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About orbit-ml-feedstock

Feedstock license: BSD-3-Clause

Home: https://orbit-ml.readthedocs.io/en/stable/

Package license: Apache-2.0

Summary: Orbit is a package for bayesian time series modeling and inference.

Development: https://github.com/uber/orbit

Documentation: https://orbit-ml.readthedocs.io/en/stable/

Orbit is a Python package for Bayesian time series forecasting and inference. It provides a familiar and intuitive initialize-fit-predict interface for time series tasks, while utilizing probabilistic programming languages under the hood.

For details, check out our documentation and tutorials:

HTML (stable): https://orbit-ml.readthedocs.io/en/stable/
HTML (latest): https://orbit-ml.readthedocs.io/en/latest/

Currently, it supports concrete implementations for the following models:

Exponential Smoothing (ETS)
Local Global Trend (LGT)
Damped Local Trend (DLT)
Kernel Time-based Regression (KTR)

It also supports the following sampling/optimization methods for model estimation/inferences:

Markov-Chain Monte Carlo (MCMC) as a full sampling method
Maximum a Posteriori (MAP) as a point estimate method
Variational Inference (VI) as a hybrid-sampling method on approximate distribution

PyPI: https://pypi.org/project/orbit-ml/

Current build status

<table><tr><td>All platforms:</td> <td> <a href="https://dev.azure.com/conda-forge/feedstock-builds/_build/latest?definitionId=15081&branchName=main"> <img src="https://dev.azure.com/conda-forge/feedstock-builds/_apis/build/status/orbit-ml-feedstock?branchName=main"> </a> </td> </tr> </table>

Current release info

Name	Downloads	Version	Platforms

Installing orbit-ml

Installing orbit-ml from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, orbit-ml can be installed with conda:

conda install orbit-ml

or with mamba:

mamba install orbit-ml

It is possible to list all of the versions of orbit-ml available on your platform with conda:

conda search orbit-ml --channel conda-forge

or with mamba:

mamba search orbit-ml --channel conda-forge

Alternatively, mamba repoquery may provide more information:

# Search all versions available on your platform:
mamba repoquery search orbit-ml --channel conda-forge

# List packages depending on `orbit-ml`:
mamba repoquery whoneeds orbit-ml --channel conda-forge

# List dependencies of `orbit-ml`:
mamba repoquery depends orbit-ml --channel conda-forge

About conda-forge

conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.

A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance conda-smithy has been developed. Using the conda-forge.yml within this repository, it is possible to re-render all of this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.

For more information please check the conda-forge documentation.

Terminology

feedstock - the conda recipe (raw material), supporting scripts and CI configuration.

conda-smithy - the tool which helps orchestrate the feedstock. Its primary use is in the construction of the CI .yml files and simplify the management of many feedstocks.

conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)

Updating orbit-ml-feedstock

If you would like to improve the orbit-ml recipe or build a new package version, please fork this repository and submit a PR. Upon submission, your changes will be run on the appropriate platforms to give the reviewer an opportunity to confirm that the changes result in a successful build. Once merged, the recipe will be re-built and uploaded automatically to the conda-forge channel, whereupon the built conda packages will be available for everybody to install and use from the conda-forge channel. Note that all branches in the conda-forge/orbit-ml-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches in the main repository should only be used to build distinct package versions.

In order to produce a uniquely identifiable distribution:

If the version of a package is not being increased, please add or increase the build/number.
If the version of a package is being increased, please remember to return the build/number back to 0.