The Noteable API interface
Project description
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.
- Log in to Noteable (sign up is free).
- In the User Settings tab, navigate to
API Tokens
and generate a new token. - 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='origami@noteable.io',
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
(defaultpython3
, see more about available kernels)hardware_size
(defaultsmall
, 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.Future
s. 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
- Fetch the content of a Notebook and write to file:
origami fetch <file-id> > notebook.ipynb
- 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 ashttp://localhost:8001/api
for local Gate development - E2E tests will use
TEST_SPACE_ID
,TEST_PROJECT_ID
, andTEST_USER_ID
env vars when running, useful in CI
Contributing
See CONTRIBUTING.md.
Open sourced with ❤️ by Noteable for the community.
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