{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyaurorax\n",
    "import datetime\n",
    "import pprint\n",
    "\n",
    "aurorax = pyaurorax.PyAuroraX()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get availability for ephemeris data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start Date:       2019-01-01\n",
      "End Date:         2019-01-10\n",
      "Program:          swarm\n",
      "Platform:         swarma\n",
      "Instrument Type:  footprint\n"
     ]
    }
   ],
   "source": [
    "# set parameters\n",
    "start_date = datetime.datetime(2019, 1, 1)\n",
    "end_date = datetime.date(2019, 1, 10)\n",
    "program = \"swarm\"\n",
    "platform = \"swarma\"\n",
    "instrument_type = \"footprint\"\n",
    "print(\"%-18s%s\" % (\"Start Date:\", start_date.strftime(\"%Y-%m-%d\")))\n",
    "print(\"%-18s%s\" % (\"End Date:\", end_date.strftime(\"%Y-%m-%d\")))\n",
    "print(\"%-18s%s\" % (\"Program:\", program))\n",
    "print(\"%-18s%s\" % (\"Platform:\", platform))\n",
    "print(\"%-18s%s\" % (\"Instrument Type:\", instrument_type))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[AvailabilityResult(data_source=DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A', metadata=None, owner=None, maintainers=None, ephemeris_metadata_schema=None, data_product_metadata_schema=None, stats=None, format='basic_info'), available_data_products=None, available_ephemeris={'2019-01-01': 1440, '2019-01-02': 1440, '2019-01-03': 1440, '2019-01-04': 1440, '2019-01-05': 1440, '2019-01-06': 1440, '2019-01-07': 1440, '2019-01-08': 1440, '2019-01-09': 1440, '2019-01-10': 1440})]\n"
     ]
    }
   ],
   "source": [
    "# get availability\n",
    "availability = aurorax.search.availability.ephemeris(start_date,\n",
    "                                                     end_date,\n",
    "                                                     program=program,\n",
    "                                                     platform=platform,\n",
    "                                                     instrument_type=instrument_type,\n",
    "                                                     format=pyaurorax.search.FORMAT_BASIC_INFO)\n",
    "print(availability)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'available_data_products': None,\n",
      " 'available_ephemeris': {'2019-01-01': 1440,\n",
      "                         '2019-01-02': 1440,\n",
      "                         '2019-01-03': 1440,\n",
      "                         '2019-01-04': 1440,\n",
      "                         '2019-01-05': 1440,\n",
      "                         '2019-01-06': 1440,\n",
      "                         '2019-01-07': 1440,\n",
      "                         '2019-01-08': 1440,\n",
      "                         '2019-01-09': 1440,\n",
      "                         '2019-01-10': 1440},\n",
      " 'data_source': DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A', metadata=None, owner=None, maintainers=None, ephemeris_metadata_schema=None, data_product_metadata_schema=None, stats=None, format='basic_info')}\n"
     ]
    }
   ],
   "source": [
    "pprint.pprint(availability[0].__dict__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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