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|PyPI| |Status| |Python Version| |License|
|Tests| |Codecov| |pre-commit| |Black|
.. |PyPI| image:: https://img.shields.io/pypi/v/dvc-render.svg :target: https://pypi.org/project/dvc-render/ :alt: PyPI .. |Status| image:: https://img.shields.io/pypi/status/dvc-render.svg :target: https://pypi.org/project/dvc-render/ :alt: Status .. |Python Version| image:: https://img.shields.io/pypi/pyversions/dvc-render :target: https://pypi.org/project/dvc-render :alt: Python Version .. |License| image:: https://img.shields.io/pypi/l/dvc-render :target: https://opensource.org/licenses/Apache-2.0 :alt: License .. |Tests| image:: https://github.com/iterative/dvc-render/workflows/Tests/badge.svg :target: https://github.com/iterative/dvc-render/actions?workflow=Tests :alt: Tests .. |Codecov| image:: https://codecov.io/gh/iterative/dvc-render/branch/main/graph/badge.svg :target: https://app.codecov.io/gh/iterative/dvc-render :alt: Codecov .. |pre-commit| image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white :target: https://github.com/pre-commit/pre-commit :alt: pre-commit .. |Black| image:: https://img.shields.io/badge/code%20style-black-000000.svg :target: https://github.com/psf/black :alt: Black
dvc-render is a library for rendering data stored in DVC plots format
_ into different output formats, like Vega_. It can also generate HTML and MarkDown reports containing multiple plots.
It is used internally by DVC_, DVCLive_, and Studio_.
Take data stored in DVC plots format
_ alongside plot properties in order to render a plot in different formats.
Take multiple renderers and build an HTML or MarkDown report.
Support for rendering Vega_ plots using custom of pre-defined templates.
The basic usage of rendering Vega Plots doesn't have any dependencies outside
Python>=3.8
.
Additional features are specified as optional requirements:
You can install DVC render via pip_ from PyPI_:
.. code:: console
$ pip install dvc-render
.. code-block:: python
from dvc_render import VegaRenderer
properties = {"template": "confusion", "x": "predicted", "y": "actual"}
datapoints = [
{"predicted": "B", "actual": "A"},
{"predicted": "A", "actual": "A"},
]
renderer = VegaRenderer(datapoints, "foo", **properties)
plot_content = renderer.get_filled_template()
plot_content
contains a valid Vega_ plot using the confusion matrix template.
.. code-block:: python
from dvc_render import render_html
render_html([renderer], "report.html")
Contributions are very welcome.
To learn more, see the Contributor Guide
_.
Distributed under the terms of the Apache 2.0 license
_,
DVC render is free and open source software.
If you encounter any problems,
please file an issue
_ along with a detailed description.
.. _Apache 2.0 license: https://opensource.org/licenses/Apache-2.0
.. _PyPI: https://pypi.org/
.. _file an issue: https://github.com/iterative/dvc-render/issues
.. _pip: https://pip.pypa.io/
.. github-only
.. _Contributor Guide: CONTRIBUTING.rst
.. _DVC: https://github.com/iterative/dvc
.. _DVCLive: https://github.com/iterative/dvclive
.. _Studio: https://github.com/iterative/studio
.. _Vega: https://vega.github.io/
.. _DVC plots format
: https://dvc.org/doc/user-guide/experiment-management/visualizing-plots#supported-plot-file-formats
FAQs
Dvc Render
We found that dvc-render demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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