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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.

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Supported Data Formats

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

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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.

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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

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Parquet File

import fiddler as fdl

# Instantiate the Model object for your model
project = fdl.Project.from_name(name='your_project_name')
model = fdl.Model.from_name(name='your_model_name', project_id=project.id)
publish_job = model.publish_batch(source='my_events_batch.parquet')

# publish_batch() is asynchronous. Use the publish job's wait() method
# if synchronous behavior is desired.
publish_job.wait()

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CSV File

import fiddler as fdl

# Instantiate the Model object for your model
project = fdl.Project.from_name(name='your_project_name')
model = fdl.Model.from_name(name='your_model_name', project_id=project.id)
publish_job = model.publish_batch(source='my_events_batch.csv')

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Pandas DataFrame

import pandas as pd
import fiddler as fdl

# Instantiate the Model object for your model
project = fdl.Project.from_name(name='your_project_name')
model = fdl.Model.from_name(name='your_model_name', project_id=project.id)

my_events_df = pd.read_csv('my_events_batch.csv')
publish_job = model.publish_batch(source=my_events_df)
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.