{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HozF_O0VM6-B"
      },
      "source": [
        "This notebook is a brief guide of downloading KPF raw (level 0) data in a given period. It requires PI credentials to access proprietary data. For more detail about PyKOA, please see:\n",
        "http://koa.ipac.caltech.edu/UserGuide/PyKOA/notebooks/PyKOA_KPF_introduction.html"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mmPy9VTCNrt-"
      },
      "source": [
        "First, we need to install the KOA python client PyKOA. This line can be removed if PyKOA is already installed."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T3H-B5qiOHGo",
        "outputId": "53ecd608-a488-4bd6-bd8c-ddb98315905c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pykoa\n",
            "  Downloading pykoa-1.7.2-py3-none-any.whl (29 kB)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from pykoa) (2.31.0)\n",
            "Collecting xmltodict (from pykoa)\n",
            "  Downloading xmltodict-0.13.0-py2.py3-none-any.whl (10.0 kB)\n",
            "Collecting bs4 (from pykoa)\n",
            "  Downloading bs4-0.0.1.tar.gz (1.1 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: lxml in /usr/local/lib/python3.10/dist-packages (from pykoa) (4.9.3)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.10/dist-packages (from bs4->pykoa) (4.11.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->pykoa) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->pykoa) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->pykoa) (2.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->pykoa) (2023.7.22)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4->bs4->pykoa) (2.4.1)\n",
            "Building wheels for collected packages: bs4\n",
            "  Building wheel for bs4 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for bs4: filename=bs4-0.0.1-py3-none-any.whl size=1256 sha256=63bffd17f595e42cc1a9e4a179b6e86d48699e94ab52b630e4e91ec865742d51\n",
            "  Stored in directory: /root/.cache/pip/wheels/25/42/45/b773edc52acb16cd2db4cf1a0b47117e2f69bb4eb300ed0e70\n",
            "Successfully built bs4\n",
            "Installing collected packages: xmltodict, bs4, pykoa\n",
            "Successfully installed bs4-0.0.1 pykoa-1.7.2 xmltodict-0.13.0\n"
          ]
        }
      ],
      "source": [
        "!pip install pykoa"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hhVJIWD0OKsS"
      },
      "source": [
        "The next steop is to import pre-requisite packages"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "4G2fXjioOKBa"
      },
      "outputs": [],
      "source": [
        "import sys\n",
        "import io\n",
        "import os\n",
        "from pykoa.koa import Koa\n",
        "from astropy.table import Table,Column"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9jJgI5RBOOOX"
      },
      "source": [
        "Then we need to assign directory that stores the query results:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "OB_GgjpsOXVk"
      },
      "outputs": [],
      "source": [
        "try:\n",
        "    os.mkdir('./output')\n",
        "except:\n",
        "    print(\" Directory exists already\", flush=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q3-Uu0RiOWm9"
      },
      "source": [
        "After that, we use a cookie for KOA log in. We can also spell out the credentials, but for security purpose, it is better to enter the userid and password interactively"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "olSx2E55OcgS",
        "outputId": "6acc6afb-9c30-42f6-fa57-f1c93cd573ba"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Userid: clee\n",
            "Password: ··········\n",
            "Successfully login as clee\n"
          ]
        }
      ],
      "source": [
        "Koa.login ('./tapcookie.txt')\n",
        "#Koa.login ('./tapcookie.txt', userid='clee', password='salami')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kBQdEWm9OdOs"
      },
      "source": [
        "We can then proceed to query KPF data taken in a given period. Note the time period is specified in UT date. The output table will be saved in the designated directory and in IPAC table format."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VaeWQLWROveh",
        "outputId": "ded62fb1-dfa5-45f3-fec7-c94772076fcc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "submitting request...\n",
            "Result downloaded to file [./output/kpf_daterange.tbl]\n",
            "          koaid                     ofname          ...   semid   propint\n",
            "------------------------- ------------------------- ... --------- -------\n",
            "KP.20230530.03614.55.fits KP.20230530.03614.55.fits ... 2023a_eng       0\n",
            "KP.20230530.03675.91.fits KP.20230530.03675.91.fits ... 2023a_eng       0\n",
            "KP.20230530.03737.14.fits KP.20230530.03737.14.fits ... 2023a_eng       0\n",
            "KP.20230530.03798.47.fits KP.20230530.03798.47.fits ... 2023a_eng       0\n",
            "KP.20230530.03859.73.fits KP.20230530.03859.73.fits ... 2023a_eng       0\n",
            "KP.20230530.03920.93.fits KP.20230530.03920.93.fits ... 2023a_eng       0\n",
            "KP.20230530.03982.15.fits KP.20230530.03982.15.fits ... 2023a_eng       0\n",
            "KP.20230530.04043.50.fits KP.20230530.04043.50.fits ... 2023a_eng       0\n",
            "KP.20230530.04104.92.fits KP.20230530.04104.92.fits ... 2023a_eng       0\n",
            "KP.20230530.04166.11.fits KP.20230530.04166.11.fits ... 2023a_eng       0\n",
            "                      ...                       ... ...       ...     ...\n",
            "KP.20230530.77362.69.fits KP.20230530.77362.69.fits ... 2023a_eng       0\n",
            "KP.20230530.77454.80.fits KP.20230530.77454.80.fits ... 2023a_eng       0\n",
            "KP.20230530.77546.95.fits KP.20230530.77546.95.fits ... 2023a_eng       0\n",
            "KP.20230530.77638.99.fits KP.20230530.77638.99.fits ... 2023a_eng       0\n",
            "KP.20230530.77731.00.fits KP.20230530.77731.00.fits ... 2023a_eng       0\n",
            "KP.20230530.77823.34.fits KP.20230530.77823.34.fits ... 2023a_eng       0\n",
            "KP.20230530.77915.23.fits KP.20230530.77915.23.fits ... 2023a_eng       0\n",
            "KP.20230530.78007.31.fits KP.20230530.78007.31.fits ... 2023a_eng       0\n",
            "KP.20230530.78099.70.fits KP.20230530.78099.70.fits ... 2023a_eng       0\n",
            "KP.20230530.78191.85.fits KP.20230530.78191.85.fits ... 2023a_eng       0\n",
            "KP.20230530.78283.75.fits KP.20230530.78283.75.fits ... 2023a_eng       0\n",
            "Length = 231 rows\n"
          ]
        }
      ],
      "source": [
        "Koa.query_datetime ('kpf', \\\n",
        "    '2023-05-30 00:00:00/2023-05-30 23:59:59', \\\n",
        "    './output/kpf_daterange.tbl', overwrite=True, format='ipac', \\\n",
        "    cookiepath='./tapcookie.txt')\n",
        "\n",
        "rec = Table.read ('./output/kpf_daterange.tbl',format='ipac')\n",
        "print (rec)\n",
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KV5BDsU4Osxd"
      },
      "source": [
        "Once we have the query result, we can download files to the designated directory, in this case to dnload_dir_kpf/. If the download function is called several times, it will check the designated directory and only download new files."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KxRXJeruPLET",
        "outputId": "112415f5-4482-4689-8137-57605486ae49"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Start downloading 3 koaid data you requested;\n",
            "please check your outdir: dnload_dir_kpf for  progress ....\n",
            "\n",
            "A total of 3 new lev0 FITS files downloaded.\n"
          ]
        }
      ],
      "source": [
        "Koa.download ('./output/kpf_daterange.tbl',\n",
        "    'ipac', \\\n",
        "    'dnload_dir_kpf',\n",
        "#    start_row=1, \\\n",
        "#    end_row=3, \\\n",
        "    cookiepath='./tapcookie.txt')"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "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": "3.11.3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}