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Fiddler provides multiple options for publishing batches of production data, allowing you to choose the format and method that best suits your needs.

Supported Data Formats

  • pandas DataFrame
  • CSV file (.csv),
  • Parquet file (.parquet)

Supported Data Locations

  • In memory - pandas DataFrame
  • Local disk - CSV, parquet
Note: Fiddler’s Python client offers the ability to integrate with Cloud data stores such as AWS S3. Refer to our Integrations Guides for examples.

Batch Publishing Examples

Publish a batch of inference events using a parquet file, CSV file, or DataFrame using Model.publish_batch(). This method executes asynchronously and returns a Job object. The job can be used to:
  • Track by ID in the UI on the Jobs page
  • Poll for status until completion
  • Use the wait() method for synchronous behavior
  • Log the job ID for reference

Parquet File

CSV File

Pandas DataFrame

Please allow a few minutes for events to populate the related charts. Total processing time is a function of both width and count of the inference events.