automatic import of python-dragonfly-opt

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+/dragonfly-opt-0.1.7.tar.gz
diff --git a/python-dragonfly-opt.spec b/python-dragonfly-opt.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-dragonfly-opt
+Version:	0.1.7
+Release:	1
+Summary:	please add a summary manually as the author left a blank one
+License:	MIT
+URL:		https://github.com/dragonfly/dragonfly/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/d8/d4/4dc27b149e1c39a06d5f91e6d5aff84c285d28e8d93fcc780b2a40ea39ec/dragonfly-opt-0.1.7.tar.gz
+BuildArch:	noarch
+
+
+%description
+Dragonfly is an open source python library for scalable Bayesian optimisation.
+Bayesian optimisation is used for optimising black-box functions whose evaluations are
+usually expensive. Beyond vanilla optimisation techniques, Dragonfly provides an array of tools to
+scale up Bayesian optimisation to expensive large scale problems.
+These include features/functionality that are especially suited for
+high dimensional optimisation (optimising for a large number of variables),
+parallel evaluations in synchronous or asynchronous settings (conducting multiple
+evaluations in parallel), multi-fidelity optimisation (using cheap approximations
+to speed up the optimisation process), and multi-objective optimisation (optimising
+multiple functions simultaneously).
+Dragonfly is compatible with Python2 (>= 2.7) and Python3 (>= 3.5) and has been tested
+on Linux, macOS, and Windows platforms.
+For documentation, installation, and a getting started guide, see our
+[readthedocs page](https://dragonfly-opt.readthedocs.io). For more details, see
+our [paper](https://arxiv.org/abs/1903.06694).
+ 
+## Installation
+See 
+[here](https://dragonfly-opt.readthedocs.io/en/master/install/)
+for detailed instructions on installing Dragonfly and its dependencies.
+**Quick Installation:**
+If you have done this kind of thing before, you should be able to install
+Dragonfly via `pip`.
+```bash
+$ sudo apt-get install python-dev python3-dev gfortran # On Ubuntu/Debian
+$ pip install numpy
+$ pip install dragonfly-opt -v
+```
+**Testing the Installation**:
+You can import Dragonfly in python to test if it was installed properly.
+If you have installed via source, make sure that you move to a different directory 
+ to avoid naming conflicts.
+```bash
+$ python
+>>> from dragonfly import minimise_function
+>>> # The first argument below is the function, the second is the domain, and the third is the budget.
+>>> min_val, min_pt, history = minimise_function(lambda x: x ** 4 - x**2 + 0.1 * x, [[-10, 10]], 10);  
+>>> min_val, min_pt
+(-0.32122746026750953, array([-0.7129672]))
+```
+Due to stochasticity in the algorithms, the above values for `min_val`, `min_pt` may be
+different. If you run it for longer (e.g.
+`min_val, min_pt, history = minimise_function(lambda x: x ** 4 - x**2 + 0.1 * x, [[-10, 10]], 100)`),
+you should get more consistent values for the minimum. 
+If the installation fails or if there are warning messages, see detailed instructions
+[here](https://dragonfly-opt.readthedocs.io/en/master/install/).
+ 
+## Quick Start
+Dragonfly can be
+used directly in the command line by calling
+[`dragonfly-script.py`](bin/dragonfly-script.py)
+or be imported in python code via the `maximise_function` function in the main library
+or in <em>ask-tell</em> mode.
+To help get started, we have provided some examples in the
+[`examples`](examples) directory.
+See our readthedocs getting started pages
+([command line](https://dragonfly-opt.readthedocs.io/en/master/getting_started_cli/),
+[Python](https://dragonfly-opt.readthedocs.io/en/master/getting_started_py/),
+[Ask-Tell](https://dragonfly-opt.readthedocs.io/en/master/getting_started_ask_tell/))
+for examples and use cases.
+**Command line**:
+Below is an example usage in the command line.
+```bash
+$ cd examples
+$ dragonfly-script.py --config synthetic/branin/config.json --options options_files/options_example.txt
+```
+**In Python code**:
+The main APIs for Dragonfly are defined in
+[`dragonfly/apis`](dragonfly/apis).
+For their definitions and arguments, see
+[`dragonfly/apis/opt.py`](dragonfly/apis/opt.py) and
+[`dragonfly/apis/moo.py`](dragonfly/apis/moo.py).
+You can import the main API in python code via,
+```python
+from dragonfly import minimise_function, maximise_function
+func = lambda x: x ** 4 - x**2 + 0.1 * x
+domain = [[-10, 10]]
+max_capital = 100
+min_val, min_pt, history = minimise_function(func, domain, max_capital)
+print(min_val, min_pt)
+max_val, max_pt, history = maximise_function(lambda x: -func(x), domain, max_capital)
+print(max_val, max_pt)
+```
+Here, `func` is the function to be maximised,
+`domain` is the domain over which `func` is to be optimised,
+and `max_capital` is the capital available for optimisation.
+The domain can be specified via a JSON file or in code.
+See
+[here](examples/synthetic/branin/in_code_demo.py),
+[here](examples/synthetic/hartmann6_4/in_code_demo.py),
+[here](examples/synthetic/discrete_euc/in_code_demo_1.py),
+[here](examples/synthetic/discrete_euc/in_code_demo_2.py),
+[here](examples/synthetic/hartmann3_constrained/in_code_demo.py),
+[here](examples/synthetic/park1_constrained/in_code_demo.py),
+[here](examples/synthetic/borehole_constrained/in_code_demo.py),
+[here](examples/synthetic/multiobjective_branin_currinexp/in_code_demo.py),
+[here](examples/synthetic/multiobjective_hartmann/in_code_demo.py),
+[here](examples/tree_reg/in_code_demo.py),
+and
+[here](examples/nas/demo_nas.py)
+for more detailed examples.
+**In Ask-Tell Mode**:
+Ask-tell mode provides you more control over your experiments where you can supply past results
+to our API in order to obtain a recommendation.
+See the [following example](examples/detailed_use_cases/in_code_demo_ask_tell.py) for more details.
+For a comprehensive list of uses cases, including multi-objective optimisation,
+multi-fidelity optimisation, neural architecture search, and other optimisation
+methods (besides Bayesian optimisation), see our readthe docs pages
+([command line](https://dragonfly-opt.readthedocs.io/en/master/getting_started_cli/),
+[Python](https://dragonfly-opt.readthedocs.io/en/master/getting_started_py/),
+[Ask-Tell](https://dragonfly-opt.readthedocs.io/en/master/getting_started_ask_tell/))).
+&nbsp;
+### Contributors
+Kirthevasan Kandasamy: [github](https://github.com/kirthevasank),
+[webpage](http://www.cs.cmu.edu/~kkandasa/)  
+Karun Raju Vysyaraju: [github](https://github.com/karunraju),
+[linkedin](https://www.linkedin.com/in/karunrajuvysyaraju)  
+Anthony Yu: [github](https://github.com/anthonyhsyu),
+[linkedin](https://www.linkedin.com/in/anthony-yu-5239a877/)  
+Willie Neiswanger: [github](https://github.com/willieneis),
+[webpage](http://www.cs.cmu.edu/~wdn/)  
+Biswajit Paria: [github](https://github.com/biswajitsc),
+[webpage](https://biswajitsc.github.io/)  
+Chris Collins: [github](https://github.com/crcollins/),
+[webpage](https://www.crcollins.com/)  
+### Acknowledgements
+Research and development of the methods in this package were funded by
+DOE grant DESC0011114, NSF grant IIS1563887, the DARPA D3M program, and AFRL.
+### Citation
+If you use any part of this code in your work, please cite our
+[JMLR paper](http://jmlr.org/papers/v21/18-223.html).
+```
+@article{JMLR:v21:18-223,
+  author  = {Kirthevasan Kandasamy and Karun Raju Vysyaraju and Willie Neiswanger and Biswajit Paria and Christopher R. Collins and Jeff Schneider and Barnabas Poczos and Eric P. Xing},
+  title   = {Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly},
+  journal = {Journal of Machine Learning Research},
+  year    = {2020},
+  volume  = {21},
+  number  = {81},
+  pages   = {1-27},
+  url     = {http://jmlr.org/papers/v21/18-223.html}
+}
+```
+### License
+This software is released under the MIT license. For more details, please refer
+[LICENSE.txt](https://github.com/dragonfly/dragonfly/blob/master/LICENSE.txt).
+For questions, please email kandasamy@cs.cmu.edu.
+"Copyright 2018-2019 Kirthevasan Kandasamy"
+
+%package -n python3-dragonfly-opt
+Summary:	please add a summary manually as the author left a blank one
+Provides:	python-dragonfly-opt
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-dragonfly-opt
+Dragonfly is an open source python library for scalable Bayesian optimisation.
+Bayesian optimisation is used for optimising black-box functions whose evaluations are
+usually expensive. Beyond vanilla optimisation techniques, Dragonfly provides an array of tools to
+scale up Bayesian optimisation to expensive large scale problems.
+These include features/functionality that are especially suited for
+high dimensional optimisation (optimising for a large number of variables),
+parallel evaluations in synchronous or asynchronous settings (conducting multiple
+evaluations in parallel), multi-fidelity optimisation (using cheap approximations
+to speed up the optimisation process), and multi-objective optimisation (optimising
+multiple functions simultaneously).
+Dragonfly is compatible with Python2 (>= 2.7) and Python3 (>= 3.5) and has been tested
+on Linux, macOS, and Windows platforms.
+For documentation, installation, and a getting started guide, see our
+[readthedocs page](https://dragonfly-opt.readthedocs.io). For more details, see
+our [paper](https://arxiv.org/abs/1903.06694).
+&nbsp;
+## Installation
+See 
+[here](https://dragonfly-opt.readthedocs.io/en/master/install/)
+for detailed instructions on installing Dragonfly and its dependencies.
+**Quick Installation:**
+If you have done this kind of thing before, you should be able to install
+Dragonfly via `pip`.
+```bash
+$ sudo apt-get install python-dev python3-dev gfortran # On Ubuntu/Debian
+$ pip install numpy
+$ pip install dragonfly-opt -v
+```
+**Testing the Installation**:
+You can import Dragonfly in python to test if it was installed properly.
+If you have installed via source, make sure that you move to a different directory 
+ to avoid naming conflicts.
+```bash
+$ python
+>>> from dragonfly import minimise_function
+>>> # The first argument below is the function, the second is the domain, and the third is the budget.
+>>> min_val, min_pt, history = minimise_function(lambda x: x ** 4 - x**2 + 0.1 * x, [[-10, 10]], 10);  
+>>> min_val, min_pt
+(-0.32122746026750953, array([-0.7129672]))
+```
+Due to stochasticity in the algorithms, the above values for `min_val`, `min_pt` may be
+different. If you run it for longer (e.g.
+`min_val, min_pt, history = minimise_function(lambda x: x ** 4 - x**2 + 0.1 * x, [[-10, 10]], 100)`),
+you should get more consistent values for the minimum. 
+If the installation fails or if there are warning messages, see detailed instructions
+[here](https://dragonfly-opt.readthedocs.io/en/master/install/).
+&nbsp;
+## Quick Start
+Dragonfly can be
+used directly in the command line by calling
+[`dragonfly-script.py`](bin/dragonfly-script.py)
+or be imported in python code via the `maximise_function` function in the main library
+or in <em>ask-tell</em> mode.
+To help get started, we have provided some examples in the
+[`examples`](examples) directory.
+See our readthedocs getting started pages
+([command line](https://dragonfly-opt.readthedocs.io/en/master/getting_started_cli/),
+[Python](https://dragonfly-opt.readthedocs.io/en/master/getting_started_py/),
+[Ask-Tell](https://dragonfly-opt.readthedocs.io/en/master/getting_started_ask_tell/))
+for examples and use cases.
+**Command line**:
+Below is an example usage in the command line.
+```bash
+$ cd examples
+$ dragonfly-script.py --config synthetic/branin/config.json --options options_files/options_example.txt
+```
+**In Python code**:
+The main APIs for Dragonfly are defined in
+[`dragonfly/apis`](dragonfly/apis).
+For their definitions and arguments, see
+[`dragonfly/apis/opt.py`](dragonfly/apis/opt.py) and
+[`dragonfly/apis/moo.py`](dragonfly/apis/moo.py).
+You can import the main API in python code via,
+```python
+from dragonfly import minimise_function, maximise_function
+func = lambda x: x ** 4 - x**2 + 0.1 * x
+domain = [[-10, 10]]
+max_capital = 100
+min_val, min_pt, history = minimise_function(func, domain, max_capital)
+print(min_val, min_pt)
+max_val, max_pt, history = maximise_function(lambda x: -func(x), domain, max_capital)
+print(max_val, max_pt)
+```
+Here, `func` is the function to be maximised,
+`domain` is the domain over which `func` is to be optimised,
+and `max_capital` is the capital available for optimisation.
+The domain can be specified via a JSON file or in code.
+See
+[here](examples/synthetic/branin/in_code_demo.py),
+[here](examples/synthetic/hartmann6_4/in_code_demo.py),
+[here](examples/synthetic/discrete_euc/in_code_demo_1.py),
+[here](examples/synthetic/discrete_euc/in_code_demo_2.py),
+[here](examples/synthetic/hartmann3_constrained/in_code_demo.py),
+[here](examples/synthetic/park1_constrained/in_code_demo.py),
+[here](examples/synthetic/borehole_constrained/in_code_demo.py),
+[here](examples/synthetic/multiobjective_branin_currinexp/in_code_demo.py),
+[here](examples/synthetic/multiobjective_hartmann/in_code_demo.py),
+[here](examples/tree_reg/in_code_demo.py),
+and
+[here](examples/nas/demo_nas.py)
+for more detailed examples.
+**In Ask-Tell Mode**:
+Ask-tell mode provides you more control over your experiments where you can supply past results
+to our API in order to obtain a recommendation.
+See the [following example](examples/detailed_use_cases/in_code_demo_ask_tell.py) for more details.
+For a comprehensive list of uses cases, including multi-objective optimisation,
+multi-fidelity optimisation, neural architecture search, and other optimisation
+methods (besides Bayesian optimisation), see our readthe docs pages
+([command line](https://dragonfly-opt.readthedocs.io/en/master/getting_started_cli/),
+[Python](https://dragonfly-opt.readthedocs.io/en/master/getting_started_py/),
+[Ask-Tell](https://dragonfly-opt.readthedocs.io/en/master/getting_started_ask_tell/))).
+&nbsp;
+### Contributors
+Kirthevasan Kandasamy: [github](https://github.com/kirthevasank),
+[webpage](http://www.cs.cmu.edu/~kkandasa/)  
+Karun Raju Vysyaraju: [github](https://github.com/karunraju),
+[linkedin](https://www.linkedin.com/in/karunrajuvysyaraju)  
+Anthony Yu: [github](https://github.com/anthonyhsyu),
+[linkedin](https://www.linkedin.com/in/anthony-yu-5239a877/)  
+Willie Neiswanger: [github](https://github.com/willieneis),
+[webpage](http://www.cs.cmu.edu/~wdn/)  
+Biswajit Paria: [github](https://github.com/biswajitsc),
+[webpage](https://biswajitsc.github.io/)  
+Chris Collins: [github](https://github.com/crcollins/),
+[webpage](https://www.crcollins.com/)  
+### Acknowledgements
+Research and development of the methods in this package were funded by
+DOE grant DESC0011114, NSF grant IIS1563887, the DARPA D3M program, and AFRL.
+### Citation
+If you use any part of this code in your work, please cite our
+[JMLR paper](http://jmlr.org/papers/v21/18-223.html).
+```
+@article{JMLR:v21:18-223,
+  author  = {Kirthevasan Kandasamy and Karun Raju Vysyaraju and Willie Neiswanger and Biswajit Paria and Christopher R. Collins and Jeff Schneider and Barnabas Poczos and Eric P. Xing},
+  title   = {Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly},
+  journal = {Journal of Machine Learning Research},
+  year    = {2020},
+  volume  = {21},
+  number  = {81},
+  pages   = {1-27},
+  url     = {http://jmlr.org/papers/v21/18-223.html}
+}
+```
+### License
+This software is released under the MIT license. For more details, please refer
+[LICENSE.txt](https://github.com/dragonfly/dragonfly/blob/master/LICENSE.txt).
+For questions, please email kandasamy@cs.cmu.edu.
+"Copyright 2018-2019 Kirthevasan Kandasamy"
+
+%package help
+Summary:	Development documents and examples for dragonfly-opt
+Provides:	python3-dragonfly-opt-doc
+%description help
+Dragonfly is an open source python library for scalable Bayesian optimisation.
+Bayesian optimisation is used for optimising black-box functions whose evaluations are
+usually expensive. Beyond vanilla optimisation techniques, Dragonfly provides an array of tools to
+scale up Bayesian optimisation to expensive large scale problems.
+These include features/functionality that are especially suited for
+high dimensional optimisation (optimising for a large number of variables),
+parallel evaluations in synchronous or asynchronous settings (conducting multiple
+evaluations in parallel), multi-fidelity optimisation (using cheap approximations
+to speed up the optimisation process), and multi-objective optimisation (optimising
+multiple functions simultaneously).
+Dragonfly is compatible with Python2 (>= 2.7) and Python3 (>= 3.5) and has been tested
+on Linux, macOS, and Windows platforms.
+For documentation, installation, and a getting started guide, see our
+[readthedocs page](https://dragonfly-opt.readthedocs.io). For more details, see
+our [paper](https://arxiv.org/abs/1903.06694).
+&nbsp;
+## Installation
+See 
+[here](https://dragonfly-opt.readthedocs.io/en/master/install/)
+for detailed instructions on installing Dragonfly and its dependencies.
+**Quick Installation:**
+If you have done this kind of thing before, you should be able to install
+Dragonfly via `pip`.
+```bash
+$ sudo apt-get install python-dev python3-dev gfortran # On Ubuntu/Debian
+$ pip install numpy
+$ pip install dragonfly-opt -v
+```
+**Testing the Installation**:
+You can import Dragonfly in python to test if it was installed properly.
+If you have installed via source, make sure that you move to a different directory 
+ to avoid naming conflicts.
+```bash
+$ python
+>>> from dragonfly import minimise_function
+>>> # The first argument below is the function, the second is the domain, and the third is the budget.
+>>> min_val, min_pt, history = minimise_function(lambda x: x ** 4 - x**2 + 0.1 * x, [[-10, 10]], 10);  
+>>> min_val, min_pt
+(-0.32122746026750953, array([-0.7129672]))
+```
+Due to stochasticity in the algorithms, the above values for `min_val`, `min_pt` may be
+different. If you run it for longer (e.g.
+`min_val, min_pt, history = minimise_function(lambda x: x ** 4 - x**2 + 0.1 * x, [[-10, 10]], 100)`),
+you should get more consistent values for the minimum. 
+If the installation fails or if there are warning messages, see detailed instructions
+[here](https://dragonfly-opt.readthedocs.io/en/master/install/).
+&nbsp;
+## Quick Start
+Dragonfly can be
+used directly in the command line by calling
+[`dragonfly-script.py`](bin/dragonfly-script.py)
+or be imported in python code via the `maximise_function` function in the main library
+or in <em>ask-tell</em> mode.
+To help get started, we have provided some examples in the
+[`examples`](examples) directory.
+See our readthedocs getting started pages
+([command line](https://dragonfly-opt.readthedocs.io/en/master/getting_started_cli/),
+[Python](https://dragonfly-opt.readthedocs.io/en/master/getting_started_py/),
+[Ask-Tell](https://dragonfly-opt.readthedocs.io/en/master/getting_started_ask_tell/))
+for examples and use cases.
+**Command line**:
+Below is an example usage in the command line.
+```bash
+$ cd examples
+$ dragonfly-script.py --config synthetic/branin/config.json --options options_files/options_example.txt
+```
+**In Python code**:
+The main APIs for Dragonfly are defined in
+[`dragonfly/apis`](dragonfly/apis).
+For their definitions and arguments, see
+[`dragonfly/apis/opt.py`](dragonfly/apis/opt.py) and
+[`dragonfly/apis/moo.py`](dragonfly/apis/moo.py).
+You can import the main API in python code via,
+```python
+from dragonfly import minimise_function, maximise_function
+func = lambda x: x ** 4 - x**2 + 0.1 * x
+domain = [[-10, 10]]
+max_capital = 100
+min_val, min_pt, history = minimise_function(func, domain, max_capital)
+print(min_val, min_pt)
+max_val, max_pt, history = maximise_function(lambda x: -func(x), domain, max_capital)
+print(max_val, max_pt)
+```
+Here, `func` is the function to be maximised,
+`domain` is the domain over which `func` is to be optimised,
+and `max_capital` is the capital available for optimisation.
+The domain can be specified via a JSON file or in code.
+See
+[here](examples/synthetic/branin/in_code_demo.py),
+[here](examples/synthetic/hartmann6_4/in_code_demo.py),
+[here](examples/synthetic/discrete_euc/in_code_demo_1.py),
+[here](examples/synthetic/discrete_euc/in_code_demo_2.py),
+[here](examples/synthetic/hartmann3_constrained/in_code_demo.py),
+[here](examples/synthetic/park1_constrained/in_code_demo.py),
+[here](examples/synthetic/borehole_constrained/in_code_demo.py),
+[here](examples/synthetic/multiobjective_branin_currinexp/in_code_demo.py),
+[here](examples/synthetic/multiobjective_hartmann/in_code_demo.py),
+[here](examples/tree_reg/in_code_demo.py),
+and
+[here](examples/nas/demo_nas.py)
+for more detailed examples.
+**In Ask-Tell Mode**:
+Ask-tell mode provides you more control over your experiments where you can supply past results
+to our API in order to obtain a recommendation.
+See the [following example](examples/detailed_use_cases/in_code_demo_ask_tell.py) for more details.
+For a comprehensive list of uses cases, including multi-objective optimisation,
+multi-fidelity optimisation, neural architecture search, and other optimisation
+methods (besides Bayesian optimisation), see our readthe docs pages
+([command line](https://dragonfly-opt.readthedocs.io/en/master/getting_started_cli/),
+[Python](https://dragonfly-opt.readthedocs.io/en/master/getting_started_py/),
+[Ask-Tell](https://dragonfly-opt.readthedocs.io/en/master/getting_started_ask_tell/))).
+&nbsp;
+### Contributors
+Kirthevasan Kandasamy: [github](https://github.com/kirthevasank),
+[webpage](http://www.cs.cmu.edu/~kkandasa/)  
+Karun Raju Vysyaraju: [github](https://github.com/karunraju),
+[linkedin](https://www.linkedin.com/in/karunrajuvysyaraju)  
+Anthony Yu: [github](https://github.com/anthonyhsyu),
+[linkedin](https://www.linkedin.com/in/anthony-yu-5239a877/)  
+Willie Neiswanger: [github](https://github.com/willieneis),
+[webpage](http://www.cs.cmu.edu/~wdn/)  
+Biswajit Paria: [github](https://github.com/biswajitsc),
+[webpage](https://biswajitsc.github.io/)  
+Chris Collins: [github](https://github.com/crcollins/),
+[webpage](https://www.crcollins.com/)  
+### Acknowledgements
+Research and development of the methods in this package were funded by
+DOE grant DESC0011114, NSF grant IIS1563887, the DARPA D3M program, and AFRL.
+### Citation
+If you use any part of this code in your work, please cite our
+[JMLR paper](http://jmlr.org/papers/v21/18-223.html).
+```
+@article{JMLR:v21:18-223,
+  author  = {Kirthevasan Kandasamy and Karun Raju Vysyaraju and Willie Neiswanger and Biswajit Paria and Christopher R. Collins and Jeff Schneider and Barnabas Poczos and Eric P. Xing},
+  title   = {Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly},
+  journal = {Journal of Machine Learning Research},
+  year    = {2020},
+  volume  = {21},
+  number  = {81},
+  pages   = {1-27},
+  url     = {http://jmlr.org/papers/v21/18-223.html}
+}
+```
+### License
+This software is released under the MIT license. For more details, please refer
+[LICENSE.txt](https://github.com/dragonfly/dragonfly/blob/master/LICENSE.txt).
+For questions, please email kandasamy@cs.cmu.edu.
+"Copyright 2018-2019 Kirthevasan Kandasamy"
+
+%prep
+%autosetup -n dragonfly-opt-0.1.7
+
+%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-dragonfly-opt -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.7-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..8a0cdb5
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+dea90014fa2d2ab33aea13f70a8410fe  dragonfly-opt-0.1.7.tar.gz