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Merge pull request #129 from lesserwhirls/codespell
Codespell
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.github/workflows/codespell.yml

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name: codespell
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on:
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pull_request:
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paths:
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- Readme.md
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permissions: {}
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jobs:
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codespell:
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name: Check for spelling errors
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- uses: codespell-project/actions-codespell@v2
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with:
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path: Readme.md

Readme.md

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### Why do we need another library besides the standard reference libraries?
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Its necessary to have independent implementations of any standard. If you don't have multiple implementations, its
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easy for the single implementer to mistake the implementation for the actual standard. Its easy to hide problems
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It's necessary to have independent implementations of any standard. If you don't have multiple implementations, it's
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easy for the single implementer to mistake the implementation for the actual standard. It's easy to hide problems
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that are actually in the standard by adding work-arounds in the code, instead of documenting problems and creating new
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versions of the standard with clear fixes. For Netcdf/Hdf, the standard is the file formats, along with their semantic
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descriptions. The API is language and library specific, and is secondary to the standard.
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Having multiple implementations is a huge win for the reference library, in that bugs are more quickly found, and
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ambiguities more quickly identified.
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### Whats wrong with the standard reference libraries?
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### What's wrong with the standard reference libraries?
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The reference libraries are well maintained but complex. They are coded in C, which is a difficult language to master
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and keep bug free, with implications for memory safety and security. The libraries require various machine and OS dependent
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HDF-EOS uses an undocumented "Object Descriptor Language (ODL)" text format, which adds a dependency on the SDP Toolkit
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and possibly other libraries. These toolkits also provide functionality such as handling projections and coordinate system
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conversions, and arguably its impossible to process HDF-EOS without them. So the value added here by an independent
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conversions, and arguably it's impossible to process HDF-EOS without them. So the value added here by an independent
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library for data access is less clear. For now, we will provide a "best-effort" to expose the internal
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contents of the file.
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The library will be thread-safe for reading multiple files concurrently.
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We are focussing on earth science data, and dont plan to support other uses except as a byproduct.
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We are focussing on earth science data, and don't plan to support other uses except as a byproduct.
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The core module will remain pure Kotlin with very minimal dependencies and no write capabilities. In particular,
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there will be no dependency on the reference C libraries (except for testing).
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#### Compare with HDF5 data model
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* Creation order is ignored
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* We dont include soft (aka symbolic) links in a group, as these point to an existing dataset (variable).
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* We don't include soft (aka symbolic) links in a group, as these point to an existing dataset (variable).
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* Opaque: hdf5 makes arrays of Opaque all the same size, which gives up some of its usefulness. If there's a need,
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we will allow Opaque(*) indicating that the sizes can vary.
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* Attributes can be of type REFERENCE, with value the full path name of the referenced dataset.

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