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Custom dictionaries #9
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This was referenced Jun 26, 2019
epage
referenced
this issue
in epage/typos
Sep 3, 2020
Sometimes you just have to live with a typo or its done intentionally (like weird company names). With this commit, a user can now identifier blessed identifiers and words. This is ostly what is needed for #9 but sometimes people will have common typos that they'll want to provide corrections for.
epage
referenced
this issue
in epage/typos
Sep 3, 2020
Sometimes you just have to live with a typo or its done intentionally (like weird company names). With this commit, a user can now identifier blessed identifiers and words. This is ostly what is needed for #9 but sometimes people will have common typos that they'll want to provide corrections for.
I realized there are three pieces of information a user may want to specify
I suspect it might get cumbersome to have 3 custom entries x 2 types of words. What if the user specifies it as [default.dictionary]
invalid=""
valid="valid"
correcton="correction" ie
We could then implement this as enum Correction {
Invalid,
Valid,
Correction(str)
} |
epage
referenced
this issue
in epage/typos
Oct 27, 2020
Switching `valid-*` to just `*` where you map typo to correction, with support for always-valid and never-valid. Fixes #9
epage
referenced
this issue
in epage/typos
Oct 27, 2020
Switching `valid-*` to just `*` where you map typo to correction, with support for always-valid and never-valid. Fixes #9
epage
referenced
this issue
in epage/typos
Oct 27, 2020
Switching `valid-*` to just `*` where you map typo to correction, with support for always-valid and never-valid. Fixes #9
epage
referenced
this issue
in epage/typos
Oct 28, 2020
Switching `valid-*` to just `*` where you map typo to correction, with support for always-valid and never-valid. Fixes #9
epage
referenced
this issue
in epage/typos
Oct 28, 2020
Switching `valid-*` to just `*` where you map typo to correction, with support for always-valid and never-valid. Fixes #9
how to use this feature? typos always get wrong when parse numpy.typing.NDArray, and it'll always modify it as ANDArray. |
Have you checked out our documentation on false positives? |
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