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update README to include all magic commands added by graph-notebok (#56)
* update README to include all magic commands added by graph-notebok * fix ML notebooks not being picked up in releases to pip
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README.md

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`%%gremlin` - Executes a Gremlin query against your database using web sockets. The results are similar to what the Gremlin console would return.
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`%%graph_notebook_config` - Sets the executing notebook's database configuration to the JSON payload provided in the cell body.
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`%%graph_notebook_vis_options` - Sets the executing notebook's [vis.js options](https://visjs.github.io/vis-network/docs/network/physics.html) to the JSON payload provided in the cell body.
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`%%neptune_ml` - Set of commands to integrate with NeptuneML functionality. [Documentation](https://aws.amazon.com/neptune/machine-learning/)
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**TIP** :point_right: There is syntax highlighting for both `%%sparql` and `%%gremlin` queries to help you structure your queries more easily.
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#### Notebook line 'magic' extensions in the IPython 3 kernel
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`%graph_notebook_config` - Returns a JSON object that contains connection information for your host.
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`%gremlin_status` - Obtain the status of Gremlin queries. [Documentation](https://docs.aws.amazon.com/neptune/latest/userguide/gremlin-api-status.html)
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`%sparql_status` - Obtain the status of SPARQL queries. [Documentation](https://docs.aws.amazon.com/neptune/latest/userguide/sparql-api-status.html)
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`%load` - Generate a form to submit a bulk loader job. [Documentation](https://docs.aws.amazon.com/neptune/latest/userguide/bulk-load.html)
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`%query_mode` - Lets you set the query mode for your queries to one of:
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`%load_ids` - Get ids of bulk load jobs. [Documentation](https://docs.aws.amazon.com/neptune/latest/userguide/load-api-reference-status-examples.html)
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* `query` (the default) : executes the query against the normal SPARQL or Gremlin endpoint
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* `explain` : Returns an explanation of the query plan instead of the query's results (valid for both SPARQL and Gremlin).
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* `profile` : Returns a profile of the query's operation, but does not actually execute the query (valid only for Gremlin).
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`%load_status` - Get the status of a provided `load_id`. [Documentation](https://docs.aws.amazon.com/neptune/latest/userguide/load-api-reference-status-examples.html)
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`%neptune_ml` - Set of commands to integrate with NeptuneML functionality. You can find a set of tutorial notebooks [here](https://github.com/aws/graph-notebook/tree/main/src/graph_notebook/notebooks/04-Machine-Learning).
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[Documentation](https://aws.amazon.com/neptune/machine-learning/)
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`%status` - Check the Health Status of the configured host endpoint. [Documentation](https://docs.aws.amazon.com/neptune/latest/userguide/access-graph-status.html)
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`%seed` - Provides a form to add data to your graph without the use of a bulk loader. both SPARQL and Gremlin have an airport routes dataset.
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`%graph_notebook_config` - Returns a JSON payload that contains connection information for your host.
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`%graph_notebook_host` - Set the host endpoint to send queries to.
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`%graph_notebook_version` - Print the version of the `graph-notebook` package
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`%graph_notebook_vis_options` - Print the Vis.js options being used for rendered graphs
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**TIP** :point_right: You can list all the magics installed in the Python 3 kernel using the `%lsmagic` command.
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src/graph_notebook/__init__.py

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SPDX-License-Identifier: Apache-2.0
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"""
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__version__ = '2.0.5'
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__version__ = '2.0.6'

src/graph_notebook/notebooks/03-Applications/__init__.py

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src/graph_notebook/notebooks/04-Machine-Learning/__init__.py

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src/graph_notebook/widgets/package.json

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{
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"name": "graph_notebook_widgets",
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"version": "2.0.5",
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"version": "2.0.6",
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"author": "amazon",
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"description": "A Custom Jupyter Library for rendering NetworkX MultiDiGraphs using vis-network",
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"dependencies": {

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