stats.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1001\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"1001\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };var element = document.getElementById(\"1001\");\n",
       "  if (element == null) {\n",
       "    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n",
       "  var css_urls = [];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1001\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };var element = document.getElementById(\"1001\");\n  if (element == null) {\n    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n    return false;\n  }\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n  var css_urls = [];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from bokeh.plotting import figure, output_notebook, show\n",
    "from bokeh.models import ColumnDataSource, HoverTool\n",
    "from datetime import datetime\n",
    "from bokeh.palettes import Spectral3\n",
    "from tabulate import tabulate\n",
    "from bokeh.transform import factor_cmap\n",
    "import js2py\n",
    "import math\n",
    "from concurrent.futures import ProcessPoolExecutor as PoolExecutor\n",
    "import requests\n",
    "import os\n",
    "\n",
    "# convenience\n",
    "output_notebook()\n",
    "pd.set_option('display.max_colwidth', -1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Globals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "API = os.getenv('API')\n",
    "NUM_CHALLENGES = 100\n",
    "NUM_BLOCKS = 100\n",
    "TOP = 10\n",
    "animalhash = js2py.require('angry-purple-tiger')\n",
    "MAX_WORKERS = 8\n",
    "REWARD_LIMIT = 500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Helpers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "code_folding": [
     0,
     10,
     21,
     32,
     42,
     52,
     87,
     97
    ]
   },
   "outputs": [],
   "source": [
    "def latest_height(api):\n",
    "    '''\n",
    "    Get latest block height\n",
    "    '''\n",
    "    r = requests.get(f'{api}/blocks?limit=1')\n",
    "    if r.status_code == 200:\n",
    "        data = r.json().get('data')\n",
    "        return data[0]['height']\n",
    "    raise Exception('Unable to get latest height')\n",
    "\n",
    "def get_blocks(api, num_blocks=100):\n",
    "    '''\n",
    "    Get past `NUM_BLOCKS` number of num_blocks\n",
    "    '''\n",
    "    r = requests.get(f'{api}/blocks?limit={num_blocks}')\n",
    "    if r.status_code == 200:\n",
    "        data = r.json().get('data')\n",
    "        assert len(data) == num_blocks\n",
    "        return data\n",
    "    raise Exception('Unable to get blocks')\n",
    "\n",
    "def get_challenges(api, num_challenges=100):\n",
    "    '''\n",
    "    Get past `LIMIT` number of challenges\n",
    "    '''\n",
    "    r = requests.get(f'{api}/challenges?limit={num_challenges}')\n",
    "    if r.status_code == 200:\n",
    "        data = r.json().get('data')\n",
    "        assert len(data) == num_challenges\n",
    "        return data\n",
    "    raise Exception('Unable to get challenges')\n",
    "\n",
    "def get_hotspots(api):\n",
    "    '''\n",
    "    Get hotspots from the api\n",
    "    '''\n",
    "    r = requests.get(f'{api}/hotspots')\n",
    "    if r.status_code == 200:\n",
    "        data = r.json().get('data')\n",
    "        return data\n",
    "    raise Exception('Unable to get hotspots')\n",
    "\n",
    "def get_accounts(api):\n",
    "    '''\n",
    "    Get accounts from the api\n",
    "    '''\n",
    "    r = requests.get(f'{api}/accounts')\n",
    "    if r.status_code == 200:\n",
    "        data = r.json().get('data')\n",
    "        return data\n",
    "    raise Exception('Unable to get accounts')\n",
    "\n",
    "def accumulate_results(challenges):\n",
    "    '''\n",
    "    Return a dict list of challenge_id, num_successes, num_failures and num_untested\n",
    "    '''\n",
    "    results = []\n",
    "    for challenge in challenges:\n",
    "        path = challenge['pathElements']\n",
    "\n",
    "        result = [element['result'] for element in path]\n",
    "        length = len(result)\n",
    "        num_untested = result.count('untested')\n",
    "\n",
    "        gray = True if num_untested == length else False\n",
    "\n",
    "        if gray:\n",
    "            num_successes = 0\n",
    "            num_failures = 0\n",
    "            num_untested = 0\n",
    "            dud = 1\n",
    "            success = 0\n",
    "        else:\n",
    "            num_successes = result.count('success')\n",
    "            num_failures = result.count('failure')\n",
    "            num_untested = num_untested\n",
    "            dud = 0\n",
    "            success = 1 if num_successes == length else 0\n",
    "        results.append({'id': challenge['id'],\n",
    "                        'num_successes': num_successes,\n",
    "                        'num_failures': num_failures,\n",
    "                        'num_untested': num_untested,\n",
    "                        'dud': dud,\n",
    "                        'path_length': len(path),\n",
    "                        'success': success})\n",
    "    return results\n",
    "\n",
    "def get_reward(reward_url):\n",
    "    '''\n",
    "    Get hotspot reward\n",
    "    '''\n",
    "    r = requests.get(reward_url)\n",
    "    if r.status_code == 200:\n",
    "        data = r.json().get('data')\n",
    "        return data\n",
    "    raise Exception(f'Unable to get rewards for {reward_url}')\n",
    "    \n",
    "def get_rewards(api, hotspots, limit=REWARD_LIMIT):\n",
    "    '''\n",
    "    Get rewards for all hotspots\n",
    "    '''\n",
    "    reward_urls = [f'{api}/hotspots/{hotspot}/rewards?limit={limit}' for hotspot in hotspots]\n",
    "    with PoolExecutor(max_workers=MAX_WORKERS) as executor:\n",
    "        rewards = []\n",
    "        for hotspot, i in zip(hotspots, executor.map(get_reward, reward_urls)):\n",
    "            rewards.extend(i)\n",
    "    return rewards"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Block Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average txns past 100 blocks: 4.93\n",
      "Average block time past 100 blocks: 1565836320.63\n",
      "Block with max txns for past 100 blocks: \n",
      "+--------+----------------------------------------------------+\n",
      "| hash   | 1y6RdJLfETKcWMUeWBHvBbGfLbfiZDjjDhg2wHyctrfNAAL6eB |\n",
      "| height | 16449                                              |\n",
      "| round  | 16449                                              |\n",
      "| time   | 1565839967                                         |\n",
      "| txns   | 25                                                 |\n",
      "+--------+----------------------------------------------------+\n"
     ]
    }
   ],
   "source": [
    "def block_stats():\n",
    "    blocks = get_blocks(API, NUM_BLOCKS)\n",
    "\n",
    "    df = pd.DataFrame(blocks)\n",
    "    max_txns = tabulate(df.max().reset_index(),tablefmt='psql', showindex='never')\n",
    "    print(f'Average txns past {NUM_BLOCKS} blocks: {df[\"txns\"].mean()}')\n",
    "    print(f'Average block time past {NUM_BLOCKS} blocks: {df[\"time\"].mean()}')\n",
    "    print(f\"Block with max txns for past {NUM_BLOCKS} blocks: \\n{max_txns}\")\n",
    "    return df\n",
    "bdf = block_stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"068f7c7c-c178-48e2-8f65-1923b01f98aa\" data-root-id=\"1003\"></div>\n"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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5839967,1565839907,1565839847,1565839787,1565839727,1565839665,1565839605,1565839545,1565839485,1565839425,1565839365,1565839305,1565839245,1565839185,1565839110,1565839001,1565838928,1565838868,1565838808,1565838748,1565838688,1565838628,1565838568,1565838508,1565838395,1565838335,1565838275,1565838215,1565838155,1565838095,1565838035,1565837930,1565837700,1565837640,1565837580,1565837520,1565837460,1565837400,1565837340,1565837222,1565837162,1565837102,1565837035,1565836975,1565836906,1565836846,1565836786,1565836669,1565836609,1565836536,1565836476,1565836416,1565836356,1565836296,1565836236,1565836176,1565836116,1565836056,1565835918,1565835858,1565835798,1565835738,1565835678,1565835523,1565835159,1565834998,1565834850,1565834732,1565834672,1565834612,1565834552,1565834492,1565834413,1565834353,1565834293,1565834225,1565834165,1565834105,1565834037,1565833948,1565833888,1565833740,1565833680,1565833510,1565833450,1565833390,1565833330,1565833270,1565833210,1565833120,1565833010,1565832950,1565832890,1565832830,1565832770,1565832684,1565832441,1565832068,1565831906,1565831841],\"txns\":[14,2,2,11,0,7,0,3,1,0,3,1,25,0,11,5,3,4,2,5,1,3,4,1,6,4,3,6,9,13,1,1,12,2,2,5,8,6,0,7,2,0,4,0,11,15,0,15,0,6,1,6,0,1,2,4,1,1,4,6,7,13,4,7,15,5,2,3,3,1,14,2,2,2,0,3,1,22,6,13,0,10,1,5,6,1,2,4,1,2,5,5,2,3,6,14,11,14,4,0]},\"selected\":{\"id\":\"1051\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1050\",\"type\":\"UnionRenderers\"}},\"id\":\"1002\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1028\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1048\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"top\":{\"field\":\"txns\"},\"width\":{\"value\":0.8},\"x\":{\"field\":\"height\"}},\"id\":\"1039\",\"type\":\"VBar\"},{\"attributes\":{\"overlay\":{\"id\":\"1049\",\"type\":\"BoxAnnotation\"}},\"id\":\"1026\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1020\",\"type\":\"BasicTicker\"},{\"attributes\":{\"data_source\":{\"id\":\"1002\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1038\",\"type\":\"VBar\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1039\",\"type\":\"VBar\"},\"selection_glyph\":null,\"view\":{\"id\":\"1041\",\"type\":\"CDSView\"}},\"id\":\"1040\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1024\",\"type\":\"PanTool\"},{\"attributes\":{\"dimension\":1,\"ticker\":{\"id\":\"1020\",\"type\":\"BasicTicker\"}},\"id\":\"1023\",\"type\":\"Grid\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"height\",\"@height\"],[\"txns\",\"@txns\"]]},\"id\":\"1042\",\"type\":\"HoverTool\"},{\"attributes\":{\"source\":{\"id\":\"1002\",\"type\":\"ColumnDataSource\"}},\"id\":\"1041\",\"type\":\"CDSView\"},{\"attributes\":{\"fill_color\":{\"value\":\"#1f77b4\"},\"line_color\":{\"value\":\"#1f77b4\"},\"top\":{\"field\":\"txns\"},\"width\":{\"value\":0.8},\"x\":{\"field\":\"height\"}},\"id\":\"1038\",\"type\":\"VBar\"},{\"attributes\":{},\"id\":\"1051\",\"type\":\"Selection\"}],\"root_ids\":[\"1003\"]},\"title\":\"Bokeh Application\",\"version\":\"1.3.4\"}};\n",
       "  var render_items = [{\"docid\":\"eedb003c-aa13-4ca2-af78-51a2c5b1b2ed\",\"roots\":{\"1003\":\"068f7c7c-c178-48e2-8f65-1923b01f98aa\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1003"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_block_stats(df):\n",
    "    source = ColumnDataSource(df)\n",
    "    p = figure(title='Txns/Block')\n",
    "\n",
    "    p.vbar(x='height', top='txns', width=0.8, source=source)\n",
    "    hover = HoverTool(tooltips=[('height', '@height'), ('txns', '@txns')])\n",
    "    p.add_tools(hover)\n",
    "    p.xaxis.axis_label = \"Txns/Block\"\n",
    "    p.yaxis.axis_label = \"NumTxns\"\n",
    "\n",
    "    show(p)\n",
    "plot_block_stats(bdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hotspot Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 scoring hotspots:\n",
      "+-----+-------------------------+---------+\n",
      "|     | name                    |   score |\n",
      "|-----+-------------------------+---------|\n",
      "| 116 | magic-carob-quail       |  0.9939 |\n",
      "| 133 | mean-alabaster-piranha  |  0.9466 |\n",
      "| 103 | delightful-stone-beetle |  0.9329 |\n",
      "| 132 | mythical-tin-hawk       |  0.919  |\n",
      "|  13 | beautiful-onyx-platypus |  0.9154 |\n",
      "| 130 | mini-currant-lizard     |  0.8971 |\n",
      "| 126 | joyous-burgundy-chicken |  0.8956 |\n",
      "|  60 | shambolic-rusty-cyborg  |  0.8937 |\n",
      "|  44 | bubbly-mandarin-panther |  0.8811 |\n",
      "|  43 | melodic-pearl-chameleon |  0.8217 |\n",
      "+-----+-------------------------+---------+\n"
     ]
    }
   ],
   "source": [
    "def hotspot_stats():\n",
    "    hotspots = get_hotspots(API)\n",
    "\n",
    "    hdf = pd.DataFrame(hotspots)\n",
    "    hdf['name'] = hdf.apply(lambda row: '-'.join(animalhash(row.address).lower().split()), axis=1)\n",
    "    print(f'Top {TOP} scoring hotspots:')\n",
    "    print(tabulate(hdf.sort_values('score', ascending=False)[['name', 'score']].head(TOP),\n",
    "                   headers='keys', tablefmt='psql'))\n",
    "    return hdf\n",
    "hdf = hotspot_stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"f931998e-1988-4cc5-bdea-804a4b203bea\" data-root-id=\"1101\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "  var render_items = [{\"docid\":\"cd108725-c08a-4c7f-a758-b6aed4708dbc\",\"roots\":{\"1101\":\"f931998e-1988-4cc5-bdea-804a4b203bea\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1101"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_hotspot_stats(df):\n",
    "    source = ColumnDataSource(df)\n",
    "    p = figure(x_range=df['name'], y_range=[0,1], title=\"Hotspot Scores\")\n",
    "\n",
    "    p.vbar(x='name', top='score', width=0.8, source=source)\n",
    "    hover = HoverTool(tooltips=[('name', '@name'), ('score', '@score')])\n",
    "    p.width = 900\n",
    "    p.add_tools(hover)\n",
    "    p.xaxis.axis_label = \"Name\"\n",
    "    p.yaxis.axis_label = \"Score\"\n",
    "    p.xaxis.major_label_text_font_size = \"4pt\"\n",
    "    p.xaxis.major_label_orientation = math.pi/4\n",
    "\n",
    "    show(p)\n",
    "plot_hotspot_stats(hdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Account stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 account balances:\n",
      "+----+-----------------------------------------------------+-----------+\n",
      "|    | address                                             |   balance |\n",
      "|----+-----------------------------------------------------+-----------|\n",
      "| 42 | 13jL4pTLq4JQBwDoH1ZBX3VPchmeTZxQSGi4cnyXXuzPPoKxcd5 |   64311.2 |\n",
      "| 69 | 1398hLeHESZHE5jVtaLAV5fdg2vrUeZEs2B92t7TzeQTtugr8dL |   45156.7 |\n",
      "| 97 | 14a5sytsEVKBVhGsVz2rJDkxf1cs1L89zvtFjmPtmPzrQHXPVjF |   37926   |\n",
      "| 82 | 14GWyFj9FjLHzoN3aX7Tq7PL6fEg4dfWPY8CrK8b9S5ZrcKDz6S |   21374.3 |\n",
      "| 85 | 12yyntxFfPhqXDKuEvmAWABNTRnXtYmcgS33WN4tk5YtyaBLDXo |   21347.8 |\n",
      "| 49 | 13o9KUMcmEdhtjXRaJ5AANHLZWBoGcTmF4MFw3MjQbubjR57jXW |   19091.6 |\n",
      "| 81 | 12z4nUiayZnbW46azcegBBB9yGkchFb1Zm7EPuh6eV1r2HT1NgC |   12842.8 |\n",
      "| 75 | 14i6nM1RbWbjQFg5NFbZS3aZJgpUGZUx5toarz6jZLPpNAb95Tq |   12548.3 |\n",
      "| 89 | 14UgUhAPq53iR8vfde6sU4vLPWRe6kZ3ioV7xaVb8hr3oafaok6 |   12213.9 |\n",
      "| 78 | 135bB6B7gGrsdPNcFwvcn12KPjTktSNZvmVbvSBKubCtEgxkpPJ |   11861.3 |\n",
      "+----+-----------------------------------------------------+-----------+\n"
     ]
    }
   ],
   "source": [
    "def account_stats():\n",
    "    accounts = get_accounts(API)\n",
    "    df = pd.DataFrame(accounts)\n",
    "    df['balance'] = df.apply(lambda row: row.balance/100000000, axis=1)\n",
    "    print(f'Top {TOP} account balances:')\n",
    "    print(tabulate(df.sort_values('balance', ascending=False)[['address', 'balance']].head(TOP),\n",
    "                   headers='keys', tablefmt='psql'))\n",
    "    return df\n",
    "adf = account_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Challenge Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Successful challenges past 100 challenges: 10\n",
      "Entirely dud challenges since past 100 challenges: 27\n"
     ]
    }
   ],
   "source": [
    "def challenge_stats():\n",
    "    challenges = get_challenges(API, NUM_CHALLENGES)\n",
    "    res = accumulate_results(challenges)\n",
    "    df = pd.DataFrame(res)\n",
    "\n",
    "    print(f\"Total Successful challenges past {NUM_CHALLENGES} challenges: {sum(df['success'] == 1)}\")\n",
    "    print(f\"Entirely dud challenges since past {NUM_CHALLENGES} challenges: {sum(df['dud'] == 1)}\")\n",
    "    return df\n",
    "cdf = challenge_stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
       "\n",
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       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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       "  var render_items = [{\"docid\":\"00ca375f-0102-4881-a197-e1f3c74da625\",\"roots\":{\"1206\":\"771fe2d2-05e6-43a0-b235-b1b4222eea9e\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
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      "application/vnd.bokehjs_exec.v0+json": ""
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       "id": "1206"
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     "output_type": "display_data"
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   ],
   "source": [
    "def plot_challenge_stats(df):\n",
    "    source = ColumnDataSource(df)\n",
    "    p = figure(title='Challenge Paths')\n",
    "\n",
    "    p.vbar(x='id', top='path_length', width=0.8, source=source)\n",
    "    hover = HoverTool(tooltips=[('id', '@id'), ('path_length', '@path_length')])\n",
    "    p.add_tools(hover)\n",
    "    p.yaxis.axis_label = \"PathLength\"\n",
    "    p.xaxis.axis_label = \"ChallengeId\"\n",
    "\n",
    "    show(p)\n",
    "plot_challenge_stats(cdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hotspot Reward Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 rewarded hotspots:\n",
      "+-----+-------------------------+----------+-----------------------------------------------------+\n",
      "|     | name                    |   amount | account                                             |\n",
      "|-----+-------------------------+----------+-----------------------------------------------------|\n",
      "| 109 | shambolic-rusty-cyborg  | 18622.9  | 13jL4pTLq4JQBwDoH1ZBX3VPchmeTZxQSGi4cnyXXuzPPoKxcd5 |\n",
      "|  55 | mean-alabaster-piranha  | 12014.8  | 14a5sytsEVKBVhGsVz2rJDkxf1cs1L89zvtFjmPtmPzrQHXPVjF |\n",
      "|   8 | mythical-tin-hawk       | 11216    | 14a5sytsEVKBVhGsVz2rJDkxf1cs1L89zvtFjmPtmPzrQHXPVjF |\n",
      "|  94 | clean-nylon-okapi       | 10950.1  | 13jL4pTLq4JQBwDoH1ZBX3VPchmeTZxQSGi4cnyXXuzPPoKxcd5 |\n",
      "|  26 | fit-iron-monkey         |  8258.26 | 14a5sytsEVKBVhGsVz2rJDkxf1cs1L89zvtFjmPtmPzrQHXPVjF |\n",
      "|  47 | cuddly-sapphire-narwhal |  7758.87 | 14i6nM1RbWbjQFg5NFbZS3aZJgpUGZUx5toarz6jZLPpNAb95Tq |\n",
      "| 114 | teeny-cider-troll       |  7491.28 | 13o9KUMcmEdhtjXRaJ5AANHLZWBoGcTmF4MFw3MjQbubjR57jXW |\n",
      "| 122 | bubbly-mandarin-panther |  7011.82 | 13jL4pTLq4JQBwDoH1ZBX3VPchmeTZxQSGi4cnyXXuzPPoKxcd5 |\n",
      "|  75 | magic-carob-quail       |  6739.23 | 12z4nUiayZnbW46azcegBBB9yGkchFb1Zm7EPuh6eV1r2HT1NgC |\n",
      "| 100 | delightful-stone-beetle |  6719.13 | 14eVPPhEPT3WwdRMqNEfbv6Pm6BADS8dCzT1auf5bKX74oTipbD |\n",
      "+-----+-------------------------+----------+-----------------------------------------------------+\n"
     ]
    }
   ],
   "source": [
    "def hotspot_reward_stats():\n",
    "    rewards = get_rewards(API, hdf['address'].values)\n",
    "    rdf = pd.DataFrame(rewards)[['gateway', 'amount', 'account']]\n",
    "    g1 = rdf.groupby(['gateway', 'account']).sum().reset_index()\n",
    "    g1['name'] = g1.apply(lambda row: '-'.join(animalhash(row.gateway).lower().split()), axis=1)\n",
    "    g1['amount'] = g1.apply(lambda row: row.amount/100000000, axis=1)\n",
    "    print(f'Top {TOP} rewarded hotspots:')\n",
    "    print(tabulate(g1.sort_values('amount', ascending=False)[['name', 'amount', 'account']].head(TOP),\n",
    "                   headers='keys', tablefmt='psql'))\n",
    "    return rdf, g1\n",
    "rdf, g = hotspot_reward_stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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1qd6UNmuQsR5FUNc1LAKJM1r7kfx37WGc1csYbvkmUGUTx992K\",\"11rWkkY2rjp1hfZ2noxtwRALArbf12hMzdytHVQrY1c1PzBX4iR\",\"11sAaGTavNJjGgpcoRL5GQACTbWQq4zvftgrZwjabMqJRNfyZn4\",\"11sJGePtegp3KSmX2VSHSJy2kvkhNUHcLh1Xprs3m7FHwnEonfo\",\"11sguEykEnHMXbw14nqo7mCwn18FsKFegaS3tcRqd2fgSKeaKcA\",\"11t2h6ERRn2kbgjFF2hdQLZwvHcMS5NqykN3FEFRzvdf9K9QE1y\",\"11tWRj2Qhnn177iVYm3KUmbPdMyhRfeqHqk9kCyiR7y57hdG9JA\",\"11uEMMjzw2bpuWW1cQHJLKPUiqzm3B8HHPtqsuiXZEhX4VxB4rB\",\"11ubZi6poph2dLTc9jvJwNtjkJxF8WaneDSdMcDoA1tcyb47rFo\",\"11uoSXSsPuuTv1cprZEqNuw5r8giCsAoqDXgsdFMR2G11tLKjkr\",\"11uvA9ZLXGUY5onTtAvMhSxjs4zMuGMganv1xSbipCxRCurUHuH\",\"11vsUeTb8g4KcELPctghGLSDWhUDGAEAkiAhERU3euC69HSNvca\",\"11wuUYRFfbkjHTsqC6HhhvAV1jJUR2mC2MHxSigWnoyiGZuRgrJ\",\"11xKKZwHYZpWcEamiZmyCA1v6YmfcfagQMGf9BJfMnDDiXkhRgV\",\"11xWTUFRswoQM82EWQqDCRCixmX57UjzXLKdeKaXhGpsp66tho\",\"11xkVWtJgF4xrRxhSy1mxYZvWc6anKA3QtrNJWdqP7J3wNkJ8tC\",\"11yXFNu9Je9gvVfyuA8jS8z6faNcZW7kPwPApWYThTk416LGmU\",\"11z6NPpfsdWZgGb5zSNz2VqHioyoVYmAGjANTPGwBKo26fBxb2U\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126],\"name\":[\"muscular-lavender-owl\",\"stale-black-opossum\",\"dazzling-bone-zebra\",\"rhythmic-shadow-spider\",\"dandy-cobalt-lemur\",\"clever-pickle-sparrow\",\"sparkly-aqua-wren\",\"elegant-hazel-starling\",\"mythical-tin-hawk\",\"blurry-seafoam-ape\",\"dizzy-opaque-wolf\",\"thankful-chili-millipede\",\"polished-pearl-anteater\",\"dandy-sangria-okapi\",\"ripe-goldenrod-cheetah\",\"proud-bubblegum-opossum\",\"noisy-laurel-starling\",\"fancy-glossy-rat\",\"proper-orchid-bee\",\"refined-bubblegum-poodle\",\"damaged-concrete-walrus\",\"obedient-mustard-sheep\",\"genuine-powder-halibut\",\"bumpy-boysenberry-manatee\",\"bent-honey-starfish\",\"flat-magenta-chipmunk\",\"fit-iron-monkey\",\"clever-tan-panther\",\"thankful-seafoam-ant\",\"main-pistachio-pangolin\",\"tame-wooden-anteater\",\"curly-berry-coyote\",\"breezy-coal-deer\",\"magic-rainbow-wasp\",\"agreeable-umber-python\",\"itchy-plastic-parakeet\",\"loud-juniper-boar\",\"funny-jade-bull\",\"cheesy-fuzzy-shrimp\",\"sour-honey-llama\",\"radiant-sable-swallow\",\"flat-lilac-shrimp\",\"boxy-holographic-rook\",\"young-sage-rook\",\"howling-gauze-guppy\",\"special-graphite-cat\",\"dry-corduroy-bird\",\"cuddly-sapphire-narwhal\",\"zany-chambray-camel\",\"spicy-seafoam-tadpole\",\"rapid-corduroy-halibut\",\"precise-tangerine-rat\",\"joyous-burgundy-chicken\",\"melted-sable-turkey\",\"round-white-sidewinder\",\"mean-alabaster-piranha\",\"creamy-linen-octopus\",\"beautiful-onyx-platypus\",\"dizzy-strawberry-cricket\",\"clever-basil-moose\",\"precise-orange-peacock\",\"rare-burlap-python\",\"harsh-concrete-lizard\",\"noisy-onyx-peacock\",\"recumbent-goldenrod-griffin\",\"mini-currant-lizard\",\"itchy-flint-puma\",\"dandy-champagne-pike\",\"soaring-iris-beetle\",\"delightful-aqua-blackbird\",\"skinny-fuchsia-mink\",\"dry-pebble-moose\",\"merry-lemon-orca\",\"bitter-bronze-okapi\",\"acidic-lime-haddock\",\"magic-carob-quail\",\"tall-watermelon-dog\",\"spare-porcelain-penguin\",\"sparkly-sable-sparrow\",\"spare-turquoise-otter\",\"micro-clear-griffin\",\"fresh-golden-wasp\",\"slow-burgundy-mandrill\",\"strong-tortilla-marmot\",\"high-frost-blackbird\",\"crazy-opaque-condor\",\"teeny-blue-dinosaur\",\"fierce-onyx-spider\",\"immense-mercurial-crocodile\",\"tiny-vermilion-platypus\",\"brave-lemon-ant\",\"main-mahogany-crane\",\"mythical-jade-tarantula\",\"atomic-fuzzy-dove\",\"clean-nylon-okapi\",\"scrawny-obsidian-halibut\",\"melted-iron-seal\",\"orbiting-cream-starfish\",\"micro-tiger-tuna\",\"cheesy-wooden-bird\",\"delightful-stone-beetle\",\"savory-chili-terrier\",\"sneaky-champagne-pig\",\"basic-ginger-oyster\",\"decent-tortilla-bee\",\"tall-blonde-condor\",\"joyous-beige-moose\",\"fierce-turquoise-anteater\",\"future-punch-ant\",\"shambolic-rusty-cyborg\",\"beautiful-burgundy-rat\",\"sweet-pebble-aphid\",\"melodic-amber-hawk\",\"happy-strawberry-lion\",\"teeny-cider-troll\",\"agreeable-walnut-weasel\",\"sneaky-mulberry-parrot\",\"melodic-pearl-chameleon\",\"howling-violet-millipede\",\"custom-walnut-monkey\",\"long-rosewood-boar\",\"savory-juniper-whale\",\"bubbly-mandarin-panther\",\"orbiting-mint-carp\",\"stale-menthol-piranha\",\"acidic-red-mouse\",\"teeny-cotton-hawk\"]},\"selected\":{\"id\":\"1391\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1390\",\"type\":\"UnionRenderers\"}},\"id\":\"1319\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1329\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1343\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"name\",\"@name\"],[\"amount\",\"@amount\"]]},\"id\":\"1358\",\"type\":\"HoverTool\"},{\"attributes\":{},\"id\":\"1336\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1388\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1389\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1327\",\"type\":\"CategoricalScale\"},{\"attributes\":{\"callback\":null,\"factors\":[\"muscular-lavender-owl\",\"stale-black-opossum\",\"dazzling-bone-zebra\",\"rhythmic-shadow-spider\",\"dandy-cobalt-lemur\",\"clever-pickle-sparrow\",\"sparkly-aqua-wren\",\"elegant-hazel-starling\",\"mythical-tin-hawk\",\"blurry-seafoam-ape\",\"dizzy-opaque-wolf\",\"thankful-chili-millipede\",\"polished-pearl-anteater\",\"dandy-sangria-okapi\",\"ripe-goldenrod-cheetah\",\"proud-bubblegum-opossum\",\"noisy-laurel-starling\",\"fancy-glossy-rat\",\"proper-orchid-bee\",\"refined-bubblegum-poodle\",\"damaged-concrete-walrus\",\"obedient-mustard-sheep\",\"genuine-powder-halibut\",\"bumpy-boysenberry-manatee\",\"bent-honey-starfish\",\"flat-magenta-chipmunk\",\"fit-iron-monkey\",\"clever-tan-panther\",\"thankful-seafoam-ant\",\"main-pistachio-pangolin\",\"tame-wooden-anteater\",\"curly-berry-coyote\",\"breezy-coal-deer\",\"magic-rainbow-wasp\",\"agreeable-umber-python\",\"itchy-plastic-parakeet\",\"loud-juniper-boar\",\"funny-jade-bull\",\"cheesy-fuzzy-shrimp\",\"sour-honey-llama\",\"radiant-sable-swallow\",\"flat-lilac-shrimp\",\"boxy-holographic-rook\",\"young-sage-rook\",\"howling-gauze-guppy\",\"special-graphite-cat\",\"dry-corduroy-bird\",\"cuddly-sapphire-narwhal\",\"zany-chambray-camel\",\"spicy-seafoam-tadpole\",\"rapid-corduroy-halibut\",\"precise-tangerine-rat\",\"joyous-burgundy-chicken\",\"melted-sable-turkey\",\"round-white-sidewinder\",\"mean-alabaster-piranha\",\"creamy-linen-octopus\",\"beautiful-onyx-platypus\",\"dizzy-strawberry-cricket\",\"clever-basil-moose\",\"precise-orange-peacock\",\"rare-burlap-python\",\"harsh-concrete-lizard\",\"noisy-onyx-peacock\",\"recumbent-goldenrod-griffin\",\"mini-currant-lizard\",\"itchy-flint-puma\",\"dandy-champagne-pike\",\"soaring-iris-beetle\",\"delightful-aqua-blackbird\",\"skinny-fuchsia-mink\",\"dry-pebble-moose\",\"merry-lemon-orca\",\"bitter-bronze-okapi\",\"acidic-lime-haddock\",\"magic-carob-quail\",\"tall-watermelon-dog\",\"spare-porcelain-penguin\",\"sparkly-sable-sparrow\",\"spare-turquoise-otter\",\"micro-clear-griffin\",\"fresh-golden-wasp\",\"slow-burgundy-mandrill\",\"strong-tortilla-marmot\",\"high-frost-blackbird\",\"crazy-opaque-condor\",\"teeny-blue-dinosaur\",\"fierce-onyx-spider\",\"immense-mercurial-crocodile\",\"tiny-vermilion-platypus\",\"brave-lemon-ant\",\"main-mahogany-crane\",\"mythical-jade-tarantula\",\"atomic-fuzzy-dove\",\"clean-nylon-okapi\",\"scrawny-obsidian-halibut\",\"melted-iron-seal\",\"orbiting-cream-starfish\",\"micro-tiger-tuna\",\"cheesy-wooden-bird\",\"delightful-stone-beetle\",\"savory-chili-terrier\",\"sneaky-champagne-pig\",\"basic-ginger-oyster\",\"decent-tortilla-bee\",\"tall-blonde-condor\",\"joyous-beige-moose\",\"fierce-turquoise-anteater\",\"future-punch-ant\",\"shambolic-rusty-cyborg\",\"beautiful-burgundy-rat\",\"sweet-pebble-aphid\",\"melodic-amber-hawk\",\"happy-strawberry-lion\",\"teeny-cider-troll\",\"agreeable-walnut-weasel\",\"sneaky-mulberry-parrot\",\"melodic-pearl-chameleon\",\"howling-violet-millipede\",\"custom-walnut-monkey\",\"long-rosewood-boar\",\"savory-juniper-whale\",\"bubbly-mandarin-panther\",\"orbiting-mint-carp\",\"stale-menthol-piranha\",\"acidic-red-mouse\",\"teeny-cotton-hawk\"]},\"id\":\"1323\",\"type\":\"FactorRange\"},{\"attributes\":{\"axis_label\":\"AggregateRewards\",\"formatter\":{\"id\":\"1388\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1336\",\"type\":\"BasicTicker\"}},\"id\":\"1335\",\"type\":\"LinearAxis\"},{\"attributes\":{\"axis_label\":\"Hotspot\",\"formatter\":{\"id\":\"1386\",\"type\":\"CategoricalTickFormatter\"},\"major_label_orientation\":0.7853981633974483,\"major_label_text_font_size\":{\"value\":\"4pt\"},\"ticker\":{\"id\":\"1332\",\"type\":\"CategoricalTicker\"}},\"id\":\"1331\",\"type\":\"CategoricalAxis\"},{\"attributes\":{},\"id\":\"1386\",\"type\":\"CategoricalTickFormatter\"}],\"root_ids\":[\"1320\"]},\"title\":\"Bokeh Application\",\"version\":\"1.3.4\"}};\n",
       "  var render_items = [{\"docid\":\"a325a398-ae71-4453-bc35-e313db01a469\",\"roots\":{\"1320\":\"53029d64-ebf0-4388-8efc-7ae4941ad7ee\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1320"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_challenge_stats(g1):\n",
    "    source = ColumnDataSource(g1)\n",
    "    p = figure(x_range=g1['name'], title=f\"Aggregated last {REWARD_LIMIT} hotspot rewards\")\n",
    "\n",
    "    p.vbar(x='name', top='amount', width=0.8, source=source)\n",
    "    hover = HoverTool(tooltips=[('name', '@name'), ('amount', '@amount')])\n",
    "    p.width = 900\n",
    "    p.add_tools(hover)\n",
    "    p.xaxis.axis_label = \"Hotspot\"\n",
    "    p.yaxis.axis_label = \"AggregateRewards\"\n",
    "    p.xaxis.major_label_text_font_size = \"4pt\"\n",
    "    p.xaxis.major_label_orientation = math.pi/4\n",
    "\n",
    "    show(p)\n",
    "plot_challenge_stats(g)"
   ]
  }
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