import domolibrary.client.DomoAuth as dmda
import os
token_auth = dmda.DomoTokenAuth(
domo_instance=os.environ['DOMO_INSTANCE'],
domo_access_token=os.environ["DOMO_ACCESS_TOKEN"],
)
await token_auth.get_auth_token()
assert isinstance(token_auth.token, str)Automated Card Backup
Backup
Cards
a short post on using DomoLibrary to automate dataset tagging
Project Configuration
Get Cards
import domolibrary.classes.DomoDatacenter as ddc
domo_datasets = await ddc.DomoDatacenter.search_datasets(
auth=token_auth,
)
domo_datasets[0:5][DomoDataset(id='da552832-c04d-46ac-936a-f982d9d3f2e6', display_type='api', data_provider_type=None, name='SalesProject01_hello world_INT *', description=None, row_count=0, column_count=0, stream_id=None, owner={'id': '1893952720', 'name': 'Jae Wilson1', 'type': 'USER', 'group': False}, formula={}, Schema=DomoDataset_Schema(dataset_id='da552832-c04d-46ac-936a-f982d9d3f2e6', columns=[]), Stream=DomoStream(id=None, dataset_id='da552832-c04d-46ac-936a-f982d9d3f2e6', transport_description=None, transport_version=None, update_method=None, data_provider_name=None, data_provider_key=None, account_id=None, account_display_name=None, account_userid=None, has_mapping=False, configuration=[], configuration_tables=[], configuration_query=None), Tags=DomoTags(tag_ls=['provider_type : api *', 'proj_phase : 01 *', 'proj_name : SalesProject *', 'ds_type : INT *']), PDP=<domolibrary.classes.DomoPDP.Dataset_PDP_Policies object>, Certification=None),
DomoDataset(id='581b58d6-4554-46c6-b0e0-c7c2f782df90', display_type='DataFlow', data_provider_type=None, name='[Alerts Demo June 22] Pipeline Validation', description=None, row_count=270, column_count=10, stream_id=1893, owner={'id': '307632801', 'name': 'Dan Brinton', 'type': 'USER', 'group': False}, formula={'calculation_036d74aa-f958-4b85-82e9-a3f1a10c4ab5': {'templateId': 1293, 'id': 'calculation_036d74aa-f958-4b85-82e9-a3f1a10c4ab5', 'name': 'Open Validation Issues', 'formula': 'sum(case when `Amount Diff` <> 0 then 1 else 0 end)', 'status': 'VALID', 'dataType': 'LONG', 'persistedOnDataSource': True, 'isAggregatable': True, 'bignumber': False, 'columnPositions': [{'columnName': '`Amount Diff`', 'columnPosition': 14}], 'variable': False}}, Schema=DomoDataset_Schema(dataset_id='581b58d6-4554-46c6-b0e0-c7c2f782df90', columns=[]), Stream=DomoStream(id=1893, dataset_id='581b58d6-4554-46c6-b0e0-c7c2f782df90', transport_description=None, transport_version=None, update_method=None, data_provider_name=None, data_provider_key=None, account_id=None, account_display_name=None, account_userid=None, has_mapping=False, configuration=[], configuration_tables=[], configuration_query=None), Tags=DomoTags(tag_ls=['developer_documentation', 'hackercore']), PDP=<domolibrary.classes.DomoPDP.Dataset_PDP_Policies object>, Certification=None),
DomoDataset(id='61c4e63d-0627-41f7-b138-74968ebd7634', display_type='domostats', data_provider_type='domostats', name='DomoStats - Activity Log', description='Domo Stats', row_count=3383565, column_count=17, stream_id=307, owner={'id': '587894148', 'name': 'Bryan Van Kampen', 'type': 'USER', 'group': False}, formula={'calculation_5deab6ee-8663-4d59-a670-6d581f1be22f': {'templateId': 1079, 'id': 'calculation_5deab6ee-8663-4d59-a670-6d581f1be22f', 'name': 'Logins (Merged from datasource: 61c4e63d-0627-41f7-b138-74968ebd7634)', 'formula': "(CASE WHEN `Action` IN ('LOGGEDIN', 'LOGGEDIN_SSO', 'LOGGEDIN_TWO_FACTOR') THEN 'Y' ELSE 'N' END)", 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Action`', 'columnPosition': 11}], 'variable': False}, 'calculation_b80f5ea7-297d-4f38-9e47-b606356994f8': {'templateId': 357, 'id': 'calculation_b80f5ea7-297d-4f38-9e47-b606356994f8', 'name': 'Distinct User', 'formula': 'COUNT(DISTINCT `Name`)', 'status': 'VALID', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Name`', 'columnPosition': 15}], 'variable': False}, 'calculation_a3478054-b428-4a47-86e1-ef41f550bd0b': {'templateId': 361, 'id': 'calculation_a3478054-b428-4a47-86e1-ef41f550bd0b', 'name': 'Failed Login', 'formula': "(CASE WHEN (`Action` = 'FAILED_LOGIN') THEN `Action` END )", 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Action`', 'columnPosition': 13}, {'columnName': '`Action`', 'columnPosition': 45}], 'variable': False}, 'calculation_eb7aa11e-f032-4723-9a98-6b50d475bcd8': {'templateId': 359, 'id': 'calculation_eb7aa11e-f032-4723-9a98-6b50d475bcd8', 'name': 'Behavior String', 'formula': "CONCAT('At ',`Event_Time`,' ',`Name`,' ',`Action`,' ','the ',`Object_Type`,' ',`Object_Name`)", 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Event_Time`', 'columnPosition': 13}, {'columnName': '`Name`', 'columnPosition': 30}, {'columnName': '`Action`', 'columnPosition': 41}, {'columnName': '`Object_Type`', 'columnPosition': 61}, {'columnName': '`Object_Name`', 'columnPosition': 79}], 'variable': False}, 'calculation_20ce4ae4-badc-4180-9e07-5f109e5d9d82': {'templateId': 360, 'id': 'calculation_20ce4ae4-badc-4180-9e07-5f109e5d9d82', 'name': 'Logins', 'formula': "(CASE WHEN `Action` IN ('LOGGEDIN','LOGGEDIN_SSO','LOGGEDIN_TWO_FACTOR') THEN 'Y' ELSE 'N' END )", 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Action`', 'columnPosition': 12}], 'variable': False}, 'calculation_0198fd23-4e28-4d22-b442-f1f68c0486b6': {'templateId': 1078, 'id': 'calculation_0198fd23-4e28-4d22-b442-f1f68c0486b6', 'name': 'Formatted Behavior String (Merged from datasource: 61c4e63d-0627-41f7-b138-74968ebd7634)', 'formula': 'CONCAT(\'<b>\', `Name`, \' at \', `Event_Time`, \': </b>\', LOWER(`Action`), \' \', \'the \', LOWER(`Object_Type`), \' "\', LOWER(`Object_Name`), \'"\')', 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Name`', 'columnPosition': 14}, {'columnName': '`Event_Time`', 'columnPosition': 30}, {'columnName': '`Action`', 'columnPosition': 60}, {'columnName': '`Object_Type`', 'columnPosition': 90}, {'columnName': '`Object_Name`', 'columnPosition': 118}], 'variable': False}, 'calculation_624dc0e1-ac48-4a78-80e8-e10461b5d01d': {'templateId': 358, 'id': 'calculation_624dc0e1-ac48-4a78-80e8-e10461b5d01d', 'name': 'Formatted Behavior String', 'formula': 'CONCAT(\'<b>\',`Name`,\' at \',`Event_Time`,\': </b>\',LOWER(`Action`),\' \',\'the \',LOWER(`Object_Type`),\' "\',LOWER(`Object_Name`),\'"\')', 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Name`', 'columnPosition': 13}, {'columnName': '`Event_Time`', 'columnPosition': 27}, {'columnName': '`Action`', 'columnPosition': 55}, {'columnName': '`Object_Type`', 'columnPosition': 82}, {'columnName': '`Object_Name`', 'columnPosition': 108}], 'variable': False}, 'calculation_418a84db-006f-4bfc-b72a-243b0263d4df': {'templateId': 1080, 'id': 'calculation_418a84db-006f-4bfc-b72a-243b0263d4df', 'name': 'Failed Login (Merged from datasource: 61c4e63d-0627-41f7-b138-74968ebd7634)', 'formula': "(CASE WHEN (`Action` = 'FAILED_LOGIN') THEN `Action` END)", 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Action`', 'columnPosition': 12}, {'columnName': '`Action`', 'columnPosition': 44}], 'variable': False}, 'calculation_8626da93-6edb-4263-a68a-793c916faf0f': {'templateId': 1077, 'id': 'calculation_8626da93-6edb-4263-a68a-793c916faf0f', 'name': 'Behavior String (Merged from datasource: 61c4e63d-0627-41f7-b138-74968ebd7634)', 'formula': "CONCAT('At ', `Event_Time`, ' ', `Name`, ' ', `Action`, ' ', 'the ', `Object_Type`, ' ', `Object_Name`)", 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Event_Time`', 'columnPosition': 14}, {'columnName': '`Name`', 'columnPosition': 33}, {'columnName': '`Action`', 'columnPosition': 46}, {'columnName': '`Object_Type`', 'columnPosition': 69}, {'columnName': '`Object_Name`', 'columnPosition': 89}], 'variable': False}, 'calculation_098eea28-d300-4221-892c-4a1317ef639a': {'templateId': 363, 'id': 'calculation_098eea28-d300-4221-892c-4a1317ef639a', 'name': 'Time Since Last Update Sort', 'formula': '(CASE WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 0) THEN 1 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 1) THEN 2 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 2) THEN 3 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 3) THEN 4 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 4) THEN 5 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 5) THEN 6 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 6) THEN 7 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 7) THEN 8 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 8) THEN 9 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 9) THEN 10 WHEN (DATEDIFF(CURDATE(),`Event_Time`) = 10) THEN 11 ELSE 12 END )', 'status': 'VALID', 'dataType': 'LONG', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Event_Time`', 'columnPosition': 32}, {'columnName': '`Event_Time`', 'columnPosition': 83}, {'columnName': '`Event_Time`', 'columnPosition': 134}, {'columnName': '`Event_Time`', 'columnPosition': 185}, {'columnName': '`Event_Time`', 'columnPosition': 236}, {'columnName': '`Event_Time`', 'columnPosition': 287}, {'columnName': '`Event_Time`', 'columnPosition': 338}, {'columnName': '`Event_Time`', 'columnPosition': 389}, {'columnName': '`Event_Time`', 'columnPosition': 440}, {'columnName': '`Event_Time`', 'columnPosition': 491}, {'columnName': '`Event_Time`', 'columnPosition': 543}], 'variable': False}, 'calculation_947f77ff-7d78-462e-a5ca-2199b919d3c3': {'templateId': 1129, 'id': 'calculation_947f77ff-7d78-462e-a5ca-2199b919d3c3', 'name': 'RowCount', 'formula': 'sum(1)', 'status': 'VALID', 'dataType': 'LONG', 'persistedOnDataSource': True, 'isAggregatable': True, 'bignumber': False, 'variable': False}, 'calculation_246dbded-588e-41ab-8b00-cae08755a2a9': {'templateId': 1081, 'id': 'calculation_246dbded-588e-41ab-8b00-cae08755a2a9', 'name': 'Login Failure Rate (Merged from datasource: 61c4e63d-0627-41f7-b138-74968ebd7634)', 'formula': "(COUNT((CASE WHEN (`Action` = 'FAILED_LOGIN') THEN `Action` END)) / COUNT((CASE WHEN `Action` IN ('LOGGEDIN', 'FAILED_LOGIN') THEN `Action` END)))", 'status': 'VALID', 'dataType': 'DECIMAL', 'persistedOnDataSource': True, 'isAggregatable': True, 'bignumber': False, 'columnPositions': [{'columnName': '`Action`', 'columnPosition': 19}, {'columnName': '`Action`', 'columnPosition': 51}, {'columnName': '`Action`', 'columnPosition': 85}, {'columnName': '`Action`', 'columnPosition': 131}], 'variable': False}, 'calculation_bb8339c9-63bb-4cf2-81d5-0fbe9ffadfd1': {'templateId': 1082, 'id': 'calculation_bb8339c9-63bb-4cf2-81d5-0fbe9ffadfd1', 'name': 'Time Since Last Update Sort (Merged from datasource: 61c4e63d-0627-41f7-b138-74968ebd7634)', 'formula': '(CASE WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 0) THEN 1 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 1) THEN 2 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 2) THEN 3 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 3) THEN 4 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 4) THEN 5 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 5) THEN 6 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 6) THEN 7 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 7) THEN 8 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 8) THEN 9 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 9) THEN 10 WHEN (DATEDIFF(CURDATE(), `Event_Time`) = 10) THEN 11 ELSE 12 END)', 'status': 'VALID', 'dataType': 'LONG', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Event_Time`', 'columnPosition': 32}, {'columnName': '`Event_Time`', 'columnPosition': 84}, {'columnName': '`Event_Time`', 'columnPosition': 136}, {'columnName': '`Event_Time`', 'columnPosition': 188}, {'columnName': '`Event_Time`', 'columnPosition': 240}, {'columnName': '`Event_Time`', 'columnPosition': 292}, {'columnName': '`Event_Time`', 'columnPosition': 344}, {'columnName': '`Event_Time`', 'columnPosition': 396}, {'columnName': '`Event_Time`', 'columnPosition': 448}, {'columnName': '`Event_Time`', 'columnPosition': 500}, {'columnName': '`Event_Time`', 'columnPosition': 553}], 'variable': False}, 'calculation_b9a7911e-4b1b-40ce-a841-1587e45bf987': {'templateId': 362, 'id': 'calculation_b9a7911e-4b1b-40ce-a841-1587e45bf987', 'name': 'Login Failure Rate', 'formula': "(COUNT((CASE WHEN (`Action` = 'FAILED_LOGIN') THEN `Action` END )) / COUNT((CASE WHEN `Action` IN ('LOGGEDIN','FAILED_LOGIN') THEN `Action` END )))", 'status': 'VALID', 'dataType': 'DECIMAL', 'persistedOnDataSource': True, 'isAggregatable': True, 'bignumber': False, 'columnPositions': [{'columnName': '`Action`', 'columnPosition': 20}, {'columnName': '`Action`', 'columnPosition': 52}, {'columnName': '`Action`', 'columnPosition': 88}, {'columnName': '`Action`', 'columnPosition': 133}], 'variable': False}}, Schema=DomoDataset_Schema(dataset_id='61c4e63d-0627-41f7-b138-74968ebd7634', columns=[]), Stream=DomoStream(id=307, dataset_id='61c4e63d-0627-41f7-b138-74968ebd7634', transport_description=None, transport_version=None, update_method=None, data_provider_name=None, data_provider_key=None, account_id=None, account_display_name=None, account_userid=None, has_mapping=False, configuration=[], configuration_tables=[], configuration_query=None), Tags=DomoTags(tag_ls=['s_domostats', 'um_REPLACE', 'udt_DAY at 4:55 PM', 'domostats']), PDP=<domolibrary.classes.DomoPDP.Dataset_PDP_Policies object>, Certification=None),
DomoDataset(id='ea859b06-5dbe-4c31-be76-de921447d550', display_type='dataset-view', data_provider_type='dataset-view', name='Transaction product sales', description='', row_count=0, column_count=32, stream_id=699, owner={'id': '316139172', 'name': 'Matt Tannyhill', 'type': 'USER', 'group': False}, formula={'calculation_e01a10c1-2f65-48ad-b0bb-1a7ff69bfc52': {'templateId': 1372, 'id': 'calculation_e01a10c1-2f65-48ad-b0bb-1a7ff69bfc52', 'name': 'Current Time Range', 'formula': "(CASE \n \tWHEN DOMO_BEAST_MODE(1428) = 'Yes' THEN\n \t (CASE\n WHEN DOMO_BEAST_MODE(1366) = 'YTD' THEN \n (CASE\n WHEN YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) <= DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN DOMO_BEAST_MODE(1366) = 'QTD' THEN\n (CASE\n WHEN QUARTER(CURDATE()) = QUARTER(`Updated Order Date`) AND YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) <= DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN DOMO_BEAST_MODE(1366) = 'MTD' THEN\n (CASE\n WHEN (MONTH(CURDATE()) = MONTH(`Updated Order Date`)) AND (YEAR(CURDATE()) = YEAR(`Updated Order Date`)) AND DAYOFYEAR(`Updated Order Date`) <= DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN DOMO_BEAST_MODE(1366) = 'WTD' THEN\n (CASE\n WHEN WEEK(CURDATE()) = WEEK(`Updated Order Date`) AND YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) <= DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n END)\n \tWHEN DOMO_BEAST_MODE(1428) = 'No' THEN\n \t (CASE\n WHEN DOMO_BEAST_MODE(1366) = 'YTD' THEN\n (CASE\n WHEN YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) < DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN DOMO_BEAST_MODE(1366) = 'QTD' THEN\n (CASE\n WHEN QUARTER(CURDATE()) = QUARTER(`Updated Order Date`) AND YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) < DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN DOMO_BEAST_MODE(1366) = 'MTD' THEN\n (CASE\n WHEN MONTH(CURDATE()) = MONTH(`Updated Order Date`) AND YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) < DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN DOMO_BEAST_MODE(1366) = 'WTD' THEN\n (CASE\n WHEN WEEK(CURDATE()) = WEEK(`Updated Order Date`) AND YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) < DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n END)\nEND)", 'status': 'VALID', 'dataType': 'DOUBLE', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Updated Order Date`', 'columnPosition': 174}, {'columnName': '`Updated Order Date`', 'columnPosition': 210}, {'columnName': '`Total Sales`', 'columnPosition': 261}, {'columnName': '`Updated Order Date`', 'columnPosition': 429}, {'columnName': '`Updated Order Date`', 'columnPosition': 478}, {'columnName': '`Updated Order Date`', 'columnPosition': 514}, {'columnName': '`Total Sales`', 'columnPosition': 565}, {'columnName': '`Updated Order Date`', 'columnPosition': 731}, {'columnName': '`Updated Order Date`', 'columnPosition': 782}, {'columnName': '`Updated Order Date`', 'columnPosition': 819}, {'columnName': '`Total Sales`', 'columnPosition': 870}, {'columnName': '`Updated Order Date`', 'columnPosition': 1033}, {'columnName': '`Updated Order Date`', 'columnPosition': 1082}, {'columnName': '`Updated Order Date`', 'columnPosition': 1118}, {'columnName': '`Total Sales`', 'columnPosition': 1169}, {'columnName': '`Updated Order Date`', 'columnPosition': 1397}, {'columnName': '`Updated Order Date`', 'columnPosition': 1433}, {'columnName': '`Total Sales`', 'columnPosition': 1483}, {'columnName': '`Updated Order Date`', 'columnPosition': 1651}, {'columnName': '`Updated Order Date`', 'columnPosition': 1700}, {'columnName': '`Updated Order Date`', 'columnPosition': 1736}, {'columnName': '`Total Sales`', 'columnPosition': 1786}, {'columnName': '`Updated Order Date`', 'columnPosition': 1950}, {'columnName': '`Updated Order Date`', 'columnPosition': 1999}, {'columnName': '`Updated Order Date`', 'columnPosition': 2035}, {'columnName': '`Total Sales`', 'columnPosition': 2085}, {'columnName': '`Updated Order Date`', 'columnPosition': 2247}, {'columnName': '`Updated Order Date`', 'columnPosition': 2296}, {'columnName': '`Updated Order Date`', 'columnPosition': 2332}, {'columnName': '`Total Sales`', 'columnPosition': 2382}], 'variable': False}, 'calculation_d9a6f946-2ff2-45ee-8344-20eaa6d9f814': {'templateId': 1432, 'id': 'calculation_d9a6f946-2ff2-45ee-8344-20eaa6d9f814', 'name': '% Diff (Level 1)', 'formula': "SUM(CASE \n \tWHEN DOMO_BEAST_MODE(1428) = 'Yes' THEN\n (CASE\n WHEN WEEK(CURDATE()) = WEEK(`Updated Order Date`) AND YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) <= DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n \tWHEN DOMO_BEAST_MODE(1428) = 'No' THEN\n (CASE\n WHEN WEEK(CURDATE()) = WEEK(`Updated Order Date`) AND YEAR(CURDATE()) = YEAR(`Updated Order Date`) AND DAYOFYEAR(`Updated Order Date`) < DAYOFYEAR(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\nEND)\n/\n(CASE \n \tWHEN DOMO_BEAST_MODE(1428) = 'Yes' THEN\n (CASE \n WHEN WEEK(CURDATE()) = 1 THEN\n (CASE\n WHEN WEEK(`Updated Order Date`) = 52 AND YEAR(CURDATE())-1 = YEAR(`Updated Order Date`) AND DAYOFWEEK(`Updated Order Date`) <= DAYOFWEEK(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN WEEK(CURDATE()) = WEEK(`Updated Order Date`) AND YEAR(CURDATE())-1 = YEAR(`Updated Order Date`) AND DAYOFWEEK(`Updated Order Date`) <= DAYOFWEEK(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n \tWHEN DOMO_BEAST_MODE(1428) = 'No' THEN\n (CASE \n WHEN WEEK(CURDATE()) = 1 THEN\n (CASE\n WHEN WEEK(`Updated Order Date`) = 52 AND YEAR(CURDATE())-1 = YEAR(`Updated Order Date`) AND DAYOFWEEK(`Updated Order Date`) < DAYOFWEEK(CURDATE()) THEN `Total Sales`\n ELSE 0\n END)\n WHEN WEEK(CURDATE()) = 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'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'variable': False}, 'calculation_a391a1a5-c0b5-43bd-8ee0-9d5b8478ff14': {'templateId': 1421, 'id': 'calculation_a391a1a5-c0b5-43bd-8ee0-9d5b8478ff14', 'name': 'Table Switch Group 1', 'formula': "CASE \nWHEN DOMO_BEAST_MODE(1419) = 'Region' then `Region`\nWHEN DOMO_BEAST_MODE(1419)= 'State' then `State`\nWHEN DOMO_BEAST_MODE(1419)= 'City' THEN `City`\nWHEN DOMO_BEAST_MODE(1419)= 'Brand' THEN `Brand`\nWHEN DOMO_BEAST_MODE(1419)= 'Category' THEN `Product Category`\nWHEN DOMO_BEAST_MODE(1419) = 'Department' THEN `Department`\nEND", 'status': 'VALID', 'dataType': 'STRING', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'columnPositions': [{'columnName': '`Region`', 'columnPosition': 49}, {'columnName': '`State`', 'columnPosition': 99}, {'columnName': '`City`', 'columnPosition': 147}, {'columnName': '`Brand`', 'columnPosition': 195}, {'columnName': '`Product Category`', 'columnPosition': 247}, {'columnName': '`Department`', 'columnPosition': 313}], 'variable': False}, 'calculation_a43f4919-3352-4bab-ba1c-ba5a502849b2': {'templateId': 1371, 'id': 'calculation_a43f4919-3352-4bab-ba1c-ba5a502849b2', 'name': 'BM Goal for 2022', 'formula': 'DOMO_BEAST_MODE(1359)', 'status': 'VALID', 'dataType': 'LONG', 'persistedOnDataSource': True, 'isAggregatable': False, 'bignumber': False, 'variable': False}}, Schema=DomoDataset_Schema(dataset_id='ea859b06-5dbe-4c31-be76-de921447d550', columns=[]), Stream=DomoStream(id=699, dataset_id='ea859b06-5dbe-4c31-be76-de921447d550', transport_description=None, transport_version=None, update_method=None, data_provider_name=None, data_provider_key=None, account_id=None, account_display_name=None, account_userid=None, has_mapping=False, configuration=[], configuration_tables=[], configuration_query=None), Tags=DomoTags(tag_ls=['Oct-28-2024 17:06', 'developer_documentation', 'hackercore']), PDP=<domolibrary.classes.DomoPDP.Dataset_PDP_Policies object>, Certification=None),
DomoDataset(id='6bbff3ee-351c-467b-bf9b-d121af70dfb8', display_type='webform', data_provider_type='webform', name='LesMisNodes', description=None, row_count=77, column_count=2, stream_id=1041, owner={'id': '1893952720', 'name': 'Jae Wilson1', 'type': 'USER', 'group': False}, formula={}, Schema=DomoDataset_Schema(dataset_id='6bbff3ee-351c-467b-bf9b-d121af70dfb8', columns=[]), Stream=DomoStream(id=1041, dataset_id='6bbff3ee-351c-467b-bf9b-d121af70dfb8', transport_description=None, transport_version=None, update_method=None, data_provider_name=None, data_provider_key=None, account_id=None, account_display_name=None, account_userid=None, has_mapping=False, configuration=[], configuration_tables=[], configuration_query=None), Tags=DomoTags(tag_ls=[]), PDP=<domolibrary.classes.DomoPDP.Dataset_PDP_Policies object>, Certification=None)]import domolibrary.classes.DomoDataset as dmd
def process_ds(
domo_dataset: dmd.DomoDataset,
) -> dict: # dictionary where each attribute except _id and _ds_name becomes a tag
"""
receives DomoDataset object, and then generates an object with attributes that will become tags.
every organization will have different naming conventions and therefore must generate different rules for how tags can be exctracted from the Domo Dataset object.
"""
proj_str = domo_dataset.name.split("_", 1)[0]
proj_name = proj_str[:-2]
proj_phase = proj_str[-2:]
_ = domo_dataset.name.split("_", 1)[1]
ds_type = _.split("_")[-1].replace(" *", "")
return {
"_id": domo_dataset.id,
"_ds_name": domo_dataset.name,
"provider_type": domo_dataset.display_type or domo_dataset.data_provider_type,
"proj_name": proj_name,
"proj_phase": proj_phase,
"ds_type": ds_type,
}import pandas as pd
# for this project we assume any dataset that ends with * has been validated as adhering to the naming convention format.
dataset_tags_to_update = [
process_ds(domo_dataset)
for domo_dataset in domo_datasets
if domo_dataset.name.endswith("*")
]
pd.DataFrame(dataset_tags_to_update)| _id | _ds_name | provider_type | proj_name | proj_phase | ds_type | |
|---|---|---|---|---|---|---|
| 0 | da552832-c04d-46ac-936a-f982d9d3f2e6 | SalesProject01_hello world_INT * | api | SalesProject | 01 | INT |
| 1 | 063dd227-2a2d-4563-a372-6d08c950e86d | SalesProject02_summary_by_month_DASH * | api | SalesProject | 02 | DASH |
| 2 | 6114155e-e6a5-4c9c-bec0-5f0b8e807579 | SalesProject01_hello world3_INT * | api | SalesProject | 01 | INT |
| 3 | e5f44d26-4028-4282-88a9-239a0f909373 | SalesProject02_summary_by_day_DASH * | api | SalesProject | 02 | DASH |
def generate_tags(tag_dict):
"""
simple utility function to collapse key/value pairs into a string
tags generated by this process will be suffixed with an *
"""
tag_ls = [
f"{key} : {tag_dict[key]} *"
for key in tag_dict.keys()
if not key.startswith("_")
]
info = {
key.replace("_", ""): tag_dict[key]
for key in tag_dict.keys()
if key.startswith("_")
}
return {"tag_ls": tag_ls, **info}from pprint import pprint
# for each dataset to update, tag_ls contains the list of tags that will be added.
dataset_tags_for_api = [generate_tags(tag_dict) for tag_dict in dataset_tags_to_update]
pprint(dataset_tags_for_api)[{'dsname': 'SalesProject01_hello world_INT *',
'id': 'da552832-c04d-46ac-936a-f982d9d3f2e6',
'tag_ls': ['provider_type : api *',
'proj_name : SalesProject *',
'proj_phase : 01 *',
'ds_type : INT *']},
{'dsname': 'SalesProject02_summary_by_month_DASH *',
'id': '063dd227-2a2d-4563-a372-6d08c950e86d',
'tag_ls': ['provider_type : api *',
'proj_name : SalesProject *',
'proj_phase : 02 *',
'ds_type : DASH *']},
{'dsname': 'SalesProject01_hello world3_INT *',
'id': '6114155e-e6a5-4c9c-bec0-5f0b8e807579',
'tag_ls': ['provider_type : api *',
'proj_name : SalesProject *',
'proj_phase : 01 *',
'ds_type : INT *']},
{'dsname': 'SalesProject02_summary_by_day_DASH *',
'id': 'e5f44d26-4028-4282-88a9-239a0f909373',
'tag_ls': ['provider_type : api *',
'proj_name : SalesProject *',
'proj_phase : 02 *',
'ds_type : DASH *']}]import asyncio
from typing import List
import domolibrary.classes.DomoDataset as dmd
async def process_dataset_tags(dataset_id, tag_ls: List[str], auth: dmda.DomoAuth):
"""
function to actually update domo dataset entities.
tags previously added by this process (denoted with the * suffix) will be removed
"""
domo_dataset = await dmd.DomoDataset.get_by_id(dataset_id=dataset_id, auth=auth)
await domo_dataset.Tags.get()
# remove old tags
remove_tag_ls = [tag for tag in domo_dataset.Tags.tag_ls if tag.endswith(" *")]
if len(remove_tag_ls) > 0:
await domo_dataset.Tags.remove(remove_tag_ls=remove_tag_ls)
# add new tags
await domo_dataset.Tags.add(add_tag_ls=tag_ls)
return {
"id": domo_dataset.id,
"name": domo_dataset.name,
"tags": domo_dataset.Tags.tag_ls,
}import pandas as pd
res = await asyncio.gather(
*[
process_dataset_tags(
dataset_id=row.get("id"), tag_ls=row.get("tag_ls"), auth=token_auth
)
for row in dataset_tags_for_api
]
)
pd.DataFrame(res)| id | name | tags | |
|---|---|---|---|
| 0 | da552832-c04d-46ac-936a-f982d9d3f2e6 | SalesProject01_hello world_INT * | [provider_type : api *, proj_phase : 01 *, pro... |
| 1 | 063dd227-2a2d-4563-a372-6d08c950e86d | SalesProject02_summary_by_month_DASH * | [provider_type : api *, proj_phase : 02 *, pro... |
| 2 | 6114155e-e6a5-4c9c-bec0-5f0b8e807579 | SalesProject01_hello world3_INT * | [provider_type : api *, proj_phase : 01 *, pro... |
| 3 | e5f44d26-4028-4282-88a9-239a0f909373 | SalesProject02_summary_by_day_DASH * | [provider_type : api *, proj_phase : 02 *, pro... |