Enable your users to access the power of the Salesforce Dataloader, but with a customizable user experience

Salesforce, as the world’s leading Customer Relationship Management (CRM) platform, is a great tool able to store vast amounts of data. As such, managing that data is routine for the platform’s administrators. One of the ways they can do that is through the Dataloader, a client application able to extract, insert, update, and delete Salesforce records.

When I first started working with Salesforceand using the Dataloader during a summer internship in 2018, I remember being scared of accidentally doing something wrong. Upon opening it, all objects I had access to appeared right in front of me, even if I did not know they existed or would be interested in them to begin with. Although it is possible to restrict which users are able to use the tool, I was interested in being able to customize the user’s experience within it and create a more controlled and optimized environment. This way, instead of showing all objects within the organization, I may for example choose to show only Opportunities, Leads and Accounts to a sales team, or Custom Metadata Types and Custom Settings to a Developer Team. The options are limitless, and in this article I will walk through an application that tries to mimic the Salesforce Dataloader in its entirety and that can serve as a stepping stone to build more tailored experiences. Some of its limitations are that it can only insert, update, and delete only at most 10k records in one job, the column names from the input Excel/Csv file must match exactly the “API Name” of the field you are trying to write in, and to login the security token obtainable from your personal settings in Salesforce is required. This solution uses the simple_salesforce and salesforce_bulk Python packages to deal with the data, as well as Tkinter to build the user interface.


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