Bahex 5615d21ce9
remove content_type metadata from pipeline after from ... commands (#14602)
# Description

`from ...` conversions pass along all metadata except `content_type`,
which they set to `None`.

## Rationale

`open`ing a file results in no `content_type` metadata if it can be
parsed into a nu data structure, and using `open --raw` results in
`content_type` metadata.

`from ...` commands should preserve metadata ***except*** for
`content_type`, as after parsing it's no longer that `content_type` and
just structured nu data.

These commands should return identical data *and* identical metadata

```nushell
open foo.csv
```

```nushell
open foo.csv --raw | from csv
```

# User-Facing Changes

N/A

# Tests + Formatting
- 🟢 toolkit fmt
- 🟢 toolkit clippy
- 🟢 toolkit test
- 🟢 toolkit test stdlib

# After Submitting
N/A
2024-12-16 15:59:18 -06:00

201 lines
6.1 KiB
Rust

use calamine::*;
use chrono::{Local, LocalResult, Offset, TimeZone, Utc};
use indexmap::IndexMap;
use nu_engine::command_prelude::*;
use std::io::Cursor;
#[derive(Clone)]
pub struct FromXlsx;
impl Command for FromXlsx {
fn name(&self) -> &str {
"from xlsx"
}
fn signature(&self) -> Signature {
Signature::build("from xlsx")
.input_output_types(vec![(Type::Binary, Type::table())])
.allow_variants_without_examples(true)
.named(
"sheets",
SyntaxShape::List(Box::new(SyntaxShape::String)),
"Only convert specified sheets",
Some('s'),
)
.category(Category::Formats)
}
fn description(&self) -> &str {
"Parse binary Excel(.xlsx) data and create table."
}
fn run(
&self,
engine_state: &EngineState,
stack: &mut Stack,
call: &Call,
input: PipelineData,
) -> Result<PipelineData, ShellError> {
let head = call.head;
let sel_sheets = if let Some(Value::List { vals: columns, .. }) =
call.get_flag(engine_state, stack, "sheets")?
{
convert_columns(columns.as_slice())?
} else {
vec![]
};
let metadata = input.metadata().map(|md| md.with_content_type(None));
from_xlsx(input, head, sel_sheets).map(|pd| pd.set_metadata(metadata))
}
fn examples(&self) -> Vec<Example> {
vec![
Example {
description: "Convert binary .xlsx data to a table",
example: "open --raw test.xlsx | from xlsx",
result: None,
},
Example {
description: "Convert binary .xlsx data to a table, specifying the tables",
example: "open --raw test.xlsx | from xlsx --sheets [Spreadsheet1]",
result: None,
},
]
}
}
fn convert_columns(columns: &[Value]) -> Result<Vec<String>, ShellError> {
let res = columns
.iter()
.map(|value| match &value {
Value::String { val: s, .. } => Ok(s.clone()),
_ => Err(ShellError::IncompatibleParametersSingle {
msg: "Incorrect column format, Only string as column name".to_string(),
span: value.span(),
}),
})
.collect::<Result<Vec<String>, _>>()?;
Ok(res)
}
fn collect_binary(input: PipelineData, span: Span) -> Result<Vec<u8>, ShellError> {
if let PipelineData::ByteStream(stream, ..) = input {
stream.into_bytes()
} else {
let mut bytes = vec![];
let mut values = input.into_iter();
loop {
match values.next() {
Some(Value::Binary { val: b, .. }) => {
bytes.extend_from_slice(&b);
}
Some(x) => {
return Err(ShellError::UnsupportedInput {
msg: "Expected binary from pipeline".to_string(),
input: "value originates from here".into(),
msg_span: span,
input_span: x.span(),
})
}
None => break,
}
}
Ok(bytes)
}
}
fn from_xlsx(
input: PipelineData,
head: Span,
sel_sheets: Vec<String>,
) -> Result<PipelineData, ShellError> {
let span = input.span();
let bytes = collect_binary(input, head)?;
let buf: Cursor<Vec<u8>> = Cursor::new(bytes);
let mut xlsx = Xlsx::<_>::new(buf).map_err(|_| ShellError::UnsupportedInput {
msg: "Could not load XLSX file".to_string(),
input: "value originates from here".into(),
msg_span: head,
input_span: span.unwrap_or(head),
})?;
let mut dict = IndexMap::new();
let mut sheet_names = xlsx.sheet_names();
if !sel_sheets.is_empty() {
sheet_names.retain(|e| sel_sheets.contains(e));
}
let tz = match Local.timestamp_opt(0, 0) {
LocalResult::Single(tz) => *tz.offset(),
_ => Utc.fix(),
};
for sheet_name in sheet_names {
let mut sheet_output = vec![];
if let Ok(current_sheet) = xlsx.worksheet_range(&sheet_name) {
for row in current_sheet.rows() {
let record = row
.iter()
.enumerate()
.map(|(i, cell)| {
let value = match cell {
Data::Empty => Value::nothing(head),
Data::String(s) => Value::string(s, head),
Data::Float(f) => Value::float(*f, head),
Data::Int(i) => Value::int(*i, head),
Data::Bool(b) => Value::bool(*b, head),
Data::DateTime(d) => d
.as_datetime()
.and_then(|d| match tz.from_local_datetime(&d) {
LocalResult::Single(d) => Some(d),
_ => None,
})
.map(|d| Value::date(d, head))
.unwrap_or(Value::nothing(head)),
_ => Value::nothing(head),
};
(format!("column{i}"), value)
})
.collect();
sheet_output.push(Value::record(record, head));
}
dict.insert(sheet_name, Value::list(sheet_output, head));
} else {
return Err(ShellError::UnsupportedInput {
msg: "Could not load sheet".to_string(),
input: "value originates from here".into(),
msg_span: head,
input_span: span.unwrap_or(head),
});
}
}
Ok(PipelineData::Value(
Value::record(dict.into_iter().collect(), head),
None,
))
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_examples() {
use crate::test_examples;
test_examples(FromXlsx {})
}
}