%global _empty_manifest_terminate_build 0
Name:		python-spylon-kernel
Version:	0.4.1
Release:	1
Summary:	Jupyter metakernel for apache spark and scala
License:	BSD 3-clause
URL:		http://github.com/maxpoint/spylon-kernel
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/3b/26/0c1c289ab535489b0e290461b0f2c45a00d2033a50a58a45f6d00c5fb205/spylon-kernel-0.4.1.tar.gz
BuildArch:	noarch


%description
# spylon-kernel
[![Build Status](https://travis-ci.org/maxpoint/spylon-kernel.svg?branch=master)](https://travis-ci.org/maxpoint/spylon-kernel)
[![codecov](https://codecov.io/gh/maxpoint/spylon-kernel/branch/master/graph/badge.svg)](https://codecov.io/gh/maxpoint/spylon-kernel)

A Scala [Jupyter kernel](http://jupyter.readthedocs.io/en/latest/projects/kernels.html) that uses [metakernel](https://github.com/Calysto/metakernel) in combination with [py4j](https://www.py4j.org/).

## Prerequisites

* Apache Spark 2.1.1 compiled for Scala 2.11
* Jupyter Notebook
* Python 3.5+

## Install

You can install the spylon-kernel package using `pip` or `conda`.

```bash
pip install spylon-kernel
# or
conda install -c conda-forge spylon-kernel
```

## Using it as a Scala Kernel

You can use spylon-kernel as Scala kernel for Jupyter Notebook. Do this when you want
to work with Spark in Scala with a bit of Python code mixed in.

Create a kernel spec for Jupyter notebook by running the following command:

```bash
python -m spylon_kernel install
```

Launch `jupyter notebook` and you should see a `spylon-kernel` as an option
in the *New* dropdown menu.

See [the basic example notebook](./examples/basic_example.ipynb) for information
about how to intiialize a Spark session and use it both in Scala and Python.

## Using it as an IPython Magic

You can also use spylon-kernel as a magic in an IPython notebook. Do this when
you want to mix a little bit of Scala into your primarily Python notebook.

```python
from spylon_kernel import register_ipython_magics
register_ipython_magics()
```

```scala
%%scala
val x = 8
x
```

## Using it as a Library

Finally, you can use spylon-kernel as a Python library. Do this when you
want to evaluate a string of Scala code in a Python script or shell.

```python
from spylon_kernel import get_scala_interpreter

interp = get_scala_interpreter()

# Evaluate the result of a scala code block.
interp.interpret("""
    val x = 8
    x
""")

interp.last_result()
```

# Release Process

Push a tag and submit a source dist to PyPI.

```
git commit -m 'REL: 0.2.1' --allow-empty
git tag -a 0.2.1 # and enter the same message as the commit
git push origin master # or send a PR

# if everything builds / tests cleanly, release to pypi
make release
```

Then update https://github.com/conda-forge/spylon-kernel-feedstock.


%package -n python3-spylon-kernel
Summary:	Jupyter metakernel for apache spark and scala
Provides:	python-spylon-kernel
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-spylon-kernel
# spylon-kernel
[![Build Status](https://travis-ci.org/maxpoint/spylon-kernel.svg?branch=master)](https://travis-ci.org/maxpoint/spylon-kernel)
[![codecov](https://codecov.io/gh/maxpoint/spylon-kernel/branch/master/graph/badge.svg)](https://codecov.io/gh/maxpoint/spylon-kernel)

A Scala [Jupyter kernel](http://jupyter.readthedocs.io/en/latest/projects/kernels.html) that uses [metakernel](https://github.com/Calysto/metakernel) in combination with [py4j](https://www.py4j.org/).

## Prerequisites

* Apache Spark 2.1.1 compiled for Scala 2.11
* Jupyter Notebook
* Python 3.5+

## Install

You can install the spylon-kernel package using `pip` or `conda`.

```bash
pip install spylon-kernel
# or
conda install -c conda-forge spylon-kernel
```

## Using it as a Scala Kernel

You can use spylon-kernel as Scala kernel for Jupyter Notebook. Do this when you want
to work with Spark in Scala with a bit of Python code mixed in.

Create a kernel spec for Jupyter notebook by running the following command:

```bash
python -m spylon_kernel install
```

Launch `jupyter notebook` and you should see a `spylon-kernel` as an option
in the *New* dropdown menu.

See [the basic example notebook](./examples/basic_example.ipynb) for information
about how to intiialize a Spark session and use it both in Scala and Python.

## Using it as an IPython Magic

You can also use spylon-kernel as a magic in an IPython notebook. Do this when
you want to mix a little bit of Scala into your primarily Python notebook.

```python
from spylon_kernel import register_ipython_magics
register_ipython_magics()
```

```scala
%%scala
val x = 8
x
```

## Using it as a Library

Finally, you can use spylon-kernel as a Python library. Do this when you
want to evaluate a string of Scala code in a Python script or shell.

```python
from spylon_kernel import get_scala_interpreter

interp = get_scala_interpreter()

# Evaluate the result of a scala code block.
interp.interpret("""
    val x = 8
    x
""")

interp.last_result()
```

# Release Process

Push a tag and submit a source dist to PyPI.

```
git commit -m 'REL: 0.2.1' --allow-empty
git tag -a 0.2.1 # and enter the same message as the commit
git push origin master # or send a PR

# if everything builds / tests cleanly, release to pypi
make release
```

Then update https://github.com/conda-forge/spylon-kernel-feedstock.


%package help
Summary:	Development documents and examples for spylon-kernel
Provides:	python3-spylon-kernel-doc
%description help
# spylon-kernel
[![Build Status](https://travis-ci.org/maxpoint/spylon-kernel.svg?branch=master)](https://travis-ci.org/maxpoint/spylon-kernel)
[![codecov](https://codecov.io/gh/maxpoint/spylon-kernel/branch/master/graph/badge.svg)](https://codecov.io/gh/maxpoint/spylon-kernel)

A Scala [Jupyter kernel](http://jupyter.readthedocs.io/en/latest/projects/kernels.html) that uses [metakernel](https://github.com/Calysto/metakernel) in combination with [py4j](https://www.py4j.org/).

## Prerequisites

* Apache Spark 2.1.1 compiled for Scala 2.11
* Jupyter Notebook
* Python 3.5+

## Install

You can install the spylon-kernel package using `pip` or `conda`.

```bash
pip install spylon-kernel
# or
conda install -c conda-forge spylon-kernel
```

## Using it as a Scala Kernel

You can use spylon-kernel as Scala kernel for Jupyter Notebook. Do this when you want
to work with Spark in Scala with a bit of Python code mixed in.

Create a kernel spec for Jupyter notebook by running the following command:

```bash
python -m spylon_kernel install
```

Launch `jupyter notebook` and you should see a `spylon-kernel` as an option
in the *New* dropdown menu.

See [the basic example notebook](./examples/basic_example.ipynb) for information
about how to intiialize a Spark session and use it both in Scala and Python.

## Using it as an IPython Magic

You can also use spylon-kernel as a magic in an IPython notebook. Do this when
you want to mix a little bit of Scala into your primarily Python notebook.

```python
from spylon_kernel import register_ipython_magics
register_ipython_magics()
```

```scala
%%scala
val x = 8
x
```

## Using it as a Library

Finally, you can use spylon-kernel as a Python library. Do this when you
want to evaluate a string of Scala code in a Python script or shell.

```python
from spylon_kernel import get_scala_interpreter

interp = get_scala_interpreter()

# Evaluate the result of a scala code block.
interp.interpret("""
    val x = 8
    x
""")

interp.last_result()
```

# Release Process

Push a tag and submit a source dist to PyPI.

```
git commit -m 'REL: 0.2.1' --allow-empty
git tag -a 0.2.1 # and enter the same message as the commit
git push origin master # or send a PR

# if everything builds / tests cleanly, release to pypi
make release
```

Then update https://github.com/conda-forge/spylon-kernel-feedstock.


%prep
%autosetup -n spylon-kernel-0.4.1

%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-spylon-kernel -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.1-1
- Package Spec generated