In Polars (1.0.0) we can use len() after group_by_dynamic() in lazy mode but not in eager mode:

from datetime import datetime

import polars as pl

df = pl.DataFrame(
    {
        "time": pl.datetime_range(
            start=datetime(2024, 6, 30),
            end=datetime(2024, 7, 16),
            interval="1d",
            eager=True,
        ),
    }
).with_columns(n=pl.int_range(pl.len()))

# len() in lazy mode: OK
x = df.lazy().group_by_dynamic("time", every="1w").len(name="count").collect()
print(x)
# shape: (4, 2)
# ┌─────────────────────┬───────┐
# │ time                ┆ count │
# │ ---                 ┆ ---   │
# │ datetime[μs]        ┆ u32   │
# ╞═════════════════════╪═══════╡
# │ 2024-06-24 00:00:00 ┆ 1     │
# │ 2024-07-01 00:00:00 ┆ 7     │
# │ 2024-07-08 00:00:00 ┆ 7     │
# │ 2024-07-15 00:00:00 ┆ 2     │
# └─────────────────────┴───────┘

# len() in eager mode: ERROR
x = df.group_by_dynamic("time", every="1w").len(name="count")
print(x)
# Traceback (most recent call last):
#   File "/Users/anto/src/poste/sda-poste-logistics/script/polars_bug_groupby_dynamic_len.py", line 26, in <module>
#     x = df.group_by_dynamic("time", every="1w").len(name="count")
#         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
# AttributeError: 'DynamicGroupBy' object has no attribute 'len'

Why is it happening? It looks very odd!

For an eager df I need to resort to:

# OK
x = df.group_by_dynamic("time", every="1w").agg(counts=pl.len())
print(x)