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@@ -0,0 +1 @@ +/spark-nlp-display-4.4.tar.gz diff --git a/python-spark-nlp-display.spec b/python-spark-nlp-display.spec new file mode 100644 index 0000000..f9df297 --- /dev/null +++ b/python-spark-nlp-display.spec @@ -0,0 +1,572 @@ +%global _empty_manifest_terminate_build 0 +Name: python-spark-nlp-display +Version: 4.4 +Release: 1 +Summary: Visualization package for Spark NLP +License: Apache Software License +URL: http://nlp.johnsnowlabs.com +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/af/27/b84525e77152b17ae6d2d39a0cee975a1d9d57ba2f8ad210649238696b31/spark-nlp-display-4.4.tar.gz +BuildArch: noarch + +Requires: python3-spark-nlp +Requires: python3-ipython +Requires: python3-svgwrite +Requires: python3-pandas +Requires: python3-numpy + +%description +# spark-nlp-display +A library for the simple visualization of different types of Spark NLP annotations. + +## Supported Visualizations: +- Dependency Parser +- Named Entity Recognition +- Entity Resolution +- Relation Extraction +- Assertion Status + +## Complete Tutorial +[](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb) + +https://github.com/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb + +### Requirements +- spark-nlp +- ipython +- svgwrite +- pandas +- numpy + +### Installation +```bash +pip install spark-nlp-display +``` + +### How to use + +### Databricks +#### For all modules, pass in the additional parameter "return_html=True" in the display function and use Databrick's function displayHTML() to render visualization as explained below: +```python +from sparknlp_display import NerVisualizer + +ner_vis = NerVisualizer() + +## To set custom label colors: +ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes + +pipeline_result = ner_light_pipeline.fullAnnotate(text) ##light pipeline +#pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline + +vis_html = ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the entity column + document_col='document', #specify the document column (default: 'document') + labels=['PER'], #only allow these labels to be displayed. (default: [] - all labels will be displayed) + return_html=True) + +displayHTML(vis_html) +``` + + +### Jupyter + +To save the visualization as html, provide the export file path: `save_path='./export.html'` for each visualizer. + + +#### Dependency Parser +```python +from sparknlp_display import DependencyParserVisualizer + +dependency_vis = DependencyParserVisualizer() + +pipeline_result = dp_pipeline.fullAnnotate(text) +#pipeline_result = dp_full_pipeline.transform(df).collect()##full pipeline + +dependency_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe. + pos_col = 'pos', #specify the pos column + dependency_col = 'dependency', #specify the dependency column + dependency_type_col = 'dependency_type', #specify the dependency type column + save_path='./export.html' # optional - to save viz as html. (default: None) + ) +``` + + + +#### Named Entity Recognition + +```python +from sparknlp_display import NerVisualizer + +ner_vis = NerVisualizer() + +pipeline_result = ner_light_pipeline.fullAnnotate(text) +#pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline + +ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the entity column + document_col='document', #specify the document column (default: 'document') + labels=['PER'], #only allow these labels to be displayed. (default: [] - all labels will be displayed) + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes + +``` + + + +#### Entity Resolution + +```python +from sparknlp_display import EntityResolverVisualizer + +er_vis = EntityResolverVisualizer() + +pipeline_result = er_light_pipeline.fullAnnotate(text) + +er_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the ner result column + resolution_col = 'resolution', + document_col='document', #specify the document column (default: 'document') + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +er_vis.set_label_colors({'TREATMENT':'#800080', 'PROBLEM':'#77b5fe'}) #set label colors by specifying hex codes + +``` + + + +#### Relation Extraction +```python +from sparknlp_display import RelationExtractionVisualizer + +re_vis = RelationExtractionVisualizer() + +pipeline_result = re_light_pipeline.fullAnnotate(text) + +re_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + relation_col = 'relations', #specify relations column + document_col = 'document', #specify document column + show_relations=True, #display relation names on arrows (default: True) + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +``` + + + +#### Assertion Status +```python +from sparknlp_display import AssertionVisualizer + +assertion_vis = AssertionVisualizer() + +pipeline_result = ner_assertion_light_pipeline.fullAnnotate(text) + +assertion_vis.display(pipeline_result[0], + label_col = 'entities', #specify the ner result column + assertion_col = 'assertion', #specify assertion column + document_col = 'document', #specify the document column (default: 'document') + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +assertion_vis.set_label_colors({'TREATMENT':'#008080', 'problem':'#800080'}) #set label colors by specifying hex codes + +``` + + + + + + +%package -n python3-spark-nlp-display +Summary: Visualization package for Spark NLP +Provides: python-spark-nlp-display +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-spark-nlp-display +# spark-nlp-display +A library for the simple visualization of different types of Spark NLP annotations. + +## Supported Visualizations: +- Dependency Parser +- Named Entity Recognition +- Entity Resolution +- Relation Extraction +- Assertion Status + +## Complete Tutorial +[](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb) + +https://github.com/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb + +### Requirements +- spark-nlp +- ipython +- svgwrite +- pandas +- numpy + +### Installation +```bash +pip install spark-nlp-display +``` + +### How to use + +### Databricks +#### For all modules, pass in the additional parameter "return_html=True" in the display function and use Databrick's function displayHTML() to render visualization as explained below: +```python +from sparknlp_display import NerVisualizer + +ner_vis = NerVisualizer() + +## To set custom label colors: +ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes + +pipeline_result = ner_light_pipeline.fullAnnotate(text) ##light pipeline +#pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline + +vis_html = ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the entity column + document_col='document', #specify the document column (default: 'document') + labels=['PER'], #only allow these labels to be displayed. (default: [] - all labels will be displayed) + return_html=True) + +displayHTML(vis_html) +``` + + +### Jupyter + +To save the visualization as html, provide the export file path: `save_path='./export.html'` for each visualizer. + + +#### Dependency Parser +```python +from sparknlp_display import DependencyParserVisualizer + +dependency_vis = DependencyParserVisualizer() + +pipeline_result = dp_pipeline.fullAnnotate(text) +#pipeline_result = dp_full_pipeline.transform(df).collect()##full pipeline + +dependency_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe. + pos_col = 'pos', #specify the pos column + dependency_col = 'dependency', #specify the dependency column + dependency_type_col = 'dependency_type', #specify the dependency type column + save_path='./export.html' # optional - to save viz as html. (default: None) + ) +``` + + + +#### Named Entity Recognition + +```python +from sparknlp_display import NerVisualizer + +ner_vis = NerVisualizer() + +pipeline_result = ner_light_pipeline.fullAnnotate(text) +#pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline + +ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the entity column + document_col='document', #specify the document column (default: 'document') + labels=['PER'], #only allow these labels to be displayed. (default: [] - all labels will be displayed) + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes + +``` + + + +#### Entity Resolution + +```python +from sparknlp_display import EntityResolverVisualizer + +er_vis = EntityResolverVisualizer() + +pipeline_result = er_light_pipeline.fullAnnotate(text) + +er_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the ner result column + resolution_col = 'resolution', + document_col='document', #specify the document column (default: 'document') + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +er_vis.set_label_colors({'TREATMENT':'#800080', 'PROBLEM':'#77b5fe'}) #set label colors by specifying hex codes + +``` + + + +#### Relation Extraction +```python +from sparknlp_display import RelationExtractionVisualizer + +re_vis = RelationExtractionVisualizer() + +pipeline_result = re_light_pipeline.fullAnnotate(text) + +re_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + relation_col = 'relations', #specify relations column + document_col = 'document', #specify document column + show_relations=True, #display relation names on arrows (default: True) + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +``` + + + +#### Assertion Status +```python +from sparknlp_display import AssertionVisualizer + +assertion_vis = AssertionVisualizer() + +pipeline_result = ner_assertion_light_pipeline.fullAnnotate(text) + +assertion_vis.display(pipeline_result[0], + label_col = 'entities', #specify the ner result column + assertion_col = 'assertion', #specify assertion column + document_col = 'document', #specify the document column (default: 'document') + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +assertion_vis.set_label_colors({'TREATMENT':'#008080', 'problem':'#800080'}) #set label colors by specifying hex codes + +``` + + + + + + +%package help +Summary: Development documents and examples for spark-nlp-display +Provides: python3-spark-nlp-display-doc +%description help +# spark-nlp-display +A library for the simple visualization of different types of Spark NLP annotations. + +## Supported Visualizations: +- Dependency Parser +- Named Entity Recognition +- Entity Resolution +- Relation Extraction +- Assertion Status + +## Complete Tutorial +[](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb) + +https://github.com/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb + +### Requirements +- spark-nlp +- ipython +- svgwrite +- pandas +- numpy + +### Installation +```bash +pip install spark-nlp-display +``` + +### How to use + +### Databricks +#### For all modules, pass in the additional parameter "return_html=True" in the display function and use Databrick's function displayHTML() to render visualization as explained below: +```python +from sparknlp_display import NerVisualizer + +ner_vis = NerVisualizer() + +## To set custom label colors: +ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes + +pipeline_result = ner_light_pipeline.fullAnnotate(text) ##light pipeline +#pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline + +vis_html = ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the entity column + document_col='document', #specify the document column (default: 'document') + labels=['PER'], #only allow these labels to be displayed. (default: [] - all labels will be displayed) + return_html=True) + +displayHTML(vis_html) +``` + + +### Jupyter + +To save the visualization as html, provide the export file path: `save_path='./export.html'` for each visualizer. + + +#### Dependency Parser +```python +from sparknlp_display import DependencyParserVisualizer + +dependency_vis = DependencyParserVisualizer() + +pipeline_result = dp_pipeline.fullAnnotate(text) +#pipeline_result = dp_full_pipeline.transform(df).collect()##full pipeline + +dependency_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe. + pos_col = 'pos', #specify the pos column + dependency_col = 'dependency', #specify the dependency column + dependency_type_col = 'dependency_type', #specify the dependency type column + save_path='./export.html' # optional - to save viz as html. (default: None) + ) +``` + + + +#### Named Entity Recognition + +```python +from sparknlp_display import NerVisualizer + +ner_vis = NerVisualizer() + +pipeline_result = ner_light_pipeline.fullAnnotate(text) +#pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline + +ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the entity column + document_col='document', #specify the document column (default: 'document') + labels=['PER'], #only allow these labels to be displayed. (default: [] - all labels will be displayed) + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes + +``` + + + +#### Entity Resolution + +```python +from sparknlp_display import EntityResolverVisualizer + +er_vis = EntityResolverVisualizer() + +pipeline_result = er_light_pipeline.fullAnnotate(text) + +er_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + label_col='entities', #specify the ner result column + resolution_col = 'resolution', + document_col='document', #specify the document column (default: 'document') + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +er_vis.set_label_colors({'TREATMENT':'#800080', 'PROBLEM':'#77b5fe'}) #set label colors by specifying hex codes + +``` + + + +#### Relation Extraction +```python +from sparknlp_display import RelationExtractionVisualizer + +re_vis = RelationExtractionVisualizer() + +pipeline_result = re_light_pipeline.fullAnnotate(text) + +re_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe + relation_col = 'relations', #specify relations column + document_col = 'document', #specify document column + show_relations=True, #display relation names on arrows (default: True) + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +``` + + + +#### Assertion Status +```python +from sparknlp_display import AssertionVisualizer + +assertion_vis = AssertionVisualizer() + +pipeline_result = ner_assertion_light_pipeline.fullAnnotate(text) + +assertion_vis.display(pipeline_result[0], + label_col = 'entities', #specify the ner result column + assertion_col = 'assertion', #specify assertion column + document_col = 'document', #specify the document column (default: 'document') + save_path='./export.html' # optional - to save viz as html. (default: None) + ) + +## To set custom label colors: +assertion_vis.set_label_colors({'TREATMENT':'#008080', 'problem':'#800080'}) #set label colors by specifying hex codes + +``` + + + + + + +%prep +%autosetup -n spark-nlp-display-4.4 + +%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-spark-nlp-display -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 4.4-1 +- Package Spec generated @@ -0,0 +1 @@ +9461edfc79bf179903daf8fdcdbfcaa6 spark-nlp-display-4.4.tar.gz |