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Runrun.it (Runrunit) is a work-management platform for planning tasks, projects, and teams. The connector extracts clients, projects, tasks, task attachments, dashboards, users, and time worked reports from the Runrun.it API.

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Configuring Runrunit as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Runrunit option from the list of connectors. Click Next and you’ll be prompted to add your access.

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1. Add account access

You’ll need to authorize Nekt to access your Runrunit data using a User Token. The following configurations are available:
  • User Token: The user token to make API calls against the Runrun.it API. Please ensure this user token has enough access to the underlying data. Check Runrun.it’s documentation to discover where you can find the Application Key and User Token.
  • Start Date: Only applies to the time_worked and time_worked_by_project_and_user streams. On the first sync, data is extracted from this date onward. If omitted, the first sync only pulls the last 7 days. Format: YYYY-MM-DD.
  • Lookback Window: (Default: 7 days) Only applies to the time_worked and time_worked_by_project_and_user streams. Fixed window to reprocess time-worked data on each run, to account for manual time adjustments made after the fact.
Once you’re done, click Next.

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2. Select streams

Choose which data streams you want to sync. For faster extractions, select only the streams that are relevant to your analysis. You can select entire groups of streams or pick specific ones.
Tip: The stream can be found more easily by typing its name.
Select the streams and click Next.

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3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table (which will effectively contain the fetched data) and the type of sync.
  • Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables as the extraction runs successfully.
  • Folder: a folder can be created inside the selected layer to group all tables being created from this new data source.
  • Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once and make this process faster!
  • Sync Type: you can choose between INCREMENTAL and FULL_TABLE.
    • Incremental: every time the extraction happens, we’ll get only the new data - which is good if, for example, you want to keep every record ever fetched.
    • Full table: every time the extraction happens, we’ll get the current state of the data - which is good if, for example, you don’t want to have deleted data in your catalog.
Once you are done configuring, click Next.

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4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often you want data to be extracted from this source. This decision usually depends on how frequently you need the new table data updated (every day, once a week, or only at specific times). Optionally, you can define some additional settings:
  • Configure Delta Log Retention and determine for how long we should store old states of this table as it gets updated. Read more about this resource here.
  • Determine when to execute an Additional Full Sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source every once in a while.
Once you are ready, click Next to finalize the setup.

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5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.
For you to be able to see it on your Catalog, you need at least one successful source run.

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Streams and Fields

Below you’ll find the available data streams from Runrunit and their corresponding fields:
Time worked report grouped by date and project. Grouping by date+project also carries the client and project-group hierarchy.Key Fields:(Note: Stream also returns standard hierarchy fields such as client and project details).
Time worked report grouped by date, project, and user. Returns time per user per project per day, including the full client and project-group hierarchy. Aggregating by user_id yields total time per user; filtering by client_id yields time per user within a specific client.Key Fields:(Note: Stream also returns standard hierarchy fields such as client and project details).

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Implementation Notes

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Time Worked Data Extraction

  • Lookback Window: The time_worked and time_worked_by_project_and_user streams utilize the configured lookback_window (default 7 days) on every incremental run. This ensures that any manual time adjustments made retroactively in Runrunit are captured and updated in your destination.
  • Start Date vs Lookback: On the first sync, if a start_date is provided, the connector fetches data from that date onward. On subsequent runs, it fetches data starting from the maximum of the start_date and the date determined by the lookback_window subtracted from the last replicated date.
  • Pagination: The report returns all rows for the requested custom range in a single response, meaning no page-by-page fetching is required for these extractions.