%global _empty_manifest_terminate_build 0 Name: python-fastcore Version: 1.5.29 Release: 1 Summary: Python supercharged for fastai development License: Apache Software License 2.0 URL: https://github.com/fastai/fastcore/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/1f/62/bb0d880d3a9306a6a042ab41ea61b082f8d2c378019f8b3d37693b9a0b44/fastcore-1.5.29.tar.gz BuildArch: noarch Requires: python3-pip Requires: python3-packaging Requires: python3-numpy Requires: python3-nbdev Requires: python3-matplotlib Requires: python3-pillow Requires: python3-torch Requires: python3-pandas Requires: python3-jupyterlab %description Python is a powerful, dynamic language. Rather than bake everything into the language, it lets the programmer customize it to make it work for them. `fastcore` uses this flexibility to add to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia, mixins from Ruby, and currying, binding, and more from Haskell. It also adds some “missing features” and clean up some rough edges in the Python standard library, such as simplifying parallel processing, and bringing ideas from NumPy over to Python’s `list` type. ## Getting started To install fastcore run: `conda install fastcore -c fastai` (if you use Anaconda, which we recommend) or `pip install fastcore`. For an [editable install](https://stackoverflow.com/questions/35064426/when-would-the-e-editable-option-be-useful-with-pip-install), clone this repo and run: `pip install -e ".[dev]"`. fastcore is tested to work on Ubuntu, macOS and Windows (versions tested are those show with the `-latest` suffix [here](https://docs.github.com/en/actions/reference/specifications-for-github-hosted-runners#supported-runners-and-hardware-resources). `fastcore` contains many features, including: - `fastcore.test`: Simple testing functions - `fastcore.foundation`: Mixins, delegation, composition, and more - `fastcore.xtras`: Utility functions to help with functional-style programming, parallel processing, and more - `fastcore.dispatch`: Multiple dispatch methods - `fastcore.transform`: Pipelines of composed partially reversible transformations To get started, we recommend you read through [the fastcore tour](https://fastcore.fast.ai/tour.html). ## Contributing After you clone this repository, please run `nbdev_install_hooks` in your terminal. This sets up git hooks, which clean up the notebooks to remove the extraneous stuff stored in the notebooks (e.g. which cells you ran) which causes unnecessary merge conflicts. To run the tests in parallel, launch `nbdev_test`. Before submitting a PR, check that the local library and notebooks match. - If you made a change to the notebooks in one of the exported cells, you can export it to the library with `nbdev_prepare`. - If you made a change to the library, you can export it back to the notebooks with `nbdev_update`. %package -n python3-fastcore Summary: Python supercharged for fastai development Provides: python-fastcore BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-fastcore Python is a powerful, dynamic language. Rather than bake everything into the language, it lets the programmer customize it to make it work for them. `fastcore` uses this flexibility to add to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia, mixins from Ruby, and currying, binding, and more from Haskell. It also adds some “missing features” and clean up some rough edges in the Python standard library, such as simplifying parallel processing, and bringing ideas from NumPy over to Python’s `list` type. ## Getting started To install fastcore run: `conda install fastcore -c fastai` (if you use Anaconda, which we recommend) or `pip install fastcore`. For an [editable install](https://stackoverflow.com/questions/35064426/when-would-the-e-editable-option-be-useful-with-pip-install), clone this repo and run: `pip install -e ".[dev]"`. fastcore is tested to work on Ubuntu, macOS and Windows (versions tested are those show with the `-latest` suffix [here](https://docs.github.com/en/actions/reference/specifications-for-github-hosted-runners#supported-runners-and-hardware-resources). `fastcore` contains many features, including: - `fastcore.test`: Simple testing functions - `fastcore.foundation`: Mixins, delegation, composition, and more - `fastcore.xtras`: Utility functions to help with functional-style programming, parallel processing, and more - `fastcore.dispatch`: Multiple dispatch methods - `fastcore.transform`: Pipelines of composed partially reversible transformations To get started, we recommend you read through [the fastcore tour](https://fastcore.fast.ai/tour.html). ## Contributing After you clone this repository, please run `nbdev_install_hooks` in your terminal. This sets up git hooks, which clean up the notebooks to remove the extraneous stuff stored in the notebooks (e.g. which cells you ran) which causes unnecessary merge conflicts. To run the tests in parallel, launch `nbdev_test`. Before submitting a PR, check that the local library and notebooks match. - If you made a change to the notebooks in one of the exported cells, you can export it to the library with `nbdev_prepare`. - If you made a change to the library, you can export it back to the notebooks with `nbdev_update`. %package help Summary: Development documents and examples for fastcore Provides: python3-fastcore-doc %description help Python is a powerful, dynamic language. Rather than bake everything into the language, it lets the programmer customize it to make it work for them. `fastcore` uses this flexibility to add to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia, mixins from Ruby, and currying, binding, and more from Haskell. It also adds some “missing features” and clean up some rough edges in the Python standard library, such as simplifying parallel processing, and bringing ideas from NumPy over to Python’s `list` type. ## Getting started To install fastcore run: `conda install fastcore -c fastai` (if you use Anaconda, which we recommend) or `pip install fastcore`. For an [editable install](https://stackoverflow.com/questions/35064426/when-would-the-e-editable-option-be-useful-with-pip-install), clone this repo and run: `pip install -e ".[dev]"`. fastcore is tested to work on Ubuntu, macOS and Windows (versions tested are those show with the `-latest` suffix [here](https://docs.github.com/en/actions/reference/specifications-for-github-hosted-runners#supported-runners-and-hardware-resources). `fastcore` contains many features, including: - `fastcore.test`: Simple testing functions - `fastcore.foundation`: Mixins, delegation, composition, and more - `fastcore.xtras`: Utility functions to help with functional-style programming, parallel processing, and more - `fastcore.dispatch`: Multiple dispatch methods - `fastcore.transform`: Pipelines of composed partially reversible transformations To get started, we recommend you read through [the fastcore tour](https://fastcore.fast.ai/tour.html). ## Contributing After you clone this repository, please run `nbdev_install_hooks` in your terminal. This sets up git hooks, which clean up the notebooks to remove the extraneous stuff stored in the notebooks (e.g. which cells you ran) which causes unnecessary merge conflicts. To run the tests in parallel, launch `nbdev_test`. Before submitting a PR, check that the local library and notebooks match. - If you made a change to the notebooks in one of the exported cells, you can export it to the library with `nbdev_prepare`. - If you made a change to the library, you can export it back to the notebooks with `nbdev_update`. %prep %autosetup -n fastcore-1.5.29 %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-fastcore -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Mon Apr 10 2023 Python_Bot - 1.5.29-1 - Package Spec generated