ValueSets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "insured-cross",
   "metadata": {},
   "outputs": [],
   "source": [
    "import getpass\n",
    "import pandas as pd\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dutch-delight",
   "metadata": {},
   "outputs": [],
   "source": [
    "username=input(\"NTS username: \")\n",
    "password = getpass.getpass(\"NTS password: \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "progressive-excitement",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://terminologieserver.nl/auth/realms/nictiz/protocol/openid-connect/token\"\n",
    "\n",
    "payload='username='+username+'&password='+password+'&grant_type=password&client_id=cli_client'\n",
    "headers = { 'Content-Type': 'application/x-www-form-urlencoded' }\n",
    "\n",
    "response = requests.request(\"POST\", url, headers=headers, data=payload)\n",
    "\n",
    "token = response.json()\n",
    "access_token = token[\"access_token\"]\n",
    "\n",
    "#print(access_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "burning-munich",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://terminologieserver.nl/fhir/ValueSet/$expand?url=http://snomed.info/sct?fhir_vs=refset\"\n",
    "\n",
    "payload={}\n",
    "headers = { 'Authorization': 'Bearer ' + access_token }\n",
    "\n",
    "response = requests.request(\"GET\", url, headers=headers, data=payload)\n",
    "\n",
    "#print(response.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "developmental-interference",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = response.json()\n",
    "\n",
    "for entry in data[\"expansion\"][\"contains\"]:\n",
    "    print(entry)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "facial-denver",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data[\"expansion\"][\"contains\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "significant-muscle",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[['code', 'display']]\n",
    "df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "broke-treasure",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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