Set German Locale explicitely

wsgi.py

@@ -1,8 +1,17 @@
+import base64
 import datetime
+import io
+from itertools import chain
+from pathlib import Path
 
+import matplotlib.dates as mdates
+import matplotlib.pyplot as plt
+import matplotlib.ticker as mtick
+import numpy as np
 import pandas as pd
 from flask import Flask, render_template, request
 from flask_caching import Cache
+from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
 
 from download_digital import construct_dataframe, get_bez_data
 
@@ -12,7 +21,9 @@ config = {
     "CACHE_THRESHOLD": 1000,
     "CACHE_DIR": "cache",
 }
+import locale
 
+locale.setlocale(locale.LC_ALL, "de_DE.UTF-8")
 app = Flask(__name__)
 app.config.from_mapping(config)
 cache = Cache(app)
@@ -34,6 +45,121 @@ def get_tables(url: str) -> tuple[pd.DataFrame, pd.DataFrame]:
     return df, df_state
 
 
+def plot(
+    current_df: pd.DataFrame | None = None,
+    data_folder: str = "data",
+    sheet_name: str = "digital",
+    total_target: int = 1500,
+    plot_all: bool = False,
+    alpha: float | None = None,
+) -> str:
+    data_dict = {}
+    for f in sorted(Path(data_folder).iterdir()):
+        with f.open("rb") as ff:
+            df = pd.read_excel(ff, sheet_name=sheet_name)
+        df = df.astype({"Digitale Befragung": "Int32"})
+        sum_val = df[["Digitale Befragung"]].sum().iloc[0]
+        key = f.name[:10]
+        data_dict[key] = sum_val
+
+    data_dict["2023-08-15"] = 275
+
+    series = pd.Series(data_dict.values(), index=data_dict)
+    series.index = series.index.astype("datetime64[ns]") + pd.DateOffset(hours=10)
+
+    df = series.to_frame("Digitale Befragung")
+    df = df.reindex(
+        pd.date_range(start="2023-08-15", end=max(data_dict.keys()))
+        + pd.DateOffset(hours=10)
+    )
+
+    if current_df is not None:
+        current_df = current_df.astype({"Digitale Befragung": "Int32"})
+        sum_val = current_df[["Digitale Befragung"]].sum().iloc[0]
+        df.loc[datetime.datetime.now()] = sum_val
+
+    plt.figure(dpi=300)
+
+    # fill weekends
+    max_date = max(data_dict.keys())
+    max_date = datetime.datetime.strptime(max_date, "%Y-%m-%d") + datetime.timedelta(
+        days=1
+    )
+    days = pd.date_range(start="2023-08-14", end=max_date)
+    for idx, day in enumerate(days[:-1]):
+        if day.weekday() >= 5:
+            plt.gca().axvspan(days[idx], days[idx + 1], alpha=0.2, color="gray")
+
+    if alpha is not None:
+        plt.fill_between(
+            df.dropna().index,
+            df.dropna()["Digitale Befragung"],
+            color="#e4004e",
+            alpha=alpha,
+        )
+
+    plt.plot(
+        df.dropna().index,
+        df.dropna()["Digitale Befragung"],
+        ls="--",
+        marker="o",
+        lw=1,
+        color="#e4004e",
+        markersize=4,
+    )
+
+    if current_df is not None:
+        plt.annotate(
+            "Jetzt",
+            (df.dropna().index[-1], df.dropna()["Digitale Befragung"][-1] * 1.03),
+            fontsize=8,
+            ha="center",
+        )
+
+    plt.plot(df.index, df["Digitale Befragung"], lw=1.5, color="#e4004e")
+
+    plt.title("Teilnahme an Digitaler Beschäftigtenbefragung")
+    plt.ylabel("# Teilnahmen")
+    plt.ylim(0, total_target + 100)
+
+    # plt.gcf().autofmt_xdate()
+
+    # use timezone offset to center tick labels
+    plt.gca().xaxis.set_major_locator(
+        mdates.WeekdayLocator([mdates.TU], tz="Etc/GMT+12")
+    )
+    plt.gca().xaxis.set_minor_locator(mdates.DayLocator())
+    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter("%a %d.%m."))
+
+    plt.grid(True, which="major", axis="y")
+    plt.grid(True, which="minor", axis="x")
+
+    plt.gca().tick_params("x", length=0, which="major")
+
+    def val_to_perc(val):
+        return 100 * val / total_target
+
+    def perc_to_val(perc):
+        return perc * total_target / 100
+
+    sec_ax = plt.gca().secondary_yaxis("right", functions=(val_to_perc, perc_to_val))
+    sec_ax.set_ylabel("# Teilnahmen [% Erfolg]")
+    sec_ax.yaxis.set_major_formatter(mtick.PercentFormatter())
+
+    plt.axhline(y=total_target, color="#48a9be", linestyle="--")
+    plt.tight_layout()
+
+    # Convert plot to PNG image
+    pngImage = io.BytesIO()
+    FigureCanvas(plt.gcf()).print_png(pngImage)
+
+    # Encode PNG image to base64 string
+    pngImageB64String = "data:image/png;base64,"
+    pngImageB64String += base64.b64encode(pngImage.getvalue()).decode("utf8")
+
+    return pngImageB64String
+
+
 @app.route("/")
 @cache.cached(timeout=50)
 def tables(
@@ -81,10 +207,13 @@ def tables(
     _print_as_html(df_state)
     _print_as_html(df)
 
+    image = plot(df_state, plot_all=True)
+
     return render_template(
         "base.html",
         tables="\n".join(output_str),
         timestamp=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        image=image,
     )