forked from extern/nushell
5e70d4121a
# Description This PR tries to resolve the overloading issue by going back to our original naming convention for dataframes. So, this PR renames all dataframe commands with a prefix of `dfr`. Some commands like `open-df` were renamed to `dfr open` and things like `into df` were renamed `dfr into-df`. I'm sure we can optimize naming a bit, but it seems to compile now. # User-Facing Changes All dataframe commands are prefixed with dfr. # Tests + Formatting Don't forget to add tests that cover your changes. Make sure you've run and fixed any issues with these commands: - `cargo fmt --all -- --check` to check standard code formatting (`cargo fmt --all` applies these changes) - `cargo clippy --workspace -- -D warnings -D clippy::unwrap_used -A clippy::needless_collect` to check that you're using the standard code style - `cargo test --workspace` to check that all tests pass # After Submitting If your PR had any user-facing changes, update [the documentation](https://github.com/nushell/nushell.github.io) after the PR is merged, if necessary. This will help us keep the docs up to date.
85 lines
2.3 KiB
Rust
85 lines
2.3 KiB
Rust
use nu_protocol::{
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ast::Call,
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engine::{Command, EngineState, Stack},
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Category, Example, PipelineData, ShellError, Signature, Span, Type, Value,
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};
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use crate::dataframe::values::Column;
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use super::super::values::NuDataFrame;
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#[derive(Clone)]
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pub struct ShapeDF;
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impl Command for ShapeDF {
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fn name(&self) -> &str {
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"dfr shape"
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}
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fn usage(&self) -> &str {
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"Shows column and row size for a dataframe"
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}
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fn signature(&self) -> Signature {
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Signature::build(self.name())
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.input_type(Type::Custom("dataframe".into()))
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.output_type(Type::Custom("dataframe".into()))
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.category(Category::Custom("dataframe".into()))
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}
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fn examples(&self) -> Vec<Example> {
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vec![Example {
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description: "Shows row and column shape",
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example: "[[a b]; [1 2] [3 4]] | dfr into-df | dfr shape",
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result: Some(
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NuDataFrame::try_from_columns(vec![
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Column::new("rows".to_string(), vec![Value::test_int(2)]),
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Column::new("columns".to_string(), vec![Value::test_int(2)]),
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])
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.expect("simple df for test should not fail")
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.into_value(Span::test_data()),
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),
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}]
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}
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fn run(
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&self,
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engine_state: &EngineState,
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stack: &mut Stack,
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call: &Call,
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input: PipelineData,
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) -> Result<PipelineData, ShellError> {
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command(engine_state, stack, call, input)
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}
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}
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fn command(
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_engine_state: &EngineState,
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_stack: &mut Stack,
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call: &Call,
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input: PipelineData,
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) -> Result<PipelineData, ShellError> {
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let df = NuDataFrame::try_from_pipeline(input, call.head)?;
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let rows = Value::int(df.as_ref().height() as i64, call.head);
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let cols = Value::int(df.as_ref().width() as i64, call.head);
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let rows_col = Column::new("rows".to_string(), vec![rows]);
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let cols_col = Column::new("columns".to_string(), vec![cols]);
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NuDataFrame::try_from_columns(vec![rows_col, cols_col])
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.map(|df| PipelineData::Value(df.into_value(call.head), None))
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}
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#[cfg(test)]
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mod test {
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use super::super::super::test_dataframe::test_dataframe;
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use super::*;
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#[test]
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fn test_examples() {
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test_dataframe(vec![Box::new(ShapeDF {})])
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}
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}
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