def apply(self):
new_block = self.block.copy()
new_block.clear()
vars_to_remove = []
for inst in self.block.body:
if inst in self.consts:
consts = self.consts[inst]
for key, value in consts.items():
if key not in dict(inst.value.kws):
continue
# collecting data from current variable
current_var = [
var for name, var in inst.value.kws if name == key
][0]
loc = current_var.loc
seq, _ = guard(find_build_sequence, self.func_ir,
current_var)
if not seq:
continue
if isinstance(value, list):
items = seq
elif isinstance(value, dict):
items = sum(map(list, seq), [])
else:
continue
# create tuple variable
stmt = make_assign(ir.Expr.build_tuple(items=items,
loc=loc),
new_block.scope,
self.func_ir,
loc,
name=f"{key}_tuple")
new_block.append(stmt)
# replace variable in call
inst.value.kws = [(kw[0],
stmt.target) if kw[0] == key else kw
for kw in inst.value.kws]
# save old variable for removing
vars_to_remove.append(current_var)
new_block.append(inst)
# remove old variables
for var in vars_to_remove:
# unsused variables are removed after new block is created b/c
# remove_unused_recursively should see all del statements of variables
remove_unused_recursively(var, new_block, self.func_ir)
return new_block
def apply(self):
init_df_stmt = import_function(init_dataframe, self._block, self._func_ir)
for stmt in self._calls_to_rewrite:
args = get_call_parameters(call=stmt.value, arg_names=self._df_arg_list)
old_data = args['data']
args['data'], args['columns'] = self._extract_dict_args(args, self._func_ir)
self._replace_call(stmt, init_df_stmt.target, args, self._block, self._func_ir)
remove_unused_recursively(old_data, self._block, self._func_ir)
return self._block
def apply(self):
for stmt in self._calls_to_rewrite:
args = get_call_parameters(call=stmt.value,
arg_names=self._df_arg_list)
old_data = args['data']
args['data'], args['columns'] = self._extract_dict_args(
args, self._func_ir)
args_len = len(args['data'])
func_name = f'init_dataframe_{args_len}'
# injected_module = modules[pd_dataframe_ext_module.__name__]
init_df = getattr(pd_dataframe_ext_module, func_name, None)
if init_df is None:
init_df_text = gen_init_dataframe_text(func_name, args_len)
init_df = gen_init_dataframe_func(
func_name, init_df_text, {
'numba': numba,
'cgutils': cgutils,
'signature': signature,
'types': types,
'get_structure_maps': get_structure_maps,
'intrinsic': intrinsic,
'DataFrameType': DataFrameType,
'ColumnLoc': ColumnLoc,
'string_type': string_type,
'intrinsic': intrinsic,
'fix_df_array': fix_df_array,
'fix_df_index': fix_df_index,
'init_empty_index': init_empty_index,
'EmptyIndexType': EmptyIndexType
})
setattr(pd_dataframe_ext_module, func_name, init_df)
init_df.__module__ = pd_dataframe_ext_module.__name__
init_df._defn.__module__ = pd_dataframe_ext_module.__name__
init_df_stmt = import_function(init_df, self._block, self._func_ir)
self._replace_call(stmt, init_df_stmt.target, args, self._block,
self._func_ir)
remove_unused_recursively(old_data, self._block, self._func_ir)
self._pipeline.typingctx.refresh()
return self._block