## import_contract()


Import a contract/schema from an external format.


Usage

``` python
import_contract(
    source,
    *,
    format=None,
    **kwargs,
)
```


Reads an external schema definition (JSON Schema, Frictionless Table Schema, dbt schema.yml, Pandera schema, Pydantic model, etc.) and produces a [ContractImport](ContractImport.md#pointblank.ContractImport) with validation steps mapped to Pointblank methods.


## Parameters


`source: Any`  
The source to import from. Can be: (1) a file path (str) to a schema/contract file, (2) a Python dict with schema content already loaded, or (3) a Python object (e.g., a Pandera `DataFrameSchema` or Pydantic model class).

`format: str | None = None`  
The format identifier (e.g., `"json_schema"`, `"frictionless"`, `"dbt"`, etc.). If `None`, the format is auto-detected from file extension or content.

`**kwargs: Any`  
Format-specific options passed to the adapter.


## Returns


`ContractImport`  
An object containing the imported columns, constraints, and methods to generate [Validate](Validate.md#pointblank.Validate) objects, [Contract](Contract.md#pointblank.Contract) objects, Python code, or YAML.


## Raises


`ValueError`  
If the format cannot be detected or no adapter is registered for it.


## Examples

``` python
import pointblank as pb

# Import from JSON Schema
result = pb.import_contract("user_profile.schema.json", format="json_schema")
validation = result.to_validate(data=my_df)
validation.interrogate()

# Auto-detect format
result = pb.import_contract("datapackage.json")

# Import from a dict
schema_dict = {"type": "object", "properties": {"age": {"type": "integer", "minimum": 0}}}
result = pb.import_contract(schema_dict, format="json_schema")
```