def lower_unbox_df_column(context, builder, sig, args):
# FIXME: last arg should be types.DType?
pyapi = context.get_python_api(builder)
c = numba.pythonapi._UnboxContext(context, builder, pyapi)
# TODO: refcounts?
col_ind = sig.args[1].value
col_name = sig.args[0].col_names[col_ind]
series_obj = c.pyapi.object_getattr_string(args[0], col_name)
arr_obj = c.pyapi.object_getattr_string(series_obj, "values")
if isinstance(sig.args[2],
types.Const) and sig.args[2].value == 11: # FIXME: str code
native_val = unbox_str_series(string_array_type, arr_obj, c)
else:
if isinstance(
sig.args[2],
types.Const) and sig.args[2].value == 12: # FIXME: dt64 code
dtype = types.NPDatetime('ns')
else:
dtype = sig.args[2].dtype
# TODO: error handling like Numba callwrappers.py
native_val = unbox_array(types.Array(dtype=dtype, ndim=1, layout='C'),
arr_obj, c)
c.pyapi.decref(series_obj)
c.pyapi.decref(arr_obj)
return native_val.value
def unbox_series(typ, val, c):
arr_obj = c.pyapi.object_getattr_string(val, "values")
if typ.dtype == string_type:
native_val = unbox_str_series(string_array_type, arr_obj, c)
elif typ.dtype == datetime_date_type:
native_val = unbox_datetime_date_array(typ, val, c)
else:
# TODO: error handling like Numba callwrappers.py
native_val = unbox_array(types.Array(dtype=typ.dtype, ndim=1, layout='C'), arr_obj, c)
c.pyapi.decref(arr_obj)
return native_val
def unbox_series(typ, val, c):
arr_obj = c.pyapi.object_getattr_string(val, "values")
series = cgutils.create_struct_proxy(typ)(c.context, c.builder)
series.data = _unbox_series_data(typ.dtype, typ.data, arr_obj, c).value
# TODO: other indices
if typ.index == string_array_type:
index_obj = c.pyapi.object_getattr_string(val, "index")
series.index = unbox_str_series(string_array_type, index_obj, c).value
if typ.is_named:
name_obj = c.pyapi.object_getattr_string(val, "name")
series.name = numba.unicode.unbox_unicode_str(
string_type, name_obj, c).value
# TODO: handle index and name
c.pyapi.decref(arr_obj)
return NativeValue(series._getvalue())
def _unbox_series_data(dtype, data_typ, arr_obj, c):
if data_typ == string_array_type:
return unbox_str_series(string_array_type, arr_obj, c)
elif dtype == datetime_date_type:
return unbox_datetime_date_array(data_typ, arr_obj, c)
elif data_typ == list_string_array_type:
return _unbox_array_list_str(arr_obj, c)
elif data_typ == string_array_split_view_type:
# XXX dummy unboxing to avoid errors in _get_dataframe_data()
out_view = c.context.make_helper(c.builder, string_array_split_view_type)
return NativeValue(out_view._getvalue())
elif isinstance(dtype, PDCategoricalDtype):
return unbox_categorical_array(data_typ, arr_obj, c)
# TODO: error handling like Numba callwrappers.py
return unbox_array(data_typ, arr_obj, c)