eae00522e2
Multi-dimensional data modeling terminal application with:
- Core data model: categories, items, groups, sparse cell store
- Formula system: recursive-descent parser, named formulas, WHERE clauses
- View system: Row/Column/Page axes, tile-based pivot, page slicing
- JSON import wizard (interactive TUI + headless auto-mode)
- Command layer: all mutations via typed Command enum for headless replay
- TUI: Ratatui grid, tile bar, formula/category/view panels, help overlay
- Persistence: .improv (JSON), .improv.gz (gzip), CSV export, autosave
- Static binary via x86_64-unknown-linux-musl + nix flake devShell
- Headless mode: --cmd '{"op":"..."}' and --script file.jsonl
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
59 lines
1.3 KiB
Rust
59 lines
1.3 KiB
Rust
use serde::{Deserialize, Serialize};
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub enum AggFunc {
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Sum,
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Avg,
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Min,
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Max,
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Count,
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}
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct Filter {
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pub category: String,
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pub item: String,
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}
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub enum Expr {
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Number(f64),
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Ref(String),
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BinOp(String, Box<Expr>, Box<Expr>),
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UnaryMinus(Box<Expr>),
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Agg(AggFunc, Box<Expr>, Option<Filter>),
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If(Box<Expr>, Box<Expr>, Box<Expr>),
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}
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct Formula {
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/// The raw formula text, e.g. "Profit = Revenue - Cost"
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pub raw: String,
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/// The item/dimension name this formula computes, e.g. "Profit"
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pub target: String,
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/// The category containing the target item
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pub target_category: String,
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/// The expression to evaluate
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pub expr: Expr,
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/// Optional WHERE filter
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pub filter: Option<Filter>,
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}
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impl Formula {
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pub fn new(
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raw: impl Into<String>,
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target: impl Into<String>,
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target_category: impl Into<String>,
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expr: Expr,
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filter: Option<Filter>,
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) -> Self {
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Self {
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raw: raw.into(),
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target: target.into(),
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target_category: target_category.into(),
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expr,
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filter,
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}
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}
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}
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