Open butterlyn opened 2 months ago
Is there anything in particular you had in mind from it for Patito? At a glance it looks like:
ValidationError
s not warnings)Rule
: a predicate which some percentage must pass (this seems in-keeping with Patito's expansion of scalar-valued validations to column-wise checks, e.g. column-wise value uniqueness)I also see it supports Polars
Can you share any more about your experience using it with Polars?
Hi, maintainer of cuallee
here.
Even when the documentation is mostly up to date with the Check
interface of cuallee
, the Control
interface lacks some love.
In any case, just wanted to say is that it does support polars
for example:
import polars as pl
from cuallee import Control
df = pl.DataFrame({"A":[1,2,3,4,5]})
Control.completeness(df)
# ========================================
shape: (1, 12)
┌─────┬───────────┬───────────┬─────────┬────────┬───────────┬───────┬──────┬───────────┬──────────┬──────────┬────────┐
│ id ┆ timestamp ┆ check ┆ level ┆ column ┆ rule ┆ value ┆ rows ┆ violation ┆ pass_rat ┆ pass_thr ┆ status │
│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ s ┆ e ┆ eshold ┆ --- │
│ i64 ┆ str ┆ str ┆ str ┆ str ┆ str ┆ str ┆ i64 ┆ --- ┆ --- ┆ --- ┆ str │
│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ i64 ┆ f64 ┆ f64 ┆ │
╞═════╪═══════════╪═══════════╪═════════╪════════╪═══════════╪═══════╪══════╪═══════════╪══════════╪══════════╪════════╡
│ 1 ┆ 2024-09-2 ┆ Completen ┆ WARNING ┆ A ┆ is_comple ┆ N/A ┆ 5 ┆ 0 ┆ 1.0 ┆ 1.0 ┆ PASS │
│ ┆ 8 ┆ ess ┆ ┆ ┆ te ┆ ┆ ┆ ┆ ┆ ┆ │
│ ┆ 08:27:32 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │
└─────┴───────────┴───────────┴─────────┴────────┴───────────┴───────┴──────┴───────────┴──────────┴──────────┴────────┘
Hi,
Was wondering if it's worth looking through the Polars checks implemented in the Python library
cuallee
to see if they're worth including inField
?