# Step Report for a Schema Check
Pointblank Validation
Step report for a schema check DuckDBsmall_table
STEP COLUMNS VALUES TBL EVAL UNITS PASS FAIL W E C EXT
#4CA64C66 1
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-- SCHEMA ✓ 1 0
0.00		 1
1.00		 -- -- -- --
2026-07-13 17:46:30 UTC< 1 s2026-07-13 17:46:30 UTC
Notes

Step 1 (schema_check) ✗ Schema validation failed: 1 unmatched column(s), 2 dtype mismatch(es).

Schema Comparison
TARGET EXPECTED
COLUMN DATA TYPE COLUMN DATA TYPE
1 date_time timestamp(6) 1 date_time ✓ timestamp ✗
2 date date 2 dates ✗ date --
3 a int64 3 a ✓ int64 ✓
4 b string 4 b ✓ --
5 c int64 5 c ✓ --
6 d float64 6 d ✓ float64 ✓
7 e boolean 7 e ✓ bool | boolean ✓
8 f string 8 f ✓ str ✗
Supplied Column Schema: [('date_time', 'timestamp'), ('dates', 'date'), ('a', 'int64'), ('b',), ('c',), ('d', 'float64'), ('e', ['bool', 'boolean']), ('f', 'str')]
Schema Match Settings COMPLETE IN ORDER COLUMN ≠ column DTYPE ≠ dtype float ≠ float64
Report for Validation Step 1 ✗ COLUMN SCHEMA MATCH COMPLETE IN ORDER COLUMN ≠ column DTYPE ≠ dtype float ≠ float64
TARGET EXPECTED
COLUMN DATA TYPE COLUMN DATA TYPE
1 date_time timestamp(6) 1 date_time ✓ timestamp ✗
2 date date 2 dates ✗ date --
3 a int64 3 a ✓ int64 ✓
4 b string 4 b ✓ --
5 c int64 5 c ✓ --
6 d float64 6 d ✓ float64 ✓
7 e boolean 7 e ✓ bool | boolean ✓
8 f string 8 f ✓ str ✗
Supplied Column Schema: [('date_time', 'timestamp'), ('dates', 'date'), ('a', 'int64'), ('b',), ('c',), ('d', 'float64'), ('e', ['bool', 'boolean']), ('f', 'str')]
``` python import pointblank as pb # Create a schema for the target table (`small_table` as a DuckDB table) schema = pb.Schema( columns=[ ("date_time", "timestamp"), # this dtype doesn't match ("dates", "date"), # this column name doesn't match ("a", "int64"), ("b",), # omit dtype to not check for it ("c",), # "" "" "" "" ("d", "float64"), ("e", ["bool", "boolean"]), # try several dtypes (second one matches) ("f", "str"), # this dtype doesn't match ] ) # Use the `col_schema_match()` validation method to perform a schema check validation = ( pb.Validate( data=pb.load_dataset(dataset="small_table", tbl_type="duckdb"), tbl_name="small_table", label="Step report for a schema check" ) .col_schema_match(schema=schema) .interrogate() ) validation ``` ``` python validation.get_step_report(i=1) ``` Preview of Input Table
DuckDBRows13Columns8
date_time timestamp
date date
a int64
b string
c int64
d float64
e boolean
f string
1 2016-01-04 11:00:00 2016-01-04 2 1-bcd-345 3 3423.29 True high
2 2016-01-04 00:32:00 2016-01-04 3 5-egh-163 8 9999.99 True low
3 2016-01-05 13:32:00 2016-01-05 6 8-kdg-938 3 2343.23 True high
4 2016-01-06 17:23:00 2016-01-06 2 5-jdo-903 NULL 3892.4 False mid
5 2016-01-09 12:36:00 2016-01-09 8 3-ldm-038 7 283.94 True low
6 2016-01-11 06:15:00 2016-01-11 4 2-dhe-923 4 3291.03 True mid
7 2016-01-15 18:46:00 2016-01-15 7 1-knw-093 3 843.34 True high
8 2016-01-17 11:27:00 2016-01-17 4 5-boe-639 2 1035.64 False low
9 2016-01-20 04:30:00 2016-01-20 3 5-bce-642 9 837.93 False high
10 2016-01-20 04:30:00 2016-01-20 3 5-bce-642 9 837.93 False high
11 2016-01-26 20:07:00 2016-01-26 4 2-dmx-010 7 833.98 True low
12 2016-01-28 02:51:00 2016-01-28 2 7-dmx-010 8 108.34 False low
13 2016-01-30 11:23:00 2016-01-30 1 3-dka-303 NULL 2230.09 True high