Initial commit: Shelly Manager with Textual CLI, Streamlit UI, and comprehensive .gitignore

Shelly device management app with mDNS/subnet discovery, inventory, configuration, and mass operations for Gen1/Gen2+ devices. Includes .gitignore excluding runtime data (device DB, user config), AI conversation history, build artifacts, and common Python/OS patterns.
2026-03-23 21:51:59 +01:00
commit 71803418e5
152 changed files with 23405 additions and 0 deletions
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+[project]
+name = "dashboard-compute-snowflake"
+version = "1.0.0"
+description = "Compute dashboard template with Snowflake connection"
+requires-python = ">=3.11"
+dependencies = [
+    "altair>=5.5.0",
+    "pandas>=2.2.3",
+    "snowflake-connector-python>=3.3.0",
+    "streamlit[snowflake]>=1.54.0",
+]
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+definition_version: 2
+entities:
+  DASHBOARD_COMPUTE_SNOWFLAKE:
+    type: streamlit
+    identifier:
+      name: DASHBOARD_COMPUTE_SNOWFLAKE
+      database: <FROM_CONNECTION>   # Use: snow connection list
+      schema: <FROM_CONNECTION>
+    query_warehouse: <FROM_CONNECTION>
+    runtime_name: SYSTEM$ST_CONTAINER_RUNTIME_PY3_11
+    # List available: SHOW EXTERNAL ACCESS INTEGRATIONS;
+    # Common: PYPI_ACCESS_INTEGRATION (verify exists)
+    external_access_integrations:
+      - <YOUR_PYPI_INTEGRATION>
+    main_file: streamlit_app.py
+    artifacts:
+      - streamlit_app.py
+      - pyproject.toml
@@ -0,0 +1,527 @@
+"""
+Compute/Resource Dashboard Template (Snowflake Edition)
+
+A resource consumption dashboard demonstrating:
+- Snowflake connection via st.connection("snowflake")
+- Parameterized queries for safe data loading
+- Multiple metric cards in a grid layout
+- @st.fragment for independent widget updates
+- Popover filters for each metric card
+- Chart/table view toggle
+- Time range filtering (1M, 6M, 1Y, QTD, YTD, All)
+
+This template uses synthetic data generated in Snowflake. Replace the
+synthetic queries with your actual table queries in production.
+"""
+
+from datetime import date, timedelta
+import re
+import pandas as pd
+import streamlit as st
+import altair as alt
+
+st.set_page_config(
+    page_title="Compute Dashboard (Snowflake)",
+    page_icon=":material/bolt:",
+    layout="wide",
+)
+
+
+# =============================================================================
+# Constants
+# =============================================================================
+
+TIME_RANGES = ["1M", "6M", "1Y", "QTD", "YTD", "All"]
+ACCOUNT_TYPES = ["Paying", "Trial", "Internal"]
+INSTANCE_TYPES = ["Standard", "High Memory", "High CPU", "GPU"]
+REGIONS = ["us-west-2", "us-east-1", "eu-west-1", "ap-northeast-1"]
+CHART_HEIGHT = 350
+
+# Base values for synthetic data generation
+BASE_VALUES = {
+    "account_type": {"Paying": 8000, "Trial": 2000, "Internal": 1000},
+    "instance_type": {"Standard": 5000, "High Memory": 3000, "High CPU": 2000, "GPU": 1500},
+    "region": {"us-west-2": 4000, "us-east-1": 3500, "eu-west-1": 2500, "ap-northeast-1": 1500},
+}
+
+
+# =============================================================================
+# Snowflake Connection and Data Loading
+# =============================================================================
+
+
+def get_snowflake_connection():
+    """Get Snowflake connection via st.connection.
+
+    Displays an error and stops the app if the connection fails.
+    """
+    try:
+        return st.connection("snowflake")
+    except Exception as e:
+        st.error(f"Failed to connect to Snowflake: {e}")
+        st.info(
+            "Make sure you have configured your Snowflake connection in "
+            "`.streamlit/secrets.toml` or via environment variables."
+        )
+        st.stop()
+
+
+# =============================================================================
+# IMPORTANT: Use parameterized queries in production
+# =============================================================================
+#
+# This demo uses synthetic data generated via SQL. In production, always use
+# parameterized queries to prevent SQL injection:
+#
+#     # GOOD: Parameterized query (safe)
+#     conn = st.connection("snowflake")
+#     df = conn.query(
+#         "SELECT * FROM metrics WHERE category = :category AND ds >= :start_date",
+#         params={"category": selected_category, "start_date": start_date}
+#     )
+#
+#     # BAD: f-string interpolation (SQL injection risk)
+#     df = conn.query(f"SELECT * FROM metrics WHERE category = '{user_input}'")
+#
+# The synthetic data generation below uses f-strings only because the values
+# are hardcoded constants, not user input. Never use f-strings with user input.
+
+def _validate_sql_identifier(name: str) -> str:
+    """Validate that a string is a safe SQL identifier (letters, digits, underscores).
+
+    Raises ValueError if the name contains unexpected characters. This prevents
+    SQL injection if the function is ever modified to accept dynamic input.
+    """
+    if not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", name):
+        raise ValueError(f"Invalid SQL identifier: {name!r}")
+    return name
+
+
+def build_synthetic_query(category_col: str, categories: list[str], base_values: dict[str, int]) -> str:
+    """Build SQL query for synthetic data.
+
+    WARNING: This function uses f-strings for demo purposes only.
+    The categories are hardcoded constants defined in this file, not user input.
+    In production, always use parameterized queries with conn.query(..., params={}).
+    """
+    # Validate the column name used as a SQL identifier (appears unquoted in SQL)
+    _validate_sql_identifier(category_col)
+
+    # Category values appear as string literals in SQL VALUES clause.
+    # Escape single quotes to prevent SQL injection.
+    safe_categories = [cat.replace("'", "''") for cat in categories]
+
+    # Build VALUES clause for categories with their base values
+    values_rows = ", ".join(
+        f"('{cat}', {base_values.get(orig, 1000)})"
+        for cat, orig in zip(safe_categories, categories)
+    )
+    
+    return f"""
+    WITH categories AS (
+        SELECT column1 AS category, column2 AS base_val 
+        FROM VALUES {values_rows}
+    ),
+    date_series AS (
+        SELECT DATEADD(day, -seq4(), CURRENT_DATE() - 1) AS ds
+        FROM TABLE(GENERATOR(ROWCOUNT => 730))
+    ),
+    base_data AS (
+        SELECT 
+            ds,
+            category,
+            base_val * POWER(1.002, DATEDIFF(day, DATEADD(year, -2, CURRENT_DATE()), ds)) AS base_trend,
+            CASE WHEN DAYOFWEEK(ds) IN (0, 6) THEN 0.4 ELSE 1.0 END AS seasonality,
+            1 + (RANDOM() / 10000000000000000000.0 - 0.5) * 0.4 AS noise
+        FROM date_series
+        CROSS JOIN categories
+        WHERE ds >= DATEADD(year, -2, CURRENT_DATE())
+    )
+    SELECT 
+        ds,
+        category AS {category_col},
+        GREATEST(0, ROUND(base_trend * seasonality * noise, 2)) AS daily_credits,
+        ROUND(AVG(GREATEST(0, base_trend * seasonality * noise)) OVER (
+            PARTITION BY category
+            ORDER BY ds ROWS BETWEEN 6 PRECEDING AND CURRENT ROW
+        ), 2) AS credits_7d_ma
+    FROM base_data
+    ORDER BY ds, {category_col}
+    """
+
+
+@st.cache_data(ttl=3600, show_spinner="Loading account type data...")
+def load_account_type_data() -> pd.DataFrame:
+    """Load credits by account type from Snowflake."""
+    conn = get_snowflake_connection()
+    query = build_synthetic_query("account_type", ACCOUNT_TYPES, BASE_VALUES["account_type"])
+    df = conn.query(query)
+    df.columns = df.columns.str.lower()
+    return df
+
+
+@st.cache_data(ttl=3600, show_spinner="Loading instance type data...")
+def load_instance_type_data() -> pd.DataFrame:
+    """Load credits by instance type from Snowflake."""
+    conn = get_snowflake_connection()
+    query = build_synthetic_query("instance_type", INSTANCE_TYPES, BASE_VALUES["instance_type"])
+    df = conn.query(query)
+    df.columns = df.columns.str.lower()
+    return df
+
+
+@st.cache_data(ttl=3600, show_spinner="Loading region data...")
+def load_region_data() -> pd.DataFrame:
+    """Load credits by region from Snowflake."""
+    conn = get_snowflake_connection()
+    query = build_synthetic_query("region", REGIONS, BASE_VALUES["region"])
+    df = conn.query(query)
+    df.columns = df.columns.str.lower()
+    return df
+
+
+# =============================================================================
+# Chart Utilities
+# =============================================================================
+
+
+def filter_by_time_range(df: pd.DataFrame, x_col: str, time_range: str) -> pd.DataFrame:
+    """Filter dataframe by time range."""
+    if time_range == "All" or df.empty:
+        return df
+
+    df = df.copy()
+    df[x_col] = pd.to_datetime(df[x_col])
+    max_date = df[x_col].max()
+
+    if time_range == "1M":
+        min_date = max_date - timedelta(days=30)
+    elif time_range == "6M":
+        min_date = max_date - timedelta(days=180)
+    elif time_range == "1Y":
+        min_date = max_date - timedelta(days=365)
+    elif time_range == "QTD":
+        quarter_month = ((max_date.month - 1) // 3) * 3 + 1
+        min_date = pd.Timestamp(date(max_date.year, quarter_month, 1))
+    elif time_range == "YTD":
+        min_date = pd.Timestamp(date(max_date.year, 1, 1))
+    else:
+        return df
+
+    return df[df[x_col] >= min_date]
+
+
+def create_line_chart(
+    df: pd.DataFrame,
+    x_col: str,
+    y_col: str,
+    color_col: str,
+    height: int,
+    show_percent: bool = False,
+) -> alt.Chart:
+    """Create a line chart."""
+    y_format = ".1%" if show_percent else ",.0f"
+    
+    return (
+        alt.Chart(df)
+        .mark_line()
+        .encode(
+            x=alt.X(f"{x_col}:T", title=None),
+            y=alt.Y(f"{y_col}:Q", title="Credits", axis=alt.Axis(format=y_format)),
+            color=alt.Color(f"{color_col}:N", legend=alt.Legend(orient="bottom")),
+            tooltip=[
+                alt.Tooltip(f"{x_col}:T", title="Date", format="%Y-%m-%d"),
+                alt.Tooltip(f"{color_col}:N", title=color_col.replace("_", " ").title()),
+                alt.Tooltip(f"{y_col}:Q", title="Credits", format=y_format),
+            ],
+        )
+        .properties(height=height)
+        .interactive()
+    )
+
+
+def create_bar_chart(
+    df: pd.DataFrame,
+    x_col: str,
+    y_col: str,
+    color_col: str,
+    height: int,
+    show_percent: bool = False,
+) -> alt.Chart:
+    """Create a stacked bar chart."""
+    y_format = ".1%" if show_percent else ",.0f"
+    
+    return (
+        alt.Chart(df)
+        .mark_bar()
+        .encode(
+            x=alt.X(f"{x_col}:T", title=None),
+            y=alt.Y(
+                f"{y_col}:Q",
+                title="Credits",
+                stack="normalize" if show_percent else True,
+                axis=alt.Axis(format=y_format),
+            ),
+            color=alt.Color(f"{color_col}:N", legend=alt.Legend(orient="bottom")),
+            tooltip=[
+                alt.Tooltip(f"{x_col}:T", title="Date", format="%Y-%m-%d"),
+                alt.Tooltip(f"{color_col}:N"),
+                alt.Tooltip(f"{y_col}:Q", format=",.0f"),
+            ],
+        )
+        .properties(height=height)
+    )
+
+
+# =============================================================================
+# Page Header Component
+# =============================================================================
+
+
+def render_page_header(title: str):
+    """Render page header with title and reset button."""
+    with st.container(
+        horizontal=True, horizontal_alignment="distribute", vertical_alignment="center"
+    ):
+        st.markdown(title)
+        if st.button(":material/restart_alt: Reset", type="tertiary"):
+            st.session_state.clear()
+            st.rerun()
+
+
+# =============================================================================
+# Metric Card Components (using @st.fragment)
+# =============================================================================
+
+
+@st.fragment
+def account_type_metric():
+    """Account type metric card with independent state."""
+    data = load_account_type_data()
+    
+    with st.container(border=True):
+        with st.container(horizontal=True, horizontal_alignment="distribute", vertical_alignment="center"):
+            st.markdown("**Credits by account type**")
+            
+            view_mode = st.segmented_control(
+                "View",
+                options=[":material/show_chart:", ":material/table:"],
+                default=":material/show_chart:",
+                key="acct_view",
+                label_visibility="collapsed",
+            )
+            
+            with st.popover("Filters", type="tertiary"):
+                selected_types = st.pills(
+                    "Account types",
+                    options=ACCOUNT_TYPES,
+                    default=["Paying"],
+                    selection_mode="multi",
+                    key="acct_types",
+                )
+                line_options = st.pills(
+                    "Lines",
+                    options=["Daily", "7-day MA"],
+                    default=["7-day MA"],
+                    selection_mode="multi",
+                    key="acct_lines",
+                )
+                chart_type = st.segmented_control(
+                    "Chart type",
+                    options=[":material/show_chart: Line", ":material/bar_chart: Bar"],
+                    default=":material/show_chart: Line",
+                    key="acct_chart",
+                )
+                show_percent = st.toggle(
+                    "Show %", value=False, key="acct_pct",
+                    disabled="Line" in (chart_type or ""),
+                )
+                time_range = st.segmented_control(
+                    "Time range",
+                    options=TIME_RANGES,
+                    default="All",
+                    key="acct_time",
+                )
+        
+        # Filter data
+        selected_types = selected_types or ["Paying"]
+        line_options = line_options or ["7-day MA"]
+        filtered = data[data["account_type"].isin(selected_types)]
+        filtered = filter_by_time_range(filtered, "ds", time_range)
+        
+        y_col = "credits_7d_ma" if "7-day MA" in line_options else "daily_credits"
+        
+        if "table" in (view_mode or ""):
+            st.dataframe(filtered, height=CHART_HEIGHT, hide_index=True)
+        else:
+            if "Bar" in (chart_type or ""):
+                st.altair_chart(
+                    create_bar_chart(filtered, "ds", y_col, "account_type", CHART_HEIGHT, show_percent),
+                )
+            else:
+                st.altair_chart(
+                    create_line_chart(filtered, "ds", y_col, "account_type", CHART_HEIGHT),
+                )
+
+
+@st.fragment
+def instance_type_metric():
+    """Instance type metric card with independent state."""
+    data = load_instance_type_data()
+    
+    with st.container(border=True):
+        with st.container(horizontal=True, horizontal_alignment="distribute", vertical_alignment="center"):
+            st.markdown("**Credits by instance type**")
+            
+            view_mode = st.segmented_control(
+                "View",
+                options=[":material/show_chart:", ":material/table:"],
+                default=":material/show_chart:",
+                key="inst_view",
+                label_visibility="collapsed",
+            )
+            
+            with st.popover("Filters", type="tertiary"):
+                selected_types = st.pills(
+                    "Instance types",
+                    options=INSTANCE_TYPES,
+                    default=INSTANCE_TYPES,
+                    selection_mode="multi",
+                    key="inst_types",
+                )
+                line_options = st.pills(
+                    "Lines",
+                    options=["Daily", "7-day MA"],
+                    default=["7-day MA"],
+                    selection_mode="multi",
+                    key="inst_lines",
+                )
+                chart_type = st.segmented_control(
+                    "Chart type",
+                    options=[":material/show_chart: Line", ":material/bar_chart: Bar"],
+                    default=":material/show_chart: Line",
+                    key="inst_chart",
+                )
+                show_percent = st.toggle(
+                    "Show %", value=False, key="inst_pct",
+                    disabled="Line" in (chart_type or ""),
+                )
+                time_range = st.segmented_control(
+                    "Time range",
+                    options=TIME_RANGES,
+                    default="All",
+                    key="inst_time",
+                )
+        
+        # Filter data
+        selected_types = selected_types or INSTANCE_TYPES
+        line_options = line_options or ["7-day MA"]
+        filtered = data[data["instance_type"].isin(selected_types)]
+        filtered = filter_by_time_range(filtered, "ds", time_range)
+        
+        y_col = "credits_7d_ma" if "7-day MA" in line_options else "daily_credits"
+        
+        if "table" in (view_mode or ""):
+            st.dataframe(filtered, height=CHART_HEIGHT, hide_index=True)
+        else:
+            if "Bar" in (chart_type or ""):
+                st.altair_chart(
+                    create_bar_chart(filtered, "ds", y_col, "instance_type", CHART_HEIGHT, show_percent),
+                )
+            else:
+                st.altair_chart(
+                    create_line_chart(filtered, "ds", y_col, "instance_type", CHART_HEIGHT),
+                )
+
+
+@st.fragment
+def region_metric():
+    """Region metric card with independent state."""
+    data = load_region_data()
+    
+    with st.container(border=True):
+        with st.container(horizontal=True, horizontal_alignment="distribute", vertical_alignment="center"):
+            st.markdown("**Credits by region**")
+            
+            view_mode = st.segmented_control(
+                "View",
+                options=[":material/show_chart:", ":material/table:"],
+                default=":material/show_chart:",
+                key="region_view",
+                label_visibility="collapsed",
+            )
+            
+            with st.popover("Filters", type="tertiary"):
+                selected_regions = st.pills(
+                    "Regions",
+                    options=REGIONS,
+                    default=REGIONS,
+                    selection_mode="multi",
+                    key="region_select",
+                )
+                line_options = st.pills(
+                    "Lines",
+                    options=["Daily", "7-day MA"],
+                    default=["7-day MA"],
+                    selection_mode="multi",
+                    key="region_lines",
+                )
+                chart_type = st.segmented_control(
+                    "Chart type",
+                    options=[":material/show_chart: Line", ":material/bar_chart: Bar"],
+                    default=":material/bar_chart: Bar",
+                    key="region_chart",
+                )
+                show_percent = st.toggle(
+                    "Show %", value=False, key="region_pct",
+                    disabled="Line" in (chart_type or ""),
+                )
+                time_range = st.segmented_control(
+                    "Time range",
+                    options=TIME_RANGES,
+                    default="All",
+                    key="region_time",
+                )
+        
+        # Filter data
+        selected_regions = selected_regions or REGIONS
+        line_options = line_options or ["7-day MA"]
+        filtered = data[data["region"].isin(selected_regions)]
+        filtered = filter_by_time_range(filtered, "ds", time_range)
+        
+        y_col = "credits_7d_ma" if "7-day MA" in line_options else "daily_credits"
+        
+        if "table" in (view_mode or ""):
+            st.dataframe(filtered, height=CHART_HEIGHT, hide_index=True)
+        else:
+            if "Bar" in (chart_type or ""):
+                st.altair_chart(
+                    create_bar_chart(filtered, "ds", y_col, "region", CHART_HEIGHT, show_percent),
+                )
+            else:
+                st.altair_chart(
+                    create_line_chart(filtered, "ds", y_col, "region", CHART_HEIGHT),
+                )
+
+
+# =============================================================================
+# Page Layout
+# =============================================================================
+
+# Check Snowflake connection
+get_snowflake_connection()
+
+render_page_header("# :material/bolt: Compute Dashboard")
+st.caption(":material/cloud: Powered by Snowflake")
+
+# Row 1: Two metrics
+col1, col2 = st.columns(2)
+
+with col1:
+    account_type_metric()
+
+with col2:
+    instance_type_metric()
+
+# Row 2: One metric (full width for region breakdown)
+region_metric()