GitLocker: The Coding Marketplace

Description:

ballet 0.19.5

ballet
A lightweight framework for collaborative, open-source data science
projects through feature 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, 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 into projects.

Next steps
Are you a data owner or project maintainer that wants to organize a
collaboration?
👉 Check out the Ballet Maintainer Guide
Are you a data scientist or enthusiast that wants to join a collaboration?
👉 Check out the Ballet Contributor Guide
Want to learn about how Ballet enables Better Feature Engineering™️?
👉 Check out the Feature Engineering Guide
Want to see a demo collaboration in progress and maybe even participate yourself?
👉 Check out the 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.

path
description

cli.py
the ballet command line utility

client.py
the interactive client for users

contrib.py
collecting feature definitions from individual modules in source files in the file system

eng/base.py
abstractions for transformers used in feature definitions, such as BaseTransformer

eng/{misc,missing,ts}.py
custom transformers for missing data, time series problems, and more

eng/external.py
re-export of transformers from external libraries such as scikit-learn and feature_engine

feature.py
the Feature abstraction

pipeline.py
the FeatureEngineeringPipeline abstraction

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/
cookiecutter templates for creating a new Ballet project or creating a new feature definition

templating.py
user-facing functionality on top of the templates

transformer.py
wrappers for transformers that make them play nicely together in a pipeline

update.py
functionality to update the project template from a new upstream release

util/
various utilities

validation/main.py
entry point for all validation routines

validation/base.py
abstractions used in validation such as the FeaturePerformanceEvaluator

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
statistical estimation routines used in feature definition selection algorithms, such as estimators for entropy, mutual information, and conditional mutual information

validation/feature_acceptance/
validation routines for feature acceptance

validation/feature_pruning/
validation routines for feature pruning

validation/feature_api/
validation routines for feature APIs

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)
Add ballet.drop_missing_targets primitive

0.19.3 (2021-06-28)

Support missing targets in discovery and feature performance evaluation (#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)

0.18.0 (2021-06-06)

Added Consumer Guide
Can use Ballet together with MLBlocks to engineer features and then use additional preprocessing and ML components (#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)
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)
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)

0.14.0 (2021-05-11)

Support using holdout data splits in validation (#75)
Fix CLI program name in projects (#74)
Fix bug with load_config usage in python REPL (#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