util_repo/colab_util.py colab_util.py \n!rm -r /tmp/colab_util_repo",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Cloning into '/tmp/colab_util_repo'...\nremote: Counting objects: 15, done.\u001b[K\nremote: Compressing objects: 100% (10/10), done.\u001b[K\nremote: Total 15 (delta 4), reused 0 (delta 0), pack-reused 0\u001b[K\nUnpacking objects: 100% (15/15), done.\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "Rzr98u6xmJbL",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "## Import colab_util, create a Google Drive handler\nYou need copy the authorization code to the prompted edit widget"
    },
    {
      "metadata": {
        "id": "mH24bepIwxl9",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "from colab_util import *\ndrive_handler = GoogleDriveHandler()",
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "yg9-uZIBmgwK",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "## Compress the target files into *.tar.gz archive"
    },
    {
      "metadata": {
        "id": "ZJMfvT3gnzt_",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Make a list of files to archive.\nFor this example, I will compress all notebooks with odd lecture index"
    },
    {
      "metadata": {
        "id": "GDK9l-qcY_FJ",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 85
        },
        "outputId": "83839afe-c216-4848-e818-488c89650203",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522896034569,
          "user_tz": 240,
          "elapsed": 332,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "import glob\nipynb_files = sorted(glob.glob('python_scientific_computing/notebooks/*.ipynb'))\narchived_files = [f for f in ipynb_files if int(f.split('/')[-1][:2]) % 2]\nfor f in archived_files:\n    print(f)",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": "python_scientific_computing/notebooks/01_Customize_Your_Jupyter.ipynb\npython_scientific_computing/notebooks/03_Quick_Introduction_on_Python3.ipynb\npython_scientific_computing/notebooks/05_Object_Oriented_Programming.ipynb\npython_scientific_computing/notebooks/07_Random_Numbers.ipynb\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "F3YMpQDSn4Pi",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "You can see the paths of 4 Jupyter notebooks have long common prefix.\nIf you make archive directly, you will have a long nested folders 'python_scientific_computing/notebooks/...'.\n\nI simple drop the longest common prefix, i.e. for this case, these 4 notebooks will appear at the root of the archive.\n\n`create_archive` will return the file path of the archive file.\nBy default, the archive file is placed at `/tmp`, you can change the temp directory by setting `temp_folder` argument.\n\nFor detailed shell command output, you can switch on the `verbose` argument manually, otherwith the process will be silence."
    },
    {
      "metadata": {
        "id": "7oWs3fYul4l7",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            },
            {
              "item_id": 2
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 190
        },
        "outputId": "618c619b-3b57-407a-df6a-8b2febd9395e",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522896039570,
          "user_tz": 240,
          "elapsed": 573,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "tar_file_path = create_archive('sample_archive', local_file_paths=archived_files, verbose=True)\ntar_file_path",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": "ignore the common prefix python_scientific_computing/notebooks/\nrunning shell command: \ntar -czvf /tmp/sample_archive.tar.gz -C python_scientific_computing/notebooks/ 01_Customize_Your_Jupyter.ipynb 03_Quick_Introduction_on_Python3.ipynb 05_Object_Oriented_Programming.ipynb 07_Random_Numbers.ipynb\n01_Customize_Your_Jupyter.ipynb\n03_Quick_Introduction_on_Python3.ipynb\n05_Object_Oriented_Programming.ipynb\n07_Random_Numbers.ipynb\n\n",
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "'/tmp/sample_archive.tar.gz'"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "metadata": {
        "id": "krZVgZd8pEAC",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "## Managing your Google Drive\n\nIn Google Drive, every file and folder are viewed as \"file\", if file A is in folder B, Google Drive will use the `parent` domain in the API to indicate the inclusion.\nAlso, every file and folder can be uniquely retrieved by its id.\nHowever, using id is inconvinient, my wrapper allows you to use same directory syntax to access files."
    },
    {
      "metadata": {
        "id": "I8lFlBgHp7zZ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Create folder `test_folder` in your Google Drive root directory, the return value is the associated id of the created folder"
    },
    {
      "metadata": {
        "id": "PLU-L3IBo-zk",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "5837d4fd-d582-455b-d57e-cfa658625414",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522896955968,
          "user_tz": 240,
          "elapsed": 1179,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "test_folder_id = drive_handler.create_folder('test_folder')\ntest_folder_id",
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "'1mUzJJ4upwVFyjN_EIeDHm_Lga1CPBnzX'"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "metadata": {
        "id": "ZUNanfYjthco",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Create sub-folder `test_sub_folder` under `test_folder`, the return value is the associated id of the created sub-folder"
    },
    {
      "metadata": {
        "id": "JESInwkLsbB6",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "3a65907f-0d82-494c-abcd-0b08d53697e7",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522896959002,
          "user_tz": 240,
          "elapsed": 2079,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "test_subfolder_id = drive_handler.create_folder('test_sub_folder', parent_path='test_folder')\ntest_subfolder_id",
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "'1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3'"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "metadata": {
        "id": "FJS-NHzXt2j0",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "If the folder already exists, the function will tell you its existence and return the id"
    },
    {
      "metadata": {
        "id": "gBw01V6csklC",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            },
            {
              "item_id": 2
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "3861f5fc-ddba-49f7-e9a1-ce0f0c33ee9a",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522896960514,
          "user_tz": 240,
          "elapsed": 918,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "same_subfolder_id = drive_handler.create_folder('test_sub_folder', parent_path='test_folder')\ntest_subfolder_id",
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": "test_sub_folder already exists\n",
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "'1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3'"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "metadata": {
        "id": "c4ml-BVWuju7",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Let's create more sub folders"
    },
    {
      "metadata": {
        "id": "9tFLfBuNuR8W",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "same_subfolder_id2 = drive_handler.create_folder('test_sub_folder2', parent_path='test_folder')\ntest_subsubfolder_id = drive_handler.create_folder('test_sub_sub_folder', parent_path='test_folder/test_sub_folder2')",
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "BzeFSaJ_u6Pc",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Get id from given directory"
    },
    {
      "metadata": {
        "id": "FJVOO6Goumc7",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "a436cbd5-4081-4c6f-838d-449316297d7e",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522897053646,
          "user_tz": 240,
          "elapsed": 1125,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "ID = drive_handler.path_to_id('test_folder/test_sub_folder2/test_sub_sub_folder')\nID, test_subsubfolder_id",
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "('1Z6-g09N27bmsQ06RpbkoAWzm1-D4Gkkd', '1Z6-g09N27bmsQ06RpbkoAWzm1-D4Gkkd')"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "metadata": {
        "id": "o7J680ZcvRE8",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "List all files under a folder given its id, by default this is not recursive, but you can set the depth by changing `max_depth` (default 0)"
    },
    {
      "metadata": {
        "id": "7EfVNEAIvOM2",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "outputId": "4859b296-bc3c-40f9-b1d4-1d0e8de9c295",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522897168272,
          "user_tz": 240,
          "elapsed": 445,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "drive_handler.list_folder(test_folder_id)",
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "[{'id': '1DZuDCFMt3aqrU5r29GJ8p77z5f2YqxRk',\n  'link': 'https://drive.google.com/drive/folders/1DZuDCFMt3aqrU5r29GJ8p77z5f2YqxRk',\n  'mimeType': 'application/vnd.google-apps.folder',\n  'title': 'test_sub_folder2'},\n {'id': '1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3',\n  'link': 'https://drive.google.com/drive/folders/1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3',\n  'mimeType': 'application/vnd.google-apps.folder',\n  'title': 'test_sub_folder'}]"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "metadata": {
        "id": "EOFjbqhLv4HA",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Setting `max_depth` to 1, you can see `test_sub_folder2` has an extra field `children`, which contains `test_sub_sub_folder`"
    },
    {
      "metadata": {
        "id": "5Bdq9iUAvqWj",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "e2f6ac2c-a5f3-4e2e-8637-234c97342ca9",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522897212563,
          "user_tz": 240,
          "elapsed": 1083,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "drive_handler.list_folder(test_folder_id, max_depth=1)",
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "[{'children': [{'id': '1Z6-g09N27bmsQ06RpbkoAWzm1-D4Gkkd',\n    'link': 'https://drive.google.com/drive/folders/1Z6-g09N27bmsQ06RpbkoAWzm1-D4Gkkd',\n    'mimeType': 'application/vnd.google-apps.folder',\n    'title': 'test_sub_sub_folder'}],\n  'id': '1DZuDCFMt3aqrU5r29GJ8p77z5f2YqxRk',\n  'link': 'https://drive.google.com/drive/folders/1DZuDCFMt3aqrU5r29GJ8p77z5f2YqxRk',\n  'mimeType': 'application/vnd.google-apps.folder',\n  'title': 'test_sub_folder2'},\n {'children': [],\n  'id': '1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3',\n  'link': 'https://drive.google.com/drive/folders/1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3',\n  'mimeType': 'application/vnd.google-apps.folder',\n  'title': 'test_sub_folder'}]"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "metadata": {
        "id": "MA3QNvZAwFfe",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "## Upload files from Colab non-persistent VM to Google Drive"
    },
    {
      "metadata": {
        "id": "9gSjqXhOwatk",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Let's try to upload the archive obtained above to path `test_folder/test_sub_folder2`, by listing the files you can find it is in the correct path"
    },
    {
      "metadata": {
        "id": "7zXXpeiuvtxL",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "0ad1bc5d-fa96-4bc8-8e3d-f3cca07dbf63",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522897359329,
          "user_tz": 240,
          "elapsed": 2373,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "drive_handler.upload(tar_file_path, parent_path='test_folder/test_sub_folder2')\ndrive_handler.list_folder(test_folder_id, max_depth=1)",
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "[{'children': [{'id': '1BRZpCMQHhTDP2qOExHPFwYKNQCpB2sQ8',\n    'link': 'https://drive.google.com/file/d/1BRZpCMQHhTDP2qOExHPFwYKNQCpB2sQ8/view?usp=drivesdk',\n    'mimeType': 'application/x-tar',\n    'title': 'sample_archive.tar.gz'},\n   {'id': '1Z6-g09N27bmsQ06RpbkoAWzm1-D4Gkkd',\n    'link': 'https://drive.google.com/drive/folders/1Z6-g09N27bmsQ06RpbkoAWzm1-D4Gkkd',\n    'mimeType': 'application/vnd.google-apps.folder',\n    'title': 'test_sub_sub_folder'}],\n  'id': '1DZuDCFMt3aqrU5r29GJ8p77z5f2YqxRk',\n  'link': 'https://drive.google.com/drive/folders/1DZuDCFMt3aqrU5r29GJ8p77z5f2YqxRk',\n  'mimeType': 'application/vnd.google-apps.folder',\n  'title': 'test_sub_folder2'},\n {'children': [],\n  'id': '1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3',\n  'link': 'https://drive.google.com/drive/folders/1R66NAmnA6OJMIqMMfXU7_hU2VrXNwaQ3',\n  'mimeType': 'application/vnd.google-apps.folder',\n  'title': 'test_sub_folder'}]"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "metadata": {
        "id": "KQxwqvf2wqj9",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "## Download files from Google Drive to Colab non-persistent VM"
    },
    {
      "metadata": {
        "id": "lNYVi1myxAn6",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Now let's download the archive file in Colab VM with path `downloaded_archive.tar.gz`, which means downloaded to the current working directory with this name"
    },
    {
      "metadata": {
        "id": "gh9nzIrGwYho",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "drive_handler.download('downloaded_archive.tar.gz', target_path='test_folder/test_sub_folder2/sample_archive.tar.gz')",
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "mW8thm_oyUb_",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Now you can see the file `downloaded_archive.tar.gz` in the current working directory.\n\nWe can make a new directory to store the extracted archive."
    },
    {
      "metadata": {
        "id": "qQRZQf_Bx2r9",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "7b3ac387-fd45-4d76-d4ca-f09eca4582ad",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522897958029,
          "user_tz": 240,
          "elapsed": 1364,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "ls",
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "text": "colab_util.py  downloaded_archive.tar.gz  \u001b[0m\u001b[01;34mpython_scientific_computing\u001b[0m/\r\n\u001b[01;34mdatalab\u001b[0m/       \u001b[01;34m__pycache__\u001b[0m/\r\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "k3j3gTZ8ysFw",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "!mkdir downloeded_files",
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "T2QYs_LFyxPM",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "245a99ed-7495-4839-f473-4a64c8d4731a",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522897985477,
          "user_tz": 240,
          "elapsed": 1444,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "ls",
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "text": "colab_util.py  downloaded_archive.tar.gz  \u001b[0m\u001b[01;34m__pycache__\u001b[0m/\r\n\u001b[01;34mdatalab\u001b[0m/       \u001b[01;34mdownloeded_files\u001b[0m/          \u001b[01;34mpython_scientific_computing\u001b[0m/\r\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "Ixyb2-UeyzKA",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": "Finally we need to extract the archive to the folder `downloeded_files`"
    },
    {
      "metadata": {
        "id": "NssYJIcbyxnv",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "extract_archive('downloaded_archive.tar.gz', target_folder='downloeded_files')",
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "v5Euhw9ZzEJd",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "output_extras": [
            {
              "item_id": 1
            }
          ],
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "36217e7e-f2f6-47ff-b94f-684618db2072",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1522898066813,
          "user_tz": 240,
          "elapsed": 1589,
          "user": {
            "displayName": "Joshua Lian",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "112640645742688411146"
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "ls downloeded_files/",
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "text": "01_Customize_Your_Jupyter.ipynb         05_Object_Oriented_Programming.ipynb\r\n03_Quick_Introduction_on_Python3.ipynb  07_Random_Numbers.ipynb\r\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "THUVqFPJzFcV",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "trusted": false
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 0,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "name": "Example Notebook of colab_util.ipynb",
      "version": "0.3.2",
      "views": {},
      "default_view": {},
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "varInspector": {
      "window_display": false,
      "cols": {
        "lenName": 16,
        "lenType": 16,
        "lenVar": 40
      },
      "kernels_config": {
        "python": {
          "library": "var_list.py",
          "delete_cmd_prefix": "del ",
          "delete_cmd_postfix": "",
          "varRefreshCmd": "print(var_dic_list())"
        },
        "r": {
          "library": "var_list.r",
          "delete_cmd_prefix": "rm(",
          "delete_cmd_postfix": ") ",
          "varRefreshCmd": "cat(var_dic_list()) "
        }
      },
      "types_to_exclude": [
        "module",
        "function",
        "builtin_function_or_method",
        "instance",
        "_Feature"
      ]
    },
    "gist": {
      "id": "",
      "data": {
        "description": "Colab Notebooks/Example Notebook of colab_util.ipynb",
        "public": true
      }
    },
    "language_info": {
      "name": "python",
      "version": "3.6.4",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 1
}