stakingRewardsSnapshots.ipynb

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  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "b75c9c09-5b8c-49ba-b7b7-5c5c24dc456a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "from datetime import datetime, timedelta, timezone\n",
    "from decimal import Decimal\n",
    "from typing import Any\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "abe4759c-0c64-4283-a906-428fac34416b",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('stakingRewardsSnapshots.json', 'r', encoding='ascii') as f:\n",
    "    xs = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "7c7aea74-0e81-4bb8-829d-13b1cdce1996",
   "metadata": {},
   "outputs": [],
   "source": [
    "xs = pd.DataFrame(xs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "26870d8a-8cce-47b0-a9d2-c6e9730e769c",
   "metadata": {},
   "outputs": [],
   "source": [
    "for c in xs.columns:\n",
    "    xs[c] = xs[c].map(Decimal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "b1f9adc1-6008-41ad-92d9-564e22d59605",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def fromtimestamp(s: Any) -> datetime:\n",
    "#     return datetime.utcfromtimestamp(int(s)).replace(tzinfo=timezone.utc)\n",
    "\n",
    "# xs['date'] = pd.to_datetime(xs['createdAtTimestamp'].map(fromtimestamp))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "359d4865-e725-4c93-8a89-112a74d0d2a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "xs['net'] = xs['periodTotalRewards'].sub(xs['periodProtocolRewards'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "ef2b1ed2-0d8d-4b83-804a-901cfcaeea1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "xs = xs.drop(['id', 'periodProtocolRewards', 'createdAtBlock', 'createdAtTimestamp'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "82d3f33d-c8ca-4ba2-b302-0f0972f93bb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>periodTotalRewards</th>\n",
       "      <th>periodDuration</th>\n",
       "      <th>totalStaked</th>\n",
       "      <th>net</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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      "text/plain": [
       "    periodTotalRewards periodDuration              totalStaked  \\\n",
       "0  9612479436968609145         263136  30452205383625944950861   \n",
       "1  4199851054506396780         167832  30452205383625944950861   \n",
       "2  2324144786224226178          87900  30452205383625944950861   \n",
       "3  2105876454087991945          87852  30452205383625944950861   \n",
       "4  2161213237022272776          88212  30452205383625944950861   \n",
       "\n",
       "                   net  \n",
       "0  8843481082011120414  \n",
       "1  3863862970145885038  \n",
       "2  2138213203326288084  \n",
       "3  1937406337760952590  \n",
       "4  1988316178060490954  "
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "dcad83d7-af9b-40b3-98e9-0fdf190977d0",
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     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "rate = xs['periodTotalRewards'].div(xs['totalStaked'])\n",
    "d = int(xs['periodDuration'].sum()) / 60/60/24\n",
    "y = float(rate.add(1).product())\n",
    "(np.power(y, 365/d) - 1) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "a8651605-8218-4655-993b-769f3e898c07",
   "metadata": {},
   "outputs": [
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     "data": {
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     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "rate = xs['net'].div(xs['totalStaked'])\n",
    "d = int(xs['periodDuration'].sum()) / 60/60/24\n",
    "y = float(rate.add(1).product())\n",
    "(np.power(y, 365/d) - 1) * 100"
   ]
  }
 ],
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