Python Client History
3.x Client Version
3.7
3.7.1
Modifications
Connection Timeout Settings: You can now configure network timeout settings when initializing the Python client. The new timeout parameter in init() accepts:
A single number (in seconds) to set the connection timeout
A tuple of two numbers (in seconds) to set both connection and read timeouts separately
3.7.0
Release highlights:
Robustness via retrying: this release introduces a persistent HTTP request retrying strategy to enhance fault tolerance in view of transient network problems and retryable HTTP request errors. You can take control of the maximum duration for which an HTTP request is retried by setting the environment variable
FIDDLER_CLIENT_RETRY_MAX_DURATION_SECONDS
.AWS SageMaker authentication support: to enable that, install version 2.236.0+ of the AWS Python SageMaker SDK. Then, before calling
init()
, set the environment variableAWS_PARTNER_APP_AUTH
totrue
and setAWS_PARTNER_APP_ARN
/AWS_PARTNER_APP_URL
to meaningful values.Logging improvements: messages are now emitted to
stderr
instead ofstdout
. Only if the calling context does not configure a root logger this library will actively declare a handler for its own log messages (this automation can be disabled by settingauto_attach_log_handler=False
duringinit()
).
Compatibility changes:
Pydantic 2.x is now supported (and compatibility with Pydantic 1.x has been retained).
Support for Python 3.8 has been dropped.
API surface additions:
Introduced
Project.get_or_create()
to reduce code required for instantiating a project.Introduced
model.remove_column()
to allow for removing a column from a model object.
Fixes:
A transient error during a job status update does not prematurely terminate waiting for a job anymore.
GET requests do not contain the
Content-Type
header anymore.
3.6
3.6.0
Removed
The
get_slice
anddownload_slice
methods are removed. Please usedownload_data
to retrieve some data.The
get_mutual_info
method is removed.The
SqlSliceQueryDataSource
option is removed from explain, feature impact and importance. Please use theDatasetDataSource
instead or the UI.
3.5
3.5.0
New Features
New
download_data
method, to download a slice of data given an environment, time range and segment. Resulted file can be downloaded either as a CSV or a Parquet file.
3.4
3.4.0
Removed
The
get_fairness
method is removed. Please use charts and custom metrics to track / compute fairness metrics on your model.
3.3
3.3.2
Modifications
Fixed the error while setting notification config for alert rule.
3.3.1
Modifications
Added validation while adding notifications to alert rules.
Upgraded dependencies to resolve known vulnerabilities - deepdiff, mypy, pytest, pytest-mock, python-decouple, types-requests and types-simplejson.
3.3.0
New Features
Introduced
upload_feature_impact()
method to upload or update feature impact manually.
3.2
3.2.0
New Features
Introduced evaluation delay in Alerts Rule.
Optional
evaluation_delay
parameter added toAlertRule.__init__
method.It is used to introduce a delay in the evaluation of the alert.
Modifications
Fix windows file permission error bug with publish method.
3.1
3.1.2
Modifications
Adds support to get schema of Column object by
fdl.Column
3.1.1
Modifications
Updated
pydantic
andtyping-extensions
dependencies to support Python 3.12.
3.1.0
New Features
Introduced the native support for model versions.
Optional
version
parameter added toModel
,Model.from_data
,Model.from_name
methods.New
duplicate()
method to seamlessly create new version from existing model.Optional
name
parameter added toModel.list
to offer the ability to list all the versions of a model.
3.0
3.0.5
New Features
Allowed usage of
group_by()
to form the grouped data for ranking models.
3.0.4
Modifications
Return Job in ModelDeployment update.
3.0.3
New Features
Added
Webhook.from_name()
Modifications
Import path fix for packtools.
3.0.2
Modifications
Fix pydantic issue with typing-extensions versions > 4.5.0
3.0.1
New Features
General
Moving all functions of client to an Object oriented approach
Methods return resource object or a deserialized object wherever possible.
Support to search model, project, dataset, baselines by their names using
from_name()
method.List methods will return iterator which handles pagination internally.
Data
Concept of environments was introduced.
Ability to download slice data to a parquet file.
Publish dataframe as stream instead of batch.
New methods for baselines.
Multiple datasets can be added to a single model. Ability to choose which dataset to use for computing feature impact / importance, surrogate generation etc.
Model can be added without dataset.
Ability to generate schema for a model.
Model delete is async and returns job details.
Added cached properties for
model
:datasets
,model_deployment
.
Alerts
New methods for alerts:
enable_notification
,disable_notification
,set_notification_config
andget_notification_config
.
Explainability
New methods in explainability:
precompute_feature_impact
,precompute_feature_importance
,get_precomputed_feature_importance
,get_precomputed_feature_impact
,precompute_predictions
.Decoupled model artifact / surrogate upload and feature impact / importance pre-computation.
Modifications
All IDs will be UUIDs instead of strings
Dataset delete is not allowed anymore
Last updated