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About static-frame-feedstock

Feedstock license: BSD-3-Clause

Home: https://github.com/static-frame/static-frame

Package license: MIT

Summary: Immutable and grow-only Pandas-like DataFrames with a more explicit and consistent interface

Development: https://github.com/static-frame/static-frame

Documentation: https://static-frame.readthedocs.io

A library of immutable and grow-only Pandas-like DataFrames with a more explicit and consistent interface. StaticFrame is suitable for applications in data science, data engineering, finance, scientific computing, and related fields where reducing opportunities for error by prohibiting in-place mutation is critical.

While many interfaces are similar to Pandas, StaticFrame deviates from Pandas in many ways: all data is immutable, and all indices are unique; the full range of NumPy data types is preserved, and date-time indices use discrete NumPy types; hierarchical indices are seamlessly integrated; and uniform approaches to element, row, and column iteration and function application are provided. Core StaticFrame depends only on NumPy and two C-extension packages (maintained by the StaticFrame team): Pandas is not a dependency.

A wide variety of table formats are supported, including input from and output to CSV, TSV, JSON, MessagePack, Excel XLSX, SQLite, HDF5, NumPy, Pandas, Arrow, and Parquet; additionally, output to xarray, VisiData, HTML, RST, Markdown, and LaTeX is supported, as well as HTML representations in Jupyter notebooks. Full serialization is also available via custom NPZ and NPY encodings, the latter supporting memory mapping.

StaticFrame features a family of multi-table containers: the Bus is a lazily-loaded container of tables, the Batch is a deferred processor of tables, the Yarn is virtual concatenation of many Buses, and the Quilt is a virtual concatenation of all tables within a single Bus or Yarn. All permit operating on large collections of tables with minimal memory overhead, as well as writing too and reading from zipped bundles of pickles, NPZ, Parquet, or delimited files, as well as XLSX workbooks, SQLite, and HDF5.

Current build status

All platforms:

Current release info

Name Downloads Version Platforms
Conda Recipe Conda Downloads Conda Version Conda Platforms

Installing static-frame

Installing static-frame 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, static-frame can be installed with conda:

conda install static-frame

or with mamba:

mamba install static-frame

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

conda search static-frame --channel conda-forge

or with mamba:

mamba search static-frame --channel conda-forge

Alternatively, mamba repoquery may provide more information:

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

# List packages depending on `static-frame`:
mamba repoquery whoneeds static-frame --channel conda-forge

# List dependencies of `static-frame`:
mamba repoquery depends static-frame --channel conda-forge

About conda-forge

Powered by NumFOCUS

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-Cloud 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 static-frame-feedstock

If you would like to improve the static-frame 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/static-frame-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.

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A conda-smithy repository for static-frame.

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