sheet_json_schema = OrderedDict()
data = next(iter(sheet.get('data', [])), {})
row_data = data.get('rowData', [])
- # spreadsheet is an OrderedDict, with orderd sheets and rows in the repsonse
-
- headers = row_data[0].get('values', [])
- first_values = row_data[1].get('values', [])
- # LOGGER.info('first_values = {}'.format(json.dumps(first_values, indent=2, sort_keys=True)))
-
- sheet_json_schema = {
- 'type': 'object',
- 'additionalProperties': False,
- 'properties': {
- '__sdc_spreadsheet_id': {
- 'type': ['null', 'string']
- },
- '__sdc_sheet_id': {
- 'type': ['null', 'integer']
- },
- '__sdc_row': {
- 'type': ['null', 'integer']
+ if row_data == []:
+ # Empty sheet, SKIP
+ LOGGER.info('SKIPPING Empty Sheet: {}'.format(sheet_title))
+ return None, None
+ else:
+ # spreadsheet is an OrderedDict, with orderd sheets and rows in the repsonse
+ headers = row_data[0].get('values', [])
+ first_values = row_data[1].get('values', [])
+ # LOGGER.info('first_values = {}'.format(json.dumps(first_values, indent=2, sort_keys=True)))
+
+ sheet_json_schema = {
+ 'type': 'object',
+ 'additionalProperties': False,
+ 'properties': {
+ '__sdc_spreadsheet_id': {
+ 'type': ['null', 'string']
+ },
+ '__sdc_sheet_id': {
+ 'type': ['null', 'integer']
+ },
+ '__sdc_row': {
+ 'type': ['null', 'integer']
+ }
}
}
- }
-
- header_list = [] # used for checking uniqueness
- columns = []
- prior_header = None
- i = 0
- skipped = 0
- # Read column headers until end or 2 consecutive skipped headers
- for header in headers:
- # LOGGER.info('header = {}'.format(json.dumps(header, indent=2, sort_keys=True)))
- column_index = i + 1
- column_letter = colnum_string(column_index)
- header_value = header.get('formattedValue')
- if header_value: # NOT skipped
- column_is_skipped = False
- skipped = 0
- column_name = '{}'.format(header_value)
- if column_name in header_list:
- raise Exception('DUPLICATE HEADER ERROR: SHEET: {}, COL: {}, CELL: {}1'.format(
- sheet_title, column_name, column_letter))
- header_list.append(column_name)
-
- first_value = None
- try:
- first_value = first_values[i]
- except IndexError as err:
- raise Exception('NO VALUE IN 2ND ROW FOR HEADER ERROR. SHEET: {}, COL: {}, CELL: {}2. {}'.format(
- sheet_title, column_name, column_letter, err))
-
- column_effective_value = first_value.get('effectiveValue', {})
-
- col_val = None
- if column_effective_value == {}:
- column_effective_value_type = 'stringValue'
- LOGGER.info('WARNING: NO VALUE IN 2ND ROW FOR HEADER. SHEET: {}, COL: {}, CELL: {}2.'.format(
- sheet_title, column_name, column_letter))
- LOGGER.info(' Setting column datatype to STRING')
- else:
- for key, val in column_effective_value.items():
- if key in ('numberValue', 'stringValue', 'boolValue'):
- column_effective_value_type = key
- col_val = str(val)
- elif key in ('errorType', 'formulaType'):
- col_val = str(val)
- raise Exception('DATA TYPE ERROR 2ND ROW VALUE: SHEET: {}, COL: {}, CELL: {}2, TYPE: {}, VALUE: {}'.format(
- sheet_title, column_name, column_letter, key, col_val))
-
- column_number_format = first_values[i].get('effectiveFormat', {}).get(
- 'numberFormat', {})
- column_number_format_type = column_number_format.get('type')
-
- # Determine datatype for sheet_json_schema
- #
- # column_effective_value_type = numberValue, stringValue, boolValue;
- # INVALID: errorType, formulaType
- # https://developers.google.com/sheets/api/reference/rest/v4/spreadsheets/other#ExtendedValue
- #
- # column_number_format_type = UNEPECIFIED, TEXT, NUMBER, PERCENT, CURRENCY, DATE,
- # TIME, DATE_TIME, SCIENTIFIC
- # https://developers.google.com/sheets/api/reference/rest/v4/spreadsheets/cells#NumberFormatType
- #
- column_format = None # Default
- if column_effective_value == {}:
- col_properties = {'type': ['null', 'string']}
- column_gs_type = 'stringValue'
- LOGGER.info('WARNING: 2ND ROW VALUE IS BLANK: SHEET: {}, COL: {}, CELL: {}2'.format(
+
+ header_list = [] # used for checking uniqueness
+ columns = []
+ prior_header = None
+ i = 0
+ skipped = 0
+ # Read column headers until end or 2 consecutive skipped headers
+ for header in headers:
+ # LOGGER.info('header = {}'.format(json.dumps(header, indent=2, sort_keys=True)))
+ column_index = i + 1
+ column_letter = colnum_string(column_index)
+ header_value = header.get('formattedValue')
+ if header_value: # NOT skipped
+ column_is_skipped = False
+ skipped = 0
+ column_name = '{}'.format(header_value)
+ if column_name in header_list:
+ raise Exception('DUPLICATE HEADER ERROR: SHEET: {}, COL: {}, CELL: {}1'.format(
sheet_title, column_name, column_letter))
- LOGGER.info(' Setting column datatype to STRING')
- elif column_effective_value_type == 'stringValue':
- col_properties = {'type': ['null', 'string']}
- column_gs_type = 'stringValue'
- elif column_effective_value_type == 'boolValue':
- col_properties = {'type': ['null', 'boolean', 'string']}
- column_gs_type = 'boolValue'
- elif column_effective_value_type == 'numberValue':
- if column_number_format_type == 'DATE_TIME':
- col_properties = {
- 'type': ['null', 'string'],
- 'format': 'date-time'
- }
- column_gs_type = 'numberType.DATE_TIME'
- elif column_number_format_type == 'DATE':
- col_properties = {
- 'type': ['null', 'string'],
- 'format': 'date'
- }
- column_gs_type = 'numberType.DATE'
- elif column_number_format_type == 'TIME':
- col_properties = {
- 'type': ['null', 'string'],
- 'format': 'time'
- }
- column_gs_type = 'numberType.TIME'
- elif column_number_format_type == 'TEXT':
+ header_list.append(column_name)
+
+ first_value = None
+ try:
+ first_value = first_values[i]
+ except IndexError as err:
+ raise Exception('NO VALUE IN 2ND ROW FOR HEADER ERROR. SHEET: {}, COL: {}, CELL: {}2. {}'.format(
+ sheet_title, column_name, column_letter, err))
+
+ column_effective_value = first_value.get('effectiveValue', {})
+
+ col_val = None
+ if column_effective_value == {}:
+ column_effective_value_type = 'stringValue'
+ LOGGER.info('WARNING: NO VALUE IN 2ND ROW FOR HEADER. SHEET: {}, COL: {}, CELL: {}2.'.format(
+ sheet_title, column_name, column_letter))
+ LOGGER.info(' Setting column datatype to STRING')
+ else:
+ for key, val in column_effective_value.items():
+ if key in ('numberValue', 'stringValue', 'boolValue'):
+ column_effective_value_type = key
+ col_val = str(val)
+ elif key in ('errorType', 'formulaType'):
+ col_val = str(val)
+ raise Exception('DATA TYPE ERROR 2ND ROW VALUE: SHEET: {}, COL: {}, CELL: {}2, TYPE: {}, VALUE: {}'.format(
+ sheet_title, column_name, column_letter, key, col_val))
+
+ column_number_format = first_values[i].get('effectiveFormat', {}).get(
+ 'numberFormat', {})
+ column_number_format_type = column_number_format.get('type')
+
+ # Determine datatype for sheet_json_schema
+ #
+ # column_effective_value_type = numberValue, stringValue, boolValue;
+ # INVALID: errorType, formulaType
+ # https://developers.google.com/sheets/api/reference/rest/v4/spreadsheets/other#ExtendedValue
+ #
+ # column_number_format_type = UNEPECIFIED, TEXT, NUMBER, PERCENT, CURRENCY, DATE,
+ # TIME, DATE_TIME, SCIENTIFIC
+ # https://developers.google.com/sheets/api/reference/rest/v4/spreadsheets/cells#NumberFormatType
+ #
+ column_format = None # Default
+ if column_effective_value == {}:
+ col_properties = {'type': ['null', 'string']}
+ column_gs_type = 'stringValue'
+ LOGGER.info('WARNING: 2ND ROW VALUE IS BLANK: SHEET: {}, COL: {}, CELL: {}2'.format(
+ sheet_title, column_name, column_letter))
+ LOGGER.info(' Setting column datatype to STRING')
+ elif column_effective_value_type == 'stringValue':
col_properties = {'type': ['null', 'string']}
column_gs_type = 'stringValue'
+ elif column_effective_value_type == 'boolValue':
+ col_properties = {'type': ['null', 'boolean', 'string']}
+ column_gs_type = 'boolValue'
+ elif column_effective_value_type == 'numberValue':
+ if column_number_format_type == 'DATE_TIME':
+ col_properties = {
+ 'type': ['null', 'string'],
+ 'format': 'date-time'
+ }
+ column_gs_type = 'numberType.DATE_TIME'
+ elif column_number_format_type == 'DATE':
+ col_properties = {
+ 'type': ['null', 'string'],
+ 'format': 'date'
+ }
+ column_gs_type = 'numberType.DATE'
+ elif column_number_format_type == 'TIME':
+ col_properties = {
+ 'type': ['null', 'string'],
+ 'format': 'time'
+ }
+ column_gs_type = 'numberType.TIME'
+ elif column_number_format_type == 'TEXT':
+ col_properties = {'type': ['null', 'string']}
+ column_gs_type = 'stringValue'
+ else:
+ # Interesting - order in the anyOf makes a difference.
+ # Number w/ multipleOf must be listed last, otherwise errors occur.
+ col_properties = {
+ 'anyOf': [
+ {
+ 'type': 'null'
+ },
+ {
+ 'type': 'number',
+ 'multipleOf': 1e-15
+ },
+ {
+ 'type': 'string'
+ }
+ ]
+ }
+ column_gs_type = 'numberType'
+ # Catch-all to deal with other types and set to string
+ # column_effective_value_type: formulaValue, errorValue, or other
else:
- # Interesting - order in the anyOf makes a difference.
- # Number w/ multipleOf must be listed last, otherwise errors occur.
- col_properties = {
- 'anyOf': [
- {
- 'type': 'string'
- },
- {
- 'type': 'null'
- },
- {
- 'type': 'number',
- 'multipleOf': 1e-15
- }
- ]
- }
- column_gs_type = 'numberType'
- # Catch-all to deal with other types and set to string
- # column_effective_value_type: formulaValue, errorValue, or other
- else:
+ col_properties = {'type': ['null', 'string']}
+ column_gs_type = 'unsupportedValue'
+ LOGGER.info('WARNING: UNSUPPORTED 2ND ROW VALUE: SHEET: {}, COL: {}, CELL: {}2, TYPE: {}, VALUE: {}'.format(
+ sheet_title, column_name, column_letter, column_effective_value_type, col_val))
+ LOGGER.info('Converting to string.')
+ else: # skipped
+ column_is_skipped = True
+ skipped = skipped + 1
+ column_index_str = str(column_index).zfill(2)
+ column_name = '__sdc_skip_col_{}'.format(column_index_str)
col_properties = {'type': ['null', 'string']}
- column_gs_type = 'unsupportedValue'
- LOGGER.info('WARNING: UNSUPPORTED 2ND ROW VALUE: SHEET: {}, COL: {}, CELL: {}2, TYPE: {}, VALUE: {}'.format(
- sheet_title, column_name, column_letter, column_effective_value_type, col_val))
- LOGGER.info('Converting to string.')
- else: # skipped
- column_is_skipped = True
- skipped = skipped + 1
- column_index_str = str(column_index).zfill(2)
- column_name = '__sdc_skip_col_{}'.format(column_index_str)
- col_properties = {'type': ['null', 'string']}
- column_gs_type = 'stringValue'
- LOGGER.info('WARNING: SKIPPED COLUMN; NO COLUMN HEADER. SHEET: {}, COL: {}, CELL: {}1'.format(
- sheet_title, column_name, column_letter))
- LOGGER.info(' This column will be skipped during data loading.')
-
- if skipped >= 2:
- # skipped = 2 consecutive skipped headers
- # Remove prior_header column_name
- sheet_json_schema['properties'].pop(prior_header, None)
- LOGGER.info('TWO CONSECUTIVE SKIPPED COLUMNS. STOPPING SCAN AT: SHEET: {}, COL: {}, CELL {}1'.format(
- sheet_title, column_name, column_letter))
- break
-
- else:
- column = {}
- column = {
- 'columnIndex': column_index,
- 'columnLetter': column_letter,
- 'columnName': column_name,
- 'columnType': column_gs_type,
- 'columnSkipped': column_is_skipped
- }
- columns.append(column)
+ column_gs_type = 'stringValue'
+ LOGGER.info('WARNING: SKIPPED COLUMN; NO COLUMN HEADER. SHEET: {}, COL: {}, CELL: {}1'.format(
+ sheet_title, column_name, column_letter))
+ LOGGER.info(' This column will be skipped during data loading.')
- sheet_json_schema['properties'][column_name] = col_properties
+ if skipped >= 2:
+ # skipped = 2 consecutive skipped headers
+ # Remove prior_header column_name
+ sheet_json_schema['properties'].pop(prior_header, None)
+ LOGGER.info('TWO CONSECUTIVE SKIPPED COLUMNS. STOPPING SCAN AT: SHEET: {}, COL: {}, CELL {}1'.format(
+ sheet_title, column_name, column_letter))
+ break
- prior_header = column_name
- i = i + 1
+ else:
+ column = {}
+ column = {
+ 'columnIndex': column_index,
+ 'columnLetter': column_letter,
+ 'columnName': column_name,
+ 'columnType': column_gs_type,
+ 'columnSkipped': column_is_skipped
+ }
+ columns.append(column)
- return sheet_json_schema, columns
+ sheet_json_schema['properties'][column_name] = col_properties
+
+ prior_header = column_name
+ i = i + 1
+
+ return sheet_json_schema, columns
# Get Header Row and 1st data row (Rows 1 & 2) from a Sheet on Spreadsheet w/ sheet_metadata query
for sheet in sheets:
# GET sheet_json_schema for each worksheet (from function above)
sheet_json_schema, columns = get_sheet_metadata(sheet, spreadsheet_id, client)
- # LOGGER.info('columns = {}'.format(columns))
-
- sheet_title = sheet.get('properties', {}).get('title')
- schemas[sheet_title] = sheet_json_schema
- sheet_mdata = metadata.new()
- sheet_mdata = metadata.get_standard_metadata(
- schema=sheet_json_schema,
- key_properties=['__sdc_row'],
- valid_replication_keys=None,
- replication_method='FULL_TABLE'
- )
- field_metadata[sheet_title] = sheet_mdata
+
+ # SKIP empty sheets (where sheet_json_schema and columns are None)
+ if sheet_json_schema and columns:
+ sheet_title = sheet.get('properties', {}).get('title')
+ schemas[sheet_title] = sheet_json_schema
+ sheet_mdata = metadata.new()
+ sheet_mdata = metadata.get_standard_metadata(
+ schema=sheet_json_schema,
+ key_properties=['__sdc_row'],
+ valid_replication_keys=None,
+ replication_method='FULL_TABLE'
+ )
+ field_metadata[sheet_title] = sheet_mdata
return schemas, field_metadata
sheet_schema, columns = get_sheet_metadata(sheet, spreadsheet_id, client)
# LOGGER.info('sheet_schema: {}'.format(sheet_schema))
- # Transform sheet_metadata
- sheet_metadata_tf = transform_sheet_metadata(spreadsheet_id, sheet, columns)
- # LOGGER.info('sheet_metadata_tf = {}'.format(sheet_metadata_tf))
- sheet_metadata.append(sheet_metadata_tf)
-
- # SHEET_DATA
- # Should this worksheet tab be synced?
- if sheet_title in selected_streams:
- LOGGER.info('STARTED Syncing Sheet {}'.format(sheet_title))
- update_currently_syncing(state, sheet_title)
- selected_fields = get_selected_fields(catalog, sheet_title)
- LOGGER.info('Stream: {}, selected_fields: {}'.format(sheet_title, selected_fields))
- write_schema(catalog, sheet_title)
-
- # Emit a Singer ACTIVATE_VERSION message before initial sync (but not subsequent syncs)
- # everytime after each sheet sync is complete.
- # This forces hard deletes on the data downstream if fewer records are sent.
- # https://github.com/singer-io/singer-python/blob/master/singer/messages.py#L137
- last_integer = int(get_bookmark(state, sheet_title, 0))
- activate_version = int(time.time() * 1000)
- activate_version_message = singer.ActivateVersionMessage(
- stream=sheet_title,
- version=activate_version)
- if last_integer == 0:
- # initial load, send activate_version before AND after data sync
- singer.write_message(activate_version_message)
- LOGGER.info('INITIAL SYNC, Stream: {}, Activate Version: {}'.format(sheet_title, activate_version))
-
- # Determine max range of columns and rows for "paging" through the data
- sheet_last_col_index = 1
- sheet_last_col_letter = 'A'
- for col in columns:
- col_index = col.get('columnIndex')
- col_letter = col.get('columnLetter')
- if col_index > sheet_last_col_index:
- sheet_last_col_index = col_index
- sheet_last_col_letter = col_letter
- sheet_max_row = sheet.get('properties').get('gridProperties', {}).get('rowCount')
-
- # Initialize paging for 1st batch
- is_last_row = False
- batch_rows = 200
- from_row = 2
- if sheet_max_row < batch_rows:
- to_row = sheet_max_row
- else:
- to_row = batch_rows
-
- # Loop thru batches (each having 200 rows of data)
- while not is_last_row and from_row < sheet_max_row and to_row <= sheet_max_row:
- range_rows = 'A{}:{}{}'.format(from_row, sheet_last_col_letter, to_row)
-
- # GET sheet_data for a worksheet tab
- sheet_data, time_extracted = get_data(
- stream_name=sheet_title,
- endpoint_config=sheets_loaded_config,
- client=client,
- spreadsheet_id=spreadsheet_id,
- range_rows=range_rows)
- # Data is returned as a list of arrays, an array of values for each row
- sheet_data_rows = sheet_data.get('values')
-
- # Transform batch of rows to JSON with keys for each column
- sheet_data_tf, row_num = transform_sheet_data(
- spreadsheet_id=spreadsheet_id,
- sheet_id=sheet_id,
- sheet_title=sheet_title,
- from_row=from_row,
- columns=columns,
- sheet_data_rows=sheet_data_rows)
- if row_num < to_row:
- is_last_row = True
-
- # Process records, send batch of records to target
- record_count = process_records(
- catalog=catalog,
- stream_name=sheet_title,
- records=sheet_data_tf,
- time_extracted=ss_time_extracted,
- version=activate_version)
- LOGGER.info('Sheet: {}, records processed: {}'.format(
- sheet_title, record_count))
-
- # Update paging from/to_row for next batch
- from_row = to_row + 1
- if to_row + batch_rows > sheet_max_row:
+ # SKIP empty sheets (where sheet_schema and columns are None)
+ if not sheet_schema or not columns:
+ LOGGER.info('SKIPPING Empty Sheet: {}'.format(sheet_title))
+ else:
+ # Transform sheet_metadata
+ sheet_metadata_tf = transform_sheet_metadata(spreadsheet_id, sheet, columns)
+ # LOGGER.info('sheet_metadata_tf = {}'.format(sheet_metadata_tf))
+ sheet_metadata.append(sheet_metadata_tf)
+
+ # SHEET_DATA
+ # Should this worksheet tab be synced?
+ if sheet_title in selected_streams:
+ LOGGER.info('STARTED Syncing Sheet {}'.format(sheet_title))
+ update_currently_syncing(state, sheet_title)
+ selected_fields = get_selected_fields(catalog, sheet_title)
+ LOGGER.info('Stream: {}, selected_fields: {}'.format(sheet_title, selected_fields))
+ write_schema(catalog, sheet_title)
+
+ # Emit a Singer ACTIVATE_VERSION message before initial sync (but not subsequent syncs)
+ # everytime after each sheet sync is complete.
+ # This forces hard deletes on the data downstream if fewer records are sent.
+ # https://github.com/singer-io/singer-python/blob/master/singer/messages.py#L137
+ last_integer = int(get_bookmark(state, sheet_title, 0))
+ activate_version = int(time.time() * 1000)
+ activate_version_message = singer.ActivateVersionMessage(
+ stream=sheet_title,
+ version=activate_version)
+ if last_integer == 0:
+ # initial load, send activate_version before AND after data sync
+ singer.write_message(activate_version_message)
+ LOGGER.info('INITIAL SYNC, Stream: {}, Activate Version: {}'.format(sheet_title, activate_version))
+
+ # Determine max range of columns and rows for "paging" through the data
+ sheet_last_col_index = 1
+ sheet_last_col_letter = 'A'
+ for col in columns:
+ col_index = col.get('columnIndex')
+ col_letter = col.get('columnLetter')
+ if col_index > sheet_last_col_index:
+ sheet_last_col_index = col_index
+ sheet_last_col_letter = col_letter
+ sheet_max_row = sheet.get('properties').get('gridProperties', {}).get('rowCount')
+
+ # Initialize paging for 1st batch
+ is_last_row = False
+ batch_rows = 200
+ from_row = 2
+ if sheet_max_row < batch_rows:
to_row = sheet_max_row
else:
- to_row = to_row + batch_rows
-
- # End of Stream: Send Activate Version and update State
- singer.write_message(activate_version_message)
- write_bookmark(state, sheet_title, activate_version)
- LOGGER.info('COMPLETE SYNC, Stream: {}, Activate Version: {}'.format(sheet_title, activate_version))
- LOGGER.info('FINISHED Syncing Sheet {}, Total Rows: {}'.format(
- sheet_title, row_num - 2)) # subtract 1 for header row
- update_currently_syncing(state, None)
-
- # SHEETS_LOADED
- # Add sheet to sheets_loaded
- sheet_loaded = {}
- sheet_loaded['spreadsheetId'] = spreadsheet_id
- sheet_loaded['sheetId'] = sheet_id
- sheet_loaded['title'] = sheet_title
- sheet_loaded['loadDate'] = strftime(utils.now())
- sheet_loaded['lastRowNumber'] = row_num
- sheets_loaded.append(sheet_loaded)
+ to_row = batch_rows
+
+ # Loop thru batches (each having 200 rows of data)
+ while not is_last_row and from_row < sheet_max_row and to_row <= sheet_max_row:
+ range_rows = 'A{}:{}{}'.format(from_row, sheet_last_col_letter, to_row)
+
+ # GET sheet_data for a worksheet tab
+ sheet_data, time_extracted = get_data(
+ stream_name=sheet_title,
+ endpoint_config=sheets_loaded_config,
+ client=client,
+ spreadsheet_id=spreadsheet_id,
+ range_rows=range_rows)
+ # Data is returned as a list of arrays, an array of values for each row
+ sheet_data_rows = sheet_data.get('values')
+
+ # Transform batch of rows to JSON with keys for each column
+ sheet_data_tf, row_num = transform_sheet_data(
+ spreadsheet_id=spreadsheet_id,
+ sheet_id=sheet_id,
+ sheet_title=sheet_title,
+ from_row=from_row,
+ columns=columns,
+ sheet_data_rows=sheet_data_rows)
+ if row_num < to_row:
+ is_last_row = True
+
+ # Process records, send batch of records to target
+ record_count = process_records(
+ catalog=catalog,
+ stream_name=sheet_title,
+ records=sheet_data_tf,
+ time_extracted=ss_time_extracted,
+ version=activate_version)
+ LOGGER.info('Sheet: {}, records processed: {}'.format(
+ sheet_title, record_count))
+
+ # Update paging from/to_row for next batch
+ from_row = to_row + 1
+ if to_row + batch_rows > sheet_max_row:
+ to_row = sheet_max_row
+ else:
+ to_row = to_row + batch_rows
+
+ # End of Stream: Send Activate Version and update State
+ singer.write_message(activate_version_message)
+ write_bookmark(state, sheet_title, activate_version)
+ LOGGER.info('COMPLETE SYNC, Stream: {}, Activate Version: {}'.format(sheet_title, activate_version))
+ LOGGER.info('FINISHED Syncing Sheet {}, Total Rows: {}'.format(
+ sheet_title, row_num - 2)) # subtract 1 for header row
+ update_currently_syncing(state, None)
+
+ # SHEETS_LOADED
+ # Add sheet to sheets_loaded
+ sheet_loaded = {}
+ sheet_loaded['spreadsheetId'] = spreadsheet_id
+ sheet_loaded['sheetId'] = sheet_id
+ sheet_loaded['title'] = sheet_title
+ sheet_loaded['loadDate'] = strftime(utils.now())
+ sheet_loaded['lastRowNumber'] = row_num
+ sheets_loaded.append(sheet_loaded)
stream_name = 'sheet_metadata'
# Sync sheet_metadata if selected
projects / github / fretlink / tap-google-sheets.git / commitdiff
