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README.md

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## Tutorials and Documentation
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For information on using the package,
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[see the stable documentation](https://symbolicutils.juliasymbolics.org/stable/). Use the
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[in-development documentation](https://symbolicutils.juliasymbolics.org/dev/) for the version of
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[see the stable documentation](https://docs.sciml.ai/SymbolicUtils/stable/). Use the
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[in-development documentation](https://docs.sciml.ai/SymbolicUtils/dev/) for the version of
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the documentation, which contains the unreleased features.
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SymbolicUtils.jl provides various utilities for symbolic computing. SymbolicUtils.jl is what one would use to build
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a Computer Algebra System (CAS). If you're looking for a complete CAS, similar to SymPy or Mathematica, see
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[Symbolics.jl](https://github.com/JuliaSymbolics/Symbolics.jl). If you want to build a crazy CAS for your weird
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Octonian algebras, you've come to the right place.
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[Symbols in SymbolicUtils](https://symbolicutils.juliasymbolics.org/#creating_symbolic_expressions) carry type information. Operations on them propagate this information. [A rule-based rewriting language](https://symbolicutils.juliasymbolics.org/rewrite/#rule-based_rewriting) can be used to find subexpressions that satisfy arbitrary conditions and apply arbitrary transformations on the matches. The library also contains a set of useful [simplification](https://juliasymbolics.github.io/SymbolicUtils.jl/#simplification) rules for expressions of numeric symbols and numbers. These can be remixed and extended for special purposes.
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[Symbols in SymbolicUtils](https://docs.sciml.ai/SymbolicUtils/stable/#Creating-symbolic-expressions) carry type information. Operations on them propagate this information. [A rule-based rewriting language](https://docs.sciml.ai/SymbolicUtils/stable/manual/rewrite/) can be used to find subexpressions that satisfy arbitrary conditions and apply arbitrary transformations on the matches. The library also contains a set of useful [simplification](https://docs.sciml.ai/SymbolicUtils/stable/#Simplification) rules for expressions of numeric symbols and numbers. These can be remixed and extended for special purposes.
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If you are a Julia package developer in need of a rule rewriting system for your own types, have a look at the [interfacing guide](https://symbolicutils.juliasymbolics.org/interface/).
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If you are a Julia package developer in need of a rule rewriting system for your own types, have a look at the [interfacing guide](https://docs.sciml.ai/SymbolicUtils/stable/manual/interface/#Interfacing-with-SymbolicUtils.jl).
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### "I don't want to read your manual, just show me some cool code"

src/types.jl

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@inline denominators(x) = isdiv(x) ? numerators(x.den) : Any[1]
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function (::Type{<:Pow{T}})(a, b; metadata=NO_METADATA) where {T}
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function Pow{T}(a, b; metadata=NO_METADATA) where {T}
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_iszero(b) && return 1
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_isone(b) && return a
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Pow{T}(; base=a, exp=b, arguments=[], metadata)

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