automatic import of python-spark-nlp-display

3 files changed, 574 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
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+/spark-nlp-display-4.4.tar.gz
diff --git a/python-spark-nlp-display.spec b/python-spark-nlp-display.spec
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+%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
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](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)
+```
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
+
+### 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)
+                       )
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/dp_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/er_viz.png)
+
+#### 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)
+               )
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/re_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/assertion_viz.png)
+
+
+
+
+%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
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](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)
+```
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
+
+### 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)
+                       )
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/dp_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/er_viz.png)
+
+#### 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)
+               )
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/re_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/assertion_viz.png)
+
+
+
+
+%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
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](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)
+```
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
+
+### 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)
+                       )
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/dp_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/er_viz.png)
+
+#### 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)
+               )
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/re_viz.png)
+
+#### 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
+
+```
+
+![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/assertion_viz.png)
+
+
+
+
+%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
diff --git a/sources b/sources
new file mode 100644
index 0000000..df8ee02
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+9461edfc79bf179903daf8fdcdbfcaa6  spark-nlp-display-4.4.tar.gz