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@@ -0,0 +1 @@ +/pyoptimus-23.5.0b0.tar.gz diff --git a/python-pyoptimus.spec b/python-pyoptimus.spec new file mode 100644 index 0000000..3b5221c --- /dev/null +++ b/python-pyoptimus.spec @@ -0,0 +1,734 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pyoptimus +Version: 23.5.0b0 +Release: 1 +Summary: Optimus is the missing framework for cleaning and pre-processing data in a distributed fashion. +License: APACHE +URL: https://github.com/hi-primus/optimus/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/4e/74/09cc31d0598263899d35084eafd5804de42f9bfbb516647f754433ed1006/pyoptimus-23.5.0b0.tar.gz +BuildArch: noarch + +Requires: python3-pandas +Requires: python3-numpy +Requires: python3-nltk +Requires: python3-requests +Requires: python3-fastnumbers +Requires: python3-setuptools +Requires: python3-Jinja2 +Requires: python3-humanize +Requires: python3-deepdiff +Requires: python3-glom +Requires: python3-statsmodels +Requires: python3-fast-histogram +Requires: python3-rply +Requires: python3-tabulate +Requires: python3-matplotlib +Requires: python3-seaborn +Requires: python3-jellyfish +Requires: python3-Metaphone +Requires: python3-num2words +Requires: python3-hi-dateinfer +Requires: python3-hi-urlparser +Requires: python3-yellowbrick +Requires: python3-openpyxl +Requires: python3-xlrd +Requires: python3-fastavro +Requires: python3-pandavro +Requires: python3-pybigquery +Requires: python3-snappy +Requires: python3-s3fs +Requires: python3-aiobotocore[boto3] +Requires: python3-tensorflow +Requires: python3-keras +Requires: python3-nltk +Requires: python3-pyspark +Requires: python3-findspark +Requires: python3-koalas +Requires: python3-pandas +Requires: python3-dask[complete] +Requires: python3-distributed +Requires: python3-dask-ml +Requires: python3-pyarrow +Requires: python3-coiled +Requires: python3-psutil +Requires: python3-vaex +Requires: python3-gputil +Requires: python3-numpy +Requires: python3-tensorflow +Requires: python3-keras +Requires: python3-nltk +Requires: python3-sqlalchemy +Requires: python3-flask +Requires: python3-flask +Requires: python3-gputil +Requires: python3-numpy +Requires: python3-distributed +Requires: python3-dask[complete] +Requires: python3-dask[complete] +Requires: python3-distributed +Requires: python3-dask-ml +Requires: python3-pyarrow +Requires: python3-coiled +Requires: python3-psutil +Requires: python3-sqlalchemy +Requires: python3-sphinx +Requires: python3-pytest +Requires: python3-mock +Requires: python3-nose +Requires: python3-pep8 +Requires: python3-pyflakes +Requires: python3-pandas +Requires: python3-pyspark +Requires: python3-findspark +Requires: python3-koalas +Requires: python3-pytest +Requires: python3-mock +Requires: python3-nose +Requires: python3-vaex + +%description +# Optimus + +[](https://hi-optimus.com) + +[](https://github.com/hi-primus/optimus/actions/workflows/main.yml) +[](https://hub.docker.com/r/hiprimus/optimus) +[](https://pypi.org/project/pyoptimus/) +[](https://github.com/hi-primus/optimus/releases) +[](http://calver.org) + +[](https://pepy.tech/project/pyoptimus) +[](https://pepy.tech/project/pyoptimus/month) +[](https://pepy.tech/project/pyoptimus/week) +[](https://github.com/bulutyazilim/awesome-datascience) +[](https://communityinviter.com/apps/hi-bumblebee/welcome) + +# Overview + +Optimus is an opinionated python library to easily load, process, plot and create ML models that run over pandas, Dask, cuDF, dask-cuDF, Vaex or Spark. + +Some amazing things Optimus can do for you: +* Process using a simple API, making it easy to use for newcomers. +* More than 100 functions to handle strings, process dates, urls and emails. +* Easily plot data from any size. +* Out of box functions to explore and fix data quality. +* Use the same code to process your data in your laptop or in a remote cluster of GPUs. + +[See Documentation](https://docs.hi-optimus.com/en/latest/) + +## Try Optimus +To launch a live notebook server to test optimus using binder or Colab, click on one of the following badges: + +[](https://mybinder.org/v2/gh/hi-primus/optimus/develop-23.5?filepath=https%3A%2F%2Fraw.githubusercontent.com%2Fhi-primus%2Foptimus%2Fdevelop-23.5%2Fexamples%2F10_min_to_optimus.ipynb) +[](https://colab.research.google.com/github/hi-primus/optimus/blob/master/examples/10_min_to_optimus_colab.ipynb) + +## Installation (pip): +In your terminal just type: +``` +pip install pyoptimus +``` + +By default Optimus install Pandas as the default engine, to install other engines you can use the following commands: + +| Engine | Command | +|-----------|----------------------------------------| +| Dask | ```pip install pyoptimus[dask]``` | +| cuDF | ```pip install pyoptimus[cudf]``` | +| Dask-cuDF | ```pip install pyoptimus[dask-cudf]``` | +| Vaex | ```pip install pyoptimus[vaex]``` | +| Spark | ```pip install pyoptimus[spark]``` | + +To install from the repo: +``` +pip install git+https://github.com/hi-primus/optimus.git@develop-23.5 +``` + +To install other engines: +``` +pip install git+https://github.com/hi-primus/optimus.git@develop-23.5#egg=pyoptimus[dask] +``` + + + +### Requirements +* Python 3.7 or 3.8 + +## Examples + +You can go to [10 minutes to Optimus](https://github.com/hi-primus/optimus/blob/develop-23.5/examples/10_min_to_optimus.ipynb) where you can find the basics to start working in a notebook. + +Also you can go to the [Examples](https://github.com/hi-primus/optimus/tree/develop-23.5/examples/examples.md) section and find specific notebooks about data cleaning, data munging, profiling, data enrichment and how to create ML and DL models. + +Here's a handy [Cheat Sheet](https://htmlpreview.github.io/?https://github.com/hi-primus/optimus/blob/develop-23.5/docs/cheatsheet/optimus_cheat_sheet.html) with the most common Optimus' operations. + +## Start Optimus + +Start Optimus using ```"pandas"```, ```"dask"```, ```"cudf"```,```"dask_cudf"```,```"vaex"``` or ```"spark"```. + +```python +from optimus import Optimus +op = Optimus("pandas") +``` + +## Loading data + +Now Optimus can load data in csv, json, parquet, avro and excel formats from a local file or from a URL. + +```python +#csv +df = op.load.csv("../examples/data/foo.csv") + +#json +df = op.load.json("../examples/data/foo.json") + +# using a url +df = op.load.json("https://raw.githubusercontent.com/hi-primus/optimus/develop-23.5/examples/data/foo.json") + +# parquet +df = op.load.parquet("../examples/data/foo.parquet") + +# ...or anything else +df = op.load.file("../examples/data/titanic3.xls") +``` + +Also, you can load data from Oracle, Redshift, MySQL and Postgres databases. + +## Saving Data + +```python +#csv +df.save.csv("data/foo.csv") + +# json +df.save.json("data/foo.json") + +# parquet +df.save.parquet("data/foo.parquet") +``` + +You can also save data to oracle, redshift, mysql and postgres. + +## Create dataframes + +Also, you can create a dataframe from scratch +```python +df = op.create.dataframe({ + 'A': ['a', 'b', 'c', 'd'], + 'B': [1, 3, 5, 7], + 'C': [2, 4, 6, None], + 'D': ['1980/04/10', '1980/04/10', '1980/04/10', '1980/04/10'] +}) +``` + +Using `display` you have a beautiful way to show your data with extra information like column number, column data type and marked white spaces. + +```python +display(df) +``` + + +## Cleaning and Processing + +Optimus was created to make data cleaning a breeze. The API was designed to be super easy to newcomers and very familiar for people that comes from Pandas. +Optimus expands the standard DataFrame functionality adding `.rows` and `.cols` accessors. + +For example you can load data from a url, transform and apply some predefined cleaning functions: + +```python +new_df = df\ + .rows.sort("rank", "desc")\ + .cols.lower(["names", "function"])\ + .cols.date_format("date arrival", "yyyy/MM/dd", "dd-MM-YYYY")\ + .cols.years_between("date arrival", "dd-MM-YYYY", output_cols="from arrival")\ + .cols.normalize_chars("names")\ + .cols.remove_special_chars("names")\ + .rows.drop(df["rank"]>8)\ + .cols.rename("*", str.lower)\ + .cols.trim("*")\ + .cols.unnest("japanese name", output_cols="other names")\ + .cols.unnest("last position seen", separator=",", output_cols="pos")\ + .cols.drop(["last position seen", "japanese name", "date arrival", "cybertronian", "nulltype"]) +``` + +# Need help? 🛠️ + +## Feedback + +Feedback is what drive Optimus future, so please take a couple of minutes to help shape the Optimus' Roadmap: http://bit.ly/optimus_survey + +Also if you want to a suggestion or feature request use https://github.com/hi-primus/optimus/issues + +## Troubleshooting + +If you have issues, see our [Troubleshooting Guide](https://github.com/hi-primus/optimus/tree/develop-23.5/troubleshooting.md) + +# Contributing to Optimus 💡 + +Contributions go far beyond pull requests and commits. We are very happy to receive any kind of contributions +including: + +* [Documentation](https://docs.hi-optimus.com/en/latest/) updates, enhancements, designs, or bugfixes. +* Spelling or grammar fixes. +* README.md corrections or redesigns. +* Adding unit, or functional [tests](https://github.com/hi-primus/optimus/tree/develop-23.5/tests) +* Triaging GitHub issues -- especially determining whether an issue still persists or is reproducible. +* [Blogging, speaking about, or creating tutorials](https://hioptimus.com/category/blog/) about Optimus and its many features. +* Helping others on our official chats + +# Backers and Sponsors + +Become a [backer](https://opencollective.com/optimus#backer) or a [sponsor](https://opencollective.com/optimus#sponsor) and get your image on our README on Github with a link to your site. + +[](#backers) [](#sponsors) + + + + +%package -n python3-pyoptimus +Summary: Optimus is the missing framework for cleaning and pre-processing data in a distributed fashion. +Provides: python-pyoptimus +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pyoptimus +# Optimus + +[](https://hi-optimus.com) + +[](https://github.com/hi-primus/optimus/actions/workflows/main.yml) +[](https://hub.docker.com/r/hiprimus/optimus) +[](https://pypi.org/project/pyoptimus/) +[](https://github.com/hi-primus/optimus/releases) +[](http://calver.org) + +[](https://pepy.tech/project/pyoptimus) +[](https://pepy.tech/project/pyoptimus/month) +[](https://pepy.tech/project/pyoptimus/week) +[](https://github.com/bulutyazilim/awesome-datascience) +[](https://communityinviter.com/apps/hi-bumblebee/welcome) + +# Overview + +Optimus is an opinionated python library to easily load, process, plot and create ML models that run over pandas, Dask, cuDF, dask-cuDF, Vaex or Spark. + +Some amazing things Optimus can do for you: +* Process using a simple API, making it easy to use for newcomers. +* More than 100 functions to handle strings, process dates, urls and emails. +* Easily plot data from any size. +* Out of box functions to explore and fix data quality. +* Use the same code to process your data in your laptop or in a remote cluster of GPUs. + +[See Documentation](https://docs.hi-optimus.com/en/latest/) + +## Try Optimus +To launch a live notebook server to test optimus using binder or Colab, click on one of the following badges: + +[](https://mybinder.org/v2/gh/hi-primus/optimus/develop-23.5?filepath=https%3A%2F%2Fraw.githubusercontent.com%2Fhi-primus%2Foptimus%2Fdevelop-23.5%2Fexamples%2F10_min_to_optimus.ipynb) +[](https://colab.research.google.com/github/hi-primus/optimus/blob/master/examples/10_min_to_optimus_colab.ipynb) + +## Installation (pip): +In your terminal just type: +``` +pip install pyoptimus +``` + +By default Optimus install Pandas as the default engine, to install other engines you can use the following commands: + +| Engine | Command | +|-----------|----------------------------------------| +| Dask | ```pip install pyoptimus[dask]``` | +| cuDF | ```pip install pyoptimus[cudf]``` | +| Dask-cuDF | ```pip install pyoptimus[dask-cudf]``` | +| Vaex | ```pip install pyoptimus[vaex]``` | +| Spark | ```pip install pyoptimus[spark]``` | + +To install from the repo: +``` +pip install git+https://github.com/hi-primus/optimus.git@develop-23.5 +``` + +To install other engines: +``` +pip install git+https://github.com/hi-primus/optimus.git@develop-23.5#egg=pyoptimus[dask] +``` + + + +### Requirements +* Python 3.7 or 3.8 + +## Examples + +You can go to [10 minutes to Optimus](https://github.com/hi-primus/optimus/blob/develop-23.5/examples/10_min_to_optimus.ipynb) where you can find the basics to start working in a notebook. + +Also you can go to the [Examples](https://github.com/hi-primus/optimus/tree/develop-23.5/examples/examples.md) section and find specific notebooks about data cleaning, data munging, profiling, data enrichment and how to create ML and DL models. + +Here's a handy [Cheat Sheet](https://htmlpreview.github.io/?https://github.com/hi-primus/optimus/blob/develop-23.5/docs/cheatsheet/optimus_cheat_sheet.html) with the most common Optimus' operations. + +## Start Optimus + +Start Optimus using ```"pandas"```, ```"dask"```, ```"cudf"```,```"dask_cudf"```,```"vaex"``` or ```"spark"```. + +```python +from optimus import Optimus +op = Optimus("pandas") +``` + +## Loading data + +Now Optimus can load data in csv, json, parquet, avro and excel formats from a local file or from a URL. + +```python +#csv +df = op.load.csv("../examples/data/foo.csv") + +#json +df = op.load.json("../examples/data/foo.json") + +# using a url +df = op.load.json("https://raw.githubusercontent.com/hi-primus/optimus/develop-23.5/examples/data/foo.json") + +# parquet +df = op.load.parquet("../examples/data/foo.parquet") + +# ...or anything else +df = op.load.file("../examples/data/titanic3.xls") +``` + +Also, you can load data from Oracle, Redshift, MySQL and Postgres databases. + +## Saving Data + +```python +#csv +df.save.csv("data/foo.csv") + +# json +df.save.json("data/foo.json") + +# parquet +df.save.parquet("data/foo.parquet") +``` + +You can also save data to oracle, redshift, mysql and postgres. + +## Create dataframes + +Also, you can create a dataframe from scratch +```python +df = op.create.dataframe({ + 'A': ['a', 'b', 'c', 'd'], + 'B': [1, 3, 5, 7], + 'C': [2, 4, 6, None], + 'D': ['1980/04/10', '1980/04/10', '1980/04/10', '1980/04/10'] +}) +``` + +Using `display` you have a beautiful way to show your data with extra information like column number, column data type and marked white spaces. + +```python +display(df) +``` + + +## Cleaning and Processing + +Optimus was created to make data cleaning a breeze. The API was designed to be super easy to newcomers and very familiar for people that comes from Pandas. +Optimus expands the standard DataFrame functionality adding `.rows` and `.cols` accessors. + +For example you can load data from a url, transform and apply some predefined cleaning functions: + +```python +new_df = df\ + .rows.sort("rank", "desc")\ + .cols.lower(["names", "function"])\ + .cols.date_format("date arrival", "yyyy/MM/dd", "dd-MM-YYYY")\ + .cols.years_between("date arrival", "dd-MM-YYYY", output_cols="from arrival")\ + .cols.normalize_chars("names")\ + .cols.remove_special_chars("names")\ + .rows.drop(df["rank"]>8)\ + .cols.rename("*", str.lower)\ + .cols.trim("*")\ + .cols.unnest("japanese name", output_cols="other names")\ + .cols.unnest("last position seen", separator=",", output_cols="pos")\ + .cols.drop(["last position seen", "japanese name", "date arrival", "cybertronian", "nulltype"]) +``` + +# Need help? 🛠️ + +## Feedback + +Feedback is what drive Optimus future, so please take a couple of minutes to help shape the Optimus' Roadmap: http://bit.ly/optimus_survey + +Also if you want to a suggestion or feature request use https://github.com/hi-primus/optimus/issues + +## Troubleshooting + +If you have issues, see our [Troubleshooting Guide](https://github.com/hi-primus/optimus/tree/develop-23.5/troubleshooting.md) + +# Contributing to Optimus 💡 + +Contributions go far beyond pull requests and commits. We are very happy to receive any kind of contributions +including: + +* [Documentation](https://docs.hi-optimus.com/en/latest/) updates, enhancements, designs, or bugfixes. +* Spelling or grammar fixes. +* README.md corrections or redesigns. +* Adding unit, or functional [tests](https://github.com/hi-primus/optimus/tree/develop-23.5/tests) +* Triaging GitHub issues -- especially determining whether an issue still persists or is reproducible. +* [Blogging, speaking about, or creating tutorials](https://hioptimus.com/category/blog/) about Optimus and its many features. +* Helping others on our official chats + +# Backers and Sponsors + +Become a [backer](https://opencollective.com/optimus#backer) or a [sponsor](https://opencollective.com/optimus#sponsor) and get your image on our README on Github with a link to your site. + +[](#backers) [](#sponsors) + + + + +%package help +Summary: Development documents and examples for pyoptimus +Provides: python3-pyoptimus-doc +%description help +# Optimus + +[](https://hi-optimus.com) + +[](https://github.com/hi-primus/optimus/actions/workflows/main.yml) +[](https://hub.docker.com/r/hiprimus/optimus) +[](https://pypi.org/project/pyoptimus/) +[](https://github.com/hi-primus/optimus/releases) +[](http://calver.org) + +[](https://pepy.tech/project/pyoptimus) +[](https://pepy.tech/project/pyoptimus/month) +[](https://pepy.tech/project/pyoptimus/week) +[](https://github.com/bulutyazilim/awesome-datascience) +[](https://communityinviter.com/apps/hi-bumblebee/welcome) + +# Overview + +Optimus is an opinionated python library to easily load, process, plot and create ML models that run over pandas, Dask, cuDF, dask-cuDF, Vaex or Spark. + +Some amazing things Optimus can do for you: +* Process using a simple API, making it easy to use for newcomers. +* More than 100 functions to handle strings, process dates, urls and emails. +* Easily plot data from any size. +* Out of box functions to explore and fix data quality. +* Use the same code to process your data in your laptop or in a remote cluster of GPUs. + +[See Documentation](https://docs.hi-optimus.com/en/latest/) + +## Try Optimus +To launch a live notebook server to test optimus using binder or Colab, click on one of the following badges: + +[](https://mybinder.org/v2/gh/hi-primus/optimus/develop-23.5?filepath=https%3A%2F%2Fraw.githubusercontent.com%2Fhi-primus%2Foptimus%2Fdevelop-23.5%2Fexamples%2F10_min_to_optimus.ipynb) +[](https://colab.research.google.com/github/hi-primus/optimus/blob/master/examples/10_min_to_optimus_colab.ipynb) + +## Installation (pip): +In your terminal just type: +``` +pip install pyoptimus +``` + +By default Optimus install Pandas as the default engine, to install other engines you can use the following commands: + +| Engine | Command | +|-----------|----------------------------------------| +| Dask | ```pip install pyoptimus[dask]``` | +| cuDF | ```pip install pyoptimus[cudf]``` | +| Dask-cuDF | ```pip install pyoptimus[dask-cudf]``` | +| Vaex | ```pip install pyoptimus[vaex]``` | +| Spark | ```pip install pyoptimus[spark]``` | + +To install from the repo: +``` +pip install git+https://github.com/hi-primus/optimus.git@develop-23.5 +``` + +To install other engines: +``` +pip install git+https://github.com/hi-primus/optimus.git@develop-23.5#egg=pyoptimus[dask] +``` + + + +### Requirements +* Python 3.7 or 3.8 + +## Examples + +You can go to [10 minutes to Optimus](https://github.com/hi-primus/optimus/blob/develop-23.5/examples/10_min_to_optimus.ipynb) where you can find the basics to start working in a notebook. + +Also you can go to the [Examples](https://github.com/hi-primus/optimus/tree/develop-23.5/examples/examples.md) section and find specific notebooks about data cleaning, data munging, profiling, data enrichment and how to create ML and DL models. + +Here's a handy [Cheat Sheet](https://htmlpreview.github.io/?https://github.com/hi-primus/optimus/blob/develop-23.5/docs/cheatsheet/optimus_cheat_sheet.html) with the most common Optimus' operations. + +## Start Optimus + +Start Optimus using ```"pandas"```, ```"dask"```, ```"cudf"```,```"dask_cudf"```,```"vaex"``` or ```"spark"```. + +```python +from optimus import Optimus +op = Optimus("pandas") +``` + +## Loading data + +Now Optimus can load data in csv, json, parquet, avro and excel formats from a local file or from a URL. + +```python +#csv +df = op.load.csv("../examples/data/foo.csv") + +#json +df = op.load.json("../examples/data/foo.json") + +# using a url +df = op.load.json("https://raw.githubusercontent.com/hi-primus/optimus/develop-23.5/examples/data/foo.json") + +# parquet +df = op.load.parquet("../examples/data/foo.parquet") + +# ...or anything else +df = op.load.file("../examples/data/titanic3.xls") +``` + +Also, you can load data from Oracle, Redshift, MySQL and Postgres databases. + +## Saving Data + +```python +#csv +df.save.csv("data/foo.csv") + +# json +df.save.json("data/foo.json") + +# parquet +df.save.parquet("data/foo.parquet") +``` + +You can also save data to oracle, redshift, mysql and postgres. + +## Create dataframes + +Also, you can create a dataframe from scratch +```python +df = op.create.dataframe({ + 'A': ['a', 'b', 'c', 'd'], + 'B': [1, 3, 5, 7], + 'C': [2, 4, 6, None], + 'D': ['1980/04/10', '1980/04/10', '1980/04/10', '1980/04/10'] +}) +``` + +Using `display` you have a beautiful way to show your data with extra information like column number, column data type and marked white spaces. + +```python +display(df) +``` + + +## Cleaning and Processing + +Optimus was created to make data cleaning a breeze. The API was designed to be super easy to newcomers and very familiar for people that comes from Pandas. +Optimus expands the standard DataFrame functionality adding `.rows` and `.cols` accessors. + +For example you can load data from a url, transform and apply some predefined cleaning functions: + +```python +new_df = df\ + .rows.sort("rank", "desc")\ + .cols.lower(["names", "function"])\ + .cols.date_format("date arrival", "yyyy/MM/dd", "dd-MM-YYYY")\ + .cols.years_between("date arrival", "dd-MM-YYYY", output_cols="from arrival")\ + .cols.normalize_chars("names")\ + .cols.remove_special_chars("names")\ + .rows.drop(df["rank"]>8)\ + .cols.rename("*", str.lower)\ + .cols.trim("*")\ + .cols.unnest("japanese name", output_cols="other names")\ + .cols.unnest("last position seen", separator=",", output_cols="pos")\ + .cols.drop(["last position seen", "japanese name", "date arrival", "cybertronian", "nulltype"]) +``` + +# Need help? 🛠️ + +## Feedback + +Feedback is what drive Optimus future, so please take a couple of minutes to help shape the Optimus' Roadmap: http://bit.ly/optimus_survey + +Also if you want to a suggestion or feature request use https://github.com/hi-primus/optimus/issues + +## Troubleshooting + +If you have issues, see our [Troubleshooting Guide](https://github.com/hi-primus/optimus/tree/develop-23.5/troubleshooting.md) + +# Contributing to Optimus 💡 + +Contributions go far beyond pull requests and commits. We are very happy to receive any kind of contributions +including: + +* [Documentation](https://docs.hi-optimus.com/en/latest/) updates, enhancements, designs, or bugfixes. +* Spelling or grammar fixes. +* README.md corrections or redesigns. +* Adding unit, or functional [tests](https://github.com/hi-primus/optimus/tree/develop-23.5/tests) +* Triaging GitHub issues -- especially determining whether an issue still persists or is reproducible. +* [Blogging, speaking about, or creating tutorials](https://hioptimus.com/category/blog/) about Optimus and its many features. +* Helping others on our official chats + +# Backers and Sponsors + +Become a [backer](https://opencollective.com/optimus#backer) or a [sponsor](https://opencollective.com/optimus#sponsor) and get your image on our README on Github with a link to your site. + +[](#backers) [](#sponsors) + + + + +%prep +%autosetup -n pyoptimus-23.5.0b0 + +%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-pyoptimus -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 23.5.0b0-1 +- Package Spec generated @@ -0,0 +1 @@ +436ca097784d7e47a7d239d02058c5c6 pyoptimus-23.5.0b0.tar.gz |