path: root/python-sdv.spec

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Name:		python-sdv
Version:	1.0.0
Release:	1
Summary:	Generate synthetic data for single table, multi table and sequential data
License:	BSL-1.1
URL:		https://github.com/sdv-dev/SDV
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/1d/22/67ed3daefd3dca25ea1bdbc0e9d329438fa0ec93f39076e1d720ff0455ad/sdv-1.0.0.tar.gz
BuildArch:	noarch

Requires:	python3-Faker
Requires:	python3-graphviz
Requires:	python3-tqdm
Requires:	python3-copulas
Requires:	python3-ctgan
Requires:	python3-deepecho
Requires:	python3-rdt
Requires:	python3-sdmetrics
Requires:	python3-cloudpickle
Requires:	python3-boto3
Requires:	python3-botocore
Requires:	python3-numpy
Requires:	python3-pandas
Requires:	python3-numpy
Requires:	python3-pandas
Requires:	python3-bumpversion
Requires:	python3-pip
Requires:	python3-watchdog
Requires:	python3-docutils
Requires:	python3-m2r2
Requires:	python3-nbsphinx
Requires:	python3-sphinx-toolbox
Requires:	python3-Sphinx
Requires:	python3-pydata-sphinx-theme
Requires:	python3-markupsafe
Requires:	python3-Jinja2
Requires:	python3-flake8
Requires:	python3-flake8-absolute-import
Requires:	python3-flake8-builtins
Requires:	python3-flake8-comprehensions
Requires:	python3-flake8-debugger
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Requires:	python3-flake8-mock
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Requires:	python3-flake8-mutable
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Requires:	python3-flake8-print
Requires:	python3-flake8-pytest-style
Requires:	python3-flake8-quotes
Requires:	python3-flake8-sfs
Requires:	python3-flake8-variables-names
Requires:	python3-dlint
Requires:	python3-isort
Requires:	python3-pandas-vet
Requires:	python3-pep8-naming
Requires:	python3-pydocstyle
Requires:	python3-autoflake
Requires:	python3-autopep8
Requires:	python3-twine
Requires:	python3-wheel
Requires:	python3-coverage
Requires:	python3-tox
Requires:	python3-invoke
Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-pytest-rerunfailures
Requires:	python3-jupyter
Requires:	python3-rundoc
Requires:	python3-pomegranate
Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-pytest-rerunfailures
Requires:	python3-jupyter
Requires:	python3-rundoc

%description
<div align="center">
  <a href="https://datacebo.com"><picture>
      <source media="(prefers-color-scheme: dark)" srcset="https://github.com/sdv-dev/SDV/blob/master/docs/images/datacebo-logo-dark-mode.png">
      <img align="center" width=40% src="https://github.com/sdv-dev/SDV/blob/master/docs/images/datacebo-logo.png"></img>
  </picture></a>
</div>
<br/>
<br/>
[The Synthetic Data Vault Project](https://sdv.dev) was first created at MIT's [Data to AI Lab](
https://dai.lids.mit.edu/) in 2016. After 4 years of research and traction with enterprise, we
created [DataCebo](https://datacebo.com) in 2020 with the goal of growing the project.
Today, DataCebo is the proud developer of SDV, the largest ecosystem for
synthetic data generation & evaluation. It is home to multiple libraries that support synthetic
data, including:
* 🔄 Data discovery & transformation. Reverse the transforms to reproduce realistic data.
* 🧠 Multiple machine learning models -- ranging from Copulas to Deep Learning -- to create tabular,
  multi table and time series data.
* 📊 Measuring quality and privacy of synthetic data, and comparing different synthetic data
  generation models.
[Get started using the SDV package](https://bit.ly/sdv-docs) -- a fully
integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
for specific needs.
# Release Notes
## 1.0.0 - 2023-03-28
This is a major release that introduces a new API to the `SDV` aimed at streamlining the process of synthetic data generation! To achieve this, this release includes the addition of several large features.
### Metadata
Some of the most notable additions are the new `SingleTableMetadata` and `MultiTableMetadata` classes. These classes enable a number of features that make it easier to synthesize your data correctly such as:
* Automatic data detection - Calling `metadata.detect_from_dataframe()` or `metadata.detect_from_csv()` will populate the metadata autonomously with values it thinks represent the data.
* Easy updating - Once an instance of the metadata is created, values can be easily updated using a number of methods defined in the API. For more info, view the [docs](https://docs.sdv.dev/sdv/single-table-data/data-preparation/single-table-metadata-api).
* Metadata validation - Calling `metadata.validate()` will return a report of any invalid definitions in the metadata specification.
* Upgrading - Users with the previous metadata format can easily update to the new specification using the `upgrade_metadata()` method.
* Saving and loading - The metadata itself can easily be saved to a json file and loaded back up later.
### Class and Module Names
Another major change is the renaming of our core modeling classes and modules. The name changes are meant to highlight the difference between the underlying machine learning models, and the objects responsible for the end-to-end workflow of generating synthetic data. The main name changes are as follows:
* `tabular` -> `single_table`
* `relational` -> `multi_table`
* `timeseries` -> `sequential`
* `BaseTabularModel` -> `BaseSingleTableSynthesizer`
* `GaussianCopula` -> `GaussianCopulaSynthesizer`
* `CTGAN` -> `CTGANSynthesizer`
* `TVAE` -> `TVAESynthesizer`
* `CopulaGan` -> `CopulaGANSynthesizer`
* `PAR` -> `PARSynthesizer`
* `HMA1` -> `HMASynthesizer`
In `SDV` 1.0, synthesizers are classes that take in metadata and handle data preprocessing, model training and model sampling. This is similar to the previous `BaseTabularModel` in `SDV` <1.0.
### Synthetic Data Workflow
`Synthesizers` in `SDV` 1.0 define a clear workflow for generating synthetic data.
1. Synthesizers are initialized with a metadata class.
2. They can then be used to transform the data and apply constraints using the `synthesizer.preprocess()` method. This step also validates that the data matches the provided metadata to avoid errors in fitting or sampling.
3. The processed data can then be fed into the underlying machine learning model using `synthesizer.fit_processed_data()`. (Alternatively, data can be preprocessed and fit to the model using `synthesizer.fit()`.)
4. Data can then be sampled using `synthesizer.sample()`.
Each synthesizer class also provides a series of methods to help users customize the transformations their data goes through. Read more about that [here](https://docs.sdv.dev/sdv/single-table-data/modeling/synthetic-data-workflow/transform-and-anonymize).
Notice that the preprocessing and model fitting steps can now be separated. This can be helpful if preprocessing is time consuming or if the data has been processed externally.
### Other Highly Requested Features
Another major addition is control over randomization. In `SDV` <1.0, users could set a seed to control the randomization for only some columns. In `SDV` 1.0, randomization is controlled for all columns. Every new call to sample generates new data, but the synthesizer's seed can be reset to the original state using `synthesizer.reset_randomization()`, enabling reproducibility.
`SDV 1.0` adds accessibility and transparency into the transformers used for preprocessing and underlying machine learning models.
* Using the `synthesizer.get_transformers()` method, you can access the transformers used to preprocess each column and view their properties. This can be useful for debugging and accessing privacy information like mappings used to mask data.
* Distribution parameters learned by copula models can be accessed using the `synthesizer.get_learned_distributions()` method.
PII handling is improved by the following features:
* Primary keys can be set to natural sdtypes (eg. SSN, email, name). Previously they could only be numerical or text.
* The `PseudoAnonymizedFaker` can be used to provide consistent mapping to PII columns. As mentioned before, the mapping itself can be accessed by viewing the transformers for the column using `synthesizer.get_transformers()`.
* A bug causing PII columns to slow down modeling is patched.
Finally, the synthetic data can now be easily evaluated using the `evaluate_quality()` and `run_diagnostic()` methods. The data can be compared visually to the actual data using the `get_column_plot()` and `get_column_pair_plot()` methods. For more info on how to visualize or interpret the synthetic data evaluation, read the docs [here](https://docs.sdv.dev/sdv/single-table-data/evaluation).
### Issues Resolved
#### New Features
* Change auto_assign_transformers to handle id types - Issue [#1325](https://github.com/sdv-dev/SDV/issues/1325) by @pvk-developer
* Change 'text' sdtype to 'id' - Issue [#1324](https://github.com/sdv-dev/SDV/issues/1324) by @frances-h
* In `upgrade_metadata`, return the object instead of writing it to a JSON file - Issue [#1319](https://github.com/sdv-dev/SDV/issues/1319) by @frances-h
* In `upgrade_metadata` index primary keys should be converted to `text` - Issue [#1318](https://github.com/sdv-dev/SDV/issues/1318) by @amontanez24
* Add `load_from_dict` to SingleTableMetadata and MultiTableMetadata - Issue [#1314](https://github.com/sdv-dev/SDV/issues/1314) by @amontanez24
* Throw a `SynthesizerInputError` if `FixedCombinations` constraint is applied to a column that is not `boolean` or `categorical` - Issue [#1306](https://github.com/sdv-dev/SDV/issues/1306) by @frances-h
* Missing `save` and `load` methods for `HMASynthesizer` - Issue [#1262](https://github.com/sdv-dev/SDV/issues/1262) by @amontanez24
* Better input validation when creating single and multi table synthesizers - Issue [#1242](https://github.com/sdv-dev/SDV/issues/1242) by @fealho
* Better input validation on `HMASynthesizer.sample` - Issue [#1241](https://github.com/sdv-dev/SDV/issues/1241) by @R-Palazzo
* Validate that relationship must be between a `primary key` and `foreign key` - Issue [#1236](https://github.com/sdv-dev/SDV/issues/1236) by @fealho
* Improve `update_column` validation for `pii` attribute - Issue [#1226](https://github.com/sdv-dev/SDV/issues/1226) by @pvk-developer
* Order the output of `get_transformers()` based on the metadata - Issue [#1222](https://github.com/sdv-dev/SDV/issues/1222) by @pvk-developer
* Log if any `numerical_distributions` will not be applied - Issue [#1212](https://github.com/sdv-dev/SDV/issues/1212) by @fealho
* Improve error handling for `GaussianCopulaSynthesizer`: `numerical_distributions` - Issue [#1211](https://github.com/sdv-dev/SDV/issues/1211) by @fealho
* Improve error handling when validating `constraints` - Issue [#1210](https://github.com/sdv-dev/SDV/issues/1210) by @fealho
* Add `fake_companies` demo - Issue [#1209](https://github.com/sdv-dev/SDV/issues/1209) by @amontanez24
* Allow me to create a custom constraint class and use it in the same file - Issue [#1205](https://github.com/sdv-dev/SDV/issues/1205) by @amontanez24
* Sampling should reset after retraining the model - Issue [#1201](https://github.com/sdv-dev/SDV/issues/1201) by @pvk-developer
* Change function name `HMASynthesizer.update_table_parameters` --> `set_table_parameters` - Issue [#1200](https://github.com/sdv-dev/SDV/issues/1200) by @pvk-developer
* Add `get_info` method to synthesizers - Issue [#1199](https://github.com/sdv-dev/SDV/issues/1199) by @fealho
* Add evaluation methods to synthesizer - Issue [#1190](https://github.com/sdv-dev/SDV/issues/1190) by @fealho
* Update `evaluate.py` to work with the new `metadata` - Issue [#1186](https://github.com/sdv-dev/SDV/issues/1186) by @fealho
* Remove old code - Issue [#1181](https://github.com/sdv-dev/SDV/issues/1181) by @pvk-developer
* Drop support for python 3.6 and add support for 3.10 - Issue [#1176](https://github.com/sdv-dev/SDV/issues/1176) by @fealho
* Add constraint methods to MultiTableSynthesizers - Issue [#1171](https://github.com/sdv-dev/SDV/issues/1171) by @fealho
* Update custom constraint workflow - Issue [#1169](https://github.com/sdv-dev/SDV/issues/1169) by @pvk-developer
* Add get_constraints method to synthesizers - Issue [#1168](https://github.com/sdv-dev/SDV/issues/1168) by @pvk-developer
* Migrate adding and validating constraints to BaseSynthesizer - Issue [#1163](https://github.com/sdv-dev/SDV/issues/1163) by @pvk-developer
* Change metadata `"SCHEMA_VERSION"` --> `"METADATA_SPEC_VERSION"` - Issue [#1139](https://github.com/sdv-dev/SDV/issues/1139) by @amontanez24
* Add ability to reset random sampling - Issue [#1130](https://github.com/sdv-dev/SDV/issues/1130) by @pvk-developer
* Add get_available_demos - Issue [#1129](https://github.com/sdv-dev/SDV/issues/1129) by @fealho
* Add demo loading functionality - Issue [#1128](https://github.com/sdv-dev/SDV/issues/1128) by @fealho
* Use logging instead of printing in detect methods - Issue [#1107](https://github.com/sdv-dev/SDV/issues/1107) by @fealho
* Add save and load methods to synthesizers - Issue [#1106](https://github.com/sdv-dev/SDV/issues/1106) by @pvk-developer
* Add sampling methods to PARSynthesizer - Issue [#1083](https://github.com/sdv-dev/SDV/issues/1083) by @amontanez24
* Add transformer methods to PARSynthesizer - Issue [#1082](https://github.com/sdv-dev/SDV/issues/1082) by @fealho
* Add validate to PARSynthesizer - Issue [#1081](https://github.com/sdv-dev/SDV/issues/1081) by @amontanez24
* Add preprocess and fit methods to PARSynthesizer - Issue [#1080](https://github.com/sdv-dev/SDV/issues/1080) by @amontanez24
* Create SingleTablePreset - Issue [#1079](https://github.com/sdv-dev/SDV/issues/1079) by @amontanez24
* Add sample method to multi-table synthesizers - Issue [#1078](https://github.com/sdv-dev/SDV/issues/1078) by @pvk-developer
* Add get_learned_distributions method to synthesizers - Issue [#1075](https://github.com/sdv-dev/SDV/issues/1075) by @pvk-developer
* Add preprocess and fit methods to multi-table synthesizers - Issue [#1074](https://github.com/sdv-dev/SDV/issues/1074) by @pvk-developer
* Add transformer related methods to BaseMultiTableSynthesizer - Issue [#1072](https://github.com/sdv-dev/SDV/issues/1072) by @fealho
* Add validate method to `BaseMultiTableSynthesizer` - Issue [#1071](https://github.com/sdv-dev/SDV/issues/1071) by @pvk-developer
* Create BaseMultiTableSynthesizer and HMASynthesizer classes - Issue [#1070](https://github.com/sdv-dev/SDV/issues/1070) by @pvk-developer
* Create PARSynthesizer - Issue [#1055](https://github.com/sdv-dev/SDV/issues/1055) by @amontanez24
* Raise an error if an invalid sdtype is provided to the metadata - Issue [#1042](https://github.com/sdv-dev/SDV/issues/1042) by @amontanez24
* Only allow datetime and numerical sdtypes to be set as the sequence index - Issue [#1030](https://github.com/sdv-dev/SDV/issues/1030) by @amontanez24
* Change set_alternate_keys to add_alternate_keys and add error handling - Issue [#1029](https://github.com/sdv-dev/SDV/issues/1029) by @amontanez24
* Create `MultiTableMetadata.add_table` method - Issue [#1024](https://github.com/sdv-dev/SDV/issues/1024) by @amontanez24
* Add update_transformers to synthesizers - Issue [#1021](https://github.com/sdv-dev/SDV/issues/1021) by @fealho
* Add assign_transformers and get_transformers methods to synthesizers - Issue [#1020](https://github.com/sdv-dev/SDV/issues/1020) by @pvk-developer
* Add fit and fit_processed_data methods to synthesizers - Issue [#1019](https://github.com/sdv-dev/SDV/issues/1019) by @pvk-developer
* Add preprocess method to synthesizers - Issue [#1018](https://github.com/sdv-dev/SDV/issues/1018) by @pvk-developer
* Add sampling to synthesizer classes - Issue [#1015](https://github.com/sdv-dev/SDV/issues/1015) by @pvk-developer
* Add validate method to synthesizer - Issue [#1014](https://github.com/sdv-dev/SDV/issues/1014) by @fealho
* Create GaussianCopula, CTGAN, TVAE and CopulaGAN synthesizer classes - Issue [#1013](https://github.com/sdv-dev/SDV/issues/1013) by @pvk-developer
* Create BaseSynthesizer class - Issue [#1012](https://github.com/sdv-dev/SDV/issues/1012) by @pvk-developer
* Add constraint conversion to upgrade_metadata - Issue [#1005](https://github.com/sdv-dev/SDV/issues/1005) by @amontanez24
* Add method to generate keys to DataProcessor - Issue [#994](https://github.com/sdv-dev/SDV/issues/994) by @pvk-developer
* Create formatter - Issue [#970](https://github.com/sdv-dev/SDV/issues/970) by @fealho
* Create a utility to load multiple CSV files at once - Issue [#969](https://github.com/sdv-dev/SDV/issues/969) by @amontanez24
* Create a utility to convert old --> new metadata format - Issue [#966](https://github.com/sdv-dev/SDV/issues/966) by @amontanez24
* Add validation check that `primary_key`, `alternate_keys` and `sequence_key` cannot be sdtype categorical - Issue [#963](https://github.com/sdv-dev/SDV/issues/963) by @fealho
* Add anonymization to DataProcessor - Issue [#950](https://github.com/sdv-dev/SDV/issues/950) by @pvk-developer
* Add utility methods to DataProcessor - Issue [#948](https://github.com/sdv-dev/SDV/issues/948) by @fealho
* Add fit, transform and reverse_transform to DataProcessor - Issue [#947](https://github.com/sdv-dev/SDV/issues/947) by @amontanez24
* Create DataProcessor class - Issue [#946](https://github.com/sdv-dev/SDV/issues/946) by @amontanez24
* Add add_constraint method to MultiTableMetadata - Issue [#895](https://github.com/sdv-dev/SDV/issues/895) by @amontanez24
* Add key related methods to MultiTableMetadata - Issue [#894](https://github.com/sdv-dev/SDV/issues/894) by @fealho
* Add update_column and add_column methods to MultiTableMetadata - Issue [#893](https://github.com/sdv-dev/SDV/issues/893) by @amontanez24
* Add detect methods to MultiTableMetadata - Issue [#892](https://github.com/sdv-dev/SDV/issues/892) by @amontanez24
* Add load_from_json and save_to_json methods to the MultiTableMetadata - Issue [#891](https://github.com/sdv-dev/SDV/issues/891) by @fealho
* Add add_relationship method to MultiTableMetadata - Issue [#890](https://github.com/sdv-dev/SDV/issues/890) by @pvk-developer
* Add validate method to MultiTableMetadata - Issue [#888](https://github.com/sdv-dev/SDV/issues/888) by @pvk-developer
* Add visualize method to MultiTableMetadata class - Issue [#884](https://github.com/sdv-dev/SDV/issues/884) by @amontanez24
* Create MultiTableMetadata class - Issue [#883](https://github.com/sdv-dev/SDV/issues/883) by @pvk-developer
* Add add_constraint method to SingleTableMetadata - Issue [#881](https://github.com/sdv-dev/SDV/issues/881) by @amontanez24
* Add key related methods to SingleTableMetadata - Issue [#880](https://github.com/sdv-dev/SDV/issues/880) by @fealho
* Add validate method to SingleTableMetadata - Issue [#879](https://github.com/sdv-dev/SDV/issues/879) by @fealho
* Add _validate_inputs class method to each constraint - Issue [#878](https://github.com/sdv-dev/SDV/issues/878) by @fealho
* Add update_column and add_column methods to SingleTableMetadata - Issue [#877](https://github.com/sdv-dev/SDV/issues/877) by @pvk-developer
* Add detect methods to SingleTableMetadata - Issue [#876](https://github.com/sdv-dev/SDV/issues/876) by @pvk-developer
* Add load_from_json and save_to_json methods to SingleTableMetadata - Issue [#874](https://github.com/sdv-dev/SDV/issues/874) by @pvk-developer
* Create SingleTableMetadata class - Issue [#873](https://github.com/sdv-dev/SDV/issues/873) by @pvk-developer
#### Bugs Fixed
* In `upgrade_metadata`, PII values are being converted to generic categorical columns - Issue [#1317](https://github.com/sdv-dev/SDV/issues/1317) by @frances-h
* `PARSynthesizer` is missing `save` and `load` methods - Issue [#1289](https://github.com/sdv-dev/SDV/issues/1289) by @amontanez24
* Confusing warning when updating transformers - Issue [#1272](https://github.com/sdv-dev/SDV/issues/1272) by @frances-h
* When adding constraints, `auto_assign_transformers` is showing columns that should no longer exist - Issue [#1260](https://github.com/sdv-dev/SDV/issues/1260) by @pvk-developer
* Cannot fit twice if I modify transformers: `ValueError: There are non-numerical values in your data.` - Issue [#1259](https://github.com/sdv-dev/SDV/issues/1259) by @frances-h
* Cannot fit twice if I add constraints: `ValueError: There are non-numerical values in your data.` - Issue [#1258](https://github.com/sdv-dev/SDV/issues/1258) by @frances-h
* `HMASynthesizer` errors out when fitting a dataset that has a table which holds primary key and foreign keys only - Issue [#1257](https://github.com/sdv-dev/SDV/issues/1257) by @pvk-developer
* Change ValueErrors to InvalidMetadataErrors - Issue [#1251](https://github.com/sdv-dev/SDV/issues/1251) by @frances-h
* Multi-table should show foreign key transformers as None - Issue [#1249](https://github.com/sdv-dev/SDV/issues/1249) by @frances-h
* Cannot use `HMASynthesizer.fit_processed_data` more than once (`KeyError`) - Issue [#1240](https://github.com/sdv-dev/SDV/issues/1240) by @frances-h
* Function `get_available_demos` crashes if a dataset's `num-tables` or `size-MB` cannot be found - Issue [#1215](https://github.com/sdv-dev/SDV/issues/1215) by @amontanez24
* Cannot supply a natural key to `HMASynthesizer` (where `sdtype` is custom): Error in `sample` - Issue [#1214](https://github.com/sdv-dev/SDV/issues/1214) by @pvk-developer
* Unable to sample when using a `PseudoAnonymizedFaker` - Issue [#1207](https://github.com/sdv-dev/SDV/issues/1207) by @pvk-developer
* Incorrect `sdtype` specified in demo dataset `student_placements_pii` - Issue [#1206](https://github.com/sdv-dev/SDV/issues/1206) by @amontanez24
* Auto assigned transformers for datetime columns don't have the right parameters - Issue [#1204](https://github.com/sdv-dev/SDV/issues/1204) by @pvk-developer
* Cannot apply `Inequality` constraint on demo dataset's datetime columns - Issue [#1203](https://github.com/sdv-dev/SDV/issues/1203) by @pvk-developer
* pii should not be required to auto-assign faker transformers - Issue [#1194](https://github.com/sdv-dev/SDV/issues/1194) by @pvk-developer
* Misc. bug fixes for SDV 1.0.0 - Issue [#1193](https://github.com/sdv-dev/SDV/issues/1193) by @pvk-developer
* Small bug fixes in demo module - Issue [#1192](https://github.com/sdv-dev/SDV/issues/1192) by @pvk-developer
* Foreign Keys are added as Alternate Keys when upgrading - Issue [#1143](https://github.com/sdv-dev/SDV/issues/1143) by @pvk-developer
* Alternate keys not unique when assigned to a semantic type - Issue [#1111](https://github.com/sdv-dev/SDV/issues/1111) by @pvk-developer
* Synthesizer errors if column is semantic type and pii is False - Issue [#1110](https://github.com/sdv-dev/SDV/issues/1110) by @fealho
* Sampled values not unique if primary key is numerical - Issue [#1109](https://github.com/sdv-dev/SDV/issues/1109) by @pvk-developer
* Validate not called during synthesizer creation - Issue [#1105](https://github.com/sdv-dev/SDV/issues/1105) by @pvk-developer
* SingleTableSynthesizer fit doesn't update rounding - Issue [#1104](https://github.com/sdv-dev/SDV/issues/1104) by @amontanez24
* Method `auto_assign_tranformers` always sets `enforce_min_max_values=True` - Issue [#1095](https://github.com/sdv-dev/SDV/issues/1095) by @fealho
* Sampled context columns in PAR must be in the same order - Issue [#1052](https://github.com/sdv-dev/SDV/issues/1052) by @amontanez24
* Incorrect schema version printing during detect_table_from_dataframe - Issue [#1038](https://github.com/sdv-dev/SDV/issues/1038) by @amontanez24
* Same relationship can be added twice to MultiTableMetadata - Issue [#1031](https://github.com/sdv-dev/SDV/issues/1031) by @amontanez24
* Miscellaneous metadata bugs - Issue [#1026](https://github.com/sdv-dev/SDV/issues/1026) by @amontanez24
#### Maintenance
* SDV Package Maintenance Updates - Issue [#1140](https://github.com/sdv-dev/SDV/issues/1140) by @amontanez24
#### Internal
* Add integration tests for 'Synthesize Sequences' demo - Issue [#1295](https://github.com/sdv-dev/SDV/issues/1295) by @pvk-developer
* Add integration tests for 'Adding Constraints' demo - Issue [#1280](https://github.com/sdv-dev/SDV/issues/1280) by @pvk-developer
* Add integration tests to the 'Use Your Own Data' demo - Issue [#1278](https://github.com/sdv-dev/SDV/issues/1278) by @frances-h
* Add integration tests for 'Synthesize Multi Tables' demo - Issue [#1277](https://github.com/sdv-dev/SDV/issues/1277) by @pvk-developer
* Add integration tests for 'Synthesize a Table' demo - Issue [#1276](https://github.com/sdv-dev/SDV/issues/1276) by @frances-h
* Update `get_available_demos` tests - Issue [#1247](https://github.com/sdv-dev/SDV/issues/1247) by @fealho
* Make private attributes public in the metadata - Issue [#1245](https://github.com/sdv-dev/SDV/issues/1245) by @fealho
## 0.18.0 - 2023-01-24
This release adds suppport for Python 3.10 and drops support for 3.6.
### Maintenance
* Drop support for python 3.6 - Issue [#1177](https://github.com/sdv-dev/SDV/issues/1177) by @amontanez24
* Support for python 3.10 - Issue [#939](https://github.com/sdv-dev/SDV/issues/939) by @amontanez24
* Support Python >=3.10,<4 - Issue [#1000](https://github.com/sdv-dev/SDV/issues/1000) by @amontanez24
## 0.17.2 - 2022-12-08
This release fixes a bug in the demo module related to loading the demo data with constraints. It also adds a name to the demo datasets. Finally, it bumps the version of `SDMetrics` used.
### Maintenance
* Upgrade SDMetrics requirement to 0.8.0 - Issue [#1125](https://github.com/sdv-dev/SDV/issues/1125) by @katxiao
### New Features
* Provide a name for the default demo datasets - Issue [#1124](https://github.com/sdv-dev/SDV/issues/1124) by @amontanez24
### Bugs Fixed
* Cannot load_tabular_demo with metadata - Issue [#1123](https://github.com/sdv-dev/SDV/issues/1123) by @amontanez24
## 0.17.1 - 2022-09-29
This release bumps the dependency requirements to use the latest version of `SDMetrics`.
### Maintenance
* Patch release: Bump required version for SDMetrics - Issue [#1010](https://github.com/sdv-dev/SDV/issues/1010) by @katxiao
## 0.17.0 - 2022-09-09
This release updates the code to use RDT version 1.2.0 and greater, so that those new features are now available in SDV. This changes the transformers that are available in SDV models to be those that are in RDT version 1.2.0. As a result, some arguments for initializing models have changed.
Additionally, this release fixes bugs related to loading models with custom constraints. It also fixes a bug that added `NaNs` to the index of sampled data when using `sample_remaining_columns`.
### Bugs Fixed
* Incorrect rounding in Custom Constraint example - Issue [#941](https://github.com/sdv-dev/SDV/issues/941) by @amontanez24
* Can't save the model if use the custom constraint - Issue [#928](https://github.com/sdv-dev/SDV/issues/928) by @pvk-developer
* User Guide code fixes - Issue [#983](https://github.com/sdv-dev/SDV/issues/983) by @amontanez24
* Index contains NaNs when using sample_remaining_columns - Issue [#985](https://github.com/sdv-dev/SDV/issues/985) by @amontanez24
* Cannot sample after loading a model with custom constraints: TypeError - Issue [#984](https://github.com/sdv-dev/SDV/issues/984) by @pvk-developer
* Set HyperTransformer config manually, based on Metadata if given - Issue [#982](https://github.com/sdv-dev/SDV/issues/982) by @pvk-developer
### New Features
* Change default metrics for evaluate - Issue [#949](https://github.com/sdv-dev/SDV/issues/949) by @fealho
### Maintenance
* Update the RDT version to 1.0 - Issue [#897](https://github.com/sdv-dev/SDV/issues/897) by @pvk-developer
## 0.16.0 - 2022-07-21
This release brings user friendly improvements and bug fixes on the `SDV` constraints, to help
users generate their synthetic data easily.
Some predefined constraints have been renamed and redefined to be more user friendly & consistent.
The custom constraint API has also been updated for usability. The SDV now automatically determines
the best `handling_strategy` to use for each constraint, attempting `transform` by default and
falling back to `reject_sampling` otherwise. The `handling_strategy` parameters are no longer
included in the API.
Finally, this version of `SDV` also unifies the parameters for all sampling related methods for
all models (including TabularPreset).
### Changes to Constraints
* `GreatherThan` constraint is now separated in two new constraints: `Inequality`, which is
  intended to be used between two columns, and `ScalarInequality`, which is intended to be used
  between a column and a scalar.
* `Between` constraint is now separated in two new constraints: `Range`, which is intended to
  be used between three columns, and `ScalarRange`, which is intended to be used between a column
  and low and high scalar values.
* `FixedIncrements` a new constraint that makes the data increment by a certain value.
* New `create_custom_constraint` function available to create custom constraints.
### Removed Constraints
* `Rounding` Rounding is automatically being handled by the ``rdt.HyperTransformer``.
* `ColumnFormula` the `create_custom_constraint` takes place over this one and allows more
  advanced usage for the end users.
### New Features
* Improve error message for invalid constraints - Issue [#801](https://github.com/sdv-dev/SDV/issues/801) by @fealho
* Numerical Instability in Constrained GaussianCopula - Issue [#806](https://github.com/sdv-dev/SDV/issues/806) by @fealho
* Unify sampling params for reject sampling - Issue [#809](https://github.com/sdv-dev/SDV/issues/809) by @amontanez24
* Split `GreaterThan` constraint into `Inequality` and `ScalarInequality` - Issue [#814](https://github.com/sdv-dev/SDV/issues/814) by @fealho
* Split `Between` constraint into `Range` and `ScalarRange` - Issue [#815](https://github.com/sdv-dev/SDV/issues/815) @pvk-developer
* Change `columns` to `column_names` in `OneHotEncoding` and `Unique` constraints - Issue [#816](https://github.com/sdv-dev/SDV/issues/816) by @amontanez24
* Update columns parameter in `Positive` and `Negative` constraint - Issue [#817](https://github.com/sdv-dev/SDV/issues/817) by @fealho
* Create `FixedIncrements` constraint - Issue [#818](https://github.com/sdv-dev/SDV/issues/818) by @amontanez24
* Improve datetime handling in `ScalarInequality` and `ScalarRange` constraints - Issue [#819](https://github.com/sdv-dev/SDV/issues/819) by @pvk-developer
* Support strict boundaries even when transform strategy is used - Issue [#820](https://github.com/sdv-dev/SDV/issues/820) by @fealho
* Add `create_custom_constraint` factory method - Issue [#836](https://github.com/sdv-dev/SDV/issues/836) by @fealho
### Internal Improvements
* Remove `handling_strategy` parameter - Issue [#833](https://github.com/sdv-dev/SDV/issues/833) by @amontanez24
* Remove `fit_columns_model` parameter - Issue [#834](https://github.com/sdv-dev/SDV/issues/834) by @pvk-developer
* Remove the `ColumnFormula` constraint - Issue [#837](https://github.com/sdv-dev/SDV/issues/837) by @amontanez24
* Move `table_data.copy` to base class of constraints - Issue [#845](https://github.com/sdv-dev/SDV/issues/845) by @fealho
### Bugs Fixed
* Numerical Instability in Constrained GaussianCopula - Issue [#801](https://github.com/sdv-dev/SDV/issues/801) by @tlranda and @fealho
* Fix error message for `FixedIncrements` - Issue [#865](https://github.com/sdv-dev/SDV/issues/865) by @pvk-developer
* Fix constraints with conditional sampling - Issue [#866](https://github.com/sdv-dev/SDV/issues/866) by @amontanez24
* Fix error message in `ScalarInequality` - Issue [#868](https://github.com/sdv-dev/SDV/issues/868) by @pvk-developer
* Cannot use `max_tries_per_batch` on sample: `TypeError: sample() got an unexpected keyword argument 'max_tries_per_batch'` - Issue [#885](https://github.com/sdv-dev/SDV/issues/885) by @amontanez24
* Conditional sampling + batch size: `ValueError: Length of values (1) does not match length of index (5)` - Issue [#886](https://github.com/sdv-dev/SDV/issues/886) by @amontanez24
* `TabularPreset` doesn't support new sampling parameters - Issue [#887](https://github.com/sdv-dev/SDV/issues/887) by @fealho
* Conditional Sampling: `batch_size` is being set to `None` by default? - Issue [#889](https://github.com/sdv-dev/SDV/issues/889) by @amontanez24
* Conditional sampling using GaussianCopula inefficient when categories are noised - Issue [#910](https://github.com/sdv-dev/SDV/issues/910) by @amontanez24
### Documentation Changes
* Show the `API` for `TabularPreset` models - Issue [#854](https://github.com/sdv-dev/SDV/issues/854) by @katxiao
* Update handling constraints doc - Pull Request [#856](https://github.com/sdv-dev/SDV/issues/856) by @amontanez24
* Update custom costraints documentation - Pull Request [#857](https://github.com/sdv-dev/SDV/issues/857) by @pvk-developer
## 0.15.0 - 2022-05-25
This release improves the speed of the `GaussianCopula` model by removing logic that previously searched for the appropriate distribution to
use. It also fixes a bug that was happening when conditional sampling was used with the `TabularPreset`.
The rest of the release focuses on making changes to improve constraints including changing the `UniqueCombinations` constraint to `FixedCombinations`,
making the `Unique` constraint work with missing values and erroring when null values are seen in the `OneHotEncoding` constraint.
### New Features
* Silence warnings coming from univariate fit in copulas - Issue [#769](https://github.com/sdv-dev/SDV/issues/769) by @pvk-developer
* Remove parameters related to distribution search and change default - Issue [#767](https://github.com/sdv-dev/SDV/issues/767) by @fealho
* Update the UniqueCombinations constraint - Issue [#793](https://github.com/sdv-dev/SDV/issues/793) by @fealho
* Make Unique constraint works with nans - Issue [#797](https://github.com/sdv-dev/SDV/issues/797) by @fealho
* Error out if nans in OneHotEncoding - Issue [#800](https://github.com/sdv-dev/SDV/issues/800) by @amontanez24
### Bugs Fixed
* Unable to sample conditionally in Tabular_Preset model - Issue [#796](https://github.com/sdv-dev/SDV/issues/796) by @katxiao
### Documentation Changes
* Support GPU computing and progress track? - Issue [#478](https://github.com/sdv-dev/SDV/issues/478) by @fealho
## 0.14.1 - 2022-05-03
This release adds a `TabularPreset`, available in the `sdv.lite` module, which allows users to easily optimize a tabular model for speed.
In this release, we also include bug fixes for sampling with conditions, an unresolved warning, and setting field distributions. Finally,
we include documentation updates for sampling and the new `TabularPreset`.
### Bugs Fixed
* Sampling with conditions={column: 0.0} for float columns doesn't work - Issue [#525](https://github.com/sdv-dev/SDV/issues/525) by @shlomihod and @tssbas
* resolved FutureWarning with Pandas replaced append by concat - Issue [#759](https://github.com/sdv-dev/SDV/issues/759) by @Deathn0t
* Field distributions bug in CopulaGAN - Issue [#747](https://github.com/sdv-dev/SDV/issues/747) by @katxiao
* Field distributions bug in GaussianCopula - Issue [#746](https://github.com/sdv-dev/SDV/issues/746) by @katxiao
### New Features
* Set default transformer to categorical_fuzzy - Issue [#768](https://github.com/sdv-dev/SDV/issues/768) by @amontanez24
* Model nulls normally when tabular preset has constraints - Issue [#764](https://github.com/sdv-dev/SDV/issues/764) by @katxiao
* Don't modify my metadata object - Issue [#754](https://github.com/sdv-dev/SDV/issues/754) by @amontanez24
* Presets should be able to handle constraints - Issue [#753](https://github.com/sdv-dev/SDV/issues/753) by @katxiao
* Change preset optimize_for --> name - Issue [#749](https://github.com/sdv-dev/SDV/issues/749) by @katxiao
* Create a speed optimized Preset - Issue [#716](https://github.com/sdv-dev/SDV/issues/716) by @katxiao
### Documentation Changes
* Add tabular preset docs - Issue [#777](https://github.com/sdv-dev/SDV/issues/777) by @katxiao
* sdv.sampling module is missing from the API - Issue [#740](https://github.com/sdv-dev/SDV/issues/740) by @katxiao
## 0.14.0 - 2022-03-21
This release updates the sampling API and splits the existing functionality into three methods - `sample`, `sample_conditions`,
and `sample_remaining_columns`. We also add support for sampling in batches, displaying a progress bar when sampling with more than one batch,
sampling deterministically, and writing the sampled results to an output file. Finally, we include fixes for sampling with conditions
and updates to the documentation.
### Bugs Fixed
* Fix write to file in sampling - Issue [#732](https://github.com/sdv-dev/SDV/issues/732) by @katxiao
* Conditional sampling doesn't work if the model has a CustomConstraint - Issue [#696](https://github.com/sdv-dev/SDV/issues/696) by @katxiao
### New Features
* Updates to GaussianCopula conditional sampling methods - Issue [#729](https://github.com/sdv-dev/SDV/issues/729) by @katxiao
* Update conditional sampling errors - Issue [#730](https://github.com/sdv-dev/SDV/issues/730) by @katxiao
* Enable Batch Sampling + Progress Bar - Issue [#693](https://github.com/sdv-dev/SDV/issues/693) by @katxiao
* Create sample_remaining_columns() method - Issue [#692](https://github.com/sdv-dev/SDV/issues/692) by @katxiao
* Create sample_conditions() method - Issue [#691](https://github.com/sdv-dev/SDV/issues/691) by @katxiao
* Improve sample() method - Issue [#690](https://github.com/sdv-dev/SDV/issues/690) by @katxiao
* Create Condition object - Issue [#689](https://github.com/sdv-dev/SDV/issues/689) by @katxiao
* Is it possible to generate data with new set of primary keys? - Issue [#686](https://github.com/sdv-dev/SDV/issues/686) by @katxiao
* No way to fix the random seed? - Issue [#157](https://github.com/sdv-dev/SDV/issues/157) by @katxiao
* Can you set a random state for the sdv.tabular.ctgan.CTGAN.sample method? - Issue [#515](https://github.com/sdv-dev/SDV/issues/515) by @katxiao
* generating different synthetic data while training the model multiple times. - Issue [#299](https://github.com/sdv-dev/SDV/issues/299) by @katxiao
### Documentation Changes
* Typo in the document documentation - Issue [#680](https://github.com/sdv-dev/SDV/issues/680) by @katxiao
## 0.13.1 - 2021-12-22
This release adds support for passing tabular constraints to the HMA1 model, and adds more explicit error handling for
metric evaluation. It also includes a fix for using categorical columns in the PAR model and documentation updates
for metadata and HMA1.
### Bugs Fixed
* Categorical column after sequence_index column - Issue [#314](https://github.com/sdv-dev/SDV/issues/314) by @fealho
### New Features
* Support passing tabular constraints to the HMA1 model - Issue [#296](https://github.com/sdv-dev/SDV/issues/296) by @katxiao
* Metric evaluation error handling metrics - Issue [#638](https://github.com/sdv-dev/SDV/issues/638) by @katxiao
### Documentation Changes
* Make true/false values lowercase in Metadata Schema specification - Issue [#664](https://github.com/sdv-dev/SDV/issues/664) by @katxiao
* Update docstrings for hma1 methods - Issue [#642](https://github.com/sdv-dev/SDV/issues/642) by @katxiao
## 0.13.0 - 2021-11-22
This release makes multiple improvements to different `Constraint` classes. The `Unique` constraint can now
handle columns with the name `index` and no longer crashes on subsets of the original data. The `Between`
constraint can now handle columns with nulls properly. The memory of all constraints was also improved.
Various other features and fixes were added. Conditional sampling no longer crashes when the `num_rows` argument
is not provided. Multiple localizations can now be used for PII fields. Scaffolding for integration tests was added
and the workflows now run `pip check`.
Additionally, this release adds support for Python 3.9!
### Bugs Fixed
* Gaussian Copula – Memory Issue in Release 0.10.0 - Issue [#459](https://github.com/sdv-dev/SDV/issues/459) by @xamm
* Applying Unique Constraint errors when calling model.fit() on a subset of data - Issue [#610](https://github.com/sdv-dev/SDV/issues/610) by @xamm
* Calling sampling with conditions and without num_rows crashes - Issue [#614](https://github.com/sdv-dev/SDV/issues/614) by @xamm
* Metadata.visualize with path parameter throws AttributeError - Issue [#634](https://github.com/sdv-dev/SDV/issues/634) by @xamm
* The Unique constraint crashes when the data contains a column called index - Issue [#616](https://github.com/sdv-dev/SDV/issues/616) by @xamm
* The Unique constraint cannot handle non-default index - Issue [#617](https://github.com/sdv-dev/SDV/issues/617) by @xamm
* ConstraintsNotMetError when applying Between constraint on datetime columns containing null values - Issue [#632](https://github.com/sdv-dev/SDV/issues/632) by @katxiao
### New Features
* Adds Multi localisations feature for PII fields defined in #308 - PR [#609](https://github.com/sdv-dev/SDV/pull/609) by @xamm
### Housekeeping Tasks
* Support latest version of Faker - Issue [#621](https://github.com/sdv-dev/SDV/issues/621) by @katxiao
* Add scaffolding for Metadata integration tests - Issue [#624](https://github.com/sdv-dev/SDV/issues/624) by @katxiao
* Add support for Python 3.9 - Issue [#631](https://github.com/sdv-dev/SDV/issues/631) by @amontanez24
### Internal Improvements
* Add pip check to CI workflows - Issue [#626](https://github.com/sdv-dev/SDV/issues/626) by @pvk-developer
### Documentation Changes
* Anonymizing PII in single table tutorials states address field as e-mail type - Issue [#604](https://github.com/sdv-dev/SDV/issues/604) by @xamm
Special thanks to @xamm, @katxiao, @pvk-developer and @amontanez24 for all the work that made this release possible!
## 0.12.1 - 2021-10-12
This release fixes bugs in constraints, metadata behavior, and SDV documentation. Specifically, we added
proper handling of data containing null values for constraints and timeseries data, and updated the
default metadata detection behavior.
### Bugs Fixed
* ValueError: The parameter loc has invalid values - Issue [#353](https://github.com/sdv-dev/SDV/issues/353) by @fealho
* Gaussian Copula is generating different data with metadata and without metadata - Issue [#576](https://github.com/sdv-dev/SDV/issues/576) by @katxiao
* Make pomegranate an optional dependency - Issue [#567](https://github.com/sdv-dev/SDV/issues/567) by @katxiao
* Small wording change for Question Issue Template - Issue [#571](https://github.com/sdv-dev/SDV/issues/571) by @katxiao
* ConstraintsNotMetError when using GreaterThan constraint with datetime - Issue [#590](https://github.com/sdv-dev/SDV/issues/590) by @katxiao
* GreaterThan constraint crashing with NaN values - Issue [#592](https://github.com/sdv-dev/SDV/issues/592) by @katxiao
* Null values in GreaterThan constraint raises error - Issue [#589](https://github.com/sdv-dev/SDV/issues/589) by @katxiao
* ColumnFormula raises ConstraintsNotMetError when checking NaN values - Issue [#593](https://github.com/sdv-dev/SDV/issues/593) by @katxiao
* GreaterThan constraint raises TypeError when using datetime - Issue [#596](https://github.com/sdv-dev/SDV/issues/596) by @katxiao
* Fix repository language - Issue [#464](https://github.com/sdv-dev/SDV/issues/464) by @fealho
* Update __init__.py - Issue [#578](https://github.com/sdv-dev/SDV/issues/578) by @dyuliu
* IndexingError: Unalignable boolean - Issue [#446](https://github.com/sdv-dev/SDV/issues/446) by @fealho
## 0.12.0 - 2021-08-17
This release focuses on improving and expanding upon the existing constraints. More specifically, the users can now
(1) specify multiple columns in `Positive` and `Negative` constraints, (2) use the new `Unique`constraint and
(3) use datetime data with the `Between` constraint. Additionaly, error messages have been added and updated
to provide more useful feedback to the user.
Besides the added features, several bugs regarding the `UniqueCombinations` and `ColumnFormula` constraints have been fixed,
and an error in the metadata.json for the `student_placements` dataset was corrected. The release also added documentation
for the `fit_columns_model` which affects the majority of the available constraints.
### New Features
* Change default fit_columns_model to False - Issue [#550](https://github.com/sdv-dev/SDV/issues/550) by @katxiao
* Support multi-column specification for positive and negative constraint - Issue [#545](https://github.com/sdv-dev/SDV/issues/545) by @sarahmish
* Raise error when multiple constraints can't be enforced - Issue [#541](https://github.com/sdv-dev/SDV/issues/541) by @amontanez24
* Create Unique Constraint - Issue [#532](https://github.com/sdv-dev/SDV/issues/532) by @amontanez24
* Passing invalid conditions when using constraints produces unreadable errors - Issue [#511](https://github.com/sdv-dev/SDV/issues/511) by @katxiao
* Improve error message for ColumnFormula constraint when constraint column used in formula - Issue [#508](https://github.com/sdv-dev/SDV/issues/508) by @katxiao
* Add datetime functionality to Between constraint - Issue [#504](https://github.com/sdv-dev/SDV/issues/504) by @katxiao
### Bugs Fixed
* UniqueCombinations constraint with handling_strategy = 'transform' yields synthetic data with nan values - Issue [#521](https://github.com/sdv-dev/SDV/issues/521) by @katxiao and @csala
* UniqueCombinations constraint outputting wrong data type - Issue [#510](https://github.com/sdv-dev/SDV/issues/510) by @katxiao and @csala
* UniqueCombinations constraint on only one column gets stuck in an infinite loop - Issue [#509](https://github.com/sdv-dev/SDV/issues/509) by @katxiao
* Conditioning on a non-constraint column using the ColumnFormula constraint - Issue [#507](https://github.com/sdv-dev/SDV/issues/507) by @katxiao
* Conditioning on the constraint column of the ColumnFormula constraint - Issue [#506](https://github.com/sdv-dev/SDV/issues/506) by @katxiao
* Update metadata.json for duration of student_placements dataset - Issue [#503](https://github.com/sdv-dev/SDV/issues/503) by @amontanez24
* Unit test for HMA1 when working with a single child row per parent row - Issue [#497](https://github.com/sdv-dev/SDV/issues/497) by @pvk-developer
* UniqueCombinations constraint for more than 2 columns - Issue [#494](https://github.com/sdv-dev/SDV/issues/494) by @katxiao and @csala
### Documentation Changes
* Add explanation of fit_columns_model to API docs - Issue [#517](https://github.com/sdv-dev/SDV/issues/517) by @katxiao
## 0.11.0 - 2021-07-12
This release primarily addresses bugs and feature requests related to using constraints for the single-table models.
Users can now enforce scalar comparison with the existing `GreaterThan` constraint and apply 5 new constraints: `OneHotEncoding`, `Positive`, `Negative`, `Between` and `Rounding`.
Additionally, the SDV will now auto-apply constraints for rounding numerical values, and for keeping the data within the observed bounds.
All related user guides are updated with the new functionality.
### New Features
* Add OneHotEncoding Constraint - Issue [#303](https://github.com/sdv-dev/SDV/issues/303) by @fealho
* GreaterThan Constraint should apply to scalars - Issue [#410](https://github.com/sdv-dev/SDV/issues/410) by @amontanez24
* Improve GreaterThan constraint - Issue [#368](https://github.com/sdv-dev/SDV/issues/368) by @amontanez24
* Add Non-negative and Positive constraints across multiple columns- Issue [#409](https://github.com/sdv-dev/SDV/issues/409) by @amontanez24
* Add Between values constraint - Issue [#367](https://github.com/sdv-dev/SDV/issues/367) by @fealho
* Ensure values fall within the specified range - Issue [#423](https://github.com/sdv-dev/SDV/issues/423) by @amontanez24
* Add Rounding constraint - Issue [#482](https://github.com/sdv-dev/SDV/issues/482) by @katxiao
* Add rounding and min/max arguments that are passed down to the NumericalTransformer - Issue [#491](https://github.com/sdv-dev/SDV/issues/491) by @amontanez24
### Bugs Fixed
* GreaterThan constraint between Date columns rasises TypeError - Issue [#421](https://github.com/sdv-dev/SDV/issues/421) by @amontanez24
* GreaterThan constraint's transform strategy fails on columns that are not float - Issue [#448](https://github.com/sdv-dev/SDV/issues/448) by @amontanez24
* AttributeError on UniqueCombinations constraint with non-strings - Issue [#196](https://github.com/sdv-dev/SDV/issues/196) by @katxiao
* Use reject sampling to sample missing columns for constraints - Issue [#435](https://github.com/sdv-dev/SDV/issues/435) by @amontanez24
### Documentation Changes
* Ensure privacy metrics are available in the API docs - Issue [#458](https://github.com/sdv-dev/SDV/issues/458) by @fealho
* Ensure forumla constraint is called ColumnFormula everywhere in the docs - Issue [#449](https://github.com/sdv-dev/SDV/issues/449) by @fealho
## 0.10.1 - 2021-06-10
This release changes the way we sample conditions to not only group by the conditions passed by the user, but also by the transformed conditions that result from them.
### Issues resolved
* Conditionally sampling on variable in constraint should have variety for other variables - Issue [#440](https://github.com/sdv-dev/SDV/issues/440) by @amontanez24
## 0.10.0 - 2021-05-21
This release improves the constraint functionality by allowing constraints and conditions
at the same time. Additional changes were made to update tutorials.
### Issues resolved
* Not able to use constraints and conditions in the same time - Issue [#379](https://github.com/sdv-dev/SDV/issues/379)
by @amontanez24
* Update benchmarking user guide for reading private datasets - Issue [#427](https://github.com/sdv-dev/SDV/issues/427)
by @katxiao
## 0.9.1 - 2021-04-29
This release broadens the constraint functionality by allowing for the `ColumnFormula`
constraint to take lambda functions and returned functions as an input for its formula.
It also improves conditional sampling by ensuring that any `id` fields generated by the
model remain unique throughout the sampled data.
The `CTGAN` model was improved by adjusting a default parameter to be more mathematically
correct.
Additional changes were made to improve tutorials as well as fix fragile tests.
### Issues resolved
* Tutorials test sometimes fails - Issue [#355](https://github.com/sdv-dev/SDV/issues/355)
by @fealho
* Duplicate IDs when using reject-sampling - Issue [#331](https://github.com/sdv-dev/SDV/issues/331)
by @amontanez24 and @csala
* discriminator_decay should be initialized at 1e-6 but it's 0 - Issue [#401](https://github.com/sdv-dev/SDV/issues/401) by @fealho and @YoucefZemmouri
* Tutorial typo - Issue [#380](https://github.com/sdv-dev/SDV/issues/380) by @fealho
* Request for sdv.constraint.ColumnFormula for a wider range of function - Issue [#373](https://github.com/sdv-dev/SDV/issues/373) by @amontanez24 and @JetfiRex
## 0.9.0 - 2021-03-31
This release brings new privacy metrics to the evaluate framework which help to determine
if the real data could be obtained or deduced from the synthetic samples.
Additionally, now there is a normalized score for the metrics, which stays between `0` and `1`.
There are improvements that reduce the usage of memory ram when sampling new data. Also there
is a new parameter to control the reject sampling crash, `graceful_reject_sampling`, which if
set to `True` and if it's not possible to generate all the requested rows, it will just issue a
warning and return whatever it was able to generate.
The `Metadata` object can now be visualized using different combinations of `names` and `details`,
which can be set to `True` or `False` in order to display only the table names with details or
without. There is also an improvement on the `validation`, which now will display all the errors
found at the end of the validation instead of only the first one.
This version also exposes all the hyperparameters of the models `CTGAN` and `TVAE` to allow a more
advanced usage. There is also a fix for the `TVAE` model on small datasets and it's performance
with `NaN` values has been improved. There is a fix for when using
`UniqueCombinationConstraint` with the `transform` strategy.
### Issues resolved
* Memory Usage Gaussian Copula Trained Model consuming high memory when generating synthetic data - Issue [#304](https://github.com/sdv-dev/SDV/issues/304) by @pvk-developer and @AnupamaGangadhar
* Add option to visualize metadata with only table names - Issue [#347](https://github.com/sdv-dev/SDV/issues/347) by @csala
* Add sample parameter to control reject sampling crash - Issue [#343](https://github.com/sdv-dev/SDV/issues/343) by @fealho
* Verbose metadata validation - Issue [#348](https://github.com/sdv-dev/SDV/issues/348) by @csala
* Missing the introduction of custom specification for hyperparameters in the TVAE model - Issue [#344](https://github.com/sdv-dev/SDV/issues/343) by @imkhoa99 and @pvk-developer
## 0.8.0 - 2021-02-24
This version adds conditional sampling for tabular models by combining a reject-sampling
strategy with the native conditional sampling capabilities from the gaussian copulas.
It also introduces several upgrades on the HMA1 algorithm that improve data quality and
robustness in the multi-table scenarios by making changes in how the parameters of the child
tables are aggregated on the parent tables, including a complete rework of how the correlation
matrices are modeled and rebuild after sampling.
### Issues resolved
* Fix probabilities contain NaN error - Issue [#326](https://github.com/sdv-dev/SDV/issues/326) by @csala
* Conditional Sampling for tabular models - Issue [#316](https://github.com/sdv-dev/SDV/issues/316) by @fealho and @csala
* HMA1: LinAlgError: SVD did not converge - Issue [#240](https://github.com/sdv-dev/SDV/issues/240) by @csala
## 0.7.0 - 2021-01-27
This release introduces a few changes in the HMA1 relational algorithm to decrease modeling
and sampling times, while also ensuring that correlations are properly kept across tables
and also adding support for some relational schemas that were not supported before.
A few changes in constraints and tabular models also ensure that situations that produced
errors before now work without errors.
### Issues resolved
* Fix unique key generation - Issue [#306](https://github.com/sdv-dev/SDV/issues/306) by @fealho
* Ensure tables that contain nothing but ids can be modeled - Issue [#302](https://github.com/sdv-dev/SDV/issues/302) by @csala
* Metadata visualization improvements - Issue [#301](https://github.com/sdv-dev/SDV/issues/301) by @csala
* Multi-parent re-model and re-sample issue - Issue [#298](https://github.com/sdv-dev/SDV/issues/298) by @csala
* Support datetimes in GreaterThan constraint - Issue [#266](https://github.com/sdv-dev/SDV/issues/266) by @rollervan
* Support for multiple foreign keys in one table - Issue [#185](https://github.com/sdv-dev/SDV/issues/185) by @csala
## 0.6.1 - 2020-12-31
SDMetrics version is updated to include the new Time Series metrics, which have also
been added to the API Reference and User Guides documentation. Additionally,
a few code has been refactored to reduce external dependencies and a few minor bugs
related to single table constraints have been fixed
### Issues resolved
* Add timeseries metrics and user guides - [Issue #289](https://github.com/sdv-dev/SDV/issues/289) by @csala
* Add functions to generate regex ids - [Issue #288](https://github.com/sdv-dev/SDV/issues/288) by @csala
* Saving a fitted tabular model with UniqueCombinations constraint raises PicklingError -
  [Issue #286](https://github.com/sdv-dev/SDV/issues/288) by @csala
* Constraints: `handling_strategy='reject_sampling'` causes `'ZeroDivisionError: division by zero'` -
  [Issue #285](https://github.com/sdv-dev/SDV/issues/285) by @csala
## 0.6.0 - 2020-12-22
This release updates to the latest CTGAN, RDT and SDMetrics libraries to introduce a
new TVAE model, multiple new metrics for single table and multi table, and fixes
issues in the re-creation of tabular models from a metadata dict.
### Issues resolved
* Upgrade to SDMetrics v0.1.0 and add `sdv.metrics` module - [Issue #281](https://github.com/sdv-dev/SDV/issues/281) by @csala
* Upgrade to CTGAN 0.3.0 and add TVAE model - [Issue #278](https://github.com/sdv-dev/SDV/issues/278) by @fealho
* Add `dtype_transformers` to `Table.from_dict` - [Issue #276](https://github.com/sdv-dev/SDV/issues/276) by @csala
* Fix Metadata `from_dict` behavior - [Issue #275](https://github.com/sdv-dev/SDV/issues/275) by @csala
## 0.5.0 - 2020-11-25
This version updates the dependencies and makes a few internal changes in order
to ensure that SDV works properly on Windows Systems, making this the first
release to be officially supported on Windows.
Apart from this, some more internal changes have been made to solve a few minor
issues from the older versions while also improving the processing speed when
processing relational datasets with the default parameters.
### API breaking changes
* The `distribution` argument of the `GaussianCopula` has been renamed to `field_distributions`.
* The `HMA1` and `SDV` classes now use the `categorical_fuzzy` transformer by default instead of
  the `one_hot_encoding` one.
### Issues resolved
* GaussianCopula: rename `distribution` argument to `field_distributions` - [Issue #237](https://github.com/sdv-dev/SDV/issues/237) by @csala
* GaussianCopula: Improve error message if an invalid distribution name is passed - [Issue #220](https://github.com/sdv-dev/SDV/issues/220) by csala
* Import urllib.request explicitly - [Issue #227](https://github.com/sdv-dev/SDV/issues/227) by @csala
* TypeError: cannot astype a datetimelike from [datetime64[ns]] to [int32] - [Issue #218](https://github.com/sdv-dev/SDV/issues/218) by @csala
* Change default categorical transformer to `categorical_fuzzy` in HMA1 - [Issue #214](https://github.com/sdv-dev/SDV/issues/214) by @csala
* Integer categoricals being sampled as strings instead of integer values - [Issue #194](https://github.com/sdv-dev/SDV/issues/194) by @csala
## 0.4.5 - 2020-10-17
In this version a new family of models for Synthetic Time Series Generation is introduced
under the `sdv.timeseries` sub-package. The new family of models now includes a new class
called `PAR`, which implements a *Probabilistic AutoRegressive* model.
This version also adds support for composite primary keys and regex based generation of id
fields in tabular models and drops Python 3.5 support.
### Issues resolved
* Drop python 3.5 support - [Issue #204](https://github.com/sdv-dev/SDV/issues/204) by @csala
* Support composite primary keys in tabular models - [Issue #207](https://github.com/sdv-dev/SDV/issues/207) by @csala
* Add the option to generate string `id` fields based on regex on tabular models - [Issue #208](https://github.com/sdv-dev/SDV/issues/208) by @csala
* Synthetic Time Series - [Issue #142](https://github.com/sdv-dev/SDV/issues/142) by @csala
## 0.4.4 - 2020-10-06
This version adds a new tabular model based on combining the CTGAN model with the reversible
transformation applied in the GaussianCopula model that converts random variables with
arbitrary distributions to new random variables with standard normal distribution.
The reversible transformation is handled by the GaussianCopulaTransformer recently added to RDT.
### Issues resolved
* Add CopulaGAN Model - [Issue #202](https://github.com/sdv-dev/SDV/issues/202) by @csala
## 0.4.3 - 2020-09-28
This release moves the models and algorithms related to generation of synthetic
relational data to a new `sdv.relational` subpackage (Issue #198)
As part of the change, also the old `sdv.models` have been removed and now
relational model is based on the recently introduced `sdv.tabular` models.
## 0.4.2 - 2020-09-19
In this release the `sdv.evaluation` module has been reworked to include 4 different
metrics and in all cases return a normalized score between 0 and 1.
Included metrics are:
- `cstest`
- `kstest`
- `logistic_detection`
- `svc_detection`
## 0.4.1 - 2020-09-07
This release fixes a couple of minor issues and introduces an important rework of the
User Guides section of the documentation.
### Issues fixed
* Error Message: "make sure the Graphviz executables are on your systems' PATH" - [Issue #182](https://github.com/sdv-dev/SDV/issues/182) by @csala
* Anonymization mappings leak - [Issue #187](https://github.com/sdv-dev/SDV/issues/187) by @csala
## 0.4.0 - 2020-08-08
In this release SDV gets new documentation, new tutorials, improvements to the Tabular API
and broader python and dependency support.
Complete list of changes:
* New Documentation site based on the `pydata-sphinx-theme`.
* New User Guides and Notebook tutorials.
* New Developer Guides section within the docs with details about the SDV architecture,
  the ecosystem libraries and how to extend and contribute to the project.
* Improved API for the Tabular models with focus on ease of use.
* Support for Python 3.8 and the newest versions of pandas, scipy and scikit-learn.
* New Slack Workspace for development discussions and community support.
## 0.3.6 - 2020-07-23
This release introduces a new concept of `Constraints`, which allow the user to define
special relationships between columns that will not be handled via modeling.
This is done via a new `sdv.constraints` subpackage which defines some well-known pre-defined
constraints, as well as a generic framework that allows the user to customize the constraints
to their needs as much as necessary.
### New Features
* Support for Constraints - [Issue #169](https://github.com/sdv-dev/SDV/issues/169) by @csala
## 0.3.5 - 2020-07-09
This release introduces a new subpackage `sdv.tabular` with models designed specifically
for single table modeling, while still providing all the usual conveniences from SDV, such
as:
* Seamless multi-type support
* Missing data handling
* PII anonymization
Currently implemented models are:
* GaussianCopula: Multivariate distributions modeled using copula functions. This is stronger
  version, with more marginal distributions and options, than the one used to model multi-table
  datasets.
* CTGAN: GAN-based data synthesizer that can generate synthetic tabular data with high fidelity.
## 0.3.4 - 2020-07-04
### New Features
* Support for Multiple Parents - [Issue #162](https://github.com/sdv-dev/SDV/issues/162) by @csala
* Sample by default the same number of rows as in the original table - [Issue #163](https://github.com/sdv-dev/SDV/issues/163) by @csala
### General Improvements
* Add benchmark - [Issue #165](https://github.com/sdv-dev/SDV/issues/165) by @csala
## 0.3.3 - 2020-06-26
### General Improvements
* Use SDMetrics for evaluation - [Issue #159](https://github.com/sdv-dev/SDV/issues/159) by @csala
## 0.3.2 - 2020-02-03
### General Improvements
* Improve metadata visualization - [Issue #151](https://github.com/sdv-dev/SDV/issues/151) by @csala @JDTheRipperPC
## 0.3.1 - 2020-01-22
### New Features
* Add Metadata Validation - [Issue #134](https://github.com/sdv-dev/SDV/issues/134) by @csala @JDTheRipperPC
* Add Metadata Visualization - [Issue #135](https://github.com/sdv-dev/SDV/issues/135) by @JDTheRipperPC
### General Improvements
* Add path to metadata JSON - [Issue #143](https://github.com/sdv-dev/SDV/issues/143) by @JDTheRipperPC
* Use new Copulas and RDT versions - [Issue #147](https://github.com/sdv-dev/SDV/issues/147) by @csala @JDTheRipperPC
## 0.3.0 - 2019-12-23
### New Features
* Create sdv.models subpackage - [Issue #141](https://github.com/sdv-dev/SDV/issues/141) by @JDTheRipperPC
## 0.2.2 - 2019-12-10
### New Features
* Adapt evaluation to the different data types - [Issue #128](https://github.com/sdv-dev/SDV/issues/128) by @csala @JDTheRipperPC
* Extend `load_demo` functionality to load other datasets - [Issue #136](https://github.com/sdv-dev/SDV/issues/136) by @JDTheRipperPC
## 0.2.1 - 2019-11-25
### New Features
* Methods to generate Metadata from DataFrames - [Issue #126](https://github.com/sdv-dev/SDV/issues/126) by @csala @JDTheRipperPC
## 0.2.0 - 2019-10-11
### New Features
* compatibility with rdt issue 72 - [Issue #120](https://github.com/sdv-dev/SDV/issues/120) by @csala @JDTheRipperPC
### General Improvements
* Error docstring sampler.__fill_text_columns - [Issue #144](https://github.com/sdv-dev/SDV/issues/114) by @JDTheRipperPC
* Reach 90% coverage - [Issue #112](https://github.com/sdv-dev/SDV/issues/112) by @JDTheRipperPC
* Review unittests - [Issue #111](https://github.com/sdv-dev/SDV/issues/111) by @JDTheRipperPC
### Bugs Fixed
* Time required for sample_all function? - [Issue #118](https://github.com/sdv-dev/SDV/issues/118) by @csala @JDTheRipperPC
## 0.1.2 - 2019-09-18
### New Features
* Add option to model the amount of child rows - Issue [93](https://github.com/sdv-dev/SDV/issues/93) by @ManuelAlvarezC
### General Improvements
* Add Evaluation Metrics - Issue [52](https://github.com/sdv-dev/SDV/issues/52) by @ManuelAlvarezC
* Ensure unicity on primary keys on different calls - Issue [63](https://github.com/sdv-dev/SDV/issues/63) by @ManuelAlvarezC
### Bugs fixed
* executing readme: 'not supported between instances of 'int' and 'NoneType' - Issue [104](https://github.com/sdv-dev/SDV/issues/104) by @csala
## 0.1.1 - Anonymization of data
* Add warnings when trying to model an unsupported dataset structure. [GH#73](https://github.com/sdv-dev/SDV/issues/73)
* Add option to anonymize data. [GH#51](https://github.com/sdv-dev/SDV/issues/51)
* Add support for modeling data with different distributions, when using `GaussianMultivariate` model. [GH#68](https://github.com/sdv-dev/SDV/issues/68)
* Add support for `VineCopulas` as a model. [GH#71](https://github.com/sdv-dev/SDV/issues/71)
* Improve `GaussianMultivariate` parameter sampling, avoiding warnings and unvalid parameters. [GH#58](https://github.com/sdv-dev/SDV/issues/58)
* Fix issue that caused that sampled categorical values sometimes got numerical values mixed. [GH#81](https://github.com/sdv-dev/SDV/issues/81)
* Improve the validation of extensions. [GH#69](https://github.com/sdv-dev/SDV/issues/69)
* Update examples. [GH#61](https://github.com/sdv-dev/SDV/issues/61)
* Replaced `Table` class with a `NamedTuple`. [GH#92](https://github.com/sdv-dev/SDV/issues/92)
* Fix inconsistent dependencies and add upper bound to dependencies. [GH#96](https://github.com/sdv-dev/SDV/issues/96)
* Fix error when merging extension in `Modeler.CPA` when running examples. [GH#86](https://github.com/sdv-dev/SDV/issues/86)
## 0.1.0 - First Release
* First release on PyPI.

%package -n python3-sdv
Summary:	Generate synthetic data for single table, multi table and sequential data
Provides:	python-sdv
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-sdv
<div align="center">
  <a href="https://datacebo.com"><picture>
      <source media="(prefers-color-scheme: dark)" srcset="https://github.com/sdv-dev/SDV/blob/master/docs/images/datacebo-logo-dark-mode.png">
      <img align="center" width=40% src="https://github.com/sdv-dev/SDV/blob/master/docs/images/datacebo-logo.png"></img>
  </picture></a>
</div>
<br/>
<br/>
[The Synthetic Data Vault Project](https://sdv.dev) was first created at MIT's [Data to AI Lab](
https://dai.lids.mit.edu/) in 2016. After 4 years of research and traction with enterprise, we
created [DataCebo](https://datacebo.com) in 2020 with the goal of growing the project.
Today, DataCebo is the proud developer of SDV, the largest ecosystem for
synthetic data generation & evaluation. It is home to multiple libraries that support synthetic
data, including:
* 🔄 Data discovery & transformation. Reverse the transforms to reproduce realistic data.
* 🧠 Multiple machine learning models -- ranging from Copulas to Deep Learning -- to create tabular,
  multi table and time series data.
* 📊 Measuring quality and privacy of synthetic data, and comparing different synthetic data
  generation models.
[Get started using the SDV package](https://bit.ly/sdv-docs) -- a fully
integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
for specific needs.
# Release Notes
## 1.0.0 - 2023-03-28
This is a major release that introduces a new API to the `SDV` aimed at streamlining the process of synthetic data generation! To achieve this, this release includes the addition of several large features.
### Metadata
Some of the most notable additions are the new `SingleTableMetadata` and `MultiTableMetadata` classes. These classes enable a number of features that make it easier to synthesize your data correctly such as:
* Automatic data detection - Calling `metadata.detect_from_dataframe()` or `metadata.detect_from_csv()` will populate the metadata autonomously with values it thinks represent the data.
* Easy updating - Once an instance of the metadata is created, values can be easily updated using a number of methods defined in the API. For more info, view the [docs](https://docs.sdv.dev/sdv/single-table-data/data-preparation/single-table-metadata-api).
* Metadata validation - Calling `metadata.validate()` will return a report of any invalid definitions in the metadata specification.
* Upgrading - Users with the previous metadata format can easily update to the new specification using the `upgrade_metadata()` method.
* Saving and loading - The metadata itself can easily be saved to a json file and loaded back up later.
### Class and Module Names
Another major change is the renaming of our core modeling classes and modules. The name changes are meant to highlight the difference between the underlying machine learning models, and the objects responsible for the end-to-end workflow of generating synthetic data. The main name changes are as follows:
* `tabular` -> `single_table`
* `relational` -> `multi_table`
* `timeseries` -> `sequential`
* `BaseTabularModel` -> `BaseSingleTableSynthesizer`
* `GaussianCopula` -> `GaussianCopulaSynthesizer`
* `CTGAN` -> `CTGANSynthesizer`
* `TVAE` -> `TVAESynthesizer`
* `CopulaGan` -> `CopulaGANSynthesizer`
* `PAR` -> `PARSynthesizer`
* `HMA1` -> `HMASynthesizer`
In `SDV` 1.0, synthesizers are classes that take in metadata and handle data preprocessing, model training and model sampling. This is similar to the previous `BaseTabularModel` in `SDV` <1.0.
### Synthetic Data Workflow
`Synthesizers` in `SDV` 1.0 define a clear workflow for generating synthetic data.
1. Synthesizers are initialized with a metadata class.
2. They can then be used to transform the data and apply constraints using the `synthesizer.preprocess()` method. This step also validates that the data matches the provided metadata to avoid errors in fitting or sampling.
3. The processed data can then be fed into the underlying machine learning model using `synthesizer.fit_processed_data()`. (Alternatively, data can be preprocessed and fit to the model using `synthesizer.fit()`.)
4. Data can then be sampled using `synthesizer.sample()`.
Each synthesizer class also provides a series of methods to help users customize the transformations their data goes through. Read more about that [here](https://docs.sdv.dev/sdv/single-table-data/modeling/synthetic-data-workflow/transform-and-anonymize).
Notice that the preprocessing and model fitting steps can now be separated. This can be helpful if preprocessing is time consuming or if the data has been processed externally.
### Other Highly Requested Features
Another major addition is control over randomization. In `SDV` <1.0, users could set a seed to control the randomization for only some columns. In `SDV` 1.0, randomization is controlled for all columns. Every new call to sample generates new data, but the synthesizer's seed can be reset to the original state using `synthesizer.reset_randomization()`, enabling reproducibility.
`SDV 1.0` adds accessibility and transparency into the transformers used for preprocessing and underlying machine learning models.
* Using the `synthesizer.get_transformers()` method, you can access the transformers used to preprocess each column and view their properties. This can be useful for debugging and accessing privacy information like mappings used to mask data.
* Distribution parameters learned by copula models can be accessed using the `synthesizer.get_learned_distributions()` method.
PII handling is improved by the following features:
* Primary keys can be set to natural sdtypes (eg. SSN, email, name). Previously they could only be numerical or text.
* The `PseudoAnonymizedFaker` can be used to provide consistent mapping to PII columns. As mentioned before, the mapping itself can be accessed by viewing the transformers for the column using `synthesizer.get_transformers()`.
* A bug causing PII columns to slow down modeling is patched.
Finally, the synthetic data can now be easily evaluated using the `evaluate_quality()` and `run_diagnostic()` methods. The data can be compared visually to the actual data using the `get_column_plot()` and `get_column_pair_plot()` methods. For more info on how to visualize or interpret the synthetic data evaluation, read the docs [here](https://docs.sdv.dev/sdv/single-table-data/evaluation).
### Issues Resolved
#### New Features
* Change auto_assign_transformers to handle id types - Issue [#1325](https://github.com/sdv-dev/SDV/issues/1325) by @pvk-developer
* Change 'text' sdtype to 'id' - Issue [#1324](https://github.com/sdv-dev/SDV/issues/1324) by @frances-h
* In `upgrade_metadata`, return the object instead of writing it to a JSON file - Issue [#1319](https://github.com/sdv-dev/SDV/issues/1319) by @frances-h
* In `upgrade_metadata` index primary keys should be converted to `text` - Issue [#1318](https://github.com/sdv-dev/SDV/issues/1318) by @amontanez24
* Add `load_from_dict` to SingleTableMetadata and MultiTableMetadata - Issue [#1314](https://github.com/sdv-dev/SDV/issues/1314) by @amontanez24
* Throw a `SynthesizerInputError` if `FixedCombinations` constraint is applied to a column that is not `boolean` or `categorical` - Issue [#1306](https://github.com/sdv-dev/SDV/issues/1306) by @frances-h
* Missing `save` and `load` methods for `HMASynthesizer` - Issue [#1262](https://github.com/sdv-dev/SDV/issues/1262) by @amontanez24
* Better input validation when creating single and multi table synthesizers - Issue [#1242](https://github.com/sdv-dev/SDV/issues/1242) by @fealho
* Better input validation on `HMASynthesizer.sample` - Issue [#1241](https://github.com/sdv-dev/SDV/issues/1241) by @R-Palazzo
* Validate that relationship must be between a `primary key` and `foreign key` - Issue [#1236](https://github.com/sdv-dev/SDV/issues/1236) by @fealho
* Improve `update_column` validation for `pii` attribute - Issue [#1226](https://github.com/sdv-dev/SDV/issues/1226) by @pvk-developer
* Order the output of `get_transformers()` based on the metadata - Issue [#1222](https://github.com/sdv-dev/SDV/issues/1222) by @pvk-developer
* Log if any `numerical_distributions` will not be applied - Issue [#1212](https://github.com/sdv-dev/SDV/issues/1212) by @fealho
* Improve error handling for `GaussianCopulaSynthesizer`: `numerical_distributions` - Issue [#1211](https://github.com/sdv-dev/SDV/issues/1211) by @fealho
* Improve error handling when validating `constraints` - Issue [#1210](https://github.com/sdv-dev/SDV/issues/1210) by @fealho
* Add `fake_companies` demo - Issue [#1209](https://github.com/sdv-dev/SDV/issues/1209) by @amontanez24
* Allow me to create a custom constraint class and use it in the same file - Issue [#1205](https://github.com/sdv-dev/SDV/issues/1205) by @amontanez24
* Sampling should reset after retraining the model - Issue [#1201](https://github.com/sdv-dev/SDV/issues/1201) by @pvk-developer
* Change function name `HMASynthesizer.update_table_parameters` --> `set_table_parameters` - Issue [#1200](https://github.com/sdv-dev/SDV/issues/1200) by @pvk-developer
* Add `get_info` method to synthesizers - Issue [#1199](https://github.com/sdv-dev/SDV/issues/1199) by @fealho
* Add evaluation methods to synthesizer - Issue [#1190](https://github.com/sdv-dev/SDV/issues/1190) by @fealho
* Update `evaluate.py` to work with the new `metadata` - Issue [#1186](https://github.com/sdv-dev/SDV/issues/1186) by @fealho
* Remove old code - Issue [#1181](https://github.com/sdv-dev/SDV/issues/1181) by @pvk-developer
* Drop support for python 3.6 and add support for 3.10 - Issue [#1176](https://github.com/sdv-dev/SDV/issues/1176) by @fealho
* Add constraint methods to MultiTableSynthesizers - Issue [#1171](https://github.com/sdv-dev/SDV/issues/1171) by @fealho
* Update custom constraint workflow - Issue [#1169](https://github.com/sdv-dev/SDV/issues/1169) by @pvk-developer
* Add get_constraints method to synthesizers - Issue [#1168](https://github.com/sdv-dev/SDV/issues/1168) by @pvk-developer
* Migrate adding and validating constraints to BaseSynthesizer - Issue [#1163](https://github.com/sdv-dev/SDV/issues/1163) by @pvk-developer
* Change metadata `"SCHEMA_VERSION"` --> `"METADATA_SPEC_VERSION"` - Issue [#1139](https://github.com/sdv-dev/SDV/issues/1139) by @amontanez24
* Add ability to reset random sampling - Issue [#1130](https://github.com/sdv-dev/SDV/issues/1130) by @pvk-developer
* Add get_available_demos - Issue [#1129](https://github.com/sdv-dev/SDV/issues/1129) by @fealho
* Add demo loading functionality - Issue [#1128](https://github.com/sdv-dev/SDV/issues/1128) by @fealho
* Use logging instead of printing in detect methods - Issue [#1107](https://github.com/sdv-dev/SDV/issues/1107) by @fealho
* Add save and load methods to synthesizers - Issue [#1106](https://github.com/sdv-dev/SDV/issues/1106) by @pvk-developer
* Add sampling methods to PARSynthesizer - Issue [#1083](https://github.com/sdv-dev/SDV/issues/1083) by @amontanez24
* Add transformer methods to PARSynthesizer - Issue [#1082](https://github.com/sdv-dev/SDV/issues/1082) by @fealho
* Add validate to PARSynthesizer - Issue [#1081](https://github.com/sdv-dev/SDV/issues/1081) by @amontanez24
* Add preprocess and fit methods to PARSynthesizer - Issue [#1080](https://github.com/sdv-dev/SDV/issues/1080) by @amontanez24
* Create SingleTablePreset - Issue [#1079](https://github.com/sdv-dev/SDV/issues/1079) by @amontanez24
* Add sample method to multi-table synthesizers - Issue [#1078](https://github.com/sdv-dev/SDV/issues/1078) by @pvk-developer
* Add get_learned_distributions method to synthesizers - Issue [#1075](https://github.com/sdv-dev/SDV/issues/1075) by @pvk-developer
* Add preprocess and fit methods to multi-table synthesizers - Issue [#1074](https://github.com/sdv-dev/SDV/issues/1074) by @pvk-developer
* Add transformer related methods to BaseMultiTableSynthesizer - Issue [#1072](https://github.com/sdv-dev/SDV/issues/1072) by @fealho
* Add validate method to `BaseMultiTableSynthesizer` - Issue [#1071](https://github.com/sdv-dev/SDV/issues/1071) by @pvk-developer
* Create BaseMultiTableSynthesizer and HMASynthesizer classes - Issue [#1070](https://github.com/sdv-dev/SDV/issues/1070) by @pvk-developer
* Create PARSynthesizer - Issue [#1055](https://github.com/sdv-dev/SDV/issues/1055) by @amontanez24
* Raise an error if an invalid sdtype is provided to the metadata - Issue [#1042](https://github.com/sdv-dev/SDV/issues/1042) by @amontanez24
* Only allow datetime and numerical sdtypes to be set as the sequence index - Issue [#1030](https://github.com/sdv-dev/SDV/issues/1030) by @amontanez24
* Change set_alternate_keys to add_alternate_keys and add error handling - Issue [#1029](https://github.com/sdv-dev/SDV/issues/1029) by @amontanez24
* Create `MultiTableMetadata.add_table` method - Issue [#1024](https://github.com/sdv-dev/SDV/issues/1024) by @amontanez24
* Add update_transformers to synthesizers - Issue [#1021](https://github.com/sdv-dev/SDV/issues/1021) by @fealho
* Add assign_transformers and get_transformers methods to synthesizers - Issue [#1020](https://github.com/sdv-dev/SDV/issues/1020) by @pvk-developer
* Add fit and fit_processed_data methods to synthesizers - Issue [#1019](https://github.com/sdv-dev/SDV/issues/1019) by @pvk-developer
* Add preprocess method to synthesizers - Issue [#1018](https://github.com/sdv-dev/SDV/issues/1018) by @pvk-developer
* Add sampling to synthesizer classes - Issue [#1015](https://github.com/sdv-dev/SDV/issues/1015) by @pvk-developer
* Add validate method to synthesizer - Issue [#1014](https://github.com/sdv-dev/SDV/issues/1014) by @fealho
* Create GaussianCopula, CTGAN, TVAE and CopulaGAN synthesizer classes - Issue [#1013](https://github.com/sdv-dev/SDV/issues/1013) by @pvk-developer
* Create BaseSynthesizer class - Issue [#1012](https://github.com/sdv-dev/SDV/issues/1012) by @pvk-developer
* Add constraint conversion to upgrade_metadata - Issue [#1005](https://github.com/sdv-dev/SDV/issues/1005) by @amontanez24
* Add method to generate keys to DataProcessor - Issue [#994](https://github.com/sdv-dev/SDV/issues/994) by @pvk-developer
* Create formatter - Issue [#970](https://github.com/sdv-dev/SDV/issues/970) by @fealho
* Create a utility to load multiple CSV files at once - Issue [#969](https://github.com/sdv-dev/SDV/issues/969) by @amontanez24
* Create a utility to convert old --> new metadata format - Issue [#966](https://github.com/sdv-dev/SDV/issues/966) by @amontanez24
* Add validation check that `primary_key`, `alternate_keys` and `sequence_key` cannot be sdtype categorical - Issue [#963](https://github.com/sdv-dev/SDV/issues/963) by @fealho
* Add anonymization to DataProcessor - Issue [#950](https://github.com/sdv-dev/SDV/issues/950) by @pvk-developer
* Add utility methods to DataProcessor - Issue [#948](https://github.com/sdv-dev/SDV/issues/948) by @fealho
* Add fit, transform and reverse_transform to DataProcessor - Issue [#947](https://github.com/sdv-dev/SDV/issues/947) by @amontanez24
* Create DataProcessor class - Issue [#946](https://github.com/sdv-dev/SDV/issues/946) by @amontanez24
* Add add_constraint method to MultiTableMetadata - Issue [#895](https://github.com/sdv-dev/SDV/issues/895) by @amontanez24
* Add key related methods to MultiTableMetadata - Issue [#894](https://github.com/sdv-dev/SDV/issues/894) by @fealho
* Add update_column and add_column methods to MultiTableMetadata - Issue [#893](https://github.com/sdv-dev/SDV/issues/893) by @amontanez24
* Add detect methods to MultiTableMetadata - Issue [#892](https://github.com/sdv-dev/SDV/issues/892) by @amontanez24
* Add load_from_json and save_to_json methods to the MultiTableMetadata - Issue [#891](https://github.com/sdv-dev/SDV/issues/891) by @fealho
* Add add_relationship method to MultiTableMetadata - Issue [#890](https://github.com/sdv-dev/SDV/issues/890) by @pvk-developer
* Add validate method to MultiTableMetadata - Issue [#888](https://github.com/sdv-dev/SDV/issues/888) by @pvk-developer
* Add visualize method to MultiTableMetadata class - Issue [#884](https://github.com/sdv-dev/SDV/issues/884) by @amontanez24
* Create MultiTableMetadata class - Issue [#883](https://github.com/sdv-dev/SDV/issues/883) by @pvk-developer
* Add add_constraint method to SingleTableMetadata - Issue [#881](https://github.com/sdv-dev/SDV/issues/881) by @amontanez24
* Add key related methods to SingleTableMetadata - Issue [#880](https://github.com/sdv-dev/SDV/issues/880) by @fealho
* Add validate method to SingleTableMetadata - Issue [#879](https://github.com/sdv-dev/SDV/issues/879) by @fealho
* Add _validate_inputs class method to each constraint - Issue [#878](https://github.com/sdv-dev/SDV/issues/878) by @fealho
* Add update_column and add_column methods to SingleTableMetadata - Issue [#877](https://github.com/sdv-dev/SDV/issues/877) by @pvk-developer
* Add detect methods to SingleTableMetadata - Issue [#876](https://github.com/sdv-dev/SDV/issues/876) by @pvk-developer
* Add load_from_json and save_to_json methods to SingleTableMetadata - Issue [#874](https://github.com/sdv-dev/SDV/issues/874) by @pvk-developer
* Create SingleTableMetadata class - Issue [#873](https://github.com/sdv-dev/SDV/issues/873) by @pvk-developer
#### Bugs Fixed
* In `upgrade_metadata`, PII values are being converted to generic categorical columns - Issue [#1317](https://github.com/sdv-dev/SDV/issues/1317) by @frances-h
* `PARSynthesizer` is missing `save` and `load` methods - Issue [#1289](https://github.com/sdv-dev/SDV/issues/1289) by @amontanez24
* Confusing warning when updating transformers - Issue [#1272](https://github.com/sdv-dev/SDV/issues/1272) by @frances-h
* When adding constraints, `auto_assign_transformers` is showing columns that should no longer exist - Issue [#1260](https://github.com/sdv-dev/SDV/issues/1260) by @pvk-developer
* Cannot fit twice if I modify transformers: `ValueError: There are non-numerical values in your data.` - Issue [#1259](https://github.com/sdv-dev/SDV/issues/1259) by @frances-h
* Cannot fit twice if I add constraints: `ValueError: There are non-numerical values in your data.` - Issue [#1258](https://github.com/sdv-dev/SDV/issues/1258) by @frances-h
* `HMASynthesizer` errors out when fitting a dataset that has a table which holds primary key and foreign keys only - Issue [#1257](https://github.com/sdv-dev/SDV/issues/1257) by @pvk-developer
* Change ValueErrors to InvalidMetadataErrors - Issue [#1251](https://github.com/sdv-dev/SDV/issues/1251) by @frances-h
* Multi-table should show foreign key transformers as None - Issue [#1249](https://github.com/sdv-dev/SDV/issues/1249) by @frances-h
* Cannot use `HMASynthesizer.fit_processed_data` more than once (`KeyError`) - Issue [#1240](https://github.com/sdv-dev/SDV/issues/1240) by @frances-h
* Function `get_available_demos` crashes if a dataset's `num-tables` or `size-MB` cannot be found - Issue [#1215](https://github.com/sdv-dev/SDV/issues/1215) by @amontanez24
* Cannot supply a natural key to `HMASynthesizer` (where `sdtype` is custom): Error in `sample` - Issue [#1214](https://github.com/sdv-dev/SDV/issues/1214) by @pvk-developer
* Unable to sample when using a `PseudoAnonymizedFaker` - Issue [#1207](https://github.com/sdv-dev/SDV/issues/1207) by @pvk-developer
* Incorrect `sdtype` specified in demo dataset `student_placements_pii` - Issue [#1206](https://github.com/sdv-dev/SDV/issues/1206) by @amontanez24
* Auto assigned transformers for datetime columns don't have the right parameters - Issue [#1204](https://github.com/sdv-dev/SDV/issues/1204) by @pvk-developer
* Cannot apply `Inequality` constraint on demo dataset's datetime columns - Issue [#1203](https://github.com/sdv-dev/SDV/issues/1203) by @pvk-developer
* pii should not be required to auto-assign faker transformers - Issue [#1194](https://github.com/sdv-dev/SDV/issues/1194) by @pvk-developer
* Misc. bug fixes for SDV 1.0.0 - Issue [#1193](https://github.com/sdv-dev/SDV/issues/1193) by @pvk-developer
* Small bug fixes in demo module - Issue [#1192](https://github.com/sdv-dev/SDV/issues/1192) by @pvk-developer
* Foreign Keys are added as Alternate Keys when upgrading - Issue [#1143](https://github.com/sdv-dev/SDV/issues/1143) by @pvk-developer
* Alternate keys not unique when assigned to a semantic type - Issue [#1111](https://github.com/sdv-dev/SDV/issues/1111) by @pvk-developer
* Synthesizer errors if column is semantic type and pii is False - Issue [#1110](https://github.com/sdv-dev/SDV/issues/1110) by @fealho
* Sampled values not unique if primary key is numerical - Issue [#1109](https://github.com/sdv-dev/SDV/issues/1109) by @pvk-developer
* Validate not called during synthesizer creation - Issue [#1105](https://github.com/sdv-dev/SDV/issues/1105) by @pvk-developer
* SingleTableSynthesizer fit doesn't update rounding - Issue [#1104](https://github.com/sdv-dev/SDV/issues/1104) by @amontanez24
* Method `auto_assign_tranformers` always sets `enforce_min_max_values=True` - Issue [#1095](https://github.com/sdv-dev/SDV/issues/1095) by @fealho
* Sampled context columns in PAR must be in the same order - Issue [#1052](https://github.com/sdv-dev/SDV/issues/1052) by @amontanez24
* Incorrect schema version printing during detect_table_from_dataframe - Issue [#1038](https://github.com/sdv-dev/SDV/issues/1038) by @amontanez24
* Same relationship can be added twice to MultiTableMetadata - Issue [#1031](https://github.com/sdv-dev/SDV/issues/1031) by @amontanez24
* Miscellaneous metadata bugs - Issue [#1026](https://github.com/sdv-dev/SDV/issues/1026) by @amontanez24
#### Maintenance
* SDV Package Maintenance Updates - Issue [#1140](https://github.com/sdv-dev/SDV/issues/1140) by @amontanez24
#### Internal
* Add integration tests for 'Synthesize Sequences' demo - Issue [#1295](https://github.com/sdv-dev/SDV/issues/1295) by @pvk-developer
* Add integration tests for 'Adding Constraints' demo - Issue [#1280](https://github.com/sdv-dev/SDV/issues/1280) by @pvk-developer
* Add integration tests to the 'Use Your Own Data' demo - Issue [#1278](https://github.com/sdv-dev/SDV/issues/1278) by @frances-h
* Add integration tests for 'Synthesize Multi Tables' demo - Issue [#1277](https://github.com/sdv-dev/SDV/issues/1277) by @pvk-developer
* Add integration tests for 'Synthesize a Table' demo - Issue [#1276](https://github.com/sdv-dev/SDV/issues/1276) by @frances-h
* Update `get_available_demos` tests - Issue [#1247](https://github.com/sdv-dev/SDV/issues/1247) by @fealho
* Make private attributes public in the metadata - Issue [#1245](https://github.com/sdv-dev/SDV/issues/1245) by @fealho
## 0.18.0 - 2023-01-24
This release adds suppport for Python 3.10 and drops support for 3.6.
### Maintenance
* Drop support for python 3.6 - Issue [#1177](https://github.com/sdv-dev/SDV/issues/1177) by @amontanez24
* Support for python 3.10 - Issue [#939](https://github.com/sdv-dev/SDV/issues/939) by @amontanez24
* Support Python >=3.10,<4 - Issue [#1000](https://github.com/sdv-dev/SDV/issues/1000) by @amontanez24
## 0.17.2 - 2022-12-08
This release fixes a bug in the demo module related to loading the demo data with constraints. It also adds a name to the demo datasets. Finally, it bumps the version of `SDMetrics` used.
### Maintenance
* Upgrade SDMetrics requirement to 0.8.0 - Issue [#1125](https://github.com/sdv-dev/SDV/issues/1125) by @katxiao
### New Features
* Provide a name for the default demo datasets - Issue [#1124](https://github.com/sdv-dev/SDV/issues/1124) by @amontanez24
### Bugs Fixed
* Cannot load_tabular_demo with metadata - Issue [#1123](https://github.com/sdv-dev/SDV/issues/1123) by @amontanez24
## 0.17.1 - 2022-09-29
This release bumps the dependency requirements to use the latest version of `SDMetrics`.
### Maintenance
* Patch release: Bump required version for SDMetrics - Issue [#1010](https://github.com/sdv-dev/SDV/issues/1010) by @katxiao
## 0.17.0 - 2022-09-09
This release updates the code to use RDT version 1.2.0 and greater, so that those new features are now available in SDV. This changes the transformers that are available in SDV models to be those that are in RDT version 1.2.0. As a result, some arguments for initializing models have changed.
Additionally, this release fixes bugs related to loading models with custom constraints. It also fixes a bug that added `NaNs` to the index of sampled data when using `sample_remaining_columns`.
### Bugs Fixed
* Incorrect rounding in Custom Constraint example - Issue [#941](https://github.com/sdv-dev/SDV/issues/941) by @amontanez24
* Can't save the model if use the custom constraint - Issue [#928](https://github.com/sdv-dev/SDV/issues/928) by @pvk-developer
* User Guide code fixes - Issue [#983](https://github.com/sdv-dev/SDV/issues/983) by @amontanez24
* Index contains NaNs when using sample_remaining_columns - Issue [#985](https://github.com/sdv-dev/SDV/issues/985) by @amontanez24
* Cannot sample after loading a model with custom constraints: TypeError - Issue [#984](https://github.com/sdv-dev/SDV/issues/984) by @pvk-developer
* Set HyperTransformer config manually, based on Metadata if given - Issue [#982](https://github.com/sdv-dev/SDV/issues/982) by @pvk-developer
### New Features
* Change default metrics for evaluate - Issue [#949](https://github.com/sdv-dev/SDV/issues/949) by @fealho
### Maintenance
* Update the RDT version to 1.0 - Issue [#897](https://github.com/sdv-dev/SDV/issues/897) by @pvk-developer
## 0.16.0 - 2022-07-21
This release brings user friendly improvements and bug fixes on the `SDV` constraints, to help
users generate their synthetic data easily.
Some predefined constraints have been renamed and redefined to be more user friendly & consistent.
The custom constraint API has also been updated for usability. The SDV now automatically determines
the best `handling_strategy` to use for each constraint, attempting `transform` by default and
falling back to `reject_sampling` otherwise. The `handling_strategy` parameters are no longer
included in the API.
Finally, this version of `SDV` also unifies the parameters for all sampling related methods for
all models (including TabularPreset).
### Changes to Constraints
* `GreatherThan` constraint is now separated in two new constraints: `Inequality`, which is
  intended to be used between two columns, and `ScalarInequality`, which is intended to be used
  between a column and a scalar.
* `Between` constraint is now separated in two new constraints: `Range`, which is intended to
  be used between three columns, and `ScalarRange`, which is intended to be used between a column
  and low and high scalar values.
* `FixedIncrements` a new constraint that makes the data increment by a certain value.
* New `create_custom_constraint` function available to create custom constraints.
### Removed Constraints
* `Rounding` Rounding is automatically being handled by the ``rdt.HyperTransformer``.
* `ColumnFormula` the `create_custom_constraint` takes place over this one and allows more
  advanced usage for the end users.
### New Features
* Improve error message for invalid constraints - Issue [#801](https://github.com/sdv-dev/SDV/issues/801) by @fealho
* Numerical Instability in Constrained GaussianCopula - Issue [#806](https://github.com/sdv-dev/SDV/issues/806) by @fealho
* Unify sampling params for reject sampling - Issue [#809](https://github.com/sdv-dev/SDV/issues/809) by @amontanez24
* Split `GreaterThan` constraint into `Inequality` and `ScalarInequality` - Issue [#814](https://github.com/sdv-dev/SDV/issues/814) by @fealho
* Split `Between` constraint into `Range` and `ScalarRange` - Issue [#815](https://github.com/sdv-dev/SDV/issues/815) @pvk-developer
* Change `columns` to `column_names` in `OneHotEncoding` and `Unique` constraints - Issue [#816](https://github.com/sdv-dev/SDV/issues/816) by @amontanez24
* Update columns parameter in `Positive` and `Negative` constraint - Issue [#817](https://github.com/sdv-dev/SDV/issues/817) by @fealho
* Create `FixedIncrements` constraint - Issue [#818](https://github.com/sdv-dev/SDV/issues/818) by @amontanez24
* Improve datetime handling in `ScalarInequality` and `ScalarRange` constraints - Issue [#819](https://github.com/sdv-dev/SDV/issues/819) by @pvk-developer
* Support strict boundaries even when transform strategy is used - Issue [#820](https://github.com/sdv-dev/SDV/issues/820) by @fealho
* Add `create_custom_constraint` factory method - Issue [#836](https://github.com/sdv-dev/SDV/issues/836) by @fealho
### Internal Improvements
* Remove `handling_strategy` parameter - Issue [#833](https://github.com/sdv-dev/SDV/issues/833) by @amontanez24
* Remove `fit_columns_model` parameter - Issue [#834](https://github.com/sdv-dev/SDV/issues/834) by @pvk-developer
* Remove the `ColumnFormula` constraint - Issue [#837](https://github.com/sdv-dev/SDV/issues/837) by @amontanez24
* Move `table_data.copy` to base class of constraints - Issue [#845](https://github.com/sdv-dev/SDV/issues/845) by @fealho
### Bugs Fixed
* Numerical Instability in Constrained GaussianCopula - Issue [#801](https://github.com/sdv-dev/SDV/issues/801) by @tlranda and @fealho
* Fix error message for `FixedIncrements` - Issue [#865](https://github.com/sdv-dev/SDV/issues/865) by @pvk-developer
* Fix constraints with conditional sampling - Issue [#866](https://github.com/sdv-dev/SDV/issues/866) by @amontanez24
* Fix error message in `ScalarInequality` - Issue [#868](https://github.com/sdv-dev/SDV/issues/868) by @pvk-developer
* Cannot use `max_tries_per_batch` on sample: `TypeError: sample() got an unexpected keyword argument 'max_tries_per_batch'` - Issue [#885](https://github.com/sdv-dev/SDV/issues/885) by @amontanez24
* Conditional sampling + batch size: `ValueError: Length of values (1) does not match length of index (5)` - Issue [#886](https://github.com/sdv-dev/SDV/issues/886) by @amontanez24
* `TabularPreset` doesn't support new sampling parameters - Issue [#887](https://github.com/sdv-dev/SDV/issues/887) by @fealho
* Conditional Sampling: `batch_size` is being set to `None` by default? - Issue [#889](https://github.com/sdv-dev/SDV/issues/889) by @amontanez24
* Conditional sampling using GaussianCopula inefficient when categories are noised - Issue [#910](https://github.com/sdv-dev/SDV/issues/910) by @amontanez24
### Documentation Changes
* Show the `API` for `TabularPreset` models - Issue [#854](https://github.com/sdv-dev/SDV/issues/854) by @katxiao
* Update handling constraints doc - Pull Request [#856](https://github.com/sdv-dev/SDV/issues/856) by @amontanez24
* Update custom costraints documentation - Pull Request [#857](https://github.com/sdv-dev/SDV/issues/857) by @pvk-developer
## 0.15.0 - 2022-05-25
This release improves the speed of the `GaussianCopula` model by removing logic that previously searched for the appropriate distribution to
use. It also fixes a bug that was happening when conditional sampling was used with the `TabularPreset`.
The rest of the release focuses on making changes to improve constraints including changing the `UniqueCombinations` constraint to `FixedCombinations`,
making the `Unique` constraint work with missing values and erroring when null values are seen in the `OneHotEncoding` constraint.
### New Features
* Silence warnings coming from univariate fit in copulas - Issue [#769](https://github.com/sdv-dev/SDV/issues/769) by @pvk-developer
* Remove parameters related to distribution search and change default - Issue [#767](https://github.com/sdv-dev/SDV/issues/767) by @fealho
* Update the UniqueCombinations constraint - Issue [#793](https://github.com/sdv-dev/SDV/issues/793) by @fealho
* Make Unique constraint works with nans - Issue [#797](https://github.com/sdv-dev/SDV/issues/797) by @fealho
* Error out if nans in OneHotEncoding - Issue [#800](https://github.com/sdv-dev/SDV/issues/800) by @amontanez24
### Bugs Fixed
* Unable to sample conditionally in Tabular_Preset model - Issue [#796](https://github.com/sdv-dev/SDV/issues/796) by @katxiao
### Documentation Changes
* Support GPU computing and progress track? - Issue [#478](https://github.com/sdv-dev/SDV/issues/478) by @fealho
## 0.14.1 - 2022-05-03
This release adds a `TabularPreset`, available in the `sdv.lite` module, which allows users to easily optimize a tabular model for speed.
In this release, we also include bug fixes for sampling with conditions, an unresolved warning, and setting field distributions. Finally,
we include documentation updates for sampling and the new `TabularPreset`.
### Bugs Fixed
* Sampling with conditions={column: 0.0} for float columns doesn't work - Issue [#525](https://github.com/sdv-dev/SDV/issues/525) by @shlomihod and @tssbas
* resolved FutureWarning with Pandas replaced append by concat - Issue [#759](https://github.com/sdv-dev/SDV/issues/759) by @Deathn0t
* Field distributions bug in CopulaGAN - Issue [#747](https://github.com/sdv-dev/SDV/issues/747) by @katxiao
* Field distributions bug in GaussianCopula - Issue [#746](https://github.com/sdv-dev/SDV/issues/746) by @katxiao
### New Features
* Set default transformer to categorical_fuzzy - Issue [#768](https://github.com/sdv-dev/SDV/issues/768) by @amontanez24
* Model nulls normally when tabular preset has constraints - Issue [#764](https://github.com/sdv-dev/SDV/issues/764) by @katxiao
* Don't modify my metadata object - Issue [#754](https://github.com/sdv-dev/SDV/issues/754) by @amontanez24
* Presets should be able to handle constraints - Issue [#753](https://github.com/sdv-dev/SDV/issues/753) by @katxiao
* Change preset optimize_for --> name - Issue [#749](https://github.com/sdv-dev/SDV/issues/749) by @katxiao
* Create a speed optimized Preset - Issue [#716](https://github.com/sdv-dev/SDV/issues/716) by @katxiao
### Documentation Changes
* Add tabular preset docs - Issue [#777](https://github.com/sdv-dev/SDV/issues/777) by @katxiao
* sdv.sampling module is missing from the API - Issue [#740](https://github.com/sdv-dev/SDV/issues/740) by @katxiao
## 0.14.0 - 2022-03-21
This release updates the sampling API and splits the existing functionality into three methods - `sample`, `sample_conditions`,
and `sample_remaining_columns`. We also add support for sampling in batches, displaying a progress bar when sampling with more than one batch,
sampling deterministically, and writing the sampled results to an output file. Finally, we include fixes for sampling with conditions
and updates to the documentation.
### Bugs Fixed
* Fix write to file in sampling - Issue [#732](https://github.com/sdv-dev/SDV/issues/732) by @katxiao
* Conditional sampling doesn't work if the model has a CustomConstraint - Issue [#696](https://github.com/sdv-dev/SDV/issues/696) by @katxiao
### New Features
* Updates to GaussianCopula conditional sampling methods - Issue [#729](https://github.com/sdv-dev/SDV/issues/729) by @katxiao
* Update conditional sampling errors - Issue [#730](https://github.com/sdv-dev/SDV/issues/730) by @katxiao
* Enable Batch Sampling + Progress Bar - Issue [#693](https://github.com/sdv-dev/SDV/issues/693) by @katxiao
* Create sample_remaining_columns() method - Issue [#692](https://github.com/sdv-dev/SDV/issues/692) by @katxiao
* Create sample_conditions() method - Issue [#691](https://github.com/sdv-dev/SDV/issues/691) by @katxiao
* Improve sample() method - Issue [#690](https://github.com/sdv-dev/SDV/issues/690) by @katxiao
* Create Condition object - Issue [#689](https://github.com/sdv-dev/SDV/issues/689) by @katxiao
* Is it possible to generate data with new set of primary keys? - Issue [#686](https://github.com/sdv-dev/SDV/issues/686) by @katxiao
* No way to fix the random seed? - Issue [#157](https://github.com/sdv-dev/SDV/issues/157) by @katxiao
* Can you set a random state for the sdv.tabular.ctgan.CTGAN.sample method? - Issue [#515](https://github.com/sdv-dev/SDV/issues/515) by @katxiao
* generating different synthetic data while training the model multiple times. - Issue [#299](https://github.com/sdv-dev/SDV/issues/299) by @katxiao
### Documentation Changes
* Typo in the document documentation - Issue [#680](https://github.com/sdv-dev/SDV/issues/680) by @katxiao
## 0.13.1 - 2021-12-22
This release adds support for passing tabular constraints to the HMA1 model, and adds more explicit error handling for
metric evaluation. It also includes a fix for using categorical columns in the PAR model and documentation updates
for metadata and HMA1.
### Bugs Fixed
* Categorical column after sequence_index column - Issue [#314](https://github.com/sdv-dev/SDV/issues/314) by @fealho
### New Features
* Support passing tabular constraints to the HMA1 model - Issue [#296](https://github.com/sdv-dev/SDV/issues/296) by @katxiao
* Metric evaluation error handling metrics - Issue [#638](https://github.com/sdv-dev/SDV/issues/638) by @katxiao
### Documentation Changes
* Make true/false values lowercase in Metadata Schema specification - Issue [#664](https://github.com/sdv-dev/SDV/issues/664) by @katxiao
* Update docstrings for hma1 methods - Issue [#642](https://github.com/sdv-dev/SDV/issues/642) by @katxiao
## 0.13.0 - 2021-11-22
This release makes multiple improvements to different `Constraint` classes. The `Unique` constraint can now
handle columns with the name `index` and no longer crashes on subsets of the original data. The `Between`
constraint can now handle columns with nulls properly. The memory of all constraints was also improved.
Various other features and fixes were added. Conditional sampling no longer crashes when the `num_rows` argument
is not provided. Multiple localizations can now be used for PII fields. Scaffolding for integration tests was added
and the workflows now run `pip check`.
Additionally, this release adds support for Python 3.9!
### Bugs Fixed
* Gaussian Copula – Memory Issue in Release 0.10.0 - Issue [#459](https://github.com/sdv-dev/SDV/issues/459) by @xamm
* Applying Unique Constraint errors when calling model.fit() on a subset of data - Issue [#610](https://github.com/sdv-dev/SDV/issues/610) by @xamm
* Calling sampling with conditions and without num_rows crashes - Issue [#614](https://github.com/sdv-dev/SDV/issues/614) by @xamm
* Metadata.visualize with path parameter throws AttributeError - Issue [#634](https://github.com/sdv-dev/SDV/issues/634) by @xamm
* The Unique constraint crashes when the data contains a column called index - Issue [#616](https://github.com/sdv-dev/SDV/issues/616) by @xamm
* The Unique constraint cannot handle non-default index - Issue [#617](https://github.com/sdv-dev/SDV/issues/617) by @xamm
* ConstraintsNotMetError when applying Between constraint on datetime columns containing null values - Issue [#632](https://github.com/sdv-dev/SDV/issues/632) by @katxiao
### New Features
* Adds Multi localisations feature for PII fields defined in #308 - PR [#609](https://github.com/sdv-dev/SDV/pull/609) by @xamm
### Housekeeping Tasks
* Support latest version of Faker - Issue [#621](https://github.com/sdv-dev/SDV/issues/621) by @katxiao
* Add scaffolding for Metadata integration tests - Issue [#624](https://github.com/sdv-dev/SDV/issues/624) by @katxiao
* Add support for Python 3.9 - Issue [#631](https://github.com/sdv-dev/SDV/issues/631) by @amontanez24
### Internal Improvements
* Add pip check to CI workflows - Issue [#626](https://github.com/sdv-dev/SDV/issues/626) by @pvk-developer
### Documentation Changes
* Anonymizing PII in single table tutorials states address field as e-mail type - Issue [#604](https://github.com/sdv-dev/SDV/issues/604) by @xamm
Special thanks to @xamm, @katxiao, @pvk-developer and @amontanez24 for all the work that made this release possible!
## 0.12.1 - 2021-10-12
This release fixes bugs in constraints, metadata behavior, and SDV documentation. Specifically, we added
proper handling of data containing null values for constraints and timeseries data, and updated the
default metadata detection behavior.
### Bugs Fixed
* ValueError: The parameter loc has invalid values - Issue [#353](https://github.com/sdv-dev/SDV/issues/353) by @fealho
* Gaussian Copula is generating different data with metadata and without metadata - Issue [#576](https://github.com/sdv-dev/SDV/issues/576) by @katxiao
* Make pomegranate an optional dependency - Issue [#567](https://github.com/sdv-dev/SDV/issues/567) by @katxiao
* Small wording change for Question Issue Template - Issue [#571](https://github.com/sdv-dev/SDV/issues/571) by @katxiao
* ConstraintsNotMetError when using GreaterThan constraint with datetime - Issue [#590](https://github.com/sdv-dev/SDV/issues/590) by @katxiao
* GreaterThan constraint crashing with NaN values - Issue [#592](https://github.com/sdv-dev/SDV/issues/592) by @katxiao
* Null values in GreaterThan constraint raises error - Issue [#589](https://github.com/sdv-dev/SDV/issues/589) by @katxiao
* ColumnFormula raises ConstraintsNotMetError when checking NaN values - Issue [#593](https://github.com/sdv-dev/SDV/issues/593) by @katxiao
* GreaterThan constraint raises TypeError when using datetime - Issue [#596](https://github.com/sdv-dev/SDV/issues/596) by @katxiao
* Fix repository language - Issue [#464](https://github.com/sdv-dev/SDV/issues/464) by @fealho
* Update __init__.py - Issue [#578](https://github.com/sdv-dev/SDV/issues/578) by @dyuliu
* IndexingError: Unalignable boolean - Issue [#446](https://github.com/sdv-dev/SDV/issues/446) by @fealho
## 0.12.0 - 2021-08-17
This release focuses on improving and expanding upon the existing constraints. More specifically, the users can now
(1) specify multiple columns in `Positive` and `Negative` constraints, (2) use the new `Unique`constraint and
(3) use datetime data with the `Between` constraint. Additionaly, error messages have been added and updated
to provide more useful feedback to the user.
Besides the added features, several bugs regarding the `UniqueCombinations` and `ColumnFormula` constraints have been fixed,
and an error in the metadata.json for the `student_placements` dataset was corrected. The release also added documentation
for the `fit_columns_model` which affects the majority of the available constraints.
### New Features
* Change default fit_columns_model to False - Issue [#550](https://github.com/sdv-dev/SDV/issues/550) by @katxiao
* Support multi-column specification for positive and negative constraint - Issue [#545](https://github.com/sdv-dev/SDV/issues/545) by @sarahmish
* Raise error when multiple constraints can't be enforced - Issue [#541](https://github.com/sdv-dev/SDV/issues/541) by @amontanez24
* Create Unique Constraint - Issue [#532](https://github.com/sdv-dev/SDV/issues/532) by @amontanez24
* Passing invalid conditions when using constraints produces unreadable errors - Issue [#511](https://github.com/sdv-dev/SDV/issues/511) by @katxiao
* Improve error message for ColumnFormula constraint when constraint column used in formula - Issue [#508](https://github.com/sdv-dev/SDV/issues/508) by @katxiao
* Add datetime functionality to Between constraint - Issue [#504](https://github.com/sdv-dev/SDV/issues/504) by @katxiao
### Bugs Fixed
* UniqueCombinations constraint with handling_strategy = 'transform' yields synthetic data with nan values - Issue [#521](https://github.com/sdv-dev/SDV/issues/521) by @katxiao and @csala
* UniqueCombinations constraint outputting wrong data type - Issue [#510](https://github.com/sdv-dev/SDV/issues/510) by @katxiao and @csala
* UniqueCombinations constraint on only one column gets stuck in an infinite loop - Issue [#509](https://github.com/sdv-dev/SDV/issues/509) by @katxiao
* Conditioning on a non-constraint column using the ColumnFormula constraint - Issue [#507](https://github.com/sdv-dev/SDV/issues/507) by @katxiao
* Conditioning on the constraint column of the ColumnFormula constraint - Issue [#506](https://github.com/sdv-dev/SDV/issues/506) by @katxiao
* Update metadata.json for duration of student_placements dataset - Issue [#503](https://github.com/sdv-dev/SDV/issues/503) by @amontanez24
* Unit test for HMA1 when working with a single child row per parent row - Issue [#497](https://github.com/sdv-dev/SDV/issues/497) by @pvk-developer
* UniqueCombinations constraint for more than 2 columns - Issue [#494](https://github.com/sdv-dev/SDV/issues/494) by @katxiao and @csala
### Documentation Changes
* Add explanation of fit_columns_model to API docs - Issue [#517](https://github.com/sdv-dev/SDV/issues/517) by @katxiao
## 0.11.0 - 2021-07-12
This release primarily addresses bugs and feature requests related to using constraints for the single-table models.
Users can now enforce scalar comparison with the existing `GreaterThan` constraint and apply 5 new constraints: `OneHotEncoding`, `Positive`, `Negative`, `Between` and `Rounding`.
Additionally, the SDV will now auto-apply constraints for rounding numerical values, and for keeping the data within the observed bounds.
All related user guides are updated with the new functionality.
### New Features
* Add OneHotEncoding Constraint - Issue [#303](https://github.com/sdv-dev/SDV/issues/303) by @fealho
* GreaterThan Constraint should apply to scalars - Issue [#410](https://github.com/sdv-dev/SDV/issues/410) by @amontanez24
* Improve GreaterThan constraint - Issue [#368](https://github.com/sdv-dev/SDV/issues/368) by @amontanez24
* Add Non-negative and Positive constraints across multiple columns- Issue [#409](https://github.com/sdv-dev/SDV/issues/409) by @amontanez24
* Add Between values constraint - Issue [#367](https://github.com/sdv-dev/SDV/issues/367) by @fealho
* Ensure values fall within the specified range - Issue [#423](https://github.com/sdv-dev/SDV/issues/423) by @amontanez24
* Add Rounding constraint - Issue [#482](https://github.com/sdv-dev/SDV/issues/482) by @katxiao
* Add rounding and min/max arguments that are passed down to the NumericalTransformer - Issue [#491](https://github.com/sdv-dev/SDV/issues/491) by @amontanez24
### Bugs Fixed
* GreaterThan constraint between Date columns rasises TypeError - Issue [#421](https://github.com/sdv-dev/SDV/issues/421) by @amontanez24
* GreaterThan constraint's transform strategy fails on columns that are not float - Issue [#448](https://github.com/sdv-dev/SDV/issues/448) by @amontanez24
* AttributeError on UniqueCombinations constraint with non-strings - Issue [#196](https://github.com/sdv-dev/SDV/issues/196) by @katxiao
* Use reject sampling to sample missing columns for constraints - Issue [#435](https://github.com/sdv-dev/SDV/issues/435) by @amontanez24
### Documentation Changes
* Ensure privacy metrics are available in the API docs - Issue [#458](https://github.com/sdv-dev/SDV/issues/458) by @fealho
* Ensure forumla constraint is called ColumnFormula everywhere in the docs - Issue [#449](https://github.com/sdv-dev/SDV/issues/449) by @fealho
## 0.10.1 - 2021-06-10
This release changes the way we sample conditions to not only group by the conditions passed by the user, but also by the transformed conditions that result from them.
### Issues resolved
* Conditionally sampling on variable in constraint should have variety for other variables - Issue [#440](https://github.com/sdv-dev/SDV/issues/440) by @amontanez24
## 0.10.0 - 2021-05-21
This release improves the constraint functionality by allowing constraints and conditions
at the same time. Additional changes were made to update tutorials.
### Issues resolved
* Not able to use constraints and conditions in the same time - Issue [#379](https://github.com/sdv-dev/SDV/issues/379)
by @amontanez24
* Update benchmarking user guide for reading private datasets - Issue [#427](https://github.com/sdv-dev/SDV/issues/427)
by @katxiao
## 0.9.1 - 2021-04-29
This release broadens the constraint functionality by allowing for the `ColumnFormula`
constraint to take lambda functions and returned functions as an input for its formula.
It also improves conditional sampling by ensuring that any `id` fields generated by the
model remain unique throughout the sampled data.
The `CTGAN` model was improved by adjusting a default parameter to be more mathematically
correct.
Additional changes were made to improve tutorials as well as fix fragile tests.
### Issues resolved
* Tutorials test sometimes fails - Issue [#355](https://github.com/sdv-dev/SDV/issues/355)
by @fealho
* Duplicate IDs when using reject-sampling - Issue [#331](https://github.com/sdv-dev/SDV/issues/331)
by @amontanez24 and @csala
* discriminator_decay should be initialized at 1e-6 but it's 0 - Issue [#401](https://github.com/sdv-dev/SDV/issues/401) by @fealho and @YoucefZemmouri
* Tutorial typo - Issue [#380](https://github.com/sdv-dev/SDV/issues/380) by @fealho
* Request for sdv.constraint.ColumnFormula for a wider range of function - Issue [#373](https://github.com/sdv-dev/SDV/issues/373) by @amontanez24 and @JetfiRex
## 0.9.0 - 2021-03-31
This release brings new privacy metrics to the evaluate framework which help to determine
if the real data could be obtained or deduced from the synthetic samples.
Additionally, now there is a normalized score for the metrics, which stays between `0` and `1`.
There are improvements that reduce the usage of memory ram when sampling new data. Also there
is a new parameter to control the reject sampling crash, `graceful_reject_sampling`, which if
set to `True` and if it's not possible to generate all the requested rows, it will just issue a
warning and return whatever it was able to generate.
The `Metadata` object can now be visualized using different combinations of `names` and `details`,
which can be set to `True` or `False` in order to display only the table names with details or
without. There is also an improvement on the `validation`, which now will display all the errors
found at the end of the validation instead of only the first one.
This version also exposes all the hyperparameters of the models `CTGAN` and `TVAE` to allow a more
advanced usage. There is also a fix for the `TVAE` model on small datasets and it's performance
with `NaN` values has been improved. There is a fix for when using
`UniqueCombinationConstraint` with the `transform` strategy.
### Issues resolved
* Memory Usage Gaussian Copula Trained Model consuming high memory when generating synthetic data - Issue [#304](https://github.com/sdv-dev/SDV/issues/304) by @pvk-developer and @AnupamaGangadhar
* Add option to visualize metadata with only table names - Issue [#347](https://github.com/sdv-dev/SDV/issues/347) by @csala
* Add sample parameter to control reject sampling crash - Issue [#343](https://github.com/sdv-dev/SDV/issues/343) by @fealho
* Verbose metadata validation - Issue [#348](https://github.com/sdv-dev/SDV/issues/348) by @csala
* Missing the introduction of custom specification for hyperparameters in the TVAE model - Issue [#344](https://github.com/sdv-dev/SDV/issues/343) by @imkhoa99 and @pvk-developer
## 0.8.0 - 2021-02-24
This version adds conditional sampling for tabular models by combining a reject-sampling
strategy with the native conditional sampling capabilities from the gaussian copulas.
It also introduces several upgrades on the HMA1 algorithm that improve data quality and
robustness in the multi-table scenarios by making changes in how the parameters of the child
tables are aggregated on the parent tables, including a complete rework of how the correlation
matrices are modeled and rebuild after sampling.
### Issues resolved
* Fix probabilities contain NaN error - Issue [#326](https://github.com/sdv-dev/SDV/issues/326) by @csala
* Conditional Sampling for tabular models - Issue [#316](https://github.com/sdv-dev/SDV/issues/316) by @fealho and @csala
* HMA1: LinAlgError: SVD did not converge - Issue [#240](https://github.com/sdv-dev/SDV/issues/240) by @csala
## 0.7.0 - 2021-01-27
This release introduces a few changes in the HMA1 relational algorithm to decrease modeling
and sampling times, while also ensuring that correlations are properly kept across tables
and also adding support for some relational schemas that were not supported before.
A few changes in constraints and tabular models also ensure that situations that produced
errors before now work without errors.
### Issues resolved
* Fix unique key generation - Issue [#306](https://github.com/sdv-dev/SDV/issues/306) by @fealho
* Ensure tables that contain nothing but ids can be modeled - Issue [#302](https://github.com/sdv-dev/SDV/issues/302) by @csala
* Metadata visualization improvements - Issue [#301](https://github.com/sdv-dev/SDV/issues/301) by @csala
* Multi-parent re-model and re-sample issue - Issue [#298](https://github.com/sdv-dev/SDV/issues/298) by @csala
* Support datetimes in GreaterThan constraint - Issue [#266](https://github.com/sdv-dev/SDV/issues/266) by @rollervan
* Support for multiple foreign keys in one table - Issue [#185](https://github.com/sdv-dev/SDV/issues/185) by @csala
## 0.6.1 - 2020-12-31
SDMetrics version is updated to include the new Time Series metrics, which have also
been added to the API Reference and User Guides documentation. Additionally,
a few code has been refactored to reduce external dependencies and a few minor bugs
related to single table constraints have been fixed
### Issues resolved
* Add timeseries metrics and user guides - [Issue #289](https://github.com/sdv-dev/SDV/issues/289) by @csala
* Add functions to generate regex ids - [Issue #288](https://github.com/sdv-dev/SDV/issues/288) by @csala
* Saving a fitted tabular model with UniqueCombinations constraint raises PicklingError -
  [Issue #286](https://github.com/sdv-dev/SDV/issues/288) by @csala
* Constraints: `handling_strategy='reject_sampling'` causes `'ZeroDivisionError: division by zero'` -
  [Issue #285](https://github.com/sdv-dev/SDV/issues/285) by @csala
## 0.6.0 - 2020-12-22
This release updates to the latest CTGAN, RDT and SDMetrics libraries to introduce a
new TVAE model, multiple new metrics for single table and multi table, and fixes
issues in the re-creation of tabular models from a metadata dict.
### Issues resolved
* Upgrade to SDMetrics v0.1.0 and add `sdv.metrics` module - [Issue #281](https://github.com/sdv-dev/SDV/issues/281) by @csala
* Upgrade to CTGAN 0.3.0 and add TVAE model - [Issue #278](https://github.com/sdv-dev/SDV/issues/278) by @fealho
* Add `dtype_transformers` to `Table.from_dict` - [Issue #276](https://github.com/sdv-dev/SDV/issues/276) by @csala
* Fix Metadata `from_dict` behavior - [Issue #275](https://github.com/sdv-dev/SDV/issues/275) by @csala
## 0.5.0 - 2020-11-25
This version updates the dependencies and makes a few internal changes in order
to ensure that SDV works properly on Windows Systems, making this the first
release to be officially supported on Windows.
Apart from this, some more internal changes have been made to solve a few minor
issues from the older versions while also improving the processing speed when
processing relational datasets with the default parameters.
### API breaking changes
* The `distribution` argument of the `GaussianCopula` has been renamed to `field_distributions`.
* The `HMA1` and `SDV` classes now use the `categorical_fuzzy` transformer by default instead of
  the `one_hot_encoding` one.
### Issues resolved
* GaussianCopula: rename `distribution` argument to `field_distributions` - [Issue #237](https://github.com/sdv-dev/SDV/issues/237) by @csala
* GaussianCopula: Improve error message if an invalid distribution name is passed - [Issue #220](https://github.com/sdv-dev/SDV/issues/220) by csala
* Import urllib.request explicitly - [Issue #227](https://github.com/sdv-dev/SDV/issues/227) by @csala
* TypeError: cannot astype a datetimelike from [datetime64[ns]] to [int32] - [Issue #218](https://github.com/sdv-dev/SDV/issues/218) by @csala
* Change default categorical transformer to `categorical_fuzzy` in HMA1 - [Issue #214](https://github.com/sdv-dev/SDV/issues/214) by @csala
* Integer categoricals being sampled as strings instead of integer values - [Issue #194](https://github.com/sdv-dev/SDV/issues/194) by @csala
## 0.4.5 - 2020-10-17
In this version a new family of models for Synthetic Time Series Generation is introduced
under the `sdv.timeseries` sub-package. The new family of models now includes a new class
called `PAR`, which implements a *Probabilistic AutoRegressive* model.
This version also adds support for composite primary keys and regex based generation of id
fields in tabular models and drops Python 3.5 support.
### Issues resolved
* Drop python 3.5 support - [Issue #204](https://github.com/sdv-dev/SDV/issues/204) by @csala
* Support composite primary keys in tabular models - [Issue #207](https://github.com/sdv-dev/SDV/issues/207) by @csala
* Add the option to generate string `id` fields based on regex on tabular models - [Issue #208](https://github.com/sdv-dev/SDV/issues/208) by @csala
* Synthetic Time Series - [Issue #142](https://github.com/sdv-dev/SDV/issues/142) by @csala
## 0.4.4 - 2020-10-06
This version adds a new tabular model based on combining the CTGAN model with the reversible
transformation applied in the GaussianCopula model that converts random variables with
arbitrary distributions to new random variables with standard normal distribution.
The reversible transformation is handled by the GaussianCopulaTransformer recently added to RDT.
### Issues resolved
* Add CopulaGAN Model - [Issue #202](https://github.com/sdv-dev/SDV/issues/202) by @csala
## 0.4.3 - 2020-09-28
This release moves the models and algorithms related to generation of synthetic
relational data to a new `sdv.relational` subpackage (Issue #198)
As part of the change, also the old `sdv.models` have been removed and now
relational model is based on the recently introduced `sdv.tabular` models.
## 0.4.2 - 2020-09-19
In this release the `sdv.evaluation` module has been reworked to include 4 different
metrics and in all cases return a normalized score between 0 and 1.
Included metrics are:
- `cstest`
- `kstest`
- `logistic_detection`
- `svc_detection`
## 0.4.1 - 2020-09-07
This release fixes a couple of minor issues and introduces an important rework of the
User Guides section of the documentation.
### Issues fixed
* Error Message: "make sure the Graphviz executables are on your systems' PATH" - [Issue #182](https://github.com/sdv-dev/SDV/issues/182) by @csala
* Anonymization mappings leak - [Issue #187](https://github.com/sdv-dev/SDV/issues/187) by @csala
## 0.4.0 - 2020-08-08
In this release SDV gets new documentation, new tutorials, improvements to the Tabular API
and broader python and dependency support.
Complete list of changes:
* New Documentation site based on the `pydata-sphinx-theme`.
* New User Guides and Notebook tutorials.
* New Developer Guides section within the docs with details about the SDV architecture,
  the ecosystem libraries and how to extend and contribute to the project.
* Improved API for the Tabular models with focus on ease of use.
* Support for Python 3.8 and the newest versions of pandas, scipy and scikit-learn.
* New Slack Workspace for development discussions and community support.
## 0.3.6 - 2020-07-23
This release introduces a new concept of `Constraints`, which allow the user to define
special relationships between columns that will not be handled via modeling.
This is done via a new `sdv.constraints` subpackage which defines some well-known pre-defined
constraints, as well as a generic framework that allows the user to customize the constraints
to their needs as much as necessary.
### New Features
* Support for Constraints - [Issue #169](https://github.com/sdv-dev/SDV/issues/169) by @csala
## 0.3.5 - 2020-07-09
This release introduces a new subpackage `sdv.tabular` with models designed specifically
for single table modeling, while still providing all the usual conveniences from SDV, such
as:
* Seamless multi-type support
* Missing data handling
* PII anonymization
Currently implemented models are:
* GaussianCopula: Multivariate distributions modeled using copula functions. This is stronger
  version, with more marginal distributions and options, than the one used to model multi-table
  datasets.
* CTGAN: GAN-based data synthesizer that can generate synthetic tabular data with high fidelity.
## 0.3.4 - 2020-07-04
### New Features
* Support for Multiple Parents - [Issue #162](https://github.com/sdv-dev/SDV/issues/162) by @csala
* Sample by default the same number of rows as in the original table - [Issue #163](https://github.com/sdv-dev/SDV/issues/163) by @csala
### General Improvements
* Add benchmark - [Issue #165](https://github.com/sdv-dev/SDV/issues/165) by @csala
## 0.3.3 - 2020-06-26
### General Improvements
* Use SDMetrics for evaluation - [Issue #159](https://github.com/sdv-dev/SDV/issues/159) by @csala
## 0.3.2 - 2020-02-03
### General Improvements
* Improve metadata visualization - [Issue #151](https://github.com/sdv-dev/SDV/issues/151) by @csala @JDTheRipperPC
## 0.3.1 - 2020-01-22
### New Features
* Add Metadata Validation - [Issue #134](https://github.com/sdv-dev/SDV/issues/134) by @csala @JDTheRipperPC
* Add Metadata Visualization - [Issue #135](https://github.com/sdv-dev/SDV/issues/135) by @JDTheRipperPC
### General Improvements
* Add path to metadata JSON - [Issue #143](https://github.com/sdv-dev/SDV/issues/143) by @JDTheRipperPC
* Use new Copulas and RDT versions - [Issue #147](https://github.com/sdv-dev/SDV/issues/147) by @csala @JDTheRipperPC
## 0.3.0 - 2019-12-23
### New Features
* Create sdv.models subpackage - [Issue #141](https://github.com/sdv-dev/SDV/issues/141) by @JDTheRipperPC
## 0.2.2 - 2019-12-10
### New Features
* Adapt evaluation to the different data types - [Issue #128](https://github.com/sdv-dev/SDV/issues/128) by @csala @JDTheRipperPC
* Extend `load_demo` functionality to load other datasets - [Issue #136](https://github.com/sdv-dev/SDV/issues/136) by @JDTheRipperPC
## 0.2.1 - 2019-11-25
### New Features
* Methods to generate Metadata from DataFrames - [Issue #126](https://github.com/sdv-dev/SDV/issues/126) by @csala @JDTheRipperPC
## 0.2.0 - 2019-10-11
### New Features
* compatibility with rdt issue 72 - [Issue #120](https://github.com/sdv-dev/SDV/issues/120) by @csala @JDTheRipperPC
### General Improvements
* Error docstring sampler.__fill_text_columns - [Issue #144](https://github.com/sdv-dev/SDV/issues/114) by @JDTheRipperPC
* Reach 90% coverage - [Issue #112](https://github.com/sdv-dev/SDV/issues/112) by @JDTheRipperPC
* Review unittests - [Issue #111](https://github.com/sdv-dev/SDV/issues/111) by @JDTheRipperPC
### Bugs Fixed
* Time required for sample_all function? - [Issue #118](https://github.com/sdv-dev/SDV/issues/118) by @csala @JDTheRipperPC
## 0.1.2 - 2019-09-18
### New Features
* Add option to model the amount of child rows - Issue [93](https://github.com/sdv-dev/SDV/issues/93) by @ManuelAlvarezC
### General Improvements
* Add Evaluation Metrics - Issue [52](https://github.com/sdv-dev/SDV/issues/52) by @ManuelAlvarezC
* Ensure unicity on primary keys on different calls - Issue [63](https://github.com/sdv-dev/SDV/issues/63) by @ManuelAlvarezC
### Bugs fixed
* executing readme: 'not supported between instances of 'int' and 'NoneType' - Issue [104](https://github.com/sdv-dev/SDV/issues/104) by @csala
## 0.1.1 - Anonymization of data
* Add warnings when trying to model an unsupported dataset structure. [GH#73](https://github.com/sdv-dev/SDV/issues/73)
* Add option to anonymize data. [GH#51](https://github.com/sdv-dev/SDV/issues/51)
* Add support for modeling data with different distributions, when using `GaussianMultivariate` model. [GH#68](https://github.com/sdv-dev/SDV/issues/68)
* Add support for `VineCopulas` as a model. [GH#71](https://github.com/sdv-dev/SDV/issues/71)
* Improve `GaussianMultivariate` parameter sampling, avoiding warnings and unvalid parameters. [GH#58](https://github.com/sdv-dev/SDV/issues/58)
* Fix issue that caused that sampled categorical values sometimes got numerical values mixed. [GH#81](https://github.com/sdv-dev/SDV/issues/81)
* Improve the validation of extensions. [GH#69](https://github.com/sdv-dev/SDV/issues/69)
* Update examples. [GH#61](https://github.com/sdv-dev/SDV/issues/61)
* Replaced `Table` class with a `NamedTuple`. [GH#92](https://github.com/sdv-dev/SDV/issues/92)
* Fix inconsistent dependencies and add upper bound to dependencies. [GH#96](https://github.com/sdv-dev/SDV/issues/96)
* Fix error when merging extension in `Modeler.CPA` when running examples. [GH#86](https://github.com/sdv-dev/SDV/issues/86)
## 0.1.0 - First Release
* First release on PyPI.

%package help
Summary:	Development documents and examples for sdv
Provides:	python3-sdv-doc
%description help
<div align="center">
  <a href="https://datacebo.com"><picture>
      <source media="(prefers-color-scheme: dark)" srcset="https://github.com/sdv-dev/SDV/blob/master/docs/images/datacebo-logo-dark-mode.png">
      <img align="center" width=40% src="https://github.com/sdv-dev/SDV/blob/master/docs/images/datacebo-logo.png"></img>
  </picture></a>
</div>
<br/>
<br/>
[The Synthetic Data Vault Project](https://sdv.dev) was first created at MIT's [Data to AI Lab](
https://dai.lids.mit.edu/) in 2016. After 4 years of research and traction with enterprise, we
created [DataCebo](https://datacebo.com) in 2020 with the goal of growing the project.
Today, DataCebo is the proud developer of SDV, the largest ecosystem for
synthetic data generation & evaluation. It is home to multiple libraries that support synthetic
data, including:
* 🔄 Data discovery & transformation. Reverse the transforms to reproduce realistic data.
* 🧠 Multiple machine learning models -- ranging from Copulas to Deep Learning -- to create tabular,
  multi table and time series data.
* 📊 Measuring quality and privacy of synthetic data, and comparing different synthetic data
  generation models.
[Get started using the SDV package](https://bit.ly/sdv-docs) -- a fully
integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
for specific needs.
# Release Notes
## 1.0.0 - 2023-03-28
This is a major release that introduces a new API to the `SDV` aimed at streamlining the process of synthetic data generation! To achieve this, this release includes the addition of several large features.
### Metadata
Some of the most notable additions are the new `SingleTableMetadata` and `MultiTableMetadata` classes. These classes enable a number of features that make it easier to synthesize your data correctly such as:
* Automatic data detection - Calling `metadata.detect_from_dataframe()` or `metadata.detect_from_csv()` will populate the metadata autonomously with values it thinks represent the data.
* Easy updating - Once an instance of the metadata is created, values can be easily updated using a number of methods defined in the API. For more info, view the [docs](https://docs.sdv.dev/sdv/single-table-data/data-preparation/single-table-metadata-api).
* Metadata validation - Calling `metadata.validate()` will return a report of any invalid definitions in the metadata specification.
* Upgrading - Users with the previous metadata format can easily update to the new specification using the `upgrade_metadata()` method.
* Saving and loading - The metadata itself can easily be saved to a json file and loaded back up later.
### Class and Module Names
Another major change is the renaming of our core modeling classes and modules. The name changes are meant to highlight the difference between the underlying machine learning models, and the objects responsible for the end-to-end workflow of generating synthetic data. The main name changes are as follows:
* `tabular` -> `single_table`
* `relational` -> `multi_table`
* `timeseries` -> `sequential`
* `BaseTabularModel` -> `BaseSingleTableSynthesizer`
* `GaussianCopula` -> `GaussianCopulaSynthesizer`
* `CTGAN` -> `CTGANSynthesizer`
* `TVAE` -> `TVAESynthesizer`
* `CopulaGan` -> `CopulaGANSynthesizer`
* `PAR` -> `PARSynthesizer`
* `HMA1` -> `HMASynthesizer`
In `SDV` 1.0, synthesizers are classes that take in metadata and handle data preprocessing, model training and model sampling. This is similar to the previous `BaseTabularModel` in `SDV` <1.0.
### Synthetic Data Workflow
`Synthesizers` in `SDV` 1.0 define a clear workflow for generating synthetic data.
1. Synthesizers are initialized with a metadata class.
2. They can then be used to transform the data and apply constraints using the `synthesizer.preprocess()` method. This step also validates that the data matches the provided metadata to avoid errors in fitting or sampling.
3. The processed data can then be fed into the underlying machine learning model using `synthesizer.fit_processed_data()`. (Alternatively, data can be preprocessed and fit to the model using `synthesizer.fit()`.)
4. Data can then be sampled using `synthesizer.sample()`.
Each synthesizer class also provides a series of methods to help users customize the transformations their data goes through. Read more about that [here](https://docs.sdv.dev/sdv/single-table-data/modeling/synthetic-data-workflow/transform-and-anonymize).
Notice that the preprocessing and model fitting steps can now be separated. This can be helpful if preprocessing is time consuming or if the data has been processed externally.
### Other Highly Requested Features
Another major addition is control over randomization. In `SDV` <1.0, users could set a seed to control the randomization for only some columns. In `SDV` 1.0, randomization is controlled for all columns. Every new call to sample generates new data, but the synthesizer's seed can be reset to the original state using `synthesizer.reset_randomization()`, enabling reproducibility.
`SDV 1.0` adds accessibility and transparency into the transformers used for preprocessing and underlying machine learning models.
* Using the `synthesizer.get_transformers()` method, you can access the transformers used to preprocess each column and view their properties. This can be useful for debugging and accessing privacy information like mappings used to mask data.
* Distribution parameters learned by copula models can be accessed using the `synthesizer.get_learned_distributions()` method.
PII handling is improved by the following features:
* Primary keys can be set to natural sdtypes (eg. SSN, email, name). Previously they could only be numerical or text.
* The `PseudoAnonymizedFaker` can be used to provide consistent mapping to PII columns. As mentioned before, the mapping itself can be accessed by viewing the transformers for the column using `synthesizer.get_transformers()`.
* A bug causing PII columns to slow down modeling is patched.
Finally, the synthetic data can now be easily evaluated using the `evaluate_quality()` and `run_diagnostic()` methods. The data can be compared visually to the actual data using the `get_column_plot()` and `get_column_pair_plot()` methods. For more info on how to visualize or interpret the synthetic data evaluation, read the docs [here](https://docs.sdv.dev/sdv/single-table-data/evaluation).
### Issues Resolved
#### New Features
* Change auto_assign_transformers to handle id types - Issue [#1325](https://github.com/sdv-dev/SDV/issues/1325) by @pvk-developer
* Change 'text' sdtype to 'id' - Issue [#1324](https://github.com/sdv-dev/SDV/issues/1324) by @frances-h
* In `upgrade_metadata`, return the object instead of writing it to a JSON file - Issue [#1319](https://github.com/sdv-dev/SDV/issues/1319) by @frances-h
* In `upgrade_metadata` index primary keys should be converted to `text` - Issue [#1318](https://github.com/sdv-dev/SDV/issues/1318) by @amontanez24
* Add `load_from_dict` to SingleTableMetadata and MultiTableMetadata - Issue [#1314](https://github.com/sdv-dev/SDV/issues/1314) by @amontanez24
* Throw a `SynthesizerInputError` if `FixedCombinations` constraint is applied to a column that is not `boolean` or `categorical` - Issue [#1306](https://github.com/sdv-dev/SDV/issues/1306) by @frances-h
* Missing `save` and `load` methods for `HMASynthesizer` - Issue [#1262](https://github.com/sdv-dev/SDV/issues/1262) by @amontanez24
* Better input validation when creating single and multi table synthesizers - Issue [#1242](https://github.com/sdv-dev/SDV/issues/1242) by @fealho
* Better input validation on `HMASynthesizer.sample` - Issue [#1241](https://github.com/sdv-dev/SDV/issues/1241) by @R-Palazzo
* Validate that relationship must be between a `primary key` and `foreign key` - Issue [#1236](https://github.com/sdv-dev/SDV/issues/1236) by @fealho
* Improve `update_column` validation for `pii` attribute - Issue [#1226](https://github.com/sdv-dev/SDV/issues/1226) by @pvk-developer
* Order the output of `get_transformers()` based on the metadata - Issue [#1222](https://github.com/sdv-dev/SDV/issues/1222) by @pvk-developer
* Log if any `numerical_distributions` will not be applied - Issue [#1212](https://github.com/sdv-dev/SDV/issues/1212) by @fealho
* Improve error handling for `GaussianCopulaSynthesizer`: `numerical_distributions` - Issue [#1211](https://github.com/sdv-dev/SDV/issues/1211) by @fealho
* Improve error handling when validating `constraints` - Issue [#1210](https://github.com/sdv-dev/SDV/issues/1210) by @fealho
* Add `fake_companies` demo - Issue [#1209](https://github.com/sdv-dev/SDV/issues/1209) by @amontanez24
* Allow me to create a custom constraint class and use it in the same file - Issue [#1205](https://github.com/sdv-dev/SDV/issues/1205) by @amontanez24
* Sampling should reset after retraining the model - Issue [#1201](https://github.com/sdv-dev/SDV/issues/1201) by @pvk-developer
* Change function name `HMASynthesizer.update_table_parameters` --> `set_table_parameters` - Issue [#1200](https://github.com/sdv-dev/SDV/issues/1200) by @pvk-developer
* Add `get_info` method to synthesizers - Issue [#1199](https://github.com/sdv-dev/SDV/issues/1199) by @fealho
* Add evaluation methods to synthesizer - Issue [#1190](https://github.com/sdv-dev/SDV/issues/1190) by @fealho
* Update `evaluate.py` to work with the new `metadata` - Issue [#1186](https://github.com/sdv-dev/SDV/issues/1186) by @fealho
* Remove old code - Issue [#1181](https://github.com/sdv-dev/SDV/issues/1181) by @pvk-developer
* Drop support for python 3.6 and add support for 3.10 - Issue [#1176](https://github.com/sdv-dev/SDV/issues/1176) by @fealho
* Add constraint methods to MultiTableSynthesizers - Issue [#1171](https://github.com/sdv-dev/SDV/issues/1171) by @fealho
* Update custom constraint workflow - Issue [#1169](https://github.com/sdv-dev/SDV/issues/1169) by @pvk-developer
* Add get_constraints method to synthesizers - Issue [#1168](https://github.com/sdv-dev/SDV/issues/1168) by @pvk-developer
* Migrate adding and validating constraints to BaseSynthesizer - Issue [#1163](https://github.com/sdv-dev/SDV/issues/1163) by @pvk-developer
* Change metadata `"SCHEMA_VERSION"` --> `"METADATA_SPEC_VERSION"` - Issue [#1139](https://github.com/sdv-dev/SDV/issues/1139) by @amontanez24
* Add ability to reset random sampling - Issue [#1130](https://github.com/sdv-dev/SDV/issues/1130) by @pvk-developer
* Add get_available_demos - Issue [#1129](https://github.com/sdv-dev/SDV/issues/1129) by @fealho
* Add demo loading functionality - Issue [#1128](https://github.com/sdv-dev/SDV/issues/1128) by @fealho
* Use logging instead of printing in detect methods - Issue [#1107](https://github.com/sdv-dev/SDV/issues/1107) by @fealho
* Add save and load methods to synthesizers - Issue [#1106](https://github.com/sdv-dev/SDV/issues/1106) by @pvk-developer
* Add sampling methods to PARSynthesizer - Issue [#1083](https://github.com/sdv-dev/SDV/issues/1083) by @amontanez24
* Add transformer methods to PARSynthesizer - Issue [#1082](https://github.com/sdv-dev/SDV/issues/1082) by @fealho
* Add validate to PARSynthesizer - Issue [#1081](https://github.com/sdv-dev/SDV/issues/1081) by @amontanez24
* Add preprocess and fit methods to PARSynthesizer - Issue [#1080](https://github.com/sdv-dev/SDV/issues/1080) by @amontanez24
* Create SingleTablePreset - Issue [#1079](https://github.com/sdv-dev/SDV/issues/1079) by @amontanez24
* Add sample method to multi-table synthesizers - Issue [#1078](https://github.com/sdv-dev/SDV/issues/1078) by @pvk-developer
* Add get_learned_distributions method to synthesizers - Issue [#1075](https://github.com/sdv-dev/SDV/issues/1075) by @pvk-developer
* Add preprocess and fit methods to multi-table synthesizers - Issue [#1074](https://github.com/sdv-dev/SDV/issues/1074) by @pvk-developer
* Add transformer related methods to BaseMultiTableSynthesizer - Issue [#1072](https://github.com/sdv-dev/SDV/issues/1072) by @fealho
* Add validate method to `BaseMultiTableSynthesizer` - Issue [#1071](https://github.com/sdv-dev/SDV/issues/1071) by @pvk-developer
* Create BaseMultiTableSynthesizer and HMASynthesizer classes - Issue [#1070](https://github.com/sdv-dev/SDV/issues/1070) by @pvk-developer
* Create PARSynthesizer - Issue [#1055](https://github.com/sdv-dev/SDV/issues/1055) by @amontanez24
* Raise an error if an invalid sdtype is provided to the metadata - Issue [#1042](https://github.com/sdv-dev/SDV/issues/1042) by @amontanez24
* Only allow datetime and numerical sdtypes to be set as the sequence index - Issue [#1030](https://github.com/sdv-dev/SDV/issues/1030) by @amontanez24
* Change set_alternate_keys to add_alternate_keys and add error handling - Issue [#1029](https://github.com/sdv-dev/SDV/issues/1029) by @amontanez24
* Create `MultiTableMetadata.add_table` method - Issue [#1024](https://github.com/sdv-dev/SDV/issues/1024) by @amontanez24
* Add update_transformers to synthesizers - Issue [#1021](https://github.com/sdv-dev/SDV/issues/1021) by @fealho
* Add assign_transformers and get_transformers methods to synthesizers - Issue [#1020](https://github.com/sdv-dev/SDV/issues/1020) by @pvk-developer
* Add fit and fit_processed_data methods to synthesizers - Issue [#1019](https://github.com/sdv-dev/SDV/issues/1019) by @pvk-developer
* Add preprocess method to synthesizers - Issue [#1018](https://github.com/sdv-dev/SDV/issues/1018) by @pvk-developer
* Add sampling to synthesizer classes - Issue [#1015](https://github.com/sdv-dev/SDV/issues/1015) by @pvk-developer
* Add validate method to synthesizer - Issue [#1014](https://github.com/sdv-dev/SDV/issues/1014) by @fealho
* Create GaussianCopula, CTGAN, TVAE and CopulaGAN synthesizer classes - Issue [#1013](https://github.com/sdv-dev/SDV/issues/1013) by @pvk-developer
* Create BaseSynthesizer class - Issue [#1012](https://github.com/sdv-dev/SDV/issues/1012) by @pvk-developer
* Add constraint conversion to upgrade_metadata - Issue [#1005](https://github.com/sdv-dev/SDV/issues/1005) by @amontanez24
* Add method to generate keys to DataProcessor - Issue [#994](https://github.com/sdv-dev/SDV/issues/994) by @pvk-developer
* Create formatter - Issue [#970](https://github.com/sdv-dev/SDV/issues/970) by @fealho
* Create a utility to load multiple CSV files at once - Issue [#969](https://github.com/sdv-dev/SDV/issues/969) by @amontanez24
* Create a utility to convert old --> new metadata format - Issue [#966](https://github.com/sdv-dev/SDV/issues/966) by @amontanez24
* Add validation check that `primary_key`, `alternate_keys` and `sequence_key` cannot be sdtype categorical - Issue [#963](https://github.com/sdv-dev/SDV/issues/963) by @fealho
* Add anonymization to DataProcessor - Issue [#950](https://github.com/sdv-dev/SDV/issues/950) by @pvk-developer
* Add utility methods to DataProcessor - Issue [#948](https://github.com/sdv-dev/SDV/issues/948) by @fealho
* Add fit, transform and reverse_transform to DataProcessor - Issue [#947](https://github.com/sdv-dev/SDV/issues/947) by @amontanez24
* Create DataProcessor class - Issue [#946](https://github.com/sdv-dev/SDV/issues/946) by @amontanez24
* Add add_constraint method to MultiTableMetadata - Issue [#895](https://github.com/sdv-dev/SDV/issues/895) by @amontanez24
* Add key related methods to MultiTableMetadata - Issue [#894](https://github.com/sdv-dev/SDV/issues/894) by @fealho
* Add update_column and add_column methods to MultiTableMetadata - Issue [#893](https://github.com/sdv-dev/SDV/issues/893) by @amontanez24
* Add detect methods to MultiTableMetadata - Issue [#892](https://github.com/sdv-dev/SDV/issues/892) by @amontanez24
* Add load_from_json and save_to_json methods to the MultiTableMetadata - Issue [#891](https://github.com/sdv-dev/SDV/issues/891) by @fealho
* Add add_relationship method to MultiTableMetadata - Issue [#890](https://github.com/sdv-dev/SDV/issues/890) by @pvk-developer
* Add validate method to MultiTableMetadata - Issue [#888](https://github.com/sdv-dev/SDV/issues/888) by @pvk-developer
* Add visualize method to MultiTableMetadata class - Issue [#884](https://github.com/sdv-dev/SDV/issues/884) by @amontanez24
* Create MultiTableMetadata class - Issue [#883](https://github.com/sdv-dev/SDV/issues/883) by @pvk-developer
* Add add_constraint method to SingleTableMetadata - Issue [#881](https://github.com/sdv-dev/SDV/issues/881) by @amontanez24
* Add key related methods to SingleTableMetadata - Issue [#880](https://github.com/sdv-dev/SDV/issues/880) by @fealho
* Add validate method to SingleTableMetadata - Issue [#879](https://github.com/sdv-dev/SDV/issues/879) by @fealho
* Add _validate_inputs class method to each constraint - Issue [#878](https://github.com/sdv-dev/SDV/issues/878) by @fealho
* Add update_column and add_column methods to SingleTableMetadata - Issue [#877](https://github.com/sdv-dev/SDV/issues/877) by @pvk-developer
* Add detect methods to SingleTableMetadata - Issue [#876](https://github.com/sdv-dev/SDV/issues/876) by @pvk-developer
* Add load_from_json and save_to_json methods to SingleTableMetadata - Issue [#874](https://github.com/sdv-dev/SDV/issues/874) by @pvk-developer
* Create SingleTableMetadata class - Issue [#873](https://github.com/sdv-dev/SDV/issues/873) by @pvk-developer
#### Bugs Fixed
* In `upgrade_metadata`, PII values are being converted to generic categorical columns - Issue [#1317](https://github.com/sdv-dev/SDV/issues/1317) by @frances-h
* `PARSynthesizer` is missing `save` and `load` methods - Issue [#1289](https://github.com/sdv-dev/SDV/issues/1289) by @amontanez24
* Confusing warning when updating transformers - Issue [#1272](https://github.com/sdv-dev/SDV/issues/1272) by @frances-h
* When adding constraints, `auto_assign_transformers` is showing columns that should no longer exist - Issue [#1260](https://github.com/sdv-dev/SDV/issues/1260) by @pvk-developer
* Cannot fit twice if I modify transformers: `ValueError: There are non-numerical values in your data.` - Issue [#1259](https://github.com/sdv-dev/SDV/issues/1259) by @frances-h
* Cannot fit twice if I add constraints: `ValueError: There are non-numerical values in your data.` - Issue [#1258](https://github.com/sdv-dev/SDV/issues/1258) by @frances-h
* `HMASynthesizer` errors out when fitting a dataset that has a table which holds primary key and foreign keys only - Issue [#1257](https://github.com/sdv-dev/SDV/issues/1257) by @pvk-developer
* Change ValueErrors to InvalidMetadataErrors - Issue [#1251](https://github.com/sdv-dev/SDV/issues/1251) by @frances-h
* Multi-table should show foreign key transformers as None - Issue [#1249](https://github.com/sdv-dev/SDV/issues/1249) by @frances-h
* Cannot use `HMASynthesizer.fit_processed_data` more than once (`KeyError`) - Issue [#1240](https://github.com/sdv-dev/SDV/issues/1240) by @frances-h
* Function `get_available_demos` crashes if a dataset's `num-tables` or `size-MB` cannot be found - Issue [#1215](https://github.com/sdv-dev/SDV/issues/1215) by @amontanez24
* Cannot supply a natural key to `HMASynthesizer` (where `sdtype` is custom): Error in `sample` - Issue [#1214](https://github.com/sdv-dev/SDV/issues/1214) by @pvk-developer
* Unable to sample when using a `PseudoAnonymizedFaker` - Issue [#1207](https://github.com/sdv-dev/SDV/issues/1207) by @pvk-developer
* Incorrect `sdtype` specified in demo dataset `student_placements_pii` - Issue [#1206](https://github.com/sdv-dev/SDV/issues/1206) by @amontanez24
* Auto assigned transformers for datetime columns don't have the right parameters - Issue [#1204](https://github.com/sdv-dev/SDV/issues/1204) by @pvk-developer
* Cannot apply `Inequality` constraint on demo dataset's datetime columns - Issue [#1203](https://github.com/sdv-dev/SDV/issues/1203) by @pvk-developer
* pii should not be required to auto-assign faker transformers - Issue [#1194](https://github.com/sdv-dev/SDV/issues/1194) by @pvk-developer
* Misc. bug fixes for SDV 1.0.0 - Issue [#1193](https://github.com/sdv-dev/SDV/issues/1193) by @pvk-developer
* Small bug fixes in demo module - Issue [#1192](https://github.com/sdv-dev/SDV/issues/1192) by @pvk-developer
* Foreign Keys are added as Alternate Keys when upgrading - Issue [#1143](https://github.com/sdv-dev/SDV/issues/1143) by @pvk-developer
* Alternate keys not unique when assigned to a semantic type - Issue [#1111](https://github.com/sdv-dev/SDV/issues/1111) by @pvk-developer
* Synthesizer errors if column is semantic type and pii is False - Issue [#1110](https://github.com/sdv-dev/SDV/issues/1110) by @fealho
* Sampled values not unique if primary key is numerical - Issue [#1109](https://github.com/sdv-dev/SDV/issues/1109) by @pvk-developer
* Validate not called during synthesizer creation - Issue [#1105](https://github.com/sdv-dev/SDV/issues/1105) by @pvk-developer
* SingleTableSynthesizer fit doesn't update rounding - Issue [#1104](https://github.com/sdv-dev/SDV/issues/1104) by @amontanez24
* Method `auto_assign_tranformers` always sets `enforce_min_max_values=True` - Issue [#1095](https://github.com/sdv-dev/SDV/issues/1095) by @fealho
* Sampled context columns in PAR must be in the same order - Issue [#1052](https://github.com/sdv-dev/SDV/issues/1052) by @amontanez24
* Incorrect schema version printing during detect_table_from_dataframe - Issue [#1038](https://github.com/sdv-dev/SDV/issues/1038) by @amontanez24
* Same relationship can be added twice to MultiTableMetadata - Issue [#1031](https://github.com/sdv-dev/SDV/issues/1031) by @amontanez24
* Miscellaneous metadata bugs - Issue [#1026](https://github.com/sdv-dev/SDV/issues/1026) by @amontanez24
#### Maintenance
* SDV Package Maintenance Updates - Issue [#1140](https://github.com/sdv-dev/SDV/issues/1140) by @amontanez24
#### Internal
* Add integration tests for 'Synthesize Sequences' demo - Issue [#1295](https://github.com/sdv-dev/SDV/issues/1295) by @pvk-developer
* Add integration tests for 'Adding Constraints' demo - Issue [#1280](https://github.com/sdv-dev/SDV/issues/1280) by @pvk-developer
* Add integration tests to the 'Use Your Own Data' demo - Issue [#1278](https://github.com/sdv-dev/SDV/issues/1278) by @frances-h
* Add integration tests for 'Synthesize Multi Tables' demo - Issue [#1277](https://github.com/sdv-dev/SDV/issues/1277) by @pvk-developer
* Add integration tests for 'Synthesize a Table' demo - Issue [#1276](https://github.com/sdv-dev/SDV/issues/1276) by @frances-h
* Update `get_available_demos` tests - Issue [#1247](https://github.com/sdv-dev/SDV/issues/1247) by @fealho
* Make private attributes public in the metadata - Issue [#1245](https://github.com/sdv-dev/SDV/issues/1245) by @fealho
## 0.18.0 - 2023-01-24
This release adds suppport for Python 3.10 and drops support for 3.6.
### Maintenance
* Drop support for python 3.6 - Issue [#1177](https://github.com/sdv-dev/SDV/issues/1177) by @amontanez24
* Support for python 3.10 - Issue [#939](https://github.com/sdv-dev/SDV/issues/939) by @amontanez24
* Support Python >=3.10,<4 - Issue [#1000](https://github.com/sdv-dev/SDV/issues/1000) by @amontanez24
## 0.17.2 - 2022-12-08
This release fixes a bug in the demo module related to loading the demo data with constraints. It also adds a name to the demo datasets. Finally, it bumps the version of `SDMetrics` used.
### Maintenance
* Upgrade SDMetrics requirement to 0.8.0 - Issue [#1125](https://github.com/sdv-dev/SDV/issues/1125) by @katxiao
### New Features
* Provide a name for the default demo datasets - Issue [#1124](https://github.com/sdv-dev/SDV/issues/1124) by @amontanez24
### Bugs Fixed
* Cannot load_tabular_demo with metadata - Issue [#1123](https://github.com/sdv-dev/SDV/issues/1123) by @amontanez24
## 0.17.1 - 2022-09-29
This release bumps the dependency requirements to use the latest version of `SDMetrics`.
### Maintenance
* Patch release: Bump required version for SDMetrics - Issue [#1010](https://github.com/sdv-dev/SDV/issues/1010) by @katxiao
## 0.17.0 - 2022-09-09
This release updates the code to use RDT version 1.2.0 and greater, so that those new features are now available in SDV. This changes the transformers that are available in SDV models to be those that are in RDT version 1.2.0. As a result, some arguments for initializing models have changed.
Additionally, this release fixes bugs related to loading models with custom constraints. It also fixes a bug that added `NaNs` to the index of sampled data when using `sample_remaining_columns`.
### Bugs Fixed
* Incorrect rounding in Custom Constraint example - Issue [#941](https://github.com/sdv-dev/SDV/issues/941) by @amontanez24
* Can't save the model if use the custom constraint - Issue [#928](https://github.com/sdv-dev/SDV/issues/928) by @pvk-developer
* User Guide code fixes - Issue [#983](https://github.com/sdv-dev/SDV/issues/983) by @amontanez24
* Index contains NaNs when using sample_remaining_columns - Issue [#985](https://github.com/sdv-dev/SDV/issues/985) by @amontanez24
* Cannot sample after loading a model with custom constraints: TypeError - Issue [#984](https://github.com/sdv-dev/SDV/issues/984) by @pvk-developer
* Set HyperTransformer config manually, based on Metadata if given - Issue [#982](https://github.com/sdv-dev/SDV/issues/982) by @pvk-developer
### New Features
* Change default metrics for evaluate - Issue [#949](https://github.com/sdv-dev/SDV/issues/949) by @fealho
### Maintenance
* Update the RDT version to 1.0 - Issue [#897](https://github.com/sdv-dev/SDV/issues/897) by @pvk-developer
## 0.16.0 - 2022-07-21
This release brings user friendly improvements and bug fixes on the `SDV` constraints, to help
users generate their synthetic data easily.
Some predefined constraints have been renamed and redefined to be more user friendly & consistent.
The custom constraint API has also been updated for usability. The SDV now automatically determines
the best `handling_strategy` to use for each constraint, attempting `transform` by default and
falling back to `reject_sampling` otherwise. The `handling_strategy` parameters are no longer
included in the API.
Finally, this version of `SDV` also unifies the parameters for all sampling related methods for
all models (including TabularPreset).
### Changes to Constraints
* `GreatherThan` constraint is now separated in two new constraints: `Inequality`, which is
  intended to be used between two columns, and `ScalarInequality`, which is intended to be used
  between a column and a scalar.
* `Between` constraint is now separated in two new constraints: `Range`, which is intended to
  be used between three columns, and `ScalarRange`, which is intended to be used between a column
  and low and high scalar values.
* `FixedIncrements` a new constraint that makes the data increment by a certain value.
* New `create_custom_constraint` function available to create custom constraints.
### Removed Constraints
* `Rounding` Rounding is automatically being handled by the ``rdt.HyperTransformer``.
* `ColumnFormula` the `create_custom_constraint` takes place over this one and allows more
  advanced usage for the end users.
### New Features
* Improve error message for invalid constraints - Issue [#801](https://github.com/sdv-dev/SDV/issues/801) by @fealho
* Numerical Instability in Constrained GaussianCopula - Issue [#806](https://github.com/sdv-dev/SDV/issues/806) by @fealho
* Unify sampling params for reject sampling - Issue [#809](https://github.com/sdv-dev/SDV/issues/809) by @amontanez24
* Split `GreaterThan` constraint into `Inequality` and `ScalarInequality` - Issue [#814](https://github.com/sdv-dev/SDV/issues/814) by @fealho
* Split `Between` constraint into `Range` and `ScalarRange` - Issue [#815](https://github.com/sdv-dev/SDV/issues/815) @pvk-developer
* Change `columns` to `column_names` in `OneHotEncoding` and `Unique` constraints - Issue [#816](https://github.com/sdv-dev/SDV/issues/816) by @amontanez24
* Update columns parameter in `Positive` and `Negative` constraint - Issue [#817](https://github.com/sdv-dev/SDV/issues/817) by @fealho
* Create `FixedIncrements` constraint - Issue [#818](https://github.com/sdv-dev/SDV/issues/818) by @amontanez24
* Improve datetime handling in `ScalarInequality` and `ScalarRange` constraints - Issue [#819](https://github.com/sdv-dev/SDV/issues/819) by @pvk-developer
* Support strict boundaries even when transform strategy is used - Issue [#820](https://github.com/sdv-dev/SDV/issues/820) by @fealho
* Add `create_custom_constraint` factory method - Issue [#836](https://github.com/sdv-dev/SDV/issues/836) by @fealho
### Internal Improvements
* Remove `handling_strategy` parameter - Issue [#833](https://github.com/sdv-dev/SDV/issues/833) by @amontanez24
* Remove `fit_columns_model` parameter - Issue [#834](https://github.com/sdv-dev/SDV/issues/834) by @pvk-developer
* Remove the `ColumnFormula` constraint - Issue [#837](https://github.com/sdv-dev/SDV/issues/837) by @amontanez24
* Move `table_data.copy` to base class of constraints - Issue [#845](https://github.com/sdv-dev/SDV/issues/845) by @fealho
### Bugs Fixed
* Numerical Instability in Constrained GaussianCopula - Issue [#801](https://github.com/sdv-dev/SDV/issues/801) by @tlranda and @fealho
* Fix error message for `FixedIncrements` - Issue [#865](https://github.com/sdv-dev/SDV/issues/865) by @pvk-developer
* Fix constraints with conditional sampling - Issue [#866](https://github.com/sdv-dev/SDV/issues/866) by @amontanez24
* Fix error message in `ScalarInequality` - Issue [#868](https://github.com/sdv-dev/SDV/issues/868) by @pvk-developer
* Cannot use `max_tries_per_batch` on sample: `TypeError: sample() got an unexpected keyword argument 'max_tries_per_batch'` - Issue [#885](https://github.com/sdv-dev/SDV/issues/885) by @amontanez24
* Conditional sampling + batch size: `ValueError: Length of values (1) does not match length of index (5)` - Issue [#886](https://github.com/sdv-dev/SDV/issues/886) by @amontanez24
* `TabularPreset` doesn't support new sampling parameters - Issue [#887](https://github.com/sdv-dev/SDV/issues/887) by @fealho
* Conditional Sampling: `batch_size` is being set to `None` by default? - Issue [#889](https://github.com/sdv-dev/SDV/issues/889) by @amontanez24
* Conditional sampling using GaussianCopula inefficient when categories are noised - Issue [#910](https://github.com/sdv-dev/SDV/issues/910) by @amontanez24
### Documentation Changes
* Show the `API` for `TabularPreset` models - Issue [#854](https://github.com/sdv-dev/SDV/issues/854) by @katxiao
* Update handling constraints doc - Pull Request [#856](https://github.com/sdv-dev/SDV/issues/856) by @amontanez24
* Update custom costraints documentation - Pull Request [#857](https://github.com/sdv-dev/SDV/issues/857) by @pvk-developer
## 0.15.0 - 2022-05-25
This release improves the speed of the `GaussianCopula` model by removing logic that previously searched for the appropriate distribution to
use. It also fixes a bug that was happening when conditional sampling was used with the `TabularPreset`.
The rest of the release focuses on making changes to improve constraints including changing the `UniqueCombinations` constraint to `FixedCombinations`,
making the `Unique` constraint work with missing values and erroring when null values are seen in the `OneHotEncoding` constraint.
### New Features
* Silence warnings coming from univariate fit in copulas - Issue [#769](https://github.com/sdv-dev/SDV/issues/769) by @pvk-developer
* Remove parameters related to distribution search and change default - Issue [#767](https://github.com/sdv-dev/SDV/issues/767) by @fealho
* Update the UniqueCombinations constraint - Issue [#793](https://github.com/sdv-dev/SDV/issues/793) by @fealho
* Make Unique constraint works with nans - Issue [#797](https://github.com/sdv-dev/SDV/issues/797) by @fealho
* Error out if nans in OneHotEncoding - Issue [#800](https://github.com/sdv-dev/SDV/issues/800) by @amontanez24
### Bugs Fixed
* Unable to sample conditionally in Tabular_Preset model - Issue [#796](https://github.com/sdv-dev/SDV/issues/796) by @katxiao
### Documentation Changes
* Support GPU computing and progress track? - Issue [#478](https://github.com/sdv-dev/SDV/issues/478) by @fealho
## 0.14.1 - 2022-05-03
This release adds a `TabularPreset`, available in the `sdv.lite` module, which allows users to easily optimize a tabular model for speed.
In this release, we also include bug fixes for sampling with conditions, an unresolved warning, and setting field distributions. Finally,
we include documentation updates for sampling and the new `TabularPreset`.
### Bugs Fixed
* Sampling with conditions={column: 0.0} for float columns doesn't work - Issue [#525](https://github.com/sdv-dev/SDV/issues/525) by @shlomihod and @tssbas
* resolved FutureWarning with Pandas replaced append by concat - Issue [#759](https://github.com/sdv-dev/SDV/issues/759) by @Deathn0t
* Field distributions bug in CopulaGAN - Issue [#747](https://github.com/sdv-dev/SDV/issues/747) by @katxiao
* Field distributions bug in GaussianCopula - Issue [#746](https://github.com/sdv-dev/SDV/issues/746) by @katxiao
### New Features
* Set default transformer to categorical_fuzzy - Issue [#768](https://github.com/sdv-dev/SDV/issues/768) by @amontanez24
* Model nulls normally when tabular preset has constraints - Issue [#764](https://github.com/sdv-dev/SDV/issues/764) by @katxiao
* Don't modify my metadata object - Issue [#754](https://github.com/sdv-dev/SDV/issues/754) by @amontanez24
* Presets should be able to handle constraints - Issue [#753](https://github.com/sdv-dev/SDV/issues/753) by @katxiao
* Change preset optimize_for --> name - Issue [#749](https://github.com/sdv-dev/SDV/issues/749) by @katxiao
* Create a speed optimized Preset - Issue [#716](https://github.com/sdv-dev/SDV/issues/716) by @katxiao
### Documentation Changes
* Add tabular preset docs - Issue [#777](https://github.com/sdv-dev/SDV/issues/777) by @katxiao
* sdv.sampling module is missing from the API - Issue [#740](https://github.com/sdv-dev/SDV/issues/740) by @katxiao
## 0.14.0 - 2022-03-21
This release updates the sampling API and splits the existing functionality into three methods - `sample`, `sample_conditions`,
and `sample_remaining_columns`. We also add support for sampling in batches, displaying a progress bar when sampling with more than one batch,
sampling deterministically, and writing the sampled results to an output file. Finally, we include fixes for sampling with conditions
and updates to the documentation.
### Bugs Fixed
* Fix write to file in sampling - Issue [#732](https://github.com/sdv-dev/SDV/issues/732) by @katxiao
* Conditional sampling doesn't work if the model has a CustomConstraint - Issue [#696](https://github.com/sdv-dev/SDV/issues/696) by @katxiao
### New Features
* Updates to GaussianCopula conditional sampling methods - Issue [#729](https://github.com/sdv-dev/SDV/issues/729) by @katxiao
* Update conditional sampling errors - Issue [#730](https://github.com/sdv-dev/SDV/issues/730) by @katxiao
* Enable Batch Sampling + Progress Bar - Issue [#693](https://github.com/sdv-dev/SDV/issues/693) by @katxiao
* Create sample_remaining_columns() method - Issue [#692](https://github.com/sdv-dev/SDV/issues/692) by @katxiao
* Create sample_conditions() method - Issue [#691](https://github.com/sdv-dev/SDV/issues/691) by @katxiao
* Improve sample() method - Issue [#690](https://github.com/sdv-dev/SDV/issues/690) by @katxiao
* Create Condition object - Issue [#689](https://github.com/sdv-dev/SDV/issues/689) by @katxiao
* Is it possible to generate data with new set of primary keys? - Issue [#686](https://github.com/sdv-dev/SDV/issues/686) by @katxiao
* No way to fix the random seed? - Issue [#157](https://github.com/sdv-dev/SDV/issues/157) by @katxiao
* Can you set a random state for the sdv.tabular.ctgan.CTGAN.sample method? - Issue [#515](https://github.com/sdv-dev/SDV/issues/515) by @katxiao
* generating different synthetic data while training the model multiple times. - Issue [#299](https://github.com/sdv-dev/SDV/issues/299) by @katxiao
### Documentation Changes
* Typo in the document documentation - Issue [#680](https://github.com/sdv-dev/SDV/issues/680) by @katxiao
## 0.13.1 - 2021-12-22
This release adds support for passing tabular constraints to the HMA1 model, and adds more explicit error handling for
metric evaluation. It also includes a fix for using categorical columns in the PAR model and documentation updates
for metadata and HMA1.
### Bugs Fixed
* Categorical column after sequence_index column - Issue [#314](https://github.com/sdv-dev/SDV/issues/314) by @fealho
### New Features
* Support passing tabular constraints to the HMA1 model - Issue [#296](https://github.com/sdv-dev/SDV/issues/296) by @katxiao
* Metric evaluation error handling metrics - Issue [#638](https://github.com/sdv-dev/SDV/issues/638) by @katxiao
### Documentation Changes
* Make true/false values lowercase in Metadata Schema specification - Issue [#664](https://github.com/sdv-dev/SDV/issues/664) by @katxiao
* Update docstrings for hma1 methods - Issue [#642](https://github.com/sdv-dev/SDV/issues/642) by @katxiao
## 0.13.0 - 2021-11-22
This release makes multiple improvements to different `Constraint` classes. The `Unique` constraint can now
handle columns with the name `index` and no longer crashes on subsets of the original data. The `Between`
constraint can now handle columns with nulls properly. The memory of all constraints was also improved.
Various other features and fixes were added. Conditional sampling no longer crashes when the `num_rows` argument
is not provided. Multiple localizations can now be used for PII fields. Scaffolding for integration tests was added
and the workflows now run `pip check`.
Additionally, this release adds support for Python 3.9!
### Bugs Fixed
* Gaussian Copula – Memory Issue in Release 0.10.0 - Issue [#459](https://github.com/sdv-dev/SDV/issues/459) by @xamm
* Applying Unique Constraint errors when calling model.fit() on a subset of data - Issue [#610](https://github.com/sdv-dev/SDV/issues/610) by @xamm
* Calling sampling with conditions and without num_rows crashes - Issue [#614](https://github.com/sdv-dev/SDV/issues/614) by @xamm
* Metadata.visualize with path parameter throws AttributeError - Issue [#634](https://github.com/sdv-dev/SDV/issues/634) by @xamm
* The Unique constraint crashes when the data contains a column called index - Issue [#616](https://github.com/sdv-dev/SDV/issues/616) by @xamm
* The Unique constraint cannot handle non-default index - Issue [#617](https://github.com/sdv-dev/SDV/issues/617) by @xamm
* ConstraintsNotMetError when applying Between constraint on datetime columns containing null values - Issue [#632](https://github.com/sdv-dev/SDV/issues/632) by @katxiao
### New Features
* Adds Multi localisations feature for PII fields defined in #308 - PR [#609](https://github.com/sdv-dev/SDV/pull/609) by @xamm
### Housekeeping Tasks
* Support latest version of Faker - Issue [#621](https://github.com/sdv-dev/SDV/issues/621) by @katxiao
* Add scaffolding for Metadata integration tests - Issue [#624](https://github.com/sdv-dev/SDV/issues/624) by @katxiao
* Add support for Python 3.9 - Issue [#631](https://github.com/sdv-dev/SDV/issues/631) by @amontanez24
### Internal Improvements
* Add pip check to CI workflows - Issue [#626](https://github.com/sdv-dev/SDV/issues/626) by @pvk-developer
### Documentation Changes
* Anonymizing PII in single table tutorials states address field as e-mail type - Issue [#604](https://github.com/sdv-dev/SDV/issues/604) by @xamm
Special thanks to @xamm, @katxiao, @pvk-developer and @amontanez24 for all the work that made this release possible!
## 0.12.1 - 2021-10-12
This release fixes bugs in constraints, metadata behavior, and SDV documentation. Specifically, we added
proper handling of data containing null values for constraints and timeseries data, and updated the
default metadata detection behavior.
### Bugs Fixed
* ValueError: The parameter loc has invalid values - Issue [#353](https://github.com/sdv-dev/SDV/issues/353) by @fealho
* Gaussian Copula is generating different data with metadata and without metadata - Issue [#576](https://github.com/sdv-dev/SDV/issues/576) by @katxiao
* Make pomegranate an optional dependency - Issue [#567](https://github.com/sdv-dev/SDV/issues/567) by @katxiao
* Small wording change for Question Issue Template - Issue [#571](https://github.com/sdv-dev/SDV/issues/571) by @katxiao
* ConstraintsNotMetError when using GreaterThan constraint with datetime - Issue [#590](https://github.com/sdv-dev/SDV/issues/590) by @katxiao
* GreaterThan constraint crashing with NaN values - Issue [#592](https://github.com/sdv-dev/SDV/issues/592) by @katxiao
* Null values in GreaterThan constraint raises error - Issue [#589](https://github.com/sdv-dev/SDV/issues/589) by @katxiao
* ColumnFormula raises ConstraintsNotMetError when checking NaN values - Issue [#593](https://github.com/sdv-dev/SDV/issues/593) by @katxiao
* GreaterThan constraint raises TypeError when using datetime - Issue [#596](https://github.com/sdv-dev/SDV/issues/596) by @katxiao
* Fix repository language - Issue [#464](https://github.com/sdv-dev/SDV/issues/464) by @fealho
* Update __init__.py - Issue [#578](https://github.com/sdv-dev/SDV/issues/578) by @dyuliu
* IndexingError: Unalignable boolean - Issue [#446](https://github.com/sdv-dev/SDV/issues/446) by @fealho
## 0.12.0 - 2021-08-17
This release focuses on improving and expanding upon the existing constraints. More specifically, the users can now
(1) specify multiple columns in `Positive` and `Negative` constraints, (2) use the new `Unique`constraint and
(3) use datetime data with the `Between` constraint. Additionaly, error messages have been added and updated
to provide more useful feedback to the user.
Besides the added features, several bugs regarding the `UniqueCombinations` and `ColumnFormula` constraints have been fixed,
and an error in the metadata.json for the `student_placements` dataset was corrected. The release also added documentation
for the `fit_columns_model` which affects the majority of the available constraints.
### New Features
* Change default fit_columns_model to False - Issue [#550](https://github.com/sdv-dev/SDV/issues/550) by @katxiao
* Support multi-column specification for positive and negative constraint - Issue [#545](https://github.com/sdv-dev/SDV/issues/545) by @sarahmish
* Raise error when multiple constraints can't be enforced - Issue [#541](https://github.com/sdv-dev/SDV/issues/541) by @amontanez24
* Create Unique Constraint - Issue [#532](https://github.com/sdv-dev/SDV/issues/532) by @amontanez24
* Passing invalid conditions when using constraints produces unreadable errors - Issue [#511](https://github.com/sdv-dev/SDV/issues/511) by @katxiao
* Improve error message for ColumnFormula constraint when constraint column used in formula - Issue [#508](https://github.com/sdv-dev/SDV/issues/508) by @katxiao
* Add datetime functionality to Between constraint - Issue [#504](https://github.com/sdv-dev/SDV/issues/504) by @katxiao
### Bugs Fixed
* UniqueCombinations constraint with handling_strategy = 'transform' yields synthetic data with nan values - Issue [#521](https://github.com/sdv-dev/SDV/issues/521) by @katxiao and @csala
* UniqueCombinations constraint outputting wrong data type - Issue [#510](https://github.com/sdv-dev/SDV/issues/510) by @katxiao and @csala
* UniqueCombinations constraint on only one column gets stuck in an infinite loop - Issue [#509](https://github.com/sdv-dev/SDV/issues/509) by @katxiao
* Conditioning on a non-constraint column using the ColumnFormula constraint - Issue [#507](https://github.com/sdv-dev/SDV/issues/507) by @katxiao
* Conditioning on the constraint column of the ColumnFormula constraint - Issue [#506](https://github.com/sdv-dev/SDV/issues/506) by @katxiao
* Update metadata.json for duration of student_placements dataset - Issue [#503](https://github.com/sdv-dev/SDV/issues/503) by @amontanez24
* Unit test for HMA1 when working with a single child row per parent row - Issue [#497](https://github.com/sdv-dev/SDV/issues/497) by @pvk-developer
* UniqueCombinations constraint for more than 2 columns - Issue [#494](https://github.com/sdv-dev/SDV/issues/494) by @katxiao and @csala
### Documentation Changes
* Add explanation of fit_columns_model to API docs - Issue [#517](https://github.com/sdv-dev/SDV/issues/517) by @katxiao
## 0.11.0 - 2021-07-12
This release primarily addresses bugs and feature requests related to using constraints for the single-table models.
Users can now enforce scalar comparison with the existing `GreaterThan` constraint and apply 5 new constraints: `OneHotEncoding`, `Positive`, `Negative`, `Between` and `Rounding`.
Additionally, the SDV will now auto-apply constraints for rounding numerical values, and for keeping the data within the observed bounds.
All related user guides are updated with the new functionality.
### New Features
* Add OneHotEncoding Constraint - Issue [#303](https://github.com/sdv-dev/SDV/issues/303) by @fealho
* GreaterThan Constraint should apply to scalars - Issue [#410](https://github.com/sdv-dev/SDV/issues/410) by @amontanez24
* Improve GreaterThan constraint - Issue [#368](https://github.com/sdv-dev/SDV/issues/368) by @amontanez24
* Add Non-negative and Positive constraints across multiple columns- Issue [#409](https://github.com/sdv-dev/SDV/issues/409) by @amontanez24
* Add Between values constraint - Issue [#367](https://github.com/sdv-dev/SDV/issues/367) by @fealho
* Ensure values fall within the specified range - Issue [#423](https://github.com/sdv-dev/SDV/issues/423) by @amontanez24
* Add Rounding constraint - Issue [#482](https://github.com/sdv-dev/SDV/issues/482) by @katxiao
* Add rounding and min/max arguments that are passed down to the NumericalTransformer - Issue [#491](https://github.com/sdv-dev/SDV/issues/491) by @amontanez24
### Bugs Fixed
* GreaterThan constraint between Date columns rasises TypeError - Issue [#421](https://github.com/sdv-dev/SDV/issues/421) by @amontanez24
* GreaterThan constraint's transform strategy fails on columns that are not float - Issue [#448](https://github.com/sdv-dev/SDV/issues/448) by @amontanez24
* AttributeError on UniqueCombinations constraint with non-strings - Issue [#196](https://github.com/sdv-dev/SDV/issues/196) by @katxiao
* Use reject sampling to sample missing columns for constraints - Issue [#435](https://github.com/sdv-dev/SDV/issues/435) by @amontanez24
### Documentation Changes
* Ensure privacy metrics are available in the API docs - Issue [#458](https://github.com/sdv-dev/SDV/issues/458) by @fealho
* Ensure forumla constraint is called ColumnFormula everywhere in the docs - Issue [#449](https://github.com/sdv-dev/SDV/issues/449) by @fealho
## 0.10.1 - 2021-06-10
This release changes the way we sample conditions to not only group by the conditions passed by the user, but also by the transformed conditions that result from them.
### Issues resolved
* Conditionally sampling on variable in constraint should have variety for other variables - Issue [#440](https://github.com/sdv-dev/SDV/issues/440) by @amontanez24
## 0.10.0 - 2021-05-21
This release improves the constraint functionality by allowing constraints and conditions
at the same time. Additional changes were made to update tutorials.
### Issues resolved
* Not able to use constraints and conditions in the same time - Issue [#379](https://github.com/sdv-dev/SDV/issues/379)
by @amontanez24
* Update benchmarking user guide for reading private datasets - Issue [#427](https://github.com/sdv-dev/SDV/issues/427)
by @katxiao
## 0.9.1 - 2021-04-29
This release broadens the constraint functionality by allowing for the `ColumnFormula`
constraint to take lambda functions and returned functions as an input for its formula.
It also improves conditional sampling by ensuring that any `id` fields generated by the
model remain unique throughout the sampled data.
The `CTGAN` model was improved by adjusting a default parameter to be more mathematically
correct.
Additional changes were made to improve tutorials as well as fix fragile tests.
### Issues resolved
* Tutorials test sometimes fails - Issue [#355](https://github.com/sdv-dev/SDV/issues/355)
by @fealho
* Duplicate IDs when using reject-sampling - Issue [#331](https://github.com/sdv-dev/SDV/issues/331)
by @amontanez24 and @csala
* discriminator_decay should be initialized at 1e-6 but it's 0 - Issue [#401](https://github.com/sdv-dev/SDV/issues/401) by @fealho and @YoucefZemmouri
* Tutorial typo - Issue [#380](https://github.com/sdv-dev/SDV/issues/380) by @fealho
* Request for sdv.constraint.ColumnFormula for a wider range of function - Issue [#373](https://github.com/sdv-dev/SDV/issues/373) by @amontanez24 and @JetfiRex
## 0.9.0 - 2021-03-31
This release brings new privacy metrics to the evaluate framework which help to determine
if the real data could be obtained or deduced from the synthetic samples.
Additionally, now there is a normalized score for the metrics, which stays between `0` and `1`.
There are improvements that reduce the usage of memory ram when sampling new data. Also there
is a new parameter to control the reject sampling crash, `graceful_reject_sampling`, which if
set to `True` and if it's not possible to generate all the requested rows, it will just issue a
warning and return whatever it was able to generate.
The `Metadata` object can now be visualized using different combinations of `names` and `details`,
which can be set to `True` or `False` in order to display only the table names with details or
without. There is also an improvement on the `validation`, which now will display all the errors
found at the end of the validation instead of only the first one.
This version also exposes all the hyperparameters of the models `CTGAN` and `TVAE` to allow a more
advanced usage. There is also a fix for the `TVAE` model on small datasets and it's performance
with `NaN` values has been improved. There is a fix for when using
`UniqueCombinationConstraint` with the `transform` strategy.
### Issues resolved
* Memory Usage Gaussian Copula Trained Model consuming high memory when generating synthetic data - Issue [#304](https://github.com/sdv-dev/SDV/issues/304) by @pvk-developer and @AnupamaGangadhar
* Add option to visualize metadata with only table names - Issue [#347](https://github.com/sdv-dev/SDV/issues/347) by @csala
* Add sample parameter to control reject sampling crash - Issue [#343](https://github.com/sdv-dev/SDV/issues/343) by @fealho
* Verbose metadata validation - Issue [#348](https://github.com/sdv-dev/SDV/issues/348) by @csala
* Missing the introduction of custom specification for hyperparameters in the TVAE model - Issue [#344](https://github.com/sdv-dev/SDV/issues/343) by @imkhoa99 and @pvk-developer
## 0.8.0 - 2021-02-24
This version adds conditional sampling for tabular models by combining a reject-sampling
strategy with the native conditional sampling capabilities from the gaussian copulas.
It also introduces several upgrades on the HMA1 algorithm that improve data quality and
robustness in the multi-table scenarios by making changes in how the parameters of the child
tables are aggregated on the parent tables, including a complete rework of how the correlation
matrices are modeled and rebuild after sampling.
### Issues resolved
* Fix probabilities contain NaN error - Issue [#326](https://github.com/sdv-dev/SDV/issues/326) by @csala
* Conditional Sampling for tabular models - Issue [#316](https://github.com/sdv-dev/SDV/issues/316) by @fealho and @csala
* HMA1: LinAlgError: SVD did not converge - Issue [#240](https://github.com/sdv-dev/SDV/issues/240) by @csala
## 0.7.0 - 2021-01-27
This release introduces a few changes in the HMA1 relational algorithm to decrease modeling
and sampling times, while also ensuring that correlations are properly kept across tables
and also adding support for some relational schemas that were not supported before.
A few changes in constraints and tabular models also ensure that situations that produced
errors before now work without errors.
### Issues resolved
* Fix unique key generation - Issue [#306](https://github.com/sdv-dev/SDV/issues/306) by @fealho
* Ensure tables that contain nothing but ids can be modeled - Issue [#302](https://github.com/sdv-dev/SDV/issues/302) by @csala
* Metadata visualization improvements - Issue [#301](https://github.com/sdv-dev/SDV/issues/301) by @csala
* Multi-parent re-model and re-sample issue - Issue [#298](https://github.com/sdv-dev/SDV/issues/298) by @csala
* Support datetimes in GreaterThan constraint - Issue [#266](https://github.com/sdv-dev/SDV/issues/266) by @rollervan
* Support for multiple foreign keys in one table - Issue [#185](https://github.com/sdv-dev/SDV/issues/185) by @csala
## 0.6.1 - 2020-12-31
SDMetrics version is updated to include the new Time Series metrics, which have also
been added to the API Reference and User Guides documentation. Additionally,
a few code has been refactored to reduce external dependencies and a few minor bugs
related to single table constraints have been fixed
### Issues resolved
* Add timeseries metrics and user guides - [Issue #289](https://github.com/sdv-dev/SDV/issues/289) by @csala
* Add functions to generate regex ids - [Issue #288](https://github.com/sdv-dev/SDV/issues/288) by @csala
* Saving a fitted tabular model with UniqueCombinations constraint raises PicklingError -
  [Issue #286](https://github.com/sdv-dev/SDV/issues/288) by @csala
* Constraints: `handling_strategy='reject_sampling'` causes `'ZeroDivisionError: division by zero'` -
  [Issue #285](https://github.com/sdv-dev/SDV/issues/285) by @csala
## 0.6.0 - 2020-12-22
This release updates to the latest CTGAN, RDT and SDMetrics libraries to introduce a
new TVAE model, multiple new metrics for single table and multi table, and fixes
issues in the re-creation of tabular models from a metadata dict.
### Issues resolved
* Upgrade to SDMetrics v0.1.0 and add `sdv.metrics` module - [Issue #281](https://github.com/sdv-dev/SDV/issues/281) by @csala
* Upgrade to CTGAN 0.3.0 and add TVAE model - [Issue #278](https://github.com/sdv-dev/SDV/issues/278) by @fealho
* Add `dtype_transformers` to `Table.from_dict` - [Issue #276](https://github.com/sdv-dev/SDV/issues/276) by @csala
* Fix Metadata `from_dict` behavior - [Issue #275](https://github.com/sdv-dev/SDV/issues/275) by @csala
## 0.5.0 - 2020-11-25
This version updates the dependencies and makes a few internal changes in order
to ensure that SDV works properly on Windows Systems, making this the first
release to be officially supported on Windows.
Apart from this, some more internal changes have been made to solve a few minor
issues from the older versions while also improving the processing speed when
processing relational datasets with the default parameters.
### API breaking changes
* The `distribution` argument of the `GaussianCopula` has been renamed to `field_distributions`.
* The `HMA1` and `SDV` classes now use the `categorical_fuzzy` transformer by default instead of
  the `one_hot_encoding` one.
### Issues resolved
* GaussianCopula: rename `distribution` argument to `field_distributions` - [Issue #237](https://github.com/sdv-dev/SDV/issues/237) by @csala
* GaussianCopula: Improve error message if an invalid distribution name is passed - [Issue #220](https://github.com/sdv-dev/SDV/issues/220) by csala
* Import urllib.request explicitly - [Issue #227](https://github.com/sdv-dev/SDV/issues/227) by @csala
* TypeError: cannot astype a datetimelike from [datetime64[ns]] to [int32] - [Issue #218](https://github.com/sdv-dev/SDV/issues/218) by @csala
* Change default categorical transformer to `categorical_fuzzy` in HMA1 - [Issue #214](https://github.com/sdv-dev/SDV/issues/214) by @csala
* Integer categoricals being sampled as strings instead of integer values - [Issue #194](https://github.com/sdv-dev/SDV/issues/194) by @csala
## 0.4.5 - 2020-10-17
In this version a new family of models for Synthetic Time Series Generation is introduced
under the `sdv.timeseries` sub-package. The new family of models now includes a new class
called `PAR`, which implements a *Probabilistic AutoRegressive* model.
This version also adds support for composite primary keys and regex based generation of id
fields in tabular models and drops Python 3.5 support.
### Issues resolved
* Drop python 3.5 support - [Issue #204](https://github.com/sdv-dev/SDV/issues/204) by @csala
* Support composite primary keys in tabular models - [Issue #207](https://github.com/sdv-dev/SDV/issues/207) by @csala
* Add the option to generate string `id` fields based on regex on tabular models - [Issue #208](https://github.com/sdv-dev/SDV/issues/208) by @csala
* Synthetic Time Series - [Issue #142](https://github.com/sdv-dev/SDV/issues/142) by @csala
## 0.4.4 - 2020-10-06
This version adds a new tabular model based on combining the CTGAN model with the reversible
transformation applied in the GaussianCopula model that converts random variables with
arbitrary distributions to new random variables with standard normal distribution.
The reversible transformation is handled by the GaussianCopulaTransformer recently added to RDT.
### Issues resolved
* Add CopulaGAN Model - [Issue #202](https://github.com/sdv-dev/SDV/issues/202) by @csala
## 0.4.3 - 2020-09-28
This release moves the models and algorithms related to generation of synthetic
relational data to a new `sdv.relational` subpackage (Issue #198)
As part of the change, also the old `sdv.models` have been removed and now
relational model is based on the recently introduced `sdv.tabular` models.
## 0.4.2 - 2020-09-19
In this release the `sdv.evaluation` module has been reworked to include 4 different
metrics and in all cases return a normalized score between 0 and 1.
Included metrics are:
- `cstest`
- `kstest`
- `logistic_detection`
- `svc_detection`
## 0.4.1 - 2020-09-07
This release fixes a couple of minor issues and introduces an important rework of the
User Guides section of the documentation.
### Issues fixed
* Error Message: "make sure the Graphviz executables are on your systems' PATH" - [Issue #182](https://github.com/sdv-dev/SDV/issues/182) by @csala
* Anonymization mappings leak - [Issue #187](https://github.com/sdv-dev/SDV/issues/187) by @csala
## 0.4.0 - 2020-08-08
In this release SDV gets new documentation, new tutorials, improvements to the Tabular API
and broader python and dependency support.
Complete list of changes:
* New Documentation site based on the `pydata-sphinx-theme`.
* New User Guides and Notebook tutorials.
* New Developer Guides section within the docs with details about the SDV architecture,
  the ecosystem libraries and how to extend and contribute to the project.
* Improved API for the Tabular models with focus on ease of use.
* Support for Python 3.8 and the newest versions of pandas, scipy and scikit-learn.
* New Slack Workspace for development discussions and community support.
## 0.3.6 - 2020-07-23
This release introduces a new concept of `Constraints`, which allow the user to define
special relationships between columns that will not be handled via modeling.
This is done via a new `sdv.constraints` subpackage which defines some well-known pre-defined
constraints, as well as a generic framework that allows the user to customize the constraints
to their needs as much as necessary.
### New Features
* Support for Constraints - [Issue #169](https://github.com/sdv-dev/SDV/issues/169) by @csala
## 0.3.5 - 2020-07-09
This release introduces a new subpackage `sdv.tabular` with models designed specifically
for single table modeling, while still providing all the usual conveniences from SDV, such
as:
* Seamless multi-type support
* Missing data handling
* PII anonymization
Currently implemented models are:
* GaussianCopula: Multivariate distributions modeled using copula functions. This is stronger
  version, with more marginal distributions and options, than the one used to model multi-table
  datasets.
* CTGAN: GAN-based data synthesizer that can generate synthetic tabular data with high fidelity.
## 0.3.4 - 2020-07-04
### New Features
* Support for Multiple Parents - [Issue #162](https://github.com/sdv-dev/SDV/issues/162) by @csala
* Sample by default the same number of rows as in the original table - [Issue #163](https://github.com/sdv-dev/SDV/issues/163) by @csala
### General Improvements
* Add benchmark - [Issue #165](https://github.com/sdv-dev/SDV/issues/165) by @csala
## 0.3.3 - 2020-06-26
### General Improvements
* Use SDMetrics for evaluation - [Issue #159](https://github.com/sdv-dev/SDV/issues/159) by @csala
## 0.3.2 - 2020-02-03
### General Improvements
* Improve metadata visualization - [Issue #151](https://github.com/sdv-dev/SDV/issues/151) by @csala @JDTheRipperPC
## 0.3.1 - 2020-01-22
### New Features
* Add Metadata Validation - [Issue #134](https://github.com/sdv-dev/SDV/issues/134) by @csala @JDTheRipperPC
* Add Metadata Visualization - [Issue #135](https://github.com/sdv-dev/SDV/issues/135) by @JDTheRipperPC
### General Improvements
* Add path to metadata JSON - [Issue #143](https://github.com/sdv-dev/SDV/issues/143) by @JDTheRipperPC
* Use new Copulas and RDT versions - [Issue #147](https://github.com/sdv-dev/SDV/issues/147) by @csala @JDTheRipperPC
## 0.3.0 - 2019-12-23
### New Features
* Create sdv.models subpackage - [Issue #141](https://github.com/sdv-dev/SDV/issues/141) by @JDTheRipperPC
## 0.2.2 - 2019-12-10
### New Features
* Adapt evaluation to the different data types - [Issue #128](https://github.com/sdv-dev/SDV/issues/128) by @csala @JDTheRipperPC
* Extend `load_demo` functionality to load other datasets - [Issue #136](https://github.com/sdv-dev/SDV/issues/136) by @JDTheRipperPC
## 0.2.1 - 2019-11-25
### New Features
* Methods to generate Metadata from DataFrames - [Issue #126](https://github.com/sdv-dev/SDV/issues/126) by @csala @JDTheRipperPC
## 0.2.0 - 2019-10-11
### New Features
* compatibility with rdt issue 72 - [Issue #120](https://github.com/sdv-dev/SDV/issues/120) by @csala @JDTheRipperPC
### General Improvements
* Error docstring sampler.__fill_text_columns - [Issue #144](https://github.com/sdv-dev/SDV/issues/114) by @JDTheRipperPC
* Reach 90% coverage - [Issue #112](https://github.com/sdv-dev/SDV/issues/112) by @JDTheRipperPC
* Review unittests - [Issue #111](https://github.com/sdv-dev/SDV/issues/111) by @JDTheRipperPC
### Bugs Fixed
* Time required for sample_all function? - [Issue #118](https://github.com/sdv-dev/SDV/issues/118) by @csala @JDTheRipperPC
## 0.1.2 - 2019-09-18
### New Features
* Add option to model the amount of child rows - Issue [93](https://github.com/sdv-dev/SDV/issues/93) by @ManuelAlvarezC
### General Improvements
* Add Evaluation Metrics - Issue [52](https://github.com/sdv-dev/SDV/issues/52) by @ManuelAlvarezC
* Ensure unicity on primary keys on different calls - Issue [63](https://github.com/sdv-dev/SDV/issues/63) by @ManuelAlvarezC
### Bugs fixed
* executing readme: 'not supported between instances of 'int' and 'NoneType' - Issue [104](https://github.com/sdv-dev/SDV/issues/104) by @csala
## 0.1.1 - Anonymization of data
* Add warnings when trying to model an unsupported dataset structure. [GH#73](https://github.com/sdv-dev/SDV/issues/73)
* Add option to anonymize data. [GH#51](https://github.com/sdv-dev/SDV/issues/51)
* Add support for modeling data with different distributions, when using `GaussianMultivariate` model. [GH#68](https://github.com/sdv-dev/SDV/issues/68)
* Add support for `VineCopulas` as a model. [GH#71](https://github.com/sdv-dev/SDV/issues/71)
* Improve `GaussianMultivariate` parameter sampling, avoiding warnings and unvalid parameters. [GH#58](https://github.com/sdv-dev/SDV/issues/58)
* Fix issue that caused that sampled categorical values sometimes got numerical values mixed. [GH#81](https://github.com/sdv-dev/SDV/issues/81)
* Improve the validation of extensions. [GH#69](https://github.com/sdv-dev/SDV/issues/69)
* Update examples. [GH#61](https://github.com/sdv-dev/SDV/issues/61)
* Replaced `Table` class with a `NamedTuple`. [GH#92](https://github.com/sdv-dev/SDV/issues/92)
* Fix inconsistent dependencies and add upper bound to dependencies. [GH#96](https://github.com/sdv-dev/SDV/issues/96)
* Fix error when merging extension in `Modeler.CPA` when running examples. [GH#86](https://github.com/sdv-dev/SDV/issues/86)
## 0.1.0 - First Release
* First release on PyPI.

%prep
%autosetup -n sdv-1.0.0

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-sdv -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.0-1
- Package Spec generated