QuantumESPRESSOParser

Documentation for QuantumESPRESSOParser.

See the Index for the complete list of documented functions and types.

The code is hosted on GitHub, with some continuous integration services to test its validity.

This repository is created and maintained by @singularitti. You are very welcome to contribute.

Installation

The package can be installed with the Julia package manager. From the Julia REPL, type ] to enter the Pkg REPL mode and run:

pkg> add QuantumESPRESSOParser

Or, equivalently, via the Pkg API:

julia> import Pkg; Pkg.add("QuantumESPRESSOParser")   Resolving package versions...
   Installed QuantumESPRESSOParser ─ v0.5.5
    Updating `~/work/QuantumESPRESSOParser.jl/QuantumESPRESSOParser.jl/docs/build/developers/Project.toml`
  [a780ab42] + QuantumESPRESSOParser v0.5.5
    Updating `~/work/QuantumESPRESSOParser.jl/QuantumESPRESSOParser.jl/docs/build/developers/Manifest.toml`
  [df5135bc] + AbInitioSoftwareBase v0.10.1
  [7d9f7c33] + Accessors v0.1.33
  [1b8a1bdb] + AnonymousEnums v0.1.1
  [b5b47461] + ComposableCommands v0.2.0
  [a33af91c] + CompositionsBase v0.1.2
  [8f4d0f93] + Conda v1.10.0
  [5218b696] + Configurations v0.17.6
  [187b0558] + ConstructionBase v1.5.4
  [93b1d1cd] + CrystallographyBase v0.14.3
  [80545937] + CrystallographyCore v0.6.1
  [55351af7] + ExproniconLite v0.10.4
  [3587e190] + InverseFunctions v0.1.12
  [ceb4388c] + IsURL v0.2.0
  [692b3bcd] + JLLWrappers v1.5.0
  [1914dd2f] + MacroTools v0.5.11
  [438e738f] + PyCall v1.96.2
  [e44308e6] + PyFortran90Namelists v0.1.0
  [51b62caa] + QuantumESPRESSOBase v0.12.0
  [a780ab42] + QuantumESPRESSOParser v0.5.5
  [cbbcb084] + ReadableRegex v0.3.2
  [189a3867] + Reexport v1.2.2
  [90137ffa] + StaticArrays v1.7.0
  [1e83bf80] + StaticArraysCore v1.4.2
  [69024149] + StringEncodings v0.3.7
  [6ec83bb0] + StructEquality v2.1.0
  [1986cc42] + Unitful v1.18.0
  [a7773ee8] + UnitfulAtomic v1.0.0
  [da9c4bc3] + UnitfulEquivalences v0.2.0
  [81def892] + VersionParsing v1.3.0
  [ddb6d928] + YAML v0.4.9
  [94ce4f54] + Libiconv_jll v1.17.0+0
  [37e2e46d] + LinearAlgebra
  [8dfed614] + Test
  [e66e0078] + CompilerSupportLibraries_jll v1.0.5+0
  [4536629a] + OpenBLAS_jll v0.3.21+4
  [8e850b90] + libblastrampoline_jll v5.8.0+0
Precompiling project...
  ✓ QuantumESPRESSOParser
  1 dependency successfully precompiled in 2 seconds. 55 already precompiled.
  1 dependency precompiled but a different version is currently loaded. Restart julia to access the new version

Documentation

• STABLE — documentation of the most recently tagged version.
• DEV — documentation of the in-development version.

Project status

The package is tested against, and being developed for, Julia 1.6 and above on Linux, macOS, and Windows.

Questions and contributions

Usage questions can be posted on our discussion page.

Contributions are very welcome, as are feature requests and suggestions. Please open an issue if you encounter any problems. The Contributing page has a few guidelines that should be followed when opening pull requests and contributing code.

Manual outline

• Installation Guide
• • Install Julia
  • • Which version should I pick?
  • Install QuantumESPRESSOParser
  • Update QuantumESPRESSOParser
  • Uninstall and reinstall QuantumESPRESSOParser
• Contributing
• • Code of conduct
  • Join the community forum
  • Improve the documentation
  • File a bug report
  • Contribute code to QuantumESPRESSOParser
  • • Step 1: decide what to work on
    • Step 2: fork QuantumESPRESSOParser
    • Step 3: install QuantumESPRESSOParser locally
    • Step 4: checkout a new branch
    • Step 5: make changes
    • Step 6a: test your code changes
    • Step 6b: test your documentation changes
    • Step 7: make a pull request
    • Step 8: respond to comments
    • Step 9: cleaning up
• Style Guide
• • Formatting
  • • Run JuliaFormatter
    • Use the Julia extension for Visual Studio Code
• Design Principles
• • Consistency vs adherence
  • Community contribution guidelines
  • Open source contributions are allowed to start small and grow over time
  • Generic code is preferred unless code is known to be specific
  • Internal types should match the types used by users when possible
  • Trait definition and adherence to generic interface is preferred when possible
  • Macros should be limited and only be used for syntactic sugar
  • Errors should be caught as high as possible, and error messages should be contextualized for newcomers
  • Subpackaging and interface packages is preferred over conditional modules via Requires.jl
  • Functions should either attempt to be non-allocating and reuse caches, or treat inputs as immutable
  • Out-Of-Place and Immutability is preferred when sufficient performant
  • Tests should attempt to cover a wide gamut of input types
  • When in doubt, a submodule should become a subpackage or separate package
  • Globals should be avoided whenever possible
  • Type-stable and Type-grounded code is preferred wherever possible
  • Closures should be avoided whenever possible
  • Numerical functionality should use the appropriate generic numerical interfaces
  • Functions should capture one underlying principle
  • Internal choices should be exposed as options whenever possible
  • Prefer code reuse over rewrites whenever possible
  • Prefer to not shadow functions
• Troubleshooting
• • Installation problems
  • • Cannot find the julia executable
  • Loading QuantumESPRESSOParser
  • • Julia compiles/loads slow

Library outline

Index