Add mod time checking

popcorn.py

@@ -5,10 +5,11 @@ app = marimo.App(width="medium")
 
 with app.setup:
     # Initialization code that runs beimpofore all other cells
+    import re
+
     import lets_plot as lp
     import marimo as mo
     import polars as pl
-    import re
 
 
 @app.cell(hide_code=True)
@@ -25,28 +26,21 @@ def _():
         except AttributeError:
             return None
 
-    sizes_df = (
+    sizes_df_raw = (
         pl.read_csv("data/file_sizes.csv")
         .with_columns(
             pl.col("name")
             .str.replace(r"data/(\d{4}-\d{2}-\d{2}).json", "${1}")
             .str.to_date()
             .alias("date"),
-            pl.col("size").map_elements(lambda x: parse_size(x), return_dtype=pl.Float32).alias("size_num")
+            pl.col("size")
+            .map_elements(lambda x: parse_size(x), return_dtype=pl.Float32)
+            .alias("size_num"),
         )
         .select(["date", "size_num", "size", "modified"])
     )
-    sizes_df_null = sizes_df.filter(pl.col("size_num").is_null())
-    sizes_df = sizes_df.filter(pl.col("size").is_not_null())
-    return
-
-
-@app.cell
-def _(sizes_df_null):
-    sizes_df_null.select(["date", "size"]).style.tab_header(
-        title="Missing Days",
-        subtitle="Days with 0B size due to missing on the popcorn server.",
-    )
+    sizes_df = sizes_df_raw.filter(pl.col("size_num").is_not_null())
+    return sizes_df, sizes_df_raw
 
 
 @app.cell
@@ -54,9 +48,10 @@ def _(sizes_df):
     (
         lp.ggplot(sizes_df, lp.aes(x="date", y="size"))
         + lp.geom_point()
+        + lp.geom_smooth(method="lm")
         + lp.labs(
-            title="File sizes",
-            subtitle="Size of daily popcorn files over time",
+            title="Size growth",
+            subtitle="Size of daily popcorn statistics files over time",
             caption="Raw json file size, without any formatting, removal of markers, characters or newlines.",
         )
     )
@@ -66,13 +61,59 @@ def _(sizes_df):
 def _(sizes_df):
     (
         lp.ggplot(sizes_df, lp.aes(x="date", y="size"))
-        + lp.geom_dotplot()
+        + lp.geom_point()
+        + lp.geom_smooth(method="lowess")
         + lp.labs(
             title="",
             subtitle="",
             caption="",
         )
     )
+    return
+
+
+@app.cell
+def _():
+    mo.md(
+        r"""
+    ## Odds and Ends
+    There are some missing days in the statistics.
+    """
+    )
+    return
+
+
+@app.cell
+def _(sizes_df_raw):
+    sizes_df_null = sizes_df_raw.filter(pl.col("size_num").is_null())
+    sizes_df_null.select(["date", "size"]).style.tab_header(
+        title="Missing Days",
+        subtitle="Days with 0B size due to missing on the popcorn server.",
+    )
+    return
+
+
+@app.cell
+def _(sizes_df):
+    def _():
+        different_modification_date = sizes_df.with_columns(
+            pl.col("modified")
+            .str.to_datetime(format="%F %T %:z", strict=False)
+            .alias("modified_dt"),
+        ).filter(pl.col("date") != pl.col("modified_dt").dt.date())
+        # This does not work well what are we showing?
+        # 'true' capture date on X but then what on Y - the
+        # same date for each? the difference in dt?
+        return (
+            lp.ggplot(
+                different_modification_date,
+                lp.aes("date", "modified_dt"),
+            )
+            + lp.geom_freqpoly()
+        )
+
+    _()
+    return
 
 
 if __name__ == "__main__":