The Runway Model SDK allows you to port new and existing machine learning models to the Runway platform. With a few lines of code, you can modify your Python model to be used and shared by others on [Runway](https://runwayml.com).
## Installing
The SDK supports Python 3.6+. You can install the module using either pip or pip3 like so:
```
pip3 install runway-python
```
Now head over to [the sdk docs](https://sdk.runwayml.com) to learn how to use the Runway Model SDK.
## Docs
Reference and documentation for the Runway Model SDK is hosted at [sdk.runwayml.com](https://sdk.runwayml.com). These docs provide an overview of how to use the SDK to port your own ML models.
The [Runway Model Template repo](https://github.com/runwayml/model-template) also contains a simple example of how to get started porting a model to Runway.
See the *Importing Models into Runway* [tutorial](https://docs.runwayapp.ai/#/importing) for a walk-through illustrating how to port a model to Runway.
## Developing
If you'd like to contribute to the development of the Runway Python SDK, you can clone and modify this repository by following the instructions below.
```bash
git clone https://github.com/runwayml/model-sdk runway-model-sdk
cd runway-model-sdk
## optionally use a virtual environment
# virtualenv -p python3 venv && source venv/bin/activate
# install dependencies
python3 setup.py install
# install the dev dependencies
make dev
```
### Testing
Automated tests for the Runway Model SDK are written using `pytest` and live in the `tests/` directory. We also provide support for code coverage via `pytest-cov`.
```bash
## Create and activate a python3 virtual environment if you need to.
# virtualenv -p python3 venv && source ./venv/bin/activate
# make sure you have the development dependencies installed
make dev
# run the tests
make test
# by default pytest suppresses stdout and stderr during testing, so run tests
# like this if you'd like to see the output from your print() statements during
# testing
make test-debug
# to generate coverage statistics while running tests, use this command.
# it prints test coverage to the console and also generates a more detailed HTML
# report in htmlcov/.
make coverage
```
If you make a PR against this repo, please be sure to include automated tests to validate that your code works as expected. PRs will be automatically blocked by a [Codecov](https://codecov.io/) bot if their changes reduce the overall test coverage of the Runway Model SDK package.
### Building the Docs
The Model SDK documentation is generated from inline source code using docstrings, [Sphinx](http://www.sphinx-doc.org/en/master/), and a modified Read the Docs HTML theme. The version of Sphinx that we are using (v2.0.1) requires Python 3.
```bash
## Create and activate a python3 virtual environment if you need to.
# virtualenv -p python3 venv && source ./venv/bin/activate
# make sure you have the docs dependencies installed
make dev-docs
# build the docs
make docs
```
Your auto-generated HTML docs should now appear in `docs/build/html`.
### Questions
We have a `#model-sdk` channel in our public [Slack](https://runwayml.com/joinslack) workspace that you can use to ask questions or chat with the Runway team about this Python module. Feel free to open an issue as well!
%package -n python3-runway-python
Summary: Helper library for creating Runway models
Provides: python-runway-python
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-runway-python
The Runway Model SDK allows you to port new and existing machine learning models to the Runway platform. With a few lines of code, you can modify your Python model to be used and shared by others on [Runway](https://runwayml.com).
## Installing
The SDK supports Python 3.6+. You can install the module using either pip or pip3 like so:
```
pip3 install runway-python
```
Now head over to [the sdk docs](https://sdk.runwayml.com) to learn how to use the Runway Model SDK.
## Docs
Reference and documentation for the Runway Model SDK is hosted at [sdk.runwayml.com](https://sdk.runwayml.com). These docs provide an overview of how to use the SDK to port your own ML models.
The [Runway Model Template repo](https://github.com/runwayml/model-template) also contains a simple example of how to get started porting a model to Runway.
See the *Importing Models into Runway* [tutorial](https://docs.runwayapp.ai/#/importing) for a walk-through illustrating how to port a model to Runway.
## Developing
If you'd like to contribute to the development of the Runway Python SDK, you can clone and modify this repository by following the instructions below.
```bash
git clone https://github.com/runwayml/model-sdk runway-model-sdk
cd runway-model-sdk
## optionally use a virtual environment
# virtualenv -p python3 venv && source venv/bin/activate
# install dependencies
python3 setup.py install
# install the dev dependencies
make dev
```
### Testing
Automated tests for the Runway Model SDK are written using `pytest` and live in the `tests/` directory. We also provide support for code coverage via `pytest-cov`.
```bash
## Create and activate a python3 virtual environment if you need to.
# virtualenv -p python3 venv && source ./venv/bin/activate
# make sure you have the development dependencies installed
make dev
# run the tests
make test
# by default pytest suppresses stdout and stderr during testing, so run tests
# like this if you'd like to see the output from your print() statements during
# testing
make test-debug
# to generate coverage statistics while running tests, use this command.
# it prints test coverage to the console and also generates a more detailed HTML
# report in htmlcov/.
make coverage
```
If you make a PR against this repo, please be sure to include automated tests to validate that your code works as expected. PRs will be automatically blocked by a [Codecov](https://codecov.io/) bot if their changes reduce the overall test coverage of the Runway Model SDK package.
### Building the Docs
The Model SDK documentation is generated from inline source code using docstrings, [Sphinx](http://www.sphinx-doc.org/en/master/), and a modified Read the Docs HTML theme. The version of Sphinx that we are using (v2.0.1) requires Python 3.
```bash
## Create and activate a python3 virtual environment if you need to.
# virtualenv -p python3 venv && source ./venv/bin/activate
# make sure you have the docs dependencies installed
make dev-docs
# build the docs
make docs
```
Your auto-generated HTML docs should now appear in `docs/build/html`.
### Questions
We have a `#model-sdk` channel in our public [Slack](https://runwayml.com/joinslack) workspace that you can use to ask questions or chat with the Runway team about this Python module. Feel free to open an issue as well!
%package help
Summary: Development documents and examples for runway-python
Provides: python3-runway-python-doc
%description help
The Runway Model SDK allows you to port new and existing machine learning models to the Runway platform. With a few lines of code, you can modify your Python model to be used and shared by others on [Runway](https://runwayml.com).
## Installing
The SDK supports Python 3.6+. You can install the module using either pip or pip3 like so:
```
pip3 install runway-python
```
Now head over to [the sdk docs](https://sdk.runwayml.com) to learn how to use the Runway Model SDK.
## Docs
Reference and documentation for the Runway Model SDK is hosted at [sdk.runwayml.com](https://sdk.runwayml.com). These docs provide an overview of how to use the SDK to port your own ML models.
The [Runway Model Template repo](https://github.com/runwayml/model-template) also contains a simple example of how to get started porting a model to Runway.
See the *Importing Models into Runway* [tutorial](https://docs.runwayapp.ai/#/importing) for a walk-through illustrating how to port a model to Runway.
## Developing
If you'd like to contribute to the development of the Runway Python SDK, you can clone and modify this repository by following the instructions below.
```bash
git clone https://github.com/runwayml/model-sdk runway-model-sdk
cd runway-model-sdk
## optionally use a virtual environment
# virtualenv -p python3 venv && source venv/bin/activate
# install dependencies
python3 setup.py install
# install the dev dependencies
make dev
```
### Testing
Automated tests for the Runway Model SDK are written using `pytest` and live in the `tests/` directory. We also provide support for code coverage via `pytest-cov`.
```bash
## Create and activate a python3 virtual environment if you need to.
# virtualenv -p python3 venv && source ./venv/bin/activate
# make sure you have the development dependencies installed
make dev
# run the tests
make test
# by default pytest suppresses stdout and stderr during testing, so run tests
# like this if you'd like to see the output from your print() statements during
# testing
make test-debug
# to generate coverage statistics while running tests, use this command.
# it prints test coverage to the console and also generates a more detailed HTML
# report in htmlcov/.
make coverage
```
If you make a PR against this repo, please be sure to include automated tests to validate that your code works as expected. PRs will be automatically blocked by a [Codecov](https://codecov.io/) bot if their changes reduce the overall test coverage of the Runway Model SDK package.
### Building the Docs
The Model SDK documentation is generated from inline source code using docstrings, [Sphinx](http://www.sphinx-doc.org/en/master/), and a modified Read the Docs HTML theme. The version of Sphinx that we are using (v2.0.1) requires Python 3.
```bash
## Create and activate a python3 virtual environment if you need to.
# virtualenv -p python3 venv && source ./venv/bin/activate
# make sure you have the docs dependencies installed
make dev-docs
# build the docs
make docs
```
Your auto-generated HTML docs should now appear in `docs/build/html`.
### Questions
We have a `#model-sdk` channel in our public [Slack](https://runwayml.com/joinslack) workspace that you can use to ask questions or chat with the Runway team about this Python module. Feel free to open an issue as well!
%prep
%autosetup -n runway-python-0.6.1
%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-runway-python -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon May 15 2023 Python_Bot