automatic import of python-text-sensitivity

1 files changed, 302 insertions, 0 deletions

diff --git a/python-text-sensitivity.spec b/python-text-sensitivity.spec
new file mode 100644
index 0000000..9059fbe
--- /dev/null
+++ b/python-text-sensitivity.spec
@@ -0,0 +1,302 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-text-sensitivity
+Version:	0.3.3
+Release:	1
+Summary:	Extension of text_explainability for sensitivity testing (robustness, fairness)
+License:	GNU LGPL v3
+URL:		https://git.science.uu.nl/m.j.robeer/text_sensitivity
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/3a/e4/ab3bae1ad306176c73838f59b68a809f1158a4ce4ed4bf97d820d694ce3a/text_sensitivity-0.3.3.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-genbase
+Requires:	python3-text-explainability
+Requires:	python3-nlpaug
+Requires:	python3-Faker
+Requires:	python3-yaspin
+
+%description
+> Extension of [text_explainability](https://git.science.uu.nl/m.j.robeer/text_explainability)
+Uses the **generic architecture** of `text_explainability` to also include tests of **safety** (_how safe it the model in production_, i.e. types of inputs it can handle), **robustness** (_how generalizable the model is in production_, e.g. stability when adding typos, or the effect of adding random unrelated data) and **fairness** (_if equal individuals are treated equally by the model_, e.g. subgroup fairness on sex and nationality).
+© Marcel Robeer, 2021
+## Quick tour
+**Safety**: test if your model is able to handle different data types.
+```python
+from text_sensitivity import RandomAscii, RandomEmojis, combine_generators
+# Generate 10 strings with random ASCII characters
+RandomAscii().generate_list(n=10)
+# Generate 5 strings with random ASCII characters and emojis
+combine_generators(RandomAscii(), RandomEmojis()).generate_list(n=5)
+```
+**Robustness**: if your model performs equally for different entities ...
+```python
+from text_sensitivity import RandomAddress, RandomEmail
+# Random address of your current locale (default = 'nl')
+RandomAddress(sep=', ').generate_list(n=5)
+# Random e-mail addresses in Spanish ('es') and Portuguese ('pt'), and include from which country the e-mail is
+RandomEmail(languages=['es', 'pt']).generate_list(n=10, attributes=True)
+```
+```python
+from text_sensitivity import compare_accuracy
+from text_sensitivity.perturbation import to_upper, add_typos
+# Is model accuracy equal when we change all sentences to uppercase?
+compare_accuracy(env, model, to_upper)
+# Is model accuracy equal when we add typos in words?
+compare_accuracy(env, model, add_typos)
+```
+**Fairness**: see if performance is equal among subgroups.
+```python
+from text_sensitivity import RandomName
+# Generate random Dutch ('nl') and Russian ('ru') names, both 'male' and 'female' (+ return attributes)
+RandomName(languages=['nl', 'ru'], sex=['male', 'female']).generate_list(n=10, attributes=True)
+```
+## Installation
+See the [installation](docs/INSTALLATION.md) instructions for an extended installation guide.
+| Method | Instructions |
+|--------|--------------|
+| `pip` | Install from [PyPI](https://pypi.org/project/text-sensitivity/) via `pip3 install text_sensitivity`. |
+| Local | Clone this repository and install via `pip3 install -e .` or locally run `python3 setup.py install`.
+## Documentation
+Full documentation of the latest version is provided at [https://text-sensitivity.readthedocs.io/](https://text-sensitivity.readthedocs.io/).
+## Example usage
+See [example_usage.md](example_usage.md) to see an example of how the package can be used, or run the lines in `example_usage.py` to do explore it interactively.
+## Releases
+`text_sensitivity` is officially released through [PyPI](https://pypi.org/project/text-sensitivity/).
+See [CHANGELOG.md](CHANGELOG.md) for a full overview of the changes for each version.
+## Citation
+```bibtex
+@misc{text_sensitivity,
+  title = {Python package text\_sensitivity},
+  author = {Marcel Robeer},
+  howpublished = {\url{https://git.science.uu.nl/m.j.robeer/text_sensitivity}},
+  year = {2021}
+}
+```
+## Maintenance
+### Contributors
+- [Marcel Robeer](https://www.uu.nl/staff/MJRobeer) (`@m.j.robeer`)
+- [Elize Herrewijnen](https://www.uu.nl/staff/EHerrewijnen) (`@e.herrewijnen`)
+### Todo
+Tasks yet to be done:
+* Word-level perturbations
+* Add fairness-specific metrics:
+    - Counterfactual fairness
+* Add expected behavior
+    - Robustness: equal to prior prediction, or in some cases might expect that it deviates
+    - Fairness: may deviate from original prediction
+* Tests
+    - Add tests for perturbations
+    - Add tests for sensitivity testing schemes
+* Add visualization ability
+## Credits
+- Edward Ma. _[NLP Augmentation](https://github.com/makcedward/nlpaug)_. 2019.
+- Daniele Faraglia and other contributors. _[Faker](https://github.com/joke2k/faker)_. 2012.
+- Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin and Sameer Singh. [Beyond Accuracy: Behavioral Testing of NLP models with CheckList](https://paperswithcode.com/paper/beyond-accuracy-behavioral-testing-of-nlp). _Association for Computational Linguistics_ (_ACL_). 2020.
+
+%package -n python3-text-sensitivity
+Summary:	Extension of text_explainability for sensitivity testing (robustness, fairness)
+Provides:	python-text-sensitivity
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-text-sensitivity
+> Extension of [text_explainability](https://git.science.uu.nl/m.j.robeer/text_explainability)
+Uses the **generic architecture** of `text_explainability` to also include tests of **safety** (_how safe it the model in production_, i.e. types of inputs it can handle), **robustness** (_how generalizable the model is in production_, e.g. stability when adding typos, or the effect of adding random unrelated data) and **fairness** (_if equal individuals are treated equally by the model_, e.g. subgroup fairness on sex and nationality).
+© Marcel Robeer, 2021
+## Quick tour
+**Safety**: test if your model is able to handle different data types.
+```python
+from text_sensitivity import RandomAscii, RandomEmojis, combine_generators
+# Generate 10 strings with random ASCII characters
+RandomAscii().generate_list(n=10)
+# Generate 5 strings with random ASCII characters and emojis
+combine_generators(RandomAscii(), RandomEmojis()).generate_list(n=5)
+```
+**Robustness**: if your model performs equally for different entities ...
+```python
+from text_sensitivity import RandomAddress, RandomEmail
+# Random address of your current locale (default = 'nl')
+RandomAddress(sep=', ').generate_list(n=5)
+# Random e-mail addresses in Spanish ('es') and Portuguese ('pt'), and include from which country the e-mail is
+RandomEmail(languages=['es', 'pt']).generate_list(n=10, attributes=True)
+```
+```python
+from text_sensitivity import compare_accuracy
+from text_sensitivity.perturbation import to_upper, add_typos
+# Is model accuracy equal when we change all sentences to uppercase?
+compare_accuracy(env, model, to_upper)
+# Is model accuracy equal when we add typos in words?
+compare_accuracy(env, model, add_typos)
+```
+**Fairness**: see if performance is equal among subgroups.
+```python
+from text_sensitivity import RandomName
+# Generate random Dutch ('nl') and Russian ('ru') names, both 'male' and 'female' (+ return attributes)
+RandomName(languages=['nl', 'ru'], sex=['male', 'female']).generate_list(n=10, attributes=True)
+```
+## Installation
+See the [installation](docs/INSTALLATION.md) instructions for an extended installation guide.
+| Method | Instructions |
+|--------|--------------|
+| `pip` | Install from [PyPI](https://pypi.org/project/text-sensitivity/) via `pip3 install text_sensitivity`. |
+| Local | Clone this repository and install via `pip3 install -e .` or locally run `python3 setup.py install`.
+## Documentation
+Full documentation of the latest version is provided at [https://text-sensitivity.readthedocs.io/](https://text-sensitivity.readthedocs.io/).
+## Example usage
+See [example_usage.md](example_usage.md) to see an example of how the package can be used, or run the lines in `example_usage.py` to do explore it interactively.
+## Releases
+`text_sensitivity` is officially released through [PyPI](https://pypi.org/project/text-sensitivity/).
+See [CHANGELOG.md](CHANGELOG.md) for a full overview of the changes for each version.
+## Citation
+```bibtex
+@misc{text_sensitivity,
+  title = {Python package text\_sensitivity},
+  author = {Marcel Robeer},
+  howpublished = {\url{https://git.science.uu.nl/m.j.robeer/text_sensitivity}},
+  year = {2021}
+}
+```
+## Maintenance
+### Contributors
+- [Marcel Robeer](https://www.uu.nl/staff/MJRobeer) (`@m.j.robeer`)
+- [Elize Herrewijnen](https://www.uu.nl/staff/EHerrewijnen) (`@e.herrewijnen`)
+### Todo
+Tasks yet to be done:
+* Word-level perturbations
+* Add fairness-specific metrics:
+    - Counterfactual fairness
+* Add expected behavior
+    - Robustness: equal to prior prediction, or in some cases might expect that it deviates
+    - Fairness: may deviate from original prediction
+* Tests
+    - Add tests for perturbations
+    - Add tests for sensitivity testing schemes
+* Add visualization ability
+## Credits
+- Edward Ma. _[NLP Augmentation](https://github.com/makcedward/nlpaug)_. 2019.
+- Daniele Faraglia and other contributors. _[Faker](https://github.com/joke2k/faker)_. 2012.
+- Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin and Sameer Singh. [Beyond Accuracy: Behavioral Testing of NLP models with CheckList](https://paperswithcode.com/paper/beyond-accuracy-behavioral-testing-of-nlp). _Association for Computational Linguistics_ (_ACL_). 2020.
+
+%package help
+Summary:	Development documents and examples for text-sensitivity
+Provides:	python3-text-sensitivity-doc
+%description help
+> Extension of [text_explainability](https://git.science.uu.nl/m.j.robeer/text_explainability)
+Uses the **generic architecture** of `text_explainability` to also include tests of **safety** (_how safe it the model in production_, i.e. types of inputs it can handle), **robustness** (_how generalizable the model is in production_, e.g. stability when adding typos, or the effect of adding random unrelated data) and **fairness** (_if equal individuals are treated equally by the model_, e.g. subgroup fairness on sex and nationality).
+© Marcel Robeer, 2021
+## Quick tour
+**Safety**: test if your model is able to handle different data types.
+```python
+from text_sensitivity import RandomAscii, RandomEmojis, combine_generators
+# Generate 10 strings with random ASCII characters
+RandomAscii().generate_list(n=10)
+# Generate 5 strings with random ASCII characters and emojis
+combine_generators(RandomAscii(), RandomEmojis()).generate_list(n=5)
+```
+**Robustness**: if your model performs equally for different entities ...
+```python
+from text_sensitivity import RandomAddress, RandomEmail
+# Random address of your current locale (default = 'nl')
+RandomAddress(sep=', ').generate_list(n=5)
+# Random e-mail addresses in Spanish ('es') and Portuguese ('pt'), and include from which country the e-mail is
+RandomEmail(languages=['es', 'pt']).generate_list(n=10, attributes=True)
+```
+```python
+from text_sensitivity import compare_accuracy
+from text_sensitivity.perturbation import to_upper, add_typos
+# Is model accuracy equal when we change all sentences to uppercase?
+compare_accuracy(env, model, to_upper)
+# Is model accuracy equal when we add typos in words?
+compare_accuracy(env, model, add_typos)
+```
+**Fairness**: see if performance is equal among subgroups.
+```python
+from text_sensitivity import RandomName
+# Generate random Dutch ('nl') and Russian ('ru') names, both 'male' and 'female' (+ return attributes)
+RandomName(languages=['nl', 'ru'], sex=['male', 'female']).generate_list(n=10, attributes=True)
+```
+## Installation
+See the [installation](docs/INSTALLATION.md) instructions for an extended installation guide.
+| Method | Instructions |
+|--------|--------------|
+| `pip` | Install from [PyPI](https://pypi.org/project/text-sensitivity/) via `pip3 install text_sensitivity`. |
+| Local | Clone this repository and install via `pip3 install -e .` or locally run `python3 setup.py install`.
+## Documentation
+Full documentation of the latest version is provided at [https://text-sensitivity.readthedocs.io/](https://text-sensitivity.readthedocs.io/).
+## Example usage
+See [example_usage.md](example_usage.md) to see an example of how the package can be used, or run the lines in `example_usage.py` to do explore it interactively.
+## Releases
+`text_sensitivity` is officially released through [PyPI](https://pypi.org/project/text-sensitivity/).
+See [CHANGELOG.md](CHANGELOG.md) for a full overview of the changes for each version.
+## Citation
+```bibtex
+@misc{text_sensitivity,
+  title = {Python package text\_sensitivity},
+  author = {Marcel Robeer},
+  howpublished = {\url{https://git.science.uu.nl/m.j.robeer/text_sensitivity}},
+  year = {2021}
+}
+```
+## Maintenance
+### Contributors
+- [Marcel Robeer](https://www.uu.nl/staff/MJRobeer) (`@m.j.robeer`)
+- [Elize Herrewijnen](https://www.uu.nl/staff/EHerrewijnen) (`@e.herrewijnen`)
+### Todo
+Tasks yet to be done:
+* Word-level perturbations
+* Add fairness-specific metrics:
+    - Counterfactual fairness
+* Add expected behavior
+    - Robustness: equal to prior prediction, or in some cases might expect that it deviates
+    - Fairness: may deviate from original prediction
+* Tests
+    - Add tests for perturbations
+    - Add tests for sensitivity testing schemes
+* Add visualization ability
+## Credits
+- Edward Ma. _[NLP Augmentation](https://github.com/makcedward/nlpaug)_. 2019.
+- Daniele Faraglia and other contributors. _[Faker](https://github.com/joke2k/faker)_. 2012.
+- Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin and Sameer Singh. [Beyond Accuracy: Behavioral Testing of NLP models with CheckList](https://paperswithcode.com/paper/beyond-accuracy-behavioral-testing-of-nlp). _Association for Computational Linguistics_ (_ACL_). 2020.
+
+%prep
+%autosetup -n text-sensitivity-0.3.3
+
+%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-text-sensitivity -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3.3-1
+- Package Spec generated