def _from_json_index(state: DataFrameState, table: dict):
if state.columns is None: # make header
state.columns = {
k: i
for i, k in enumerate(next(iter(table.values())).keys())
}
for row in table.keys():
yield csv_row(td for td in table[row].values())
else:
for row in table.keys():
yield csv_row(table[row][col] for col in state.columns)
def _from_json_split(state: DataFrameState, table: dict):
table_columns = {k: i for i, k in enumerate(table['columns'])}
if state.columns is None: # make header
state.columns = table_columns
for row in table['data']:
yield csv_row(row)
else:
idxs = [state.columns[k] for k in table_columns]
for row in table['data']:
yield csv_row(row[idx] for idx in idxs)
def _from_csv_without_index(state: DataFrameState, table: Iterator[str]):
row_str = next(table) # skip column names
table_columns = tuple(csv_unquote(s) for s in csv_split(row_str, ','))
if state.columns is None:
state.columns = table_columns
for row_str in table:
if not row_str: # skip blank line
continue
if not row_str.strip():
yield csv_quote(row_str)
else:
yield row_str
elif not all(
c1 == c2
for c1, c2 in itertools.zip_longest(state.columns, table_columns)):
idxs = [state.columns[k] for k in table_columns]
for row_str in table:
if not row_str: # skip blank line
continue
if not row_str.strip():
yield csv_quote(row_str)
else:
tr = tuple(s for s in csv_split(row_str, ","))
yield csv_row(tr[i] for i in idxs)
else:
for row_str in table:
if not row_str: # skip blank line
continue
if not row_str.strip():
yield csv_quote(row_str)
else:
yield row_str
def _from_json_columns(state: DataFrameState, table: dict):
if state.columns is None: # make header
state.columns = {k: i for i, k in enumerate(table.keys())}
for row in next(iter(table.values())):
yield csv_row(table[col][row] for col in state.columns)
def _from_json_values(_: DataFrameState, table: list):
for tr in table:
yield csv_row(tr)
def _from_json_records(state: DataFrameState, table: list):
if state.columns is None: # make header
state.columns = {k: i for i, k in enumerate(table[0].keys())}
for tr in table:
yield csv_row(tr[c] for c in state.columns)