%global _empty_manifest_terminate_build 0
Name:		python-ballet
Version:	0.19.5
Release:	1
Summary:	Core functionality for lightweight, collaborative data science projects
License:	MIT license
URL:		https://github.com/ballet/ballet
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/a6/00/405612a825efa4dac5524a14501cdbff0426ad22bc24e98bfb0e945876f5/ballet-0.19.5.tar.gz
BuildArch:	noarch

Requires:	python3-black
Requires:	python3-cookiecutter
Requires:	python3-Click
Requires:	python3-dill
Requires:	python3-dynaconf
Requires:	python3-funcy
Requires:	python3-gitpython
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Requires:	python3-dataclasses
Requires:	python3-scikit-learn
Requires:	python3-scikit-learn
Requires:	python3-category-encoders
Requires:	python3-feature-engine
Requires:	python3-featuretools-sklearn-transformer
Requires:	python3-skits
Requires:	python3-tsfresh
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Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-pytest-virtualenv
Requires:	python3-tox
Requires:	python3-responses
Requires:	python3-feature-engine
Requires:	python3-featuretools-sklearn-transformer
Requires:	python3-skits
Requires:	python3-coverage
Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-pytest-virtualenv
Requires:	python3-tox
Requires:	python3-responses
Requires:	python3-tsfresh

%description
[![PyPI Shield](https://img.shields.io/pypi/v/ballet.svg)](https://pypi.org/project/ballet)
[![Tests](https://github.com/ballet/ballet/workflows/Tests/badge.svg)](https://github.com/ballet/ballet/actions?query=workflow%3A%22Tests%22)
[![codecov Shield](https://codecov.io/gh/ballet/ballet/branch/master/graph/badge.svg)](https://codecov.io/gh/ballet/ballet)


# ballet

A **light**weight framework for collaborative, open-source data science
projects through **feat**ure engineering.

- Free software: MIT license
- Documentation: https://ballet.github.io/ballet
- Homepage: https://github.com/ballet/ballet

## Overview

Do you develop machine learning models? Do you work by yourself or on a team?
Do you share notebooks or are you committing code to a shared repository? In
contrast to successful, massively collaborative, open-source projects like
the Linux kernel, the Rails framework, Firefox, GNU, or Tensorflow, most
data science projects are developed by just a handful of people. But think if
the open-source community could leverage its ingenuity and determination to
collaboratively develop data science projects to predict the incidence of
disease in a population, to predict whether vulnerable children will be evicted
from their homes, or to predict whether learners will drop out of online
courses.

Our vision is to make collaborative data science possible by making it more
like open-source software development. Our approach is based on decomposing the
data science process into modular patches
that can then be intelligently combined, representing objects like "feature definition",
"labeling function", or "prediction task definition". Collaborators work in
parallel to write patches and submit them to a repo. The core Ballet framework
provides the underlying functionality to merge high-quality contributions,
collect modules from the file system, and compose the accepted contributions
into a single product. It also provides [Assemblé](https://github.com/ballet/ballet-assemble), a familiar notebook-based development
experience that is friendly to data scientists and other inexperienced
open-source contributors. We don't require any computing infrastructure beyond
that which is commonly used in open-source software development.

Currently, Ballet focuses on supporting collaboratively developing
*feature engineering pipelines*, an important part of many data science
projects. Individual feature definitions are represented as separate Python modules,
declaring the subset of a dataframe that they operate on and a
scikit-learn-style learned transformer that extracts feature values from the
raw data. Ballet collects individual feature definitions and composes them into a
feature engineering pipeline. At any point, a project built on Ballet can be
installed for end-to-end feature engineering on new data instances for the
same problem. How do we ensure the feature engineering pipeline is always
useful? Ballet thoroughly validates proposed feature definitions for correctness and
machine learning performance, using an extensive test suite and a novel
streaming feature definition selection algorithm. Accepted feature definitions can be
automatically merged by the [Ballet Bot](https://github.com/ballet/ballet-bot) into projects.

<img src="./docs/_static/feature_lifecycle.png" alt="Ballet Feature Lifecycle" width="400" />

## Next steps

*Are you a data owner or project maintainer that wants to organize a
collaboration?*

👉 Check out the [Ballet Maintainer Guide](https://ballet.github.io/ballet/maintainer_guide.html)

*Are you a data scientist or enthusiast that wants to join a collaboration?*

👉 Check out the [Ballet Contributor Guide](https://ballet.github.io/ballet/contributor_guide.html)

*Want to learn about how Ballet enables Better Feature Engineering™️?*

👉 Check out the [Feature Engineering Guide](https://ballet.github.io/ballet/feature_engineering_guide.html)

*Want to see a demo collaboration in progress and maybe even participate yourself?*

👉 Check out the [ballet-predict-house-prices](https://github.com/HDI-Project/ballet-predict-house-prices) project

## Source code organization

This is a quick overview to the Ballet core source code organization. For more information about contributing to Ballet core itself, see [here](https://ballet.github.io/ballet/contributing.html).

| path | description |
| ---- | ----------- |
| [`cli.py`](ballet/cli.py) | the `ballet` command line utility |
| [`client.py`](ballet/client.py) | the interactive client for users |
| [`contrib.py`](ballet/contrib.py) | collecting feature definitions from individual modules in source files in the file system |
| [`eng/base.py`](ballet/eng/base.py) | abstractions for transformers used in feature definitions, such as `BaseTransformer` |
| [`eng/{misc,missing,ts}.py`](ballet/eng/) | custom transformers for missing data, time series problems, and more |
| [`eng/external.py`](ballet/eng/external.py) | re-export of transformers from external libraries such as scikit-learn and feature_engine |
| [`feature.py`](ballet/feature.py) | the `Feature` abstraction |
| [`pipeline.py`](ballet/pipeline.py) | the `FeatureEngineeringPipeline` abstraction |
| [`project.py`](ballet/project.py) | the interface between a specific Ballet project and the core Ballet library, such as utilities to load project-specific information and the `Project` abstraction |
| [`templates/`](ballet/templates/) | cookiecutter templates for creating a new Ballet project or creating a new feature definition |
| [`templating.py`](ballet/templating.py) | user-facing functionality on top of the templates |
| [`transformer.py`](ballet/transformer.py) | wrappers for transformers that make them play nicely together in a pipeline |
| [`update.py`](ballet/update.py) | functionality to update the project template from a new upstream release |
| [`util/`](ballet/util/) | various utilities |
| [`validation/main.py`](ballet/validation/main.py) | entry point for all validation routines |
| [`validation/base.py`](ballet/validation/base.py) | abstractions used in validation such as the `FeaturePerformanceEvaluator` |
| [`validation/common.py`](ballet/validation/common.py) | common functionality used in validation, such as the ability to collect relevant changes between a current environment and a reference environment (such as a pull request vs a default branch) |
| [`validation/entropy.py`](ballet/validation/entropy.py) | statistical estimation routines used in feature definition selection algorithms, such as estimators for entropy, mutual information, and conditional mutual information |
| [`validation/feature_acceptance/`](ballet/validation/feature_acceptance/) | validation routines for feature acceptance
| [`validation/feature_pruning/`](ballet/validation/feature_pruning/) | validation routines for feature pruning |
| [`validation/feature_api/`](ballet/validation/feature_api/) | validation routines for feature APIs |
| [`validation/project_structure/`](ballet/validation/project_structure/) | validation routines for project structure |


# History

## 0.19.5 (2021-07-17)

* Fix bug with deepcopying `ballet.pipeline.FeatureEngineeringPipeline`

## 0.19.4 (2021-07-17)

* Fix bug with deepcopying `ballet.eng.base.SubsetTransformer` ([#90](https://github.com/ballet/ballet/issues/90))
* Add `ballet.drop_missing_targets` primitive

## 0.19.3 (2021-06-28)

* Support missing targets in discovery and feature performance evaluation ([#89](https://github.com/ballet/ballet/pull/89))
* Add `ninputs` to summary statistics in `ballet.discovery.discover`

## 0.19.2 (2021-06-21)

* Improve discrete column detection in the case of many repeated values
* Add `ncontinuous` and `ndiscrete` to summary statistics in `ballet.discovery.discover`

## 0.19.1 (2021-06-20)

* Defer computation of some expensive summary statistics in `ballet.discovery.discover`

## 0.19.0 (2021-06-16)

* Support callable as feature input ([#88](https://github.com/ballet/ballet/pull/88))

## 0.18.0 (2021-06-06)

* Added [Consumer Guide](https://ballet.github.io/ballet/consumer_guide.html)
* Can use Ballet together with MLBlocks to engineer features and then use additional preprocessing and ML components ([#86](https://github.com/ballet/ballet/pull/86))
* Can wrap the extracted feature matrix in a data frame with named columns derived from ``feature.output`` or ``feature.name``
* Implemented `ballet.encoder.EncoderPipeline` to (mostly) mirror `ballet.pipeline.FeatureEngineeringPipeline`
* Can specify the dataset used for fitting the pipeline in the engineer-features CLI via `--train-dir path/to/train/dir`

## 0.17.0 (2021-05-24)

* Support nested transformers, both with nested features and with input/transformer tuples wrapped with SubsetTransformers ([#82](https://github.com/ballet/ballet/pull/82))
* Allow `Client.discover` to skip summary statistics if development dataset cannot be loaded or if features produce errors

## 0.16.0 (2021-05-22)

* Add `Client.discover` functionality ([#80](https://github.com/ballet/ballet/pull/80))
* Switch the order of `NullFiller` parameters to more closely resemble `fillna` signature

## 0.15.2 (2021-05-14)

* Operate columnwise in `VarianceThresholdAccepter`, rather than computing the variance of
    the entire feature group.

## 0.15.1 (2021-05-12)

* Add debug logging for new accepters

## 0.15.0 (2021-05-12)

* Add `VarianceThresholdAccepter`, `MutualInformationAccepter`, and `CompoundAccepter` ([#76](https://github.com/ballet/ballet/pull/76))

## 0.14.0 (2021-05-11)

* Support using holdout data splits in validation ([#75](https://github.com/ballet/ballet/pull/75))
* Fix CLI program name in projects ([#74](https://github.com/ballet/ballet/pull/74))
* Fix bug with `load_config` usage in python REPL ([#73](https://github.com/ballet/ballet/pull/73))
* Reorganize external feature engineering primitives to `ballet/eng/external/**.py`. Imports like `from ballet.eng.external import MyPrimitive` are unaffected.

## 0.13.1 (2021-04-02)

* Fix upgrade check in `ballet update-project-template` to migrate away from deprecated PyPI XML-RPC API.

## 0.13.0 (2021-03-30)

* Fix links in project template

## 0.12.0 (2021-03-10)

* Automate creation of GitHub repository in quickstart

## 0.11.0 (2021-03-04)

* Allow validation to be run from topic branches locally

## 0.10.0 (2021-02-23)

* Add `Project.version` property

## 0.9.0 (2021-02-16)

* Add support for managed branching via `ballet start-new-feature --branching` (defaults to enabled)
* Remove confusing `ballet.project.config` attribute
* Implement `ballet.project.load_config` as a better alternative, and use this in the project template's `load_data`

## 0.8.2 (2021-02-16)

* Fix bug with `str(t)` or `repr(t)` for `DelegatingRobustTransformer`

## 0.8.1 (2021-02-16)

* Fix bug with `str(t)` or `repr(t)` for `SimpleFunctionTransformer`

## 0.8.0 (2021-02-02)

* Fix bug with detecting updates to Ballet due to PyPI API outage
* Fix some dependency conflicts
* Reference ballet-assemble in project template
* Bump feature_engine to 1.0

## 0.7.11 (2020-09-16)

* Reduce verbosity of conversion approach logging by moving some messages to TRACE level
* Implement "else" transformer for `ConditionalTransformer`
* Improve GFSSF iteration logging

## 0.7.10 (2020-09-08)

* Fix bug with different treatment of y_df and y; now, y_df is passed to the feature engineering pipeline, and y is passed to the feature validation routines as applicable.
* Switch back to using Gitter

## 0.7.9 (2020-08-15)

* Add give_advice feature for FeatureAPICheck and other checks to log message on how to fix failure
* Improve logging of GFSSFAccepter and GFSSFPruner
* Improve `__str__` for DelegatingRobustTransformer and consequently consumers
* Change default log format to SIMPLE_LOG_FORMAT
* Various bug fixes and improvements

## 0.7.8 (2020-08-13)

* Add CanTransformNewRowsCheck to feature API checks

## 0.7.7 (2020-08-12)

* Support `None` as the transformer in a `Feature`, it will be automatically converted to an `IdentityTransformer`
* Implement `ColumnSelector`
* Update docs
* Various bug fixes and improvements

## 0.7.6 (2020-08-12)

* Re-export feature engineering primitives from various libraries
* Show type annotations in docs
* Update guides
* Various bug fixes and improvements

## 0.7.5 (2020-08-03)

* Make validator parameters configurable in ballet.yml file (e.g. λ_1 and λ_2 for GFSSF algorithms)
* Support dynaconf 3.x

## 0.7.4 (2020-07-22)

* Accept logger names, as well as logger instances, in `ballet.util.log.enable`
* Updated docs

## 0.7.3 (2020-07-21)

* Add `load_data` method with built-in caching to project API
* Fix bug in GFSSF accepter
* Always use encoded target during validation
* Various bug fixes and improvements

## 0.7.2 (2020-07-21)

* Add sample analysis notebook to project template
* Add binder url/badge to project template
* Fix bug with enabling logging with multiple loggers

## 0.7.1 (2020-07-20)

* Add client for easy interactive usage (`ballet.b`)
* Add binder setup to project template

## 0.7 (2020-07-17)

* Revamp project template: update project structure, create single API via FeatureEngineeringProject, use and add support for pyinvoke, revamp build into engineer_features, support repolockr bot
* Improve ballet.project.Project: can create by ascending from given path, can create from current working directory, can resolve arbitrary project symbol, exposes project's API
* Check for and notify of new release of ballet during project update (`ballet update-project-template`)
* Add ComputedValueTransformer to ballet.eng
* Move stacklog to separate project and install it
* Add validators that {never,always} accept submissions
* Add feature API checks to ensure that the feature can fit and transform a single row
* Add feature engineering guide to documentation and significantly expand contributor guide
* Add bot installation instructions to maintainer guide
* Add type annotations throughout
* Drop support for py35, add support for py38
* Deprecate modeling code
* Various bug fixes and improvements

## 0.6 (2019-11-12)

* Implement GFSSF validators and random validators
* Improve validators and allow validators to be configured in ballet.yml
* Improve project template
* Create ballet CLI
* Bug fixes and performance improvements

## 0.5 (2018-10-14)

* Add project template and ballet-quickstart command
* Add project structure checks and feature API checks
* Implement multi-stage validation routine driver

## 0.4 (2018-09-21)

* Implement `Modeler` for versatile modeling and evaluation
* Change project name

## 0.3 (2018-04-28)

* Implement `PullRequestFeatureValidator`
* Add `util.travis`, `util.modutil`, `util.git` util modules

## 0.2 (2018-04-11)

* Implement `ArrayLikeEqualityTestingMixin`
* Implement `collect_contrib_features`

## 0.1 (2018-04-08)

* First release on PyPI




%package -n python3-ballet
Summary:	Core functionality for lightweight, collaborative data science projects
Provides:	python-ballet
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-ballet
[![PyPI Shield](https://img.shields.io/pypi/v/ballet.svg)](https://pypi.org/project/ballet)
[![Tests](https://github.com/ballet/ballet/workflows/Tests/badge.svg)](https://github.com/ballet/ballet/actions?query=workflow%3A%22Tests%22)
[![codecov Shield](https://codecov.io/gh/ballet/ballet/branch/master/graph/badge.svg)](https://codecov.io/gh/ballet/ballet)


# ballet

A **light**weight framework for collaborative, open-source data science
projects through **feat**ure engineering.

- Free software: MIT license
- Documentation: https://ballet.github.io/ballet
- Homepage: https://github.com/ballet/ballet

## Overview

Do you develop machine learning models? Do you work by yourself or on a team?
Do you share notebooks or are you committing code to a shared repository? In
contrast to successful, massively collaborative, open-source projects like
the Linux kernel, the Rails framework, Firefox, GNU, or Tensorflow, most
data science projects are developed by just a handful of people. But think if
the open-source community could leverage its ingenuity and determination to
collaboratively develop data science projects to predict the incidence of
disease in a population, to predict whether vulnerable children will be evicted
from their homes, or to predict whether learners will drop out of online
courses.

Our vision is to make collaborative data science possible by making it more
like open-source software development. Our approach is based on decomposing the
data science process into modular patches
that can then be intelligently combined, representing objects like "feature definition",
"labeling function", or "prediction task definition". Collaborators work in
parallel to write patches and submit them to a repo. The core Ballet framework
provides the underlying functionality to merge high-quality contributions,
collect modules from the file system, and compose the accepted contributions
into a single product. It also provides [Assemblé](https://github.com/ballet/ballet-assemble), a familiar notebook-based development
experience that is friendly to data scientists and other inexperienced
open-source contributors. We don't require any computing infrastructure beyond
that which is commonly used in open-source software development.

Currently, Ballet focuses on supporting collaboratively developing
*feature engineering pipelines*, an important part of many data science
projects. Individual feature definitions are represented as separate Python modules,
declaring the subset of a dataframe that they operate on and a
scikit-learn-style learned transformer that extracts feature values from the
raw data. Ballet collects individual feature definitions and composes them into a
feature engineering pipeline. At any point, a project built on Ballet can be
installed for end-to-end feature engineering on new data instances for the
same problem. How do we ensure the feature engineering pipeline is always
useful? Ballet thoroughly validates proposed feature definitions for correctness and
machine learning performance, using an extensive test suite and a novel
streaming feature definition selection algorithm. Accepted feature definitions can be
automatically merged by the [Ballet Bot](https://github.com/ballet/ballet-bot) into projects.

<img src="./docs/_static/feature_lifecycle.png" alt="Ballet Feature Lifecycle" width="400" />

## Next steps

*Are you a data owner or project maintainer that wants to organize a
collaboration?*

👉 Check out the [Ballet Maintainer Guide](https://ballet.github.io/ballet/maintainer_guide.html)

*Are you a data scientist or enthusiast that wants to join a collaboration?*

👉 Check out the [Ballet Contributor Guide](https://ballet.github.io/ballet/contributor_guide.html)

*Want to learn about how Ballet enables Better Feature Engineering™️?*

👉 Check out the [Feature Engineering Guide](https://ballet.github.io/ballet/feature_engineering_guide.html)

*Want to see a demo collaboration in progress and maybe even participate yourself?*

👉 Check out the [ballet-predict-house-prices](https://github.com/HDI-Project/ballet-predict-house-prices) project

## Source code organization

This is a quick overview to the Ballet core source code organization. For more information about contributing to Ballet core itself, see [here](https://ballet.github.io/ballet/contributing.html).

| path | description |
| ---- | ----------- |
| [`cli.py`](ballet/cli.py) | the `ballet` command line utility |
| [`client.py`](ballet/client.py) | the interactive client for users |
| [`contrib.py`](ballet/contrib.py) | collecting feature definitions from individual modules in source files in the file system |
| [`eng/base.py`](ballet/eng/base.py) | abstractions for transformers used in feature definitions, such as `BaseTransformer` |
| [`eng/{misc,missing,ts}.py`](ballet/eng/) | custom transformers for missing data, time series problems, and more |
| [`eng/external.py`](ballet/eng/external.py) | re-export of transformers from external libraries such as scikit-learn and feature_engine |
| [`feature.py`](ballet/feature.py) | the `Feature` abstraction |
| [`pipeline.py`](ballet/pipeline.py) | the `FeatureEngineeringPipeline` abstraction |
| [`project.py`](ballet/project.py) | the interface between a specific Ballet project and the core Ballet library, such as utilities to load project-specific information and the `Project` abstraction |
| [`templates/`](ballet/templates/) | cookiecutter templates for creating a new Ballet project or creating a new feature definition |
| [`templating.py`](ballet/templating.py) | user-facing functionality on top of the templates |
| [`transformer.py`](ballet/transformer.py) | wrappers for transformers that make them play nicely together in a pipeline |
| [`update.py`](ballet/update.py) | functionality to update the project template from a new upstream release |
| [`util/`](ballet/util/) | various utilities |
| [`validation/main.py`](ballet/validation/main.py) | entry point for all validation routines |
| [`validation/base.py`](ballet/validation/base.py) | abstractions used in validation such as the `FeaturePerformanceEvaluator` |
| [`validation/common.py`](ballet/validation/common.py) | common functionality used in validation, such as the ability to collect relevant changes between a current environment and a reference environment (such as a pull request vs a default branch) |
| [`validation/entropy.py`](ballet/validation/entropy.py) | statistical estimation routines used in feature definition selection algorithms, such as estimators for entropy, mutual information, and conditional mutual information |
| [`validation/feature_acceptance/`](ballet/validation/feature_acceptance/) | validation routines for feature acceptance
| [`validation/feature_pruning/`](ballet/validation/feature_pruning/) | validation routines for feature pruning |
| [`validation/feature_api/`](ballet/validation/feature_api/) | validation routines for feature APIs |
| [`validation/project_structure/`](ballet/validation/project_structure/) | validation routines for project structure |


# History

## 0.19.5 (2021-07-17)

* Fix bug with deepcopying `ballet.pipeline.FeatureEngineeringPipeline`

## 0.19.4 (2021-07-17)

* Fix bug with deepcopying `ballet.eng.base.SubsetTransformer` ([#90](https://github.com/ballet/ballet/issues/90))
* Add `ballet.drop_missing_targets` primitive

## 0.19.3 (2021-06-28)

* Support missing targets in discovery and feature performance evaluation ([#89](https://github.com/ballet/ballet/pull/89))
* Add `ninputs` to summary statistics in `ballet.discovery.discover`

## 0.19.2 (2021-06-21)

* Improve discrete column detection in the case of many repeated values
* Add `ncontinuous` and `ndiscrete` to summary statistics in `ballet.discovery.discover`

## 0.19.1 (2021-06-20)

* Defer computation of some expensive summary statistics in `ballet.discovery.discover`

## 0.19.0 (2021-06-16)

* Support callable as feature input ([#88](https://github.com/ballet/ballet/pull/88))

## 0.18.0 (2021-06-06)

* Added [Consumer Guide](https://ballet.github.io/ballet/consumer_guide.html)
* Can use Ballet together with MLBlocks to engineer features and then use additional preprocessing and ML components ([#86](https://github.com/ballet/ballet/pull/86))
* Can wrap the extracted feature matrix in a data frame with named columns derived from ``feature.output`` or ``feature.name``
* Implemented `ballet.encoder.EncoderPipeline` to (mostly) mirror `ballet.pipeline.FeatureEngineeringPipeline`
* Can specify the dataset used for fitting the pipeline in the engineer-features CLI via `--train-dir path/to/train/dir`

## 0.17.0 (2021-05-24)

* Support nested transformers, both with nested features and with input/transformer tuples wrapped with SubsetTransformers ([#82](https://github.com/ballet/ballet/pull/82))
* Allow `Client.discover` to skip summary statistics if development dataset cannot be loaded or if features produce errors

## 0.16.0 (2021-05-22)

* Add `Client.discover` functionality ([#80](https://github.com/ballet/ballet/pull/80))
* Switch the order of `NullFiller` parameters to more closely resemble `fillna` signature

## 0.15.2 (2021-05-14)

* Operate columnwise in `VarianceThresholdAccepter`, rather than computing the variance of
    the entire feature group.

## 0.15.1 (2021-05-12)

* Add debug logging for new accepters

## 0.15.0 (2021-05-12)

* Add `VarianceThresholdAccepter`, `MutualInformationAccepter`, and `CompoundAccepter` ([#76](https://github.com/ballet/ballet/pull/76))

## 0.14.0 (2021-05-11)

* Support using holdout data splits in validation ([#75](https://github.com/ballet/ballet/pull/75))
* Fix CLI program name in projects ([#74](https://github.com/ballet/ballet/pull/74))
* Fix bug with `load_config` usage in python REPL ([#73](https://github.com/ballet/ballet/pull/73))
* Reorganize external feature engineering primitives to `ballet/eng/external/**.py`. Imports like `from ballet.eng.external import MyPrimitive` are unaffected.

## 0.13.1 (2021-04-02)

* Fix upgrade check in `ballet update-project-template` to migrate away from deprecated PyPI XML-RPC API.

## 0.13.0 (2021-03-30)

* Fix links in project template

## 0.12.0 (2021-03-10)

* Automate creation of GitHub repository in quickstart

## 0.11.0 (2021-03-04)

* Allow validation to be run from topic branches locally

## 0.10.0 (2021-02-23)

* Add `Project.version` property

## 0.9.0 (2021-02-16)

* Add support for managed branching via `ballet start-new-feature --branching` (defaults to enabled)
* Remove confusing `ballet.project.config` attribute
* Implement `ballet.project.load_config` as a better alternative, and use this in the project template's `load_data`

## 0.8.2 (2021-02-16)

* Fix bug with `str(t)` or `repr(t)` for `DelegatingRobustTransformer`

## 0.8.1 (2021-02-16)

* Fix bug with `str(t)` or `repr(t)` for `SimpleFunctionTransformer`

## 0.8.0 (2021-02-02)

* Fix bug with detecting updates to Ballet due to PyPI API outage
* Fix some dependency conflicts
* Reference ballet-assemble in project template
* Bump feature_engine to 1.0

## 0.7.11 (2020-09-16)

* Reduce verbosity of conversion approach logging by moving some messages to TRACE level
* Implement "else" transformer for `ConditionalTransformer`
* Improve GFSSF iteration logging

## 0.7.10 (2020-09-08)

* Fix bug with different treatment of y_df and y; now, y_df is passed to the feature engineering pipeline, and y is passed to the feature validation routines as applicable.
* Switch back to using Gitter

## 0.7.9 (2020-08-15)

* Add give_advice feature for FeatureAPICheck and other checks to log message on how to fix failure
* Improve logging of GFSSFAccepter and GFSSFPruner
* Improve `__str__` for DelegatingRobustTransformer and consequently consumers
* Change default log format to SIMPLE_LOG_FORMAT
* Various bug fixes and improvements

## 0.7.8 (2020-08-13)

* Add CanTransformNewRowsCheck to feature API checks

## 0.7.7 (2020-08-12)

* Support `None` as the transformer in a `Feature`, it will be automatically converted to an `IdentityTransformer`
* Implement `ColumnSelector`
* Update docs
* Various bug fixes and improvements

## 0.7.6 (2020-08-12)

* Re-export feature engineering primitives from various libraries
* Show type annotations in docs
* Update guides
* Various bug fixes and improvements

## 0.7.5 (2020-08-03)

* Make validator parameters configurable in ballet.yml file (e.g. λ_1 and λ_2 for GFSSF algorithms)
* Support dynaconf 3.x

## 0.7.4 (2020-07-22)

* Accept logger names, as well as logger instances, in `ballet.util.log.enable`
* Updated docs

## 0.7.3 (2020-07-21)

* Add `load_data` method with built-in caching to project API
* Fix bug in GFSSF accepter
* Always use encoded target during validation
* Various bug fixes and improvements

## 0.7.2 (2020-07-21)

* Add sample analysis notebook to project template
* Add binder url/badge to project template
* Fix bug with enabling logging with multiple loggers

## 0.7.1 (2020-07-20)

* Add client for easy interactive usage (`ballet.b`)
* Add binder setup to project template

## 0.7 (2020-07-17)

* Revamp project template: update project structure, create single API via FeatureEngineeringProject, use and add support for pyinvoke, revamp build into engineer_features, support repolockr bot
* Improve ballet.project.Project: can create by ascending from given path, can create from current working directory, can resolve arbitrary project symbol, exposes project's API
* Check for and notify of new release of ballet during project update (`ballet update-project-template`)
* Add ComputedValueTransformer to ballet.eng
* Move stacklog to separate project and install it
* Add validators that {never,always} accept submissions
* Add feature API checks to ensure that the feature can fit and transform a single row
* Add feature engineering guide to documentation and significantly expand contributor guide
* Add bot installation instructions to maintainer guide
* Add type annotations throughout
* Drop support for py35, add support for py38
* Deprecate modeling code
* Various bug fixes and improvements

## 0.6 (2019-11-12)

* Implement GFSSF validators and random validators
* Improve validators and allow validators to be configured in ballet.yml
* Improve project template
* Create ballet CLI
* Bug fixes and performance improvements

## 0.5 (2018-10-14)

* Add project template and ballet-quickstart command
* Add project structure checks and feature API checks
* Implement multi-stage validation routine driver

## 0.4 (2018-09-21)

* Implement `Modeler` for versatile modeling and evaluation
* Change project name

## 0.3 (2018-04-28)

* Implement `PullRequestFeatureValidator`
* Add `util.travis`, `util.modutil`, `util.git` util modules

## 0.2 (2018-04-11)

* Implement `ArrayLikeEqualityTestingMixin`
* Implement `collect_contrib_features`

## 0.1 (2018-04-08)

* First release on PyPI




%package help
Summary:	Development documents and examples for ballet
Provides:	python3-ballet-doc
%description help
[![PyPI Shield](https://img.shields.io/pypi/v/ballet.svg)](https://pypi.org/project/ballet)
[![Tests](https://github.com/ballet/ballet/workflows/Tests/badge.svg)](https://github.com/ballet/ballet/actions?query=workflow%3A%22Tests%22)
[![codecov Shield](https://codecov.io/gh/ballet/ballet/branch/master/graph/badge.svg)](https://codecov.io/gh/ballet/ballet)


# ballet

A **light**weight framework for collaborative, open-source data science
projects through **feat**ure engineering.

- Free software: MIT license
- Documentation: https://ballet.github.io/ballet
- Homepage: https://github.com/ballet/ballet

## Overview

Do you develop machine learning models? Do you work by yourself or on a team?
Do you share notebooks or are you committing code to a shared repository? In
contrast to successful, massively collaborative, open-source projects like
the Linux kernel, the Rails framework, Firefox, GNU, or Tensorflow, most
data science projects are developed by just a handful of people. But think if
the open-source community could leverage its ingenuity and determination to
collaboratively develop data science projects to predict the incidence of
disease in a population, to predict whether vulnerable children will be evicted
from their homes, or to predict whether learners will drop out of online
courses.

Our vision is to make collaborative data science possible by making it more
like open-source software development. Our approach is based on decomposing the
data science process into modular patches
that can then be intelligently combined, representing objects like "feature definition",
"labeling function", or "prediction task definition". Collaborators work in
parallel to write patches and submit them to a repo. The core Ballet framework
provides the underlying functionality to merge high-quality contributions,
collect modules from the file system, and compose the accepted contributions
into a single product. It also provides [Assemblé](https://github.com/ballet/ballet-assemble), a familiar notebook-based development
experience that is friendly to data scientists and other inexperienced
open-source contributors. We don't require any computing infrastructure beyond
that which is commonly used in open-source software development.

Currently, Ballet focuses on supporting collaboratively developing
*feature engineering pipelines*, an important part of many data science
projects. Individual feature definitions are represented as separate Python modules,
declaring the subset of a dataframe that they operate on and a
scikit-learn-style learned transformer that extracts feature values from the
raw data. Ballet collects individual feature definitions and composes them into a
feature engineering pipeline. At any point, a project built on Ballet can be
installed for end-to-end feature engineering on new data instances for the
same problem. How do we ensure the feature engineering pipeline is always
useful? Ballet thoroughly validates proposed feature definitions for correctness and
machine learning performance, using an extensive test suite and a novel
streaming feature definition selection algorithm. Accepted feature definitions can be
automatically merged by the [Ballet Bot](https://github.com/ballet/ballet-bot) into projects.

<img src="./docs/_static/feature_lifecycle.png" alt="Ballet Feature Lifecycle" width="400" />

## Next steps

*Are you a data owner or project maintainer that wants to organize a
collaboration?*

👉 Check out the [Ballet Maintainer Guide](https://ballet.github.io/ballet/maintainer_guide.html)

*Are you a data scientist or enthusiast that wants to join a collaboration?*

👉 Check out the [Ballet Contributor Guide](https://ballet.github.io/ballet/contributor_guide.html)

*Want to learn about how Ballet enables Better Feature Engineering™️?*

👉 Check out the [Feature Engineering Guide](https://ballet.github.io/ballet/feature_engineering_guide.html)

*Want to see a demo collaboration in progress and maybe even participate yourself?*

👉 Check out the [ballet-predict-house-prices](https://github.com/HDI-Project/ballet-predict-house-prices) project

## Source code organization

This is a quick overview to the Ballet core source code organization. For more information about contributing to Ballet core itself, see [here](https://ballet.github.io/ballet/contributing.html).

| path | description |
| ---- | ----------- |
| [`cli.py`](ballet/cli.py) | the `ballet` command line utility |
| [`client.py`](ballet/client.py) | the interactive client for users |
| [`contrib.py`](ballet/contrib.py) | collecting feature definitions from individual modules in source files in the file system |
| [`eng/base.py`](ballet/eng/base.py) | abstractions for transformers used in feature definitions, such as `BaseTransformer` |
| [`eng/{misc,missing,ts}.py`](ballet/eng/) | custom transformers for missing data, time series problems, and more |
| [`eng/external.py`](ballet/eng/external.py) | re-export of transformers from external libraries such as scikit-learn and feature_engine |
| [`feature.py`](ballet/feature.py) | the `Feature` abstraction |
| [`pipeline.py`](ballet/pipeline.py) | the `FeatureEngineeringPipeline` abstraction |
| [`project.py`](ballet/project.py) | the interface between a specific Ballet project and the core Ballet library, such as utilities to load project-specific information and the `Project` abstraction |
| [`templates/`](ballet/templates/) | cookiecutter templates for creating a new Ballet project or creating a new feature definition |
| [`templating.py`](ballet/templating.py) | user-facing functionality on top of the templates |
| [`transformer.py`](ballet/transformer.py) | wrappers for transformers that make them play nicely together in a pipeline |
| [`update.py`](ballet/update.py) | functionality to update the project template from a new upstream release |
| [`util/`](ballet/util/) | various utilities |
| [`validation/main.py`](ballet/validation/main.py) | entry point for all validation routines |
| [`validation/base.py`](ballet/validation/base.py) | abstractions used in validation such as the `FeaturePerformanceEvaluator` |
| [`validation/common.py`](ballet/validation/common.py) | common functionality used in validation, such as the ability to collect relevant changes between a current environment and a reference environment (such as a pull request vs a default branch) |
| [`validation/entropy.py`](ballet/validation/entropy.py) | statistical estimation routines used in feature definition selection algorithms, such as estimators for entropy, mutual information, and conditional mutual information |
| [`validation/feature_acceptance/`](ballet/validation/feature_acceptance/) | validation routines for feature acceptance
| [`validation/feature_pruning/`](ballet/validation/feature_pruning/) | validation routines for feature pruning |
| [`validation/feature_api/`](ballet/validation/feature_api/) | validation routines for feature APIs |
| [`validation/project_structure/`](ballet/validation/project_structure/) | validation routines for project structure |


# History

## 0.19.5 (2021-07-17)

* Fix bug with deepcopying `ballet.pipeline.FeatureEngineeringPipeline`

## 0.19.4 (2021-07-17)

* Fix bug with deepcopying `ballet.eng.base.SubsetTransformer` ([#90](https://github.com/ballet/ballet/issues/90))
* Add `ballet.drop_missing_targets` primitive

## 0.19.3 (2021-06-28)

* Support missing targets in discovery and feature performance evaluation ([#89](https://github.com/ballet/ballet/pull/89))
* Add `ninputs` to summary statistics in `ballet.discovery.discover`

## 0.19.2 (2021-06-21)

* Improve discrete column detection in the case of many repeated values
* Add `ncontinuous` and `ndiscrete` to summary statistics in `ballet.discovery.discover`

## 0.19.1 (2021-06-20)

* Defer computation of some expensive summary statistics in `ballet.discovery.discover`

## 0.19.0 (2021-06-16)

* Support callable as feature input ([#88](https://github.com/ballet/ballet/pull/88))

## 0.18.0 (2021-06-06)

* Added [Consumer Guide](https://ballet.github.io/ballet/consumer_guide.html)
* Can use Ballet together with MLBlocks to engineer features and then use additional preprocessing and ML components ([#86](https://github.com/ballet/ballet/pull/86))
* Can wrap the extracted feature matrix in a data frame with named columns derived from ``feature.output`` or ``feature.name``
* Implemented `ballet.encoder.EncoderPipeline` to (mostly) mirror `ballet.pipeline.FeatureEngineeringPipeline`
* Can specify the dataset used for fitting the pipeline in the engineer-features CLI via `--train-dir path/to/train/dir`

## 0.17.0 (2021-05-24)

* Support nested transformers, both with nested features and with input/transformer tuples wrapped with SubsetTransformers ([#82](https://github.com/ballet/ballet/pull/82))
* Allow `Client.discover` to skip summary statistics if development dataset cannot be loaded or if features produce errors

## 0.16.0 (2021-05-22)

* Add `Client.discover` functionality ([#80](https://github.com/ballet/ballet/pull/80))
* Switch the order of `NullFiller` parameters to more closely resemble `fillna` signature

## 0.15.2 (2021-05-14)

* Operate columnwise in `VarianceThresholdAccepter`, rather than computing the variance of
    the entire feature group.

## 0.15.1 (2021-05-12)

* Add debug logging for new accepters

## 0.15.0 (2021-05-12)

* Add `VarianceThresholdAccepter`, `MutualInformationAccepter`, and `CompoundAccepter` ([#76](https://github.com/ballet/ballet/pull/76))

## 0.14.0 (2021-05-11)

* Support using holdout data splits in validation ([#75](https://github.com/ballet/ballet/pull/75))
* Fix CLI program name in projects ([#74](https://github.com/ballet/ballet/pull/74))
* Fix bug with `load_config` usage in python REPL ([#73](https://github.com/ballet/ballet/pull/73))
* Reorganize external feature engineering primitives to `ballet/eng/external/**.py`. Imports like `from ballet.eng.external import MyPrimitive` are unaffected.

## 0.13.1 (2021-04-02)

* Fix upgrade check in `ballet update-project-template` to migrate away from deprecated PyPI XML-RPC API.

## 0.13.0 (2021-03-30)

* Fix links in project template

## 0.12.0 (2021-03-10)

* Automate creation of GitHub repository in quickstart

## 0.11.0 (2021-03-04)

* Allow validation to be run from topic branches locally

## 0.10.0 (2021-02-23)

* Add `Project.version` property

## 0.9.0 (2021-02-16)

* Add support for managed branching via `ballet start-new-feature --branching` (defaults to enabled)
* Remove confusing `ballet.project.config` attribute
* Implement `ballet.project.load_config` as a better alternative, and use this in the project template's `load_data`

## 0.8.2 (2021-02-16)

* Fix bug with `str(t)` or `repr(t)` for `DelegatingRobustTransformer`

## 0.8.1 (2021-02-16)

* Fix bug with `str(t)` or `repr(t)` for `SimpleFunctionTransformer`

## 0.8.0 (2021-02-02)

* Fix bug with detecting updates to Ballet due to PyPI API outage
* Fix some dependency conflicts
* Reference ballet-assemble in project template
* Bump feature_engine to 1.0

## 0.7.11 (2020-09-16)

* Reduce verbosity of conversion approach logging by moving some messages to TRACE level
* Implement "else" transformer for `ConditionalTransformer`
* Improve GFSSF iteration logging

## 0.7.10 (2020-09-08)

* Fix bug with different treatment of y_df and y; now, y_df is passed to the feature engineering pipeline, and y is passed to the feature validation routines as applicable.
* Switch back to using Gitter

## 0.7.9 (2020-08-15)

* Add give_advice feature for FeatureAPICheck and other checks to log message on how to fix failure
* Improve logging of GFSSFAccepter and GFSSFPruner
* Improve `__str__` for DelegatingRobustTransformer and consequently consumers
* Change default log format to SIMPLE_LOG_FORMAT
* Various bug fixes and improvements

## 0.7.8 (2020-08-13)

* Add CanTransformNewRowsCheck to feature API checks

## 0.7.7 (2020-08-12)

* Support `None` as the transformer in a `Feature`, it will be automatically converted to an `IdentityTransformer`
* Implement `ColumnSelector`
* Update docs
* Various bug fixes and improvements

## 0.7.6 (2020-08-12)

* Re-export feature engineering primitives from various libraries
* Show type annotations in docs
* Update guides
* Various bug fixes and improvements

## 0.7.5 (2020-08-03)

* Make validator parameters configurable in ballet.yml file (e.g. λ_1 and λ_2 for GFSSF algorithms)
* Support dynaconf 3.x

## 0.7.4 (2020-07-22)

* Accept logger names, as well as logger instances, in `ballet.util.log.enable`
* Updated docs

## 0.7.3 (2020-07-21)

* Add `load_data` method with built-in caching to project API
* Fix bug in GFSSF accepter
* Always use encoded target during validation
* Various bug fixes and improvements

## 0.7.2 (2020-07-21)

* Add sample analysis notebook to project template
* Add binder url/badge to project template
* Fix bug with enabling logging with multiple loggers

## 0.7.1 (2020-07-20)

* Add client for easy interactive usage (`ballet.b`)
* Add binder setup to project template

## 0.7 (2020-07-17)

* Revamp project template: update project structure, create single API via FeatureEngineeringProject, use and add support for pyinvoke, revamp build into engineer_features, support repolockr bot
* Improve ballet.project.Project: can create by ascending from given path, can create from current working directory, can resolve arbitrary project symbol, exposes project's API
* Check for and notify of new release of ballet during project update (`ballet update-project-template`)
* Add ComputedValueTransformer to ballet.eng
* Move stacklog to separate project and install it
* Add validators that {never,always} accept submissions
* Add feature API checks to ensure that the feature can fit and transform a single row
* Add feature engineering guide to documentation and significantly expand contributor guide
* Add bot installation instructions to maintainer guide
* Add type annotations throughout
* Drop support for py35, add support for py38
* Deprecate modeling code
* Various bug fixes and improvements

## 0.6 (2019-11-12)

* Implement GFSSF validators and random validators
* Improve validators and allow validators to be configured in ballet.yml
* Improve project template
* Create ballet CLI
* Bug fixes and performance improvements

## 0.5 (2018-10-14)

* Add project template and ballet-quickstart command
* Add project structure checks and feature API checks
* Implement multi-stage validation routine driver

## 0.4 (2018-09-21)

* Implement `Modeler` for versatile modeling and evaluation
* Change project name

## 0.3 (2018-04-28)

* Implement `PullRequestFeatureValidator`
* Add `util.travis`, `util.modutil`, `util.git` util modules

## 0.2 (2018-04-11)

* Implement `ArrayLikeEqualityTestingMixin`
* Implement `collect_contrib_features`

## 0.1 (2018-04-08)

* First release on PyPI




%prep
%autosetup -n ballet-0.19.5

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

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

%changelog
* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.19.5-1
- Package Spec generated