How to use from_frictionless_schema method in pandera

Best Python code snippet using pandera_python

io.py

Source:io.py

...499            "required": self.required,500            "name": self.name,501            "regex": self.regex,502        }503def from_frictionless_schema(504    schema: Union[str, Path, Dict, FrictionlessSchema]505) -> DataFrameSchema:506    # pylint: disable=line-too-long507    """Create a :class:`~pandera.schemas.DataFrameSchema` from either a508    frictionless json/yaml schema file saved on disk, or from a frictionless509    schema already loaded into memory.510    Each field from the frictionless schema will be converted to a pandera511    column specification using :class:`~pandera.io.FrictionlessFieldParser`512    to map field characteristics to pandera column specifications.513    :param schema: the frictionless schema object (or a514        string/Path to the location on disk of a schema specification) to515        parse.516    :returns: dataframe schema with frictionless field specs converted to517        pandera column checks and constraints for use as normal.518    :example:519    Here, we're defining a very basic frictionless schema in memory before520    parsing it and then querying the resulting521    :class:`~pandera.schemas.DataFrameSchema` object as per any other Pandera522    schema:523    >>> from pandera.io import from_frictionless_schema524    >>>525    >>> FRICTIONLESS_SCHEMA = {526    ...     "fields": [527    ...         {528    ...             "name": "column_1",529    ...             "type": "integer",530    ...             "constraints": {"minimum": 10, "maximum": 99}531    ...         },532    ...         {533    ...             "name": "column_2",534    ...             "type": "string",535    ...             "constraints": {"maxLength": 10, "pattern": "\\S+"}536    ...         },537    ...     ],538    ...     "primaryKey": "column_1"539    ... }540    >>> schema = from_frictionless_schema(FRICTIONLESS_SCHEMA)541    >>> schema.columns["column_1"].checks542    [<Check in_range: in_range(10, 99)>]543    >>> schema.columns["column_1"].required544    True545    >>> schema.columns["column_1"].unique546    True547    >>> schema.columns["column_2"].checks548    [<Check str_length: str_length(None, 10)>, <Check str_matches: str_matches(re.compile('^\\\\S+$'))>]549    """550    if not isinstance(schema, FrictionlessSchema):551        schema = FrictionlessSchema(schema)552    assembled_schema = {553        "columns": {554            field.name: FrictionlessFieldParser(...

20211122_pycon_blackrock_data_testing.py

Source:20211122_pycon_blackrock_data_testing.py

...295            "constraints": {"isin": ["A", "B", "C"]}296        },297    ],298}299schema = from_frictionless_schema(frictionless_schema)300print(schema)301# %% [markdown] slideshow={"slide_type": "slide"}302# #### Facilitate Property-based Testing with Generative Schemas303#304# Generate valid examples under the schema's constraints305# %%306RawData.example(size=3)307# %%308CleanData.example(size=3)309# %% slideshow={"slide_type": "slide"}310# Transform your unit test suite!311from hypothesis import given312@pa.check_types313def clean(raw_data: DataFrame[RawData]) -> DataFrame[CleanData]:...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.