HEA-592 Inital setup;app may fail

apps/viz/apps.py

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+# viz/apps.py
+from django.apps import AppConfig
+from django.utils.translation import gettext_lazy as _
+
+
+class VizConfig(AppConfig):
+    default_auto_field = "django.db.models.BigAutoField"
+    name = "viz"
+    verbose_name = _("viz")

apps/viz/dash/inventory_dashboard/app.py

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+import plotly.express as px
+from dash import dash_table, dcc, html
+from dash.dependencies import Input, Output
+from django_plotly_dash import DjangoDash
+
+from .functions import fetch_data, prepare_livelihood_data, prepare_wealth_group_data
+
+# API Endpoints
+LIVELIHOOD_STRATEGY_URL = "https://headev.fews.net/api/livelihoodstrategy/"
+WEALTH_GROUP_URL = "https://headev.fews.net/api/wealthgroupcharacteristicvalue/"
+
+# Fetch and prepare data
+livelihood_data = fetch_data(LIVELIHOOD_STRATEGY_URL)
+wealth_group_data = fetch_data(WEALTH_GROUP_URL)
+
+livelihood_data = prepare_livelihood_data(livelihood_data)
+wealth_group_data = prepare_wealth_group_data(wealth_group_data)
+
+# Unique countries and livelihood zones for dropdowns
+unique_countries = sorted(livelihood_data["country_code"].unique())
+unique_zones = sorted(livelihood_data["livelihood_zone"].unique())
+
+# Dash app
+app = DjangoDash("Inventory_dashboard")
+app.title = "HEA Dashboard"
+
+# Layout
+app.layout = html.Div(
+    [
+        html.H1("HEA Data Inventory Dashboard", style={"textAlign": "center"}),
+        dcc.Dropdown(
+            id="country-dropdown",
+            options=[{"label": country, "value": country} for country in unique_countries],
+            placeholder="Select Country",
+            multi=False,
+        ),
+        dcc.Dropdown(
+            id="livelihood-zone-dropdown",
+            options=[{"label": zone, "value": zone} for zone in unique_zones],
+            placeholder="Select Livelihood Zone(s)",
+            multi=True,
+        ),
+        html.Div(
+            [
+                html.Div(dcc.Graph(id="wealth-chart"), style={"width": "48%", "display": "inline-block"}),
+                html.Div(dcc.Graph(id="livelihood-chart"), style={"width": "48%", "display": "inline-block"}),
+            ]
+        ),
+        html.Div(
+            [
+                html.H3("Data Table", style={"textAlign": "center"}),
+                dash_table.DataTable(
+                    id="data-table",
+                    columns=[
+                        {"name": "Livelihood Zone", "id": "livelihood_zone"},
+                        {"name": "Strategy Type Count", "id": "Count"},
+                        {"name": "Wealth Characteristics Count", "id": "Wealth Characteristics Count"},
+                    ],
+                    style_table={"overflowX": "auto"},
+                    style_cell={"textAlign": "left"},
+                    page_size=10,
+                ),
+            ]
+        ),
+    ]
+)
+
+
+# Callbacks
+@app.callback(
+    [
+        Output("livelihood-zone-dropdown", "options"),
+        Output("wealth-chart", "figure"),
+        Output("livelihood-chart", "figure"),
+        Output("data-table", "data"),
+    ],
+    [Input("country-dropdown", "value"), Input("livelihood-zone-dropdown", "value")],
+)
+def update_charts(selected_country, selected_zones):
+    # Filter data based on selected country
+    if selected_country:
+        filtered_livelihood = livelihood_data[livelihood_data["country_code"] == selected_country]
+        filtered_wealth = wealth_group_data[wealth_group_data["country_code"] == selected_country]
+        filtered_zones = sorted(filtered_livelihood["livelihood_zone"].unique())
+    else:
+        filtered_livelihood = livelihood_data
+        filtered_wealth = wealth_group_data
+        filtered_zones = unique_zones
+
+    # Update options for livelihood zone dropdown
+    zone_options = [{"label": zone, "value": zone} for zone in filtered_zones]
+
+    # Filter data based on selected livelihood zones
+    if selected_zones:
+        filtered_livelihood = filtered_livelihood[filtered_livelihood["livelihood_zone"].isin(selected_zones)]
+        filtered_wealth = filtered_wealth[filtered_wealth["livelihood_zone"].isin(selected_zones)]
+
+    # Group data for charts
+    livelihood_grouped = (
+        filtered_livelihood.groupby(["livelihood_zone", "strategy_type_label"]).size().reset_index(name="Count")
+    )
+    wealth_grouped = filtered_wealth.groupby("livelihood_zone").size().reset_index(name="Wealth Characteristics Count")
+
+    wealth_fig = px.bar(
+        wealth_grouped,
+        x="livelihood_zone",
+        y="Wealth Characteristics Count",
+        title="Wealth Characteristics per Baseline",
+        labels={"livelihood_zone": "Baseline", "Wealth Characteristics Count": "Count"},
+    )
+
+    livelihood_fig = px.bar(
+        livelihood_grouped,
+        x="strategy_type_label",
+        y="Count",
+        color="livelihood_zone",
+        title="Livelihood Strategies per Baseline",
+        labels={"strategy_type_label": "Strategy Type", "Count": "Count", "livelihood_zone": "Baseline"},
+    )
+
+    return zone_options, wealth_fig, livelihood_fig, livelihood_grouped.to_dict("records")
+
+
+# Run the app
+if __name__ == "__main__":
+    app.run_server(debug=True)

apps/viz/dash/inventory_dashboard/functions.py

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+import pandas as pd
+import requests
+
+
+def fetch_data(api_url):
+    """
+    Fetch data from the given API endpoint and return as a Pandas DataFrame.
+    """
+    try:
+        response = requests.get(api_url)
+        response.raise_for_status()
+        data = response.json()
+        return pd.DataFrame(data)
+    except Exception as e:
+        print(f"Error fetching data: {e}")
+        return pd.DataFrame()
+
+
+def prepare_livelihood_data(df):
+    """
+    Prepare livelihood strategy data for visualization.
+    """
+    df.rename(columns={"livelihood_zone_country": "country_code"}, inplace=True)
+    df["ls_baseline_date"] = df["livelihood_zone_baseline_label"].str.split(": ").str[1]
+    df["ls_baseline_month"] = pd.to_datetime(df["ls_baseline_date"], errors="coerce").dt.month_name()
+    return df
+
+
+def prepare_wealth_group_data(df):
+    """
+    Prepare wealth group data for visualization.
+    """
+    df.rename(columns={"livelihood_zone_country_code": "country_code"}, inplace=True)
+    return df

apps/viz/dash_wrapper.py

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+from django_plotly_dash import DjangoDash
+
+
+class SecureDjangoDash(DjangoDash):
+    """
+    An extended version of DjangoDash that allows fine-grained control of permissions
+    and clickjacking protection
+    """
+
+    xframe_options = "DENY"  # None (i.e. Allow) or SAMEORIGIN or DENY
+    login_required = True
+    permission_required = None
+
+    def __init__(self, *args, **kwargs):
+        self.permission_required = kwargs.pop("permission_required", None)
+        super().__init__(*args, **kwargs)