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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 :
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import naas
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Schedule your notebook

Send in production this notebook and run it, every day at 9:00
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# do stuff in your notebook
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naas.scheduler.add(recurrence="0 9 * * *")
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Add a dependency

Send in production any file type like test.csv as a dependency:
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naas.dependency.add("test.csv")
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Add a secret key

Copy in production any secret key :
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naas.secret.add(name="API_NAME", secret="API_KEY")
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Remove the previous line and get your secret key with :
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naas.secret.get(name="MY_API_KEY")
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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:
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naas.api.add()
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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:
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naas.api.respond_notebook()
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Expose assets

Copy in production this asset ( file ) and allow to get it by calling the returned url:
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link = naas.assets.add("tesla-chart.html")
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Send notifications

Send an email notification to anyone, to notify about data changes, alert on notebooks operations, etc...
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# Get link var from previous step
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subject = "The tesla action is going up"
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content = "check in the link the chart data maide from fresh dataset : " + link
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naas.notifications.send(email=email, subject=subject, content=content)
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Help

Open

If at any time you are lost, you need help, or just want some info!
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import naas
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​
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naas.open_help()
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That will open a chat box with us

Close help chat

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import naas
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​
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naas.close_help()
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Documentation

Show a button to quickly open this documentation from Jupyter
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import naas
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naas.doc()
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Last modified 5mo ago