tap_google_sheets/schema.py

   1 import os
   2 import json
   3 from collections import OrderedDict
   4 import singer
   5 from singer import metadata
   6 from tap_google_sheets.streams import STREAMS
   7
   8 LOGGER = singer.get_logger()
   9
  10 # Reference:
  11 # https://github.com/singer-io/getting-started/blob/master/docs/DISCOVERY_MODE.md#Metadata
  12
  13 # Convert column index to column letter
  14 def colnum_string(num):
  15     string = ""
  16     while num > 0:
  17         num, remainder = divmod(num - 1, 26)
  18         string = chr(65 + remainder) + string
  19     return string
  20
  21
  22 # Create sheet_metadata_json with columns from sheet
  23 def get_sheet_schema_columns(sheet):
  24     sheet_title = sheet.get('properties', {}).get('title')
  25     sheet_json_schema = OrderedDict()
  26     data = next(iter(sheet.get('data', [])), {})
  27     row_data = data.get('rowData', [])
  28     if row_data == []:
  29         # Empty sheet, SKIP
  30         LOGGER.info('SKIPPING Empty Sheet: {}'.format(sheet_title))
  31         return None, None
  32     # spreadsheet is an OrderedDict, with orderd sheets and rows in the repsonse
  33     headers = row_data[0].get('values', [])
  34     first_values = row_data[1].get('values', [])
  35     # LOGGER.info('first_values = {}'.format(json.dumps(first_values, indent=2, sort_keys=True)))
  36
  37     sheet_json_schema = {
  38         'type': 'object',
  39         'additionalProperties': False,
  40         'properties': {
  41             '__sdc_spreadsheet_id': {
  42                 'type': ['null', 'string']
  43             },
  44             '__sdc_sheet_id': {
  45                 'type': ['null', 'integer']
  46             },
  47             '__sdc_row': {
  48                 'type': ['null', 'integer']
  49             }
  50         }
  51     }
  52
  53     header_list = [] # used for checking uniqueness
  54     columns = []
  55     prior_header = None
  56     i = 0
  57     skipped = 0
  58     # Read column headers until end or 2 consecutive skipped headers
  59     for header in headers:
  60         # LOGGER.info('header = {}'.format(json.dumps(header, indent=2, sort_keys=True)))
  61         column_index = i + 1
  62         column_letter = colnum_string(column_index)
  63         header_value = header.get('formattedValue')
  64         if header_value: # NOT skipped
  65             column_is_skipped = False
  66             skipped = 0
  67             column_name = '{}'.format(header_value)
  68             if column_name in header_list:
  69                 raise Exception('DUPLICATE HEADER ERROR: SHEET: {}, COL: {}, CELL: {}1'.format(
  70                     sheet_title, column_name, column_letter))
  71             header_list.append(column_name)
  72
  73             first_value = None
  74             try:
  75                 first_value = first_values[i]
  76             except IndexError as err:
  77                 raise Exception('NO VALUE IN 2ND ROW FOR HEADER ERROR. SHEET: {}, COL: {}, CELL: {}2. {}'.format(
  78                     sheet_title, column_name, column_letter, err))
  79
  80             column_effective_value = first_value.get('effectiveValue', {})
  81
  82             col_val = None
  83             if column_effective_value == {}:
  84                 column_effective_value_type = 'stringValue'
  85                 LOGGER.info('WARNING: NO VALUE IN 2ND ROW FOR HEADER. SHEET: {}, COL: {}, CELL: {}2.'.format(
  86                     sheet_title, column_name, column_letter))
  87                 LOGGER.info('   Setting column datatype to STRING')
  88             else:
  89                 for key, val in column_effective_value.items():
  90                     if key in ('numberValue', 'stringValue', 'boolValue'):
  91                         column_effective_value_type = key
  92                         col_val = str(val)
  93                     elif key in ('errorType', 'formulaType'):
  94                         col_val = str(val)
  95                         raise Exception('DATA TYPE ERROR 2ND ROW VALUE: SHEET: {}, COL: {}, CELL: {}2, TYPE: {}, VALUE: {}'.format(
  96                             sheet_title, column_name, column_letter, key, col_val))
  97
  98             column_number_format = first_values[i].get('effectiveFormat', {}).get(
  99                 'numberFormat', {})
 100             column_number_format_type = column_number_format.get('type')
 101
 102             # Determine datatype for sheet_json_schema
 103             #
 104             # column_effective_value_type = numberValue, stringValue, boolValue;
 105             #  INVALID: errorType, formulaType
 106             #  https://developers.google.com/sheets/api/reference/rest/v4/spreadsheets/other#ExtendedValue
 107             #
 108             # column_number_format_type = UNEPECIFIED, TEXT, NUMBER, PERCENT, CURRENCY, DATE,
 109             #   TIME, DATE_TIME, SCIENTIFIC
 110             #  https://developers.google.com/sheets/api/reference/rest/v4/spreadsheets/cells#NumberFormatType
 111             #
 112             column_format = None # Default
 113             if column_effective_value == {}:
 114                 col_properties = {'type': ['null', 'string']}
 115                 column_gs_type = 'stringValue'
 116                 LOGGER.info('WARNING: 2ND ROW VALUE IS BLANK: SHEET: {}, COL: {}, CELL: {}2'.format(
 117                         sheet_title, column_name, column_letter))
 118                 LOGGER.info('   Setting column datatype to STRING')
 119             elif column_effective_value_type == 'stringValue':
 120                 col_properties = {'type': ['null', 'string']}
 121                 column_gs_type = 'stringValue'
 122             elif column_effective_value_type == 'boolValue':
 123                 col_properties = {'type': ['null', 'boolean', 'string']}
 124                 column_gs_type = 'boolValue'
 125             elif column_effective_value_type == 'numberValue':
 126                 if column_number_format_type == 'DATE_TIME':
 127                     col_properties = {
 128                         'type': ['null', 'string'],
 129                         'format': 'date-time'
 130                     }
 131                     column_gs_type = 'numberType.DATE_TIME'
 132                 elif column_number_format_type == 'DATE':
 133                     col_properties = {
 134                         'type': ['null', 'string'],
 135                         'format': 'date'
 136                     }
 137                     column_gs_type = 'numberType.DATE'
 138                 elif column_number_format_type == 'TIME':
 139                     col_properties = {
 140                         'type': ['null', 'string'],
 141                         'format': 'time'
 142                     }
 143                     column_gs_type = 'numberType.TIME'
 144                 elif column_number_format_type == 'TEXT':
 145                     col_properties = {'type': ['null', 'string']}
 146                     column_gs_type = 'stringValue'
 147                 else:
 148                     # Interesting - order in the anyOf makes a difference.
 149                     # Number w/ multipleOf must be listed last, otherwise errors occur.
 150                     col_properties =  {
 151                         'anyOf': [
 152                             {
 153                                 'type': 'null'
 154                             },
 155                             {
 156                                 'type': 'number',
 157                                 'multipleOf': 1e-15
 158                             },
 159                             {
 160                                 'type': 'string'
 161                             }
 162                         ]
 163                     }
 164                     column_gs_type = 'numberType'
 165             # Catch-all to deal with other types and set to string
 166             # column_effective_value_type: formulaValue, errorValue, or other
 167             else:
 168                 col_properties = {'type': ['null', 'string']}
 169                 column_gs_type = 'unsupportedValue'
 170                 LOGGER.info('WARNING: UNSUPPORTED 2ND ROW VALUE: SHEET: {}, COL: {}, CELL: {}2, TYPE: {}, VALUE: {}'.format(
 171                         sheet_title, column_name, column_letter, column_effective_value_type, col_val))
 172                 LOGGER.info('Converting to string.')
 173         else: # skipped
 174             column_is_skipped = True
 175             skipped = skipped + 1
 176             column_index_str = str(column_index).zfill(2)
 177             column_name = '__sdc_skip_col_{}'.format(column_index_str)
 178             col_properties = {'type': ['null', 'string']}
 179             column_gs_type = 'stringValue'
 180             LOGGER.info('WARNING: SKIPPED COLUMN; NO COLUMN HEADER. SHEET: {}, COL: {}, CELL: {}1'.format(
 181                 sheet_title, column_name, column_letter))
 182             LOGGER.info('  This column will be skipped during data loading.')
 183
 184         if skipped >= 2:
 185             # skipped = 2 consecutive skipped headers
 186             # Remove prior_header column_name
 187             sheet_json_schema['properties'].pop(prior_header, None)
 188             LOGGER.info('TWO CONSECUTIVE SKIPPED COLUMNS. STOPPING SCAN AT: SHEET: {}, COL: {}, CELL {}1'.format(
 189                 sheet_title, column_name, column_letter))
 190             break
 191
 192         else:
 193             column = {}
 194             column = {
 195                 'columnIndex': column_index,
 196                 'columnLetter': column_letter,
 197                 'columnName': column_name,
 198                 'columnType': column_gs_type,
 199                 'columnSkipped': column_is_skipped
 200             }
 201             columns.append(column)
 202
 203             sheet_json_schema['properties'][column_name] = col_properties
 204
 205         prior_header = column_name
 206         i = i + 1
 207
 208     return sheet_json_schema, columns
 209
 210
 211 # Get Header Row and 1st data row (Rows 1 & 2) from a Sheet on Spreadsheet w/ sheet_metadata query
 212 #   endpoint: spreadsheets/{spreadsheet_id}
 213 #   params: includeGridData = true, ranges = '{sheet_title}'!1:2
 214 # This endpoint includes detailed metadata about each cell - incl. data type, formatting, etc.
 215 def get_sheet_metadata(sheet, spreadsheet_id, client):
 216     sheet_id = sheet.get('properties', {}).get('sheetId')
 217     sheet_title = sheet.get('properties', {}).get('title')
 218     LOGGER.info('sheet_id = {}, sheet_title = {}'.format(sheet_id, sheet_title))
 219
 220     stream_name = 'sheet_metadata'
 221     stream_metadata = STREAMS.get(stream_name)
 222     api = stream_metadata.get('api', 'sheets')
 223     params = stream_metadata.get('params', {})
 224     querystring = '&'.join(['%s=%s' % (key, value) for (key, value) in \
 225         params.items()]).replace('{sheet_title}', sheet_title)
 226     path = '{}?{}'.format(stream_metadata.get('path').replace('{spreadsheet_id}', \
 227         spreadsheet_id), querystring)
 228
 229     sheet_md_results = client.get(path=path, api=api, endpoint=stream_name)
 230     # sheet_metadata: 1st `sheets` node in results
 231     sheet_metadata = sheet_md_results.get('sheets')[0]
 232
 233     # Create sheet_json_schema (for discovery/catalog) and columns (for sheet_metadata results)
 234     try:
 235         sheet_json_schema, columns = get_sheet_schema_columns(sheet_metadata)
 236     except:
 237         LOGGER.info('SKIPPING Malformed sheet: {}'.format(sheet_title))
 238         sheet_json_schema, columns = None, None
 239
 240     return sheet_json_schema, columns
 241
 242
 243 def get_abs_path(path):
 244     return os.path.join(os.path.dirname(os.path.realpath(__file__)), path)
 245
 246 def get_schemas(client, spreadsheet_id):
 247     schemas = {}
 248     field_metadata = {}
 249
 250     for stream_name, stream_metadata in STREAMS.items():
 251         schema_path = get_abs_path('schemas/{}.json'.format(stream_name))
 252         with open(schema_path) as file:
 253             schema = json.load(file)
 254         schemas[stream_name] = schema
 255         mdata = metadata.new()
 256
 257         # Documentation:
 258         # https://github.com/singer-io/getting-started/blob/master/docs/DISCOVERY_MODE.md#singer-python-helper-functions
 259         # Reference:
 260         # https://github.com/singer-io/singer-python/blob/master/singer/metadata.py#L25-L44
 261         mdata = metadata.get_standard_metadata(
 262             schema=schema,
 263             key_properties=stream_metadata.get('key_properties', None),
 264             valid_replication_keys=stream_metadata.get('replication_keys', None),
 265             replication_method=stream_metadata.get('replication_method', None)
 266         )
 267         field_metadata[stream_name] = mdata
 268
 269         if stream_name == 'spreadsheet_metadata':
 270             api = stream_metadata.get('api', 'sheets')
 271             params = stream_metadata.get('params', {})
 272             querystring = '&'.join(['%s=%s' % (key, value) for (key, value) in params.items()])
 273             path = '{}?{}'.format(stream_metadata.get('path').replace('{spreadsheet_id}', \
 274                 spreadsheet_id), querystring)
 275
 276             # GET spreadsheet_metadata, which incl. sheets (basic metadata for each worksheet)
 277             spreadsheet_md_results = client.get(path=path, params=querystring, api=api, \
 278                 endpoint=stream_name)
 279
 280             sheets = spreadsheet_md_results.get('sheets')
 281             if sheets:
 282                 # Loop thru each worksheet in spreadsheet
 283                 for sheet in sheets:
 284                     # GET sheet_json_schema for each worksheet (from function above)
 285                     sheet_json_schema, columns = get_sheet_metadata(sheet, spreadsheet_id, client)
 286
 287                     # SKIP empty sheets (where sheet_json_schema and columns are None)
 288                     if sheet_json_schema and columns:
 289                         sheet_title = sheet.get('properties', {}).get('title')
 290                         schemas[sheet_title] = sheet_json_schema
 291                         sheet_mdata = metadata.new()
 292                         sheet_mdata = metadata.get_standard_metadata(
 293                             schema=sheet_json_schema,
 294                             key_properties=['__sdc_row'],
 295                             valid_replication_keys=None,
 296                             replication_method='FULL_TABLE'
 297                         )
 298                         field_metadata[sheet_title] = sheet_mdata
 299
 300     return schemas, field_metadata