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AWS CDK (Python) sample to create Amazon Neptune graph database and connect to Neptune Workbench (Jupyter Notebook)

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AWS CDK Python project for Amazon Neptune and Jupyter Notebooks

This is a project to create an Amazon Neptune database using AWS CDK (Python), and create a Neptune workbench connected to it.

The cdk.json file tells the CDK Toolkit how to execute your app.

This project is set up like a standard Python project. The initialization process also creates a virtualenv within this project, stored under the .env directory. To create the virtualenv it assumes that there is a python3 (or python for Windows) executable in your path with access to the venv package. If for any reason the automatic creation of the virtualenv fails, you can create the virtualenv manually.

To manually create a virtualenv on MacOS and Linux:

$ git clone https://github.com/ksmin23/neptune-tutorial.git
$ cd neptune-tutorial/
$ python3 -m venv .env

After the init process completes and the virtualenv is created, you can use the following step to activate your virtualenv.

$ source .env/bin/activate

If you are a Windows platform, you would activate the virtualenv like this:

% .env\Scripts\activate.bat

Once the virtualenv is activated, you can install the required dependencies.

$ pip install -r requirements.txt

At this point you can now synthesize the CloudFormation template for this code.

$ cdk synth

You can also create Amazon Neptune database and Neptune workbench.

$ cdk deploy

To add additional dependencies, for example other CDK libraries, just add them to your setup.py file and rerun the pip install -r requirements.txt command.

Useful commands

  • cdk ls list all stacks in the app
  • cdk synth emits the synthesized CloudFormation template
  • cdk deploy deploy this stack to your default AWS account/region
  • cdk diff compare deployed stack with current state
  • cdk docs open CDK documentation

Enjoy!

License

These samples are available under the MIT License.

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AWS CDK (Python) sample to create Amazon Neptune graph database and connect to Neptune Workbench (Jupyter Notebook)

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