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sfc-gh-vsekar/spcs_api_connect_with_snowpark_session.ipynb

Last active October 28, 2024 13:59
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Connect to API end point hosted in Snowpark Containers (SPCS) using Snowpark
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spcs_api_connect_with_snowpark_session.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Connect to API service endpoint, hosted in Snowpark Containers using Snowpark\n",
"\n",
"**Dated: Jan-2024**\n",
"\n",
"\n",
"This notebook demonstrates the gist of connecting to a REST API, hosted in Snowpark Container Services (SPCS). This demonstation\n",
"uses Snowpark (Python), but I am sure the approach would for Java / Scala implementations also."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Establish a Snowpark session\n",
"\n",
"from snowflake.snowpark.session import Session\n",
"\n",
"# Establish a Snowpark session\n",
"snowflake_connection_info = {\n",
" \"url\": \"https://<account locator>.snowflakecomputing.com\"\n",
" ,\"account\": \"<account locator>\"\n",
" ,\"account_name\": \"<account identifier>, do not include the organization name\"\n",
" ,\"organization\": \"<account org name>\"\n",
" ,\"user\": \"XXXX\"\n",
" ,\"password\": \"XXXX\"\n",
"}\n",
"\n",
"# I am establishing 2 snowpark sessions. \n",
"# One for DML processing with Snowflake and Another for interacting with the API.\n",
"sp_session = Session.builder.configs(snowflake_connection_info).create()\n",
"\n",
"# Another for interacting with the API.\n",
"api_sp_session = Session.builder.configs(snowflake_connection_info).create()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To access the API, the program would need to login into Snowflake. For this we need to get the JWT session token."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Get JWT Token\n",
"\n",
"api_sp_session.sql(f\"alter session set python_connector_query_result_format = json;\").collect()\n",
"\n",
"# Get the session token, which will be used for API calls for authentication\n",
"sptoken_data = api_sp_session.connection._rest._token_request('ISSUE')\n",
"api_session_token = sptoken_data['data']['sessionToken']\n",
"\n",
"# craft the request to ingress endpoint with authz\n",
"api_headers = {'Authorization': f'''Snowflake Token=\"{api_session_token}\"'''}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next we fetch the public URL, where the api endpoint is accessible for the service. We can retreive this using the command:\n",
"[SHOW ENDPOINTS](https://docs.snowflake.com/en/sql-reference/sql/show-endpoints)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Retreive the API end point for the SPCS \n",
"\n",
"spcs_service_name = '<your snowpark service name>'\n",
"spdf = sp_session.sql(f'''show endpoints in service {spcs_service_name} ''')\n",
"spdf.show()\n",
"\n",
"# Retreive the URL, mapped to the endpoint in the SPCS specifical file URL\n",
"# Ref: https://docs.snowflake.com/en/developer-guide/snowpark-container-services/specification-reference#spec-endpoints-field-optional\n",
"\n",
"# In this example, my endpoint is mapped to 'api'\n",
"spcs_endpoint = 'api'\n",
"df = spdf.filter(f''' \"name\" = '{spcs_endpoint}' ''').to_pandas()\n",
"api_base_url = df['ingress_url'].iloc[0]\n",
"api_base_url = f'http://{api_base_url}'\n",
"print(f'API Base url: {api_base_url}')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next we are ready to make a call with the API.\n",
"\n",
"#### API using GET method"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Interact with the API end point\n",
"\n",
"import json\n",
"import requests\n",
"\n",
"print(f'Requesting to {api_base_url} ... \\n ')\n",
"response = requests.get(f'{api_base_url}/', headers = api_headers)\n",
"print(response.status_code)\n",
"print(response.text)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### API using POST method"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"params_data = {\n",
" 'first_name' : 'john'\n",
" ,'last_name' : 'doe'\n",
" ,'email' : '[email protected]'\n",
"}\n",
"\n",
"# Added content to existing api_header\n",
"api_headers['Content-Type'] = 'application/json'\n",
"r = requests.get(llm_codegen_url, params = params_data, headers = api_headers)\n",
"print(f'Status : {r.status_code}')\n",
"print(f'Body: \\n')\n",
"print(r.json())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "venkat_env",
"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": "3.9.18"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
@emanueol
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emanueol commented Oct 28, 2024

Hi, what is it and one setups that "ISSUE" in:

sptoken_data = api_sp_session.connection._rest._token_request('ISSUE') ?

Thanks~

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