{
  "cells": [
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Intro to Flipside API/SDK: Getting Started\n",
        "\n",
        "<em>install Flipside with pip</em><br/>\n",
        "`pip install flipside`"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Import the package"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from flipside import Flipside"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Run your first query<br/>\n",
        "<em>Remember to copy/paste your API Key from https://flipsidecrypto.xyz/api-keys below.</em>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "import os\n",
        "YOUR_API_KEY = os.environ.get(\"FLIPSIDE_API_KEY\")\n",
        "\n",
        "# Invoke the ShroomDK class to create an instance of the SDK\n",
        "sdk = Flipside(YOUR_API_KEY)\n",
        "\n",
        "# Run a query\n",
        "xMETRIC_contract_address = '0x15848C9672e99be386807b9101f83A16EB017bb5'\n",
        "\n",
        "query_result_set = sdk.query(f\"\"\"\n",
        "    SELECT count(distinct to_address) as recipient_count\n",
        "    FROM polygon.core.fact_token_transfers\n",
        "    WHERE block_timestamp > '2022-07-10T00:00:00'\n",
        "        AND contract_address = lower('{xMETRIC_contract_address}')\n",
        "        AND to_address != lower('0x4b8923746a1D9943bbd408F477572762801efE4d')\n",
        "\"\"\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Query Result Set\n",
        "\n",
        "```python\n",
        "class QueryResultSet(BaseModel):\n",
        "    query_id: Union[str, None] = Field(None, description=\"The server id of the query\")\n",
        "    status: str = Field(False, description=\"The status of the query (`PENDING`, `FINISHED`, `ERROR`)\")\n",
        "    columns: Union[List[str], None] = Field(None, description=\"The names of the columns in the result set\")\n",
        "    column_types: Union[List[str], None] = Field(None, description=\"The type of the columns in the result set\")\n",
        "    rows: Union[List[Any], None] = Field(None, description=\"The results of the query\")\n",
        "    run_stats: Union[QueryRunStats, None] = Field(\n",
        "        None,\n",
        "        description=\"Summary stats on the query run (i.e. the number of rows returned, the elapsed time, etc)\",\n",
        "    )\n",
        "    records: Union[List[Any], None] = Field(None, description=\"The results of the query transformed as an array of objects\")\n",
        "    error: Any\n",
        "\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "## Explore the result set object\n",
        "\n",
        "records = query_result_set.records\n",
        "\n",
        "print(records[0])\n",
        "\n",
        "print(f\"There are {records[0]['recipient_count']} unique recipients of xMETRIC tokens.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### xMETRIC Leaderboard\n",
        "Retrieve the balance of every xMETRIC holder"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "vscode": {
          "languageId": "sql"
        }
      },
      "outputs": [],
      "source": [
        "WITH sent_tokens AS (\n",
        "  SELECT \n",
        "    to_address as Participant,\n",
        "    sum(raw_amount/pow(10,18)) as xMETRIC\n",
        "  FROM polygon.core.fact_token_transfers\n",
        "  WHERE\n",
        "    block_timestamp::date > '2022-07-10'::date \n",
        "    AND contract_address = lower('0x15848C9672e99be386807b9101f83A16EB017bb5')\n",
        "    AND to_address != lower('0x4b8923746a1D9943bbd408F477572762801efE4d')\n",
        "  GROUP BY 1\n",
        "),\n",
        "burnt_tokens AS (\n",
        "  SELECT\n",
        "    to_address as Participant,\n",
        "    sum(raw_amount/pow(10,18)) as xMETRIC\n",
        "  FROM polygon.core.fact_token_transfers\n",
        "  WHERE\n",
        "    block_timestamp::date > '2022-07-10'::date \n",
        "    AND contract_address = lower('0x15848C9672e99be386807b9101f83A16EB017bb5')\n",
        "    AND to_address = lower('0x0000000000000000000000000000000000000000')\n",
        "  GROUP BY 1\n",
        ")\n",
        "SELECT\n",
        "  sent_tokens.Participant as \"participant_addr\",\n",
        "  coalesce(sent_tokens.xmetric,0) - coalesce(burnt_tokens.xMETRIC,0) as \"balance\"\n",
        "FROM sent_tokens \n",
        "LEFT JOIN burnt_tokens ON sent_tokens.Participant = burnt_tokens.Participant\n",
        "ORDER BY 2 DESC"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Load the sql query from a file\n",
        "leaderboard_sql_query = open(\"./sql/xmetric_leaderboard.sql\", 'r').read()\n",
        "\n",
        "# Run the query with pagination\n",
        "\n",
        "page_number = 1\n",
        "page_size = 10\n",
        "\n",
        "leaderboard_result_set = sdk.query(\n",
        "    leaderboard_sql_query, \n",
        "    page_size=page_size,\n",
        "    page_number=page_number)\n",
        "\n",
        "for record in leaderboard_result_set.records:\n",
        "    print(record)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Plot the xMETRIC LeaderBoard Results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "full_leaderboard_result_set = sdk.query(leaderboard_sql_query)\n",
        "\n",
        "import pandas as pd\n",
        "import plotly.express as px\n",
        "\n",
        "df = pd.DataFrame(full_leaderboard_result_set.records)\n",
        "\n",
        "fig = px.histogram(df, x=\"balance\", marginal=\"box\", hover_data=df.columns, nbins=200)\n",
        "\n",
        "fig.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Cross Chain xMETRIC User Exploration"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "vscode": {
          "languageId": "sql"
        }
      },
      "outputs": [],
      "source": [
        "WITH xmetric_holders AS (\n",
        "    SELECT to_address as holder_addr\n",
        "    FROM polygon.core.fact_token_transfers\n",
        "    WHERE block_timestamp > '2022-07-10T00:00:00'\n",
        "        AND contract_address = lower('0x15848C9672e99be386807b9101f83A16EB017bb5')\n",
        "        AND to_address != lower('0x4b8923746a1D9943bbd408F477572762801efE4d')\n",
        ")\n",
        "SELECT\n",
        "    token_name,\n",
        "    symbol,\n",
        "    count(distinct user_address) as num_holders,\n",
        "    median(usd_value_now) as median_usd_holdings\n",
        "FROM ethereum.core.ez_current_balances\n",
        "INNER JOIN xmetric_holders \n",
        "    ON ethereum.core.ez_current_balances.user_address = xmetric_holders.holder_addr\n",
        "WHERE ethereum.core.ez_current_balances.usd_value_now > 0\n",
        "GROUP BY 1, 2\n",
        "ORDER BY 3 DESC\n",
        "LIMIT 25"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Load the sql query from a file\n",
        "xmetric_eth_holdings_sql_query = open(\"./sql/xmetric_eth_holdings.sql\", 'r').read()\n",
        "\n",
        "# Run the query\n",
        "xmetric_eth_holdings_results = sdk.query(xmetric_eth_holdings_sql_query)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Plot the results\n",
        "df = pd.DataFrame(xmetric_eth_holdings_results.records)\n",
        "\n",
        "fig = px.bar(df, x=\"token_name\", y=\"num_holders\", hover_data=df.columns)\n",
        "\n",
        "fig.show()"
      ]
    }
  ],
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