Origami

Launch, edit, and share Jupyter notebooks in automation.

Install | Getting Started | Documentation | License | Code of Conduct | Contributing

Intro to Origami

Origami is a 🐍 Python library for talking to Noteable notebooks. This is the official way to access the full breadth of API calls and access patterns in async Python for rich programmatic access to notebooks. You can use Noteable for free with a quick signup.

Requirements

Python 3.8

Installation

For stable release:

pip install noteable-origami

poetry add noteable-origami

For alpha pre-release:

pip install noteable-origami --pre

Getting Started

Note Developer note: For pre-1.0 release information, see the pre-1.0 README

API Tokens

The Noteable API requires an authentication token. You can manage tokens at the Noteable user settings page.

1. Log in to Noteable (sign up is free).
2. In the User Settings tab, navigate to API Tokens and generate a new token.
3. Copy the generated token to the clipboard and save in a secure location, to be read into your Python environment later.

The token can be passed directly in to APIClient on initialization, or set it as env var NOTEABLE_TOKEN.

Usage

The example below will guide you through the basics of creating a notebook, adding content, executing code, and seeing the output. For more examples, see our Use Cases section.

Setting up the APIClient

Using the API token you created previously, load it into your notebook environment so it can be passed into the APIClient directly. (If you're in Noteable, you can create a Secret that can be read in as an environment variable.)

import os
from origami.clients.api import APIClient

# if we have the `NOTEABLE_TOKEN` environment variable set,
# we don't need to pass it in to the APIClient directly
api_client = APIClient()

The APIClient is what we'll use to make HTTP requests to Noteable's REST API.

Checking your user information

user = await api_client.user_info()
user

User(
    id=UUID('f1a2b3c4-5678-4d90-ef01-23456789abcd'),
    created_at=datetime.datetime(2023, 1, 1, 0, 0, 0, 0, tzinfo=datetime.timezone.utc),
    updated_at=datetime.datetime(2023, 1, 1, 0, 0, 0, 0, tzinfo=datetime.timezone.utc),
    deleted_at=None,
    handle='ori.gami',
    email='[email protected]',
    first_name='Ori',
    last_name='Gami',
    origamist_default_project_id=UUID('a1b2c3d4-e5f6-4a7b-8123-abcdef123456'),
    principal_sub='pat:0a1b2c3d4e5f6g7h8i9j10k11l',
    auth_type='pat:0a1b2c3d4e5f6g7h8i9j10k11l'
)

(The information returned should match your user account information associated with the previously-generated API token.)

Creating a new Notebook

Note For this example, we're using the origamist_default_project_id, which is the default project designed to be used by the ChatGPT plugin. Feel free to replace it with projects you have access to in Noteable!

Provide a file path as well as a project_id (UUID) where the Notebook will exist.

project_id = user.origamist_default_project_id

file = await api_client.create_notebook(
    project_id=project_id,
    path="Origami Demo.ipynb"
)
file

File(
    id=UUID('bcd12345-6789-4abc-d012-3456abcdef90'),
    created_at=datetime.datetime(2023, 2, 2, 0, 0, 0, 0, tzinfo=datetime.timezone.utc),
    updated_at=datetime.datetime(2023, 2, 2, 0, 0, 0, 0, tzinfo=datetime.timezone.utc),
    deleted_at=None,
    filename='Origami Demo.ipynb',
    path=PosixPath('Origami Demo.ipynb'),
    project_id=UUID('a1b2c3d4-e5f6-4a7b-8123-abcdef123456'),
    space_id=UUID('7890ab12-3412-4cde-8901-2345abcdef67'),
    size=0,
    mimetype=None,
    type='notebook',
    current_version_id=None,
    presigned_download_url=None,
    url='https://app.noteable.io/f/abc12312-3412-4abc-8123-abc12312abc1/Origami Demo.ipynb'
)

Launching a Kernel

At a minimum, the file_id from the Notebook is required. Additionally, you can specify:

• kernel_name (default python3, see more about available kernels)
• hardware_size (default small, see more about hardware options).

kernel_session = await api_client.launch_kernel(file_id=file.id)
kernel_session

KernelSession(
    id=UUID('e1f2a345-6789-4b01-cdef-1234567890ab'),
    kernel=KernelDetails(
        name='python3',
        last_activity=datetime.datetime(2023, 2, 2, 1, 0, 0, 0, tzinfo=datetime.timezone.utc),
        execution_state='idle'
    )
)

Adding Cells

Content updates and code execution is handled through the Noteable Real-Time Update (RTU) websocket connection.

realtime_notebook = await api_client.connect_realtime(file)

Warning You may see messages like Received un-modeled RTU message msg.channel= .... This is expected as we update the Noteable backend services' messaging.

Once the RTU client is connected, we can begin adding cells, executing code, and more! First, let's add a code cell with a basic Python print statement.

from origami.models.notebook import CodeCell

cell = CodeCell(source="print('Hello World')")
await realtime_notebook.add_cell(cell=cell)

(You can also pass code source directly into .add_cell(source='CODE HERE') as a shortcut.)

Running a Code Cell

The returned value is a dictionary of asyncio.Futures. Awaiting those futures will block until the cells have completed execution. The return value of the Futures is the up-to-date cell. If there's output, an output collection id will be set on the cell metadata.

import asyncio

queued_execution = await realtime_notebook.queue_execution(cell.id)
cells = await asyncio.gather(*queued_execution)
cell = cells[0]
cell

CodeCell(
    id='2345ab6c-de78-4901-bcde-f1234567890a',
    source="print('Hello World')",
    metadata={
        'noteable': {'output_collection_id': UUID('d1234e5f-6789-4a0b-c123-4567890abcdef')},
        'ExecuteTime': {
            'start_time': '2023-02-02T01:00:00.000000 00:00',
            'end_time': '2023-02-02T01:00:00.050000 00:00'
        }
    },
    cell_type='code',
    execution_count=None,
    outputs=[]
)

Getting Cell Output

We can call the .output_collection_id property on cells directly, rather than having to parse the cell metadata.

output_collection = await api_client.get_output_collection(cell.output_collection_id)
output_collection

KernelOutputCollection(
    id=UUID('d1234e5f-6789-4a0b-c123-4567890abcdef'),
    created_at=datetime.datetime(2023, 2, 2, 1, 0, 1, 000000, tzinfo=datetime.timezone.utc),
    updated_at=datetime.datetime(2023, 2, 2, 1, 0, 1, 000000, tzinfo=datetime.timezone.utc),
    deleted_at=None,
    cell_id='2345ab6c-de78-4901-bcde-f1234567890a',
    widget_model_id=None,
    file_id=UUID('bcd12345-6789-4abc-d012-3456abcdef90'),
    outputs=[
        KernelOutput(
            id=UUID('abcdef90-1234-4a56-7890-abcdef123456'),
            created_at=datetime.datetime(2023, 2, 2, 1, 0, 1, 000000, tzinfo=datetime.timezone.utc),
            updated_at=datetime.datetime(2023, 2, 2, 1, 0, 1, 000000, tzinfo=datetime.timezone.utc),
            deleted_at=None,
            type='stream',
            display_id=None,
            available_mimetypes=['text/plain'],
            content_metadata=KernelOutputContent(raw='{"name":"stdout"}', url=None, mimetype='application/json'),
            content=KernelOutputContent(raw='Hello World\n', url=None, mimetype='text/plain'),
            content_for_llm=KernelOutputContent(raw='Hello World\n', url=None, mimetype='text/plain'),
            parent_collection_id=UUID('d1234e5f-6789-4a0b-c123-4567890abcdef')
        )
    ]
)

CLI

Origami has a small CLI for fetching the content of a Notebook, and tailing a Notebook to see all RTU messages being emitted on the relevant RTU channels.

pip install noteable-origami[cli]
poetry install -E cli

1. Fetch the content of a Notebook and write to file: origami fetch <file-id> > notebook.ipynb
2. Tail a Notebook, useful when debugging RTU messages: origami tail <file-id>

Dev ENV settings

• Use NOTEABLE_API_URL to point to non-production clusters, such as http://localhost:8001/api for local Gate development
• E2E tests will use TEST_SPACE_ID, TEST_PROJECT_ID, and TEST_USER_ID env vars when running, useful in CI

Contributing

See CONTRIBUTING.md.

Open sourced with ❤️ by Noteable for the community.