230216_(Bucket_boto3).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2f4c1982",
   "metadata": {},
   "outputs": [],
   "source": [
    "import boto3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7b5c1881",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.26.72'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boto3.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1c3a85c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ABC'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from easydict import EasyDict\n",
    "\n",
    "adict = dict()\n",
    "adict[\"abc\"] = \"ABC\"\n",
    "adict[\"abc\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c829ee46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ABC'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adict = EasyDict()\n",
    "adict.abc = \"ABC\"\n",
    "adict.abc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4438b993",
   "metadata": {},
   "outputs": [],
   "source": [
    "settings = EasyDict()\n",
    "\n",
    "settings.AWS_ACCESS_KEY_ID = \"\" # AWS 자격증명 ID\n",
    "settings.AWS_SECRET_ACCESS_KEY = \"\" # AWS 자격증명 PW\n",
    "settings.AWS_REGION_NAME = \"ap-northeast-2\" # AWS 지역\n",
    "settings.AWS_ACCOUNT_ID = \"\" # 계정 ID\n",
    "\n",
    "settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "70522830",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<botocore.client.S3 at 0x7f0be64d6a30>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import boto3\n",
    "\n",
    "s3_client = boto3.client(\n",
    "    service_name = \"s3\",\n",
    "    aws_access_key_id = settings.AWS_ACCESS_KEY_ID,\n",
    "    aws_secret_access_key = settings.AWS_SECRET_ACCESS_KEY,\n",
    "    region_name = settings.AWS_REGION_NAME,\n",
    ")\n",
    "s3_client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b89d33be",
   "metadata": {},
   "outputs": [],
   "source": [
    "settings.AWS_BUCKET_NAME = 'genia-bucket'\n",
    "obj = s3_client.get_object(Bucket=settings.AWS_BUCKET_NAME, Key=\"raw/abalone.csv\")\n",
    "obj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9339d81c",
   "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>Type</th>\n",
       "      <th>LongestShell</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>WholeWeight</th>\n",
       "      <th>ShuckedWeight</th>\n",
       "      <th>VisceraWeight</th>\n",
       "      <th>ShellWeight</th>\n",
       "      <th>Rings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M</td>\n",
       "      <td>0.455</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.095</td>\n",
       "      <td>0.5140</td>\n",
       "      <td>0.2245</td>\n",
       "      <td>0.1010</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.265</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.2255</td>\n",
       "      <td>0.0995</td>\n",
       "      <td>0.0485</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>F</td>\n",
       "      <td>0.530</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.135</td>\n",
       "      <td>0.6770</td>\n",
       "      <td>0.2565</td>\n",
       "      <td>0.1415</td>\n",
       "      <td>0.2100</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.5160</td>\n",
       "      <td>0.2155</td>\n",
       "      <td>0.1140</td>\n",
       "      <td>0.1550</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>I</td>\n",
       "      <td>0.330</td>\n",
       "      <td>0.255</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.0895</td>\n",
       "      <td>0.0395</td>\n",
       "      <td>0.0550</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4172</th>\n",
       "      <td>F</td>\n",
       "      <td>0.565</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.165</td>\n",
       "      <td>0.8870</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.2390</td>\n",
       "      <td>0.2490</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4173</th>\n",
       "      <td>M</td>\n",
       "      <td>0.590</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.135</td>\n",
       "      <td>0.9660</td>\n",
       "      <td>0.4390</td>\n",
       "      <td>0.2145</td>\n",
       "      <td>0.2605</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4174</th>\n",
       "      <td>M</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.475</td>\n",
       "      <td>0.205</td>\n",
       "      <td>1.1760</td>\n",
       "      <td>0.5255</td>\n",
       "      <td>0.2875</td>\n",
       "      <td>0.3080</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4175</th>\n",
       "      <td>F</td>\n",
       "      <td>0.625</td>\n",
       "      <td>0.485</td>\n",
       "      <td>0.150</td>\n",
       "      <td>1.0945</td>\n",
       "      <td>0.5310</td>\n",
       "      <td>0.2610</td>\n",
       "      <td>0.2960</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4176</th>\n",
       "      <td>M</td>\n",
       "      <td>0.710</td>\n",
       "      <td>0.555</td>\n",
       "      <td>0.195</td>\n",
       "      <td>1.9485</td>\n",
       "      <td>0.9455</td>\n",
       "      <td>0.3765</td>\n",
       "      <td>0.4950</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4177 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Type  LongestShell  Diameter  Height  WholeWeight  ShuckedWeight  \\\n",
       "0       M         0.455     0.365   0.095       0.5140         0.2245   \n",
       "1       M         0.350     0.265   0.090       0.2255         0.0995   \n",
       "2       F         0.530     0.420   0.135       0.6770         0.2565   \n",
       "3       M         0.440     0.365   0.125       0.5160         0.2155   \n",
       "4       I         0.330     0.255   0.080       0.2050         0.0895   \n",
       "...   ...           ...       ...     ...          ...            ...   \n",
       "4172    F         0.565     0.450   0.165       0.8870         0.3700   \n",
       "4173    M         0.590     0.440   0.135       0.9660         0.4390   \n",
       "4174    M         0.600     0.475   0.205       1.1760         0.5255   \n",
       "4175    F         0.625     0.485   0.150       1.0945         0.5310   \n",
       "4176    M         0.710     0.555   0.195       1.9485         0.9455   \n",
       "\n",
       "      VisceraWeight  ShellWeight  Rings  \n",
       "0            0.1010       0.1500     15  \n",
       "1            0.0485       0.0700      7  \n",
       "2            0.1415       0.2100      9  \n",
       "3            0.1140       0.1550     10  \n",
       "4            0.0395       0.0550      7  \n",
       "...             ...          ...    ...  \n",
       "4172         0.2390       0.2490     11  \n",
       "4173         0.2145       0.2605     10  \n",
       "4174         0.2875       0.3080      9  \n",
       "4175         0.2610       0.2960     10  \n",
       "4176         0.3765       0.4950     12  \n",
       "\n",
       "[4177 rows x 9 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(obj[\"Body\"], encoding=\"utf-8\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ddb910c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['M', 'F', 'I'], dtype=object)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Type\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e760f25a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Type</th>\n",
       "      <th>LongestShell</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>WholeWeight</th>\n",
       "      <th>ShuckedWeight</th>\n",
       "      <th>VisceraWeight</th>\n",
       "      <th>ShellWeight</th>\n",
       "      <th>Rings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M</td>\n",
       "      <td>0.455</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.095</td>\n",
       "      <td>0.5140</td>\n",
       "      <td>0.2245</td>\n",
       "      <td>0.1010</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.265</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.2255</td>\n",
       "      <td>0.0995</td>\n",
       "      <td>0.0485</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.5160</td>\n",
       "      <td>0.2155</td>\n",
       "      <td>0.1140</td>\n",
       "      <td>0.1550</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M</td>\n",
       "      <td>0.475</td>\n",
       "      <td>0.370</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.5095</td>\n",
       "      <td>0.2165</td>\n",
       "      <td>0.1125</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.4060</td>\n",
       "      <td>0.1675</td>\n",
       "      <td>0.0810</td>\n",
       "      <td>0.1350</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4170</th>\n",
       "      <td>M</td>\n",
       "      <td>0.550</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.8395</td>\n",
       "      <td>0.3155</td>\n",
       "      <td>0.1955</td>\n",
       "      <td>0.2405</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4171</th>\n",
       "      <td>M</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.155</td>\n",
       "      <td>0.8675</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1720</td>\n",
       "      <td>0.2290</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4173</th>\n",
       "      <td>M</td>\n",
       "      <td>0.590</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.135</td>\n",
       "      <td>0.9660</td>\n",
       "      <td>0.4390</td>\n",
       "      <td>0.2145</td>\n",
       "      <td>0.2605</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4174</th>\n",
       "      <td>M</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.475</td>\n",
       "      <td>0.205</td>\n",
       "      <td>1.1760</td>\n",
       "      <td>0.5255</td>\n",
       "      <td>0.2875</td>\n",
       "      <td>0.3080</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4176</th>\n",
       "      <td>M</td>\n",
       "      <td>0.710</td>\n",
       "      <td>0.555</td>\n",
       "      <td>0.195</td>\n",
       "      <td>1.9485</td>\n",
       "      <td>0.9455</td>\n",
       "      <td>0.3765</td>\n",
       "      <td>0.4950</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1528 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Type  LongestShell  Diameter  Height  WholeWeight  ShuckedWeight  \\\n",
       "0       M         0.455     0.365   0.095       0.5140         0.2245   \n",
       "1       M         0.350     0.265   0.090       0.2255         0.0995   \n",
       "3       M         0.440     0.365   0.125       0.5160         0.2155   \n",
       "8       M         0.475     0.370   0.125       0.5095         0.2165   \n",
       "11      M         0.430     0.350   0.110       0.4060         0.1675   \n",
       "...   ...           ...       ...     ...          ...            ...   \n",
       "4170    M         0.550     0.430   0.130       0.8395         0.3155   \n",
       "4171    M         0.560     0.430   0.155       0.8675         0.4000   \n",
       "4173    M         0.590     0.440   0.135       0.9660         0.4390   \n",
       "4174    M         0.600     0.475   0.205       1.1760         0.5255   \n",
       "4176    M         0.710     0.555   0.195       1.9485         0.9455   \n",
       "\n",
       "      VisceraWeight  ShellWeight  Rings  \n",
       "0            0.1010       0.1500     15  \n",
       "1            0.0485       0.0700      7  \n",
       "3            0.1140       0.1550     10  \n",
       "8            0.1125       0.1650      9  \n",
       "11           0.0810       0.1350     10  \n",
       "...             ...          ...    ...  \n",
       "4170         0.1955       0.2405     10  \n",
       "4171         0.1720       0.2290      8  \n",
       "4173         0.2145       0.2605     10  \n",
       "4174         0.2875       0.3080      9  \n",
       "4176         0.3765       0.4950     12  \n",
       "\n",
       "[1528 rows x 9 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df.Type == \"M\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "bde867f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('student2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "535e7941",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install pyarrow\n",
    "df.to_parquet('./student2_again.parquet', engine=\"pyarrow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "bce03355",
   "metadata": {},
   "outputs": [],
   "source": [
    "s3_client.upload_file('./student2.csv', settings.AWS_BUCKET_NAME, \"upload-test/student2.csv\")\n",
    "s3_client.upload_file('./student2_again.parquet', settings.AWS_BUCKET_NAME, \"upload-test/student2_again.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82140bfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# s3://genia-bucket/upload-test/{YOUR_ID}.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a1abb1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"./teacher.csv\", encoding=\"utf-8\", index=False)\n",
    "\n",
    "response = s3_client.put_object(\n",
    "    Body = \"fileupload\",\n",
    "    Bucket = \"bucket_name\",\n",
    "    Key = \"path.csv\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "a01836b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from smart_open import open as s_open\n",
    "\n",
    "file_name = f\"s3://{settings.AWS_BUCKET_NAME}/upload-test/student2.parquet\"\n",
    "\n",
    "with s_open(file_name, \"wb\", transport_params=dict(client=s3_client)) as out_file:\n",
    "    df.to_parquet(out_file, engine=\"pyarrow\", compression=\"gzip\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "4b32614f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Package                      Version\n",
      "---------------------------- ---------\n",
      "absl-py                      1.4.0\n",
      "anyio                        3.6.2\n",
      "argon2-cffi                  21.3.0\n",
      "argon2-cffi-bindings         21.2.0\n",
      "arrow                        1.2.3\n",
      "asttokens                    2.2.1\n",
      "astunparse                   1.6.3\n",
      "attrs                        22.2.0\n",
      "backcall                     0.2.0\n",
      "beautifulsoup4               4.11.2\n",
      "bleach                       6.0.0\n",
      "boto3                        1.26.72\n",
      "botocore                     1.29.72\n",
      "cachetools                   5.3.0\n",
      "certifi                      2022.12.7\n",
      "cffi                         1.15.1\n",
      "charset-normalizer           3.0.1\n",
      "comm                         0.1.2\n",
      "debugpy                      1.6.6\n",
      "decorator                    5.1.1\n",
      "defusedxml                   0.7.1\n",
      "easydict                     1.10\n",
      "executing                    1.2.0\n",
      "fastjsonschema               2.16.2\n",
      "flatbuffers                  23.1.21\n",
      "fqdn                         1.5.1\n",
      "gast                         0.4.0\n",
      "google-auth                  2.16.0\n",
      "google-auth-oauthlib         0.4.6\n",
      "google-pasta                 0.2.0\n",
      "grpcio                       1.51.1\n",
      "h5py                         3.8.0\n",
      "idna                         3.4\n",
      "importlib-metadata           6.0.0\n",
      "ipykernel                    6.21.2\n",
      "ipython                      8.10.0\n",
      "ipython-genutils             0.2.0\n",
      "ipywidgets                   8.0.4\n",
      "isoduration                  20.11.0\n",
      "jedi                         0.18.2\n",
      "Jinja2                       3.1.2\n",
      "jmespath                     1.0.1\n",
      "jsonpointer                  2.3\n",
      "jsonschema                   4.17.3\n",
      "jupyter                      1.0.0\n",
      "jupyter_client               8.0.2\n",
      "jupyter-console              6.5.1\n",
      "jupyter_core                 5.2.0\n",
      "jupyter-events               0.6.3\n",
      "jupyter_server               2.3.0\n",
      "jupyter_server_terminals     0.4.4\n",
      "jupyterlab-pygments          0.2.2\n",
      "jupyterlab-widgets           3.0.5\n",
      "keras                        2.11.0\n",
      "libclang                     15.0.6.1\n",
      "Markdown                     3.4.1\n",
      "MarkupSafe                   2.1.2\n",
      "matplotlib-inline            0.1.6\n",
      "mistune                      2.0.5\n",
      "nbclassic                    0.5.1\n",
      "nbclient                     0.7.2\n",
      "nbconvert                    7.2.9\n",
      "nbformat                     5.7.3\n",
      "nest-asyncio                 1.5.6\n",
      "notebook                     6.5.2\n",
      "notebook_shim                0.2.2\n",
      "numpy                        1.24.2\n",
      "oauthlib                     3.2.2\n",
      "opt-einsum                   3.3.0\n",
      "packaging                    23.0\n",
      "pandas                       1.5.3\n",
      "pandocfilters                1.5.0\n",
      "parso                        0.8.3\n",
      "pexpect                      4.8.0\n",
      "pickleshare                  0.7.5\n",
      "pip                          23.0\n",
      "platformdirs                 3.0.0\n",
      "prometheus-client            0.16.0\n",
      "prompt-toolkit               3.0.36\n",
      "protobuf                     3.19.6\n",
      "psutil                       5.9.4\n",
      "ptyprocess                   0.7.0\n",
      "pure-eval                    0.2.2\n",
      "pyarrow                      11.0.0\n",
      "pyasn1                       0.4.8\n",
      "pyasn1-modules               0.2.8\n",
      "pycparser                    2.21\n",
      "Pygments                     2.14.0\n",
      "PyMySQL                      1.0.2\n",
      "pyrsistent                   0.19.3\n",
      "python-dateutil              2.8.2\n",
      "python-json-logger           2.0.6\n",
      "pytz                         2022.7.1\n",
      "PyYAML                       6.0\n",
      "pyzmq                        25.0.0\n",
      "qtconsole                    5.4.0\n",
      "QtPy                         2.3.0\n",
      "requests                     2.28.2\n",
      "requests-oauthlib            1.3.1\n",
      "rfc3339-validator            0.1.4\n",
      "rfc3986-validator            0.1.1\n",
      "rsa                          4.9\n",
      "s3transfer                   0.6.0\n",
      "Send2Trash                   1.8.0\n",
      "setuptools                   58.1.0\n",
      "six                          1.16.0\n",
      "smart-open                   6.3.0\n",
      "sniffio                      1.3.0\n",
      "soupsieve                    2.4\n",
      "stack-data                   0.6.2\n",
      "tensorboard                  2.11.2\n",
      "tensorboard-data-server      0.6.1\n",
      "tensorboard-plugin-wit       1.8.1\n",
      "tensorflow                   2.11.0\n",
      "tensorflow-estimator         2.11.0\n",
      "tensorflow-io-gcs-filesystem 0.30.0\n",
      "termcolor                    2.2.0\n",
      "terminado                    0.17.1\n",
      "tinycss2                     1.2.1\n",
      "tornado                      6.2\n",
      "traitlets                    5.9.0\n",
      "typing_extensions            4.5.0\n",
      "uri-template                 1.2.0\n",
      "urllib3                      1.26.14\n",
      "wcwidth                      0.2.6\n",
      "webcolors                    1.12\n",
      "webencodings                 0.5.1\n",
      "websocket-client             1.5.1\n",
      "Werkzeug                     2.2.3\n",
      "wheel                        0.38.4\n",
      "widgetsnbextension           4.0.5\n",
      "wrapt                        1.14.1\n",
      "zipp                         3.13.0\n"
     ]
    }
   ],
   "source": [
    "!pip list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "c0b4c5fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip freeze > requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "062734fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total 52\r\n",
      "drwxrwxr-x 4 1000 1000  4096 Feb 16 08:10  .\r\n",
      "drwxr-xr-x 1 root root  4096 Feb 16 02:26  ..\r\n",
      "drwx------ 4 root root  4096 Feb 16 06:16  .Trash-0\r\n",
      "drwxr-xr-x 2 root root  4096 Feb 16 06:21  .ipynb_checkpoints\r\n",
      "-rw-r--r-- 1 root root 28532 Feb 16 08:10 '230216_(Bucket_boto3).ipynb'\r\n",
      "-rw-rw-r-- 1 1000 1000   268 Feb 16 02:19  Dockerfile\r\n",
      "-rw-rw-r-- 1 1000 1000  2396 Feb 16 08:11  requirements.txt\r\n"
     ]
    }
   ],
   "source": [
    "!ls -al\n",
    "# 수정된 것을 확인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "a399e6e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "absl-py==1.4.0\r\n",
      "anyio==3.6.2\r\n",
      "argon2-cffi==21.3.0\r\n",
      "argon2-cffi-bindings==21.2.0\r\n",
      "arrow==1.2.3\r\n",
      "asttokens==2.2.1\r\n",
      "astunparse==1.6.3\r\n",
      "attrs==22.2.0\r\n",
      "backcall==0.2.0\r\n",
      "beautifulsoup4==4.11.2\r\n",
      "bleach==6.0.0\r\n",
      "boto3==1.26.72\r\n",
      "botocore==1.29.72\r\n",
      "cachetools==5.3.0\r\n",
      "certifi==2022.12.7\r\n",
      "cffi==1.15.1\r\n",
      "charset-normalizer==3.0.1\r\n",
      "comm==0.1.2\r\n",
      "debugpy==1.6.6\r\n",
      "decorator==5.1.1\r\n",
      "defusedxml==0.7.1\r\n",
      "easydict==1.10\r\n",
      "executing==1.2.0\r\n",
      "fastjsonschema==2.16.2\r\n",
      "flatbuffers==23.1.21\r\n",
      "fqdn==1.5.1\r\n",
      "gast==0.4.0\r\n",
      "google-auth==2.16.0\r\n",
      "google-auth-oauthlib==0.4.6\r\n",
      "google-pasta==0.2.0\r\n",
      "grpcio==1.51.1\r\n",
      "h5py==3.8.0\r\n",
      "idna==3.4\r\n",
      "importlib-metadata==6.0.0\r\n",
      "ipykernel==6.21.2\r\n",
      "ipython==8.10.0\r\n",
      "ipython-genutils==0.2.0\r\n",
      "ipywidgets==8.0.4\r\n",
      "isoduration==20.11.0\r\n",
      "jedi==0.18.2\r\n",
      "Jinja2==3.1.2\r\n",
      "jmespath==1.0.1\r\n",
      "jsonpointer==2.3\r\n",
      "jsonschema==4.17.3\r\n",
      "jupyter==1.0.0\r\n",
      "jupyter-console==6.5.1\r\n",
      "jupyter-events==0.6.3\r\n",
      "jupyter_client==8.0.2\r\n",
      "jupyter_core==5.2.0\r\n",
      "jupyter_server==2.3.0\r\n",
      "jupyter_server_terminals==0.4.4\r\n",
      "jupyterlab-pygments==0.2.2\r\n",
      "jupyterlab-widgets==3.0.5\r\n",
      "keras==2.11.0\r\n",
      "libclang==15.0.6.1\r\n",
      "Markdown==3.4.1\r\n",
      "MarkupSafe==2.1.2\r\n",
      "matplotlib-inline==0.1.6\r\n",
      "mistune==2.0.5\r\n",
      "nbclassic==0.5.1\r\n",
      "nbclient==0.7.2\r\n",
      "nbconvert==7.2.9\r\n",
      "nbformat==5.7.3\r\n",
      "nest-asyncio==1.5.6\r\n",
      "notebook==6.5.2\r\n",
      "notebook_shim==0.2.2\r\n",
      "numpy==1.24.2\r\n",
      "oauthlib==3.2.2\r\n",
      "opt-einsum==3.3.0\r\n",
      "packaging==23.0\r\n",
      "pandas==1.5.3\r\n",
      "pandocfilters==1.5.0\r\n",
      "parso==0.8.3\r\n",
      "pexpect==4.8.0\r\n",
      "pickleshare==0.7.5\r\n",
      "platformdirs==3.0.0\r\n",
      "prometheus-client==0.16.0\r\n",
      "prompt-toolkit==3.0.36\r\n",
      "protobuf==3.19.6\r\n",
      "psutil==5.9.4\r\n",
      "ptyprocess==0.7.0\r\n",
      "pure-eval==0.2.2\r\n",
      "pyarrow==11.0.0\r\n",
      "pyasn1==0.4.8\r\n",
      "pyasn1-modules==0.2.8\r\n",
      "pycparser==2.21\r\n",
      "Pygments==2.14.0\r\n",
      "PyMySQL==1.0.2\r\n",
      "pyrsistent==0.19.3\r\n",
      "python-dateutil==2.8.2\r\n",
      "python-json-logger==2.0.6\r\n",
      "pytz==2022.7.1\r\n",
      "PyYAML==6.0\r\n",
      "pyzmq==25.0.0\r\n",
      "qtconsole==5.4.0\r\n",
      "QtPy==2.3.0\r\n",
      "requests==2.28.2\r\n",
      "requests-oauthlib==1.3.1\r\n",
      "rfc3339-validator==0.1.4\r\n",
      "rfc3986-validator==0.1.1\r\n",
      "rsa==4.9\r\n",
      "s3transfer==0.6.0\r\n",
      "Send2Trash==1.8.0\r\n",
      "six==1.16.0\r\n",
      "smart-open==6.3.0\r\n",
      "sniffio==1.3.0\r\n",
      "soupsieve==2.4\r\n",
      "stack-data==0.6.2\r\n",
      "tensorboard==2.11.2\r\n",
      "tensorboard-data-server==0.6.1\r\n",
      "tensorboard-plugin-wit==1.8.1\r\n",
      "tensorflow==2.11.0\r\n",
      "tensorflow-estimator==2.11.0\r\n",
      "tensorflow-io-gcs-filesystem==0.30.0\r\n",
      "termcolor==2.2.0\r\n",
      "terminado==0.17.1\r\n",
      "tinycss2==1.2.1\r\n",
      "tornado==6.2\r\n",
      "traitlets==5.9.0\r\n",
      "typing_extensions==4.5.0\r\n",
      "uri-template==1.2.0\r\n",
      "urllib3==1.26.14\r\n",
      "wcwidth==0.2.6\r\n",
      "webcolors==1.12\r\n",
      "webencodings==0.5.1\r\n",
      "websocket-client==1.5.1\r\n",
      "Werkzeug==2.2.3\r\n",
      "widgetsnbextension==4.0.5\r\n",
      "wrapt==1.14.1\r\n",
      "zipp==3.13.0\r\n"
     ]
    }
   ],
   "source": [
    "!cat requirements.txt\n",
    "# 리눅스 환경에서도 가능\n",
    "# 느낌표를 붙이면 리눅스 환경으로 쓸 수 있음"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}