Quickstart

How to start using Naas in minutes.

Naas augments Jupyter Notebooks by adding micro-services accessible in low-code to easily access data, automation, and AI.

The product is based on 3 elements: features, drivers, and templates.

The templates enable "data geeks" to kickstart projects in minutes. They may include low-code drivers that act as super connectors to facilitate access to tools, and complex libraries (database, API, ML algorithm...) while the low-code features (scheduling, asset sharing, notifications...) enable faster iteration and deployment of outputs to end-users, in a headless way.

Naas is forever free to use with 100 credits/month on its hosted version www.naas.ai. πŸ‘‰Open your account

If you contribute to this library of open-source notebooks templates, you can X2 your monthly credits πŸ†

Local installation

If you want to use Naas on your local Jupyter environment, it's free and open-source, just follow the procedure below :

Why Naas?

Jupyter Notebooks are awesome, but using them in production can be risky & messy.

Naas allows Jupyter Notebooks to become a safe production environment!

Basic features

Naas makes a dynamic production environment based on your current notebook folder.

Create a folder, open a notebook, and import Naas :

import naas

Schedule your notebook

Send in production this notebook and run it, every day at 9:00

# do stuff in your notebook
naas.scheduler.add(recurrence="0 9 * * *")

Add a dependency

Send in production any file type like test.csv as a dependency:

naas.dependency.add("test.csv")

Add a secret key

Copy in production any secret key :

naas.secret.add(name="API_NAME", secret="API_KEY")

Remove the previous line and get your secret key with :

naas.secret.get(name="MY_API_KEY")

This allows you to push your notebook in production without sensitive data getting exposed.

Advanced features

If you use Naas cloud they all work natively, otherwise go to :

Use Notebooks as API

Copy in production this notebook and allow to run it by calling the returned URL:

naas.api.add()

Call the URL with your navigator you will get a message and see the notebook has run.

If you want to download the notebook result instead, add this line:

naas.api.respond_notebook()

Expose assets

Copy in production this asset ( file ) and allow to get it by calling the returned url:

link = naas.assets.add("tesla-chart.html")

Send notifications

Send an email notification to anyone, to notify about data changes, alert on notebooks operations, etc...

# Get link var from previous step
subject = "The tesla action is going up"
content = "check in the link the chart data maide from fresh dataset : " + link
naas.notifications.send(email=email, subject=subject, content=content)

Help

Open

If at any time you are lost, you need help, or just want some info!

import naas
​
naas.open_help()

That will open a chat box with us

Close help chat

import naas
​
naas.close_help()

Documentation

Show a button to quickly open this documentation from Jupyter

import naas
naas.doc()