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@@ -18,6 +18,131 @@ except ImportError:
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st.set_page_config(page_title="Growth Segmentation Dashboard", layout="wide")
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+# ---- UI i18n ----
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+I18N = {
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+ "zh": {
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+ "dashboard_title": "Lyrria 增长看板",
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+ "sidebar_lang": "Language / 语言",
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+ "sidebar_filters": "筛选器",
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+ "sidebar_segment": "用户分层（users.user_segment）",
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+ "sidebar_school": "学校（org_name）",
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+ "sidebar_exclude_test": "排除 users.is_test_user = 1",
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+ "sidebar_target_date": "目标日期",
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+ "sidebar_view_members": "查看共创社区成员",
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+ "community_dialog_title": "共创社区成员",
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+ "community_subheader": "共创社区成员",
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+ "community_rule": "规则：未退出社区，且邮箱来自 users.email 或手机号注册后在 early_community 留存邮箱。",
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+ "community_count": "参与成员数",
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+ "community_empty": "当前没有符合条件的共创社区成员。",
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+ "dau_trend": "DAU 趋势",
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+ "curr_trend": "CURR 趋势",
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+ "axis_date": "日期",
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+ "axis_dau": "DAU",
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+ "axis_curr": "CURR（%）",
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+ "tooltip_curr": "CURR（%）",
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+ "tooltip_prev_day_active": "昨日活跃",
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+ "tooltip_retained_today": "今日留存",
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+ "tooltip_dau_today": "今日 DAU",
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+ "trend3_caption_1": "30 天走势：左轴=每日用户对话总时长（秒），右轴=页面浏览量（次）。",
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+ "trend3_caption_2": "图例说明：蓝线=对话时长（秒）；橙线=Lumi 商店 PV；绿线=Lumi 装扮 PV。",
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+ "line_duration": "对话时长（秒）",
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+ "line_shop_pv": "Lumi 商店 PV",
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+ "line_outfits_pv": "Lumi 装扮 PV",
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+ "legend_lines": "曲线",
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+ "axis_duration": "对话时长（秒）",
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+ "axis_pv_count": "页面浏览量（次）",
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+ "tooltip_pv_type": "PV 类型",
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+ "tooltip_pv": "PV",
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+ "segments_on": "分群（日期：{date}）",
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+ "segment_new": "新用户",
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+ "segment_current": "持续活跃",
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+ "segment_reactivated": "重新活跃",
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+ "segment_at_risk_7d": "风险流失（7 天）",
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+ "segment_at_risk_30d": "风险流失（30 天）",
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+ "segment_dormant_30d": "沉睡（>=30 天）",
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+ "active_today_composition": "今日活跃构成",
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+ "not_active_today": "今日未活跃",
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+ "metric_inactive_total": "未活跃 / 总用户",
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+ "caption_active_comp": "今日 DAU 的构成。",
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+ "caption_inactive_comp": "当前筛选人群中，今日未活跃用户的分布。",
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+ "hint_share_dau": "占 DAU 的比例。",
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+ "hint_share_inactive": "占今日未活跃用户的比例。",
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+ "caption_of": "占 {denom} 的 {pct}。{hint}",
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+ "drilldown_title": "明细下钻（前 50 位用户）",
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+ "drilldown_caption": "邮箱、手机号为 `users` 表字段；未录入则为空。",
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+ "tab_active_today": "今日活跃",
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+ "tab_at_risk": "风险流失",
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+ "tab_dormant": "沉睡",
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+ },
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+ "en": {
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+ "dashboard_title": "Lyrria Growth Dashboard",
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+ "sidebar_lang": "Language / 语言",
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+ "sidebar_filters": "Filters",
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+ "sidebar_segment": "users.user_segment",
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+ "sidebar_school": "School (org_name)",
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+ "sidebar_exclude_test": "Exclude users.is_test_user = 1",
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+ "sidebar_target_date": "Target date",
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+ "sidebar_view_members": "View Community Members",
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+ "community_dialog_title": "Community Members",
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+ "community_subheader": "Community Members",
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+ "community_rule": "Rule: not opted out, and email comes from users.email or from early_community after phone sign-up.",
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+ "community_count": "Members Count",
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+ "community_empty": "No community members match the current rule.",
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+ "dau_trend": "DAU trend",
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+ "curr_trend": "CURR trend",
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+ "axis_date": "Date",
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+ "axis_dau": "DAU",
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+ "axis_curr": "CURR (%)",
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+ "tooltip_curr": "CURR (%)",
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+ "tooltip_prev_day_active": "Prev-day active",
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+ "tooltip_retained_today": "Retained today",
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+ "tooltip_dau_today": "DAU today",
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+ "trend3_caption_1": "30-day trend: left axis = total daily conversation duration (s), right axis = page views.",
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+ "trend3_caption_2": "Legend: blue = Conversation duration (s); orange = Lumi shop PV; green = Lumi outfits PV.",
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+ "line_duration": "Conversation duration (s)",
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+ "line_shop_pv": "Lumi shop PV",
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+ "line_outfits_pv": "Lumi outfits PV",
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+ "legend_lines": "Lines",
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+ "axis_duration": "Conversation duration (s)",
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+ "axis_pv_count": "Page views (count)",
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+ "tooltip_pv_type": "PV type",
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+ "tooltip_pv": "PV",
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+ "segments_on": "Segments on {date}",
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+ "segment_new": "New",
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+ "segment_current": "Current",
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+ "segment_reactivated": "Reactivated",
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+ "segment_at_risk_7d": "At-risk (7d)",
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+ "segment_at_risk_30d": "At-risk (30d)",
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+ "segment_dormant_30d": "Dormant (>=30d)",
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+ "active_today_composition": "Active today composition",
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+ "not_active_today": "Not active today",
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+ "metric_inactive_total": "Inactive / Total",
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+ "caption_active_comp": "How today's DAU is composed.",
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+ "caption_inactive_comp": "Breakdown of users who are not active today (within the current filtered cohort).",
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+ "hint_share_dau": "Share of DAU.",
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+ "hint_share_inactive": "Share of users not active today.",
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+ "caption_of": "{pct} of {denom}. {hint}",
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+ "drilldown_title": "Drill-down (first 50 users)",
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+ "drilldown_caption": "Email and phone come from the `users` table; blank means missing.",
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+ "tab_active_today": "Active today",
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+ "tab_at_risk": "At-risk",
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+ "tab_dormant": "Dormant",
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+ },
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+}
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+
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+
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+def get_lang() -> str:
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+ selected = st.sidebar.selectbox(I18N["en"]["sidebar_lang"], options=["中文", "English"], index=1)
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+ return "zh" if selected == "中文" else "en"
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+
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+
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+lang = get_lang()
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+
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+
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+def t(key: str, **kwargs) -> str:
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+ text = I18N.get(lang, I18N["en"]).get(key, key)
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+ return text.format(**kwargs) if kwargs else text
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+
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# ---- MySQL config from setting.conf ----
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SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
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DEFAULT_CONF = os.path.join(SCRIPT_DIR, "setting.conf")
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@@ -137,10 +262,10 @@ def read_community_members_df() -> pd.DataFrame:
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def _render_community_members_content():
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members_df = read_community_members_df()
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- st.caption("规则：未退出社区，且邮箱来自 users.email 或手机号注册后在 early_community 留存邮箱。")
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- st.metric("参与成员数", f"{len(members_df):,}")
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+ st.caption(t("community_rule"))
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+ st.metric(t("community_count"), f"{len(members_df):,}")
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if members_df.empty:
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- st.info("当前没有符合条件的共创社区成员。")
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+ st.info(t("community_empty"))
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return
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st.dataframe(
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members_df,
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@@ -164,28 +289,53 @@ def _apply_dialog_extra_wide_style():
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if hasattr(st, "dialog"):
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- @st.dialog("共创社区成员", width="large")
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+ @st.dialog(t("community_dialog_title"), width="large")
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def show_community_members_dialog():
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_apply_dialog_extra_wide_style()
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_render_community_members_content()
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else:
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def show_community_members_dialog():
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- st.subheader("共创社区成员")
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+ st.subheader(t("community_subheader"))
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_render_community_members_content()
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-st.title("Lyrria Growth Dashboard")
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+st.title(t("dashboard_title"))
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# ---- Sidebar ----
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-st.sidebar.header("Filters")
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+st.sidebar.header(t("sidebar_filters"))
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segments = read_df("SELECT DISTINCT user_segment AS seg FROM users WHERE user_segment IS NOT NULL ORDER BY seg")["seg"].dropna().tolist()
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-orgs = read_df("SELECT DISTINCT org_id_snapshot AS org FROM user_daily_activity WHERE org_id_snapshot IS NOT NULL ORDER BY org")["org"].tolist()
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+org_df = read_df(
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+ """
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+ SELECT DISTINCT uda.org_id_snapshot AS org_id, o.org_name
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+ FROM user_daily_activity uda
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+ LEFT JOIN organizations o
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+ ON o.org_id COLLATE utf8mb4_unicode_ci = uda.org_id_snapshot COLLATE utf8mb4_unicode_ci
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+ WHERE uda.org_id_snapshot IS NOT NULL
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+ ORDER BY
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+ COALESCE(
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+ o.org_name COLLATE utf8mb4_unicode_ci,
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+ uda.org_id_snapshot COLLATE utf8mb4_unicode_ci
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+ ),
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+ uda.org_id_snapshot COLLATE utf8mb4_unicode_ci
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+ """
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+)
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+org_df["org_id"] = org_df["org_id"].astype(str)
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+org_map = {
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+ row["org_id"]: (str(row["org_name"]).strip() if pd.notna(row["org_name"]) and str(row["org_name"]).strip() else row["org_id"])
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+ for _, row in org_df.iterrows()
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+}
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+orgs = org_df["org_id"].tolist()
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segment_default = [s for s in segments if s != "internal"] if segments else []
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-segment_sel = st.sidebar.multiselect("users.user_segment", options=segments, default=segment_default)
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-org_sel = st.sidebar.multiselect("org_id_snapshot (school)", options=orgs, default=[])
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+segment_sel = st.sidebar.multiselect(t("sidebar_segment"), options=segments, default=segment_default)
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+org_sel = st.sidebar.multiselect(
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+ t("sidebar_school"),
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+ options=orgs,
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+ default=[],
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+ format_func=lambda org_id: org_map.get(org_id, org_id),
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+)
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-exclude_test = st.sidebar.checkbox("Exclude users.is_test_user = 1", value=True)
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+exclude_test = st.sidebar.checkbox(t("sidebar_exclude_test"), value=True)
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# Date bounds
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max_day = pd.to_datetime(read_df("SELECT MAX(activity_date) AS d FROM user_daily_activity")["d"].iloc[0]).date()
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@@ -194,14 +344,14 @@ today = date.today()
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# UX: 默认选择今天，允许选择今天之前所有日期（若库里最小日期晚于今天，则回退为该最小日期）
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target_day = st.sidebar.date_input(
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- "Target date",
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+ t("sidebar_target_date"),
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value=today if today >= min_day else min_day,
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min_value=min_day,
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max_value=today if today >= min_day else min_day,
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)
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st.sidebar.markdown("---")
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-if st.sidebar.button("查看共创社区成员", use_container_width=True):
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+if st.sidebar.button(t("sidebar_view_members"), use_container_width=True):
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show_community_members_dialog()
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# ---- Load users (for universe + test filter) ----
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@@ -260,7 +410,7 @@ else:
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cohort_universe = universe_users
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# ---- Trend (DAU, by day) ----
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-st.subheader("DAU trend")
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+st.subheader(t("dau_trend"))
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# 最近 30 天（含 target_day）；若早于库内最小日期则截断
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trend_start = max(min_day, target_day - timedelta(days=29))
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dau_raw = (
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@@ -285,15 +435,15 @@ chart = (
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alt.Chart(trend)
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.mark_line(point=True)
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.encode(
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- x=alt.X("day:N", axis=alt.Axis(title="Date", labelAngle=0)),
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- y=alt.Y("dau:Q", axis=alt.Axis(title="DAU")),
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+ x=alt.X("day:N", axis=alt.Axis(title=t("axis_date"), labelAngle=0)),
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+ y=alt.Y("dau:Q", axis=alt.Axis(title=t("axis_dau"))),
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tooltip=["day", "dau"],
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)
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)
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st.altair_chart(chart, use_container_width=True)
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# ---- Trend (CURR, by day from curr_daily) ----
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-st.subheader("CURR trend")
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+st.subheader(t("curr_trend"))
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curr_start = max(min_day, target_day - timedelta(days=29))
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curr_df = read_df(
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"""
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@@ -321,14 +471,14 @@ curr_chart = (
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alt.Chart(curr_plot)
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.mark_line(point=True, color="#f59e0b")
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.encode(
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- x=alt.X("day:N", axis=alt.Axis(title="Date", labelAngle=0)),
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- y=alt.Y("curr_rate_pct:Q", axis=alt.Axis(title="CURR (%)", format=".2f")),
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+ x=alt.X("day:N", axis=alt.Axis(title=t("axis_date"), labelAngle=0)),
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+ y=alt.Y("curr_rate_pct:Q", axis=alt.Axis(title=t("axis_curr"), format=".2f")),
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tooltip=[
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"day",
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- alt.Tooltip("curr_rate_pct:Q", title="CURR (%)", format=".2f"),
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- alt.Tooltip("prev_day_active_count:Q", title="Prev-day active"),
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- alt.Tooltip("retained_count:Q", title="Retained today"),
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- alt.Tooltip("total_active_today:Q", title="DAU today"),
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+ alt.Tooltip("curr_rate_pct:Q", title=t("tooltip_curr"), format=".2f"),
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+ alt.Tooltip("prev_day_active_count:Q", title=t("tooltip_prev_day_active")),
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+ alt.Tooltip("retained_count:Q", title=t("tooltip_retained_today")),
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+ alt.Tooltip("total_active_today:Q", title=t("tooltip_dau_today")),
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],
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)
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)
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@@ -380,23 +530,37 @@ for col in ["lumi_shop_pv", "lumi_outfits_pv", "total_conversation_duration_seco
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trend3_plot[col] = trend3_plot[col].fillna(0)
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trend3_plot["day"] = trend3_plot["activity_date"].astype(str)
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-st.caption("30d 走势：左轴=每日用户对话总时长(秒)，右轴=页面浏览量(次)。三条线：lumi-shop、lumi-outfits、对话时长。")
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+st.caption(t("trend3_caption_1"))
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+st.caption(t("trend3_caption_2"))
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+
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+duration_label = t("line_duration")
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+shop_label = t("line_shop_pv")
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+outfits_label = t("line_outfits_pv")
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duration_line = (
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alt.Chart(trend3_plot)
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+ .transform_calculate(line_type=f"'{duration_label}'")
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.mark_line(point=True, color="#3b82f6")
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.encode(
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- x=alt.X("day:N", axis=alt.Axis(title="Date", labelAngle=0)),
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+ x=alt.X("day:N", axis=alt.Axis(title=t("axis_date"), labelAngle=0)),
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y=alt.Y(
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"total_conversation_duration_seconds:Q",
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- axis=alt.Axis(title="Conversation duration (s)"),
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+ axis=alt.Axis(title=t("axis_duration")),
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scale=alt.Scale(domainMin=0),
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),
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+ color=alt.Color(
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+ "line_type:N",
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+ scale=alt.Scale(
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+ domain=[duration_label, shop_label, outfits_label],
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+ range=["#3b82f6", "#f59e0b", "#10b981"],
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+ ),
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+ legend=alt.Legend(title=t("legend_lines")),
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+ ),
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tooltip=[
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"day",
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- alt.Tooltip("total_conversation_duration_seconds:Q", title="Conversation duration (s)", format=",.0f"),
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- alt.Tooltip("lumi_shop_pv:Q", title="Lumi shop PV", format=",d"),
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- alt.Tooltip("lumi_outfits_pv:Q", title="Lumi outfits PV", format=",d"),
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+ alt.Tooltip("total_conversation_duration_seconds:Q", title=duration_label, format=",.0f"),
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+ alt.Tooltip("lumi_shop_pv:Q", title=shop_label, format=",d"),
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+ alt.Tooltip("lumi_outfits_pv:Q", title=outfits_label, format=",d"),
|
|
|
],
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|
|
)
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|
|
)
|
|
|
@@ -407,30 +571,32 @@ pv_lines = (
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|
|
["lumi_shop_pv", "lumi_outfits_pv"],
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|
as_=["pv_type", "pv_count"],
|
|
|
)
|
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|
+ .transform_calculate(
|
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|
+ line_type=f"""
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|
+ datum.pv_type === 'lumi_shop_pv' ? '{shop_label}' : '{outfits_label}'
|
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|
+ """
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|
|
+ )
|
|
|
.mark_line(point=True)
|
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|
.encode(
|
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|
x=alt.X("day:N"),
|
|
|
y=alt.Y(
|
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|
"pv_count:Q",
|
|
|
- axis=alt.Axis(title="Page views (count)", orient="right"),
|
|
|
+ axis=alt.Axis(title=t("axis_pv_count"), orient="right"),
|
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|
scale=alt.Scale(domainMin=0),
|
|
|
),
|
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|
color=alt.Color(
|
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|
- "pv_type:N",
|
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|
+ "line_type:N",
|
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|
scale=alt.Scale(
|
|
|
- domain=["lumi_shop_pv", "lumi_outfits_pv"],
|
|
|
- range=["#f59e0b", "#10b981"],
|
|
|
- ),
|
|
|
- legend=alt.Legend(
|
|
|
- title="PV lines",
|
|
|
- labelExpr="datum.value === 'lumi_shop_pv' ? 'Lumi shop PV' : 'Lumi outfits PV'",
|
|
|
+ domain=[duration_label, shop_label, outfits_label],
|
|
|
+ range=["#3b82f6", "#f59e0b", "#10b981"],
|
|
|
),
|
|
|
+ legend=alt.Legend(title=t("legend_lines")),
|
|
|
),
|
|
|
tooltip=[
|
|
|
"day",
|
|
|
- alt.Tooltip("pv_type:N", title="PV type"),
|
|
|
- alt.Tooltip("pv_count:Q", title="PV", format=",d"),
|
|
|
- alt.Tooltip("total_conversation_duration_seconds:Q", title="Conversation duration (s)", format=",.0f"),
|
|
|
+ alt.Tooltip("pv_type:N", title=t("tooltip_pv_type")),
|
|
|
+ alt.Tooltip("pv_count:Q", title=t("tooltip_pv"), format=",d"),
|
|
|
+ alt.Tooltip("total_conversation_duration_seconds:Q", title=duration_label, format=",.0f"),
|
|
|
],
|
|
|
)
|
|
|
)
|
|
|
@@ -501,19 +667,19 @@ dormant_users = {
|
|
|
}
|
|
|
|
|
|
# ---- Segments visualization (Duolingo-like, no tables) ----
|
|
|
-st.subheader(f"Segments on {d0.isoformat()}")
|
|
|
+st.subheader(t("segments_on", date=d0.isoformat()))
|
|
|
|
|
|
active_buckets = [
|
|
|
- ("New", len(new_users)),
|
|
|
- ("Current", len(current_users)),
|
|
|
- ("Reactivated", len(reactivated_users)),
|
|
|
+ ("segment_new", len(new_users)),
|
|
|
+ ("segment_current", len(current_users)),
|
|
|
+ ("segment_reactivated", len(reactivated_users)),
|
|
|
]
|
|
|
active_total = len(active_today)
|
|
|
inactive_total = max(0, len(cohort_universe) - len(active_today))
|
|
|
inactive_buckets = [
|
|
|
- ("At-risk (7d)", len(at_risk_wau)),
|
|
|
- ("At-risk (30d)", len(at_risk_mau)),
|
|
|
- ("Dormant (≥30d)", len(dormant_users)),
|
|
|
+ ("segment_at_risk_7d", len(at_risk_wau)),
|
|
|
+ ("segment_at_risk_30d", len(at_risk_mau)),
|
|
|
+ ("segment_dormant_30d", len(dormant_users)),
|
|
|
]
|
|
|
|
|
|
def segment_card(label: str, value: int, denom: int, hint: str):
|
|
|
@@ -528,7 +694,7 @@ def segment_card(label: str, value: int, denom: int, hint: str):
|
|
|
unsafe_allow_html=True,
|
|
|
)
|
|
|
st.progress(min(max(pct, 0.0), 1.0))
|
|
|
- st.caption(f"{pct:.1%} of {denom:,}. {hint}")
|
|
|
+ st.caption(t("caption_of", pct=f"{pct:.1%}", denom=f"{denom:,}", hint=hint))
|
|
|
|
|
|
|
|
|
def drilldown_table(user_ids: set, users_df: pd.DataFrame, limit: int = 50) -> pd.DataFrame:
|
|
|
@@ -562,31 +728,31 @@ left, right = st.columns(2, gap="large")
|
|
|
with left:
|
|
|
t1, t2 = st.columns([3, 1], vertical_alignment="center")
|
|
|
with t1:
|
|
|
- st.markdown("### Active today composition")
|
|
|
+ st.markdown(f"### {t('active_today_composition')}")
|
|
|
with t2:
|
|
|
st.metric("DAU", len(active_today))
|
|
|
|
|
|
- st.caption("How today's DAU is composed.")
|
|
|
- for label, val in active_buckets:
|
|
|
- segment_card(label, val, active_total, "Share of DAU.")
|
|
|
+ st.caption(t("caption_active_comp"))
|
|
|
+ for label_key, val in active_buckets:
|
|
|
+ segment_card(t(label_key), val, active_total, t("hint_share_dau"))
|
|
|
|
|
|
with right:
|
|
|
t1, t2 = st.columns([2, 2], vertical_alignment="center")
|
|
|
with t1:
|
|
|
- st.markdown("### Not active today")
|
|
|
+ st.markdown(f"### {t('not_active_today')}")
|
|
|
with t2:
|
|
|
- st.metric("Inactive / Total", f"{inactive_total:,} / {len(cohort_universe):,}")
|
|
|
+ st.metric(t("metric_inactive_total"), f"{inactive_total:,} / {len(cohort_universe):,}")
|
|
|
|
|
|
- st.caption("Breakdown of users who are not active today (within the current filtered cohort).")
|
|
|
- for label, val in inactive_buckets:
|
|
|
- segment_card(label, val, inactive_total, "Share of users not active today.")
|
|
|
+ st.caption(t("caption_inactive_comp"))
|
|
|
+ for label_key, val in inactive_buckets:
|
|
|
+ segment_card(t(label_key), val, inactive_total, t("hint_share_inactive"))
|
|
|
|
|
|
|
|
|
st.markdown("---")
|
|
|
# ---- Drill down ----
|
|
|
-st.subheader("Drill-down (first 50 users)")
|
|
|
-st.caption("邮箱、手机号为 `users` 表字段；未录入则为空。")
|
|
|
-tab1, tab2, tab3 = st.tabs(["Active today", "At-risk", "Dormant"])
|
|
|
+st.subheader(t("drilldown_title"))
|
|
|
+st.caption(t("drilldown_caption"))
|
|
|
+tab1, tab2, tab3 = st.tabs([t("tab_active_today"), t("tab_at_risk"), t("tab_dormant")])
|
|
|
with tab1:
|
|
|
st.dataframe(
|
|
|
drilldown_table(active_today, users),
|
