TechDay_UPE_Acesso_Azure.ipynb

techday_upe_acesso_azure.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "TechDay_UPE_Acesso_Azure.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "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/leocosta037/d31bbc5c1d875e2563bf3878e7cd6290/techday_upe_acesso_azure.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HxQXiY7uQTQE"
      },
      "source": [
        "# Notebook para acesso ao Storage de Blobs do Azure"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mo4kEG_yQ1X-"
      },
      "source": [
        "Material para consulta"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UH6IvEyRQ15V"
      },
      "source": [
        "https://docs.microsoft.com/pt-br/azure/storage/blobs/storage-quickstart-blobs-python\n",
        "\n",
        "https://docs.microsoft.com/pt-br/azure/storage/blobs/storage-blobs-introduction\n",
        "\n",
        "https://pypi.org/project/azure-storage-blob/\n",
        "\n",
        "https://docs.microsoft.com/pt-br/python/api/azure-storage-blob/azure.storage.blob.blobserviceclient?view=azure-python\n",
        "\n",
        "https://docs.microsoft.com/pt-br/python/api/azure-storage-blob/azure.storage.blob.blobclient?view=azure-python#upload-blob-data--blob-type--blobtype-blockblob---blockblob----length-none--metadata-none----kwargs-\n",
        "\n",
        "https://github.com/Azure/azure-storage-python/tree/master/azure-storage-blob\n",
        "\n",
        "https://medium.com/microsoftazure/guidance-for-using-azure-storage-explorer-with-azure-ad-authorization-for-azure-storage-data-access-663c2c88efb"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jXwXFX9R_wvc"
      },
      "source": [
        "# Inicialização"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AaVu6PG-FhAt"
      },
      "source": [
        "pip install azure-storage-blob"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VoWRY0YbDdb2"
      },
      "source": [
        "import os, uuid\n",
        "from azure.storage.blob import BlobServiceClient, BlobClient, ContainerClient, __version__\n",
        "\n",
        "try:\n",
        "    print(\"Azure Blob Storage v\" + __version__ + \" - Python quickstart sample\")\n",
        "\n",
        "    # Quick start code goes here\n",
        "\n",
        "except Exception as ex:\n",
        "    print('Exception:')\n",
        "    print(ex)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lKDkhmdOU1d3"
      },
      "source": [
        "# Importação do Google Drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9i2FR-qNm3Uy"
      },
      "source": [
        "# Carregamento"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mlKjHP5zJoNw"
      },
      "source": [
        "AZURE_STORAGE_CONNECTION_STRING='' # Inserir string de conexão do Azure Storage"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8YsyjqQYJKe9"
      },
      "source": [
        "# Create the BlobServiceClient object which will be used to create a container client\n",
        "blob_service_client = BlobServiceClient.from_connection_string(AZURE_STORAGE_CONNECTION_STRING)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KeLIVoJPmx5f"
      },
      "source": [
        "# Funções"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TEPDi2YBNmuC"
      },
      "source": [
        "# Create a unique name for the container\n",
        "container_name = str('') # Inserir o nome do contâiner a ser criado\n",
        "\n",
        "# Create the container\n",
        "container_client = blob_service_client.create_container(container_name)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fn7IQU08Lx6-"
      },
      "source": [
        "# Create a local directory to hold blob data\n",
        "local_path = \"\" # Inserir o caminho da pasta onde se localiza o arquivo no PC\n",
        "#os.mkdir(local_path)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uCt5UC8uOKj3"
      },
      "source": [
        "# Create a file in the local data directory to upload and download\n",
        "#local_file_name = local_path + '/' + file\n",
        "local_file_name = '' # Inserir o nome do arquivo no PC\n",
        "upload_file_path = os.path.join(local_path, local_file_name)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FXM74BuIOWs4"
      },
      "source": [
        "'''\n",
        "# Write text to the file\n",
        "file = open(upload_file_path, 'w')\n",
        "file.write(\"Qualquer coisa 123\")\n",
        "file.close()'''"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RMURiacVQEjI"
      },
      "source": [
        "# Create a blob client using the local file name as the name for the blob\n",
        "blob_client = blob_service_client.get_blob_client(container=container_name, blob=local_file_name)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7BW9siuIQNoV"
      },
      "source": [
        "print(\"\\nUploading to Azure Storage as blob:\\n\\t\" + local_file_name)\n",
        "\n",
        "# Upload the created file\n",
        "with open(upload_file_path, \"rb\") as data:\n",
        "    blob_client.upload_blob(data)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QF_dXSINLe_k"
      },
      "source": [
        "print(\"\\nListing blobs...\")\n",
        "\n",
        "# List the blobs in the container\n",
        "blob_list = container_client.list_blobs()\n",
        "for blob in blob_list:\n",
        "    print(\"\\t\" + blob.name)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qGIBoKLdYmcJ"
      },
      "source": [
        "# Download the blob to a local file\n",
        "# Add 'DOWNLOAD' before the .txt extension so you can see both files in the data directory\n",
        "download_file_path = local_file_name\n",
        "print(\"\\nDownloading blob to \\n\\t\" + download_file_path)\n",
        "\n",
        "with open(download_file_path, \"wb\") as download_file:\n",
        "    download_file.write(blob_client.download_blob().readall())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eRnt3o4JRJ__"
      },
      "source": [
        "Excluir um container"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r4E8yeofRQVo"
      },
      "source": [
        "# Clean up\n",
        "print(\"\\nPress the Enter key to begin clean up\")\n",
        "input()\n",
        "\n",
        "print(\"Deleting blob container...\")\n",
        "container_client.delete_container()\n",
        "\n",
        "print(\"Deleting the local source and downloaded files...\")\n",
        "os.remove(upload_file_path)\n",
        "os.remove(download_file_path)\n",
        "os.rmdir(local_path)\n",
        "\n",
        "print(\"Done\")"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}