Merge pull request #7 from LisaLeib/cogsrch-py-sample-update-1

added indexer status script to notebook and sentence to readme

Author: HeidiSteen

README.md

@@ -21,4 +21,4 @@ This sample is a .ipynb file containing a Python3 notebook used in [Quickstart:
 
 This sample is a .ipynb file containing a Python3 notebook used in [Tutorial: Python Tutorial: Call Cognitive Services APIs in an Azure Search indexing pipeline](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-blob-python). There are three placeholder values to insert: an Azure Search service, an admin API key, and a connection string to a blob storage resource that you will create in the tutorial. Replace them with valid values to create an indexing pipeline that searches for and extracts text and text representations of images and scanned documents. This sample leverages cognitive skills from the Azure Cognitive Services API, such as entity recognition and language detection.
 
-Run the steps individually and make sure the printed response status or response output appears before continuing to the next step. The step that creates the indexer, in particular, may take a few minutes to complete.
+Run the steps individually and make sure the printed response status or response output appears before continuing to the next step. The step that creates the indexer, in particular, may take a few minutes to complete. See the tutorial for more details.

Tutorial-AI-Enrichment-Jupyter-Notebook/PythonTutorial-AzureSearch-AIEnrichment.ipynb

@@ -261,6 +261,17 @@
     "print(r.status_code)\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Get indexer status\n",
+    "r = requests.get(endpoint + \"/indexers/\" + indexer_name + \"/status\", headers=headers,params=params)\n",
+    "pprint(json.dumps(r.json(), indent=1))"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -284,13 +295,6 @@
     "r = requests.get(endpoint + \"/indexes/\" + index_name + \"/docs?&search=*&$select=organizations\", headers=headers, params=params)\n",
     "pprint(r.json())"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {