#19: move slc notebook to repo ai lab

doc/changes/changes_2.1.0.md

@@ -16,6 +16,7 @@ Version: 2.1.0
 
 * 277 Added the SaaS database parameters to the configuration page.
 * 279 Made the notebooks tests running in SaaS as well as in the Docker-DB.
+* 19 Added SLC notebook
 
 ## Security
 

doc/developer_guide/testing.md

@@ -1,51 +1,82 @@
-### Tests
+# Tests
 
-XAL comes with a number of tests in directory `test`.
-Besides, unit and integrations tests in the respective directories
-there are tests in directory `codebuild`, see [Executing AWS CodeBuild](ci.md#executing-aws-codebuild).
+XAIL comes with a number of tests in the directory `test`. Besides, unit and integration tests in the respective directories, there are tests in the directory `codebuild`, see [Executing AWS CodeBuild](ci.md#executing-aws-codebuild).
 
-# Speeding up Docker-based Tests
+## Speeding up Docker-based Tests
 
-Creating a docker image is quite time-consuming, currently around 7 minutes. In order to use an existing
-docker image in the tests in `integration/test_create_dss_docker_image.py`
-simply add CLI option `--dss-docker-image` when calling `pytest`:
+Creating a docker image is quite time-consuming, currently around 7 minutes.
+
+To get test results faster, you can use an existing Docker image. You can create such an image using the [CLI command](commands.md#release-commands) `create-docker-image` or run your tests once with an additional CLI option `--keep-dss-docker-image` to keep the image rather than removing it after the test session.
+
+Sample usage of the command `create-docker-image`:
+```shell
+poetry run exasol/ds/sandbox/main.py \
+       create-docker-image \
+       --version 9.9.9 \
+       --log-level info
+```
+
+To use an existing docker image in the tests in `integration/test_create_dss_docker_image.py`, simply add the CLI option `--dss-docker-image` when calling `pytest`:
 
 ```shell
 poetry run pytest --dss-docker-image exasol/ai-lab:2.1.0
 ```
 
-#### Executing tests involving AWS resources
+## Tests for Jupyter Notebooks
+
+The AI-Lab also contains end-to-end tests for Jupyter notebooks. Executing these tests can take several hours, currently ~3h.
+
+The notebook tests are based on a common parameterized [test-runner](../../test/notebook_test_runner/test_notebooks_in_dss_docker_image.py). The test-runner contains a single parameterized test case on the outer level. Each time the test is executed, the test is parameterized with a Python file from the directory [test/notebooks](../../test/notebooks/) containing the particular test cases for one of the Jupyter notebooks.
+
+The outer test case then uses a session-scoped fixture for creating an ordinary AI-Lab Docker image. Another session-scoped fixture adds some packages for executing the notebook tests, resulting in a second Docker image. Finally, the test-runner launches a Docker container from the second image and runs the inner test cases for the current notebook inside the Docker container.
+
+In total, the following Docker entities are involved:
+* Docker image 1 of the AI-Lab
+* Docker image 2 for running the inner notebook tests
+* Docker container running Docker image 2
 
-In AWS web interface, IAM create an access key for CLI usage and save or download the *access key id* and the *secret access key*.
+### Speeding up Notebook Tests
 
-In file `~/.aws/config` add lines
+You can speed up the notebook tests using the [same strategy](#speeding-up-docker-based-tests) as for tests involving the basic Docker image for the AI-Lab.
+
+The CLI option to keep the image is `--keep-docker-image-notebook-test`, the option for using an existing Docker image for executing the notebook tests is `--docker-image-notebook-test`.
+
+```shell
+poetry run pytest --docker-image-notebook-test <name:version>
+```
+
+## Executing Tests Involving AWS Resources
+
+In the AWS web interface, IAM create an access key for CLI usage and save or download the *access key id* and the *secret access key*.
+
+In the file `~/.aws/config`, add lines:
 
 ```
 [profile dss_aws_tests]
 region = eu-central-1
 ```
 
-In file `~/.aws/credentials` add
+In the file `~/.aws/credentials`, add:
 
 ```
 [dss_aws_tests]
 aws_access_key_id=...
 aws_secret_access_key=...
 ```
 
-In case your are using MFA authentication please allocate a temporary token.
+In case you are using MFA authentication, please allocate a temporary token.
 
-After that you can set an environment variable and execute the tests involving AWS resources:
+After that, you can set an environment variable and execute the tests involving AWS resources:
 
 ```shell
 export AWS_PROFILE=dss_aws_tests_mfa
 poetry run pytest test/test_deploy_codebuild.py
 ```
 
-#### Executing tests involving Ansible
+## Executing Tests Involving Ansible
 
-For making pytest display Ansible log messages, please use
+To make pytest display Ansible log messages, please use:
 
 ```shell
 poetry run pytest -s -o log_cli=true -o log_cli_level=INFO
-```
+```