Validate.to_yaml()

Serialize this validation plan to a yaml_interrogate()-compatible YAML config.

Usage

Validate.to_yaml(path=None)

The to_yaml() method renders the validation plan as a YAML document using the same schema consumed by yaml_interrogate(). This enables storing plans as configuration, sharing them across projects, and round-tripping a plan through YAML.

Parameters

path: str | Path | None = None: An optional file path. If provided, the YAML is written to this file (parent directories are created as needed) in addition to being returned.

Returns

str: The validation plan as a YAML string. The tbl field is set from tbl_name when available, otherwise to the placeholder your_data; set it to a loadable data source before passing the YAML to yaml_interrogate(). The reference field is written the same way as in to_code(): a file path or connection string as-is, and the placeholder your_reference_data (with a warning) for an in-memory table.

Notes On Fidelity

As with to_code(), steps carrying non-serializable Python objects (pre= callables, actions=, callable active=, and the expressions of col_vals_expr()/conjointly()/specially()) cannot be represented in YAML; a placeholder is emitted and a warning is raised.

Examples

Let’s create a validation plan for the small_table dataset and write it as YAML.

import pointblank as pb

small_table = pb.load_dataset(dataset="small_table", tbl_type="polars")

validation = (
    pb.Validate(data=small_table, tbl_name="small_table", thresholds=(0.1, 0.2))
    .col_vals_gt(columns="d", value=100)
    .col_vals_not_null(columns="c")
    .col_vals_in_set(columns="f", set=["low", "mid", "high"])
)

yaml_config = validation.to_yaml()

print(yaml_config)

tbl: small_table
tbl_name: small_table
thresholds:
  warning: 0.1
  error: 0.2
steps:
- col_vals_gt:
    columns: d
    value: 100
- col_vals_not_null:
    columns: c
- col_vals_in_set:
    columns: f
    set:
    - low
    - mid
    - high

Each step becomes an entry under steps, named after its method and with its arguments beneath. The tbl field was set from tbl_name=. Here, that name happens to be a dataset that yaml_interrogate() can load, so the YAML runs as is:

pb.yaml_interrogate(yaml_config)

		STEP	COLUMNS	VALUES	EVAL	UNITS	PASS	FAIL	W	E	C	EXT
Pointblank Validation
2026-11-05\|01:34:19 Polarssmall_tableWARNING0.1ERROR0.2CRITICAL—
#4CA64C	1	col_vals_gt()	d	100	✓	13	13 1.00	0 0.00	○	○	—	—
#AAAAAA	2	col_vals_not_null()	c	—	✓	13	11 0.85	2 0.15	●	○	—
#4CA64C	3	col_vals_in_set()	f	low, mid, high	✓	13	13 1.00	0 0.00	○	○	—	—

For a table of your own, set tbl to a file path or connection string before running the YAML. To keep the configuration (for instance, in version control next to the pipeline it checks), give to_yaml() a path=, which writes the file and still returns the string.