observation_upload.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "23f36510-9eca-4004-a553-363ac29108e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "patient_id = 40079\n",
    "study_id = 30017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ce72d503-b209-419e-a94c-61b199becd36",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'uuid': '0a5a5276-039d-4400-bd63-2f8413964032',\n",
       " 'schema_id': {'namespace': 'omh', 'name': 'blood-glucose', 'version': '4.0'},\n",
       " 'source_creation_date_time': '2025-10-29T20:16:53Z',\n",
       " 'modality': 'sensed',\n",
       " 'acquisition_rate': {'number_of_times': 1,\n",
       "  'time_window': {'value': 5, 'unit': 'min'}},\n",
       " 'external_datasheets': [{'datasheet_type': 'data source',\n",
       "   'datasheet_reference': 'https://www.libreview.com/'},\n",
       "  {'datasheet_type': 'measuring device',\n",
       "   'datasheet_reference': 'https://www.freestyle.abbott/us-en/products/freestyle-libre-3.html'}]}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import json\n",
    "\n",
    "with open(\"blood_glucose.json\") as f:\n",
    "    cgm_records = json.load(f)\n",
    "cgm_records[\"header\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "311b7613-0511-40ef-bc5e-de9baddb888a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'uuid': 'b27411f4-358b-44ed-8f0c-1b40a3120858',\n",
       " 'schema_id': {'namespace': 'ieee', 'name': 'food-entry', 'version': '0.1'},\n",
       " 'source_creation_date_time': '2025-10-29T20:16:53Z',\n",
       " 'modality': 'self-reported',\n",
       " 'external_datasheets': [{'datasheet_type': 'recording app',\n",
       "   'datasheet_reference': 'https://cronometer.com/index.html'}]}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open(\"food_entry.json\") as f:\n",
    "    food_entry = json.load(f)\n",
    "food_entry['header']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d9b94b69-03da-4cf9-8512-1500c72966a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'uuid': '1c4e7a5d-2c1e-4fae-a7fc-b497c7595e94',\n",
       " 'schema_id': {'namespace': 'ieee',\n",
       "  'name': 'sleep-stage-summary',\n",
       "  'version': '1.0'},\n",
       " 'source_creation_date_time': '2025-10-29T20:16:53Z',\n",
       " 'modality': 'sensed',\n",
       " 'external_datasheets': [{'datasheet_type': 'data aggregator',\n",
       "   'datasheet_reference': 'https://www.fitabase.com/media/2126/fitabase-fitbit-data-dictionary-as-of-05162025.pdf'},\n",
       "  {'datasheet_type': 'measuring device',\n",
       "   'datasheet_reference': 'https://store.google.com/us/product/fitbit_sense_2?hl=en-US&pli=1'},\n",
       "  {'datasheet_type': 'processing algorithm', 'datasheet_reference': ''},\n",
       "  {'datasheet_type': 'manufacturer',\n",
       "   'datasheet_reference': 'https://store.google.com/category/watches_trackers?hl=en-US'}]}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open(\"sleep_stage_summary.json\") as f:\n",
    "    sleep_stage = json.load(f)\n",
    "sleep_stage['header']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "772c9874-b7a5-4aae-96be-ecede9ecfbd5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'74bb39f0-5fa3-58c0-b88f-f96d03bf7513'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import uuid\n",
    "from datetime import UTC, datetime\n",
    "\n",
    "epoch = datetime(1900, 1, 1, tzinfo=UTC)\n",
    "ns_uuid = uuid.UUID('d15785047be14c68b5a21c30e8e15c91')\n",
    "ns_uuid\n",
    "def uuid_for_reading(reading):\n",
    "    # dt = datetime.fromisoformat(reading['effective_time_frame']['date_time'])\n",
    "    # clock_seq = int((dt - epoch).total_seconds())\n",
    "    return str(uuid.uuid5(ns_uuid, json.dumps(reading)))\n",
    "\n",
    "uuid_for_reading(cgm_records[\"body\"][2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "72839c14-4d70-4444-a03a-6d34a5645d5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from jupyterhealth_client import JupyterHealthClient\n",
    "\n",
    "jhc = JupyterHealthClient()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "249283f2-b7a9-4c6b-b95b-48dcafdf1162",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'studyScopeConsents': [{'id': 94,\n",
       "   'studyPatient': {'id': 78, 'study': 30017, 'patient': 40079},\n",
       "   'scopeCode': {'id': 50001,\n",
       "    'codingSystem': 'https://w3id.org/openmhealth',\n",
       "    'codingCode': 'omh:blood-glucose:4.0',\n",
       "    'text': 'Blood glucose'},\n",
       "   'consented': True,\n",
       "   'consentedTime': '2025-10-31T04:40:58.012671Z'},\n",
       "  {'id': 95,\n",
       "   'studyPatient': {'id': 78, 'study': 30017, 'patient': 40079},\n",
       "   'scopeCode': {'id': 50006,\n",
       "    'codingSystem': 'https://w3id.org/openmhealth',\n",
       "    'codingCode': 'ieee:sleep-stage-summary:1.0',\n",
       "    'text': 'Sleep Stage Summary'},\n",
       "   'consented': True,\n",
       "   'consentedTime': '2025-10-31T04:40:58.012671Z'},\n",
       "  {'id': 96,\n",
       "   'studyPatient': {'id': 78, 'study': 30017, 'patient': 40079},\n",
       "   'scopeCode': {'id': 50007,\n",
       "    'codingSystem': 'https://w3id.org/openmhealth',\n",
       "    'codingCode': 'ieee:food-entry:0.1',\n",
       "    'text': 'Food Entry'},\n",
       "   'consented': True,\n",
       "   'consentedTime': '2025-10-31T04:40:58.012671Z'}]}"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jhc._api_request(\n",
    "    f\"patients/{patient_id}/consents\",\n",
    "    method=\"POST\",\n",
    "    json={\n",
    "        \"studyScopeConsents\": [\n",
    "            {\n",
    "                \"studyId\": study_id,\n",
    "                \"scopeConsents\": [\n",
    "                    {\n",
    "                        \"codingSystem\": \"https://w3id.org/openmhealth\",\n",
    "                        \"codingCode\": \"omh:blood-glucose:4.0\",\n",
    "                        \"consented\": True,\n",
    "                    },\n",
    "                    {\n",
    "                        \"codingSystem\": \"https://w3id.org/openmhealth\",\n",
    "                        \"codingCode\": \"ieee:sleep-stage-summary:1.0\",\n",
    "                        \"consented\": True,\n",
    "                    },\n",
    "                    {\n",
    "                        \"codingSystem\": \"https://w3id.org/openmhealth\",\n",
    "                        \"codingCode\": \"ieee:food-entry:0.1\",\n",
    "                        \"consented\": True,\n",
    "                    },\n",
    "                ],\n",
    "            }\n",
    "        ]\n",
    "    },\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c7fc40b9-1b56-4ed1-8872-b14c066461ab",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import base64\n",
    "import json\n",
    "from tqdm.notebook import tqdm\n",
    "\n",
    "\n",
    "def upload_records(header, readings, device_id, patient_id, chunk_size=100):\n",
    "    schema_id = header['schema_id']\n",
    "    coding = [\n",
    "        {\"system\": \"https://w3id.org/openmhealth\",\n",
    "        \"code\": f\"{schema_id['namespace']}:{schema_id['name']}:{schema_id['version']}\",\n",
    "        }\n",
    "     ]\n",
    "\n",
    "    for i in tqdm(range(0, len(readings), chunk_size)):\n",
    "        readings_chunk = readings[i:i + chunk_size]\n",
    "        entries = []\n",
    "        for reading in readings[i:i + chunk_size]:\n",
    "\n",
    "            reading_header = header.copy()\n",
    "            reading_header['uuid'] = uuid_for_reading(reading)\n",
    "            # reading_header['source_creation_date_time'] = reading['effective_time_frame']['date_time']\n",
    "            record = dict(\n",
    "                header=reading_header,\n",
    "                body=reading,\n",
    "            )\n",
    "            entry =                 {\n",
    "                    \"resource\": {\n",
    "                        \"resourceType\": \"Observation\",\n",
    "                        \"status\": \"final\",\n",
    "                        \"code\": {\n",
    "                            \"coding\": coding,\n",
    "                        },\n",
    "                        \"subject\": {\"reference\": f\"Patient/{patient_id}\"},\n",
    "                        \"device\": {\"reference\": f\"Device/{device_id}\"},\n",
    "                        \"valueAttachment\": {\n",
    "                            \"contentType\": \"application/json\",\n",
    "                            \"data\": base64.b64encode(json.dumps(record).encode()).decode(),\n",
    "                        },\n",
    "                    },\n",
    "                    \"request\": {\"method\": \"POST\", \"url\": \"Observation\"},\n",
    "                }\n",
    "            entries.append(entry)\n",
    "\n",
    "        request_payload = {\n",
    "            \"resourceType\": \"Bundle\",\n",
    "            \"type\": \"batch\",\n",
    "            \"entry\": entries,\n",
    "        }\n",
    "\n",
    "        r = jhc._api_request(\"\", method=\"POST\", fhir=True, json=request_payload)\n",
    "        for entry in r['entry']:\n",
    "            if 'outcome' in entry['response']:\n",
    "                for issue in entry['response']['outcome']['issue']:\n",
    "                    print(issue['diagnostics'])\n",
    "                raise ValueError(\"error!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "f42921dc-5b53-406c-a482-066c0de335e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "59be4e96e4174f93a6df68462fc9aba7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/41 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "upload_records(cgm_records[\"header\"], cgm_records[\"body\"], patient_id=patient_id, device_id=70005)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "6b633416-35cf-46a6-9006-3025e90fbb9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "456a9849bc274987a497a8860335b73c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "upload_records(food_entry['header'], food_entry['body'], patient_id=patient_id, device_id=70003)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "2e682bcf-825f-4b19-a5e8-04e59b3f9208",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "abc6569b3e3d41cf883b3b3136c639b6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "upload_records(sleep_stage['header'], sleep_stage['body'], patient_id=patient_id, device_id=70004)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6bccdad2-a12f-4b00-aef1-d62438834fcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from jupyterhealth_client import Code, JupyterHealthClient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8af976ce-e68a-4b17-a11e-53056d6a1658",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Code.SLEEP_STAGE_SUMMARY: 'ieee:sleep-stage-summary:1.0'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Code.SLEEP_STAGE_SUMMARY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cbeaa140-47c0-4746-9a54-7065f3b210ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4018"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = jhc.list_observations_df(patient_id=patient_id, study_id=study_id, code=Code.BLOOD_GLUCOSE.value, limit=10_000)\n",
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ddd2f1ca-43cf-468f-b764-75d07e4d08a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = jhc.list_observations_df(patient_id=patient_id, study_id=study_id, code=Code.FOOD_ENTRY.value)\n",
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "40ed59b0-d9a8-4d2d-834d-ca51c95200bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = jhc.list_observations_df(patient_id=patient_id, study_id=study_id, code=Code.SLEEP_STAGE_SUMMARY.value)\n",
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "79a77c74-ecdd-4771-8bcb-739ab9e1bcc5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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    "name": "ipython",
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   "file_extension": ".py",
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