Add route for single states

wsgi.py

@@ -11,10 +11,10 @@ import matplotlib.pyplot as plt
 import matplotlib.ticker as mtick
 import numpy as np
 import pandas as pd
-from flask import Flask, Markup, render_template, request
+from flask import Flask, Markup, abort, render_template, request
 from flask_caching import Cache
 
-from download_digital import construct_dataframe, get_bez_data, get_landesbezirk
+from download_digital import construct_dataframe, get_bez_data, get_landesbezirk, landesbezirk_dict
 
 config = {
     "CACHE_TYPE": "FileSystemCache",
@@ -23,6 +23,14 @@ config = {
     "CACHE_DIR": "cache",
 }
 
+abbrev_dict = {
+    "BBR": "Berlin-Brandenburg",
+    "BaWü": "Baden-Württemberg",
+    "NRW": "Nordrhein-Westfalen",
+    "RLP": "Rheinland-Pfalz-Saarland",
+    "SAT": "Sachsen, Sachsen-Anhalt, Thüringen",
+}
+
 os.environ["TZ"] = "Europe/Berlin"
 time.tzset()
 
@@ -96,6 +104,7 @@ def plot(
     total_targets: tuple[int, ...] = (1500, 2500, 3500),
     alpha: float | None = None,
     landesbez_str: str | None = None,
+    fix_lims: bool = True,
 ) -> str:
     fig = plt.figure(dpi=300)
 
@@ -125,7 +134,7 @@ def plot(
                 ls="--",
                 marker="o",
                 lw=1,
-                color="#e4004e" if bez is None else None,
+                color="#e4004e" if bez is None or not fix_lims else None,
                 markersize=4,
                 label=bez if bez is not None else "Bundesweit",
             )
@@ -152,14 +161,15 @@ def plot(
     plt.title("Teilnahme an Digitaler Beschäftigtenbefragung")
     plt.ylabel("# Teilnahmen")
 
-    max_val = df.sum(axis=1).max().item()
+    if fix_lims:
+        max_val = df.sum(axis=1).max().item()
 
-    nearest_target = np.array(total_targets, dtype=np.float32) - max_val
-    nearest_target[nearest_target <= 0] = np.inf
-    idx = np.argmin(nearest_target)
+        nearest_target = np.array(total_targets, dtype=np.float32) - max_val
+        nearest_target[nearest_target <= 0] = np.inf
+        idx = np.argmin(nearest_target)
 
-    ceil_val = max(max_val, total_targets[idx])
-    plt.ylim(0, ceil_val * 1.025)
+        ceil_val = max(max_val, total_targets[idx])
+        plt.ylim(0, ceil_val * 1.025)
     plt.legend()
 
     # use timezone offset to center tick labels
@@ -184,8 +194,9 @@ def plot(
     sec_ax.set_ylabel("# Teilnahmen [% Erfolg]")
     sec_ax.yaxis.set_major_formatter(mtick.PercentFormatter())
 
-    for total_target in total_targets:
-        plt.axhline(y=total_target, color="#48a9be", linestyle="--")
+    if fix_lims:
+        for total_target in total_targets:
+            plt.axhline(y=total_target, color="#48a9be", linestyle="--")
 
     plt.tight_layout()
 
@@ -195,6 +206,8 @@ def plot(
 def create_fig(
     url: str = "https://beschaeftigtenbefragung.verdi.de/",
     importance_factor: float = 1.0,
+    landesbez_strs: list[str | None] | None = None,
+    fix_lims: bool = True,
 ):
     curr_datetime = datetime.datetime.now()
     try:
@@ -230,17 +243,19 @@ def create_fig(
         timestamp = Markup(f'<font color="red">{key} 10:00:00</font>')
 
     total = plot_df.loc[curr_datetime].sum()
-    landesbez_strs = [None] + [
-        bez
-        for bez in plot_df.columns
-        if plot_df.loc[curr_datetime][bez] >= importance_factor * total
-    ]
+    if landesbez_strs is None:
+        landesbez_strs = [None] + [
+            bez
+            for bez in plot_df.columns
+            if plot_df.loc[curr_datetime][bez] >= importance_factor * total
+        ]
     return (
         plot(
             curr_datetime,
             plot_df,
             annotate_current=annotate_current,
             landesbez_str=landesbez_strs,
+            fix_lims=fix_lims,
         ),
         df,
         df_state,
@@ -257,73 +272,110 @@ def convert_fig_to_svg(fig: plt.Figure) -> str:
     return imgdata.read()
 
 
-@app.route("/")
-@cache.cached(query_string=True)
-def tables():
-    def _print_as_html(df: pd.DataFrame, total: int | None = None) -> None:
-        df = df.astype({"Digitale Befragung": "Int32"})
+def _print_as_html(df: pd.DataFrame, output_str: list[str], total: int | None = None, dropna: bool = True) -> list[str]:
+    df = df.astype({"Digitale Befragung": "Int32"})
+    if dropna:
         df = df.dropna()
-        with pd.option_context("display.max_rows", None):
-            table = df.to_html(
-                index_names=False,
-                justify="left",
-                index=False,
-                classes="sortable dataframe",
-            )
+    with pd.option_context("display.max_rows", None):
+        table = df.to_html(
+            index_names=False,
+            justify="left",
+            index=False,
+            classes="sortable dataframe",
+        )
 
-            tfoot = [
-                "  <tfoot>",
-                "    <tr>",
-                "      <td>Gesamt</td>",
+        tfoot = [
+            "  <tfoot>",
+            "    <tr>",
+            "      <td>Gesamt</td>",
+        ]
+        for i in range(len(df.columns) - 2):
+            tfoot.append("      <td></td>")
+        tfoot.extend(
+            [
+                f"      <td>{df['Digitale Befragung'].sum()}</td>",
+                "    </tr>",
             ]
+        )
+        if total:
+            tfoot.extend([
+                "    <tr>",
+                "      <td>Weitere Bezirke</td>",
+            ])
             for i in range(len(df.columns) - 2):
                 tfoot.append("      <td></td>")
             tfoot.extend(
                 [
-                    f"      <td>{df['Digitale Befragung'].sum()}</td>",
+                    f"      <td>{total - df['Digitale Befragung'].sum()}</td>",
                     "    </tr>",
                 ]
             )
-            if total:
-                tfoot.extend([
-                    "    <tr>",
-                    "      <td>Weitere Bezirke</td>",
-                ])
-                for i in range(len(df.columns) - 2):
-                    tfoot.append("      <td></td>")
-                tfoot.extend(
-                    [
-                        f"      <td>{total - df['Digitale Befragung'].sum()}</td>",
-                        "    </tr>",
-                    ]
-                )
-            tfoot.append("  </tfoot>")
+        tfoot.append("  </tfoot>")
 
-            tfoot = "\n".join(tfoot)
-            idx = table.index("</table>")
-            output_str.append(table[: idx - 1])
-            output_str.append(tfoot)
-            output_str.append(table[idx:])
+        tfoot = "\n".join(tfoot)
+        idx = table.index("</table>")
+        output_str.append(table[: idx - 1])
+        output_str.append(tfoot)
+        output_str.append(table[idx:])
+    return output_str
 
 
+@app.route("/<state>")
+@cache.cached(query_string=True)
+def state_dashboard(state: str):
+    if state in abbrev_dict:
+        state = abbrev_dict[state]
+
+    if state not in landesbezirk_dict.values():
+        abort(404)
+
     importance_factor = request.args.get("importance")
     if not importance_factor:
         importance_factor = 1.0
     else:
         importance_factor = float(importance_factor)
 
+    fig, df, df_state, timestamp = create_fig(landesbez_strs=[state], fix_lims=False)
+    svg_string = convert_fig_to_svg(fig)
+    plt.close()
+
+    df["Bundesland"] = df.index.map(get_landesbezirk)
+    df = df.rename(columns={"Bundesland": "Landesbezirk"})
+
+    df_state = df_state.loc[df_state["Landesbezirk"] == state]
+    df = df.loc[df["Landesbezirk"] == state]
+
     output_str = []
+    output_str = _print_as_html(df_state, output_str, dropna=False)
+    output_str = _print_as_html(df, output_str, total=df_state['Digitale Befragung'].sum(), dropna=False)
+
+    return render_template(
+        "base.html",
+        tables="\n".join(output_str),
+        timestamp=timestamp,
+        image=svg_string,
+    )
+
+
+@app.route("/")
+@cache.cached(query_string=True)
+def dashboard():
+    importance_factor = request.args.get("importance")
+    if not importance_factor:
+        importance_factor = 1.0
+    else:
+        importance_factor = float(importance_factor)
 
     fig, df, df_state, timestamp = create_fig(importance_factor=importance_factor)
     svg_string = convert_fig_to_svg(fig)
     plt.close()
 
-    _print_as_html(df_state)
-
     df["Bundesland"] = df.index.map(get_landesbezirk)
     df = df.rename(columns={"Bundesland": "Landesbezirk"})
 
-    _print_as_html(df, total=df_state['Digitale Befragung'].sum())
+    output_str = []
+    output_str = _print_as_html(df_state, output_str, dropna=False)
+    output_str = _print_as_html(df, output_str, total=df_state['Digitale Befragung'].sum())
 
     return render_template(
         "base.html",