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Patil2099John Andersen
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docs: conf: Changed HTML theme to RTD
Co-authored-by: John Andersen <john.s.andersen@intel.com> Signed-off-by: John Andersen <john.s.andersen@intel.com>
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.travis.yml

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- docker pull mariadb:10
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- mkdir -p /home/travis/.cache/
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- mkdir -p /home/travis/.local/bin/
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- pip install coverage codecov sphinx sphinxcontrib-asyncio black
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- pip install coverage codecov sphinx sphinxcontrib-asyncio black sphinx_rtd_theme
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- curl -sSL https://github.com/XAMPPRocky/tokei/releases/download/v9.1.1/tokei-v9.1.1-x86_64-unknown-linux-gnu.tar.gz | tar xvz -C "$HOME/.local/bin/"
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script:
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- ./.ci/run.sh

CHANGELOG.md

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with entrypoints.
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- HTTP API service to enable interacting with DFFML over HTTP. Currently
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includes APIs for configuring and using Sources.
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- MySQL protocol source to work with data from a MySQL protocol compatable db
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- Bandit module which checks for high confidence and high severity issues.
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- Download python package obtained from package json url and extract to a
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temporary directory and clean up after it's usage.
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- Run a single operation in a standalone fashion.
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- MySQL protocol source to work with data from a MySQL protocol compatible db
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- shouldi example got a bandit operation which tells users not to install if
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there are more than 5 issues of high severity and confidence.
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- dev service got the ability to run a single operation in a standalone fashion.
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### Changed
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- feature/codesec became it's own branch, binsec
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- BaseOrchestratorContext `run_operations` strict is default to true. With
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- Ran `black` on whole codebase, including all submodules
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- CI style check now checks whole codebase
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- Merged HACKING.md into CONTRIBUTING.md
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- shouldi/cli to run bandit and safety checks.
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- The way safety gets called.
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- shouldi example runs bandit now in addition to safety
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- The way safety gets called
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- Switched documentation to Read The Docs theme
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### Fixed
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- Docs get version from dffml.version.VERSION.
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- FileSource zipfiles are wrapped with TextIOWrapper because CSVSource expects
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- CSV source now has `entry_point` decoration
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- JSON source now has `entry_point` decoration
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- Strict flag in df.memory is now on by default
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- Dynamicly created scikit models get config args correctly
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- Dynamically created scikit models get config args correctly
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### Removed
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- Repo objects are no longer classification specific. Their `classify`,
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`classified`, and `classification` methods were removed.

README.md

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# Data Flow Facilitator for Machine Learning (dffml)
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[![Build Status](https://travis-ci.org/intel/dffml.svg?branch=master)](https://travis-ci.org/intel/dffml) [![codecov](https://codecov.io/gh/intel/dffml/branch/master/graph/badge.svg)](https://codecov.io/gh/intel/dffml) [![CII](https://bestpractices.coreinfrastructure.org/projects/2594/badge)](https://bestpractices.coreinfrastructure.org/projects/2594) [![Gitter chat](https://badges.gitter.im/gitterHQ/gitter.svg)](https://gitter.im/dffml/community) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
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[![Build Status](https://travis-ci.org/intel/dffml.svg?branch=master)](https://travis-ci.org/intel/dffml) [![codecov](https://codecov.io/gh/intel/dffml/branch/master/graph/badge.svg)](https://codecov.io/gh/intel/dffml) [![CII](https://bestpractices.coreinfrastructure.org/projects/2594/badge)](https://bestpractices.coreinfrastructure.org/projects/2594) [![Gitter chat](https://badges.gitter.im/gitterHQ/gitter.svg)](https://gitter.im/dffml/community) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
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## Documentation
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docs/conf.py

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# The theme to use for HTML and HTML Help pages. See the documentation for
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# a list of builtin themes.
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#
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html_theme = "alabaster"
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html_theme = "sphinx_rtd_theme"
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html_theme_options = {
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"description": "The fastest path to machine learning integration",

docs/index.rst

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Welcome to DFFML!
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=================
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.. image:: https://travis-ci.org/intel/dffml.svg?branch=master
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:target: https://travis-ci.org/intel/dffml
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:alt: Build Status
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.. image:: https://codecov.io/gh/intel/dffml/branch/master/graph/badge.svg
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:target: https://codecov.io/gh/intel/dffml
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:alt: codecov
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.. image:: https://bestpractices.coreinfrastructure.org/projects/2594/badge
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:target: https://bestpractices.coreinfrastructure.org/projects/2594
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:alt: CII
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.. image:: https://badges.gitter.im/gitterHQ/gitter.svg
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:target: https://gitter.im/dffml/community
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:alt: Gitter chat
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.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
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:target: https://github.com/psf/black
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:alt: Code style: black
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Data Flow Facilitator for Machine Learning (DFFML) provides APIs for dataset
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generation, storage, and model definition.
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setup.py

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"sphinx",
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"sphinxcontrib-asyncio",
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"black",
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"sphinx_rtd_theme",
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],
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},
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entry_points={

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