def generate_table(self, meta, sheet, row_set):
offset, headers = headers_guess(row_set.sample)
row_set.register_processor(headers_processor(headers))
row_set.register_processor(offset_processor(offset + 1))
schema = TabularSchema({
'sheet_name': row_set.name,
'content_hash': meta.content_hash,
'sheet': sheet
})
columns = [schema.add_column(h) for h in headers]
log.info("Creating internal table: %s columns, table: %r", len(columns),
schema.table_name)
tabular = Tabular(schema)
tabular.drop()
tabular.create()
def generate_rows():
for i, row in enumerate(row_set):
record = {}
for cell, column in zip(row, columns):
record[column.name] = string_value(cell.value)
if len(record):
for column in columns:
record[column.name] = record.get(column.name, None)
yield record
log.info("Loaded %s rows.", i)
tabular.load_iter(generate_rows())
return schema
def ingest(self, meta, local_path):
with open(local_path, 'rb') as fh:
db = DBF(fh)
schema = TabularSchema({
'content_hash': meta.content_hash,
'sheet': 0
})
columns = [schema.add_column(h) for h in db.fields.keys()]
columns = {c.label: c.name for c in columns}
tabular = Tabular(schema)
tabular.drop()
tabular.create()
def generate_rows():
if db.numrec == 0:
return
text = []
for i in xrange(0, db.numrec):
for v in db.select(i).values():
if isinstance(v, str):
text.append(v)
encoding = guess_encoding(' '.join(text))
for i in xrange(0, db.numrec):
row = db.select(i)
record = {}
for k, value in row.items():
name = columns.get(k)
record[name] = string_value(value, encoding=encoding)
if len(record):
for name in columns.values():
record[name] = record.get(name, None)
yield record
log.info("Loaded %s rows.", i)
tabular.load_iter(generate_rows())
meta.tables = [schema]
document = self.create_document(meta)
self.emit(document)