vegafusion_core/spec/transform/
sequence.rs

1use crate::spec::transform::{TransformColumns, TransformSpecTrait};
2use serde::{Deserialize, Serialize};
3use serde_json::Value;
4use std::collections::HashMap;
5
6use crate::error::Result;
7use crate::expression::column_usage::{ColumnUsage, DatasetsColumnUsage, VlSelectionFields};
8use crate::expression::parser::parse;
9
10use crate::spec::values::{NumberOrSignalSpec, SignalExpressionSpec};
11use crate::task_graph::graph::ScopedVariable;
12use crate::task_graph::scope::TaskScope;
13use crate::task_graph::task::InputVariable;
14
15/// Struct that serializes to Vega spec for the sequence transform.
16/// This is currently only needed to report the proper input dependencies
17#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
18pub struct SequenceTransformSpec {
19    pub start: NumberOrSignalSpec,
20    pub stop: NumberOrSignalSpec,
21
22    #[serde(rename = "as", skip_serializing_if = "Option::is_none")]
23    pub as_: Option<String>,
24
25    #[serde(skip_serializing_if = "Option::is_none")]
26    pub step: Option<NumberOrSignalSpec>,
27
28    #[serde(flatten)]
29    pub extra: HashMap<String, Value>,
30}
31
32impl SequenceTransformSpec {
33    pub fn as_(&self) -> String {
34        self.as_.clone().unwrap_or_else(|| "data".to_string())
35    }
36}
37
38impl TransformSpecTrait for SequenceTransformSpec {
39    fn supported(&self) -> bool {
40        let mut signals = vec![&self.start, &self.stop];
41        if let Some(step) = &self.step {
42            signals.push(step);
43        }
44        for sig in signals {
45            if let NumberOrSignalSpec::Signal(SignalExpressionSpec { signal }) = sig {
46                if let Ok(expr) = parse(signal.as_str()) {
47                    if !expr.is_supported() {
48                        // Signal expression is not supported
49                        return false;
50                    }
51                } else {
52                    // Failed to parse expression, not supported
53                    return false;
54                }
55            }
56        }
57        true
58    }
59
60    fn input_vars(&self) -> Result<Vec<InputVariable>> {
61        let mut input_vars: Vec<InputVariable> = Vec::new();
62        input_vars.extend(self.start.input_vars()?);
63        input_vars.extend(self.stop.input_vars()?);
64        if let Some(step) = &self.step {
65            input_vars.extend(step.input_vars()?);
66        }
67
68        Ok(input_vars)
69    }
70
71    fn transform_columns(
72        &self,
73        _datum_var: &Option<ScopedVariable>,
74        _usage_scope: &[u32],
75        _task_scope: &TaskScope,
76        _vl_selection_fields: &VlSelectionFields,
77    ) -> TransformColumns {
78        // Sequence uses not columns and produces a single column
79        TransformColumns::Overwrite {
80            usage: DatasetsColumnUsage::empty(),
81            produced: ColumnUsage::from(self.as_().as_str()),
82        }
83    }
84}
vegafusion_core/spec/transform/sequence.rs

vegafusion_core/spec/transform/
sequence.rs
