start

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.10-slim
+FROM python:3.11-slim
 WORKDIR /app
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt

app.py

@@ -8,171 +8,66 @@ import json
 import os
 
 st.set_page_config(page_title="Crypto Dash", layout="wide")
-IS_HF_SPACE = bool(os.getenv("SPACE_ID") or os.getenv("SPACE_REPO_NAME"))
 
 
-def normalize_cohorts(raw_cohorts) -> pd.DataFrame:
-    """Return a normalized DataFrame with columns: cohort_day, user_count."""
-    if raw_cohorts is None:
-        return pd.DataFrame(columns=["cohort_day", "user_count"])
-
-    if isinstance(raw_cohorts, dict):
-        rows = []
-        for day, count in raw_cohorts.items():
-            rows.append({"cohort_day": day, "user_count": count})
-        df = pd.DataFrame(rows)
-    else:
-        df = pd.DataFrame(raw_cohorts)
-
-    if df.empty:
-        return pd.DataFrame(columns=["cohort_day", "user_count"])
+def load_data() -> dict:
+    app_dir = os.path.dirname(os.path.abspath(__file__))
+    data_path = os.path.join(app_dir, "data.json")
+    with open(data_path, "r", encoding="utf-8") as f:
+        payload = json.load(f)
+    return payload[0] if isinstance(payload, list) else payload
 
-    # Some payloads can use alternative field names.
-    rename_map = {
-        "day": "cohort_day",
-        "cohort": "cohort_day",
-        "count": "user_count",
-        "users": "user_count",
-        "tx_count": "user_count",
-    }
-    df = df.rename(columns=rename_map)
 
-    required_cols = {"cohort_day", "user_count"}
-    if not required_cols.issubset(df.columns):
+def build_cohorts_df(data: dict) -> pd.DataFrame:
+    raw = data.get("users_by_cohorts", [])
+    if not raw:
         return pd.DataFrame(columns=["cohort_day", "user_count"])
-
+    df = pd.DataFrame(raw)
     df["cohort_day"] = pd.to_numeric(df["cohort_day"], errors="coerce")
     df["user_count"] = pd.to_numeric(df["user_count"], errors="coerce")
-    df = df.dropna(subset=["cohort_day", "user_count"]).sort_values("cohort_day")
-
-    if df.empty:
-        return pd.DataFrame(columns=["cohort_day", "user_count"])
-
-    return df[["cohort_day", "user_count"]]
-
-
-def cohorts_from_daily_map(raw_daily_map) -> pd.DataFrame:
-    """Build cohorts from txs_per_day_by_cohorts format.
-
-    Expected shape:
-    {
-      "2025-07-27": {"2": 1, "3": 2, ...},
-      "2025-07-28": {"2": 3, ...}
-    }
-    """
-    if not isinstance(raw_daily_map, dict) or not raw_daily_map:
-        return pd.DataFrame(columns=["cohort_day", "user_count"])
-
-    totals = {}
-    for _, cohorts in raw_daily_map.items():
-        if not isinstance(cohorts, dict):
-            continue
-        for day, count in cohorts.items():
-            try:
-                d = float(day)
-                c = float(count)
-            except (TypeError, ValueError):
-                continue
-            totals[d] = totals.get(d, 0.0) + c
-
-    if not totals:
-        return pd.DataFrame(columns=["cohort_day", "user_count"])
+    return df.dropna().sort_values("cohort_day").reset_index(drop=True)
 
-    df = pd.DataFrame(
-        [{"cohort_day": day, "user_count": count} for day, count in totals.items()]
-    ).sort_values("cohort_day")
-    return df
 
-def load_report_data() -> dict:
-    """Load report data from data.json next to app.py.
-
-    Handles both formats: a list with one report or a single report object.
-    """
-    app_dir = os.path.dirname(os.path.abspath(__file__))
-    data_path = os.path.join(app_dir, "data.json")
-
-    if not os.path.exists(data_path):
-        st.error(f"Файл data.json не найден: {data_path}")
-        st.stop()
-
-    try:
-        with open(data_path, "r", encoding="utf-8") as f:
-            payload = json.load(f)
-    except json.JSONDecodeError as exc:
-        st.error(f"Ошибка формата JSON в data.json: {exc}")
-        st.stop()
-
-    if isinstance(payload, list):
-        if not payload:
-            st.error("data.json содержит пустой список.")
-            st.stop()
-        return payload[0]
-
-    if isinstance(payload, dict):
-        return payload
-
-    st.error("Неподдерживаемый формат data.json. Ожидался объект или список объектов.")
+try:
+    data = load_data()
+except Exception as e:
+    st.error(f"Ошибка загрузки data.json: {e}")
     st.stop()
 
-
-data = load_report_data()
-
 st.title("📊 Blockchain Dashboard")
 
-# KPI блоки
+# KPI
 c1, c2, c3 = st.columns(3)
 c1.metric("Total TX", f"{data['total_tx_amount']:,}")
 c2.metric("DAU", f"{data['dau']:,}")
 c3.metric("New Wallets", f"{data['new_wallets_amount']:,}")
 
-# График когорт
+# Chart
 st.subheader("User Activity by Cohort Day")
-cohorts_raw = data.get("users_by_cohorts", [])
-df_cohorts = normalize_cohorts(cohorts_raw)
 
-if df_cohorts.empty:
-    # Fallback source when users_by_cohorts is missing/invalid in some reports.
-    daily_map_raw = data.get("txs_per_day_by_cohorts", {})
-    df_cohorts = cohorts_from_daily_map(daily_map_raw)
+df = build_cohorts_df(data)
 
-st.info(f"🔍 Debug Info: DataFrame is empty? {df_cohorts.empty} | Shape: {df_cohorts.shape}")
-
-if df_cohorts.empty:
-    st.warning("Нет данных для графика: users_by_cohorts и txs_per_day_by_cohorts пустые или невалидные.")
+if df.empty:
+    st.warning("Нет данных для графика.")
 else:
-    st.caption("1. Table Data (Guaranteed Fallback)")
-    st.table(df_cohorts.head(10))
-
-    st.caption("2. Server-rendered fallback (matplotlib - No JS required)")
-    mpl_fig, mpl_ax = plt.subplots(figsize=(9, 4))
-    mpl_ax.plot(df_cohorts["cohort_day"], df_cohorts["user_count"], linewidth=2)
-    mpl_ax.fill_between(df_cohorts["cohort_day"], df_cohorts["user_count"], alpha=0.25)
-    mpl_ax.set_xlabel("cohort_day")
-    mpl_ax.set_ylabel("user_count")
-    mpl_ax.grid(alpha=0.2)
+    # 1. Plotly (primary)
+    fig = px.area(df, x="cohort_day", y="user_count",
+                  title="Cohort Activity",
+                  template="plotly_white")
+    fig.update_layout(height=400, margin=dict(l=20, r=20, t=40, b=20))
+    st.plotly_chart(fig, use_container_width=True)
+
+    # 2. Matplotlib PNG (server-side, always visible)
+    mpl_fig, ax = plt.subplots(figsize=(10, 3))
+    ax.fill_between(df["cohort_day"], df["user_count"], alpha=0.4)
+    ax.plot(df["cohort_day"], df["user_count"], linewidth=2)
+    ax.set_xlabel("Cohort Day")
+    ax.set_ylabel("Users")
+    ax.set_title("Cohort Activity (server-rendered)")
+    ax.grid(alpha=0.3)
     st.pyplot(mpl_fig)
     plt.close(mpl_fig)
 
-    st.caption("3. Native chart (Altair)")
-    st.area_chart(df_cohorts.set_index("cohort_day")["user_count"])
-
-    try:
-        st.caption("4. Plotly chart")
-        fig = px.area(df_cohorts, x="cohort_day", y="user_count", template="plotly")
-        fig.update_layout(height=400, margin=dict(l=20, r=20, t=20, b=20))
-        st.plotly_chart(fig)
-    except Exception as exc:
-        st.warning(f"Plotly не отрисован: {exc}")
-
-    st.caption("Chart debug")
-    st.metric("Rows", len(df_cohorts))
-    st.metric("Min day", int(df_cohorts["cohort_day"].min()))
-    st.metric("Max day", int(df_cohorts["cohort_day"].max()))
-
-    # Guaranteed non-visual fallback for environments where JS charts are blocked.
-    with st.expander("Chart data preview"):
-        st.dataframe(df_cohorts)
-
-# Проверка данных внизу
+# Raw data
 with st.expander("Raw Data"):
-    st.write(data)
+    st.write(data)

requirements.txt

@@ -1,5 +1,4 @@
-streamlit==1.55.0
+streamlit
 pandas
-plotly==6.6.0
-matplotlib
-websockets
+plotly
+matplotlib