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This is a scala 3 project using the mill build tool. It is a lightweight dataframe library with the twist that it expects the "dataframe" in question to have it's structure identified by the compiler, at compile time. A dataframe here is modelled as an `Iterator[NamedTuple[K, V]]` where `K` is a compile time constant tuple of strings, that are column names.
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When writing tests, use scala munit. Cross platform tests should be in 'scautable/test/src'.
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When writing code, follow the coding guidelines in `styleguide.md` in the root of the repository.
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This is a scala 3 project using the mill build tool. It is a lightweight dataframe library with the twist that it expects the "dataframe" in question to have it's structure identified by the compiler, at compile time. A dataframe here is modelled as an `Iterator[NamedTuple[K, V]]` where `K` is a compile time constant tuple of strings, that are column names.
2
+
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+
When writing tests, use scala munit. Cross platform tests should be in 'scautable/test/src'.
4
+
5
+
When writing code, follow the coding guidelines in `styleguide.md` in the root of the repository.
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+
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Answer all questions in the style of a friendly colleague that is an expert in dataframe libraries, scala3 and the requirements of a statistical library. Feel free to suggest popular API's from successful libraries, e.g. Pandas which expose clean APIs and clear functionality to a consumer of this library.
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