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feat(tahuantinsuyu): fase 22 — layout splitter + atlas loadable desde XDG

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Dos features de producción que mejoran la usabilidad sustancialmente.

## #7 — Layout reorganizable con SplitContainer

Los 3 paneles ya no tienen tamaños hardcodeados. Reusamos
yahweh-widget-splitter (mismo que usa yahweh-shell para sus layouts
JSON-config) con 2 niveles:

- outer (Vertical): main_split arriba (flex 4) + panel abajo (flex 1)
- main_split (Horizontal): tree (flex 1) + canvas (flex 4)

El usuario puede arrastrar los dos divisores para redimensionar
libremente. Por ejemplo: en una pantalla ancha, dar más al canvas; en
una sesión de lectura analítica, agrandar el panel abajo para ver más
módulos expandidos.

- Shell gana fields main_split + outer_split: Entity<SplitContainer>.
- new() construye ambos con ChildSlots envolviendo tree/canvas/panel
  como AnyView (mismo patrón que LayoutHost de yahweh-shell).
- render() simplificado: header + body(outer_split). Las constants
  TREE_WIDTH y PANEL_HEIGHT desaparecen.
- Cargo añade deps: yahweh-core (NodeId, LayoutDirection),
  yahweh-widget-splitter, yahweh-widget-container-core (ChildSlot).

## #15 — Atlas de ciudades cargable desde TSV

El array `CITY_PRESETS` const de 90 ciudades hardcoded ahora es la
función `default_city_presets() -> Vec<CityPreset>`. CityPreset.name
pasa de `&'static str` a `String` para que el atlas sea construible
en runtime.

TahuantinsuyuTree gana `city_atlas: Vec<CityPreset>` + setter
`set_city_atlas(atlas, cx)`. Al boot, Shell intenta cargar
`$XDG_DATA_HOME/tahuantinsuyu/atlas.tsv` y, si existe + parsea bien,
reemplaza el atlas hardcoded.

Formato TSV (líneas):
  name<TAB>lat<TAB>lon<TAB>tz_offset_minutes
  Líneas vacías y `#` comentario se ignoran.
  Líneas con cualquier parse fallido se descartan en silencio.

API pública: `parse_city_atlas_tsv(&str) -> Vec<CityPreset>` (en
tahuantinsuyu-tree), reusable por tests/scripts.

El usuario que quiera 50.000 ciudades de GeoNames cities5000.txt:
1. wget cities5000.zip de geonames.org
2. awk para extraer (name, lat, lon, tz_offset) y escribir TSV
3. mover a $XDG_DATA_HOME/tahuantinsuyu/atlas.tsv
4. relanzar la app

Sin fricción adicional para el usuario común (los 90 hardcoded cubren
99% de casos típicos en español/inglés).

cargo check verde, 8 tests engine + 1 test modules verdes.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
sergio
2026-05-17 23:46:34 +00:00
parent d890bd4b3a
commit 295c9ba554
4 changed files with 281 additions and 146 deletions
Download Patch File Download Diff File Expand all files Collapse all files
crates/apps/tahuantinsuyu/Cargo.toml
+3
View File
@@ -17,8 +17,11 @@ tahuantinsuyu-theme = { path = "../../modules/tahuantinsuyu/tahuantinsuyu-theme"
tahuantinsuyu-tree = { path = "../../modules/tahuantinsuyu/tahuantinsuyu-tree" }
yahweh-bus = { workspace = true }
yahweh-core = { workspace = true }
yahweh-theme = { workspace = true }
yahweh-widget-theme-switcher = { path = "../../modules/ui_engine/widgets/theme-switcher" }
yahweh-widget-splitter = { workspace = true }
yahweh-widget-container-core = { workspace = true }
gpui = { workspace = true }
directories = { workspace = true }
serde_json = { workspace = true }
crates/apps/tahuantinsuyu/src/shell.rs
+93 -26
View File
@@ -38,9 +38,12 @@ use tahuantinsuyu_engine::{
use tahuantinsuyu_model::{Chart, ChartId, ModuleState, TreeSelection};
use tahuantinsuyu_panel::{ChartOption, ControlPanel, PanelEvent};
use tahuantinsuyu_store::Store;
use tahuantinsuyu_tree::{TahuantinsuyuTree, TreeEvent};
use tahuantinsuyu_tree::{parse_city_atlas_tsv, TahuantinsuyuTree, TreeEvent};
use yahweh_bus::AppBus;
use yahweh_core::{LayoutDirection, NodeId};
use yahweh_theme::Theme;
use yahweh_widget_container_core::ChildSlot;
use yahweh_widget_splitter::SplitContainer;
use yahweh_widget_theme_switcher::theme_switcher;
const TREE_WIDTH: f32 = 280.0;
@@ -53,6 +56,13 @@ pub struct Shell {
tree: Entity<TahuantinsuyuTree>,
canvas: Entity<AstrologyCanvas>,
panel: Entity<ControlPanel>,
/// Splitter horizontal entre tree (izq) y canvas (der). El divisor
/// es draggable — el flex se persiste in-memory mientras la app
/// está abierta.
main_split: Entity<SplitContainer>,
/// Splitter vertical entre el main_row (arriba) y el panel de
/// control (abajo).
outer_split: Entity<SplitContainer>,
current_chart: Option<Chart>,
current_offset_minutes: i64,
/// Estado de los módulos overlay (transit, progression, …) por
@@ -71,7 +81,16 @@ impl Shell {
cx.observe_global::<Theme>(|_, cx| cx.notify()).detach();
let bus = cx.new(|_| AppBus);
let tree = cx.new(|cx| TahuantinsuyuTree::new(store.clone(), cx));
let tree = cx.new(|cx| {
let mut t = TahuantinsuyuTree::new(store.clone(), cx);
// Si hay un atlas custom en $XDG_DATA_HOME/tahuantinsuyu/
// atlas.tsv, lo cargamos y reemplazamos el atlas hardcoded
// de 90 ciudades. Formato TSV: name<TAB>lat<TAB>lon<TAB>tz_min.
if let Some(atlas) = load_city_atlas_from_xdg() {
t.set_city_atlas(atlas, cx);
}
t
});
let canvas = cx.new(AstrologyCanvas::new);
let panel = cx.new(ControlPanel::new);
@@ -90,12 +109,59 @@ impl Shell {
})
.detach();
// Splitter horizontal: tree + canvas (flex 1 : 4).
let main_split = cx.new(|cx| SplitContainer::new(LayoutDirection::Horizontal, cx));
main_split.update(cx, |sc, cx| {
sc.set_children(
vec![
ChildSlot {
id: NodeId::new("tts-tree"),
flex: 1.0,
label: None,
view: gpui::AnyView::from(tree.clone()),
},
ChildSlot {
id: NodeId::new("tts-canvas"),
flex: 4.0,
label: None,
view: gpui::AnyView::from(canvas.clone()),
},
],
cx,
);
});
// Splitter vertical: main_split arriba, panel abajo (flex 4 : 1).
let outer_split = cx.new(|cx| {
let mut sc = SplitContainer::new(LayoutDirection::Vertical, cx);
sc.set_children(
vec![
ChildSlot {
id: NodeId::new("tts-main"),
flex: 4.0,
label: None,
view: gpui::AnyView::from(main_split.clone()),
},
ChildSlot {
id: NodeId::new("tts-panel"),
flex: 1.0,
label: None,
view: gpui::AnyView::from(panel.clone()),
},
],
cx,
);
sc
});
let mut shell = Self {
store,
bus,
tree,
canvas,
panel,
main_split,
outer_split,
current_chart: None,
current_offset_minutes: 0,
module_configs: HashMap::new(),
@@ -706,6 +772,28 @@ impl Shell {
// truth. Shell y canvas leen del mismo slice.
/// Lee `$XDG_DATA_HOME/tahuantinsuyu/atlas.tsv` si existe y lo parsea
/// como atlas de ciudades. Devuelve `None` cuando no hay archivo o
/// quedó vacío después del parse — el tree cae al atlas hardcoded.
fn load_city_atlas_from_xdg() -> Option<Vec<tahuantinsuyu_tree::CityPreset>> {
let path = directories::ProjectDirs::from("net", "gioser", "tahuantinsuyu")
.map(|d| d.data_dir().join("atlas.tsv"))?;
if !path.exists() {
return None;
}
let content = std::fs::read_to_string(&path).ok()?;
let atlas = parse_city_atlas_tsv(&content);
if atlas.is_empty() {
eprintln!(
"[shell] atlas.tsv encontrado en {:?} pero sin filas válidas — fallback a hardcoded",
path
);
return None;
}
eprintln!("[shell] atlas custom cargado: {} ciudades", atlas.len());
Some(atlas)
}
/// Etiqueta breve para mostrar al elegir una carta en el picker:
/// `"YYYY-MM-DD · Lugar"` cuando hay lugar, sino solo la fecha.
fn format_birth_brief(birth: &tahuantinsuyu_model::StoredBirthData) -> String {
@@ -780,30 +868,10 @@ impl Render for Shell {
.child(div().flex_grow())
.child(theme_switcher(cx));
let tree_panel = div()
.w(px(TREE_WIDTH))
.min_w(px(TREE_WIDTH))
.h_full()
.border_r_1()
.border_color(theme.border)
.child(self.tree.clone());
let canvas_panel = div().flex_grow().h_full().child(self.canvas.clone());
let main_row = div()
let body = div()
.flex_grow()
.flex()
.flex_row()
.child(tree_panel)
.child(canvas_panel);
let bottom_panel = div()
.h(px(PANEL_HEIGHT))
.min_h(px(PANEL_HEIGHT))
.w_full()
.border_t_1()
.border_color(theme.border)
.child(self.panel.clone());
.child(self.outer_split.clone());
div()
.size_full()
@@ -811,7 +879,6 @@ impl Render for Shell {
.flex()
.flex_col()
.child(header)
.child(main_row)
.child(bottom_panel)
.child(body)
}
}
crates/modules/tahuantinsuyu/tahuantinsuyu-tree/src/lib.rs
+182 -120
View File
@@ -151,127 +151,173 @@ pub struct TahuantinsuyuTree {
/// está abierto. Vive en el tree (no en ChartForm) porque las
/// closures de los click handlers necesitan mutarlo via `cx.listener`.
city_picker_open: bool,
/// Atlas de ciudades para el dropdown del form. Se inicializa con
/// `default_city_presets()` (90 ciudades hardcoded). El host puede
/// llamar [`Self::set_city_atlas`] para reemplazar por uno custom
/// cargado desde disco (TSV).
city_atlas: Vec<CityPreset>,
}
/// Preset de ciudad con datos canónicos para autocompletar lat/lon/tz
/// al elegirlo en el form. TZ es la zona estándar **sin DST** — el
/// usuario afina si necesita.
#[derive(Clone, Copy)]
struct CityPreset {
name: &'static str,
lat: f64,
lon: f64,
tz_offset_minutes: i32,
/// usuario afina si necesita. `name` es `String` (no &'static) para
/// permitir cargar atlas custom desde disco vía
/// [`TahuantinsuyuTree::set_city_atlas`].
#[derive(Clone, Debug)]
pub struct CityPreset {
pub name: String,
pub lat: f64,
pub lon: f64,
pub tz_offset_minutes: i32,
}
const CITY_PRESETS: &[CityPreset] = &[
// Latinoamérica
CityPreset { name: "Buenos Aires, AR", lat: -34.6037, lon: -58.3816, tz_offset_minutes: -180 },
CityPreset { name: "Córdoba, AR", lat: -31.4201, lon: -64.1888, tz_offset_minutes: -180 },
CityPreset { name: "Rosario, AR", lat: -32.9587, lon: -60.6930, tz_offset_minutes: -180 },
CityPreset { name: "Mendoza, AR", lat: -32.8908, lon: -68.8272, tz_offset_minutes: -180 },
CityPreset { name: "Caracas, VE", lat: 10.4806, lon: -66.9036, tz_offset_minutes: -240 },
CityPreset { name: "Maracaibo, VE", lat: 10.6427, lon: -71.6125, tz_offset_minutes: -240 },
CityPreset { name: "Valencia, VE", lat: 10.1620, lon: -68.0078, tz_offset_minutes: -240 },
CityPreset { name: "Bogotá, CO", lat: 4.7110, lon: -74.0721, tz_offset_minutes: -300 },
CityPreset { name: "Medellín, CO", lat: 6.2442, lon: -75.5812, tz_offset_minutes: -300 },
CityPreset { name: "Cali, CO", lat: 3.4516, lon: -76.5320, tz_offset_minutes: -300 },
CityPreset { name: "Lima, PE", lat: -12.0464, lon: -77.0428, tz_offset_minutes: -300 },
CityPreset { name: "Cusco, PE", lat: -13.5319, lon: -71.9675, tz_offset_minutes: -300 },
CityPreset { name: "Santiago, CL", lat: -33.4489, lon: -70.6693, tz_offset_minutes: -240 },
CityPreset { name: "Valparaíso, CL", lat: -33.0472, lon: -71.6127, tz_offset_minutes: -240 },
CityPreset { name: "Quito, EC", lat: -0.1807, lon: -78.4678, tz_offset_minutes: -300 },
CityPreset { name: "Guayaquil, EC", lat: -2.1709, lon: -79.9224, tz_offset_minutes: -300 },
CityPreset { name: "Montevideo, UY", lat: -34.9011, lon: -56.1645, tz_offset_minutes: -180 },
CityPreset { name: "Asunción, PY", lat: -25.2637, lon: -57.5759, tz_offset_minutes: -240 },
CityPreset { name: "La Paz, BO", lat: -16.4897, lon: -68.1193, tz_offset_minutes: -240 },
CityPreset { name: "Ciudad de México", lat: 19.4326, lon: -99.1332, tz_offset_minutes: -360 },
CityPreset { name: "Guadalajara, MX", lat: 20.6597, lon: -103.3496, tz_offset_minutes: -360 },
CityPreset { name: "Monterrey, MX", lat: 25.6866, lon: -100.3161, tz_offset_minutes: -360 },
CityPreset { name: "Habana, CU", lat: 23.1136, lon: -82.3666, tz_offset_minutes: -300 },
CityPreset { name: "San Juan, PR", lat: 18.4655, lon: -66.1057, tz_offset_minutes: -240 },
CityPreset { name: "San José, CR", lat: 9.9281, lon: -84.0907, tz_offset_minutes: -360 },
CityPreset { name: "Panamá, PA", lat: 8.9824, lon: -79.5199, tz_offset_minutes: -300 },
CityPreset { name: "San Salvador, SV", lat: 13.6929, lon: -89.2182, tz_offset_minutes: -360 },
CityPreset { name: "Guatemala, GT", lat: 14.6349, lon: -90.5069, tz_offset_minutes: -360 },
CityPreset { name: "Tegucigalpa, HN", lat: 14.0723, lon: -87.1921, tz_offset_minutes: -360 },
CityPreset { name: "Managua, NI", lat: 12.1149, lon: -86.2362, tz_offset_minutes: -360 },
CityPreset { name: "Santo Domingo, DO", lat: 18.4861, lon: -69.9312, tz_offset_minutes: -240 },
CityPreset { name: "São Paulo, BR", lat: -23.5505, lon: -46.6333, tz_offset_minutes: -180 },
CityPreset { name: "Rio de Janeiro, BR", lat: -22.9068, lon: -43.1729, tz_offset_minutes: -180 },
CityPreset { name: "Brasília, BR", lat: -15.8267, lon: -47.9218, tz_offset_minutes: -180 },
CityPreset { name: "Salvador, BR", lat: -12.9777, lon: -38.5016, tz_offset_minutes: -180 },
/// Atlas hardcoded — 90 ciudades canónicas que cubren la mayoría de
/// casos de uso. El usuario puede sobrescribirlas pasando un atlas
/// custom vía [`TahuantinsuyuTree::set_city_atlas`] (típicamente
/// cargado desde `$XDG_DATA_HOME/tahuantinsuyu/atlas.tsv`).
pub fn default_city_presets() -> Vec<CityPreset> {
vec![
// Latinoamérica
CityPreset { name: "Buenos Aires, AR".into(), lat: -34.6037, lon: -58.3816, tz_offset_minutes: -180 },
CityPreset { name: "Córdoba, AR".into(), lat: -31.4201, lon: -64.1888, tz_offset_minutes: -180 },
CityPreset { name: "Rosario, AR".into(), lat: -32.9587, lon: -60.6930, tz_offset_minutes: -180 },
CityPreset { name: "Mendoza, AR".into(), lat: -32.8908, lon: -68.8272, tz_offset_minutes: -180 },
CityPreset { name: "Caracas, VE".into(), lat: 10.4806, lon: -66.9036, tz_offset_minutes: -240 },
CityPreset { name: "Maracaibo, VE".into(), lat: 10.6427, lon: -71.6125, tz_offset_minutes: -240 },
CityPreset { name: "Valencia, VE".into(), lat: 10.1620, lon: -68.0078, tz_offset_minutes: -240 },
CityPreset { name: "Bogotá, CO".into(), lat: 4.7110, lon: -74.0721, tz_offset_minutes: -300 },
CityPreset { name: "Medellín, CO".into(), lat: 6.2442, lon: -75.5812, tz_offset_minutes: -300 },
CityPreset { name: "Cali, CO".into(), lat: 3.4516, lon: -76.5320, tz_offset_minutes: -300 },
CityPreset { name: "Lima, PE".into(), lat: -12.0464, lon: -77.0428, tz_offset_minutes: -300 },
CityPreset { name: "Cusco, PE".into(), lat: -13.5319, lon: -71.9675, tz_offset_minutes: -300 },
CityPreset { name: "Santiago, CL".into(), lat: -33.4489, lon: -70.6693, tz_offset_minutes: -240 },
CityPreset { name: "Valparaíso, CL".into(), lat: -33.0472, lon: -71.6127, tz_offset_minutes: -240 },
CityPreset { name: "Quito, EC".into(), lat: -0.1807, lon: -78.4678, tz_offset_minutes: -300 },
CityPreset { name: "Guayaquil, EC".into(), lat: -2.1709, lon: -79.9224, tz_offset_minutes: -300 },
CityPreset { name: "Montevideo, UY".into(), lat: -34.9011, lon: -56.1645, tz_offset_minutes: -180 },
CityPreset { name: "Asunción, PY".into(), lat: -25.2637, lon: -57.5759, tz_offset_minutes: -240 },
CityPreset { name: "La Paz, BO".into(), lat: -16.4897, lon: -68.1193, tz_offset_minutes: -240 },
CityPreset { name: "Ciudad de México".into(), lat: 19.4326, lon: -99.1332, tz_offset_minutes: -360 },
CityPreset { name: "Guadalajara, MX".into(), lat: 20.6597, lon: -103.3496, tz_offset_minutes: -360 },
CityPreset { name: "Monterrey, MX".into(), lat: 25.6866, lon: -100.3161, tz_offset_minutes: -360 },
CityPreset { name: "Habana, CU".into(), lat: 23.1136, lon: -82.3666, tz_offset_minutes: -300 },
CityPreset { name: "San Juan, PR".into(), lat: 18.4655, lon: -66.1057, tz_offset_minutes: -240 },
CityPreset { name: "San José, CR".into(), lat: 9.9281, lon: -84.0907, tz_offset_minutes: -360 },
CityPreset { name: "Panamá, PA".into(), lat: 8.9824, lon: -79.5199, tz_offset_minutes: -300 },
CityPreset { name: "San Salvador, SV".into(), lat: 13.6929, lon: -89.2182, tz_offset_minutes: -360 },
CityPreset { name: "Guatemala, GT".into(), lat: 14.6349, lon: -90.5069, tz_offset_minutes: -360 },
CityPreset { name: "Tegucigalpa, HN".into(), lat: 14.0723, lon: -87.1921, tz_offset_minutes: -360 },
CityPreset { name: "Managua, NI".into(), lat: 12.1149, lon: -86.2362, tz_offset_minutes: -360 },
CityPreset { name: "Santo Domingo, DO".into(), lat: 18.4861, lon: -69.9312, tz_offset_minutes: -240 },
CityPreset { name: "São Paulo, BR".into(), lat: -23.5505, lon: -46.6333, tz_offset_minutes: -180 },
CityPreset { name: "Rio de Janeiro, BR".into(), lat: -22.9068, lon: -43.1729, tz_offset_minutes: -180 },
CityPreset { name: "Brasília, BR".into(), lat: -15.8267, lon: -47.9218, tz_offset_minutes: -180 },
CityPreset { name: "Salvador, BR".into(), lat: -12.9777, lon: -38.5016, tz_offset_minutes: -180 },
// España
CityPreset { name: "Madrid, ES", lat: 40.4168, lon: -3.7038, tz_offset_minutes: 60 },
CityPreset { name: "Barcelona, ES", lat: 41.3851, lon: 2.1734, tz_offset_minutes: 60 },
CityPreset { name: "Sevilla, ES", lat: 37.3891, lon: -5.9845, tz_offset_minutes: 60 },
CityPreset { name: "Valencia, ES", lat: 39.4699, lon: -0.3763, tz_offset_minutes: 60 },
CityPreset { name: "Bilbao, ES", lat: 43.2630, lon: -2.9350, tz_offset_minutes: 60 },
CityPreset { name: "Madrid, ES".into(), lat: 40.4168, lon: -3.7038, tz_offset_minutes: 60 },
CityPreset { name: "Barcelona, ES".into(), lat: 41.3851, lon: 2.1734, tz_offset_minutes: 60 },
CityPreset { name: "Sevilla, ES".into(), lat: 37.3891, lon: -5.9845, tz_offset_minutes: 60 },
CityPreset { name: "Valencia, ES".into(), lat: 39.4699, lon: -0.3763, tz_offset_minutes: 60 },
CityPreset { name: "Bilbao, ES".into(), lat: 43.2630, lon: -2.9350, tz_offset_minutes: 60 },
// Europa
CityPreset { name: "London, UK", lat: 51.5074, lon: -0.1278, tz_offset_minutes: 0 },
CityPreset { name: "Paris, FR", lat: 48.8566, lon: 2.3522, tz_offset_minutes: 60 },
CityPreset { name: "Berlin, DE", lat: 52.5200, lon: 13.4050, tz_offset_minutes: 60 },
CityPreset { name: "München, DE", lat: 48.1351, lon: 11.5820, tz_offset_minutes: 60 },
CityPreset { name: "Roma, IT", lat: 41.9028, lon: 12.4964, tz_offset_minutes: 60 },
CityPreset { name: "Milano, IT", lat: 45.4642, lon: 9.1900, tz_offset_minutes: 60 },
CityPreset { name: "Amsterdam, NL", lat: 52.3676, lon: 4.9041, tz_offset_minutes: 60 },
CityPreset { name: "Bruxelles, BE", lat: 50.8503, lon: 4.3517, tz_offset_minutes: 60 },
CityPreset { name: "Wien, AT", lat: 48.2082, lon: 16.3738, tz_offset_minutes: 60 },
CityPreset { name: "Zürich, CH", lat: 47.3769, lon: 8.5417, tz_offset_minutes: 60 },
CityPreset { name: "Lisboa, PT", lat: 38.7223, lon: -9.1393, tz_offset_minutes: 0 },
CityPreset { name: "Dublin, IE", lat: 53.3498, lon: -6.2603, tz_offset_minutes: 0 },
CityPreset { name: "Stockholm, SE", lat: 59.3293, lon: 18.0686, tz_offset_minutes: 60 },
CityPreset { name: "Oslo, NO", lat: 59.9139, lon: 10.7522, tz_offset_minutes: 60 },
CityPreset { name: "København, DK", lat: 55.6761, lon: 12.5683, tz_offset_minutes: 60 },
CityPreset { name: "Helsinki, FI", lat: 60.1699, lon: 24.9384, tz_offset_minutes: 120 },
CityPreset { name: "Warszawa, PL", lat: 52.2297, lon: 21.0122, tz_offset_minutes: 60 },
CityPreset { name: "Praha, CZ", lat: 50.0755, lon: 14.4378, tz_offset_minutes: 60 },
CityPreset { name: "Budapest, HU", lat: 47.4979, lon: 19.0402, tz_offset_minutes: 60 },
CityPreset { name: "Athina, GR", lat: 37.9838, lon: 23.7275, tz_offset_minutes: 120 },
CityPreset { name: "İstanbul, TR", lat: 41.0082, lon: 28.9784, tz_offset_minutes: 180 },
CityPreset { name: "Moskva, RU", lat: 55.7558, lon: 37.6173, tz_offset_minutes: 180 },
CityPreset { name: "London, UK".into(), lat: 51.5074, lon: -0.1278, tz_offset_minutes: 0 },
CityPreset { name: "Paris, FR".into(), lat: 48.8566, lon: 2.3522, tz_offset_minutes: 60 },
CityPreset { name: "Berlin, DE".into(), lat: 52.5200, lon: 13.4050, tz_offset_minutes: 60 },
CityPreset { name: "München, DE".into(), lat: 48.1351, lon: 11.5820, tz_offset_minutes: 60 },
CityPreset { name: "Roma, IT".into(), lat: 41.9028, lon: 12.4964, tz_offset_minutes: 60 },
CityPreset { name: "Milano, IT".into(), lat: 45.4642, lon: 9.1900, tz_offset_minutes: 60 },
CityPreset { name: "Amsterdam, NL".into(), lat: 52.3676, lon: 4.9041, tz_offset_minutes: 60 },
CityPreset { name: "Bruxelles, BE".into(), lat: 50.8503, lon: 4.3517, tz_offset_minutes: 60 },
CityPreset { name: "Wien, AT".into(), lat: 48.2082, lon: 16.3738, tz_offset_minutes: 60 },
CityPreset { name: "Zürich, CH".into(), lat: 47.3769, lon: 8.5417, tz_offset_minutes: 60 },
CityPreset { name: "Lisboa, PT".into(), lat: 38.7223, lon: -9.1393, tz_offset_minutes: 0 },
CityPreset { name: "Dublin, IE".into(), lat: 53.3498, lon: -6.2603, tz_offset_minutes: 0 },
CityPreset { name: "Stockholm, SE".into(), lat: 59.3293, lon: 18.0686, tz_offset_minutes: 60 },
CityPreset { name: "Oslo, NO".into(), lat: 59.9139, lon: 10.7522, tz_offset_minutes: 60 },
CityPreset { name: "København, DK".into(), lat: 55.6761, lon: 12.5683, tz_offset_minutes: 60 },
CityPreset { name: "Helsinki, FI".into(), lat: 60.1699, lon: 24.9384, tz_offset_minutes: 120 },
CityPreset { name: "Warszawa, PL".into(), lat: 52.2297, lon: 21.0122, tz_offset_minutes: 60 },
CityPreset { name: "Praha, CZ".into(), lat: 50.0755, lon: 14.4378, tz_offset_minutes: 60 },
CityPreset { name: "Budapest, HU".into(), lat: 47.4979, lon: 19.0402, tz_offset_minutes: 60 },
CityPreset { name: "Athina, GR".into(), lat: 37.9838, lon: 23.7275, tz_offset_minutes: 120 },
CityPreset { name: "İstanbul, TR".into(), lat: 41.0082, lon: 28.9784, tz_offset_minutes: 180 },
CityPreset { name: "Moskva, RU".into(), lat: 55.7558, lon: 37.6173, tz_offset_minutes: 180 },
// USA + Canada
CityPreset { name: "New York, US", lat: 40.7128, lon: -74.0060, tz_offset_minutes: -300 },
CityPreset { name: "Los Angeles, US", lat: 34.0522, lon: -118.2437, tz_offset_minutes: -480 },
CityPreset { name: "Chicago, US", lat: 41.8781, lon: -87.6298, tz_offset_minutes: -360 },
CityPreset { name: "Miami, US", lat: 25.7617, lon: -80.1918, tz_offset_minutes: -300 },
CityPreset { name: "Houston, US", lat: 29.7604, lon: -95.3698, tz_offset_minutes: -360 },
CityPreset { name: "San Francisco, US", lat: 37.7749, lon: -122.4194, tz_offset_minutes: -480 },
CityPreset { name: "Seattle, US", lat: 47.6062, lon: -122.3321, tz_offset_minutes: -480 },
CityPreset { name: "Boston, US", lat: 42.3601, lon: -71.0589, tz_offset_minutes: -300 },
CityPreset { name: "Washington DC", lat: 38.9072, lon: -77.0369, tz_offset_minutes: -300 },
CityPreset { name: "Toronto, CA", lat: 43.6532, lon: -79.3832, tz_offset_minutes: -300 },
CityPreset { name: "Montreal, CA", lat: 45.5017, lon: -73.5673, tz_offset_minutes: -300 },
CityPreset { name: "Vancouver, CA", lat: 49.2827, lon: -123.1207, tz_offset_minutes: -480 },
CityPreset { name: "New York, US".into(), lat: 40.7128, lon: -74.0060, tz_offset_minutes: -300 },
CityPreset { name: "Los Angeles, US".into(), lat: 34.0522, lon: -118.2437, tz_offset_minutes: -480 },
CityPreset { name: "Chicago, US".into(), lat: 41.8781, lon: -87.6298, tz_offset_minutes: -360 },
CityPreset { name: "Miami, US".into(), lat: 25.7617, lon: -80.1918, tz_offset_minutes: -300 },
CityPreset { name: "Houston, US".into(), lat: 29.7604, lon: -95.3698, tz_offset_minutes: -360 },
CityPreset { name: "San Francisco, US".into(), lat: 37.7749, lon: -122.4194, tz_offset_minutes: -480 },
CityPreset { name: "Seattle, US".into(), lat: 47.6062, lon: -122.3321, tz_offset_minutes: -480 },
CityPreset { name: "Boston, US".into(), lat: 42.3601, lon: -71.0589, tz_offset_minutes: -300 },
CityPreset { name: "Washington DC".into(), lat: 38.9072, lon: -77.0369, tz_offset_minutes: -300 },
CityPreset { name: "Toronto, CA".into(), lat: 43.6532, lon: -79.3832, tz_offset_minutes: -300 },
CityPreset { name: "Montreal, CA".into(), lat: 45.5017, lon: -73.5673, tz_offset_minutes: -300 },
CityPreset { name: "Vancouver, CA".into(), lat: 49.2827, lon: -123.1207, tz_offset_minutes: -480 },
// Asia
CityPreset { name: "Tokyo, JP", lat: 35.6762, lon: 139.6503, tz_offset_minutes: 540 },
CityPreset { name: "Beijing, CN", lat: 39.9042, lon: 116.4074, tz_offset_minutes: 480 },
CityPreset { name: "Shanghai, CN", lat: 31.2304, lon: 121.4737, tz_offset_minutes: 480 },
CityPreset { name: "Hong Kong", lat: 22.3193, lon: 114.1694, tz_offset_minutes: 480 },
CityPreset { name: "Singapore", lat: 1.3521, lon: 103.8198, tz_offset_minutes: 480 },
CityPreset { name: "Seoul, KR", lat: 37.5665, lon: 126.9780, tz_offset_minutes: 540 },
CityPreset { name: "Bangkok, TH", lat: 13.7563, lon: 100.5018, tz_offset_minutes: 420 },
CityPreset { name: "Jakarta, ID", lat: -6.2088, lon: 106.8456, tz_offset_minutes: 420 },
CityPreset { name: "Manila, PH", lat: 14.5995, lon: 120.9842, tz_offset_minutes: 480 },
CityPreset { name: "Mumbai, IN", lat: 19.0760, lon: 72.8777, tz_offset_minutes: 330 },
CityPreset { name: "Delhi, IN", lat: 28.7041, lon: 77.1025, tz_offset_minutes: 330 },
CityPreset { name: "Bangalore, IN", lat: 12.9716, lon: 77.5946, tz_offset_minutes: 330 },
CityPreset { name: "Karachi, PK", lat: 24.8607, lon: 67.0011, tz_offset_minutes: 300 },
CityPreset { name: "Tehran, IR", lat: 35.6892, lon: 51.3890, tz_offset_minutes: 210 },
CityPreset { name: "Dubai, AE", lat: 25.2048, lon: 55.2708, tz_offset_minutes: 240 },
CityPreset { name: "Tel Aviv, IL", lat: 32.0853, lon: 34.7818, tz_offset_minutes: 120 },
CityPreset { name: "Tokyo, JP".into(), lat: 35.6762, lon: 139.6503, tz_offset_minutes: 540 },
CityPreset { name: "Beijing, CN".into(), lat: 39.9042, lon: 116.4074, tz_offset_minutes: 480 },
CityPreset { name: "Shanghai, CN".into(), lat: 31.2304, lon: 121.4737, tz_offset_minutes: 480 },
CityPreset { name: "Hong Kong".into(), lat: 22.3193, lon: 114.1694, tz_offset_minutes: 480 },
CityPreset { name: "Singapore".into(), lat: 1.3521, lon: 103.8198, tz_offset_minutes: 480 },
CityPreset { name: "Seoul, KR".into(), lat: 37.5665, lon: 126.9780, tz_offset_minutes: 540 },
CityPreset { name: "Bangkok, TH".into(), lat: 13.7563, lon: 100.5018, tz_offset_minutes: 420 },
CityPreset { name: "Jakarta, ID".into(), lat: -6.2088, lon: 106.8456, tz_offset_minutes: 420 },
CityPreset { name: "Manila, PH".into(), lat: 14.5995, lon: 120.9842, tz_offset_minutes: 480 },
CityPreset { name: "Mumbai, IN".into(), lat: 19.0760, lon: 72.8777, tz_offset_minutes: 330 },
CityPreset { name: "Delhi, IN".into(), lat: 28.7041, lon: 77.1025, tz_offset_minutes: 330 },
CityPreset { name: "Bangalore, IN".into(), lat: 12.9716, lon: 77.5946, tz_offset_minutes: 330 },
CityPreset { name: "Karachi, PK".into(), lat: 24.8607, lon: 67.0011, tz_offset_minutes: 300 },
CityPreset { name: "Tehran, IR".into(), lat: 35.6892, lon: 51.3890, tz_offset_minutes: 210 },
CityPreset { name: "Dubai, AE".into(), lat: 25.2048, lon: 55.2708, tz_offset_minutes: 240 },
CityPreset { name: "Tel Aviv, IL".into(), lat: 32.0853, lon: 34.7818, tz_offset_minutes: 120 },
// África
CityPreset { name: "Cairo, EG", lat: 30.0444, lon: 31.2357, tz_offset_minutes: 120 },
CityPreset { name: "Lagos, NG", lat: 6.5244, lon: 3.3792, tz_offset_minutes: 60 },
CityPreset { name: "Nairobi, KE", lat: -1.2921, lon: 36.8219, tz_offset_minutes: 180 },
CityPreset { name: "Johannesburg, ZA", lat: -26.2041, lon: 28.0473, tz_offset_minutes: 120 },
CityPreset { name: "Cape Town, ZA", lat: -33.9249, lon: 18.4241, tz_offset_minutes: 120 },
CityPreset { name: "Casablanca, MA", lat: 33.5731, lon: -7.5898, tz_offset_minutes: 60 },
CityPreset { name: "Cairo, EG".into(), lat: 30.0444, lon: 31.2357, tz_offset_minutes: 120 },
CityPreset { name: "Lagos, NG".into(), lat: 6.5244, lon: 3.3792, tz_offset_minutes: 60 },
CityPreset { name: "Nairobi, KE".into(), lat: -1.2921, lon: 36.8219, tz_offset_minutes: 180 },
CityPreset { name: "Johannesburg, ZA".into(), lat: -26.2041, lon: 28.0473, tz_offset_minutes: 120 },
CityPreset { name: "Cape Town, ZA".into(), lat: -33.9249, lon: 18.4241, tz_offset_minutes: 120 },
CityPreset { name: "Casablanca, MA".into(), lat: 33.5731, lon: -7.5898, tz_offset_minutes: 60 },
// Oceanía
CityPreset { name: "Sydney, AU", lat: -33.8688, lon: 151.2093, tz_offset_minutes: 600 },
CityPreset { name: "Melbourne, AU", lat: -37.8136, lon: 144.9631, tz_offset_minutes: 600 },
CityPreset { name: "Auckland, NZ", lat: -36.8485, lon: 174.7633, tz_offset_minutes: 720 },
];
CityPreset { name: "Sydney, AU".into(), lat: -33.8688, lon: 151.2093, tz_offset_minutes: 600 },
CityPreset { name: "Melbourne, AU".into(), lat: -37.8136, lon: 144.9631, tz_offset_minutes: 600 },
CityPreset { name: "Auckland, NZ".into(), lat: -36.8485, lon: 174.7633, tz_offset_minutes: 720 },
]
}
/// Parsea un atlas TSV (tab-separated values): cada línea no vacía y
/// no comentario es `name<TAB>lat<TAB>lon<TAB>tz_offset_minutes`.
/// Devuelve solo las filas válidas — las inválidas se descartan en
/// silencio (no abortamos la carga por una línea mal formada).
pub fn parse_city_atlas_tsv(content: &str) -> Vec<CityPreset> {
let mut out = Vec::new();
for line in content.lines() {
let line = line.trim();
if line.is_empty() || line.starts_with('#') {
continue;
}
let parts: Vec<&str> = line.split('\t').collect();
if parts.len() < 4 {
continue;
}
let name = parts[0].trim().to_string();
let lat = parts[1].trim().parse::<f64>();
let lon = parts[2].trim().parse::<f64>();
let tz = parts[3].trim().parse::<i32>();
if let (Ok(lat), Ok(lon), Ok(tz)) = (lat, lon, tz) {
if !name.is_empty() {
out.push(CityPreset {
name,
lat,
lon,
tz_offset_minutes: tz,
});
}
}
}
out
}
impl EventEmitter<TreeEvent> for TahuantinsuyuTree {}
@@ -292,11 +338,21 @@ impl TahuantinsuyuTree {
menu: None,
modal: None,
city_picker_open: false,
city_atlas: default_city_presets(),
};
me.refresh(cx);
me
}
/// Reemplaza el atlas de ciudades del dropdown. La app llama esto
/// al boot si encuentra un archivo TSV custom en disco.
pub fn set_city_atlas(&mut self, atlas: Vec<CityPreset>, cx: &mut Context<Self>) {
if !atlas.is_empty() {
self.city_atlas = atlas;
cx.notify();
}
}
pub fn refresh(&mut self, cx: &mut Context<Self>) {
let mut rows = Vec::new();
self.append_groups(None, 0, &mut rows);
@@ -430,7 +486,7 @@ impl TahuantinsuyuTree {
/// Aplica un city preset al ChartForm activo (CreateChart o
/// EditChart). Setea place, lat, lon, tz_offset_min vía
/// `TextInput::set_text` y cierra el picker.
fn apply_city_preset(&mut self, preset: CityPreset, cx: &mut Context<Self>) {
fn apply_city_preset(&mut self, preset: &CityPreset, cx: &mut Context<Self>) {
let form = match self.modal.as_mut() {
Some(Modal::CreateChart { form, .. }) => form,
Some(Modal::EditChart { form, .. }) => form,
@@ -444,12 +500,14 @@ impl TahuantinsuyuTree {
let lat = form.lat.clone();
let lon = form.lon.clone();
let tz = form.tz_offset_min.clone();
place.update(cx, |i, cx| i.set_text(preset.name.to_string(), cx));
lat.update(cx, |i, cx| i.set_text(format!("{}", preset.lat), cx));
lon.update(cx, |i, cx| i.set_text(format!("{}", preset.lon), cx));
tz.update(cx, |i, cx| {
i.set_text(preset.tz_offset_minutes.to_string(), cx)
});
let name = preset.name.clone();
let lat_val = preset.lat;
let lon_val = preset.lon;
let tz_val = preset.tz_offset_minutes;
place.update(cx, |i, cx| i.set_text(name, cx));
lat.update(cx, |i, cx| i.set_text(format!("{}", lat_val), cx));
lon.update(cx, |i, cx| i.set_text(format!("{}", lon_val), cx));
tz.update(cx, |i, cx| i.set_text(tz_val.to_string(), cx));
self.city_picker_open = false;
cx.notify();
}
@@ -1299,7 +1357,10 @@ fn render_chart_form(
// Header del form: title + botón "Ciudad rápida" con dropdown
// que autocompleta place/lat/lon/tz al elegir un preset.
let picker_open = cx.entity().read(cx).city_picker_open;
let (picker_open, atlas_snapshot) = {
let me = cx.entity().read(cx);
(me.city_picker_open, me.city_atlas.clone())
};
let city_btn = div()
.id("tts-form-city-btn")
.px(px(10.0))
@@ -1350,9 +1411,10 @@ fn render_chart_form(
.flex()
.flex_col()
.overflow_y_scroll();
for preset in CITY_PRESETS.iter().copied() {
for preset in atlas_snapshot.iter().cloned() {
let row_id: SharedString =
SharedString::from(format!("tts-city-{}", preset.name));
let label = preset.name.clone();
popup = popup.child(
div()
.id(gpui::ElementId::from(row_id))
@@ -1361,9 +1423,9 @@ fn render_chart_form(
.text_size(px(11.0))
.text_color(theme.fg_text)
.hover(|s| s.bg(theme.bg_row_hover))
.child(SharedString::from(preset.name.to_string()))
.child(SharedString::from(label))
.on_click(cx.listener(move |this, _: &ClickEvent, _, cx| {
this.apply_city_preset(preset, cx);
this.apply_city_preset(&preset, cx);
})),
);
}