def parsed_as_values(string_table):
values = []
column_names = string_table['column_names']
for row in string_table['rows']:
cell = row[column_names[0]]
v = parse(cell)
assert v is not None, f"Failed to parse `{cell}'"
values.append(v)
string_table['values'] = values
def _parse_value(cell: str, variables: dict) -> Value:
m = pattern.match(cell)
if m:
var = m.group(1)
assert var in variables, f"Invalid expect variable usages: {cell}"
cell = variables.get(var, None)
assert cell is not None
value = parse(cell)
assert value is not None, f"parse error: column is {cell}"
return value
def dataset(string_table):
ds = DataSet()
ds.column_names = string_table['column_names']
ds.rows = []
for row in string_table['rows']:
nrow = Row()
nrow.values = []
for column in ds.column_names:
value = parse(row[column])
assert value is not None, \
f'parse error: column is {column}:{row[column]}'
nrow.values.append(value)
ds.rows.append(nrow)
return ds
def parsed_as_values(string_table):
cell = string_table['text']
v = parse(cell)
assert v is not None, f"Failed to parse `{cell}'"
string_table['value'] = v