automatic import of python-pelion-sagemaker-controller

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+/pelion_sagemaker_controller-0.1.5.tar.gz
diff --git a/python-pelion-sagemaker-controller.spec b/python-pelion-sagemaker-controller.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-pelion-sagemaker-controller
+Version:	0.1.5
+Release:	1
+Summary:	AWS Sagemaker Controller notebook/client API for Pelion Edge Gateways
+License:	Apache 2.0
+URL:		https://github.com/DougAnsonAtARM/pelion-sagemaker-controller
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/37/b7/e7f554f6e282b0eb7327244c743cbd5c4a5583ced17bf4b89ae4b366d913/pelion_sagemaker_controller-0.1.5.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-requests
+Requires:	python3-uuid
+
+%description
+## Sagemaker Edge Agent Controller client API for Pelion Edge 
+
+#### PyPi:  [https://pypi.org/project/pelion\_sagemaker\_controller/](https://pypi.org/project/pelion\_sagemaker\_controller/)
+
+This python package simplifies the Data Scientist's job of accessing, via a Sagemaker Jupyter Notebook, the Sagemaker Edge Agent running on their Pelion Edge enabled gateway.
+
+### Controller API Instance Creation
+
+To create an instance of this API:
+	
+	# Required import
+	from pelion_sagemaker_controller import pelion_sagemaker_controller
+	
+	#
+	# Invoke constructor with Pelion API Key, Pelion GW Device ID
+	# You can also optionally specify the Pelion API endpoint you want to use
+	#
+	api = pelion_sagemaker_controller.ControllerAPI(
+			api_key='<ak_xxxx>', 
+			device_id='<pelion_gw_device_id>', 
+			api_endpoint='api.us-east-1.mbedcloud.com'
+			)
+		
+		
+### Supported Commands
+
+The following commands are supported by this API:
+
+#### Get Configuration
+
+	api.pelion_get_config()
+	
+	This call returns a JSON with the current Edge Device representing the 
+	Sagemaker service's configuration
+	
+#### Set Configuration
+
+	api.pelion_set_config({'foo':'bar'})
+	
+	This call updates or adds key/values to the current Edge Device's configuration
+	
+#### List Models
+
+	api.pelion_list_models()
+	
+	This call returns a JSON outlining all of the loaded models
+	
+#### Load Model
+
+	api.pelion_load_model('model-name','compiled-model-x.y.tar.gz')
+	
+	This call loads up the requested Sagemaker-compiled model whose compiled 
+	contents are located within the S3 bucket defined in the configuration
+	and utilized by the Sagemaker service
+	
+#### Unload Model
+
+	api.pelion_unload_model('model-name')
+	
+	This call unloads the loaded model referenced by the name 'model-name'
+	
+#### Reload Model
+
+	api.pelion_reload_model('model-name','compiled-model-x.y.tar.gz')
+	
+	This call is a convenience method for simply performing an "unload" followed by
+	a "load" of a given model using the methods above. 
+	
+#### Predict
+
+	api.pelion_predict(
+	          'model-name',
+	          's3:///input.data', 
+	          's3:///prediction_result.data'
+	          )
+	
+	This call invokes the model prediction using the specified input.data file that is
+	configured to be pulled from the Sagemaker S3 bucket (per configuration). The output
+	result from the prediction will be stored in a file that will be saved to the same
+	directory in the S3 bucket. 
+	
+	In addition to S3 bucket support, you can locally reference input/output requirements
+	using the "file:///" protocol - in this case the Sagemaker Edge Agent working directory
+	on the Pelion Edge Gateway will contain the specified files. 
+	
+#### Last Command Result
+
+	api.pelion_last_cmd_result()
+	
+	This call returns the last invocation/call results. In cases where predictions take
+	a long time to complete, this call may be used in a polling situation to determine
+	when the prediction operation has completed. 
+
+
+
+
+
+%package -n python3-pelion-sagemaker-controller
+Summary:	AWS Sagemaker Controller notebook/client API for Pelion Edge Gateways
+Provides:	python-pelion-sagemaker-controller
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-pelion-sagemaker-controller
+## Sagemaker Edge Agent Controller client API for Pelion Edge 
+
+#### PyPi:  [https://pypi.org/project/pelion\_sagemaker\_controller/](https://pypi.org/project/pelion\_sagemaker\_controller/)
+
+This python package simplifies the Data Scientist's job of accessing, via a Sagemaker Jupyter Notebook, the Sagemaker Edge Agent running on their Pelion Edge enabled gateway.
+
+### Controller API Instance Creation
+
+To create an instance of this API:
+	
+	# Required import
+	from pelion_sagemaker_controller import pelion_sagemaker_controller
+	
+	#
+	# Invoke constructor with Pelion API Key, Pelion GW Device ID
+	# You can also optionally specify the Pelion API endpoint you want to use
+	#
+	api = pelion_sagemaker_controller.ControllerAPI(
+			api_key='<ak_xxxx>', 
+			device_id='<pelion_gw_device_id>', 
+			api_endpoint='api.us-east-1.mbedcloud.com'
+			)
+		
+		
+### Supported Commands
+
+The following commands are supported by this API:
+
+#### Get Configuration
+
+	api.pelion_get_config()
+	
+	This call returns a JSON with the current Edge Device representing the 
+	Sagemaker service's configuration
+	
+#### Set Configuration
+
+	api.pelion_set_config({'foo':'bar'})
+	
+	This call updates or adds key/values to the current Edge Device's configuration
+	
+#### List Models
+
+	api.pelion_list_models()
+	
+	This call returns a JSON outlining all of the loaded models
+	
+#### Load Model
+
+	api.pelion_load_model('model-name','compiled-model-x.y.tar.gz')
+	
+	This call loads up the requested Sagemaker-compiled model whose compiled 
+	contents are located within the S3 bucket defined in the configuration
+	and utilized by the Sagemaker service
+	
+#### Unload Model
+
+	api.pelion_unload_model('model-name')
+	
+	This call unloads the loaded model referenced by the name 'model-name'
+	
+#### Reload Model
+
+	api.pelion_reload_model('model-name','compiled-model-x.y.tar.gz')
+	
+	This call is a convenience method for simply performing an "unload" followed by
+	a "load" of a given model using the methods above. 
+	
+#### Predict
+
+	api.pelion_predict(
+	          'model-name',
+	          's3:///input.data', 
+	          's3:///prediction_result.data'
+	          )
+	
+	This call invokes the model prediction using the specified input.data file that is
+	configured to be pulled from the Sagemaker S3 bucket (per configuration). The output
+	result from the prediction will be stored in a file that will be saved to the same
+	directory in the S3 bucket. 
+	
+	In addition to S3 bucket support, you can locally reference input/output requirements
+	using the "file:///" protocol - in this case the Sagemaker Edge Agent working directory
+	on the Pelion Edge Gateway will contain the specified files. 
+	
+#### Last Command Result
+
+	api.pelion_last_cmd_result()
+	
+	This call returns the last invocation/call results. In cases where predictions take
+	a long time to complete, this call may be used in a polling situation to determine
+	when the prediction operation has completed. 
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for pelion-sagemaker-controller
+Provides:	python3-pelion-sagemaker-controller-doc
+%description help
+## Sagemaker Edge Agent Controller client API for Pelion Edge 
+
+#### PyPi:  [https://pypi.org/project/pelion\_sagemaker\_controller/](https://pypi.org/project/pelion\_sagemaker\_controller/)
+
+This python package simplifies the Data Scientist's job of accessing, via a Sagemaker Jupyter Notebook, the Sagemaker Edge Agent running on their Pelion Edge enabled gateway.
+
+### Controller API Instance Creation
+
+To create an instance of this API:
+	
+	# Required import
+	from pelion_sagemaker_controller import pelion_sagemaker_controller
+	
+	#
+	# Invoke constructor with Pelion API Key, Pelion GW Device ID
+	# You can also optionally specify the Pelion API endpoint you want to use
+	#
+	api = pelion_sagemaker_controller.ControllerAPI(
+			api_key='<ak_xxxx>', 
+			device_id='<pelion_gw_device_id>', 
+			api_endpoint='api.us-east-1.mbedcloud.com'
+			)
+		
+		
+### Supported Commands
+
+The following commands are supported by this API:
+
+#### Get Configuration
+
+	api.pelion_get_config()
+	
+	This call returns a JSON with the current Edge Device representing the 
+	Sagemaker service's configuration
+	
+#### Set Configuration
+
+	api.pelion_set_config({'foo':'bar'})
+	
+	This call updates or adds key/values to the current Edge Device's configuration
+	
+#### List Models
+
+	api.pelion_list_models()
+	
+	This call returns a JSON outlining all of the loaded models
+	
+#### Load Model
+
+	api.pelion_load_model('model-name','compiled-model-x.y.tar.gz')
+	
+	This call loads up the requested Sagemaker-compiled model whose compiled 
+	contents are located within the S3 bucket defined in the configuration
+	and utilized by the Sagemaker service
+	
+#### Unload Model
+
+	api.pelion_unload_model('model-name')
+	
+	This call unloads the loaded model referenced by the name 'model-name'
+	
+#### Reload Model
+
+	api.pelion_reload_model('model-name','compiled-model-x.y.tar.gz')
+	
+	This call is a convenience method for simply performing an "unload" followed by
+	a "load" of a given model using the methods above. 
+	
+#### Predict
+
+	api.pelion_predict(
+	          'model-name',
+	          's3:///input.data', 
+	          's3:///prediction_result.data'
+	          )
+	
+	This call invokes the model prediction using the specified input.data file that is
+	configured to be pulled from the Sagemaker S3 bucket (per configuration). The output
+	result from the prediction will be stored in a file that will be saved to the same
+	directory in the S3 bucket. 
+	
+	In addition to S3 bucket support, you can locally reference input/output requirements
+	using the "file:///" protocol - in this case the Sagemaker Edge Agent working directory
+	on the Pelion Edge Gateway will contain the specified files. 
+	
+#### Last Command Result
+
+	api.pelion_last_cmd_result()
+	
+	This call returns the last invocation/call results. In cases where predictions take
+	a long time to complete, this call may be used in a polling situation to determine
+	when the prediction operation has completed. 
+
+
+
+
+
+%prep
+%autosetup -n pelion-sagemaker-controller-0.1.5
+
+%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-pelion-sagemaker-controller -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.5-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..fa028f5
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+769c0f1f3bcc714fd95c89de078d1019  pelion_sagemaker_controller-0.1.5.tar.gz