%global _empty_manifest_terminate_build 0
Name:		python-papermill
Version:	2.4.0
Release:	1
Summary:	Parametrize and run Jupyter and nteract Notebooks
License:	BSD
URL:		https://github.com/nteract/papermill
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b8/c9/56294fddb4b19b074fece0c277cbe9159501d7bb2e143f477e6d776342ae/papermill-2.4.0.tar.gz
BuildArch:	noarch

Requires:	python3-ansiwrap
Requires:	python3-click
Requires:	python3-pyyaml
Requires:	python3-nbformat
Requires:	python3-nbclient
Requires:	python3-tqdm
Requires:	python3-requests
Requires:	python3-entrypoints
Requires:	python3-tenacity
Requires:	python3-boto3
Requires:	python3-azure-datalake-store
Requires:	python3-azure-storage-blob
Requires:	python3-requests
Requires:	python3-gcsfs
Requires:	python3-pyarrow
Requires:	python3-black
Requires:	python3-azure-datalake-store
Requires:	python3-azure-storage-blob
Requires:	python3-requests
Requires:	python3-black
Requires:	python3-boto3
Requires:	python3-botocore
Requires:	python3-codecov
Requires:	python3-coverage
Requires:	python3-google-compute-engine
Requires:	python3-ipython
Requires:	python3-ipywidgets
Requires:	python3-notebook
Requires:	python3-moto
Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-pytest-mock
Requires:	python3-pytest-env
Requires:	python3-requests
Requires:	python3-check-manifest
Requires:	python3-attrs
Requires:	python3-pre-commit
Requires:	python3-flake8
Requires:	python3-tox
Requires:	python3-bumpversion
Requires:	python3-recommonmark
Requires:	python3-pip
Requires:	python3-wheel
Requires:	python3-setuptools
Requires:	python3-twine
Requires:	python3-azure-datalake-store
Requires:	python3-azure-storage-blob
Requires:	python3-gcsfs
Requires:	python3-pyarrow
Requires:	python3-black
Requires:	python3-gcsfs
Requires:	python3-PyGithub
Requires:	python3-pyarrow
Requires:	python3-boto3
Requires:	python3-boto3
Requires:	python3-botocore
Requires:	python3-codecov
Requires:	python3-coverage
Requires:	python3-google-compute-engine
Requires:	python3-ipython
Requires:	python3-ipywidgets
Requires:	python3-notebook
Requires:	python3-moto
Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-pytest-mock
Requires:	python3-pytest-env
Requires:	python3-requests
Requires:	python3-check-manifest
Requires:	python3-attrs
Requires:	python3-pre-commit
Requires:	python3-flake8
Requires:	python3-tox
Requires:	python3-bumpversion
Requires:	python3-recommonmark
Requires:	python3-pip
Requires:	python3-wheel
Requires:	python3-setuptools
Requires:	python3-twine
Requires:	python3-azure-datalake-store
Requires:	python3-azure-storage-blob
Requires:	python3-gcsfs
Requires:	python3-pyarrow
Requires:	python3-black

%description
<!---(binder links generated at https://mybinder.readthedocs.io/en/latest/howto/badges.html and compressed at https://tinyurl.com) -->
[![CI](https://github.com/nteract/papermill/actions/workflows/ci.yml/badge.svg)](https://github.com/nteract/papermill/actions/workflows/ci.yml)
[![CI](https://github.com/nteract/papermill/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/nteract/papermill/actions/workflows/ci.yml)
[![image](https://codecov.io/github/nteract/papermill/coverage.svg?branch=main)](https://codecov.io/github/nteract/papermill?branch=main)
[![Documentation Status](https://readthedocs.org/projects/papermill/badge/?version=latest)](http://papermill.readthedocs.io/en/latest/?badge=latest)
[![badge](https://tinyurl.com/ybwovtw2)](https://mybinder.org/v2/gh/nteract/papermill/main?filepath=binder%2Fprocess_highlight_dates.ipynb)
[![badge](https://tinyurl.com/y7uz2eh9)](https://mybinder.org/v2/gh/nteract/papermill/main?)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/papermill)](https://pypi.org/project/papermill/)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
[![papermill](https://snyk.io/advisor/python/papermill/badge.svg)](https://snyk.io/advisor/python/papermill)
[![Anaconda-Server Badge](https://anaconda.org/conda-forge/papermill/badges/downloads.svg)](https://anaconda.org/conda-forge/papermill)
**papermill** is a tool for parameterizing, executing, and analyzing
Jupyter Notebooks.
Papermill lets you:
-   **parameterize** notebooks
-   **execute** notebooks
This opens up new opportunities for how notebooks can be used. For
example:
-   Perhaps you have a financial report that you wish to run with
    different values on the first or last day of a month or at the
    beginning or end of the year, **using parameters** makes this task
    easier.
-   Do you want to run a notebook and depending on its results, choose a
    particular notebook to run next? You can now programmatically
    **execute a workflow** without having to copy and paste from
    notebook to notebook manually.
Papermill takes an *opinionated* approach to notebook parameterization and
execution based on our experiences using notebooks at scale in data
pipelines.
## Installation
From the command line:
``` {.sourceCode .bash}
pip install papermill
```
For all optional io dependencies, you can specify individual bundles
like `s3`, or `azure` -- or use `all`. To use Black to format parameters you can add as an extra requires ['black'].
``` {.sourceCode .bash}
pip install papermill[all]
```
## Python Version Support
This library currently supports Python 3.7+ versions. As minor Python
versions are officially sunset by the Python org papermill will similarly
drop support in the future.
## Usage
### Parameterizing a Notebook
To parameterize your notebook designate a cell with the tag ``parameters``.
![enable parameters in Jupyter](docs/img/enable_parameters.gif)
Papermill looks for the ``parameters`` cell and treats this cell as defaults for the parameters passed in at execution time. Papermill will add a new cell tagged with ``injected-parameters`` with input parameters in order to overwrite the values in ``parameters``. If no cell is tagged with ``parameters`` the injected cell will be inserted at the top of the notebook.
Additionally, if you rerun notebooks through papermill and it will reuse the ``injected-parameters`` cell from the prior run. In this case Papermill will replace the old ``injected-parameters`` cell with the new run's inputs.
![image](docs/img/parameters.png)
### Executing a Notebook
The two ways to execute the notebook with parameters are: (1) through
the Python API and (2) through the command line interface.
#### Execute via the Python API
``` {.sourceCode .python}
import papermill as pm
pm.execute_notebook(
   'path/to/input.ipynb',
   'path/to/output.ipynb',
   parameters = dict(alpha=0.6, ratio=0.1)
)
```
#### Execute via CLI
Here's an example of a local notebook being executed and output to an
Amazon S3 account:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1
```
**NOTE:**
If you use multiple AWS accounts, and you have [properly configured your AWS  credentials](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html), then you can specify which account to use by setting the `AWS_PROFILE` environment variable at the command-line. For example:
``` {.sourceCode .bash}
$ AWS_PROFILE=dev_account papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1
```
In the above example, two parameters are set: ``alpha`` and ``l1_ratio`` using ``-p`` (``--parameters`` also works). Parameter values that look like booleans or numbers will be interpreted as such. Here are the different ways users may set parameters:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -r version 1.0
```
Using ``-r`` or ``--parameters_raw``, users can set parameters one by one. However, unlike ``-p``, the parameter will remain a string, even if it may be interpreted as a number or boolean.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -f parameters.yaml
```
Using ``-f`` or ``--parameters_file``, users can provide a YAML file from which parameter values should be read.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
alpha: 0.6
l1_ratio: 0.1"
```
Using ``-y`` or ``--parameters_yaml``, users can directly provide a YAML string containing parameter values.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -b YWxwaGE6IDAuNgpsMV9yYXRpbzogMC4xCg==
```
Using ``-b`` or ``--parameters_base64``, users can provide a YAML string, base64-encoded, containing parameter values.
When using YAML to pass arguments, through ``-y``, ``-b`` or ``-f``, parameter values can be arrays or dictionaries:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
x:
    - 0.0
    - 1.0
    - 2.0
    - 3.0
linear_function:
    slope: 3.0
    intercept: 1.0"
```
#### Supported Name Handlers
Papermill supports the following name handlers for input and output paths during execution:
 * Local file system: `local`
 * HTTP, HTTPS protocol:  `http://, https://`
 * Amazon Web Services: [AWS S3](https://aws.amazon.com/s3/) `s3://`
 * Azure: [Azure DataLake Store](https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-overview), [Azure Blob Store](https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blobs-overview) `adl://, abs://`
 * Google Cloud: [Google Cloud Storage](https://cloud.google.com/storage/) `gs://`

%package -n python3-papermill
Summary:	Parametrize and run Jupyter and nteract Notebooks
Provides:	python-papermill
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-papermill
<!---(binder links generated at https://mybinder.readthedocs.io/en/latest/howto/badges.html and compressed at https://tinyurl.com) -->
[![CI](https://github.com/nteract/papermill/actions/workflows/ci.yml/badge.svg)](https://github.com/nteract/papermill/actions/workflows/ci.yml)
[![CI](https://github.com/nteract/papermill/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/nteract/papermill/actions/workflows/ci.yml)
[![image](https://codecov.io/github/nteract/papermill/coverage.svg?branch=main)](https://codecov.io/github/nteract/papermill?branch=main)
[![Documentation Status](https://readthedocs.org/projects/papermill/badge/?version=latest)](http://papermill.readthedocs.io/en/latest/?badge=latest)
[![badge](https://tinyurl.com/ybwovtw2)](https://mybinder.org/v2/gh/nteract/papermill/main?filepath=binder%2Fprocess_highlight_dates.ipynb)
[![badge](https://tinyurl.com/y7uz2eh9)](https://mybinder.org/v2/gh/nteract/papermill/main?)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/papermill)](https://pypi.org/project/papermill/)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
[![papermill](https://snyk.io/advisor/python/papermill/badge.svg)](https://snyk.io/advisor/python/papermill)
[![Anaconda-Server Badge](https://anaconda.org/conda-forge/papermill/badges/downloads.svg)](https://anaconda.org/conda-forge/papermill)
**papermill** is a tool for parameterizing, executing, and analyzing
Jupyter Notebooks.
Papermill lets you:
-   **parameterize** notebooks
-   **execute** notebooks
This opens up new opportunities for how notebooks can be used. For
example:
-   Perhaps you have a financial report that you wish to run with
    different values on the first or last day of a month or at the
    beginning or end of the year, **using parameters** makes this task
    easier.
-   Do you want to run a notebook and depending on its results, choose a
    particular notebook to run next? You can now programmatically
    **execute a workflow** without having to copy and paste from
    notebook to notebook manually.
Papermill takes an *opinionated* approach to notebook parameterization and
execution based on our experiences using notebooks at scale in data
pipelines.
## Installation
From the command line:
``` {.sourceCode .bash}
pip install papermill
```
For all optional io dependencies, you can specify individual bundles
like `s3`, or `azure` -- or use `all`. To use Black to format parameters you can add as an extra requires ['black'].
``` {.sourceCode .bash}
pip install papermill[all]
```
## Python Version Support
This library currently supports Python 3.7+ versions. As minor Python
versions are officially sunset by the Python org papermill will similarly
drop support in the future.
## Usage
### Parameterizing a Notebook
To parameterize your notebook designate a cell with the tag ``parameters``.
![enable parameters in Jupyter](docs/img/enable_parameters.gif)
Papermill looks for the ``parameters`` cell and treats this cell as defaults for the parameters passed in at execution time. Papermill will add a new cell tagged with ``injected-parameters`` with input parameters in order to overwrite the values in ``parameters``. If no cell is tagged with ``parameters`` the injected cell will be inserted at the top of the notebook.
Additionally, if you rerun notebooks through papermill and it will reuse the ``injected-parameters`` cell from the prior run. In this case Papermill will replace the old ``injected-parameters`` cell with the new run's inputs.
![image](docs/img/parameters.png)
### Executing a Notebook
The two ways to execute the notebook with parameters are: (1) through
the Python API and (2) through the command line interface.
#### Execute via the Python API
``` {.sourceCode .python}
import papermill as pm
pm.execute_notebook(
   'path/to/input.ipynb',
   'path/to/output.ipynb',
   parameters = dict(alpha=0.6, ratio=0.1)
)
```
#### Execute via CLI
Here's an example of a local notebook being executed and output to an
Amazon S3 account:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1
```
**NOTE:**
If you use multiple AWS accounts, and you have [properly configured your AWS  credentials](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html), then you can specify which account to use by setting the `AWS_PROFILE` environment variable at the command-line. For example:
``` {.sourceCode .bash}
$ AWS_PROFILE=dev_account papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1
```
In the above example, two parameters are set: ``alpha`` and ``l1_ratio`` using ``-p`` (``--parameters`` also works). Parameter values that look like booleans or numbers will be interpreted as such. Here are the different ways users may set parameters:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -r version 1.0
```
Using ``-r`` or ``--parameters_raw``, users can set parameters one by one. However, unlike ``-p``, the parameter will remain a string, even if it may be interpreted as a number or boolean.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -f parameters.yaml
```
Using ``-f`` or ``--parameters_file``, users can provide a YAML file from which parameter values should be read.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
alpha: 0.6
l1_ratio: 0.1"
```
Using ``-y`` or ``--parameters_yaml``, users can directly provide a YAML string containing parameter values.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -b YWxwaGE6IDAuNgpsMV9yYXRpbzogMC4xCg==
```
Using ``-b`` or ``--parameters_base64``, users can provide a YAML string, base64-encoded, containing parameter values.
When using YAML to pass arguments, through ``-y``, ``-b`` or ``-f``, parameter values can be arrays or dictionaries:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
x:
    - 0.0
    - 1.0
    - 2.0
    - 3.0
linear_function:
    slope: 3.0
    intercept: 1.0"
```
#### Supported Name Handlers
Papermill supports the following name handlers for input and output paths during execution:
 * Local file system: `local`
 * HTTP, HTTPS protocol:  `http://, https://`
 * Amazon Web Services: [AWS S3](https://aws.amazon.com/s3/) `s3://`
 * Azure: [Azure DataLake Store](https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-overview), [Azure Blob Store](https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blobs-overview) `adl://, abs://`
 * Google Cloud: [Google Cloud Storage](https://cloud.google.com/storage/) `gs://`

%package help
Summary:	Development documents and examples for papermill
Provides:	python3-papermill-doc
%description help
<!---(binder links generated at https://mybinder.readthedocs.io/en/latest/howto/badges.html and compressed at https://tinyurl.com) -->
[![CI](https://github.com/nteract/papermill/actions/workflows/ci.yml/badge.svg)](https://github.com/nteract/papermill/actions/workflows/ci.yml)
[![CI](https://github.com/nteract/papermill/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/nteract/papermill/actions/workflows/ci.yml)
[![image](https://codecov.io/github/nteract/papermill/coverage.svg?branch=main)](https://codecov.io/github/nteract/papermill?branch=main)
[![Documentation Status](https://readthedocs.org/projects/papermill/badge/?version=latest)](http://papermill.readthedocs.io/en/latest/?badge=latest)
[![badge](https://tinyurl.com/ybwovtw2)](https://mybinder.org/v2/gh/nteract/papermill/main?filepath=binder%2Fprocess_highlight_dates.ipynb)
[![badge](https://tinyurl.com/y7uz2eh9)](https://mybinder.org/v2/gh/nteract/papermill/main?)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/papermill)](https://pypi.org/project/papermill/)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
[![papermill](https://snyk.io/advisor/python/papermill/badge.svg)](https://snyk.io/advisor/python/papermill)
[![Anaconda-Server Badge](https://anaconda.org/conda-forge/papermill/badges/downloads.svg)](https://anaconda.org/conda-forge/papermill)
**papermill** is a tool for parameterizing, executing, and analyzing
Jupyter Notebooks.
Papermill lets you:
-   **parameterize** notebooks
-   **execute** notebooks
This opens up new opportunities for how notebooks can be used. For
example:
-   Perhaps you have a financial report that you wish to run with
    different values on the first or last day of a month or at the
    beginning or end of the year, **using parameters** makes this task
    easier.
-   Do you want to run a notebook and depending on its results, choose a
    particular notebook to run next? You can now programmatically
    **execute a workflow** without having to copy and paste from
    notebook to notebook manually.
Papermill takes an *opinionated* approach to notebook parameterization and
execution based on our experiences using notebooks at scale in data
pipelines.
## Installation
From the command line:
``` {.sourceCode .bash}
pip install papermill
```
For all optional io dependencies, you can specify individual bundles
like `s3`, or `azure` -- or use `all`. To use Black to format parameters you can add as an extra requires ['black'].
``` {.sourceCode .bash}
pip install papermill[all]
```
## Python Version Support
This library currently supports Python 3.7+ versions. As minor Python
versions are officially sunset by the Python org papermill will similarly
drop support in the future.
## Usage
### Parameterizing a Notebook
To parameterize your notebook designate a cell with the tag ``parameters``.
![enable parameters in Jupyter](docs/img/enable_parameters.gif)
Papermill looks for the ``parameters`` cell and treats this cell as defaults for the parameters passed in at execution time. Papermill will add a new cell tagged with ``injected-parameters`` with input parameters in order to overwrite the values in ``parameters``. If no cell is tagged with ``parameters`` the injected cell will be inserted at the top of the notebook.
Additionally, if you rerun notebooks through papermill and it will reuse the ``injected-parameters`` cell from the prior run. In this case Papermill will replace the old ``injected-parameters`` cell with the new run's inputs.
![image](docs/img/parameters.png)
### Executing a Notebook
The two ways to execute the notebook with parameters are: (1) through
the Python API and (2) through the command line interface.
#### Execute via the Python API
``` {.sourceCode .python}
import papermill as pm
pm.execute_notebook(
   'path/to/input.ipynb',
   'path/to/output.ipynb',
   parameters = dict(alpha=0.6, ratio=0.1)
)
```
#### Execute via CLI
Here's an example of a local notebook being executed and output to an
Amazon S3 account:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1
```
**NOTE:**
If you use multiple AWS accounts, and you have [properly configured your AWS  credentials](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html), then you can specify which account to use by setting the `AWS_PROFILE` environment variable at the command-line. For example:
``` {.sourceCode .bash}
$ AWS_PROFILE=dev_account papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1
```
In the above example, two parameters are set: ``alpha`` and ``l1_ratio`` using ``-p`` (``--parameters`` also works). Parameter values that look like booleans or numbers will be interpreted as such. Here are the different ways users may set parameters:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -r version 1.0
```
Using ``-r`` or ``--parameters_raw``, users can set parameters one by one. However, unlike ``-p``, the parameter will remain a string, even if it may be interpreted as a number or boolean.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -f parameters.yaml
```
Using ``-f`` or ``--parameters_file``, users can provide a YAML file from which parameter values should be read.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
alpha: 0.6
l1_ratio: 0.1"
```
Using ``-y`` or ``--parameters_yaml``, users can directly provide a YAML string containing parameter values.
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -b YWxwaGE6IDAuNgpsMV9yYXRpbzogMC4xCg==
```
Using ``-b`` or ``--parameters_base64``, users can provide a YAML string, base64-encoded, containing parameter values.
When using YAML to pass arguments, through ``-y``, ``-b`` or ``-f``, parameter values can be arrays or dictionaries:
``` {.sourceCode .bash}
$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
x:
    - 0.0
    - 1.0
    - 2.0
    - 3.0
linear_function:
    slope: 3.0
    intercept: 1.0"
```
#### Supported Name Handlers
Papermill supports the following name handlers for input and output paths during execution:
 * Local file system: `local`
 * HTTP, HTTPS protocol:  `http://, https://`
 * Amazon Web Services: [AWS S3](https://aws.amazon.com/s3/) `s3://`
 * Azure: [Azure DataLake Store](https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-overview), [Azure Blob Store](https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blobs-overview) `adl://, abs://`
 * Google Cloud: [Google Cloud Storage](https://cloud.google.com/storage/) `gs://`

%prep
%autosetup -n papermill-2.4.0

%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-papermill -f filelist.lst
%dir %{python3_sitelib}/*

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

%changelog
* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 2.4.0-1
- Package Spec generated