automatic import of python-pandas-awsopeneuler20.03

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diff --git a/.gitignore b/.gitignore
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--- a/.gitignore
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+/pandas-aws-0.1.6.tar.gz
diff --git a/python-pandas-aws.spec b/python-pandas-aws.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-pandas-aws
+Version:	0.1.6
+Release:	1
+Summary:	please add a summary manually as the author left a blank one
+License:	MIT
+URL:		https://github.com/FlorentPajot/pandas-aws
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/bb/99/352369f0265066eeb3d222f312beb555df5b6676fa0a30d93e6edceeabe6/pandas-aws-0.1.6.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-boto3
+Requires:	python3-pandas
+Requires:	python3-fastparquet
+Requires:	python3-pyarrow
+Requires:	python3-xlsxwriter
+Requires:	python3-xlrd
+Requires:	python3-psycopg2
+
+%description
+[![Build Status](https://travis-ci.com/FlorentPajot/pandas-aws.svg?branch=master)](https://travis-ci.com/FlorentPajot/pandas-aws) [![codecov](https://codecov.io/gh/FlorentPajot/pandas-aws/branch/master/graph/badge.svg)](https://codecov.io/gh/FlorentPajot/pandas-aws)
+
+# Pandas AWS - AWS made easy for data scientists
+
+Pandas AWS makes it super easy to use a pandas.DataFrame along with AWS services.
+
+## Working with S3
+
+First create an S3 client to be used later and define a bucket
+```
+from pandas_aws import get_client
+
+s3 = get_client('s3')
+MY_BUCKET= 'pandas-aws-bucket'
+```
+Example 1: get a DataFrame from a parquet file stored in S3
+```
+from pandas_aws.s3 import get_df
+
+df_from_parquet_file = get_df(s3, MY_BUCKET, 'my_parquet_file_path', format='parquet')
+```
+Example 2: get a DataFrame from multiple CSV files (with same schema) stored in S3
+```
+from pandas_aws.s3 import get_df_from_keys
+
+df_from_list = get_df_from_keys(s3, MY_BUCKET, prefix='my-folder', suffix='.csv')
+```
+Example 3: put a DataFrame into S3 using an xlsx (Excel) file format
+```
+from pandas_aws.s3 import put_df
+
+put_df(s3, my_dataframe, MY_BUCKET, 'target_file_path', format='xlsx')
+```
+Example 4: put a DataFrame into S3 using multi parts upload
+```
+from pandas_aws.s3 import put_df
+
+put_df(s3, my_dataframe, MY_BUCKET, 'target_file_path', format='csv', compression='gzip', parts=8)
+```
+
+# Installing pandas-aws
+
+## Pip installation
+
+You can use pip to download the package
+
+`pip install pandas-aws`
+
+# Contributing to pandas-aws
+
+## Git clone
+
+We use the `develop` brand as the release branch, thus `git clone` the repository and `git checkout develop` in order to get the latest version in development.
+
+```
+git clone git@github.com:FlorentPajot/pandas-aws.git
+```
+
+## Preparing your environment
+
+Pandas AWS uses `poetry` to manage dependencies. Thus, `poetry` is required:
+
+`curl -SSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python`
+
+Create a separate Python environment, for example using `pyenv` along with `pyenv-virtualenv` and Python 3.7.7:
+
+```
+pyenv install 3.7.7
+pyenv virtualenv 3.7.7 pandas-aws
+pyenv activate pandas-aws
+```
+
+Check your environment using:
+```
+which python
+// should show something like .pyenv/shims/python
+python -V
+// should show python 3.7.7 (or any other version you selected)
+pip list
+// should show barely nothing except pip and setuptools
+```
+
+In cas your encounter a problem, check `Pyenv` documentation.
+
+Then install dependencies with poetry after your `git clone` from the project repository:
+
+`poetry install`
+
+## Guidelines
+
+Todo
+
+## Requires
+The project needs the following dependencies:
+- libpq-dev (psycopg2 dependency)
+
+
+%package -n python3-pandas-aws
+Summary:	please add a summary manually as the author left a blank one
+Provides:	python-pandas-aws
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-pandas-aws
+[![Build Status](https://travis-ci.com/FlorentPajot/pandas-aws.svg?branch=master)](https://travis-ci.com/FlorentPajot/pandas-aws) [![codecov](https://codecov.io/gh/FlorentPajot/pandas-aws/branch/master/graph/badge.svg)](https://codecov.io/gh/FlorentPajot/pandas-aws)
+
+# Pandas AWS - AWS made easy for data scientists
+
+Pandas AWS makes it super easy to use a pandas.DataFrame along with AWS services.
+
+## Working with S3
+
+First create an S3 client to be used later and define a bucket
+```
+from pandas_aws import get_client
+
+s3 = get_client('s3')
+MY_BUCKET= 'pandas-aws-bucket'
+```
+Example 1: get a DataFrame from a parquet file stored in S3
+```
+from pandas_aws.s3 import get_df
+
+df_from_parquet_file = get_df(s3, MY_BUCKET, 'my_parquet_file_path', format='parquet')
+```
+Example 2: get a DataFrame from multiple CSV files (with same schema) stored in S3
+```
+from pandas_aws.s3 import get_df_from_keys
+
+df_from_list = get_df_from_keys(s3, MY_BUCKET, prefix='my-folder', suffix='.csv')
+```
+Example 3: put a DataFrame into S3 using an xlsx (Excel) file format
+```
+from pandas_aws.s3 import put_df
+
+put_df(s3, my_dataframe, MY_BUCKET, 'target_file_path', format='xlsx')
+```
+Example 4: put a DataFrame into S3 using multi parts upload
+```
+from pandas_aws.s3 import put_df
+
+put_df(s3, my_dataframe, MY_BUCKET, 'target_file_path', format='csv', compression='gzip', parts=8)
+```
+
+# Installing pandas-aws
+
+## Pip installation
+
+You can use pip to download the package
+
+`pip install pandas-aws`
+
+# Contributing to pandas-aws
+
+## Git clone
+
+We use the `develop` brand as the release branch, thus `git clone` the repository and `git checkout develop` in order to get the latest version in development.
+
+```
+git clone git@github.com:FlorentPajot/pandas-aws.git
+```
+
+## Preparing your environment
+
+Pandas AWS uses `poetry` to manage dependencies. Thus, `poetry` is required:
+
+`curl -SSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python`
+
+Create a separate Python environment, for example using `pyenv` along with `pyenv-virtualenv` and Python 3.7.7:
+
+```
+pyenv install 3.7.7
+pyenv virtualenv 3.7.7 pandas-aws
+pyenv activate pandas-aws
+```
+
+Check your environment using:
+```
+which python
+// should show something like .pyenv/shims/python
+python -V
+// should show python 3.7.7 (or any other version you selected)
+pip list
+// should show barely nothing except pip and setuptools
+```
+
+In cas your encounter a problem, check `Pyenv` documentation.
+
+Then install dependencies with poetry after your `git clone` from the project repository:
+
+`poetry install`
+
+## Guidelines
+
+Todo
+
+## Requires
+The project needs the following dependencies:
+- libpq-dev (psycopg2 dependency)
+
+
+%package help
+Summary:	Development documents and examples for pandas-aws
+Provides:	python3-pandas-aws-doc
+%description help
+[![Build Status](https://travis-ci.com/FlorentPajot/pandas-aws.svg?branch=master)](https://travis-ci.com/FlorentPajot/pandas-aws) [![codecov](https://codecov.io/gh/FlorentPajot/pandas-aws/branch/master/graph/badge.svg)](https://codecov.io/gh/FlorentPajot/pandas-aws)
+
+# Pandas AWS - AWS made easy for data scientists
+
+Pandas AWS makes it super easy to use a pandas.DataFrame along with AWS services.
+
+## Working with S3
+
+First create an S3 client to be used later and define a bucket
+```
+from pandas_aws import get_client
+
+s3 = get_client('s3')
+MY_BUCKET= 'pandas-aws-bucket'
+```
+Example 1: get a DataFrame from a parquet file stored in S3
+```
+from pandas_aws.s3 import get_df
+
+df_from_parquet_file = get_df(s3, MY_BUCKET, 'my_parquet_file_path', format='parquet')
+```
+Example 2: get a DataFrame from multiple CSV files (with same schema) stored in S3
+```
+from pandas_aws.s3 import get_df_from_keys
+
+df_from_list = get_df_from_keys(s3, MY_BUCKET, prefix='my-folder', suffix='.csv')
+```
+Example 3: put a DataFrame into S3 using an xlsx (Excel) file format
+```
+from pandas_aws.s3 import put_df
+
+put_df(s3, my_dataframe, MY_BUCKET, 'target_file_path', format='xlsx')
+```
+Example 4: put a DataFrame into S3 using multi parts upload
+```
+from pandas_aws.s3 import put_df
+
+put_df(s3, my_dataframe, MY_BUCKET, 'target_file_path', format='csv', compression='gzip', parts=8)
+```
+
+# Installing pandas-aws
+
+## Pip installation
+
+You can use pip to download the package
+
+`pip install pandas-aws`
+
+# Contributing to pandas-aws
+
+## Git clone
+
+We use the `develop` brand as the release branch, thus `git clone` the repository and `git checkout develop` in order to get the latest version in development.
+
+```
+git clone git@github.com:FlorentPajot/pandas-aws.git
+```
+
+## Preparing your environment
+
+Pandas AWS uses `poetry` to manage dependencies. Thus, `poetry` is required:
+
+`curl -SSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python`
+
+Create a separate Python environment, for example using `pyenv` along with `pyenv-virtualenv` and Python 3.7.7:
+
+```
+pyenv install 3.7.7
+pyenv virtualenv 3.7.7 pandas-aws
+pyenv activate pandas-aws
+```
+
+Check your environment using:
+```
+which python
+// should show something like .pyenv/shims/python
+python -V
+// should show python 3.7.7 (or any other version you selected)
+pip list
+// should show barely nothing except pip and setuptools
+```
+
+In cas your encounter a problem, check `Pyenv` documentation.
+
+Then install dependencies with poetry after your `git clone` from the project repository:
+
+`poetry install`
+
+## Guidelines
+
+Todo
+
+## Requires
+The project needs the following dependencies:
+- libpq-dev (psycopg2 dependency)
+
+
+%prep
+%autosetup -n pandas-aws-0.1.6
+
+%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-pandas-aws -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.6-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..5c8329e
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+4213a1ea72c310acafaebf27b574ae04  pandas-aws-0.1.6.tar.gz