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diff --git a/python-dpu-utils.spec b/python-dpu-utils.spec new file mode 100644 index 0000000..8048b95 --- /dev/null +++ b/python-dpu-utils.spec @@ -0,0 +1,498 @@ +%global _empty_manifest_terminate_build 0 +Name: python-dpu-utils +Version: 0.6.1 +Release: 1 +Summary: Python utilities used by Deep Procedural Intelligence +License: MIT +URL: https://github.com/microsoft/dpu-utils +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/1d/6b/0507dd6dbf64d015e67d27b6191cd1239c89639efeca8165099ac39d4450/dpu_utils-0.6.1.tar.gz +BuildArch: noarch + +Requires: python3-azure-storage-blob +Requires: python3-azure-identity +Requires: python3-numpy +Requires: python3-docopt +Requires: python3-tqdm +Requires: python3-SetSimilaritySearch +Requires: python3-sentencepiece +Requires: python3-cffi +Requires: python3-regex + +%description +# DPU Utilities  +[](https://deepproceduralintelligence.visualstudio.com/dpu-utils/_build/latest?definitionId=3) + + +This contains a set of utilities used across projects of the [DPU team](https://www.microsoft.com/en-us/research/project/program/). + +## Python + +Stored in the `python` subdirectory, published as the `dpu-utils` package. + +### Installation + +```bash +pip install dpu-utils +``` +OR via the community-maintained Conda recipe: +```bash +conda install -c conda-forge dpu-utils +``` + +### Overview +Below you can find an overview of the utilities included. Detailed documentation +is provided at the docstring of each class. + +##### Generic Utilities `dpu_utils.utils` +* [`ChunkWriter`](python/dpu_utils/utils/chunkwriter.py) provides a convenient API for writing output in multiple parts (chunks). +* [`RichPath`](python/dpu_utils/utils/richpath.py) an API that abstract local and Azure Blob paths in your code. +* [`*Iterator`](python/dpu_utils/utils/iterators.py) Wrappers that can parallelize and shuffle iterators. +* [`{load,save}_json[l]_gz`](python/dpu_utils/utils/dataloading.py) convenience API for loading and writing `.json[l].gz` files. +* [`git_tag_run`](python/dpu_utils/utils/gitlog.py) tags the current working directory git the state of the code. +* [`run_and_debug`](python/dpu_utils/utils/debughelper.py) when an exception happens, start a debug session. Usually a wrapper of `__main__`. + +##### General Machine Learning Utilities `dpu_utils.mlutils` +* [`Vocabulary`](python/dpu_utils/mlutils/vocabulary.py) map elements into unique integer ids and back. + Commonly used in machine learning models that work over discrete data (e.g. + words in NLP). Contains methods for converting an list of tokens into their + "tensorized" for of integer ids. +* [`BpeVocabulary`](python/dpu_utils/mlutils/bpevocabulary.py) a vocabulary for machine learning models that employs BPE (via `sentencepiece`). +* [`CharTensorizer`](python/dpu_utils/mlutils/chartensorizer.py) convert character sequences into into tensors, commonly used + in machine learning models whose input is a list of characters. + +##### Code-related Utilities `dpu_utils.codeutils` +* [`split_identifier_into_parts()`](python/dpu_utils/codeutils/identifiersplitting.py) split identifiers into subtokens on CamelCase and snake_case. +* [`Lattice`](python/dpu_utils/codeutils/lattice/lattice.py), [`CSharpLattice`](python/dpu_utils/codeutils/lattice/csharplattice.py) represent lattices and useful operations on lattices in Python. +* [`get_language_keywords()`](python/dpu_utils/codeutils/keywords/keywordlist.py) an API to retrieve the keyword tokens for many programming languages. +* [`language_candidates_from_suffix()`](python/dpu_utils/codeutils/filesuffix.py) a function to retrieve the candidate language given the file suffix. +* [`deduplication.DuplicateDetector`](python/dpu_utils/codeutils/deduplication/deduplication.py) API to detects (near)duplicates in codebases. +See also [here](#approximate-duplicate-code-detection) for a command line tool. +* [`treesitter.parser_for`](python/dpu_utils/codeutils/treesitter/parser.py) get [Tree-sitter](https://tree-sitter.github.io/tree-sitter/) parser by language name. + +##### TensorFlow 1.x Utilities `dpu_utils.tfutils` +* [`get_activation`](python/dpu_utils/tfutils/activation.py) retrieve activations function by name. +* [`GradRatioLoggingOptimizer`](python/dpu_utils/tfutils/gradratiologgingoptimizer.py) a wrapper around optimizers that logs the ratios of grad norms to parameter norms. +* [`TFVariableSaver`](python/dpu_utils/tfutils/tfvariablesaver.py) save TF variables in an object that can be pickled. + +Unsorted segment operations following TensorFlow's [`unsorted_segment_sum`](https://www.tensorflow.org/api_docs/python/tf/math/unsorted_segment_sum) operations: +* [`unsorted_segment_logsumexp`](python/dpu_utils/tfutils/unsortedsegmentops.py) +* [`unsorted_segment_log_softmax`](python/dpu_utils/tfutils/unsortedsegmentops.py) +* [`unsorted_segment_softmax`](python/dpu_utils/tfutils/unsortedsegmentops.py) + +##### TensorFlow 2.x Utilities `dpu_utils.tf2utils` +* [`get_activation_function_by_name`](python/dpu_utils/tf2utils/activation.py) retrieve activation functions by name. +* [`gelu`](python/dpu_utils/tf2utils/activation.py) The GeLU activation function. +* [`MLP`](python/dpu_utils/tf2utils/mlp.py) An MLP layer. + +Unsorted segment operations following TensorFlow's [`unsorted_segment_sum`](https://www.tensorflow.org/api_docs/python/tf/math/unsorted_segment_sum) operations: +* [`unsorted_segment_logsumexp`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) +* [`unsorted_segment_log_softmax`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) +* [`unsorted_segment_softmax`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) + + +##### TensorFlow Models `dpu_utils.tfmodels` +* [`SparseGGNN`](python/dpu_utils/tfmodels/sparsegnn.py) a sparse GGNN implementation. +* [`AsyncGGNN`](python/dpu_utils/tfmodels/asyncgnn.py) an asynchronous GGNN implementation. + +These models have not been tested with TF 2.0. + +##### PyTorch Utilities `dpu_utils.ptutils` +* [`BaseComponent`](python/dpu_utils/ptutils/basecomponent.py) a wrapper abstract class around `nn.Module` that + takes care of essential elements of most neural network components. +* [`ComponentTrainer`](python/dpu_utils/ptutils/basecomponent.py) a training loop for `BaseComponent`s. + + +### Command-line tools + +#### Approximate Duplicate Code Detection +You can use the `deduplicationcli` command to detect duplicates in pre-processed source code, by invoking +```bash +deduplicationcli DATA_PATH OUT_JSON +``` +where `DATA_PATH` is a file containing tokenized `.jsonl.gz` files and `OUT_JSON` is the target output file. +For more options look at `--help`. + +An exact (but usually slower) version of this can be found [here](https://github.com/Microsoft/near-duplicate-code-detector) +along with code to tokenize Java, C#, Python and JavaScript into the relevant formats. + +### Tests + +#### Run the unit tests + +```bash +python setup.py test +``` + +#### Generate code coverage reports + +```bash +# pip install coverage +coverage run --source dpu_utils/ setup.py test && \ + coverage html +``` + +The resulting HTML file will be in `htmlcov/index.html`. + +## .NET + +Stored in the `dotnet` subdirectory. + +Generic Utilities: +* `Microsoft.Research.DPU.Utils.RichPath`: a convenient way of using both paths and Azure paths in your code. + +Code-related Utilities: +* `Microsoft.Research.DPU.CSharpSourceGraphExtraction`: infrastructure to extract Program Graphs from C# projects. + +# Contributing + +This project welcomes contributions and suggestions. Most contributions require you to agree to a +Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us +the rights to use your contribution. For details, visit https://cla.microsoft.com. + +When you submit a pull request, a CLA-bot will automatically determine whether you need to provide +a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions +provided by the bot. You will only need to do this once across all repos using our CLA. + +This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). +For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or +contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. + + + + +%package -n python3-dpu-utils +Summary: Python utilities used by Deep Procedural Intelligence +Provides: python-dpu-utils +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-dpu-utils +# DPU Utilities  +[](https://deepproceduralintelligence.visualstudio.com/dpu-utils/_build/latest?definitionId=3) + + +This contains a set of utilities used across projects of the [DPU team](https://www.microsoft.com/en-us/research/project/program/). + +## Python + +Stored in the `python` subdirectory, published as the `dpu-utils` package. + +### Installation + +```bash +pip install dpu-utils +``` +OR via the community-maintained Conda recipe: +```bash +conda install -c conda-forge dpu-utils +``` + +### Overview +Below you can find an overview of the utilities included. Detailed documentation +is provided at the docstring of each class. + +##### Generic Utilities `dpu_utils.utils` +* [`ChunkWriter`](python/dpu_utils/utils/chunkwriter.py) provides a convenient API for writing output in multiple parts (chunks). +* [`RichPath`](python/dpu_utils/utils/richpath.py) an API that abstract local and Azure Blob paths in your code. +* [`*Iterator`](python/dpu_utils/utils/iterators.py) Wrappers that can parallelize and shuffle iterators. +* [`{load,save}_json[l]_gz`](python/dpu_utils/utils/dataloading.py) convenience API for loading and writing `.json[l].gz` files. +* [`git_tag_run`](python/dpu_utils/utils/gitlog.py) tags the current working directory git the state of the code. +* [`run_and_debug`](python/dpu_utils/utils/debughelper.py) when an exception happens, start a debug session. Usually a wrapper of `__main__`. + +##### General Machine Learning Utilities `dpu_utils.mlutils` +* [`Vocabulary`](python/dpu_utils/mlutils/vocabulary.py) map elements into unique integer ids and back. + Commonly used in machine learning models that work over discrete data (e.g. + words in NLP). Contains methods for converting an list of tokens into their + "tensorized" for of integer ids. +* [`BpeVocabulary`](python/dpu_utils/mlutils/bpevocabulary.py) a vocabulary for machine learning models that employs BPE (via `sentencepiece`). +* [`CharTensorizer`](python/dpu_utils/mlutils/chartensorizer.py) convert character sequences into into tensors, commonly used + in machine learning models whose input is a list of characters. + +##### Code-related Utilities `dpu_utils.codeutils` +* [`split_identifier_into_parts()`](python/dpu_utils/codeutils/identifiersplitting.py) split identifiers into subtokens on CamelCase and snake_case. +* [`Lattice`](python/dpu_utils/codeutils/lattice/lattice.py), [`CSharpLattice`](python/dpu_utils/codeutils/lattice/csharplattice.py) represent lattices and useful operations on lattices in Python. +* [`get_language_keywords()`](python/dpu_utils/codeutils/keywords/keywordlist.py) an API to retrieve the keyword tokens for many programming languages. +* [`language_candidates_from_suffix()`](python/dpu_utils/codeutils/filesuffix.py) a function to retrieve the candidate language given the file suffix. +* [`deduplication.DuplicateDetector`](python/dpu_utils/codeutils/deduplication/deduplication.py) API to detects (near)duplicates in codebases. +See also [here](#approximate-duplicate-code-detection) for a command line tool. +* [`treesitter.parser_for`](python/dpu_utils/codeutils/treesitter/parser.py) get [Tree-sitter](https://tree-sitter.github.io/tree-sitter/) parser by language name. + +##### TensorFlow 1.x Utilities `dpu_utils.tfutils` +* [`get_activation`](python/dpu_utils/tfutils/activation.py) retrieve activations function by name. +* [`GradRatioLoggingOptimizer`](python/dpu_utils/tfutils/gradratiologgingoptimizer.py) a wrapper around optimizers that logs the ratios of grad norms to parameter norms. +* [`TFVariableSaver`](python/dpu_utils/tfutils/tfvariablesaver.py) save TF variables in an object that can be pickled. + +Unsorted segment operations following TensorFlow's [`unsorted_segment_sum`](https://www.tensorflow.org/api_docs/python/tf/math/unsorted_segment_sum) operations: +* [`unsorted_segment_logsumexp`](python/dpu_utils/tfutils/unsortedsegmentops.py) +* [`unsorted_segment_log_softmax`](python/dpu_utils/tfutils/unsortedsegmentops.py) +* [`unsorted_segment_softmax`](python/dpu_utils/tfutils/unsortedsegmentops.py) + +##### TensorFlow 2.x Utilities `dpu_utils.tf2utils` +* [`get_activation_function_by_name`](python/dpu_utils/tf2utils/activation.py) retrieve activation functions by name. +* [`gelu`](python/dpu_utils/tf2utils/activation.py) The GeLU activation function. +* [`MLP`](python/dpu_utils/tf2utils/mlp.py) An MLP layer. + +Unsorted segment operations following TensorFlow's [`unsorted_segment_sum`](https://www.tensorflow.org/api_docs/python/tf/math/unsorted_segment_sum) operations: +* [`unsorted_segment_logsumexp`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) +* [`unsorted_segment_log_softmax`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) +* [`unsorted_segment_softmax`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) + + +##### TensorFlow Models `dpu_utils.tfmodels` +* [`SparseGGNN`](python/dpu_utils/tfmodels/sparsegnn.py) a sparse GGNN implementation. +* [`AsyncGGNN`](python/dpu_utils/tfmodels/asyncgnn.py) an asynchronous GGNN implementation. + +These models have not been tested with TF 2.0. + +##### PyTorch Utilities `dpu_utils.ptutils` +* [`BaseComponent`](python/dpu_utils/ptutils/basecomponent.py) a wrapper abstract class around `nn.Module` that + takes care of essential elements of most neural network components. +* [`ComponentTrainer`](python/dpu_utils/ptutils/basecomponent.py) a training loop for `BaseComponent`s. + + +### Command-line tools + +#### Approximate Duplicate Code Detection +You can use the `deduplicationcli` command to detect duplicates in pre-processed source code, by invoking +```bash +deduplicationcli DATA_PATH OUT_JSON +``` +where `DATA_PATH` is a file containing tokenized `.jsonl.gz` files and `OUT_JSON` is the target output file. +For more options look at `--help`. + +An exact (but usually slower) version of this can be found [here](https://github.com/Microsoft/near-duplicate-code-detector) +along with code to tokenize Java, C#, Python and JavaScript into the relevant formats. + +### Tests + +#### Run the unit tests + +```bash +python setup.py test +``` + +#### Generate code coverage reports + +```bash +# pip install coverage +coverage run --source dpu_utils/ setup.py test && \ + coverage html +``` + +The resulting HTML file will be in `htmlcov/index.html`. + +## .NET + +Stored in the `dotnet` subdirectory. + +Generic Utilities: +* `Microsoft.Research.DPU.Utils.RichPath`: a convenient way of using both paths and Azure paths in your code. + +Code-related Utilities: +* `Microsoft.Research.DPU.CSharpSourceGraphExtraction`: infrastructure to extract Program Graphs from C# projects. + +# Contributing + +This project welcomes contributions and suggestions. Most contributions require you to agree to a +Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us +the rights to use your contribution. For details, visit https://cla.microsoft.com. + +When you submit a pull request, a CLA-bot will automatically determine whether you need to provide +a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions +provided by the bot. You will only need to do this once across all repos using our CLA. + +This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). +For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or +contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. + + + + +%package help +Summary: Development documents and examples for dpu-utils +Provides: python3-dpu-utils-doc +%description help +# DPU Utilities  +[](https://deepproceduralintelligence.visualstudio.com/dpu-utils/_build/latest?definitionId=3) + + +This contains a set of utilities used across projects of the [DPU team](https://www.microsoft.com/en-us/research/project/program/). + +## Python + +Stored in the `python` subdirectory, published as the `dpu-utils` package. + +### Installation + +```bash +pip install dpu-utils +``` +OR via the community-maintained Conda recipe: +```bash +conda install -c conda-forge dpu-utils +``` + +### Overview +Below you can find an overview of the utilities included. Detailed documentation +is provided at the docstring of each class. + +##### Generic Utilities `dpu_utils.utils` +* [`ChunkWriter`](python/dpu_utils/utils/chunkwriter.py) provides a convenient API for writing output in multiple parts (chunks). +* [`RichPath`](python/dpu_utils/utils/richpath.py) an API that abstract local and Azure Blob paths in your code. +* [`*Iterator`](python/dpu_utils/utils/iterators.py) Wrappers that can parallelize and shuffle iterators. +* [`{load,save}_json[l]_gz`](python/dpu_utils/utils/dataloading.py) convenience API for loading and writing `.json[l].gz` files. +* [`git_tag_run`](python/dpu_utils/utils/gitlog.py) tags the current working directory git the state of the code. +* [`run_and_debug`](python/dpu_utils/utils/debughelper.py) when an exception happens, start a debug session. Usually a wrapper of `__main__`. + +##### General Machine Learning Utilities `dpu_utils.mlutils` +* [`Vocabulary`](python/dpu_utils/mlutils/vocabulary.py) map elements into unique integer ids and back. + Commonly used in machine learning models that work over discrete data (e.g. + words in NLP). Contains methods for converting an list of tokens into their + "tensorized" for of integer ids. +* [`BpeVocabulary`](python/dpu_utils/mlutils/bpevocabulary.py) a vocabulary for machine learning models that employs BPE (via `sentencepiece`). +* [`CharTensorizer`](python/dpu_utils/mlutils/chartensorizer.py) convert character sequences into into tensors, commonly used + in machine learning models whose input is a list of characters. + +##### Code-related Utilities `dpu_utils.codeutils` +* [`split_identifier_into_parts()`](python/dpu_utils/codeutils/identifiersplitting.py) split identifiers into subtokens on CamelCase and snake_case. +* [`Lattice`](python/dpu_utils/codeutils/lattice/lattice.py), [`CSharpLattice`](python/dpu_utils/codeutils/lattice/csharplattice.py) represent lattices and useful operations on lattices in Python. +* [`get_language_keywords()`](python/dpu_utils/codeutils/keywords/keywordlist.py) an API to retrieve the keyword tokens for many programming languages. +* [`language_candidates_from_suffix()`](python/dpu_utils/codeutils/filesuffix.py) a function to retrieve the candidate language given the file suffix. +* [`deduplication.DuplicateDetector`](python/dpu_utils/codeutils/deduplication/deduplication.py) API to detects (near)duplicates in codebases. +See also [here](#approximate-duplicate-code-detection) for a command line tool. +* [`treesitter.parser_for`](python/dpu_utils/codeutils/treesitter/parser.py) get [Tree-sitter](https://tree-sitter.github.io/tree-sitter/) parser by language name. + +##### TensorFlow 1.x Utilities `dpu_utils.tfutils` +* [`get_activation`](python/dpu_utils/tfutils/activation.py) retrieve activations function by name. +* [`GradRatioLoggingOptimizer`](python/dpu_utils/tfutils/gradratiologgingoptimizer.py) a wrapper around optimizers that logs the ratios of grad norms to parameter norms. +* [`TFVariableSaver`](python/dpu_utils/tfutils/tfvariablesaver.py) save TF variables in an object that can be pickled. + +Unsorted segment operations following TensorFlow's [`unsorted_segment_sum`](https://www.tensorflow.org/api_docs/python/tf/math/unsorted_segment_sum) operations: +* [`unsorted_segment_logsumexp`](python/dpu_utils/tfutils/unsortedsegmentops.py) +* [`unsorted_segment_log_softmax`](python/dpu_utils/tfutils/unsortedsegmentops.py) +* [`unsorted_segment_softmax`](python/dpu_utils/tfutils/unsortedsegmentops.py) + +##### TensorFlow 2.x Utilities `dpu_utils.tf2utils` +* [`get_activation_function_by_name`](python/dpu_utils/tf2utils/activation.py) retrieve activation functions by name. +* [`gelu`](python/dpu_utils/tf2utils/activation.py) The GeLU activation function. +* [`MLP`](python/dpu_utils/tf2utils/mlp.py) An MLP layer. + +Unsorted segment operations following TensorFlow's [`unsorted_segment_sum`](https://www.tensorflow.org/api_docs/python/tf/math/unsorted_segment_sum) operations: +* [`unsorted_segment_logsumexp`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) +* [`unsorted_segment_log_softmax`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) +* [`unsorted_segment_softmax`](python/dpu_utils/tf2utils/unsorted_segment_ops.py) + + +##### TensorFlow Models `dpu_utils.tfmodels` +* [`SparseGGNN`](python/dpu_utils/tfmodels/sparsegnn.py) a sparse GGNN implementation. +* [`AsyncGGNN`](python/dpu_utils/tfmodels/asyncgnn.py) an asynchronous GGNN implementation. + +These models have not been tested with TF 2.0. + +##### PyTorch Utilities `dpu_utils.ptutils` +* [`BaseComponent`](python/dpu_utils/ptutils/basecomponent.py) a wrapper abstract class around `nn.Module` that + takes care of essential elements of most neural network components. +* [`ComponentTrainer`](python/dpu_utils/ptutils/basecomponent.py) a training loop for `BaseComponent`s. + + +### Command-line tools + +#### Approximate Duplicate Code Detection +You can use the `deduplicationcli` command to detect duplicates in pre-processed source code, by invoking +```bash +deduplicationcli DATA_PATH OUT_JSON +``` +where `DATA_PATH` is a file containing tokenized `.jsonl.gz` files and `OUT_JSON` is the target output file. +For more options look at `--help`. + +An exact (but usually slower) version of this can be found [here](https://github.com/Microsoft/near-duplicate-code-detector) +along with code to tokenize Java, C#, Python and JavaScript into the relevant formats. + +### Tests + +#### Run the unit tests + +```bash +python setup.py test +``` + +#### Generate code coverage reports + +```bash +# pip install coverage +coverage run --source dpu_utils/ setup.py test && \ + coverage html +``` + +The resulting HTML file will be in `htmlcov/index.html`. + +## .NET + +Stored in the `dotnet` subdirectory. + +Generic Utilities: +* `Microsoft.Research.DPU.Utils.RichPath`: a convenient way of using both paths and Azure paths in your code. + +Code-related Utilities: +* `Microsoft.Research.DPU.CSharpSourceGraphExtraction`: infrastructure to extract Program Graphs from C# projects. + +# Contributing + +This project welcomes contributions and suggestions. Most contributions require you to agree to a +Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us +the rights to use your contribution. For details, visit https://cla.microsoft.com. + +When you submit a pull request, a CLA-bot will automatically determine whether you need to provide +a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions +provided by the bot. You will only need to do this once across all repos using our CLA. + +This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). +For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or +contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. + + + + +%prep +%autosetup -n dpu-utils-0.6.1 + +%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-dpu-utils -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.1-1 +- Package Spec generated |