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https://github.com/nushell/nushell.git
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028fc9b9cd
Refactored out most of internal work for summarizing data opening the door for generating charts from it. A model is introduced to hold information needed for a summary, Histogram command is an example of a partial usage. This is the beginning. Removed implicit arithmetic traits on Value and Primitive to avoid mixed types panics. The std operations traits can't fail and we can't guarantee that. We can handle gracefully now since compute_values was introduced after the parser changes four months ago. The handling logic should be taken care of either explicitly or in compute_values. The zero identity trait was also removed (and implementing this forced us to also implement Add, Mult, etc) Also: the `math` operations now remove in the output if a given column is not computable: ``` > ls | math sum ──────┬────────── size │ 150.9 KB ──────┴────────── ```
73 lines
2.4 KiB
Rust
73 lines
2.4 KiB
Rust
use crate::prelude::*;
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use nu_errors::ShellError;
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use nu_protocol::{Dictionary, ReturnSuccess, UntaggedValue, Value};
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use indexmap::map::IndexMap;
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pub type MathFunction = fn(values: &[Value], tag: &Tag) -> Result<Value, ShellError>;
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pub async fn run_with_function(
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RunnableContext {
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mut input, name, ..
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}: RunnableContext,
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mf: MathFunction,
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) -> Result<OutputStream, ShellError> {
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let values: Vec<Value> = input.drain_vec().await;
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let res = calculate(&values, &name, mf);
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match res {
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Ok(v) => {
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if v.value.is_table() {
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Ok(OutputStream::from(
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v.table_entries()
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.map(|v| ReturnSuccess::value(v.clone()))
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.collect::<Vec<_>>(),
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))
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} else {
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Ok(OutputStream::one(ReturnSuccess::value(v)))
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}
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}
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Err(e) => Err(e),
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}
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}
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pub fn calculate(values: &[Value], name: &Tag, mf: MathFunction) -> Result<Value, ShellError> {
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if values.iter().all(|v| v.is_primitive()) {
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mf(&values, &name)
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} else {
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// If we are not dealing with Primitives, then perhaps we are dealing with a table
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// Create a key for each column name
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let mut column_values = IndexMap::new();
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for value in values {
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if let UntaggedValue::Row(row_dict) = &value.value {
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for (key, value) in row_dict.entries.iter() {
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column_values
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.entry(key.clone())
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.and_modify(|v: &mut Vec<Value>| v.push(value.clone()))
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.or_insert(vec![value.clone()]);
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}
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}
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}
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// The mathematical function operates over the columns of the table
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let mut column_totals = IndexMap::new();
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for (col_name, col_vals) in column_values {
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if let Ok(out) = mf(&col_vals, &name) {
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column_totals.insert(col_name, out);
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}
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}
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if column_totals.keys().len() == 0 {
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return Err(ShellError::labeled_error(
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"Attempted to compute values that can't be operated on",
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"value appears here",
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name.span,
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));
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}
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Ok(UntaggedValue::Row(Dictionary {
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entries: column_totals,
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})
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.into_untagged_value())
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}
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}
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