Bases: ABC
, ModelFactoryMixin
Main synthesizer class.
This class cannot be directly instanciated because of the specificities between RegularSynthesizer
, TimeSeriesSynthesizer
or MultiTableSynthesizer
sample
methods.
Methods
fit
: train a synthesizer instance.sample
: request synthetic data.status
: current status of the synthesizer instance.
Note
The synthesizer instance is created in the backend only when the fit
method is called.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
client |
Client
|
(optional) Client to connect to the backend |
None
|
Source code in ydata/sdk/synthesizers/synthesizer.py
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|
status: Status
property
Get the status of a synthesizer instance.
Returns:
Type | Description |
---|---|
Status
|
Synthesizer status |
uid: UID
property
fit(X, privacy_level=PrivacyLevel.HIGH_FIDELITY, datatype=None, sortbykey=None, entities=None, generate_cols=None, exclude_cols=None, dtypes=None, target=None, anonymize=None, condition_on=None)
Fit the synthesizer.
The synthesizer accepts as training dataset either a pandas DataFrame
directly or a YData DataSource
.
When the training dataset is a pandas DataFrame
, the argument datatype
is required as it cannot be deduced.
The argumentsortbykey
is mandatory for TimeSeries
.
By default, if generate_cols
or exclude_cols
are not specified, all columns are generated by the synthesizer.
The argument exclude_cols
has precedence over generate_cols
, i.e. a column col
will not be generated if it is in both list.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
X |
Union[DataSource, DataFrame]
|
Training dataset |
required |
privacy_level |
PrivacyLevel
|
Synthesizer privacy level (defaults to high fidelity) |
HIGH_FIDELITY
|
datatype |
Optional[Union[DataSourceType, str]]
|
(optional) Dataset datatype - required if |
None
|
sortbykey |
Union[str, List[str]]
|
(optional) column(s) to use to sort timeseries datasets |
None
|
entities |
Union[str, List[str]]
|
(optional) columns representing entities ID |
None
|
generate_cols |
List[str]
|
(optional) columns that should be synthesized |
None
|
exclude_cols |
List[str]
|
(optional) columns that should not be synthesized |
None
|
dtypes |
Dict[str, Union[str, DataType]]
|
(optional) datatype mapping that will overwrite the datasource metadata column datatypes |
None
|
target |
Optional[str]
|
(optional) Target for the dataset |
None
|
name |
Optional[str]
|
(optional) Synthesizer instance name |
required |
anonymize |
Optional[str]
|
(optional) fields to anonymize and the anonymization strategy |
None
|
condition_on |
Optional[List[str]]
|
(Optional[List[str]]): (optional) list of features to condition upon |
None
|
Source code in ydata/sdk/synthesizers/synthesizer.py
list(client=None)
staticmethod
List the synthesizer instances.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
client |
Client
|
(optional) Client to connect to the backend |
None
|
Returns:
Type | Description |
---|---|
SynthesizersList
|
List of synthesizers |
Source code in ydata/sdk/synthesizers/synthesizer.py
PrivacyLevel
Bases: StringEnum
Privacy level exposed to the end-user.
BALANCED_PRIVACY_FIDELITY = 'BALANCED_PRIVACY_FIDELITY'
class-attribute
instance-attribute
Balanced privacy/fidelity
HIGH_FIDELITY = 'HIGH_FIDELITY'
class-attribute
instance-attribute
High fidelity
HIGH_PRIVACY = 'HIGH_PRIVACY'
class-attribute
instance-attribute
High privacy