Changelog

NEXT RELEASE

1.5.0 - 2025/10/23

1.4.0 - 2025/10/22

1.3.0 - 2025/10/14

1.2.0 - 2025/10/08

1.1.0 - 2025/09/23

1.0.10 - 2025/09/15

1.0.9 - 2025/08/26

• BREAKING: deprecated ratio and distance thresholds

1.0.8 - 2025/07/25

• feat : add endpoint to render plots

1.0.7 - 2025/07/16

• refactor: improve results download

• fix: compliance with the new api version

1.0.6 - 2025/07/03

• fix: compliance with the new api version

1.0.5 - 2025/05/26

• fix: use specific avatar-yaml version

1.0.4 - 2025/05/20

• feat: support generating multitable reports

• feat: add advisor functionality

1.0.3 - 2025/04/30

• feat: make mandatory a set_name in the runner

1.0.2 - 2025/04/29

• BREAKING: feat: Release of the python client for the API 1.0.0 🚀 🥳.

• feat: New documentation of the python client.

0.15.0 - 2024/08/26

• feat: add tutorial on job management

• feat: add GeolocationNormalizationProcessor

• chore: remove timeout to avoid re-POST

• BREAKING: chore: remove all batch from client side

0.14.0 - 2024/08/07

• BREAKING: remove deprecated persistance_job_id

• BREAKING: remove deprecated to_categorical_threshold

0.13.0 - 2024/07/24

• BREAKING: send the total size of the stream at the start of the stream

• Remove dependency on libmagic

0.12.0 - 2024/07/05

• BREAKING: refactor: Dataset.columns is required

0.11.0 - 2024/07/01

• BREAKING: fix dataset upload

0.10.0 - 2024/06/18

• BREAKING: fix dataset upload

0.9.2 - 2024/06/11

• feat: retry any kind of network error

0.9.1 - 2024/06/10

• feat: retry on DNS resolution errors

0.9.0 - 2024/06/06

• feat: add categorical hidden rate variable to privacy parameters

• BREAKING refactor: categorical hidden rate is optional in PrivacyMetrics

0.8.0 - 2024/06/05

• BREAKING feat: add linkage methods to TableLink and make linear sum assignment the default method.

• BREAKING refactor: remove ExcludeCategoricalParameters and replace it by ExcludeVariablesParameters

0.7.4 - 2024/05/15

• Add advice for choosing avatarization parameters

• Speed up projector load and save

• Remove dataset_id from get_variable_contributions

• Add size agnostic bi-directional arrow/parquet streaming utilities

0.7.3 - 2024/04/29

• Allow passing filetype in datasets.download_dataset and pandas_integration.download_dataframe to change the format of the retrieved data

• Deprecate datasets.download_dataset_as_stream and datasets.create_dataset_from_stream

• Deprecate the ‘should_stream’ argument from pandas_integration.upload_dataframe and pandas_integration.download_dataframe

• Deprecate ‘request’ argument from datasets.create_dataset in favor of ‘source’ argument

• Add ‘destination’ argument to datasets.download_dataset

0.7.2 - 2024/04/12

• fix: remove retry logic around Job.last_updated_at

0.7.1 - 2024/04/11

• feat: overhaul client architecture

0.7.0- 2024/04/05

• fix: change shuffle multi-table process to return the right dataframe

• fix: return metric parameter error to user

• feat: return error to user if data contains ninf

• feat: improve multi-table anonymization quality (utility)

• feat: verify compatibility with server on client init

• feat: add dataset name in the multitable privacy metrics

• feat: create privacy geolocation assessment feature

• refactor: add custom methods for Datasets

• refactor: change seed place for avatarization and metrics job parameters to guarantee reproducibility

0.6.2

• feat: add should_verify_ssl to ApiClient to bypass

• refactor: revert to AvatarizationParameters.dataset_id being required

• feat: add pydantic constraints to privacy metrics fields

• feat: add multi table avatarization and privacy metrics jobs

• feat: add ‘name’ keyword argument to create_dataset

0.6.1

• feat: enable parquet format for dataset upload

• feat: use pydantic v2

• feat: add InterRecordBoundedCumulatedDifferenceProcessor

• fix: max file size error message

0.6.0

• feat: detect potential id columns

• feat: add created_at, kind to Jobs

• feat: add time series

0.5.2

• feat: add InterRecordBoundedRangeDifferenceProcessor

0.5.1

• fix: compatibility mapping due to breaking change

BREAKING CHANGE

• remove broken endpoint /projections

0.4.0

• feat: Limit the size of nb_days in find_all_jobs_by_user

• feat: implement anonymization, metrics and report generation as a batch

• feat: apply license check only during anonymization, not during upload

• fix: Prevent user from uploaded a dataframe with bool dtype

• fix: Correctly handle error on missing job

• fix: standardize metrics in the anonymization report

BREAKING CHANGE

• remove patch parameter from create_dataset

0.3.3

• Add should_stream parameter to {upload,download}_dataframe and {create,download}_dataset. This should prevent issues with timeouts during upload and download, as well as lessen the load on the server for big files.

• Add jobs.cancel_job method to cancel a job

• Add use_categorical_reduction parameter

• Add maximum password length of 128 characters

• Add report creation without avatarization job

• Remove re-raise of JSONDecodeError

• Add commit hash to generated files

• Fix: verify that known_variables and target are known when launching a privacy metrics job

• Fix: call analyze_dataset only once in notebooks

0.3.2

• catch JSONDecodeError and re-raise with more info

0.3.1

• add should_verify_ssl to allow usage of self-signed certificate on server side

• add InterRecordCumulatedDifferenceProcessor

• add InterRecordRangeDifferenceProcessor

• improve logging and error handling in avatarization_pipeline to resume easier on failure

0.3.0

BREAKING

• ReportCreate now takes required avatarization_job_id, signal_job_id, and privacy_job_id parameters

• Mark AvatarizationParameters.to_categorical_threshold as deprecated

• client.jobs.create_avatarization_job behaviour does not compute metrics anymore. Use client.jobs.create_full_avatarization_job instead

• AvatarizationResult now has signal_metrics and privacy_metrics properties as Optional

• Verify dataset size on upload. This will prevent you from uploading a dataset that is too big to handle for the server

• The direct_match_protection privacy metrics got renamed to column_direct_match_protection

• dataset_id from AvatarizationParameters is now required

• dataset_id from AvatarizationJob,SignalMetricsJob and PrivacyMetricsJob got removed

• client.users.get_user now accepts an id rather than a username

• SignalMetricsParameters.job_id got renamed to persistance_job_id

• CreateUser does not take is_email_confirmed as parameter anymore

• Processors get imported from avatars.processors instead of avatars.processor.{processor_name}

  • Example: from avatars.processors.expected_mean import ExpectedMeanProcessor becomes from avatars.processors import ExpectedMeanProcessor

Others

• feat: add more metrics and graphs to report

• feat: add client.compatibility.is_client_compatible to verify client-server compatibility

• feat: enable to avatarize without calculating metrics using client.jobs.create_avatarization_job

• feat: add nb_dimensions property to Dataset

• feat: add User object

• feat: use patch in client.datasets.create_dataset to patch dataset columns on upload

• feat: add correlation_protection_rate, inference_continuous, inference_categorical, row_direct_match_protection and closest_rate privacy metrics

• feat: add known_variables, target, closest_rate_percentage_threshold, and closest_rate_ratio_threshold to PrivacyMetricsParameters

• docs: add multiple versions of the documentation

• feat: each user now belongs to an organization and gets a new field: organization_id

• fix: fixed a bug where computing privacy metrics with distinct missing values was impossible

0.2.2

• Improve type hints of the method

• Update tutorial notebooks with smaller datasets

• Fix bugs in tutorial notebooks

• Improve error message when the call to the API times out

• Add jobs.find_all_jobs_by_user

• Add two new privacy metrics: direct_match_protection and categorical_hidden_rate

• Add the DatetimeProcessor

0.2.1

• Fix to processor taking the wrong number of arguments

• Make the toolz package a mandatory dependency

• Fix a handling of a target variable equaling zero

0.2.0

• Drop support for python3.8 # BREAKING CHANGE

• Drop jobs.get_job and job.create_job. # BREAKING CHANGE

• Rename DatasetResponse to Dataset # BREAKING CHANGE

• Rename client.pandas to client.pandas_integration # BREAKING CHANGE

• Add separate endpoint to compute metrics separately using jobs.create_signal_metrics_job and jobs.create_privacy_metrics_job.

• Add separate endpoint to access metrics jobs using jobs.get_signal_metrics and job.get_privacy_metrics

• Add processors to pre- and post-process your data before, and after avatarization for custom use-cases. These are accessible under avatars.processors.

• Handle errors more gracefully

• Add ExcludeCategoricalParameters to use embedded processor on the server side

0.1.16

• Add forgotten password endpoint

• Add reset password endpoint

• JobParameters becomes AvatarizationParameters

• Add DCR and NNDR to privacy metrics

0.1.15

• Handle category dtype

• Fix dtype casting of datetime columns

• Add ability to login with email

• Add filtering options to find_users

• Avatarizations are now called with create_avatarization_job and AvatarizationJobCreate. create_job and JobCreate are deprecated but still work.

• dataset_id is now passed to AvatarizationParameters and not AvatarizationJobCreate.

• Job.dataset_id is deprecated. Use Job.parameters.dataset_id instead.

BREAKING

• Remove get_health_config call.

0.1.14

• Give access to avatars unshuffled avatars dataset

0.1.13

• Remove default value for to_categorical_threshold

• Use logger.info instead of print