Create notebook to upload test data to dataland

notebooks/provide_test_data.ipynb

@@ -0,0 +1,88 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "document_id='4abdfd0764559831fdd2e972abab0f34bc7300c650f6f789beea10ecb7d20251'\n",
+      "[CompanyIdAndName(company_name='E.ON SE', company_id='8863987f-df05-452f-8067-11f72e771345')]\n"
+     ]
+    }
+   ],
+   "source": [
+    "%run base.ipynb\n",
+    "import json\n",
+    "from pathlib import Path\n",
+    "\n",
+    "from dataland_qa_lab.utils import config\n",
+    "\n",
+    "pdf_path = Path(\"../data/pdfs/\")\n",
+    "json_path = Path(\"../data/jsons/\")\n",
+    "\n",
+    "conf = config.get_config()\n",
+    "dataland_client = conf.dataland_client\n",
+    "\n",
+    "dataset = dataland_client.company_api.get_companies_by_search_string(search_string=\"E.ON SE\", result_limit=1)\n",
+    "\n",
+    "# upload pdf file to dataland\n",
+    "if not dataland_client.documents_api.get_document(\n",
+    "    document_id=\"4abdfd0764559831fdd2e972abab0f34bc7300c650f6f789beea10ecb7d20251\"):\n",
+    "\n",
+    "    pdf_file_path = pdf_path / \"eon.pdf\"\n",
+    "    pdf_content = pdf_file_path.read_bytes()\n",
+    "\n",
+    "    print(dataland_client.documents_api.post_document(document=pdf_content))\n",
+    "\n",
+    "# change companyID in json file\n",
+    "company_id = dataset[0].company_id\n",
+    "\n",
+    "json_file_path = json_path / \"eon.json\"\n",
+    "with json_file_path.open(encoding=\"utf-8\") as f:\n",
+    "    json_data = json.load(f)\n",
+    "\n",
+    "json_data[\"companyID\"] = company_id\n",
+    "\n",
+    "with json_file_path.open(\"w\", encoding=\"utf-8\") as f:\n",
+    "    json.dump(json_data, f, indent=4)\n",
+    "\n",
+    "# upload data to dataland\n",
+    "response = dataland_client.nuclear_and_gas_api.post_data(\n",
+    "    data=json_data\n",
+    ")\n",
+    "\n",
+    "print(dataset)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.13.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}