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@@ -0,0 +1 @@ +/dossier.models-0.6.16.tar.gz diff --git a/python-dossier-models.spec b/python-dossier-models.spec new file mode 100644 index 0000000..549a2e8 --- /dev/null +++ b/python-dossier-models.spec @@ -0,0 +1,495 @@ +%global _empty_manifest_terminate_build 0 +Name: python-dossier.models +Version: 0.6.16 +Release: 1 +Summary: Active learning models +License: MIT +URL: http://github.com/dossier/dossier.models +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/0e/3c/a0496eb03f1c31f066a32fa87a4b5177839f231ba0aa9279ecc28b796bb8/dossier.models-0.6.16.tar.gz +BuildArch: noarch + + +%description +`dossier.models` is a Python package that provides experimental active learning +models. They are meant to be used as search engines through `dossier.web` web +services. + +### Installation + +`dossier.models` is on PyPI and can be installed with `pip`: + +```bash +pip install dossier.models +``` + +Currently, `dossier.models` requires Python 2.7. It is not yet Python 3 +compatible. + + +### Documentation + +API documentation with examples is available as part of the Dossier Stack +documentation: +[http://dossier-stack.readthedocs.org](http://dossier-stack.readthedocs.org#module-dossier.models) + + +### Running a simple example + +`dossier.models` comes with an example web application that demonstrates how to +use all of the Dossier Stack components to do active learning. The following is +a step-by-step guide to get you up and running with a simple example of +SortingDesk. This guide assumes basic familiarity with standard Python tools +like `pip` and `virtualenv`. + +This guide also requires a database of some sort to store data. You can use +any of the backends supported by [kvlayer](https://github.com/diffeo/kvlayer) +(like PostgreSQL, HBase or MySQL). For this guide, we'll use Redis since it +requires very little setup. Just make sure it is installed and running on your +system. + +Here are a couple of screenshots of SortingDesk in action: + +[](http://i.imgur.com/I0qT4M9.png) +[](http://i.imgur.com/Uxeksx5.png) + +First, you should create a new Python virtual environment and install +`dossier.models` from PyPI: + +```bash +$ virtualenv dossier +$ source ./dossier/bin/activate +$ pip install dossier.models +``` + +Depending upon your system setup, this may take a bit of time since +`dossier.models` depends on `numpy`, `scipy` and `scikit-learn`. + +Now verify that `dossier.models` is installed correctly: + +```bash +$ python -c 'import dossier.models' +``` + +If all is well, then the command should complete successfully without any +output. + +Next, we need to setup configuration so that Dossier Stack knows which database +to use and which indexes to create on feature collections. You can grab +a sample configuration from GitHub: + +```bash +$ curl -O https://raw.githubusercontent.com/dossier/dossier.models/master/data/config.yaml +``` + +The config looks like this: + +```yaml +kvlayer: + app_name: dossier + namespace: models + storage_type: redis + storage_addresses: ['localhost:6379'] + +dossier.store: + feature_indexes: ['name', 'keywords'] +``` + +The first section configures your database credentials. This config assumes +you're using Redis running on `localhost` on port `6379` (the default). + +The second section tells Dossier Stack which indexes to create on feature +collections. This configuration is dependent on the features in your data. +In this sample configuration, we've chosen `name` and `keywords` because both +are features in the sample data set. + +To download and load the sample data set, grab it from GitHub and use the +`dossier.store` command to load it: + +```bash +$ curl -O https://raw.githubusercontent.com/dossier/dossier.models/master/data/example.fc +$ dossier.store -c config.yaml load --id-feature content_id example.fc +``` + +The `dossier.store` command allows you to interact with feature collections +stored in your database. The `--id-feature` flag tells `dossier.store` to use +the value of the `content_id` feature as the feature collection's primary key. +If this flag is omitted, then a `uuid` is generated instead. + +You can confirm that data was added to your database with the `ids` command: + +```bash +$ dossier.store -c config.yaml ids +doc11 +doc12 +doc21 +doc22 +doc23 +... +``` + +Finally, you can run the web application bundled with `dossier.models`: + +```bash +$ dossier.models -c config.yaml +``` + +Open your browser to +[http://localhost:8080/SortingDesk](http://localhost:8080/SortingDesk) to +see an example of `SortingDesk` with the sample data. If you click on the `X` +link on an item in the queue, a negative label will be added between it and the +query indicated at the top of the page. Or you can drag an item from the queue +into a bin---or drop it anywhere on the body page to create a new bin. Bins can +also be dragged on to other bins to merge them. Go ahead and try it. You can +confirm that a label was made with the `dossier.label` command: + +```bash +$ dossier.label -c config.yaml list +Label(doc22, doc42, annotator=unknown, 2014-11-26 16:02:01, value=CorefValue.Negative) +``` + +You should also be able to see labels being added in the output of the +`dossier.models` command if you're running it in your terminal. + +There is also a simpler example using plain `SortingQueue` available at +[http://localhost:8080/SortingQueue](http://localhost:8080/SortingQueue). + +%package -n python3-dossier.models +Summary: Active learning models +Provides: python-dossier.models +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-dossier.models +`dossier.models` is a Python package that provides experimental active learning +models. They are meant to be used as search engines through `dossier.web` web +services. + +### Installation + +`dossier.models` is on PyPI and can be installed with `pip`: + +```bash +pip install dossier.models +``` + +Currently, `dossier.models` requires Python 2.7. It is not yet Python 3 +compatible. + + +### Documentation + +API documentation with examples is available as part of the Dossier Stack +documentation: +[http://dossier-stack.readthedocs.org](http://dossier-stack.readthedocs.org#module-dossier.models) + + +### Running a simple example + +`dossier.models` comes with an example web application that demonstrates how to +use all of the Dossier Stack components to do active learning. The following is +a step-by-step guide to get you up and running with a simple example of +SortingDesk. This guide assumes basic familiarity with standard Python tools +like `pip` and `virtualenv`. + +This guide also requires a database of some sort to store data. You can use +any of the backends supported by [kvlayer](https://github.com/diffeo/kvlayer) +(like PostgreSQL, HBase or MySQL). For this guide, we'll use Redis since it +requires very little setup. Just make sure it is installed and running on your +system. + +Here are a couple of screenshots of SortingDesk in action: + +[](http://i.imgur.com/I0qT4M9.png) +[](http://i.imgur.com/Uxeksx5.png) + +First, you should create a new Python virtual environment and install +`dossier.models` from PyPI: + +```bash +$ virtualenv dossier +$ source ./dossier/bin/activate +$ pip install dossier.models +``` + +Depending upon your system setup, this may take a bit of time since +`dossier.models` depends on `numpy`, `scipy` and `scikit-learn`. + +Now verify that `dossier.models` is installed correctly: + +```bash +$ python -c 'import dossier.models' +``` + +If all is well, then the command should complete successfully without any +output. + +Next, we need to setup configuration so that Dossier Stack knows which database +to use and which indexes to create on feature collections. You can grab +a sample configuration from GitHub: + +```bash +$ curl -O https://raw.githubusercontent.com/dossier/dossier.models/master/data/config.yaml +``` + +The config looks like this: + +```yaml +kvlayer: + app_name: dossier + namespace: models + storage_type: redis + storage_addresses: ['localhost:6379'] + +dossier.store: + feature_indexes: ['name', 'keywords'] +``` + +The first section configures your database credentials. This config assumes +you're using Redis running on `localhost` on port `6379` (the default). + +The second section tells Dossier Stack which indexes to create on feature +collections. This configuration is dependent on the features in your data. +In this sample configuration, we've chosen `name` and `keywords` because both +are features in the sample data set. + +To download and load the sample data set, grab it from GitHub and use the +`dossier.store` command to load it: + +```bash +$ curl -O https://raw.githubusercontent.com/dossier/dossier.models/master/data/example.fc +$ dossier.store -c config.yaml load --id-feature content_id example.fc +``` + +The `dossier.store` command allows you to interact with feature collections +stored in your database. The `--id-feature` flag tells `dossier.store` to use +the value of the `content_id` feature as the feature collection's primary key. +If this flag is omitted, then a `uuid` is generated instead. + +You can confirm that data was added to your database with the `ids` command: + +```bash +$ dossier.store -c config.yaml ids +doc11 +doc12 +doc21 +doc22 +doc23 +... +``` + +Finally, you can run the web application bundled with `dossier.models`: + +```bash +$ dossier.models -c config.yaml +``` + +Open your browser to +[http://localhost:8080/SortingDesk](http://localhost:8080/SortingDesk) to +see an example of `SortingDesk` with the sample data. If you click on the `X` +link on an item in the queue, a negative label will be added between it and the +query indicated at the top of the page. Or you can drag an item from the queue +into a bin---or drop it anywhere on the body page to create a new bin. Bins can +also be dragged on to other bins to merge them. Go ahead and try it. You can +confirm that a label was made with the `dossier.label` command: + +```bash +$ dossier.label -c config.yaml list +Label(doc22, doc42, annotator=unknown, 2014-11-26 16:02:01, value=CorefValue.Negative) +``` + +You should also be able to see labels being added in the output of the +`dossier.models` command if you're running it in your terminal. + +There is also a simpler example using plain `SortingQueue` available at +[http://localhost:8080/SortingQueue](http://localhost:8080/SortingQueue). + +%package help +Summary: Development documents and examples for dossier.models +Provides: python3-dossier.models-doc +%description help +`dossier.models` is a Python package that provides experimental active learning +models. They are meant to be used as search engines through `dossier.web` web +services. + +### Installation + +`dossier.models` is on PyPI and can be installed with `pip`: + +```bash +pip install dossier.models +``` + +Currently, `dossier.models` requires Python 2.7. It is not yet Python 3 +compatible. + + +### Documentation + +API documentation with examples is available as part of the Dossier Stack +documentation: +[http://dossier-stack.readthedocs.org](http://dossier-stack.readthedocs.org#module-dossier.models) + + +### Running a simple example + +`dossier.models` comes with an example web application that demonstrates how to +use all of the Dossier Stack components to do active learning. The following is +a step-by-step guide to get you up and running with a simple example of +SortingDesk. This guide assumes basic familiarity with standard Python tools +like `pip` and `virtualenv`. + +This guide also requires a database of some sort to store data. You can use +any of the backends supported by [kvlayer](https://github.com/diffeo/kvlayer) +(like PostgreSQL, HBase or MySQL). For this guide, we'll use Redis since it +requires very little setup. Just make sure it is installed and running on your +system. + +Here are a couple of screenshots of SortingDesk in action: + +[](http://i.imgur.com/I0qT4M9.png) +[](http://i.imgur.com/Uxeksx5.png) + +First, you should create a new Python virtual environment and install +`dossier.models` from PyPI: + +```bash +$ virtualenv dossier +$ source ./dossier/bin/activate +$ pip install dossier.models +``` + +Depending upon your system setup, this may take a bit of time since +`dossier.models` depends on `numpy`, `scipy` and `scikit-learn`. + +Now verify that `dossier.models` is installed correctly: + +```bash +$ python -c 'import dossier.models' +``` + +If all is well, then the command should complete successfully without any +output. + +Next, we need to setup configuration so that Dossier Stack knows which database +to use and which indexes to create on feature collections. You can grab +a sample configuration from GitHub: + +```bash +$ curl -O https://raw.githubusercontent.com/dossier/dossier.models/master/data/config.yaml +``` + +The config looks like this: + +```yaml +kvlayer: + app_name: dossier + namespace: models + storage_type: redis + storage_addresses: ['localhost:6379'] + +dossier.store: + feature_indexes: ['name', 'keywords'] +``` + +The first section configures your database credentials. This config assumes +you're using Redis running on `localhost` on port `6379` (the default). + +The second section tells Dossier Stack which indexes to create on feature +collections. This configuration is dependent on the features in your data. +In this sample configuration, we've chosen `name` and `keywords` because both +are features in the sample data set. + +To download and load the sample data set, grab it from GitHub and use the +`dossier.store` command to load it: + +```bash +$ curl -O https://raw.githubusercontent.com/dossier/dossier.models/master/data/example.fc +$ dossier.store -c config.yaml load --id-feature content_id example.fc +``` + +The `dossier.store` command allows you to interact with feature collections +stored in your database. The `--id-feature` flag tells `dossier.store` to use +the value of the `content_id` feature as the feature collection's primary key. +If this flag is omitted, then a `uuid` is generated instead. + +You can confirm that data was added to your database with the `ids` command: + +```bash +$ dossier.store -c config.yaml ids +doc11 +doc12 +doc21 +doc22 +doc23 +... +``` + +Finally, you can run the web application bundled with `dossier.models`: + +```bash +$ dossier.models -c config.yaml +``` + +Open your browser to +[http://localhost:8080/SortingDesk](http://localhost:8080/SortingDesk) to +see an example of `SortingDesk` with the sample data. If you click on the `X` +link on an item in the queue, a negative label will be added between it and the +query indicated at the top of the page. Or you can drag an item from the queue +into a bin---or drop it anywhere on the body page to create a new bin. Bins can +also be dragged on to other bins to merge them. Go ahead and try it. You can +confirm that a label was made with the `dossier.label` command: + +```bash +$ dossier.label -c config.yaml list +Label(doc22, doc42, annotator=unknown, 2014-11-26 16:02:01, value=CorefValue.Negative) +``` + +You should also be able to see labels being added in the output of the +`dossier.models` command if you're running it in your terminal. + +There is also a simpler example using plain `SortingQueue` available at +[http://localhost:8080/SortingQueue](http://localhost:8080/SortingQueue). + +%prep +%autosetup -n dossier.models-0.6.16 + +%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-dossier.models -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.16-1 +- Package Spec generated @@ -0,0 +1 @@ +8e3302d30a77dc510746c91bd8dfb8ad dossier.models-0.6.16.tar.gz |