remove references to extension; swap it with emulator (#5)

* remove references to extension; swap it with emulator

* Update credit-scoring-with-snowpark/README.md

Co-authored-by: Waldemar Hummer <[email protected]>

---------

Co-authored-by: Waldemar Hummer <[email protected]>

Author: HarshCasper

credit-scoring-with-snowpark/README.md

@@ -1,23 +1,23 @@
 # Credit Scoring with Snowpark & LocalStack
 
-This notebook demonstrates how to use Snowpark for Python to perform exploratory data analysis (EDA) on a credit scoring dataset. This notebook uses LocalStack's Snowflake extension to emulate Snowflake APIs locally.
+This notebook demonstrates how to use Snowpark for Python to perform exploratory data analysis (EDA) on a credit scoring dataset. This notebook uses LocalStack's Snowflake emulator to run Snowflake data pipelines locally.
 
 ## Prerequisites
 
-- [LocalStack](https://localstack.cloud/) with `LOCALSTACK_AUTH_TOKEN` environment variable set
-- [LocalStack Snowflake extension](https://discuss.localstack.cloud/t/introducing-the-localstack-snowflake-extension-experimental/665)
+- [`localstack` CLI](https://docs.localstack.cloud/getting-started/installation/#localstack-cli) with [`LOCALSTACK_AUTH_TOKEN`](https://docs.localstack.cloud/getting-started/auth-token/) environment variable set
+- [LocalStack Snowflake emulator](https://snowflake.localstack.cloud/getting-started/installation/)
 - [Snowpark for Python](https://docs.snowflake.com/en/developer-guide/snowpark/python/index)
 - [Jupyter Notebook](https://jupyter.org/)
 
 ## Running the notebook
 
-Start the LocalStack container using your preferred method. Ensure that you have access to LocalStack's Snowflake extension. Start a Jupyter Notebook server and open the notebook in your browser.
+Start the LocalStack container using your preferred method. Ensure that you have access to LocalStack's Snowflake emulator. Start a Jupyter Notebook server and open the notebook in your browser.
 
 ```bash
 jupyter notebook
 ```
 
-Open the `credit-scoring-eda.ipynb` notebook and run the cells to see the results. Follow the instructions in the notebook to install the required packages and set up the Snowflake extension.
+Open the `credit-scoring-eda.ipynb` notebook and run the cells to see the results. Follow the instructions in the notebook to install the required packages and set up the Snowflake emulator.
 
 ## License
 

credit-scoring-with-snowpark/credit-scoring-eda.ipynb

@@ -7,7 +7,7 @@
    "source": [
     "# Credit Scoring with Snowpark & LocalStack\n",
     "\n",
-    "In this notebook, we will explore how you can use LocalStack's Snowflake emulator extension, to develop and test your Snowflake data pipelines entirely on your local machine! In this notebook, we will showcase how you can use LocalStack's Snowflake with Snowpark for Python and your favorite Python libraries for data analysis!"
+    "In this notebook, we will explore how you can use LocalStack's Snowflake emulator, to develop and test your Snowflake data pipelines entirely on your local machine! In this notebook, we will showcase how you can use LocalStack's Snowflake with Snowpark for Python and your favorite Python libraries for data analysis!"
    ]
   },
   {

lambda-snowpark-connector/Makefile

@@ -28,7 +28,7 @@ local-invoke:   ## Invoke the Lambda locally
 	--payload '{"body": "test" }' output.txt
 
 start-localstack:
-	DOCKER_FLAGS="-e DEBUG=1 -e SF_LOG=trace" LAMBDA_RUNTIME_ENVIRONMENT_TIMEOUT=180 localstack start -d
+	DOCKER_FLAGS="-e DEBUG=1 -e SF_LOG=trace" LAMBDA_RUNTIME_ENVIRONMENT_TIMEOUT=180 IMAGE_NAME=localstack/snowflake:latest localstack start -d
 
 ready:         ## Check if the LocalStack container is up and running.
 	localstack wait -t 20 && echo "LocalStack is ready to use!"

lambda-snowpark-connector/README.md

@@ -10,8 +10,8 @@ This example demonstrates how to connect Snowpark to AWS Lambda locally using Lo
 ## Prerequisites
 
 - Python 3.10 installed locally
-- [LocalStack](https://localstack.cloud/) with `LOCALSTACK_AUTH_TOKEN` environment variable set
-- [LocalStack Snowflake extension](https://discuss.localstack.cloud/t/introducing-the-localstack-snowflake-extension-experimental/665)
+- [`localstack` CLI](https://docs.localstack.cloud/getting-started/installation/#localstack-cli) with [`LOCALSTACK_AUTH_TOKEN`](https://docs.localstack.cloud/getting-started/auth-token/) environment variable set
+- [LocalStack Snowflake emulator](https://snowflake.localstack.cloud/getting-started/installation/)
 
 ## Instructions
 
@@ -25,7 +25,7 @@ make install
 
 ### Start the LocalStack container
 
-Start LocalStack after installing the Snowflake extension:
+Start LocalStack:
 
 ```bash
 make start-localstack

predicting-customer-spend/README.md

@@ -2,11 +2,11 @@
 
 An E-Commerce company aims to apply machine learning for understanding customer engagement with its digital platforms (website and app). The goal is to determine whether to prioritize improving the mobile app or website. Using a Linear Regression model, we will assess the impact of user activity on the likelihood of increased spending.
 
-In this sample notebook, we will explore how you can use LocalStack's Snowflake emulator extension, to develop and test your Snowflake data pipelines entirely on your local machine! In this notebook, we will showcase how you can use LocalStack's Snowflake with Snowpark for Python and your favorite Python libraries for data analysis and machine learning.
+In this sample notebook, we will explore how you can use LocalStack's Snowflake emulator to develop and test your Snowflake data pipelines entirely on your local machine! In this notebook, we will showcase how you can use LocalStack's Snowflake with Snowpark for Python and your favorite Python libraries for data analysis and machine learning.
 
 ## Prerequisites
 
--   [LocalStack](https://localstack.cloud/)  with  `LOCALSTACK_AUTH_TOKEN`  environment variable set
+- [`localstack` CLI](https://docs.localstack.cloud/getting-started/installation/#localstack-cli) with [`LOCALSTACK_AUTH_TOKEN`](https://docs.localstack.cloud/getting-started/auth-token/) environment variable set
 -   [LocalStack Snowflake emulator](https://snowflake.localstack.cloud/getting-started/installation/)
 -   [Snowpark for Python](https://docs.snowflake.com/en/developer-guide/snowpark/python/index)
 -   [Jupyter Notebook](https://jupyter.org/)
@@ -19,7 +19,7 @@ Start the [LocalStack Snowflake emulator](https://snowflake.localstack.cloud/get
 jupyter notebook
 ```
 
-Open the `linear-regression-model.ipynb` notebook and run the cells to see the results. Follow the instructions in the notebook to install the required packages and set up the Snowflake extension.
+Open the `linear-regression-model.ipynb` notebook and run the cells to see the results. Follow the instructions in the notebook to install the required packages and set up the Snowflake emulator.
 
 ## License
 

predicting-customer-spend/linear-regression-model.ipynb

@@ -9,7 +9,7 @@
     "\n",
     "An E-Commerce company aims to apply machine learning for understanding customer engagement with its digital platforms (website and app). The goal is to determine whether to prioritize improving the mobile app or website. Using a Linear Regression model, we will assess the impact of user activity on the likelihood of increased spending.\n",
     "\n",
-    "In this notebook, we will explore how you can use LocalStack's Snowflake emulator extension, to develop and test your Snowflake data pipelines entirely on your local machine! In this notebook, we will showcase how you can use LocalStack's Snowflake with Snowpark for Python and your favorite Python libraries for data analysis and machine learning."
+    "In this notebook, we will explore how you can use LocalStack's Snowflake emulator to develop and test your Snowflake data pipelines entirely on your local machine! In this notebook, we will showcase how you can use LocalStack's Snowflake with Snowpark for Python and your favorite Python libraries for data analysis and machine learning."
    ]
   },
   {