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4e43916fb1
...
dcbec17064
62
wsgi.py
62
wsgi.py
@ -8,7 +8,7 @@ import matplotlib.pyplot as plt
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import matplotlib.ticker as mtick
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import numpy as np
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import pandas as pd
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from flask import Flask, Markup, render_template, request
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from flask import Flask, render_template, request
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from flask_caching import Cache
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from download_digital import construct_dataframe, get_bez_data
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@ -48,10 +48,9 @@ def plot(
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data_folder: str = "data",
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sheet_name: str = "digital",
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total_target: int = 1500,
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plot_all: bool = False,
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alpha: float | None = None,
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) -> str:
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curr_datetime = datetime.datetime.now()
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data_dict = {}
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## Important: If multiple results are stored for the same date
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@ -74,22 +73,22 @@ def plot(
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df = series.to_frame("Digitale Befragung")
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df = df.reindex(
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pd.date_range(start="2023-08-15", end=curr_datetime)
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pd.date_range(start="2023-08-15", end=max(data_dict.keys()))
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+ pd.DateOffset(hours=10)
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)
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if current_df is not None:
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current_df = current_df.astype({"Digitale Befragung": "Int32"})
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sum_val = current_df[["Digitale Befragung"]].sum().iloc[0]
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df.loc[curr_datetime] = sum_val
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if pd.isna(df.loc[df.index.max()][0]):
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df = df.drop([df.index.max()])
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df.loc[datetime.datetime.now()] = sum_val
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fig = plt.figure(dpi=300)
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# fill weekends
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max_date = curr_datetime + datetime.timedelta(days=1)
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max_date = max(data_dict.keys())
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max_date = datetime.datetime.strptime(max_date, "%Y-%m-%d") + datetime.timedelta(
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days=1
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)
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days = pd.date_range(start="2023-08-14", end=max_date)
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for idx, day in enumerate(days[:-1]):
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if day.weekday() >= 5:
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@ -167,6 +166,16 @@ def plot(
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def tables(
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url: str = "https://beschaeftigtenbefragung.verdi.de/",
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):
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df, df_state = get_tables(url)
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df = df.sort_values(
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["Digitale Befragung", "Bundesland", "Bezirk"], ascending=[False, True, True]
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)
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df_state = df_state.sort_values("Landesbezirk")
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output_str = []
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def _print_as_html(df: pd.DataFrame):
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df = df.astype({"Digitale Befragung": "Int32"})
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with pd.option_context("display.max_rows", None):
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@ -197,44 +206,15 @@ def tables(
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output_str.append(tfoot)
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output_str.append(table[idx:])
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output_str = []
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try:
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df, df_state = get_tables(url)
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df = df.sort_values(
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["Digitale Befragung", "Bundesland", "Bezirk"],
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ascending=[False, True, True],
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)
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df_state = df_state.sort_values("Landesbezirk")
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image = plot(df_state)
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timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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except Exception:
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last_file = sorted(Path("data").iterdir())[-1]
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key = last_file.name[:10]
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with (Path("data") / f"{key}_data.ods").open("rb") as ff:
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df = pd.read_excel(ff, sheet_name="digital").astype(
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{"Digitale Befragung": "Int32"}
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)
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with (Path("data") / f"{key}_state_data.ods").open("rb") as ff:
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df_state = pd.read_excel(ff, sheet_name="digital").astype(
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{"Digitale Befragung": "Int32"}
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)
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image = plot()
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timestamp = Markup(f'<font color="red">{key} 10:00:00</font>')
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_print_as_html(df_state)
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_print_as_html(df)
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image = plot(df_state, plot_all=True)
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return render_template(
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"base.html",
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tables="\n".join(output_str),
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timestamp=timestamp,
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timestamp=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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image=image,
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)
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