fiddler-client 0.7.0

Python client for Fiddler Service

Fiddler Client

Python client for interacting with Fiddler. Provides a user-friendly interface to our REST API and enables event publishing for use with our monitoring features.

Requirements

Requires Python >= Python-3.6.3.

Installation

$ pip3 install fiddler-client

API Example Usage

Documentation for the API can be found here. For examples of interacting with our APIs, please check out our Quick Start Guide as well as the work notebooks found on our Samples Github.

Version History

0.7.0

• Dataset Refactor

  • Datasets refactored to be members of a Project
    • This is a change promoting Datasets to be first class within Fiddler. It will affects both the UI and several API in Fiddler
  • Many API utilizing Projects will now require project_id passed as a parameter

• New Features

  • Added fdl.update_model() to client
    • update the specified model, with model binary and package.py from the specified model_dir
  • Added fdl.get_model() to client
    • download the model binary, package.py and model.yaml to the given output dir.
  • Added fdl.publish_events_batch() to client
    • Publishes a batch events object to Fiddler Service.
    • Note: Support for other batch methods including fdl.publish_events_log() and fdl.publish_parquet_s3() will be deprecated in the near future in favor of fdl.publish_events_batch()

• Changes

  • Simplified logic within fld.upload-dataset()
  • Added client/server handshake for checking version compatibilities
    • Warning issued in case of mismatch
  • Deleted redundant APIs
    • fdl.create_surrogate_model()
    • fdl.upload_model_sklearn()
  • Restructured APIs to be more duck typing-friendly (relaxing data type restrictions)
  • Patches for minor bug-fixes

0.6.18

• Features

  • Minor updates to ease use of binary classification labels

0.6.17

• Features

  • Added new arguments to ModelInfo.from_dataset_info()
    • preferred_explanation_method to express a preferred default explanation algorithm for a model
    • custom_explanation_names to support user-provided explanation algorithms which the user will implement on their model object via package.py.

0.6.16

• Features

  • Minor improvements to publish_events_log() to circumvent datatype conversion issues

0.6.15

• Features

  • Added strict name checks

0.6.14

• Features

  • Added client-native multithreading support for publish_events_log() using new parameters num_threads and batch_size

0.6.13

• Features

  • Added fdl.generate_sample_events() to client
    • API for generating monitoring traffic to test out Fiddler
  • Added fdl.trigger_pre_computation() to client
    • Triggers various precomputation steps within the Fiddler service based on input parameters.
  • Optionally add proxies to FiddlerApi() init

0.6.12

• Features

  • Added fdl.publish_parquet_s3() to client
    • Publishes parquet events file from S3 to Fiddler instance. Experimental and may be expanded in the future.

0.6.10

• Features

  • Added fdl.register_model() to client
    • Register a model in fiddler. This will generate a surrogate model, which can be replaced later with original model.