Detail: Frame: Accessor Type Clinic
Overview: Frame: Accessor Type Clinic
- Frame.via_type_clinic.to_hint
- Frame.via_type_clinic
- TypeClinic.to_hint()[source]
Return the type hint (the type and/or generic aliases necessary) to represent the object given at initialization.
>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), index=sf.IndexHierarchy.from_product((0, 1), ('p', 'q')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x') >>> f <Frame: x> <Index> a b c <<U1> <IndexHierarchy> 0 p 10 False 1517-01-01 0 q 2 True 1517-04-01 1 p 8 True 1517-12-31 1 q 3 False 1517-06-30 <int64> <<U1> <int64> <bool> <datetime64[D]> >>> f.via_type_clinic.to_hint() static_frame.core.frame.Frame[static_frame.core.index_hierarchy.IndexHierarchy[static_frame.core.index.Index[numpy.int64], static_frame.core.index.Index[numpy.str_]], static_frame.core.index.Index[numpy.str_], numpy.int64, numpy.bool_, numpy.datetime64]
- Frame.via_type_clinic.check(hint, *, fail_fast)
- Frame.via_type_clinic
- TypeClinic.check(hint, /, *, fail_fast=False)[source]
Given a hint (a type and/or generic alias), raise a
ClinicError
exception describing the result of the check if an error is found.- Parameters:
fail_fast – If True, return on first failure. If False, all failures are discovered and reported.
>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), index=sf.IndexHierarchy.from_product((0, 1), ('p', 'q')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x') >>> f <Frame: x> <Index> a b c <<U1> <IndexHierarchy> 0 p 10 False 1517-01-01 0 q 2 True 1517-04-01 1 p 8 True 1517-12-31 1 q 3 False 1517-06-30 <int64> <<U1> <int64> <bool> <datetime64[D]> >>> f.via_type_clinic.check(sf.Frame[sf.IndexHierarchy[sf.Index[np.int64], sf.Index[np.str_]], sf.Index[np.int64], np.int64, np.bool_, np.str_]) ClinicError('\nIn Frame[IndexHierarchy[Index[int64], Index[str_]], Index[int64], int64, bool_, str_]\n└── Expected str_, provided datetime64 invalid\nIn Frame[IndexHierarchy[Index[int64], Index[str_]], Index[int64], int64, bool_, str_]\n└── Index[int64]\n └── Expected int64, provided str_ invalid')
- Frame.via_type_clinic.warn(hint, *, fail_fast, category)
- Frame.via_type_clinic
- TypeClinic.warn(hint, /, *, fail_fast=False, category=<class 'UserWarning'>)[source]
Given a hint (a type and/or generic alias), issue a warning describing the result of the check if an error is found.
- Parameters:
fail_fast – If True, return on first failure. If False, all failures are discovered and reported.
category – The
Warning
subclass to be used for issueing the warning.
- Frame.via_type_clinic.__call__(hint, *, fail_fast)
- Frame.via_type_clinic
- TypeClinic.__call__(hint, /, *, fail_fast=False)[source]
Given a hint (a type and/or generic alias), return a
ClinicResult
object describing the result of the check.- Parameters:
fail_fast – If True, return on first failure. If False, all failures are discovered and reported.
>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), index=sf.IndexHierarchy.from_product((0, 1), ('p', 'q')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x') >>> f <Frame: x> <Index> a b c <<U1> <IndexHierarchy> 0 p 10 False 1517-01-01 0 q 2 True 1517-04-01 1 p 8 True 1517-12-31 1 q 3 False 1517-06-30 <int64> <<U1> <int64> <bool> <datetime64[D]> >>> cr = f.via_type_clinic(sf.Frame[sf.IndexHierarchy[sf.Index[np.int64], sf.Index[np.str_]], sf.Index[np.int64], np.int64, np.bool_, np.str_]) >>> cr <ClinicResult: 2 errors> >>> cr.validated False >>> cr.to_str() In Frame[IndexHierarchy[Index[int64], Index[str_]], Index[int64], int64, bool_, str_] └── Expected str_, provided datetime64 invalid In Frame[IndexHierarchy[Index[int64], Index[str_]], Index[int64], int64, bool_, str_] └── Index[int64] └── Expected int64, provided str_ invalid
- Frame.via_type_clinic.__repr__
- Frame.via_type_clinic
- TypeClinic.__repr__()[source]
Return a compact string representation of the type hint (the type and/or generic aliases necessary) to represent the object given at initialization.
>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), index=sf.IndexHierarchy.from_product((0, 1), ('p', 'q')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x') >>> f <Frame: x> <Index> a b c <<U1> <IndexHierarchy> 0 p 10 False 1517-01-01 0 q 2 True 1517-04-01 1 p 8 True 1517-12-31 1 q 3 False 1517-06-30 <int64> <<U1> <int64> <bool> <datetime64[D]> >>> f.via_type_clinic Frame[IndexHierarchy[Index[int64], Index[str_]], Index[str_], int64, bool_, datetime64]
Frame: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Assignment | Selector | Iterator | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression | Accessor Hashlib | Accessor Type Clinic | Accessor Reduce