JupyterLab Extension for INFACore

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You can create your first job using INFACore in just a few steps!

When you log in to INFACore from JupyterLab, the INFACore Home page appears in JupyterLab, as shown in the following image:

The INFACore Home page displays in JupyterLab, where you can perform basic operations. The SDKs help you programmatically call the INFACore methods and classes.

On the left-hand side, you can see the JupyterLab work area where you can programmatically invoke the INFACore Python SDK. On the right-hand side, the JupyterLab interface for INFACore provides you with the options to perform basic operations to get you started.

You can perform the following tasks from the INFACore user interface:

Set up the runtime environment.

Before you can connect to a data source or to apply functions to a data source, you need to install the runtime environment. The runtime environment is the execution platform for running all the INFACore jobs.

Connect to your data source.

The data source is the endpoint from where you want to read from or write data. Select the data source to which you want to connect and then create a connection to connect to the data source.

Apply functions to your data.

Functions represent the operations that you want to perform on the data.

To invoke the INFACore Python SDK for various operations, see the

INFACore SDK Reference for Python

After you create your first job, you can also:

Monitor the activity of your jobs and operations in the

Activity logs

page.

Download the log files for a job to the agent machine.

Use the in-built forms to refer INFACore to colleagues, write a feedback about INFACore, or to submit requests. In the

Connect to Data Sources

section, you can request for new connections to access data source endpoints from INFACore. In the

Apply Functions

section, you can also submit a request for new functions, with the purpose defined.

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JupyterLab Extension for INFACore

JupyterLab Extension for INFACore

Let's get started

Let's get started