1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
|
%global _empty_manifest_terminate_build 0
Name: python-commonroad-io
Version: 2023.1
Release: 1
Summary: Python tool to read, write, and visualize CommonRoad scenarios and solutions for automated vehicles.
License: BSD
URL: https://commonroad.in.tum.de
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/b6/8a/92e275aba2def65257c8bf485dc7e0477332773344417f5df13ebd104529/commonroad_io-2023.1.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-numpy
Requires: python3-numpy
Requires: python3-scipy
Requires: python3-scipy
Requires: python3-shapely
Requires: python3-matplotlib
Requires: python3-lxml
Requires: python3-networkx
Requires: python3-Pillow
Requires: python3-iso3166
Requires: python3-commonroad-vehicle-models
Requires: python3-rtree
Requires: python3-protobuf
Requires: python3-omegaconf
Requires: python3-tqdm
%description
# CommonRoad
[](https://svgshare.com/i/Zhy.svg)
[](https://svgshare.com/i/ZjP.svg)
[](https://svgshare.com/i/ZhY.svg)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](http://commonroad-io.readthedocs.io/?badge=latest)
Numerical experiments for motion planning of road vehicles require numerous ingredients: vehicle dynamics,
a road network, static obstacles, dynamic obstacles and their movement over time, goal regions, a cost function, etc.
Providing a description of the numerical experiment precise enough to reproduce it might require several pages of
information.
Thus, only key aspects are typically described in scientific publications, making it impossible to reproduce
results - yet, reproducibility is an important asset of good science.
Composable benchmarks for motion planning on roads (CommonRoad) are proposed so that numerical experiments are fully
defined by a unique ID; all required information to reconstruct the experiment can be found on [commonroad.in.tum.de](https://commonroad.in.tum.de/).
Each benchmark is composed of a [vehicle model](https://gitlab.lrz.de/tum-cps/commonroad-vehicle-models/blob/master/vehicleModels_commonRoad.pdf),
a [cost function](https://gitlab.lrz.de/tum-cps/commonroad-cost-functions/blob/master/costFunctions_commonRoad.pdf),
and a [scenario](https://commonroad.in.tum.de/scenarios/) (including goals and constraints).
The scenarios are partly recorded from real traffic and partly hand-crafted to create dangerous situations.
Solutions to the benchmarks can be uploaded and ranked on the CommonRoad Website.
Learn more about the scenario specification [here](https://gitlab.lrz.de/tum-cps/commonroad-scenarios/blob/master/documentation/XML_commonRoad_2020a.pdf).
# commonroad-io
The commonroad-io package provides methods to read, write, and visualize CommonRoad scenarios and planning problems. Furthermore, it can be used as a framework for implementing motion planning algorithms to solve CommonRoad Benchmarks and is the basis for other tools of the CommonRoad Framework.
With commonroad-io, those solutions can be written to xml-files for uploading them on [commonroad.in.tum.de](https://commonroad.in.tum.de/).
commonroad-io 2023.1 is compatible with CommonRoad scenarios in version 2020a and supports reading 2018b scenarios.
The software is written in Python and tested on Linux for the Python 3.7, 3.8, 3.9, 3.10, and 3.11.
## Documentation
The full documentation of the API and introducing examples can be found under [commonroad.in.tum.de](https://commonroad-io.readthedocs.io/en/latest/).
For getting started, we recommend our [tutorials](https://commonroad.in.tum.de/commonroad-io).
## Additional Tools
Based on commonroad-io, we have developed a list of tools supporting the development of motion-planning algorithms:
* [Drivability Checker](https://commonroad.in.tum.de/tools/drivability-checker)
* [CommonRoad-SUMO Interface](https://commonroad.in.tum.de/tools/sumo-interface)
* [Scenario Designer](https://commonroad.in.tum.de/tools/scenario-designer)
* [Vehicle Models](https://commonroad.in.tum.de/tools/model-cost-functions)
* [Dateset Converters](https://gitlab.lrz.de/tum-cps/dataset-converters)
* [Interactive Scenarios](https://gitlab.lrz.de/tum-cps/commonroad-interactive-scenarios)
* [Apollo Interface](https://gitlab.lrz.de/tum-cps/commonroad-apollo-interface)
## Requirements
The required dependencies for running commonroad-io are:
* numpy>=1.13
* scipy>=1.5.2
* shapely>=2.0.1
* matplotlib>=2.2.2
* lxml>=4.2.2
* networkx>=2.2
* Pillow>=7.0.0
* commonroad-vehicle-models>=2.0.0
* rtree>=0.8.3
* protobuf==3.20.1
## Installation
commonroad-io can be installed with::
pip install commonroad-io
Alternatively, clone from our gitlab repository::
git clone https://gitlab.lrz.de/tum-cps/commonroad_io.git
and add the folder commonroad-io to your Python environment.
## Changelog
Compared to version 2022.3, the following features have been added or changed:
### Added
- Support for shapely>=2.0.0
### Fixed
- Writing scenarios without location to protobuf
- Dashed lanelet boundaries with fixed dash position
- Default plot limits for focused obstacle
- Use dt from scenario as default for video creation
- Apply axis visible-option also for video creation
- Protobuf FileReader marking road network related IDs as used
- State attribute comparison
### Changed
- Name of SIDEWALK and BUSLANE traffic signs to PEDESTRIAN_SIDEWALK and BUS_LANE
- Packaging and dependency management using poetry
## Authors
Contribution (in alphabetic order by last name): Yannick Ballnath, Behtarin Ferdousi, Luis Gressenbuch, Moritz Klischat,
Markus Koschi, Sebastian Maierhofer, Stefanie Manzinger, Christina Miller, Christian Pek, Anna-Katharina Rettinger,
Simon Sagmeister, Moritz Untersperger, Murat Üste, Xiao Wang
## Credits
We gratefully acknowledge partial financial support by
* DFG (German Research Foundation) Priority Program SPP 1835 Cooperative Interacting Automobiles
* BMW Group within the Car@TUM project
* German Federal Ministry of Economics and Technology through the research initiative Ko-HAF
## Citation
**If you use our code for research, please consider to cite our paper:**
```
@inproceedings{Althoff2017a,
author = {Althoff, Matthias and Koschi, Markus and Manzinger, Stefanie},
title = {CommonRoad: Composable benchmarks for motion planning on roads},
booktitle = {Proc. of the IEEE Intelligent Vehicles Symposium},
year = {2017},
abstract = {Numerical experiments for motion planning of road vehicles require numerous components: vehicle
dynamics, a road network, static obstacles, dynamic obstacles and their movement over time, goal
regions, a cost function, etc. Providing a description of the numerical experiment precise enough to
reproduce it might require several pages of information. Thus, only key aspects are typically described
in scientific publications, making it impossible to reproduce results—yet, re- producibility is an
important asset of good science. Composable benchmarks for motion planning on roads (CommonRoad) are
proposed so that numerical experiments are fully defined by a unique ID; all information required to
reconstruct the experiment can be found on the CommonRoad website. Each benchmark is composed by a
vehicle model, a cost function, and a scenario (including goals and constraints). The scenarios are
partly recorded from real traffic and partly hand-crafted to create dangerous situations. We hope that
CommonRoad saves researchers time since one does not have to search for realistic parameters of vehicle
dynamics or realistic traffic situations, yet provides the freedom to compose a benchmark that fits
one’s needs.},
}
```
%package -n python3-commonroad-io
Summary: Python tool to read, write, and visualize CommonRoad scenarios and solutions for automated vehicles.
Provides: python-commonroad-io
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-commonroad-io
# CommonRoad
[](https://svgshare.com/i/Zhy.svg)
[](https://svgshare.com/i/ZjP.svg)
[](https://svgshare.com/i/ZhY.svg)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](http://commonroad-io.readthedocs.io/?badge=latest)
Numerical experiments for motion planning of road vehicles require numerous ingredients: vehicle dynamics,
a road network, static obstacles, dynamic obstacles and their movement over time, goal regions, a cost function, etc.
Providing a description of the numerical experiment precise enough to reproduce it might require several pages of
information.
Thus, only key aspects are typically described in scientific publications, making it impossible to reproduce
results - yet, reproducibility is an important asset of good science.
Composable benchmarks for motion planning on roads (CommonRoad) are proposed so that numerical experiments are fully
defined by a unique ID; all required information to reconstruct the experiment can be found on [commonroad.in.tum.de](https://commonroad.in.tum.de/).
Each benchmark is composed of a [vehicle model](https://gitlab.lrz.de/tum-cps/commonroad-vehicle-models/blob/master/vehicleModels_commonRoad.pdf),
a [cost function](https://gitlab.lrz.de/tum-cps/commonroad-cost-functions/blob/master/costFunctions_commonRoad.pdf),
and a [scenario](https://commonroad.in.tum.de/scenarios/) (including goals and constraints).
The scenarios are partly recorded from real traffic and partly hand-crafted to create dangerous situations.
Solutions to the benchmarks can be uploaded and ranked on the CommonRoad Website.
Learn more about the scenario specification [here](https://gitlab.lrz.de/tum-cps/commonroad-scenarios/blob/master/documentation/XML_commonRoad_2020a.pdf).
# commonroad-io
The commonroad-io package provides methods to read, write, and visualize CommonRoad scenarios and planning problems. Furthermore, it can be used as a framework for implementing motion planning algorithms to solve CommonRoad Benchmarks and is the basis for other tools of the CommonRoad Framework.
With commonroad-io, those solutions can be written to xml-files for uploading them on [commonroad.in.tum.de](https://commonroad.in.tum.de/).
commonroad-io 2023.1 is compatible with CommonRoad scenarios in version 2020a and supports reading 2018b scenarios.
The software is written in Python and tested on Linux for the Python 3.7, 3.8, 3.9, 3.10, and 3.11.
## Documentation
The full documentation of the API and introducing examples can be found under [commonroad.in.tum.de](https://commonroad-io.readthedocs.io/en/latest/).
For getting started, we recommend our [tutorials](https://commonroad.in.tum.de/commonroad-io).
## Additional Tools
Based on commonroad-io, we have developed a list of tools supporting the development of motion-planning algorithms:
* [Drivability Checker](https://commonroad.in.tum.de/tools/drivability-checker)
* [CommonRoad-SUMO Interface](https://commonroad.in.tum.de/tools/sumo-interface)
* [Scenario Designer](https://commonroad.in.tum.de/tools/scenario-designer)
* [Vehicle Models](https://commonroad.in.tum.de/tools/model-cost-functions)
* [Dateset Converters](https://gitlab.lrz.de/tum-cps/dataset-converters)
* [Interactive Scenarios](https://gitlab.lrz.de/tum-cps/commonroad-interactive-scenarios)
* [Apollo Interface](https://gitlab.lrz.de/tum-cps/commonroad-apollo-interface)
## Requirements
The required dependencies for running commonroad-io are:
* numpy>=1.13
* scipy>=1.5.2
* shapely>=2.0.1
* matplotlib>=2.2.2
* lxml>=4.2.2
* networkx>=2.2
* Pillow>=7.0.0
* commonroad-vehicle-models>=2.0.0
* rtree>=0.8.3
* protobuf==3.20.1
## Installation
commonroad-io can be installed with::
pip install commonroad-io
Alternatively, clone from our gitlab repository::
git clone https://gitlab.lrz.de/tum-cps/commonroad_io.git
and add the folder commonroad-io to your Python environment.
## Changelog
Compared to version 2022.3, the following features have been added or changed:
### Added
- Support for shapely>=2.0.0
### Fixed
- Writing scenarios without location to protobuf
- Dashed lanelet boundaries with fixed dash position
- Default plot limits for focused obstacle
- Use dt from scenario as default for video creation
- Apply axis visible-option also for video creation
- Protobuf FileReader marking road network related IDs as used
- State attribute comparison
### Changed
- Name of SIDEWALK and BUSLANE traffic signs to PEDESTRIAN_SIDEWALK and BUS_LANE
- Packaging and dependency management using poetry
## Authors
Contribution (in alphabetic order by last name): Yannick Ballnath, Behtarin Ferdousi, Luis Gressenbuch, Moritz Klischat,
Markus Koschi, Sebastian Maierhofer, Stefanie Manzinger, Christina Miller, Christian Pek, Anna-Katharina Rettinger,
Simon Sagmeister, Moritz Untersperger, Murat Üste, Xiao Wang
## Credits
We gratefully acknowledge partial financial support by
* DFG (German Research Foundation) Priority Program SPP 1835 Cooperative Interacting Automobiles
* BMW Group within the Car@TUM project
* German Federal Ministry of Economics and Technology through the research initiative Ko-HAF
## Citation
**If you use our code for research, please consider to cite our paper:**
```
@inproceedings{Althoff2017a,
author = {Althoff, Matthias and Koschi, Markus and Manzinger, Stefanie},
title = {CommonRoad: Composable benchmarks for motion planning on roads},
booktitle = {Proc. of the IEEE Intelligent Vehicles Symposium},
year = {2017},
abstract = {Numerical experiments for motion planning of road vehicles require numerous components: vehicle
dynamics, a road network, static obstacles, dynamic obstacles and their movement over time, goal
regions, a cost function, etc. Providing a description of the numerical experiment precise enough to
reproduce it might require several pages of information. Thus, only key aspects are typically described
in scientific publications, making it impossible to reproduce results—yet, re- producibility is an
important asset of good science. Composable benchmarks for motion planning on roads (CommonRoad) are
proposed so that numerical experiments are fully defined by a unique ID; all information required to
reconstruct the experiment can be found on the CommonRoad website. Each benchmark is composed by a
vehicle model, a cost function, and a scenario (including goals and constraints). The scenarios are
partly recorded from real traffic and partly hand-crafted to create dangerous situations. We hope that
CommonRoad saves researchers time since one does not have to search for realistic parameters of vehicle
dynamics or realistic traffic situations, yet provides the freedom to compose a benchmark that fits
one’s needs.},
}
```
%package help
Summary: Development documents and examples for commonroad-io
Provides: python3-commonroad-io-doc
%description help
# CommonRoad
[](https://svgshare.com/i/Zhy.svg)
[](https://svgshare.com/i/ZjP.svg)
[](https://svgshare.com/i/ZhY.svg)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](https://pypi.python.org/pypi/commonroad-io/)
[](http://commonroad-io.readthedocs.io/?badge=latest)
Numerical experiments for motion planning of road vehicles require numerous ingredients: vehicle dynamics,
a road network, static obstacles, dynamic obstacles and their movement over time, goal regions, a cost function, etc.
Providing a description of the numerical experiment precise enough to reproduce it might require several pages of
information.
Thus, only key aspects are typically described in scientific publications, making it impossible to reproduce
results - yet, reproducibility is an important asset of good science.
Composable benchmarks for motion planning on roads (CommonRoad) are proposed so that numerical experiments are fully
defined by a unique ID; all required information to reconstruct the experiment can be found on [commonroad.in.tum.de](https://commonroad.in.tum.de/).
Each benchmark is composed of a [vehicle model](https://gitlab.lrz.de/tum-cps/commonroad-vehicle-models/blob/master/vehicleModels_commonRoad.pdf),
a [cost function](https://gitlab.lrz.de/tum-cps/commonroad-cost-functions/blob/master/costFunctions_commonRoad.pdf),
and a [scenario](https://commonroad.in.tum.de/scenarios/) (including goals and constraints).
The scenarios are partly recorded from real traffic and partly hand-crafted to create dangerous situations.
Solutions to the benchmarks can be uploaded and ranked on the CommonRoad Website.
Learn more about the scenario specification [here](https://gitlab.lrz.de/tum-cps/commonroad-scenarios/blob/master/documentation/XML_commonRoad_2020a.pdf).
# commonroad-io
The commonroad-io package provides methods to read, write, and visualize CommonRoad scenarios and planning problems. Furthermore, it can be used as a framework for implementing motion planning algorithms to solve CommonRoad Benchmarks and is the basis for other tools of the CommonRoad Framework.
With commonroad-io, those solutions can be written to xml-files for uploading them on [commonroad.in.tum.de](https://commonroad.in.tum.de/).
commonroad-io 2023.1 is compatible with CommonRoad scenarios in version 2020a and supports reading 2018b scenarios.
The software is written in Python and tested on Linux for the Python 3.7, 3.8, 3.9, 3.10, and 3.11.
## Documentation
The full documentation of the API and introducing examples can be found under [commonroad.in.tum.de](https://commonroad-io.readthedocs.io/en/latest/).
For getting started, we recommend our [tutorials](https://commonroad.in.tum.de/commonroad-io).
## Additional Tools
Based on commonroad-io, we have developed a list of tools supporting the development of motion-planning algorithms:
* [Drivability Checker](https://commonroad.in.tum.de/tools/drivability-checker)
* [CommonRoad-SUMO Interface](https://commonroad.in.tum.de/tools/sumo-interface)
* [Scenario Designer](https://commonroad.in.tum.de/tools/scenario-designer)
* [Vehicle Models](https://commonroad.in.tum.de/tools/model-cost-functions)
* [Dateset Converters](https://gitlab.lrz.de/tum-cps/dataset-converters)
* [Interactive Scenarios](https://gitlab.lrz.de/tum-cps/commonroad-interactive-scenarios)
* [Apollo Interface](https://gitlab.lrz.de/tum-cps/commonroad-apollo-interface)
## Requirements
The required dependencies for running commonroad-io are:
* numpy>=1.13
* scipy>=1.5.2
* shapely>=2.0.1
* matplotlib>=2.2.2
* lxml>=4.2.2
* networkx>=2.2
* Pillow>=7.0.0
* commonroad-vehicle-models>=2.0.0
* rtree>=0.8.3
* protobuf==3.20.1
## Installation
commonroad-io can be installed with::
pip install commonroad-io
Alternatively, clone from our gitlab repository::
git clone https://gitlab.lrz.de/tum-cps/commonroad_io.git
and add the folder commonroad-io to your Python environment.
## Changelog
Compared to version 2022.3, the following features have been added or changed:
### Added
- Support for shapely>=2.0.0
### Fixed
- Writing scenarios without location to protobuf
- Dashed lanelet boundaries with fixed dash position
- Default plot limits for focused obstacle
- Use dt from scenario as default for video creation
- Apply axis visible-option also for video creation
- Protobuf FileReader marking road network related IDs as used
- State attribute comparison
### Changed
- Name of SIDEWALK and BUSLANE traffic signs to PEDESTRIAN_SIDEWALK and BUS_LANE
- Packaging and dependency management using poetry
## Authors
Contribution (in alphabetic order by last name): Yannick Ballnath, Behtarin Ferdousi, Luis Gressenbuch, Moritz Klischat,
Markus Koschi, Sebastian Maierhofer, Stefanie Manzinger, Christina Miller, Christian Pek, Anna-Katharina Rettinger,
Simon Sagmeister, Moritz Untersperger, Murat Üste, Xiao Wang
## Credits
We gratefully acknowledge partial financial support by
* DFG (German Research Foundation) Priority Program SPP 1835 Cooperative Interacting Automobiles
* BMW Group within the Car@TUM project
* German Federal Ministry of Economics and Technology through the research initiative Ko-HAF
## Citation
**If you use our code for research, please consider to cite our paper:**
```
@inproceedings{Althoff2017a,
author = {Althoff, Matthias and Koschi, Markus and Manzinger, Stefanie},
title = {CommonRoad: Composable benchmarks for motion planning on roads},
booktitle = {Proc. of the IEEE Intelligent Vehicles Symposium},
year = {2017},
abstract = {Numerical experiments for motion planning of road vehicles require numerous components: vehicle
dynamics, a road network, static obstacles, dynamic obstacles and their movement over time, goal
regions, a cost function, etc. Providing a description of the numerical experiment precise enough to
reproduce it might require several pages of information. Thus, only key aspects are typically described
in scientific publications, making it impossible to reproduce results—yet, re- producibility is an
important asset of good science. Composable benchmarks for motion planning on roads (CommonRoad) are
proposed so that numerical experiments are fully defined by a unique ID; all information required to
reconstruct the experiment can be found on the CommonRoad website. Each benchmark is composed by a
vehicle model, a cost function, and a scenario (including goals and constraints). The scenarios are
partly recorded from real traffic and partly hand-crafted to create dangerous situations. We hope that
CommonRoad saves researchers time since one does not have to search for realistic parameters of vehicle
dynamics or realistic traffic situations, yet provides the freedom to compose a benchmark that fits
one’s needs.},
}
```
%prep
%autosetup -n commonroad-io-2023.1
%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-commonroad-io -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 2023.1-1
- Package Spec generated
|
