How to download csv data from Sanbase.ipynb

how-to-download-csv-data-from-sanbase.ipynb

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  "metadata": {
    "colab": {
      "name": "How to download csv data from Sanbase.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOtusSn+LPJWG2ahG+DKGoj",
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      "name": "python3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/Partysun/7f9fe6a0c357a41d22676867810bdd35/how-to-download-csv-data-from-sanbase.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E5x3QnjiMxGb"
      },
      "source": [
        "## Install sanpy library"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_BgyvAh-OjJQ"
      },
      "source": [
        "1. Install sanpy library\n",
        "  \n",
        "  For more details -> visit [sanpy github](https://github.com/santiment/sanpy)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JNjk4lGYKZue",
        "outputId": "ebedd501-3d9c-4ced-bff7-f238429bc6ea",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!pip install sanpy"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting sanpy\n",
            "  Downloading https://files.pythonhosted.org/packages/57/10/3c7974cdfe76f827afb57fbb05b15058287c29d0ae1c0911faa16dfbac36/sanpy-0.8.5-py3-none-any.whl\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (from sanpy) (1.1.3)\n",
            "Collecting iso8601\n",
            "  Downloading https://files.pythonhosted.org/packages/f5/c7/06b5938e79a09112a256f26a1ae0551b04bc6aafcb71fd7ee2390c2c54c6/iso8601-0.1.13-py2.py3-none-any.whl\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from sanpy) (2.23.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from sanpy) (50.3.2)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas->sanpy) (2018.9)\n",
            "Requirement already satisfied: numpy>=1.15.4 in /usr/local/lib/python3.6/dist-packages (from pandas->sanpy) (1.18.5)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.6/dist-packages (from pandas->sanpy) (2.8.1)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->sanpy) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->sanpy) (2020.6.20)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->sanpy) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->sanpy) (2.10)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.7.3->pandas->sanpy) (1.15.0)\n",
            "Installing collected packages: iso8601, sanpy\n",
            "Successfully installed iso8601-0.1.13 sanpy-0.8.5\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6u0QXuBMO5d3"
      },
      "source": [
        "2. Pick desirable timeframe\n",
        "  \n",
        "  In this example we take last 7 days"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kTjqKhzbNXMw",
        "outputId": "138f8a32-15b7-4b34-ba19-81188d3c913c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 37
        }
      },
      "source": [
        "from datetime import datetime, timedelta\n",
        "utc_now = datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%SZ')\n",
        "from_date = (datetime.utcnow() - timedelta(days=7)).strftime('%Y-%m-%dT%H:%M:%SZ')"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2020-10-26T13:50:06Z'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CBZrIbwVPGXU"
      },
      "source": [
        "3. Fetch data\n",
        "  \n",
        "  In this example we fetch daily_active_address metric.\n",
        "  For more metrics you can check [this](https://api.santiment.net/graphiql?query=%7BgetAvailableMetrics%7D) or [Santiment Academy](https://academy.santiment.net/metrics/)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r3BZewx3K8Rb"
      },
      "source": [
        "import san\n",
        "\n",
        "df = san.get(\n",
        "    \"daily_active_addresses/santiment\",\n",
        "    from_date=from_date,\n",
        "    to_date=utc_now,\n",
        "    interval=\"1d\"\n",
        ")"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q5epQDbnMMlu",
        "outputId": "f9d9a9a0-8a6a-496d-e7c9-21964bb0fc8c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "from IPython.display import HTML\n",
        "import base64\n",
        "\n",
        "def create_download_link(df, title = \"Download CSV file\", filename = \"data.csv\"):  \n",
        "    csv = df.to_csv()\n",
        "    b64 = base64.b64encode(csv.encode())\n",
        "    payload = b64.decode()\n",
        "    html = '<a download=\"{filename}\" href=\"data:text/csv;base64,{payload}\" target=\"_blank\">{title}</a>'\n",
        "    html = html.format(payload=payload,title=title,filename=filename)\n",
        "    return HTML(html)\n",
        "\n",
        "## Let's create a link for CSV file\n",
        "create_download_link(df)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<a download=\"data.csv\" href=\"data:text/csv;base64,ZGF0ZXRpbWUsdmFsdWUKMjAyMC0xMC0yNyAwMDowMDowMCswMDowMCw5LjAKMjAyMC0xMC0yOCAwMDowMDowMCswMDowMCwxNS4wCjIwMjAtMTAtMjkgMDA6MDA6MDArMDA6MDAsMTYuMAoyMDIwLTEwLTMwIDAwOjAwOjAwKzAwOjAwLDE0LjAKMjAyMC0xMC0zMSAwMDowMDowMCswMDowMCwyLjAKMjAyMC0xMS0wMSAwMDowMDowMCswMDowMCwyLjAKMjAyMC0xMS0wMiAwMDowMDowMCswMDowMCw1LjAK\" target=\"_blank\">Download CSV file</a>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EEGcKIe9Obe5"
      },
      "source": [
        ""
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}