adjustTask.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlalchemy as db\n",
    "from sqlalchemy import orm\n",
    "from sqlalchemy import text\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "engines = {\n",
    "    \"db1\": db.create_engine(\"postgres://localhost:5433/db-1\"),\n",
    "    \"db2\": db.create_engine(\"postgres://localhost:5434/db-2\"),\n",
    "    \"db3\": db.create_engine(\"postgres://localhost:5435/db-3\")\n",
    "} "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "sessions = {\n",
    "    \"session1\": orm.sessionmaker(engines[\"db1\"]),\n",
    "    \"session2\": orm.sessionmaker(engines[\"db2\"]),\n",
    "    \"session3\": orm.sessionmaker(engines[\"db3\"])\n",
    "} "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = sessions[\"session1\"]()\n",
    "s2 = sessions[\"session2\"]()\n",
    "s3 = sessions[\"session3\"]()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(columns=[\"country\", \"installs\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "sql = text(\"select country, sum(installs) from installs_by_country where EXTRACT(Month from created_at) = 5 and EXTRACT(Year from created_at) = 2019 and paid = true group by country\")\n",
    "results = []\n",
    "results.append( engines[\"db1\"].execute(sql))\n",
    "results.append( engines[\"db2\"].execute(sql))\n",
    "results.append( engines[\"db3\"].execute(sql))\n",
    "data=[]\n",
    "for result in results:\n",
    "    for row in result:\n",
    "        data.append((row[0], row[1]))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>installs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DE</td>\n",
       "      <td>128419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GB</td>\n",
       "      <td>125354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>IT</td>\n",
       "      <td>120229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RU</td>\n",
       "      <td>117296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TR</td>\n",
       "      <td>127249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>US</td>\n",
       "      <td>116795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DE</td>\n",
       "      <td>128419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>GB</td>\n",
       "      <td>125354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>IT</td>\n",
       "      <td>120229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>RU</td>\n",
       "      <td>117296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>TR</td>\n",
       "      <td>127249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>US</td>\n",
       "      <td>116795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>DE</td>\n",
       "      <td>128419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>GB</td>\n",
       "      <td>125354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>IT</td>\n",
       "      <td>120229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>RU</td>\n",
       "      <td>117296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>TR</td>\n",
       "      <td>127249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>US</td>\n",
       "      <td>116795</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   country  installs\n",
       "0       DE    128419\n",
       "1       GB    125354\n",
       "2       IT    120229\n",
       "3       RU    117296\n",
       "4       TR    127249\n",
       "5       US    116795\n",
       "6       DE    128419\n",
       "7       GB    125354\n",
       "8       IT    120229\n",
       "9       RU    117296\n",
       "10      TR    127249\n",
       "11      US    116795\n",
       "12      DE    128419\n",
       "13      GB    125354\n",
       "14      IT    120229\n",
       "15      RU    117296\n",
       "16      TR    127249\n",
       "17      US    116795"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(data =data,  columns=[\"country\", \"installs\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>installs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>385257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GB</th>\n",
       "      <td>376062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT</th>\n",
       "      <td>360687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RU</th>\n",
       "      <td>351888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TR</th>\n",
       "      <td>381747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>350385</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         installs\n",
       "country          \n",
       "DE         385257\n",
       "GB         376062\n",
       "IT         360687\n",
       "RU         351888\n",
       "TR         381747\n",
       "US         350385"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby([\"country\"]).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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