company tab v0.1

app.py

@@ -11,6 +11,7 @@ You may obtain a copy of the License at
 App URL: https://huggingface.co/spaces/reddgr/sss
 '''
 
+### DEBUGGING COMMAND (DGR):
 # cd C:\Users\david\Documents\git\miax-tfm-dgr; python app.py
 from pathlib import Path
 from typing import Tuple
@@ -38,7 +39,6 @@ tokens = env_options.check_env(use_dotenv=USE_DOTENV, dotenv_path=DOTENV_PATH, e
 
 emb_model = SentenceTransformer(EMB_MODEL_PATH, token = tokens.get("HF_TOKEN"))
 
-
 #### CONEXIÓN DE DUCKDB CON EL DATASET PARA INDEXAR ####
 print("Initializing DuckDB connection...")
 con = duckdb.connect()
@@ -67,14 +67,16 @@ last_search_query: str = ""
 last_column_filters: list[tuple[str, str]] = []
 last_sort_col_label: str = ""
 last_sort_dir: str = ""
+selected_ticker: str = ""
 
 # ---------------------------------------------------------------------------
 # CONFIG --------------------------------------------------------------------
 # ---------------------------------------------------------------------------
-app_dataset = load_dataset(DATASET_PATH, split="train", token = tokens.get("HF_TOKEN")).to_pandas()
 
+app_dataset = load_dataset(DATASET_PATH, split="train", token = tokens.get("HF_TOKEN")).to_pandas()
 dh_app = fdh.FrontDatasetHandler(app_dataset=app_dataset)
 maestro = dh_app.app_dataset[dh_app.app_dataset['quoteType']=='EQUITY'].copy()
+print("maestro_columns", maestro.columns.to_list())
 maestro_etf = dh_app.app_dataset[dh_app.app_dataset['quoteType']=='ETF'].copy()
 
 with open(JSON_PATH / "app_column_config.json", "r") as f:
@@ -295,8 +297,20 @@ def reset_initial() -> tuple[pd.DataFrame,str,int,str,str,str]:
 # DATOS INICIALES -----------------------------------------------------------
 # ---------------------------------------------------------------------------
 
+#last_result_df = utils.format_results(maestro[caracteristicas].head(MAX_ROWS).copy(), rename_columns)
+#_initial_slice, _initial_label = _paginate(last_result_df, 1)
+
 last_result_df = utils.format_results(maestro[caracteristicas].head(MAX_ROWS).copy(), rename_columns)
 _initial_slice, _initial_label = _paginate(last_result_df, 1)
+# Ticker por defecto es el primero de la lista
+if not last_result_df.empty:
+    selected_ticker = last_result_df.iloc[0][rename_columns.get('ticker','ticker')]
+# Fetch initial company info
+if selected_ticker:
+    init_name, init_summary, init_details = utils.get_company_info(maestro, selected_ticker, rename_columns)
+else:
+    init_name, init_summary, init_details = "", "", pd.DataFrame()
+
 
 # ---------------------------------------------------------------------------
 # UI ------------------------------------------------------------------------
@@ -313,7 +327,7 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
     # ---------------------- TOP INPUT -------------------------------------
     with gr.Row(equal_height=True):
         theme_input = gr.Textbox(show_label=False, placeholder="Search a theme. i.e. 'lithium'", scale=2)
-        ticker_input = gr.Textbox(show_label=False, placeholder="Enter a ticker symbol", scale=1)   
+        ticker_input = gr.Textbox(show_label=False, placeholder="Enter a ticker symbol. i.e. 'nvda'", scale=1)   
         buscar_button = gr.Button("Search")
         gr.HTML("<div></div>")
         reset_button = gr.Button("Reset", elem_classes="small-btn")
@@ -323,38 +337,132 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
     # ---------------------- SEARCH SUMMARY ------------------------
     summary_display = gr.Markdown("", elem_classes="search-spec")
 
-    # ---------------------- DATAFRAME & PAGINATION ------------------------
-
-    output_df = gr.Dataframe(
-        value=_initial_slice,
-        interactive=False,
-        elem_classes="clickable-columns",
-        # max_height=500
+    # ---------------------- RESULTS ↔ COMPANY TABS ----------------------------
+    with gr.Tabs(selected=0) as main_tabs:                  # 0 = “Results”
+        # ---- TAB 1: GRID --------------------------------------------------
+        with gr.TabItem("Grid"):
+            output_df = gr.Dataframe(
+                value=_initial_slice,
+                interactive=False,
+                elem_classes="df-cells",
+            )
+
+            with gr.Row():
+                btn_prev  = gr.Button("Previous", elem_classes="small-btn")
+                pagination_label = gr.Markdown(_initial_label)
+                btn_next  = gr.Button("Next", elem_classes="small-btn")
+                gr.Markdown("&nbsp;" * 20)
+                sort_col = gr.Dropdown(
+                    [rename_columns.get(c, c) for c in caracteristicas],
+                    value=None,
+                    label="Reset and sort by:",
+                    allow_custom_value=False,
+                    scale=2,
+                )
+                sort_dir = gr.Radio(
+                    ["Ascending", "Descending"],
+                    value="Descending",
+                    label="",
+                    scale=1,
+                )
+
+        # ---- TAB 2: COMPANY --------------------------------------------------
+        with gr.TabItem("Company details")as company_tab: ####
+            company_title   = gr.Markdown(f"## {init_name}" if init_name else "### Company Name")
+            company_summary = gr.Markdown(init_summary)
+            company_details = gr.Dataframe(value=init_details, interactive=False)
+
+    def on_company_tab(evt: gr.SelectData):
+        global selected_ticker
+        if evt.selected and selected_ticker:
+            maestro_details = maestro.copy()
+            maestro_details.drop(columns=["embeddings"], inplace=True, errors="ignore")
+            name, summary, details_df = utils.get_company_info(maestro_details, selected_ticker, rename_columns)
+            return (
+                gr.update(value=f"## {name}"),
+                gr.update(value=summary),
+                gr.update(value=details_df)
+            )
+        return gr.update(), gr.update(), gr.update()
+
+    company_tab.select(
+        on_company_tab,
+        inputs=[],
+        outputs=[company_title, company_summary, company_details]
     )
 
+            
+    page_state = gr.State(1)
 
-    # ---------------------- PAGINATION AND SORT CONTROLS ---------------------
-    with gr.Row():
-        btn_prev = gr.Button("Previous", elem_classes="small-btn")
-        pagination_label = gr.Markdown(_initial_label)
-        btn_next = gr.Button("Next", elem_classes="small-btn")
-        gr.Markdown("&nbsp;" * 20)
-        # merged sort controls on right
-        sort_col = gr.Dropdown(
-            choices=[rename_columns.get(c, c) for c in caracteristicas],
-            value=None,
-            label="Reset and sort by:",
-            allow_custom_value=False,
-            scale=2,
+
+    # ---------------------- COMPANY DETAIL ---------------------
+    def on_table_select(evt: gr.SelectData):
+        print(f"DEBUG on_table_select called: index={evt.index}, value={evt.value}")
+        global last_result_df, selected_ticker
+        row_i, col_i = evt.index
+        if col_i == 0:
+            ticker = evt.value
+            print(f"DEBUG ticker extracted: {ticker}")
+            selected_ticker = ticker
+        elif col_i == 1 or (4 <= col_i <= 10):
+            display_col = rename_columns.get("ticker", "ticker")
+            ticker = last_result_df.iloc[row_i][display_col]
+            print(f"DEBUG ticker extracted: {ticker}")
+        else:
+            return filter_by_column(evt) + (
+                gr.update(selected=0), "", "", pd.DataFrame()
+            )
+        name, summary, details_df = utils.get_company_info(
+            maestro, ticker, rename_columns
         )
-        sort_dir = gr.Radio(
-            choices=["Ascending", "Descending"],
-            value="Descending",
-            label="",
-            scale=1,
+        print(f"DEBUG ➡ selected ticker={ticker}, name={name}")
+        return (
+            last_result_df,
+            pagination_label,
+            page_state,
+            summary_display,
+            gr.update(selected=1),         # ← change here
+            gr.update(value=f"## {name}"),
+            gr.update(value=summary),
+            gr.update(value=details_df)
         )
 
-    page_state = gr.State(1)
+
+    output_df.select(
+        on_table_select,
+        inputs=[],
+        outputs=[
+            output_df, pagination_label, page_state, summary_display,
+            main_tabs, company_title, company_summary, company_details
+        ]
+    )
+
+    # — Update company‑details whenever the table’s first row changes —
+    def on_df_first_row_change(df: pd.DataFrame):
+        global selected_ticker
+        # if table is empty, do nothing
+        if df is None or df.empty:
+            return gr.update(), gr.update(), gr.update()
+        # extract ticker from first row
+        ticker_col = rename_columns.get('ticker','ticker')
+        new_ticker = df.iloc[0][ticker_col]
+        # if it really changed, fetch new info
+        if new_ticker != selected_ticker:
+            selected_ticker = new_ticker
+            name, summary, details_df = utils.get_company_info(maestro, selected_ticker, rename_columns)
+            return (
+                gr.update(value=f"## {name}"),
+                gr.update(value=summary),
+                gr.update(value=details_df)
+            )
+        # otherwise leave components as‑is
+        return gr.update(), gr.update(), gr.update()
+
+    output_df.change(
+        on_df_first_row_change,
+        inputs=[output_df],
+        outputs=[company_title, company_summary, company_details]
+    )
 
     # ---------------------- EXCLUSION FILTER TOGGLES --------------------------------
     # De momento excluimos esta funcionalidad, al menos en la tabla de acciones, 
@@ -394,7 +502,7 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
     )
 
     ticker_input.submit(
-        reset_page, None, page_state
+        reset_page, [], page_state
     ).then(
         search_all,
         inputs=inputs,
@@ -402,7 +510,7 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
     )
 
     theme_input.submit(
-        reset_page, None, page_state
+        reset_page, [], page_state
     ).then(
         search_all,
         inputs=inputs,
@@ -411,7 +519,7 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
 
     random_button.click(
         random_action,
-        None,
+        [],
         [ticker_input, page_state, theme_input]
     ).then(
         search_all,
@@ -421,7 +529,7 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
 
     reset_button.click(
         reset_initial,
-        None,
+        [],
         [output_df, pagination_label, page_state, ticker_input, theme_input, sort_col, summary_display]
     )
 
@@ -453,6 +561,18 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
         outputs=[output_df, pagination_label, page_state, summary_display]
     )
 
+
+    def on_tab_change(tab_index):
+        if tab_index == 1 and selected_ticker:
+            name, summary, details_df = utils.get_company_info(maestro, selected_ticker, rename_columns)
+            return (
+                gr.update(value=f"## {name}"),
+                gr.update(value=summary),
+                gr.update(value=details_df)
+            )
+        return gr.update(), gr.update(), gr.update()
+
+
     # ---------------------- FILTERS BY COLUMN ------------------ #
     filterable_columns = [rename_columns.get(c, c) for c in cat_cols]
 
@@ -472,12 +592,6 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
         summary = _compose_summary()
         return slice_df, label, 1, summary
 
-
-    output_df.select(
-        filter_by_column,
-        outputs=[output_df, pagination_label, page_state, summary_display]
-    )
-
 # ---------------------------------------------------------------------------
 # LAUNCH --------------------------------------------------------------------
 # ---------------------------------------------------------------------------

src/app_utils.py

@@ -93,4 +93,37 @@ def get_company_info(
     })
     df["Field"] = df["Field"].map(lambda c: rename_columns.get(c, c))
 
+    # Round _norm fields to 3 decimal places
+    for i, field in enumerate(df["Field"]):
+        if field.endswith("_norm"):
+            value = df.iloc[i]["Value"]
+            if isinstance(value, (int, float)) and not pd.isna(value):
+                df.iloc[i, df.columns.get_loc("Value")] = round(value, 3)
+        # Process numeric fields using format_results function
+        # Extract numeric fields (excluding already processed _norm fields)
+        numeric_fields = []
+        numeric_values = []
+        numeric_indices = []
+        
+        for i, (display_field, value) in enumerate(zip(df["Field"], df["Value"])):
+            if not display_field.endswith("_norm") and isinstance(value, (int, float)) and not pd.isna(value):
+                # Get original field name using inverse rename dictionary
+                orig_field = next((k for k, v in rename_columns.items() if v == display_field), display_field)
+                numeric_fields.append(orig_field)
+                numeric_values.append(value)
+                numeric_indices.append(i)
+        
+        if numeric_fields:
+            # Create a single-row dataframe with original field names
+            temp_df = pd.DataFrame([numeric_values], columns=numeric_fields)
+            
+            # Apply format_results function
+            formatted_df = format_results(temp_df, rename_columns)
+            
+            # Put formatted values back into the original dataframe
+            for i, field in zip(numeric_indices, numeric_fields):
+                display_field = rename_columns.get(field, field)
+                df.iloc[i, df.columns.get_loc("Value")] = formatted_df.iloc[0][display_field]
+        
+
     return name, summary, df