Compute difference between dates and convert into weeks/months/years in polars dataframe

I have a pl.DataFrame with a start_date and end_date column. I need to compute the difference between those two columns and add new columns representing the result in days, weeks, months and years.

I would be fine to get an approximate result, meaning dividing the days by 7 / 30 / 365.
My problem is to convert the duration[ns] type into an integer type.

import datetime

import polars as pl

df = pl.DataFrame(
    {"start_date": datetime.date(2024, 1, 1), "end_date": datetime.date(2024, 7, 31)}
)

df = df.with_columns((pl.col("end_date") - pl.col("start_date")).alias("days"))
print(df)

shape: (1, 3)
┌────────────┬────────────┬──────────────┐
│ start_date ┆ end_date   ┆ days         │
│ ---        ┆ ---        ┆ ---          │
│ date       ┆ date       ┆ duration[ms] │
╞════════════╪════════════╪══════════════╡
│ 2024-01-01 ┆ 2024-07-31 ┆ 212d         │
└────────────┴────────────┴──────────────┘

>Solution :

you can use dt.total_days() to extract hours from Duration datatype:

df.with_columns(
    days = (pl.col.end_date - pl.col.start_date).total_days()
)

┌────────────┬────────────┬──────┐
│ start_date ┆ end_date   ┆ days │
│ ---        ┆ ---        ┆ ---  │
│ date       ┆ date       ┆ i64  │
╞════════════╪════════════╪══════╡
│ 2024-01-01 ┆ 2024-07-31 ┆ 212  │
└────────────┴────────────┴──────┘