src/ui.py - ui - Chaizee/ZenithCode_Incident-LLM-analytics

src/ui.py
129 строк5 KB
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Вывод UI результатов в отдельный модуль
09 июн 2026, 03:10
09 июн 2026, 03:10580712b
from __future__ import annotations

from typing import Any

import pandas as pd
import plotly.express as px
import streamlit as st

_REQUIRED_CHART_COLUMNS = {"municipality", "problem_count", "mean_severity"}


def _format_number(value: Any, digits: int = 1) -> str:
    try:
        number = float(value)
    except (TypeError, ValueError):
        return "—"

    if number.is_integer():
        return f"{int(number):,}".replace(",", " ")
    return f"{number:.{digits}f}".replace(".", ",")


def render_summary(text_summary: str | None) -> None:
    st.subheader("Справка для руководства")
    st.caption("Краткая выжимка по наиболее заметным проблемам и зонам внимания.")

    summary = (text_summary or "").strip()
    if not summary:
        st.info("Справка пока не сформирована.")
        return

    with st.container(border=True):
        st.markdown("**Executive summary**")
        st.write(summary)


def render_charts(df: pd.DataFrame | None) -> None:
    st.subheader("Аналитика по муниципалитетам")
    st.caption("Сравнение количества проблемных обращений и средней тяжести по ТОП муниципалитетов.")

    if df is None or df.empty:
        st.warning("Нет данных для построения графиков.")
        return

    missing = _REQUIRED_CHART_COLUMNS.difference(df.columns)
    if missing:
        st.warning(f"Для графиков не хватает столбцов: {', '.join(sorted(missing))}.")
        return

    chart_df = df.copy()
    chart_df["problem_count"] = pd.to_numeric(chart_df["problem_count"], errors="coerce").fillna(0)
    chart_df["mean_severity"] = pd.to_numeric(chart_df["mean_severity"], errors="coerce").fillna(0)
    chart_df = chart_df.sort_values(["problem_count", "mean_severity"], ascending=False)

    total_problems = int(chart_df["problem_count"].sum())
    avg_severity = chart_df["mean_severity"].mean()
    leader = str(chart_df.iloc[0]["municipality"]) if not chart_df.empty else "—"

    with st.container(border=True):
        col_total, col_avg, col_leader = st.columns(3)
        col_total.metric("Проблем в ТОП", _format_number(total_problems))
        col_avg.metric("Средняя тяжесть", _format_number(avg_severity, digits=2))
        col_leader.metric("Лидер по проблемам", leader)

    tab_count, tab_severity, tab_data = st.tabs([
        "Количество проблем",
        "Средняя тяжесть",
        "Данные",
    ])

    with tab_count:
        sorted_for_bar = chart_df.sort_values("problem_count", ascending=True)
        fig = px.bar(
            sorted_for_bar,
            x="problem_count",
            y="municipality",
            orientation="h",
            text="problem_count",
            labels={
                "problem_count": "Проблемных обращений",
                "municipality": "Муниципалитет",
                "mean_severity": "Средняя тяжесть",
            },
            hover_data={"mean_severity": ":.2f", "municipality": False},
        )
        fig.update_traces(textposition="outside", cliponaxis=False)
        fig.update_layout(
            height=max(360, len(chart_df) * 46),
            margin=dict(l=0, r=42, t=18, b=0),
            xaxis_title="Проблемных обращений",
            yaxis_title=None,
            showlegend=False,
        )
        st.plotly_chart(fig, use_container_width=True)

    with tab_severity:
        sorted_for_severity = chart_df.sort_values("mean_severity", ascending=True)
        fig = px.bar(
            sorted_for_severity,
            x="mean_severity",
            y="municipality",
            orientation="h",
            text=sorted_for_severity["mean_severity"].round(2),
            labels={
                "mean_severity": "Средняя тяжесть",
                "municipality": "Муниципалитет",
                "problem_count": "Проблемных обращений",
            },
            hover_data={"problem_count": True, "municipality": False},
        )
        fig.update_traces(textposition="outside", cliponaxis=False)
        fig.update_layout(
            height=max(360, len(chart_df) * 46),
            margin=dict(l=0, r=42, t=18, b=0),
            xaxis_title="Средняя тяжесть",
            yaxis_title=None,
            showlegend=False,
        )
        st.plotly_chart(fig, use_container_width=True)

    with tab_data:
        display_df = chart_df.rename(
            columns={
                "municipality": "Муниципалитет",
                "problem_count": "Проблемных обращений",
                "mean_severity": "Средняя тяжесть",
            }
        )
        st.dataframe(display_df, use_container_width=True, hide_index=True)