How to use to_pandera_column method in pandera

Best Python code snippet using pandera_python

io.py

Source:io.py Github

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...487 This currently returns ``False`` for all fields within a frictionless488 schema.489 """490 return False491 def to_pandera_column(self) -> Dict:492 """Export this field to a column spec dictionary."""493 return {494 "checks": self.checks,495 "coerce": self.coerce,496 "nullable": self.nullable,497 "unique": self.unique,498 "dtype": self.dtype,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(555 field, schema.primary_key556 ).to_pandera_column()557 for field in schema.fields558 },559 "index": None,560 "checks": None,561 "coerce": True,562 "strict": True,563 # only set dataframe-level uniqueness if the frictionless primary564 # key property specifies more than one field565 "unique": (566 None if len(schema.primary_key) == 1 else list(schema.primary_key)567 ),568 }...

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