| import io |
| import os |
| from pathlib import Path |
|
|
| import pandas as pd |
| import streamlit as st |
|
|
| from business_export_job import JobConfig, run_job |
|
|
| |
| if "SWISSPARL_OUTPUT_DIR" not in os.environ: |
| os.environ["SWISSPARL_OUTPUT_DIR"] = str(Path(__file__).parent / "output") |
|
|
| OUTPUT_DIR = Path(os.environ["SWISSPARL_OUTPUT_DIR"]) |
| OUTPUT_DIR.mkdir(parents=True, exist_ok=True) |
|
|
| st.set_page_config(page_title="SwissParl Topic Tagger – Results", layout="wide") |
| st.title("SwissParl Topic Tagger – Results") |
|
|
| with st.sidebar: |
| st.header("Actions") |
| if st.button("Trigger Topic Modelling", help="Run the topic modelling job now."): |
| with st.spinner("Running topic modelling... this may take a while."): |
| try: |
| config = JobConfig.from_env() |
| |
| if "{timestamp}" not in config.output_filename_template: |
| config = JobConfig( |
| output_dir=config.output_dir, |
| output_filename_template=config.output_filename_template.replace(".xlsx", "-{timestamp}.xlsx"), |
| days_past=config.days_past, |
| start_date=config.start_date, |
| end_date=config.end_date, |
| languages=config.languages, |
| language_priority=config.language_priority, |
| topic_score_threshold=config.topic_score_threshold, |
| min_chunk_days=config.min_chunk_days, |
| excel_sheet_name=config.excel_sheet_name, |
| ) |
| output_path = run_job(config) |
| st.success(f"Job completed! Result saved to `{output_path.name}`") |
| st.rerun() |
| except Exception as e: |
| st.error(f"Job failed: {e}") |
|
|
| excel_files = sorted(OUTPUT_DIR.glob("*.xlsx"), reverse=True) |
|
|
| if not excel_files: |
| st.warning(f"No Excel files found in `{OUTPUT_DIR}`. Use the sidebar button to run the topic modelling job.") |
| st.stop() |
|
|
| selected = st.selectbox( |
| "Select a result file", |
| excel_files, |
| format_func=lambda p: p.name, |
| ) |
|
|
|
|
| @st.cache_data |
| def load_excel(path: str) -> pd.DataFrame: |
| return pd.read_excel(path, engine="openpyxl") |
|
|
|
|
| df = load_excel(str(selected)) |
|
|
| |
| buf = io.BytesIO() |
| with pd.ExcelWriter(buf, engine="openpyxl") as writer: |
| df.to_excel(writer, index=False) |
| buf.seek(0) |
|
|
| col1, col2 = st.columns([3, 1]) |
| with col1: |
| st.caption(f"{len(df):,} rows · {len(df.columns)} columns · `{selected.name}`") |
| with col2: |
| st.download_button( |
| label="Download Excel", |
| data=buf, |
| file_name=selected.name, |
| mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", |
| ) |
|
|
| |
| search = st.text_input("Filter rows (searches all text columns)", "") |
| if search: |
| mask = df.apply( |
| lambda col: col.astype(str).str.contains(search, case=False, na=False) |
| ).any(axis=1) |
| df = df[mask] |
| st.caption(f"{len(df):,} rows match the filter") |
|
|
| st.dataframe(df, use_container_width=True, height=600) |
|
|
