Push version to 0.15.0 (manually)

Author: tomfaulhaber

CHANGELOG.md

@@ -1,5 +1,18 @@
 # Changelog
 
+## v0.15.0 (2020-09-23)
+
+### Bugs
+
+* Fixed [Issue #4](https://github.com/aws-samples/sagemaker-run-notebook/issues/4), a regression where the invocation of papermill would fail with "No such kernel". (Note that any containers built under v0.14.0, should be rebuilt with `run-notebook )
+
+### Features
+
+Two small changes:
+
+* Added a `-v` option to run-notebook to display the current installed version of the library.
+* Changed the install scripts for SageMaker notebooks to install directly from the release on GitHub so users don't need to copy to an S3 bucket first.
+
 ## v0.14.0 (2020-09-14)
 
 ### Features

QuickStart.md

@@ -164,12 +164,12 @@ When the notebook has run, you can find the jobs with `aws sagemaker list-proces
 
 To follow this recipe, you'll need to have AWS credentials set up that give you full permission on CloudFormation. You'll add more permissions with the installed policy later in the recipe.
 
-You'll need installation file that you can download from the [latest release][release]: sagemaker_run_notebook-0.14.0.tar.gz.
+You'll need installation file that you can download from the [latest release][release]: sagemaker_run_notebook-0.15.0.tar.gz.
 
 #### 1. Install the library
 
 ```sh
-$ pip install sagemaker_run_notebook-0.14.0.tar.gz
+$ pip install sagemaker_run_notebook-0.15.0.tar.gz
 ```
 
 This installs the sagemaker run notebook library and CLI tool. It also installs the JupyterLab plug-in but does not activate it. See below in "Using the JupyterLab Extension" for more information.
@@ -250,22 +250,20 @@ Once you have the infrastructure and containers set up, the best way to activate
 
 #### In a SageMaker Notebook instance
 
-1. Upload the installation package, sagemaker_run_notebook-0.14.0.tar.gz, from the [latest release][release] to a location of your choosing in S3.
-2. On the AWS SageMaker console, go to Lifecycle Configuration. Create a new lifecycle configuration and add the `start.sh` script (available on [GitHub][start.sh]) to the start action. Edit the S3 location to where you uploaded the installation tar file.
-3. Start or restart your notebook instance after setting the lifecycle configuration to point at your newly created lifecycle configuration.
+1. On the AWS SageMaker console, go to Lifecycle Configuration. Create a new lifecycle configuration and add the `start.sh` script (available on [GitHub][start.sh]) to the start action. (The easiest way is just to copy and paste from GitHub to the AWS console.)
+2. Start or restart your notebook instance after setting the lifecycle configuration to point at your newly created lifecycle configuration.
 
 [start.sh]: https://github.com/aws-samples/sagemaker-run-notebook/blob/master/scripts/lifecycle-config/start.sh
 
 #### In SageMaker Studio
 
 When you open SageMaker Studio, you can add the extension with the following steps:
 
-1. Upload the the installation package, sagemaker_run_notebook-0.14.0.tar.gz, from the [latest release][release] to a location of your choosing in S3.
-2. Save the  `install-run-notebook.sh` script (available on [GitHub][install-run-notebook.sh]) to your home directory in Studio. The easiest way to do this is to open a text file and paste the contents in. Then edit the S3 location to where you uploaded the installation tar file and save it as `install-run-notebook.sh`.
-3. Open a terminal tab (`File`->`New`->`Terminal`) and run the script as `bash install-run-notebook.sh`.
-4. When it's complete, refresh your Studio browser tab and you'll see the sidebar scheduler tab.
+1. Save the  `install-run-notebook.sh` script (available on [GitHub][install-run-notebook.sh]) to your home directory in Studio. The easiest way to do this is to open a text file and paste the contents in.
+2. Open a terminal tab (`File`->`New`->`Terminal`) and run the script as `bash install-run-notebook.sh`.
+3. When it's complete, refresh your Studio browser tab and you'll see the sidebar scheduler tab.
 
-If you restart your server app, just rerun steps 3 & 4 and you'll have the extension ready to go.
+If you restart your server app, just rerun steps 2 & 3 and you'll have the extension ready to go.
 
 [install-run-notebook.sh]: https://github.com/aws-samples/sagemaker-run-notebook/blob/master/scripts/studio/install-run-notebook.sh
 

build-dist-files.sh

@@ -10,7 +10,7 @@
 #
 # They all live in the subdirectory "manual_dist/"
 
-VERSION=0.14.0
+VERSION=0.15.0
 
 make artifacts
 

labextension/package.json

@@ -1,6 +1,6 @@
 {
   "name": "sagemaker_run_notebook",
-  "version": "0.14.0",
+  "version": "0.15.0",
   "description": "Execute notebooks on a schedule in SageMaker",
   "keywords": [
     "jupyter",

sagemaker_run_notebook/server_extension/_version.py

@@ -11,7 +11,7 @@
 # ANY KIND, either express or implied. See the License for the specific
 # language governing permissions and limitations under the License.
 
-version_info = (0, 14, 0)
+version_info = (0, 15, 0)
 flag = ""
 
 __version__ = ".".join(map(str, version_info)) + flag

scripts/lifecycle-config/ReadMe.md

@@ -4,12 +4,9 @@ This directory has a lifecycle configuration script that lets you set up the Jup
 
 To use this lifecycle configuration, perform the following steps:
 
-1. Use the [AWS CLI][1] to copy the SageMaker Run Notebook tar file to a location in S3, for example `aws s3 cp sagemaker_run_notebook-0.14.0.tar.gz s3://my-bucket/some-path/`
-2. Edit `start.sh` to point at the s3 location and correct plugin version from the previous step.
-3. On the SageMaker AWS console, select "Lifecycle configurations" in the left column and create a new lifecycle configuration called `install-run-notebook-extension`. Copy the contents of `start.sh` into the "Start Notebook" script. You can leave the "Create Notebook" script blank.
-4. When creating a new notebook instance, open the "Additional configuration" option in the "Notebook instance settings" and select the `install-run-notebook-extension`. You can also add this configuration to an existing notebook instance by stopping the instance, opening the instance on the console (by clicking on the instance name in the list of instances), and adding the new configuration there. Then restart your notebook instance.
+1. On the SageMaker AWS console, select "Lifecycle configurations" in the left column and create a new lifecycle configuration called `install-run-notebook-extension`. Copy the contents of `start.sh` into the "Start Notebook" script. You can leave the "Create Notebook" script blank.
+2. When creating a new notebook instance, open the "Additional configuration" option in the "Notebook instance settings" and select the `install-run-notebook-extension`. You can also add this configuration to an existing notebook instance by stopping the instance, opening the instance on the console (by clicking on the instance name in the list of instances), and adding the new configuration there. Then restart your notebook instance.
 
-For more information about lifecycle configurations, see ["Customize a Notebook Instance Using a Lifecycle Configuration Script"][2] in the AWS documentation.
+For more information about lifecycle configurations, see ["Customize a Notebook Instance Using a Lifecycle Configuration Script"][1] in the AWS documentation.
 
-[1]: https://aws.amazon.com/cli/
-[2]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html
+[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html

scripts/lifecycle-config/start.sh

@@ -26,7 +26,7 @@ set -e
 sudo -u ec2-user -i <<'EOF'
 
 # PARAMETERS
-VERSION=0.14.0
+VERSION=0.15.0
 
 EXTENSION_NAME=sagemaker_run_notebook
 

scripts/studio/install-run-notebook.sh

@@ -1,4 +1,4 @@
-version=0.14.0
+version=0.15.0
 pip install https://github.com/aws-samples/sagemaker-run-notebook/releases/download/v${version}/sagemaker_run_notebook-${version}.tar.gz
 jlpm config set cache-folder /tmp/yarncache
 jupyter lab build --debug --minimize=False