wsgi.py

@@ -1,17 +1,8 @@
-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
 
@@ -21,9 +12,7 @@ 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)
@@ -45,121 +34,6 @@ 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(
@@ -207,13 +81,10 @@ 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,
     )