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Merge pull request #2 from Snowflake-Labs/initial-release-branch
Initial release branch
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‎SiS Deployment/deploy_app.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Deploy App to Snowflake"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from snowflake.snowpark import Session\n",
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"from string import Template\n",
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"import json"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Connect to Snowflake"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can create a session however you like. Here are two possible options. "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"OPTION 1 - Using builder.getOrCreate() to access an existing toml file\n",
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"- https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-connect#connecting-using-the-connections-toml-file"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"session = Session.builder.getOrCreate()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"OPTION 2 - Using connection params inside builder.configs().create() "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# connection_params = dict(\n",
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"# user=\"\",\n",
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"# role=\"\",\n",
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"# password=\"\",\n",
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"# account=\"\",\n",
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"# )\n",
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"\n",
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"# session = Session.builder.configs(connection_params).create()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Establish metadata\n",
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"\n",
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"NOTE: In the metadata dict below, you can change any of the key:value pairs EXCEPT main_file=\"automl_app.py\"."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"metadata = dict(\n",
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" database_name=\"ML_SIDEKICK\",\n",
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" schema_name=\"ST_APPS\",\n",
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" stage_name=\"APP_STG\",\n",
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" app_name=\"ML_SIDEKICK\",\n",
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" main_file=\"automl_app.py\", # DO NOT CHANGE\n",
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" query_warehouse=\"COMPUTE_WH\", # CHANGE TO AN EXISTING WAREHOUSE\n",
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")\n",
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"with open(\"deployment_structure.json\", \"r\") as config:\n",
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" upload_metadata = json.loads(config.read())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Templates"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"create_db = Template(\"CREATE DATABASE IF NOT EXISTS $db\")\n",
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"create_schema = Template(\"CREATE SCHEMA IF NOT EXISTS $db.$schema\")\n",
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"create_stage = Template(\n",
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" \"\"\"\n",
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"CREATE STAGE IF NOT EXISTS $db.$schema.$stage\n",
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"DIRECTORY=(ENABLE=TRUE);\n",
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"\"\"\"\n",
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")\n",
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"create_streamlit = Template(\n",
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" \"\"\"CREATE STREAMLIT IF NOT EXISTS $db.$schema.$app_name\n",
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" ROOT_LOCATION = '@$db.$schema.$stage'\n",
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" MAIN_FILE = '$main_file'\n",
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" QUERY_WAREHOUSE = $wh\n",
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" COMMENT = '{\"origin\":\"sf_sit\", \"name\":\"ml_sidekick\", \"version\":{\"major\":1, \"minor\":0}, \"attributes\":{\"component\":\"sis_app\"}}'\n",
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" \"\"\"\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"##### Populate Templates"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"db_query = create_db.substitute(db=metadata.get(\"database_name\"))\n",
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"\n",
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"schema_qry = create_schema.substitute(\n",
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" db=metadata.get(\"database_name\"), schema=metadata.get(\"schema_name\")\n",
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")\n",
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"\n",
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"stage_qry = create_stage.substitute(\n",
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" db=metadata.get(\"database_name\"),\n",
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" schema=metadata.get(\"schema_name\"),\n",
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" stage=metadata.get(\"stage_name\"),\n",
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")\n",
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"\n",
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"app_create_qry = create_streamlit.substitute(\n",
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" app_name=metadata.get(\"app_name\"),\n",
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" db=metadata.get(\"database_name\"),\n",
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" schema=metadata.get(\"schema_name\"),\n",
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" stage=metadata.get(\"stage_name\"),\n",
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" main_file=metadata.get(\"main_file\"),\n",
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" wh=metadata.get(\"query_warehouse\"),\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Row(status='AUTO_ML already exists, statement succeeded.')]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"session.sql(db_query).collect()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Row(status='ST_APPS already exists, statement succeeded.')]"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"session.sql(schema_qry).collect()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Row(status='APP_STG already exists, statement succeeded.')]"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"session.sql(stage_qry).collect()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Upload project files"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"db = metadata.get(\"database_name\")\n",
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"schema = metadata.get(\"schema_name\")\n",
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"stage = metadata.get(\"stage_name\")\n",
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"for i in upload_metadata.get(\"files\"):\n",
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" for file in i.get(\"files\"):\n",
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" path = \"\" if i.get(\"parent\") == \"root\" else i.get(\"parent\")\n",
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" session.file.put(\n",
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" local_file_name=file,\n",
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" stage_location=f\"@{db}.{schema}.{stage}/{path}\",\n",
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" auto_compress=False,\n",
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" overwrite=True,\n",
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" )"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Finally, Create the app"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Row(status='Streamlit STREAMLIT_AUTO_ML successfully created.')]"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"session.sql(app_create_qry).collect()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "streamlit-automl",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎SiS Deployment/deployment_structure.json‎

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{
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"files": [
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{
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"parent": "root",
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"files": [
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"../streamlit_automl/automl_app.py",
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"../streamlit_automl/callbacks.py",
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"../streamlit_automl/cli.py",
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"../streamlit_automl/code_exporter.py",
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"../streamlit_automl/common.py",
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"../streamlit_automl/histograms.py",
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"../streamlit_automl/ml_modeling.py",
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"../streamlit_automl/ml_ops.py",
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"../streamlit_automl/model_metrics.py",
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"../streamlit_automl/preprocessing.py",
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"../streamlit_automl/utils.py",
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"../streamlit_automl/environment.yml"
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]
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},
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{
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"parent": "styles",
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"files": [
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"../streamlit_automl/styles/css_bootstrap.html"
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]
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},
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{
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"parent": "resources",
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"files": [
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"../streamlit_automl/resources/background.png",
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"../streamlit_automl/resources/db.svg",
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"../streamlit_automl/resources/glaciers_back.png",
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"../streamlit_automl/resources/loader.gif",
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"../streamlit_automl/resources/Snowflake_ICON_Alert.png",
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"../streamlit_automl/resources/Snowflake_ICON_Chat.png",
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"../streamlit_automl/resources/Snowflake_ICON_Check.png"
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]
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}
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]
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}

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