info() Function

The info() function provides guidelines for using Connector.

info() can be called using a Connector object, without parameters:

from dataprep.connector import connect, info

# Access tokens can be accessed generated here:
dc = connect('yelp', _auth={'access_token':'cCMHU4M4t7rdt*********vp3whGzFjgIKIm0'})

Or by specifying the API to query as a parameter:



  • config_path is the path to the folder containing configuration files. There are two ways to load configuration files. Details can be found in the previous configuraton file section.

  • update is used to specify if new configuration files should be pulled from the GitHub repo where up to date configuration files are hosted.


  • Table displays table(s) of data that can be accessed. Each table has a corresponding API endpoint which will be queried automatically by connector.

  • Parameters identifies parameters that can be used in the query function to access specific data. info() indicates if the parameter is required for all queries of the specified table.

  • Examples shows how methods of the Connector class can be called. The access_token value must be replaced with an authorization key that can be generated by following instructions on the developer website of the API.

  • Schema displays column names and column data types of the DataFrame returned by the query function.


Below shows the case for the Yelp website. You can see:

  • Yelp has one table: “businesses”.

  • The businesses table has seven parameters: location, term, latitude, longitude, limit, categories and sort_by. The location parameter is required, while the other parameters are optional.

  • The example shows how to connect and query Yelp. More details can be found in the “connect” and “query” sections.

  • The schema shows there will be 20 columns of data returned. Each row of the schema displays a column name and its corresponding data type. For example the “name” and “image_url” columns contain string data while “latitude” and “longitude” columns contain float data.

from dataprep.connector import info
info('yelp', update=True)

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