finish tutorials

Author: HarshCasper

public/images/snowflake/credit_df_cat.png

@@ -28,10 +28,10 @@ The code in this tutorial is available on [GitHub](https://github.com/localstack
 
 Create a new directory for your lambda function and navigate to it:
 
-{{< command >}}
-$ mkdir -p lambda-snowpark
-$ cd lambda-snowpark
-{{< / command >}}
+```bash
+mkdir -p lambda-snowpark
+cd lambda-snowpark
+```
 
 Create a new file named `handler.py` and add the following code:
 
@@ -112,61 +112,61 @@ You can now install the dependencies for your Lambda function. These include:
 
 Run the following command:
 
-{{< command >}}
-$ pip3 install \
+```bash
+pip3 install \
 		--platform manylinux2010_x86_64 \
 		--implementation cp \
 		--only-binary=:all: --upgrade \
 		--target ./libs \
  		snowflake-connector-python==2.7.9 boto3==1.26.153 botocore==1.29.153
-{{< / command >}}
+```
 
 ## Package the Lambda function
 
 Package the Lambda function and its dependencies into a ZIP file. Run the following command:
 
-{{< command >}}
-$ mkdir -p build
-$ cp -r libs/* build/
-$ (cd build && zip -q -r function-py.zip .)
-{{< / command >}}
+```bash
+mkdir -p build
+cp -r libs/* build/
+(cd build && zip -q -r function-py.zip .)
+```
 
 You have now created a ZIP file named `function-py.zip` that contains the Lambda function and its dependencies.
 
 ## Start the LocalStack container
 
 Start your LocalStack container in your preferred terminal/shell.
 
-{{< command >}}
-$ export LOCALSTACK_AUTH_TOKEN=<your_auth_token>
-$ DEBUG=1 \
+```bash
+export LOCALSTACK_AUTH_TOKEN=<your_auth_token>
+DEBUG=1 \
   LAMBDA_RUNTIME_ENVIRONMENT_TIMEOUT=180 \
   IMAGE_NAME=localstack/snowflake \
   localstack start
-{{< / command >}}
+```
 
 > The `DEBUG=1` environment variable is set to enable debug logs. It would allow you to see the SQL queries executed by the Lambda function. The `LAMBDA_RUNTIME_ENVIRONMENT_TIMEOUT` environment variable is set to increase the Lambda function's timeout to 180 seconds.
 
 ## Deploy the Lambda function
 
 You can now deploy the Lambda function to LocalStack using the `awslocal` CLI. Run the following command:
 
-{{< command >}}
-$ awslocal lambda create-function \
+```bash
+awslocal lambda create-function \
     --function-name localstack-snowflake-lambda-example \
 	--runtime python3.10 \
 	--timeout 180 \
 	--zip-file fileb://build/function-py.zip \
 	--handler handler.lambda_handler \
 	--role arn:aws:iam::000000000000:role/lambda-role
-{{< / command >}}
+```
 
 After successfully deploying the Lambda function, you will receive a response with the details of the function. You can now invoke the function using the `awslocal` CLI:
 
-{{< command >}}
-$ awslocal lambda invoke --function-name localstack-snowflake-lambda-example \
+```bash
+awslocal lambda invoke --function-name localstack-snowflake-lambda-example \
 	--payload '{"body": "test" }' output.txt
-{{< / command >}}
+```
 
 You will receive a response with the details of the invocation. You can view the output in the `output.txt` file. To see the SQL queries executed by the Lambda function, check the logs by navigating to LocalStack logs (`localstack logs`).
 

public/images/snowflake/credit_df_hist.png

@@ -25,10 +25,10 @@ You should also download [`credit_files.csv`](https://github.com/localstack-samp
 
 Start your LocalStack container in your preferred terminal/shell.
 
-{{< command >}}
-$ export LOCALSTACK_AUTH_TOKEN=<your_auth_token>
-$ IMAGE_NAME=localstack/snowflake localstack start
-{{< / command >}}
+```bash
+export LOCALSTACK_AUTH_TOKEN=<your_auth_token>
+IMAGE_NAME=localstack/snowflake localstack start
+```
 
 ## Create a Snowpark session
 
@@ -126,7 +126,7 @@ credit_df.toPandas().hist(figsize=(15,15))
 The following output is displayed:
 <br><br>
 
-<img src="credit_df_hist.png" alt="credit_df_hist" width="700"/>
+![credit_df_hist](/images/snowflake/credit_df_hist.png)
 <br><br>
 
 You can also visualize the categorical features of the `credit_df` table:
@@ -155,8 +155,8 @@ plt.show()
 The following output is displayed:
 <br><br>
 
-<img src="credit_df_cat.png" alt="credit_df_cat" width="700"/>
+![credit_df_cat](/images/snowflake/credit_df_cat.png)
 
 ## Conclusion
 
-You can now perform further experimentations with the Snowflake emulator. For example, you can use the Snowpark API to run queries to get various insights, such as determining the range of loans per different category.
+You can now perform further experimentations with the Snowflake emulator. For example, you can use the Snowpark API to run queries to get various insights, such as determining the range of loans per different category.