Dataset SQLite3 Example.ipynb

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   "source": [
    "# SQLite Creation"
   ]
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   "source": [
    "Example of creating a dataset that will be compatible with [Summary Loop](https://github.com/CannyLab/summary_loop) training scripts.\n",
    "\n",
    "Another option is to modify the [collate_fn](https://pytorch.org/docs/stable/data.html) of the scripts, to interface with another data format.\n"
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   "source": [
    "import sqlite3, os # This is a built in, no need to install\n",
    "\n",
    "example_dataset = [\n",
    "    {\"title\": \"Example document1\", \"body\": \"The body of the very first document in the collection\"},\n",
    "    {\"title\": \"Example document2\", \"body\": \"The body of the second document in the collection. You could put any data in here.\"},\n",
    "]"
   ]
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   "source": [
    "db_file = \"/home/phillab/dataset/example_dataset.db\"\n",
    "\n",
    "if os.path.isfile(db_file):\n",
    "    os.remove(db_file)\n",
    "\n",
    "conn = sqlite3.connect(db_file,detect_types=sqlite3.PARSE_DECLTYPES)\n",
    "conn.row_factory = sqlite3.Row\n",
    "c = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CREATE TABLE\n",
    "\n",
    "sql_create = \"CREATE TABLE articles (id INTEGER PRIMARY KEY AUTOINCREMENT, title TEXT NOT NULL, body TEXT);\"\n",
    "c.execute(sql_create)\n",
    "conn.commit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sql_insert = \"INSERT INTO articles (title, body) VALUES (?, ?)\"\n",
    "\n",
    "for a in example_dataset:\n",
    "    c.execute(sql_insert, (a['title'], a['body']))\n",
    "conn.commit()"
   ]
  }
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