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>
247 lines
8.0 KiB
Rust
247 lines
8.0 KiB
Rust
use serde_json::Value;
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use anyhow::{anyhow, Result};
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use super::analyzer::{FieldKind, FieldProposal, analyze_records, extract_array_at_path, find_array_paths};
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use crate::model::Model;
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use crate::model::cell::{CellKey, CellValue};
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#[derive(Debug, Clone, PartialEq)]
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pub enum WizardState {
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Preview,
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SelectArrayPath,
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ReviewProposals,
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NameModel,
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Done,
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}
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#[derive(Debug)]
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pub struct ImportWizard {
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pub state: WizardState,
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pub raw: Value,
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pub array_paths: Vec<String>,
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pub selected_path: String,
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pub records: Vec<Value>,
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pub proposals: Vec<FieldProposal>,
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pub model_name: String,
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pub cursor: usize,
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/// Message to display
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pub message: Option<String>,
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}
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impl ImportWizard {
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pub fn new(raw: Value) -> Self {
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let array_paths = find_array_paths(&raw);
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let state = if raw.is_array() {
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WizardState::ReviewProposals
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} else if array_paths.len() == 1 {
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WizardState::ReviewProposals
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} else {
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WizardState::SelectArrayPath
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};
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let mut wizard = Self {
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state: WizardState::Preview,
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raw: raw.clone(),
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array_paths: array_paths.clone(),
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selected_path: String::new(),
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records: vec![],
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proposals: vec![],
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model_name: "Imported Model".to_string(),
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cursor: 0,
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message: None,
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};
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// Auto-select if array at root or single path
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if raw.is_array() {
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wizard.select_path("");
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} else if array_paths.len() == 1 {
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let path = array_paths[0].clone();
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wizard.select_path(&path);
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}
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wizard.state = if wizard.records.is_empty() && raw.is_object() {
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WizardState::SelectArrayPath
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} else {
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wizard.advance();
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return wizard;
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};
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wizard
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}
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fn select_path(&mut self, path: &str) {
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self.selected_path = path.to_string();
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if let Some(arr) = extract_array_at_path(&self.raw, path) {
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self.records = arr.clone();
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self.proposals = analyze_records(&self.records);
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}
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}
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pub fn advance(&mut self) {
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self.state = match self.state {
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WizardState::Preview => {
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if self.array_paths.len() <= 1 {
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WizardState::ReviewProposals
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} else {
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WizardState::SelectArrayPath
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}
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}
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WizardState::SelectArrayPath => WizardState::ReviewProposals,
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WizardState::ReviewProposals => WizardState::NameModel,
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WizardState::NameModel => WizardState::Done,
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WizardState::Done => WizardState::Done,
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};
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self.cursor = 0;
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self.message = None;
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}
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pub fn confirm_path(&mut self) {
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if self.cursor < self.array_paths.len() {
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let path = self.array_paths[self.cursor].clone();
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self.select_path(&path);
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self.advance();
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}
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}
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pub fn toggle_proposal(&mut self) {
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if self.cursor < self.proposals.len() {
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self.proposals[self.cursor].accepted = !self.proposals[self.cursor].accepted;
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}
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}
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pub fn cycle_proposal_kind(&mut self) {
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if self.cursor < self.proposals.len() {
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let p = &mut self.proposals[self.cursor];
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p.kind = match p.kind {
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FieldKind::Category => FieldKind::Measure,
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FieldKind::Measure => FieldKind::TimeCategory,
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FieldKind::TimeCategory => FieldKind::Label,
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FieldKind::Label => FieldKind::Category,
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};
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}
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}
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pub fn move_cursor(&mut self, delta: i32) {
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let len = match self.state {
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WizardState::SelectArrayPath => self.array_paths.len(),
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WizardState::ReviewProposals => self.proposals.len(),
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_ => 0,
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};
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if len == 0 { return; }
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if delta > 0 {
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self.cursor = (self.cursor + 1).min(len - 1);
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} else if self.cursor > 0 {
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self.cursor -= 1;
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}
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}
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pub fn push_name_char(&mut self, c: char) {
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self.model_name.push(c);
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}
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pub fn pop_name_char(&mut self) {
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self.model_name.pop();
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}
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pub fn build_model(&self) -> Result<Model> {
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let mut model = Model::new(self.model_name.clone());
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// Collect categories and measures from accepted proposals
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let categories: Vec<&FieldProposal> = self.proposals.iter()
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.filter(|p| p.accepted && matches!(p.kind, FieldKind::Category | FieldKind::TimeCategory))
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.collect();
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let measures: Vec<&FieldProposal> = self.proposals.iter()
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.filter(|p| p.accepted && p.kind == FieldKind::Measure)
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.collect();
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if categories.is_empty() {
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return Err(anyhow!("At least one category must be accepted"));
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}
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// Add categories
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for cat_proposal in &categories {
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model.add_category(&cat_proposal.field)?;
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if let Some(cat) = model.category_mut(&cat_proposal.field) {
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for val in &cat_proposal.distinct_values {
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cat.add_item(val);
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}
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}
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}
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// If there are measures, add a "Measure" category
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if !measures.is_empty() {
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model.add_category("Measure")?;
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if let Some(cat) = model.category_mut("Measure") {
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for m in &measures {
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cat.add_item(&m.field);
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}
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}
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}
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// Import records as cells
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for record in &self.records {
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if let Value::Object(map) = record {
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// Build base coordinate from category fields
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let mut coords: Vec<(String, String)> = vec![];
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let mut valid = true;
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for cat_proposal in &categories {
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let val = map.get(&cat_proposal.field)
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.and_then(|v| v.as_str())
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.map(|s| s.to_string())
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.or_else(|| map.get(&cat_proposal.field).map(|v| v.to_string()));
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if let Some(v) = val {
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// Ensure item exists
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if let Some(cat) = model.category_mut(&cat_proposal.field) {
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cat.add_item(&v);
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}
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coords.push((cat_proposal.field.clone(), v));
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} else {
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valid = false;
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break;
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}
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}
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if !valid { continue; }
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// Add each measure as a cell
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for measure in &measures {
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if let Some(val) = map.get(&measure.field).and_then(|v| v.as_f64()) {
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let mut cell_coords = coords.clone();
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if !measures.is_empty() {
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cell_coords.push(("Measure".to_string(), measure.field.clone()));
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}
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let key = CellKey::new(cell_coords);
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model.set_cell(key, CellValue::Number(val));
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}
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}
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}
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}
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Ok(model)
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}
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pub fn preview_summary(&self) -> String {
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match &self.raw {
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Value::Array(arr) => {
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format!(
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"Array of {} records. Sample keys: {}",
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arr.len(),
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arr.first()
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.and_then(|r| r.as_object())
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.map(|m| m.keys().take(5).cloned().collect::<Vec<_>>().join(", "))
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.unwrap_or_default()
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)
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}
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Value::Object(map) => {
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format!(
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"Object with {} top-level keys: {}",
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map.len(),
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map.keys().take(10).cloned().collect::<Vec<_>>().join(", ")
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)
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}
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_ => "Unknown JSON structure".to_string(),
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}
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}
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}
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