.gitignore

@@ -1,4 +1,3 @@
-plots
 .venv
 cache
 __pycache__

plot.py

@@ -1,17 +0,0 @@
-from pathlib import Path
-
-import fire
-import matplotlib.pyplot as plt
-
-from wsgi import create_fig
-
-
-def main(folder: str = "plots"):
-    fig, _df, _df_state, timestamp = create_fig()
-    timestamp = timestamp.replace(" ", "_")
-    timestamp = timestamp.replace(":", "-")
-    fig.savefig(Path(folder) / f"digital_plot_{timestamp}.png", dpi=300)
-
-
-if __name__ == "__main__":
-    fire.Fire(main)

wsgi.py

@@ -183,53 +183,6 @@ def plot(
 
     return fig
 
-def create_fig(url: str = "https://beschaeftigtenbefragung.verdi.de/", importance_factor: float = 1.0):
-    curr_datetime = datetime.datetime.now()
-    try:
-        df, df_state = get_tables(url)
-
-        df = df.sort_values(
-            ["Digitale Befragung", "Bundesland", "Bezirk"],
-            ascending=[False, True, True],
-        )
-
-        df_state = df_state.sort_values("Landesbezirk")
-
-        plot_df = create_plot_df(curr_datetime, df_state)
-        annotate_current = True
-        timestamp = curr_datetime.strftime("%Y-%m-%d %H:%M:%S")
-
-    except Exception as e:
-        print(e)
-        last_file = sorted(Path("data").iterdir())[-1]
-        key = last_file.name[:10]
-
-        with (Path("data") / f"{key}_data.ods").open("rb") as ff:
-            df = pd.read_excel(ff, sheet_name="digital", index_col=0).astype(
-                {"Digitale Befragung": "Int32"}
-            )
-        with (Path("data") / f"{key}_state_data.ods").open("rb") as ff:
-            df_state = pd.read_excel(ff, sheet_name="digital", index_col=0).astype(
-                {"Digitale Befragung": "Int32"}
-            )
-
-        plot_df = create_plot_df(curr_datetime)
-        annotate_current = False
-        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
-    ]
-    return plot(
-        curr_datetime,
-        plot_df,
-        annotate_current=annotate_current,
-        landesbez_str=landesbez_strs,
-    ), df, df_state, timestamp
-
 
 def convert_fig_to_svg(fig: plt.Figure) -> str:
     # Convert plot to SVG image
@@ -242,7 +195,10 @@ def convert_fig_to_svg(fig: plt.Figure) -> str:
 
 @app.route("/")
 @cache.cached()
-def tables():
+def tables(
+    url: str = "https://beschaeftigtenbefragung.verdi.de/",
+    importance_factor: float = 1,
+):
     def _print_as_html(df: pd.DataFrame):
         df = df.astype({"Digitale Befragung": "Int32"})
         with pd.option_context("display.max_rows", None):
@@ -275,7 +231,52 @@ def tables():
 
     output_str = []
 
-    fig, df, df_state, timestamp = create_fig()
+    curr_datetime = datetime.datetime.now()
+
+    try:
+        df, df_state = get_tables(url)
+
+        df = df.sort_values(
+            ["Digitale Befragung", "Bundesland", "Bezirk"],
+            ascending=[False, True, True],
+        )
+
+        df_state = df_state.sort_values("Landesbezirk")
+
+        plot_df = create_plot_df(curr_datetime, df_state)
+        annotate_current = True
+        timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
+    except Exception as e:
+        print(e)
+        last_file = sorted(Path("data").iterdir())[-1]
+        key = last_file.name[:10]
+
+        with (Path("data") / f"{key}_data.ods").open("rb") as ff:
+            df = pd.read_excel(ff, sheet_name="digital", index_col=0).astype(
+                {"Digitale Befragung": "Int32"}
+            )
+        with (Path("data") / f"{key}_state_data.ods").open("rb") as ff:
+            df_state = pd.read_excel(ff, sheet_name="digital", index_col=0).astype(
+                {"Digitale Befragung": "Int32"}
+            )
+
+        plot_df = create_plot_df(curr_datetime)
+        annotate_current = False
+        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
+    ]
+    fig = plot(
+        curr_datetime,
+        plot_df,
+        annotate_current=annotate_current,
+        landesbez_str=landesbez_strs,
+    )
     svg_string = convert_fig_to_svg(fig)
     plt.close()