If you want to use Naas on your local Jupyter environment, it's free and open-source, just follow the procedure below :
Naas makes a dynamic production environment based out of your current notebook folder.
Create a folder, open a notebook, and import Naas :
Send in production this notebook and run it, every day at 9:00
# do stuff in your notebooknaas.scheduler.add(recurrence="0 9 * * *")
Send in production any file type like
test.csv as a dependency:
Copy in production any secret key :
Remove the previous line and get your secret key with :
This allows you to push your notebook in production without sensitive data getting exposed.
If you use Naas cloud they all work natively, otherwise go to :
Copy in production this notebook and allow to run it by calling the returned URL:
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:
Copy in production this asset ( file ) and allow to get it by calling the returned url:
link = naas.assets.add("tesla-chart.html")
Send an email notification to anyone, notify about data changes, alert on notebooks operations, etc...
# Get link var from previous stepemail = "[email protected]"subject = "The tesla action is going up"content = "check in the link the chart data maide from fresh dataset : " + linknaas.notifications.send(email=email, subject=subject, content=content)
the version number in your local machine
the last version number in Github
If you need update it will restart your machine
Show a button to quick open this documentation from Jupyter
show feature request inside Jupyter
import naasmode = "naas" # can be naas, naas_drivers, awesome_notebooknaas.feature_request(mode)