def unbox_dataframe(typ, val, c):
"""unbox dataframe to an empty DataFrame struct
columns will be extracted later if necessary.
"""
n_cols = len(typ.columns)
column_strs = [
numba.unicode.make_string_from_constant(c.context, c.builder,
string_type, a)
for a in typ.columns
]
# create dataframe struct and store values
dataframe = cgutils.create_struct_proxy(typ)(c.context, c.builder)
column_tup = c.context.make_tuple(c.builder,
types.UniTuple(string_type, n_cols),
column_strs)
zero = c.context.get_constant(types.int8, 0)
unboxed_tup = c.context.make_tuple(
c.builder, types.UniTuple(types.int8, n_cols + 1),
[zero] * (n_cols + 1))
# TODO: support unboxing index
if typ.index == types.none:
dataframe.index = c.context.get_constant(types.none, None)
dataframe.columns = column_tup
dataframe.unboxed = unboxed_tup
dataframe.parent = val
# increase refcount of stored values
if c.context.enable_nrt:
# TODO: other objects?
for var in column_strs:
c.context.nrt.incref(c.builder, string_type, var)
return NativeValue(dataframe._getvalue())
def unbox_dataframe(typ, val, c):
"""unbox dataframe to an empty DataFrame struct
columns will be extracted later if necessary.
"""
n_cols = len(typ.columns)
column_strs = [
numba.unicode.make_string_from_constant(c.context, c.builder,
string_type, a)
for a in typ.columns
]
# create dataframe struct and store values
dataframe = cgutils.create_struct_proxy(typ)(c.context, c.builder)
column_tup = c.context.make_tuple(c.builder,
types.UniTuple(string_type, n_cols),
column_strs)
# this unboxes all DF columns so that no column unboxing occurs later
for col_ind in range(n_cols):
series_obj = c.pyapi.object_getattr_string(val, typ.columns[col_ind])
arr_obj = c.pyapi.object_getattr_string(series_obj, "values")
ty_series = typ.data[col_ind]
if isinstance(ty_series, types.Array):
native_val = unbox_array(typ.data[col_ind], arr_obj, c)
elif ty_series == string_array_type:
native_val = unbox_str_series(string_array_type, series_obj, c)
dataframe.data = c.builder.insert_value(dataframe.data,
native_val.value, col_ind)
# TODO: support unboxing index
if typ.index == types.none:
dataframe.index = c.context.get_constant(types.none, None)
if typ.index == string_array_type:
index_obj = c.pyapi.object_getattr_string(val, "index")
dataframe.index = unbox_str_series(string_array_type, index_obj,
c).value
if isinstance(typ.index, types.Array):
index_obj = c.pyapi.object_getattr_string(val, "index")
index_data = c.pyapi.object_getattr_string(index_obj, "_data")
dataframe.index = unbox_array(typ.index, index_data, c).value
dataframe.columns = column_tup
dataframe.parent = val
# increase refcount of stored values
if c.context.enable_nrt:
# TODO: other objects?
for var in column_strs:
c.context.nrt.incref(c.builder, string_type, var)
return NativeValue(dataframe._getvalue())