def box_dataframe(typ, val, c):
context = c.context
builder = c.builder
col_names = typ.columns
arr_typs = typ.data
dataframe = cgutils.create_struct_proxy(typ)(context, builder, value=val)
pyapi = c.pyapi
# gil_state = pyapi.gil_ensure() # acquire GIL
mod_name = context.insert_const_string(c.builder.module, "pandas")
class_obj = pyapi.import_module_noblock(mod_name)
df_dict = pyapi.dict_new()
arrays_list_objs = {}
for cname, arr_typ in zip(col_names, arr_typs):
# df['cname'] = boxed_arr
# TODO: datetime.date, DatetimeIndex?
name_str = context.insert_const_string(c.builder.module, cname)
cname_obj = pyapi.string_from_string(name_str)
col_loc = typ.column_loc[cname]
type_id, col_id = col_loc.type_id, col_loc.col_id
# dataframe.data looks like a tuple(list(array))
# e.g. ([array(int64, 1d, C), array(int64, 1d, C)], [array(float64, 1d, C)])
arrays_list_obj = arrays_list_objs.get(type_id)
if arrays_list_obj is None:
list_typ = types.List(arr_typ)
# extracting list from the tuple
list_val = builder.extract_value(dataframe.data, type_id)
# getting array from the list to box it then
arrays_list_obj = box_list(list_typ, list_val, c)
arrays_list_objs[type_id] = arrays_list_obj
# PyList_GetItem returns borrowed reference
arr_obj = pyapi.list_getitem(arrays_list_obj, col_id)
pyapi.dict_setitem(df_dict, cname_obj, arr_obj)
pyapi.decref(cname_obj)
df_obj = pyapi.call_method(class_obj, "DataFrame", (df_dict,))
pyapi.decref(df_dict)
# set df.index if necessary
if typ.index != types.none:
index_obj = _box_index_data(typ.index, dataframe.index, c)
pyapi.object_setattr_string(df_obj, 'index', index_obj)
pyapi.decref(index_obj)
for arrays_list_obj in arrays_list_objs.values():
pyapi.decref(arrays_list_obj)
pyapi.decref(class_obj)
# pyapi.gil_release(gil_state) # release GIL
return df_obj
def box_dataframe(typ, val, c):
context = c.context
builder = c.builder
n_cols = len(typ.columns)
col_names = typ.columns
arr_typs = typ.data
dtypes = [a.dtype for a in arr_typs] # TODO: check Categorical
dataframe = cgutils.create_struct_proxy(typ)(context, builder, value=val)
col_arrs = [builder.extract_value(dataframe.data, i) for i in range(n_cols)]
# df unboxed from Python
has_parent = cgutils.is_not_null(builder, dataframe.parent)
pyapi = c.pyapi
# gil_state = pyapi.gil_ensure() # acquire GIL
mod_name = context.insert_const_string(c.builder.module, "pandas")
class_obj = pyapi.import_module_noblock(mod_name)
df_dict = pyapi.dict_new()
for i, cname, arr, arr_typ, dtype in zip(range(n_cols), col_names, col_arrs, arr_typs, dtypes):
# df['cname'] = boxed_arr
# TODO: datetime.date, DatetimeIndex?
name_str = context.insert_const_string(c.builder.module, cname)
cname_obj = pyapi.string_from_string(name_str)
if dtype == string_type:
arr_obj = box_str_arr(arr_typ, arr, c)
elif isinstance(arr_typ, Categorical):
arr_obj = box_Categorical(arr_typ, arr, c)
# context.nrt.incref(builder, arr_typ, arr)
elif dtype == types.List(string_type):
arr_obj = box_list(list_string_array_type, arr, c)
# context.nrt.incref(builder, arr_typ, arr) # TODO required?
# pyapi.print_object(arr_obj)
else:
arr_obj = box_array(arr_typ, arr, c)
# TODO: is incref required?
# context.nrt.incref(builder, arr_typ, arr)
pyapi.dict_setitem(df_dict, cname_obj, arr_obj)
pyapi.decref(arr_obj)
pyapi.decref(cname_obj)
df_obj = pyapi.call_method(class_obj, "DataFrame", (df_dict,))
pyapi.decref(df_dict)
# set df.index if necessary
if typ.index != types.none:
arr_obj = _box_series_data(typ.index.dtype, typ.index, dataframe.index, c)
pyapi.object_setattr_string(df_obj, 'index', arr_obj)
pyapi.decref(arr_obj)
pyapi.decref(class_obj)
# pyapi.gil_release(gil_state) # release GIL
return df_obj
def _box_series_data(dtype, data_typ, val, c):
if isinstance(dtype, types.BaseTuple):
np_dtype = np.dtype(','.join(str(t) for t in dtype.types), align=True)
dtype = numba.np.numpy_support.from_dtype(np_dtype)
if dtype == string_type:
arr = box_str_arr(string_array_type, val, c)
elif isinstance(dtype, CategoricalDtypeType):
arr = box_Categorical(data_typ, val, c)
elif dtype == types.List(string_type):
arr = box_list(list_string_array_type, val, c)
else:
arr = box_array(data_typ, val, c)
if isinstance(dtype, types.Record):
o_str = c.context.insert_const_string(c.builder.module, "O")
o_str = c.pyapi.string_from_string(o_str)
arr = c.pyapi.call_method(arr, "astype", (o_str, ))
return arr
