automatic import of python-arambhmlopeneuler20.03

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diff --git a/.gitignore b/.gitignore
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+/ARAMBHML-0.2.4.tar.gz
diff --git a/python-arambhml.spec b/python-arambhml.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-ARAMBHML
+Version:	0.2.4
+Release:	1
+Summary:	An Auto ML framework that solves Classification Tasks
+License:	MIT License
+URL:		https://pypi.org/project/ARAMBHML/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b7/66/6f645cb49554775688745ae35782f37279b79d2e157f22d94bf248a4e1c9/ARAMBHML-0.2.4.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pandas
+Requires:	python3-numpy
+Requires:	python3-matplotlib
+Requires:	python3-seaborn
+Requires:	python3-scikit-learn
+Requires:	python3-sklearn-pandas
+Requires:	python3-xgboost
+Requires:	python3-plotly
+Requires:	python3-plotly-express
+
+%description
+
+# Auto ML for Solving Classification Problems for Tabular Data
+
+[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
+[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)   
+
+
+## Functionality of the Auto ML Framework
+
+- Detects the type of problem from the given target feature
+- Does EDA on it's own
+- Finds out if there are null values present or not
+- If null values are present they are treated specifically with the class they are present in
+- Forms train-test split on it's own
+- Applies 6 ML models to show the use which model performs the best
+
+## Usage
+
+- Make sure you have Python installed in your system.
+- Run Following command in the CMD.
+ ```
+  pip install ARAMBHML
+  ```
+## Example
+
+
+# test.py
+ ```
+  from ARAMBHML import arambhNet
+  ```
+ ```
+  new = arambhNet(path,target) #target is the dependent feature and path is the path of csv file
+  ```
+ ```
+  new.get_model_details(path,target)
+  ```
+
+## Run the Above Commands to get the results.
+
+
+**NOTE** There are more than functionalities available, you can press "tab" after "new." to get the options
+
+## Here you can perform EDA and also see how do models perform on the dataset.
+
+## Note 
+- I have tried to implement all the functionality, it might have some bugs also. Moreover a number of more functionalities would be added later.
+
+
+
+
+%package -n python3-ARAMBHML
+Summary:	An Auto ML framework that solves Classification Tasks
+Provides:	python-ARAMBHML
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-ARAMBHML
+
+# Auto ML for Solving Classification Problems for Tabular Data
+
+[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
+[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)   
+
+
+## Functionality of the Auto ML Framework
+
+- Detects the type of problem from the given target feature
+- Does EDA on it's own
+- Finds out if there are null values present or not
+- If null values are present they are treated specifically with the class they are present in
+- Forms train-test split on it's own
+- Applies 6 ML models to show the use which model performs the best
+
+## Usage
+
+- Make sure you have Python installed in your system.
+- Run Following command in the CMD.
+ ```
+  pip install ARAMBHML
+  ```
+## Example
+
+
+# test.py
+ ```
+  from ARAMBHML import arambhNet
+  ```
+ ```
+  new = arambhNet(path,target) #target is the dependent feature and path is the path of csv file
+  ```
+ ```
+  new.get_model_details(path,target)
+  ```
+
+## Run the Above Commands to get the results.
+
+
+**NOTE** There are more than functionalities available, you can press "tab" after "new." to get the options
+
+## Here you can perform EDA and also see how do models perform on the dataset.
+
+## Note 
+- I have tried to implement all the functionality, it might have some bugs also. Moreover a number of more functionalities would be added later.
+
+
+
+
+%package help
+Summary:	Development documents and examples for ARAMBHML
+Provides:	python3-ARAMBHML-doc
+%description help
+
+# Auto ML for Solving Classification Problems for Tabular Data
+
+[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
+[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)   
+
+
+## Functionality of the Auto ML Framework
+
+- Detects the type of problem from the given target feature
+- Does EDA on it's own
+- Finds out if there are null values present or not
+- If null values are present they are treated specifically with the class they are present in
+- Forms train-test split on it's own
+- Applies 6 ML models to show the use which model performs the best
+
+## Usage
+
+- Make sure you have Python installed in your system.
+- Run Following command in the CMD.
+ ```
+  pip install ARAMBHML
+  ```
+## Example
+
+
+# test.py
+ ```
+  from ARAMBHML import arambhNet
+  ```
+ ```
+  new = arambhNet(path,target) #target is the dependent feature and path is the path of csv file
+  ```
+ ```
+  new.get_model_details(path,target)
+  ```
+
+## Run the Above Commands to get the results.
+
+
+**NOTE** There are more than functionalities available, you can press "tab" after "new." to get the options
+
+## Here you can perform EDA and also see how do models perform on the dataset.
+
+## Note 
+- I have tried to implement all the functionality, it might have some bugs also. Moreover a number of more functionalities would be added later.
+
+
+
+
+%prep
+%autosetup -n ARAMBHML-0.2.4
+
+%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-ARAMBHML -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.4-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..235b37c
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+db0453990b92b30f5dfb7776cdb35ed3  ARAMBHML-0.2.4.tar.gz