Merge pull request #48 from rstudio/refine-readme

Refine README + docs

Author: isabelizimm

.gitignore

@@ -137,3 +137,7 @@ dmypy.json
 .pyre/
 
 NOTES.md
+
+## RStudio
+*.Rproj
+.Rproj.user

README.md

@@ -1,4 +1,4 @@
-# vetiver <img src='docs/figures/logo.png' align="right" height="139" />
+# vetiver <a href='https://rstudio.github.io/vetiver-python/'><img src='docs/figures/logo.png' align="right" height="139" /></a>
 
 <!-- badges: start -->
 
@@ -9,42 +9,63 @@ experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](h
 
 _Vetiver, the oil of tranquility, is used as a stabilizing ingredient in perfumery to preserve more volatile fragrances._
 
-Python parallel to [R vetiver](https://github.com/tidymodels/vetiver) package.
+The goal of vetiver is to provide fluent tooling to version, share, deploy, and monitor a trained model. Functions handle both recording and checking the model's input data prototype, and predicting from a remote API endpoint. The vetiver package is extensible, with generics that can support many kinds of models, and available for both Python and R. To learn more about vetiver, see the documentation at <https://vetiver.rstudio.com/>
 
-## Usage
+You can use vetiver with:
 
-`vetiver` is used to deploy a trained model to predict from a remote endpoint.
+-   [scikit-learn](https://scikit-learn.org/)
+-   [PyTorch](https://pytorch.org/)
 
-Key features include:
+## Installation
 
-- **Simple:** designed to fit into a data scientist's natural workflow
-- **Robust:** ability to check input data types to minimize type failures in a model
-- **Advanced support:** easily deploy multiple endpoints to handle pre- and post- processing
-- Based on [FastAPI](https://github.com/tiangolo/fastapi), using [OpenAPI](https://github.com/OAI/OpenAPI-Specification)
+You can install the released version of vetiver from [PyPI](https://pypi.org/project/vetiver/):
 
-## Get Started
+```python
+pip install vetiver
+```
 
-`pip install vetiver`
+And the development version from [GitHub](https://github.com/rstudio/vetiver-python) with:
 
-To begin, initialize a `VetiverModel` with a trained model and an example of data (usually training data) to built a data prototype.
+```python
+python -m pip install git+https://github.com/rstudio/vetiver-python
+```
+
+## Example
+
+A `VetiverModel()` object collects the information needed to store, version, and deploy a trained model. 
 
 ```python
-my_model = VetiverModel(model = linear_reg, ptype_data = train_data)
+from vetiver import mock, VetiverModel
+
+X, y = mock.get_mock_data()
+model = mock.get_mock_model().fit(X, y)
+
+v = VetiverModel(model, save_ptype=True, ptype_data=X)
 ```
 
-Next, you can build a model-aware API and run it locally.
+You can **version** and **share** your `VetiverModel()` by choosing a [pins](https://rstudio.github.io/pins-python/) "board" for it, including a local folder, RStudio Connect, Amazon S3, and more.
 
 ```python
-my_app = VetiverAPI(my_model)
-my_app.run()
+from pins import board_temp
+from vetiver import vetiver_pin_write
+
+model_board = board_temp(versioned = True, allow_pickle_read = True)
+vetiver_pin_write(model_board, v)
 ```
 
-To view more, see [this repo of examples](https://github.com/isabelizimm/vetiverpydemo).
+You can **deploy** your pinned `VetiverModel()` using `VetiverAPI()`, an extension of [FastAPI](https://fastapi.tiangolo.com/).
 
-## License
+```python
+from vetiver import VetiverAPI
+app = VetiverAPI(v, check_ptype = True)
+```
+
+To start a server using this object, use `app.run(port = 8080)` or your port of choice.
 
 ## Contributing
 
-This project is released with a [Contributor Code of
-Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).
-By contributing to this project, you agree to abide by its terms.
+This project is released with a [Contributor Code of Conduct](https://www.contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
+
+- For questions and discussions about deploying models, statistical modeling, and machine learning, please [post on RStudio Community](https://community.rstudio.com/new-topic?category_id=15&tags=vetiver,question).
+
+- If you think you have encountered a bug, please [submit an issue](https://github.com/rstudio/vetiver-python/issues).

docs/source/index.rst

@@ -1,6 +1,6 @@
 vetiver
 ===================================
-The goal of vetiver is to provide fluent tooling to version, share, deploy, and monitor a trained model. Functions handle both recording and checking the model’s input data prototype, and predicting from a remote API endpoint. 
+The goal of vetiver is to provide fluent tooling to version, share, deploy, and monitor a trained model. Functions handle both recording and checking the model’s input data prototype, and predicting from a remote API endpoint.
 You can use vetiver with:
 
 - `scikit-learn <https://scikit-learn.org/stable/>`_
@@ -12,16 +12,15 @@ You can install the released version of vetiver from `PyPI <https://pypi.org/pro
 
    pip install vetiver
 
-And the development version from `GitHub <https://github.com/tidymodels/vetiver-python>`_ with:
+And the development version from `GitHub <https://github.com/rstudio/vetiver-python>`_ with:
 
 .. code-block:: bash
 
-   python -m pip install git+https://github.com/tidymodels/vetiver-python
+   python -m pip install git+https://github.com/rstudio/vetiver-python
 
 
-This website documents the public API of Vetiver (for Python). See the `main Vetiver website <https://juliasilge.github.io/vetiver.dev/>`_ for
-a more holistic introduction to the API. The left-hand sidebar lists the full public
-API, and the sections below (linked to the right-hand sidebar) break it into similar groups, based on task.
+This website documents the public API of Vetiver (for Python). See `vetiver.rstudio.com <https://vetiver.rstudio.com>`_ for
+more on how to get started.
 
 .. toctree::
    :maxdepth: 2