automatic import of python-deepecho

3 files changed, 304 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..5e5b740 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/deepecho-0.4.0.tar.gz
diff --git a/python-deepecho.spec b/python-deepecho.spec
new file mode 100644
index 0000000..48d808c
--- /dev/null
+++ b/python-deepecho.spec
@@ -0,0 +1,302 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-deepecho
+Version:	0.4.0
+Release:	1
+Summary:	Create sequential synthetic data of mixed types using a GAN.
+License:	BSL-1.1
+URL:		https://github.com/sdv-dev/DeepEcho
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/98/84/7040528e28a57d7d2e6d28b40896df82501a38fa179f32d289ae974f1552/deepecho-0.4.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-tqdm
+Requires:	python3-numpy
+Requires:	python3-pandas
+Requires:	python3-torch
+Requires:	python3-numpy
+Requires:	python3-pandas
+Requires:	python3-torch
+Requires:	python3-setuptools
+Requires:	python3-bumpversion
+Requires:	python3-pip
+Requires:	python3-watchdog
+Requires:	python3-flake8
+Requires:	python3-flake8-absolute-import
+Requires:	python3-flake8-docstrings
+Requires:	python3-flake8-sfs
+Requires:	python3-isort
+Requires:	python3-pylint
+Requires:	python3-flake8-builtins
+Requires:	python3-flake8-debugger
+Requires:	python3-flake8-mock
+Requires:	python3-dlint
+Requires:	python3-flake8-eradicate
+Requires:	python3-flake8-mutable
+Requires:	python3-flake8-fixme
+Requires:	python3-flake8-multiline-containers
+Requires:	python3-flake8-quotes
+Requires:	python3-flake8-variables-names
+Requires:	python3-pep8-naming
+Requires:	python3-flake8-expression-complexity
+Requires:	python3-flake8-print
+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-pytest
+Requires:	python3-pytest-cov
+Requires:	python3-pytest-rerunfailures
+Requires:	python3-jupyter
+Requires:	python3-rundoc
+
+%description
+<div align="center">
+<a href="https://datacebo.com"><img align="center" width=40% src="https://github.com/sdv-dev/SDV/blob/master/docs/images/DataCebo.png"></img></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://sdv.dev/SDV/getting_started/install.html) -- a fully
+integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
+for specific needs.
+# History
+## 0.3.0 - 2021-11-15
+This release adds support for Python 3.9 and updates dependencies to ensure compatibility with the rest
+of the SDV ecosystem.
+* Add support for Python 3.9 - Issue [#41](https://github.com/sdv-dev/DeepEcho/issues/41) by @fealho
+* Add pip check to CI workflows internal improvements - Issue [#39](https://github.com/sdv-dev/DeepEcho/issues/39) by @pvk-developer
+* Add support for pylint>2.7.2 housekeeping - Issue [#33](https://github.com/sdv-dev/DeepEcho/issues/33) by @fealho
+* Add support for torch>=1.8 housekeeping - Issue [#32](https://github.com/sdv-dev/DeepEcho/issues/32) by @fealho
+## 0.2.1 - 2021-10-12
+This release fixes a bug with how DeepEcho handles NaN values.
+* Handling NaN's bug - Issue [#35](https://github.com/sdv-dev/DeepEcho/issues/35) by @fealho
+## 0.2.0 - 2021-02-24
+Maintenance release to update dependencies and ensure compatibility with the rest
+of the SDV ecosystem libraries.
+## 0.1.4 - 2020-10-16
+Minor maintenance version to update dependencies and documentation, and
+also make the demo data loading function parse dates properly.
+## 0.1.3 - 2020-10-16
+This version includes several minor improvements to the PAR model and the
+way the sequences are generated:
+* Sequences can now be generated without dropping the sequence index.
+* The PAR model learns the min and max length of the sequence from the input data.
+* NaN values are properly supported for both categorical and numerical columns.
+* NaN values are generated for numerical columns only if there were NaNs in the input data.
+* Constant columns can now be modeled.
+## 0.1.2 - 2020-09-15
+Add BasicGAN Model and additional benchmarking results.
+## 0.1.1 - 2020-08-15
+This release includes a few new features to make DeepEcho work on more types of datasets
+as well as to making it easier to add new datasets to the benchmarking framework.
+* Add `segment_size` and `sequence_index` arguments to `fit` method.
+* Add `sequence_length` as an optional argument to `sample` and `sample_sequence` methods.
+* Update the Dataset storage format to add `sequence_index` and versioning.
+* Separate the sequence assembling process in its own `deepecho.sequences` module.
+* Add function `make_dataset` to create a dataset from a dataframe and just a few column names.
+* Add notebook tutorial to show how to create a datasets and use them.
+## 0.1.0 - 2020-08-11
+First release.
+Included Features:
+* PARModel
+* Demo dataset and tutorials
+* Benchmarking Framework
+* Support and instructions for benchmarking on a Kubernetes cluster.
+
+%package -n python3-deepecho
+Summary:	Create sequential synthetic data of mixed types using a GAN.
+Provides:	python-deepecho
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-deepecho
+<div align="center">
+<a href="https://datacebo.com"><img align="center" width=40% src="https://github.com/sdv-dev/SDV/blob/master/docs/images/DataCebo.png"></img></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://sdv.dev/SDV/getting_started/install.html) -- a fully
+integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
+for specific needs.
+# History
+## 0.3.0 - 2021-11-15
+This release adds support for Python 3.9 and updates dependencies to ensure compatibility with the rest
+of the SDV ecosystem.
+* Add support for Python 3.9 - Issue [#41](https://github.com/sdv-dev/DeepEcho/issues/41) by @fealho
+* Add pip check to CI workflows internal improvements - Issue [#39](https://github.com/sdv-dev/DeepEcho/issues/39) by @pvk-developer
+* Add support for pylint>2.7.2 housekeeping - Issue [#33](https://github.com/sdv-dev/DeepEcho/issues/33) by @fealho
+* Add support for torch>=1.8 housekeeping - Issue [#32](https://github.com/sdv-dev/DeepEcho/issues/32) by @fealho
+## 0.2.1 - 2021-10-12
+This release fixes a bug with how DeepEcho handles NaN values.
+* Handling NaN's bug - Issue [#35](https://github.com/sdv-dev/DeepEcho/issues/35) by @fealho
+## 0.2.0 - 2021-02-24
+Maintenance release to update dependencies and ensure compatibility with the rest
+of the SDV ecosystem libraries.
+## 0.1.4 - 2020-10-16
+Minor maintenance version to update dependencies and documentation, and
+also make the demo data loading function parse dates properly.
+## 0.1.3 - 2020-10-16
+This version includes several minor improvements to the PAR model and the
+way the sequences are generated:
+* Sequences can now be generated without dropping the sequence index.
+* The PAR model learns the min and max length of the sequence from the input data.
+* NaN values are properly supported for both categorical and numerical columns.
+* NaN values are generated for numerical columns only if there were NaNs in the input data.
+* Constant columns can now be modeled.
+## 0.1.2 - 2020-09-15
+Add BasicGAN Model and additional benchmarking results.
+## 0.1.1 - 2020-08-15
+This release includes a few new features to make DeepEcho work on more types of datasets
+as well as to making it easier to add new datasets to the benchmarking framework.
+* Add `segment_size` and `sequence_index` arguments to `fit` method.
+* Add `sequence_length` as an optional argument to `sample` and `sample_sequence` methods.
+* Update the Dataset storage format to add `sequence_index` and versioning.
+* Separate the sequence assembling process in its own `deepecho.sequences` module.
+* Add function `make_dataset` to create a dataset from a dataframe and just a few column names.
+* Add notebook tutorial to show how to create a datasets and use them.
+## 0.1.0 - 2020-08-11
+First release.
+Included Features:
+* PARModel
+* Demo dataset and tutorials
+* Benchmarking Framework
+* Support and instructions for benchmarking on a Kubernetes cluster.
+
+%package help
+Summary:	Development documents and examples for deepecho
+Provides:	python3-deepecho-doc
+%description help
+<div align="center">
+<a href="https://datacebo.com"><img align="center" width=40% src="https://github.com/sdv-dev/SDV/blob/master/docs/images/DataCebo.png"></img></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://sdv.dev/SDV/getting_started/install.html) -- a fully
+integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
+for specific needs.
+# History
+## 0.3.0 - 2021-11-15
+This release adds support for Python 3.9 and updates dependencies to ensure compatibility with the rest
+of the SDV ecosystem.
+* Add support for Python 3.9 - Issue [#41](https://github.com/sdv-dev/DeepEcho/issues/41) by @fealho
+* Add pip check to CI workflows internal improvements - Issue [#39](https://github.com/sdv-dev/DeepEcho/issues/39) by @pvk-developer
+* Add support for pylint>2.7.2 housekeeping - Issue [#33](https://github.com/sdv-dev/DeepEcho/issues/33) by @fealho
+* Add support for torch>=1.8 housekeeping - Issue [#32](https://github.com/sdv-dev/DeepEcho/issues/32) by @fealho
+## 0.2.1 - 2021-10-12
+This release fixes a bug with how DeepEcho handles NaN values.
+* Handling NaN's bug - Issue [#35](https://github.com/sdv-dev/DeepEcho/issues/35) by @fealho
+## 0.2.0 - 2021-02-24
+Maintenance release to update dependencies and ensure compatibility with the rest
+of the SDV ecosystem libraries.
+## 0.1.4 - 2020-10-16
+Minor maintenance version to update dependencies and documentation, and
+also make the demo data loading function parse dates properly.
+## 0.1.3 - 2020-10-16
+This version includes several minor improvements to the PAR model and the
+way the sequences are generated:
+* Sequences can now be generated without dropping the sequence index.
+* The PAR model learns the min and max length of the sequence from the input data.
+* NaN values are properly supported for both categorical and numerical columns.
+* NaN values are generated for numerical columns only if there were NaNs in the input data.
+* Constant columns can now be modeled.
+## 0.1.2 - 2020-09-15
+Add BasicGAN Model and additional benchmarking results.
+## 0.1.1 - 2020-08-15
+This release includes a few new features to make DeepEcho work on more types of datasets
+as well as to making it easier to add new datasets to the benchmarking framework.
+* Add `segment_size` and `sequence_index` arguments to `fit` method.
+* Add `sequence_length` as an optional argument to `sample` and `sample_sequence` methods.
+* Update the Dataset storage format to add `sequence_index` and versioning.
+* Separate the sequence assembling process in its own `deepecho.sequences` module.
+* Add function `make_dataset` to create a dataset from a dataframe and just a few column names.
+* Add notebook tutorial to show how to create a datasets and use them.
+## 0.1.0 - 2020-08-11
+First release.
+Included Features:
+* PARModel
+* Demo dataset and tutorials
+* Benchmarking Framework
+* Support and instructions for benchmarking on a Kubernetes cluster.
+
+%prep
+%autosetup -n deepecho-0.4.0
+
+%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-deepecho -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..2812ccc
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+72a7ed1b609be655b254aa8cc712ef61  deepecho-0.4.0.tar.gz