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FIX # - Bump version and CHANGELOG for release 0.7.0
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github-actions authored and Galileo-Galilei committed Mar 17, 2021
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7 changes: 6 additions & 1 deletion CHANGELOG.md
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## [Unreleased]

## [0.7.0] - 2021-03-17

### Added

- `kedro-mlflow` now supports `kedro>=0.17.1` ([#144](https://github.com/Galileo-Galilei/kedro-mlflow/issues/144)).

### Changed

- Drop support for `kedro==0.17.0`, since the kedro core team [made a breaking change in `0.17.1`](https://github.com/quantumblacklabs/kedro/blob/master/RELEASE.md#breaking-changes-to-the-api). All future plugin updates will be only compatible with `kedro>=0.17.1`.
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- Add `MlflowDataSet` for artifacts autologging
- Add `PipelineMl` class and its `pipeline_ml` factory for pipeline packaging and service

[Unreleased]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.6.0...HEAD
[Unreleased]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.0...HEAD

[0.7.0]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.6.0...0.7.0

[0.6.0]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.5.0...0.6.0

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2 changes: 1 addition & 1 deletion README.md
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----------------------------------------------------------
| Branch | Tests | Coverage | Documentation | Deployment | Activity |
|--------|-------|----------|---------------|------------|------------|
| `master` | [![test](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/test/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=workflow%3Atest+branch%3Amaster) | [![codecov](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master/graph/badge.svg)](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master)|[![Documentation](https://readthedocs.org/projects/kedro-mlflow/badge/?version=stable)](https://kedro-mlflow.readthedocs.io/en/stable/)|[![publish](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/publish/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=branch%3Amaster+workflow%3Apublish)|[![commit](https://img.shields.io/github/commits-since/Galileo-Galilei/kedro-mlflow/0.6.0)](https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.6.0...master)|
| `master` | [![test](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/test/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=workflow%3Atest+branch%3Amaster) | [![codecov](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master/graph/badge.svg)](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master)|[![Documentation](https://readthedocs.org/projects/kedro-mlflow/badge/?version=stable)](https://kedro-mlflow.readthedocs.io/en/stable/)|[![publish](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/publish/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=branch%3Amaster+workflow%3Apublish)|[![commit](https://img.shields.io/github/commits-since/Galileo-Galilei/kedro-mlflow/0.7.0)](https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.0...master)|

# What is kedro-mlflow?

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4 changes: 2 additions & 2 deletions docs/source/01_introduction/02_motivation.md
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Expand Up @@ -44,6 +44,6 @@ Above implementations have the advantage of being very straightforward and *mlfl
|Logging metrics |``catalog.yml`` |``MlflowMetricsDataSet`` |
|Logging Pipeline as model |``hooks.py`` |``KedroPipelineModel`` and ``pipeline_ml_factory``|

In the current version (``kedro_mlflow=0.6.0``), `kedro-mlflow` does not provide interface to set tags outside a Kedro ``Pipeline``. Some of above decisions are subject to debate and design decisions (for instance, metrics are often updated in a loop during each epoch / training iteration and it does not always make sense to register the metric between computation steps, e.g. as a an I/O operation after a node run).
In the current version (``kedro_mlflow=0.7.0``), `kedro-mlflow` does not provide interface to set tags outside a Kedro ``Pipeline``. Some of above decisions are subject to debate and design decisions (for instance, metrics are often updated in a loop during each epoch / training iteration and it does not always make sense to register the metric between computation steps, e.g. as a an I/O operation after a node run).

_**Note:** the version ``0.6.0`` does not need any ``MLProject`` file to use mlflow inside your Kedro project. As seen in the [introduction](./01_introduction.md), this file overlaps with Kedro configuration files._
_**Note:** the version ``0.7.0`` does not need any ``MLProject`` file to use mlflow inside your Kedro project. As seen in the [introduction](./01_introduction.md), this file overlaps with Kedro configuration files._
4 changes: 2 additions & 2 deletions docs/source/02_installation/01_installation.md
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Expand Up @@ -77,10 +77,10 @@ projects. It is developed as part of
the Kedro initiative at QuantumBlack.

Installed plugins:
kedro_mlflow: 0.6.0 (hooks:global,project)
kedro_mlflow: 0.7.0 (hooks:global,project)
```

The version ``0.6.0`` of the plugin is installed and has both global and project commands.
The version ``0.7.0`` of the plugin is installed and has both global and project commands.

That's it! You are now ready to go!

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2 changes: 1 addition & 1 deletion docs/source/03_getting_started/01_example_project.md
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Expand Up @@ -7,7 +7,7 @@ Create a conda environment and install ``kedro-mlflow`` (this will automatically
```console
conda create -n km_example python=3.6.8 --yes
conda activate km_example
pip install kedro-mlflow==0.6.0
pip install kedro-mlflow==0.7.0
```

## Install the toy project
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## Automatic parameters versioning

Parameters versioning is automatic when the ``MlflowNodeHook`` is added to [the hook list of the ``ProjectContext``](../02_installation/02_setup.md#declaring-kedro-mlflow-hooks). In ``kedro-mlflow==0.6.0``, the `mlflow.yml` configuration file has a parameter called ``flatten_dict_params`` which enables to [log as distinct parameters the (key, value) pairs of a ```Dict`` parameter](../07_python_objects/02_Hooks.md).
Parameters versioning is automatic when the ``MlflowNodeHook`` is added to [the hook list of the ``ProjectContext``](../02_installation/02_setup.md#declaring-kedro-mlflow-hooks). In ``kedro-mlflow==0.7.0``, the `mlflow.yml` configuration file has a parameter called ``flatten_dict_params`` which enables to [log as distinct parameters the (key, value) pairs of a ```Dict`` parameter](../07_python_objects/02_Hooks.md).

You **do not need any additional configuration** to benefit from parameters versioning.

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Expand Up @@ -78,7 +78,7 @@ Setting the `mlflow_tracking_uri` key of `mlflow.yml` to the url of this server

You can refer to [this issue](https://github.com/Galileo-Galilei/kedro-mlflow/issues/15) for further details.

In ``kedro-mlflow==0.6.0`` you must configure these elements by yourself. Further releases will introduce helpers for configuration.
In ``kedro-mlflow==0.7.0`` you must configure these elements by yourself. Further releases will introduce helpers for configuration.

### Can I log an artifact in a specific run?

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2 changes: 1 addition & 1 deletion kedro_mlflow/__init__.py
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"""kedro-mlflow plugin constants
"""
__version__ = "0.6.0"
__version__ = "0.7.0"
2 changes: 1 addition & 1 deletion setup.cfg
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[bumpversion]
current_version = 0.6.0
current_version = 0.7.0

[tool:pytest]
addopts = --cov=kedro_mlflow --cov-report=html tests/
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4 changes: 2 additions & 2 deletions setup.py
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Expand Up @@ -25,7 +25,7 @@ def _parse_requirements(path, encoding="utf-8"):

setup(
name=NAME,
version="0.6.0", # this will be bumped automatically by bump2version
version="0.7.0", # this will be bumped automatically by bump2version
description="A kedro-plugin to use mlflow in your kedro projects",
license="Apache Software License (Apache 2.0)",
long_description=README,
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"tests": [
"pytest>=5.4.0, <7.0.0",
"pytest-cov>=2.8.0, <3.0.0",
"pytest-lazy-fixture>=0.6.0, <1.0.0",
"pytest-lazy-fixture>=0.7.0, <1.0.0",
"pytest-mock>=3.1.0, <4.0.0",
"scikit-learn>=0.23.0, <0.25.0",
"flake8==3.8.4", # ensure consistency with pre-commit
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