# auditlog_logentry

object_pk: 24
object_repr: Social Media Influvencer as of 2024-12-09 05:29:44.623000+00:00
timestamp: 2024-12-26 11:44:53.060119
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "24"], "history_date": ["None", "2024-12-09 05:29:44.623000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 25
object_repr: Social Media Influvencer as of 2024-12-09 05:36:32.069000+00:00
timestamp: 2024-12-26 11:44:53.064319
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "25"], "history_date": ["None", "2024-12-09 05:36:32.069000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 26
object_repr: Social Media Influvencer as of 2024-12-09 05:36:37.670000+00:00
timestamp: 2024-12-26 11:44:53.072694
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "26"], "history_date": ["None", "2024-12-09 05:36:37.670000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 27
object_repr: Social Media Influvencer as of 2024-12-09 05:41:32.527000+00:00
timestamp: 2024-12-26 11:44:53.078509
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "27"], "history_date": ["None", "2024-12-09 05:41:32.527000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 28
object_repr: Social Media Influvencer as of 2024-12-09 05:41:49.267000+00:00
timestamp: 2024-12-26 11:44:53.085383
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "28"], "history_date": ["None", "2024-12-09 05:41:49.267000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 29
object_repr: Social Media Influvencer as of 2024-12-09 05:42:06.763000+00:00
timestamp: 2024-12-26 11:44:53.091450
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "29"], "history_date": ["None", "2024-12-09 05:42:06.763000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 30
object_repr: Social Media Influvencer as of 2024-12-09 05:42:11.592000+00:00
timestamp: 2024-12-26 11:44:53.093712
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "30"], "history_date": ["None", "2024-12-09 05:42:11.592000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 31
object_repr: Social Media Influvencer as of 2024-12-09 11:05:35.708000+00:00
timestamp: 2024-12-26 11:44:53.096491
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "31"], "history_date": ["None", "2024-12-09 11:05:35.708000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 32
object_repr: Social Media Influvencer as of 2024-12-09 11:06:37.940000+00:00
timestamp: 2024-12-26 11:44:53.104362
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "32"], "history_date": ["None", "2024-12-09 11:06:37.940000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 33
object_repr: Social Media Influvencer as of 2024-12-09 11:22:34.873000+00:00
timestamp: 2024-12-26 11:44:53.111239
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "33"], "history_date": ["None", "2024-12-09 11:22:34.873000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 34
object_repr: Social Media Influvencer as of 2024-12-09 11:22:40.444000+00:00
timestamp: 2024-12-26 11:44:53.116084
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "34"], "history_date": ["None", "2024-12-09 11:22:40.444000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 35
object_repr: Social Media Influvencer as of 2024-12-10 03:06:08.373000+00:00
timestamp: 2024-12-26 11:44:53.124174
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "35"], "history_date": ["None", "2024-12-10 03:06:08.373000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 36
object_repr: Social Media Influvencer as of 2024-12-10 03:06:17.492000+00:00
timestamp: 2024-12-26 11:44:53.128143
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "36"], "history_date": ["None", "2024-12-10 03:06:17.492000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 37
object_repr: Social Media Influvencer as of 2024-12-10 03:22:10.140000+00:00
timestamp: 2024-12-26 11:44:53.134104
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "37"], "history_date": ["None", "2024-12-10 03:22:10.140000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 38
object_repr: Social Media Influvencer as of 2024-12-10 03:22:31.426000+00:00
timestamp: 2024-12-26 11:44:53.142993
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "company_id": ["None", "1"], "history_id": ["None", "38"], "history_date": ["None", "2024-12-10 03:22:31.426000"], "history_type": ["None", "~"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "is_active": ["None", "True"], "history_highlight": ["None", "False"], "id": ["None", "3"]}


object_pk: 1
object_repr: Contact Customer
timestamp: 2024-12-26 11:44:53.154908
remote_addr: 127.0.0.1
changes:
  {"id": ["None", "1"], "title": ["None", "Contact Customer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "10"], "archive": ["None", "False"], "company_id": ["None", "1"], "employee_key_result": ["None", "pms.EmployeeKeyResult.None"], "created_at": ["None", "2024-09-17 09:31:25.485000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 2
object_repr: Digital Marketing
timestamp: 2024-12-26 11:44:53.159904
remote_addr: 127.0.0.1
changes:
  {"id": ["None", "2"], "title": ["None", "Digital Marketing"], "description": ["None", "Descriptio"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "10"], "archive": ["None", "False"], "company_id": ["None", "1"], "employee_key_result": ["None", "pms.EmployeeKeyResult.None"], "created_at": ["None", "2024-09-17 09:32:03.931000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 3
object_repr: Social Media Influvencer
timestamp: 2024-12-26 11:44:53.162414
remote_addr: 127.0.0.1
changes:
  {"id": ["None", "3"], "title": ["None", "Social Media Influvencer"], "description": ["None", "Description"], "progress_type": ["None", "%"], "target_value": ["None", "100"], "duration": ["None", "2"], "archive": ["None", "False"], "company_id": ["None", "1"], "employee_key_result": ["None", "pms.EmployeeKeyResult.None"], "created_at": ["None", "2024-09-17 09:32:55.218000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 1
object_repr: Increase Sales
timestamp: 2024-12-26 11:44:53.170821
remote_addr: 127.0.0.1
changes:
  {"id": ["None", "1"], "duration_unit": ["None", "months"], "duration": ["None", "1"], "add_assignees": ["None", "False"], "archive": ["None", "False"], "title": ["None", "Increase Sales"], "created_by": ["None", "1"], "created_at": ["None", "2024-09-17 09:33:00.753000"], "employee_objective": ["None", "pms.EmployeeObjective.None"], "modified_by": ["None", "1"], "description": ["None", "Description"], "is_active": ["None", "True"]}


object_pk: 1
object_repr: Increase Sales
timestamp: 2024-12-26 11:44:53.211471
remote_addr: 127.0.0.1
changes:
  {"assignees": {"type": "m2m", "operation": "add", "objects": ["Abigail Roberts (PEP15)", "Alexander Smith (PEP16)", "Andrew Hayes (PEP74)"]}}


object_pk: 1
object_repr: Increase Sales
timestamp: 2024-12-26 11:44:53.231613
remote_addr: 127.0.0.1
changes:
  {"key_result_id": {"type": "m2m", "operation": "add", "objects": ["Social Media Influvencer", "Digital Marketing", "Contact Customer"]}}


object_pk: 1
object_repr: Increase Sales | Abigail Roberts (PEP15)
timestamp: 2024-12-26 11:44:53.245156
remote_addr: 127.0.0.1
changes:
  {"status": ["None", "Not Started"], "progress_percentage": ["None", "0"], "archive": ["None", "False"], "updated_at": ["None", "2024-09-17"], "employee_key_result": ["None", "pms.EmployeeKeyResult.None"], "start_date": ["None", "2024-09-23"], "emp_objective": ["None", "pms.Comment.None"], "modified_by": ["None", "1"], "end_date": ["None", "2024-10-23"], "created_at": ["None", "2024-09-17"], "objective_id": ["None", "1"], "employee_id": ["None", "12"], "created_by": ["None", "1"], "id": ["None", "1"], "history_set": ["None", "pms.HistoricalEmployeeObjective.None"], "is_active": ["None", "True"]}


object_pk: 2
object_repr: Increase Sales | Alexander Smith (PEP16)
timestamp: 2024-12-26 11:44:53.259593
remote_addr: 127.0.0.1
changes:
  {"status": ["None", "Not Started"], "progress_percentage": ["None", "0"], "archive": ["None", "False"], "updated_at": ["None", "2024-09-17"], "employee_key_result": ["None", "pms.EmployeeKeyResult.None"], "start_date": ["None", "2024-09-23"], "emp_objective": ["None", "pms.Comment.None"], "modified_by": ["None", "1"], "end_date": ["None", "2024-10-23"], "created_at": ["None", "2024-09-17"], "objective_id": ["None", "1"], "employee_id": ["None", "13"], "created_by": ["None", "1"], "id": ["None", "2"], "history_set": ["None", "pms.HistoricalEmployeeObjective.None"], "is_active": ["None", "True"]}


object_pk: 3
object_repr: Increase Sales | Andrew Hayes (PEP74)
timestamp: 2024-12-26 11:44:53.271666
remote_addr: 127.0.0.1
changes:
  {"status": ["None", "Not Started"], "progress_percentage": ["None", "0"], "archive": ["None", "False"], "updated_at": ["None", "2024-09-17"], "employee_key_result": ["None", "pms.EmployeeKeyResult.None"], "start_date": ["None", "2024-09-23"], "emp_objective": ["None", "pms.Comment.None"], "modified_by": ["None", "1"], "end_date": ["None", "2024-10-23"], "created_at": ["None", "2024-09-17"], "objective_id": ["None", "1"], "employee_id": ["None", "68"], "created_by": ["None", "1"], "id": ["None", "3"], "history_set": ["None", "pms.HistoricalEmployeeObjective.None"], "is_active": ["None", "True"]}


object_pk: 1
object_repr: Social Media Influvencer | Abigail Roberts (PEP15)
timestamp: 2024-12-26 11:44:53.289914
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "1"], "key_result_id": ["None", "3"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "1"], "key_result": ["None", "Social Media Influvencer"]}


object_pk: 2
object_repr: Digital Marketing | Abigail Roberts (PEP15)
timestamp: 2024-12-26 11:44:53.299092
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "1"], "key_result_id": ["None", "2"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "2"], "key_result": ["None", "Digital Marketing"]}


object_pk: 3
object_repr: Contact Customer | Abigail Roberts (PEP15)
timestamp: 2024-12-26 11:44:53.309550
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "1"], "key_result_id": ["None", "1"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "3"], "key_result": ["None", "Contact Customer"]}


object_pk: 4
object_repr: Social Media Influvencer | Alexander Smith (PEP16)
timestamp: 2024-12-26 11:44:53.316067
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "2"], "key_result_id": ["None", "3"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "4"], "key_result": ["None", "Social Media Influvencer"]}


object_pk: 5
object_repr: Digital Marketing | Alexander Smith (PEP16)
timestamp: 2024-12-26 11:44:53.328070
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "2"], "key_result_id": ["None", "2"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "5"], "key_result": ["None", "Digital Marketing"]}


object_pk: 6
object_repr: Contact Customer | Alexander Smith (PEP16)
timestamp: 2024-12-26 11:44:53.339475
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "2"], "key_result_id": ["None", "1"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "6"], "key_result": ["None", "Contact Customer"]}


object_pk: 7
object_repr: Social Media Influvencer | Andrew Hayes (PEP74)
timestamp: 2024-12-26 11:44:53.348932
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "3"], "key_result_id": ["None", "3"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "7"], "key_result": ["None", "Social Media Influvencer"]}


object_pk: 8
object_repr: Digital Marketing | Andrew Hayes (PEP74)
timestamp: 2024-12-26 11:44:53.359679
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "3"], "key_result_id": ["None", "2"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "8"], "key_result": ["None", "Digital Marketing"]}


object_pk: 9
object_repr: Contact Customer | Andrew Hayes (PEP74)
timestamp: 2024-12-26 11:44:53.365680
remote_addr: 127.0.0.1
changes:
  {"employee_objective_id": ["None", "3"], "key_result_id": ["None", "1"], "progress_type": ["None", "%"], "status": ["None", "Not Started"], "created_at": ["None", "2024-09-17"], "updated_at": ["None", "2024-09-17"], "start_value": ["None", "0"], "current_value": ["None", "0"], "target_value": ["None", "100"], "progress_percentage": ["None", "0"], "key_result_feedback": ["None", "pms.KeyResultFeedback.None"], "id": ["None", "9"], "key_result": ["None", "Contact Customer"]}


object_pk: 1
object_repr: Developer Question
timestamp: 2024-12-26 11:44:53.376379
remote_addr: 127.0.0.1
changes:
  {"feedback_question_template": ["None", "pms.Feedback.None"], "id": ["None", "1"], "question": ["None", "pms.Question.None"], "question_template": ["None", "Developer Question"], "created_at": ["None", "2024-12-10 03:12:56.357000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 1
object_repr: Can you share an example of a time employee positively impacted the team or a project?
timestamp: 2024-12-26 11:44:53.398494
remote_addr: 127.0.0.1
changes:
  {"template_id": ["None", "1"], "meeting_answer_question_id": ["None", "pms.MeetingsAnswer.None"], "id": ["None", "1"], "answer_question_id": ["None", "pms.Answer.None"], "question": ["None", "Can you share an example of a time employee positively impacted the team or a project?"], "question_type": ["None", "1"], "created_at": ["None", "2024-12-10 03:14:44.788000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"], "question_options": ["None", "pms.QuestionOptions.None"]}


object_pk: 2
object_repr: How would you describe your working relationship with this employee
timestamp: 2024-12-26 11:44:53.401498
remote_addr: 127.0.0.1
changes:
  {"template_id": ["None", "1"], "meeting_answer_question_id": ["None", "pms.MeetingsAnswer.None"], "id": ["None", "2"], "answer_question_id": ["None", "pms.Answer.None"], "question": ["None", "How would you describe your working relationship with this employee"], "question_type": ["None", "2"], "created_at": ["None", "2024-12-10 03:15:07.690000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"], "question_options": ["None", "pms.QuestionOptions.None"]}


object_pk: 3
object_repr: What skills or behaviors do you think employee could improve to be even more effective?
timestamp: 2024-12-26 11:44:53.405471
remote_addr: 127.0.0.1
changes:
  {"template_id": ["None", "1"], "meeting_answer_question_id": ["None", "pms.MeetingsAnswer.None"], "id": ["None", "3"], "answer_question_id": ["None", "pms.Answer.None"], "question": ["None", "What skills or behaviors do you think employee could improve to be even more effective?"], "question_type": ["None", "4"], "created_at": ["None", "2024-12-10 03:16:18.905000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"], "question_options": ["None", "pms.QuestionOptions.None"]}


object_pk: 1
object_repr: QuestionOptions object (1)
timestamp: 2024-12-26 11:44:53.411164
remote_addr: 127.0.0.1
changes:
  {"option_d": ["None", "Nothing"], "question_id": ["None", "3"], "option_a": ["None", "Coding"], "id": ["None", "1"], "option_c": ["None", "Meeting"], "created_at": ["None", "2024-12-10 03:16:18.925000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "option_b": ["None", "Communication"], "is_active": ["None", "True"]}


object_pk: 1
object_repr: Isabella - Isabella Feedback
timestamp: 2024-12-26 11:44:53.422335
remote_addr: 127.0.0.1
changes:
  {"feedback_answer": ["None", "pms.Answer.None"], "review_cycle": ["None", "Isabella Feedback"], "manager_id": ["None", "13"], "employee_id": ["None", "14"], "question_template_id": ["None", "1"], "status": ["None", "Not Started"], "archive": ["None", "False"], "start_date": ["None", "2024-11-01"], "end_date": ["None", "2024-11-30"], "cyclic_feedback": ["None", "False"], "id": ["None", "1"], "created_at": ["None", "2024-12-10 03:17:18.931000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"], "feedback_key_result": ["None", "pms.KeyResultFeedback.None"]}


object_pk: 1
object_repr: Isabella - Isabella Feedback
timestamp: 2024-12-26 11:44:53.429330
remote_addr: 127.0.0.1
changes:
  {"colleague_id": {"type": "m2m", "operation": "add", "objects": ["Charlotte White (PEP19)", "Grace Allen (PEP21)"]}}


object_pk: 1
object_repr: Horilla Technical Meeting
timestamp: 2024-12-26 11:44:53.443921
remote_addr: 127.0.0.1
changes:
  {"id": ["None", "1"], "title": ["None", "Horilla Technical Meeting"], "date": ["None", "2024-12-12 04:30:00"], "question_template": ["None", "1"], "meeting_answer": ["None", "pms.MeetingsAnswer.None"], "show_response": ["None", "False"], "created_at": ["None", "2024-12-10 03:20:51.009000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 1
object_repr: Horilla Technical Meeting
timestamp: 2024-12-26 11:44:53.457486
remote_addr: 127.0.0.1
changes:
  {"employee_id": {"type": "m2m", "operation": "add", "objects": ["Abigail Roberts (PEP15)", "Adam Luis (PEP00)", "Aiden Murphy (PEP40)", "Alexander Smith (PEP16)"]}}


object_pk: 1
object_repr: Horilla Technical Meeting
timestamp: 2024-12-26 11:44:53.479806
remote_addr: 127.0.0.1
changes:
  {"answer_employees": {"type": "m2m", "operation": "add", "objects": ["Abigail Roberts (PEP15)", "Aiden Murphy (PEP40)", "Alexander Smith (PEP16)"]}}


object_pk: 1
object_repr: Single Filers
timestamp: 2024-12-26 11:44:53.562840
remote_addr: 127.0.0.1
changes:
  {"filing_status": ["None", "Single Filers"], "based_on": ["None", "taxable_gross_pay"], "use_py": ["None", "False"], "python_code": ["None", "\"\"\"\nfederal_tax.py\n\"\"\"\n\nYEARLY_TAXABLE_INCOME = 189000.52\n\n\ndef calcluate_federal_tax(yearly_income: int, **kwargs) -> float:\n    \"\"\"\n    Federal Tax calculation method\n\n    yearly_income: The early converted 'based on' amount\n\n    eg: yearly_income-> 189000 then taxable_amount-> 39312.0 (yearly)\n    \"\"\"\n\n    def filter_brackets(brackets: list) -> list:\n        \"\"\"\n        This method to filter out the actual brackets/brackets range\n        \"\"\"\n        # brackets that contains actual bracket range, calculated_rate, and diff amount\n        filterd_brackets = []\n        for bracket in brackets:\n            if bracket[\"max\"] > bracket[\"min\"]:\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725}\n\n                # finding diff amount and adding to the bracket\n                bracket[\"diff\"] = bracket[\"max\"] - bracket[\"min\"]\n                # find bracket rate from the difference and adding to bracket\n                bracket[\"calculated_rate\"] = (bracket[\"rate\"] / 100) * bracket[\"diff\"]\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725, 'diff': 33725, 'calculated_rate': 4047.0}\n\n                filterd_brackets.append(bracket)\n                continue\n            # returning valid filtered brackets\n            return filterd_brackets\n        # returning valid filtered brackets\n        return filterd_brackets\n\n    # filter_brackets method/function will sort out the brackets\n\n    # for example for the 189000 yearly income come in the 32% group,\n    # so the final the max considered as min(231250,189000) which is 189000\n    brackets = [\n        {\"rate\": 10, \"min\": 0, \"max\": min(11000, yearly_income)},\n        {\"rate\": 12, \"min\": 11000, \"max\": min(44725, yearly_income)},\n        {\"rate\": 22, \"min\": 44725, \"max\": min(95375, yearly_income)},\n        {\"rate\": 24, \"min\": 95375, \"max\": min(182100, yearly_income)},\n        {\"rate\": 32, \"min\": 182100, \"max\": min(231250, yearly_income)},\n        {\"rate\": 35, \"min\": 231250, \"max\": min(578125, yearly_income)},\n        {\"rate\": 37, \"min\": 578125, \"max\": max(578125, yearly_income)},\n    ]\n\n    # filtering the brackets to actual range\n    brackets = filter_brackets(brackets=brackets)\n\n    # finding yearly taxable amount\n    taxable_amount = sum(bracket[\"calculated_rate\"] for bracket in brackets)\n\n    \"\"\"\n    use formated_result method to print the table\n    \"\"\"\n    # formated_result(brackets=brackets, taxable_amount=taxable_amount)\n\n    # returning the taxable amount later on the yearly taxable amount-\n    # is converted to daily and calculate federal tax for the total days between the\n    # Payslip period\n    return taxable_amount\n\n\ndef formated_result(brackets: dict, taxable_amount: float) -> None:\n    \"\"\"\n    It will print the brackets such a formated way\n    \"\"\"\n    col_width = 7\n    print(\"----------------------Brackets----------------------\")\n    print(\n        f\"|{'Rate':<{col_width}}  |{'Min':<{col_width}} |{'Max':<{col_width}}  |{'Taxable':<{col_width}}  |{'Bracket Tax':<{col_width}} |\"\n    )\n\n    for bracket in brackets:\n        print(\n            f\"|{bracket['rate']:<{col_width}}% |{bracket['min']:<{col_width}} | {bracket['max']:<{col_width}} | {bracket['diff']:<{col_width}} | {round(bracket['calculated_rate'],2):<{col_width + 3}} |\"\n        )\n\n    print(f\"|             YEARLY TAXABLE INCOME    | {taxable_amount}    |\")\n    print(\"----------------------------------------------------\")\n\n\nmonth_taxable = calcluate_federal_tax(YEARLY_TAXABLE_INCOME)\nprint(\"YEARLY TAXABLE AMOUNT\", month_taxable)"], "description": ["None", ""], "contracts": ["None", "payroll.Contract.None"], "id": ["None", "1"], "created_at": ["None", "2024-11-21 08:42:22.725000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 2
object_repr: Married Filing Separately(MFS)
timestamp: 2024-12-26 11:44:53.567678
remote_addr: 127.0.0.1
changes:
  {"filing_status": ["None", "Married Filing Separately(MFS)"], "based_on": ["None", "taxable_gross_pay"], "use_py": ["None", "False"], "python_code": ["None", "\"\"\"\nfederal_tax.py\n\"\"\"\n\nYEARLY_TAXABLE_INCOME = 189000.52\n\n\ndef calcluate_federal_tax(yearly_income: int, **kwargs) -> float:\n    \"\"\"\n    Federal Tax calculation method\n\n    yearly_income: The early converted 'based on' amount\n\n    eg: yearly_income-> 189000 then taxable_amount-> 39312.0 (yearly)\n    \"\"\"\n\n    def filter_brackets(brackets: list) -> list:\n        \"\"\"\n        This method to filter out the actual brackets/brackets range\n        \"\"\"\n        # brackets that contains actual bracket range, calculated_rate, and diff amount\n        filterd_brackets = []\n        for bracket in brackets:\n            if bracket[\"max\"] > bracket[\"min\"]:\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725}\n\n                # finding diff amount and adding to the bracket\n                bracket[\"diff\"] = bracket[\"max\"] - bracket[\"min\"]\n                # find bracket rate from the difference and adding to bracket\n                bracket[\"calculated_rate\"] = (bracket[\"rate\"] / 100) * bracket[\"diff\"]\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725, 'diff': 33725, 'calculated_rate': 4047.0}\n\n                filterd_brackets.append(bracket)\n                continue\n            # returning valid filtered brackets\n            return filterd_brackets\n        # returning valid filtered brackets\n        return filterd_brackets\n\n    # filter_brackets method/function will sort out the brackets\n\n    # for example for the 189000 yearly income come in the 32% group,\n    # so the final the max considered as min(231250,189000) which is 189000\n    brackets = [\n        {\"rate\": 10, \"min\": 0, \"max\": min(11000, yearly_income)},\n        {\"rate\": 12, \"min\": 11000, \"max\": min(44725, yearly_income)},\n        {\"rate\": 22, \"min\": 44725, \"max\": min(95375, yearly_income)},\n        {\"rate\": 24, \"min\": 95375, \"max\": min(182100, yearly_income)},\n        {\"rate\": 32, \"min\": 182100, \"max\": min(231250, yearly_income)},\n        {\"rate\": 35, \"min\": 231250, \"max\": min(578125, yearly_income)},\n        {\"rate\": 37, \"min\": 578125, \"max\": max(578125, yearly_income)},\n    ]\n\n    # filtering the brackets to actual range\n    brackets = filter_brackets(brackets=brackets)\n\n    # finding yearly taxable amount\n    taxable_amount = sum(bracket[\"calculated_rate\"] for bracket in brackets)\n\n    \"\"\"\n    use formated_result method to print the table\n    \"\"\"\n    # formated_result(brackets=brackets, taxable_amount=taxable_amount)\n\n    # returning the taxable amount later on the yearly taxable amount-\n    # is converted to daily and calculate federal tax for the total days between the\n    # Payslip period\n    return taxable_amount\n\n\ndef formated_result(brackets: dict, taxable_amount: float) -> None:\n    \"\"\"\n    It will print the brackets such a formated way\n    \"\"\"\n    col_width = 7\n    print(\"----------------------Brackets----------------------\")\n    print(\n        f\"|{'Rate':<{col_width}}  |{'Min':<{col_width}} |{'Max':<{col_width}}  |{'Taxable':<{col_width}}  |{'Bracket Tax':<{col_width}} |\"\n    )\n\n    for bracket in brackets:\n        print(\n            f\"|{bracket['rate']:<{col_width}}% |{bracket['min']:<{col_width}} | {bracket['max']:<{col_width}} | {bracket['diff']:<{col_width}} | {round(bracket['calculated_rate'],2):<{col_width + 3}} |\"\n        )\n\n    print(f\"|             YEARLY TAXABLE INCOME    | {taxable_amount}    |\")\n    print(\"----------------------------------------------------\")\n\n\nmonth_taxable = calcluate_federal_tax(YEARLY_TAXABLE_INCOME)\nprint(\"YEARLY TAXABLE AMOUNT\", month_taxable)"], "description": ["None", ""], "contracts": ["None", "payroll.Contract.None"], "id": ["None", "2"], "created_at": ["None", "2024-11-21 08:42:28.019000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 3
object_repr: Married Filing Jointly (MFJ)
timestamp: 2024-12-26 11:44:53.572007
remote_addr: 127.0.0.1
changes:
  {"filing_status": ["None", "Married Filing Jointly (MFJ)"], "based_on": ["None", "taxable_gross_pay"], "use_py": ["None", "False"], "python_code": ["None", "\"\"\"\nfederal_tax.py\n\"\"\"\n\nYEARLY_TAXABLE_INCOME = 189000.52\n\n\ndef calcluate_federal_tax(yearly_income: int, **kwargs) -> float:\n    \"\"\"\n    Federal Tax calculation method\n\n    yearly_income: The early converted 'based on' amount\n\n    eg: yearly_income-> 189000 then taxable_amount-> 39312.0 (yearly)\n    \"\"\"\n\n    def filter_brackets(brackets: list) -> list:\n        \"\"\"\n        This method to filter out the actual brackets/brackets range\n        \"\"\"\n        # brackets that contains actual bracket range, calculated_rate, and diff amount\n        filterd_brackets = []\n        for bracket in brackets:\n            if bracket[\"max\"] > bracket[\"min\"]:\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725}\n\n                # finding diff amount and adding to the bracket\n                bracket[\"diff\"] = bracket[\"max\"] - bracket[\"min\"]\n                # find bracket rate from the difference and adding to bracket\n                bracket[\"calculated_rate\"] = (bracket[\"rate\"] / 100) * bracket[\"diff\"]\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725, 'diff': 33725, 'calculated_rate': 4047.0}\n\n                filterd_brackets.append(bracket)\n                continue\n            # returning valid filtered brackets\n            return filterd_brackets\n        # returning valid filtered brackets\n        return filterd_brackets\n\n    # filter_brackets method/function will sort out the brackets\n\n    # for example for the 189000 yearly income come in the 32% group,\n    # so the final the max considered as min(231250,189000) which is 189000\n    brackets = [\n        {\"rate\": 10, \"min\": 0, \"max\": min(11000, yearly_income)},\n        {\"rate\": 12, \"min\": 11000, \"max\": min(44725, yearly_income)},\n        {\"rate\": 22, \"min\": 44725, \"max\": min(95375, yearly_income)},\n        {\"rate\": 24, \"min\": 95375, \"max\": min(182100, yearly_income)},\n        {\"rate\": 32, \"min\": 182100, \"max\": min(231250, yearly_income)},\n        {\"rate\": 35, \"min\": 231250, \"max\": min(578125, yearly_income)},\n        {\"rate\": 37, \"min\": 578125, \"max\": max(578125, yearly_income)},\n    ]\n\n    # filtering the brackets to actual range\n    brackets = filter_brackets(brackets=brackets)\n\n    # finding yearly taxable amount\n    taxable_amount = sum(bracket[\"calculated_rate\"] for bracket in brackets)\n\n    \"\"\"\n    use formated_result method to print the table\n    \"\"\"\n    # formated_result(brackets=brackets, taxable_amount=taxable_amount)\n\n    # returning the taxable amount later on the yearly taxable amount-\n    # is converted to daily and calculate federal tax for the total days between the\n    # Payslip period\n    return taxable_amount\n\n\ndef formated_result(brackets: dict, taxable_amount: float) -> None:\n    \"\"\"\n    It will print the brackets such a formated way\n    \"\"\"\n    col_width = 7\n    print(\"----------------------Brackets----------------------\")\n    print(\n        f\"|{'Rate':<{col_width}}  |{'Min':<{col_width}} |{'Max':<{col_width}}  |{'Taxable':<{col_width}}  |{'Bracket Tax':<{col_width}} |\"\n    )\n\n    for bracket in brackets:\n        print(\n            f\"|{bracket['rate']:<{col_width}}% |{bracket['min']:<{col_width}} | {bracket['max']:<{col_width}} | {bracket['diff']:<{col_width}} | {round(bracket['calculated_rate'],2):<{col_width + 3}} |\"\n        )\n\n    print(f\"|             YEARLY TAXABLE INCOME    | {taxable_amount}    |\")\n    print(\"----------------------------------------------------\")\n\n\nmonth_taxable = calcluate_federal_tax(YEARLY_TAXABLE_INCOME)\nprint(\"YEARLY TAXABLE AMOUNT\", month_taxable)"], "description": ["None", ""], "contracts": ["None", "payroll.Contract.None"], "id": ["None", "3"], "created_at": ["None", "2024-11-21 08:42:34.764000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 4
object_repr: Head of Household (HOH)
timestamp: 2024-12-26 11:44:53.576002
remote_addr: 127.0.0.1
changes:
  {"filing_status": ["None", "Head of Household (HOH)"], "based_on": ["None", "taxable_gross_pay"], "use_py": ["None", "False"], "python_code": ["None", "\"\"\"\nfederal_tax.py\n\"\"\"\n\nYEARLY_TAXABLE_INCOME = 189000.52\n\n\ndef calcluate_federal_tax(yearly_income: int, **kwargs) -> float:\n    \"\"\"\n    Federal Tax calculation method\n\n    yearly_income: The early converted 'based on' amount\n\n    eg: yearly_income-> 189000 then taxable_amount-> 39312.0 (yearly)\n    \"\"\"\n\n    def filter_brackets(brackets: list) -> list:\n        \"\"\"\n        This method to filter out the actual brackets/brackets range\n        \"\"\"\n        # brackets that contains actual bracket range, calculated_rate, and diff amount\n        filterd_brackets = []\n        for bracket in brackets:\n            if bracket[\"max\"] > bracket[\"min\"]:\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725}\n\n                # finding diff amount and adding to the bracket\n                bracket[\"diff\"] = bracket[\"max\"] - bracket[\"min\"]\n                # find bracket rate from the difference and adding to bracket\n                bracket[\"calculated_rate\"] = (bracket[\"rate\"] / 100) * bracket[\"diff\"]\n\n                # bracket: {'rate': 12, 'min': 11000, 'max': 44725, 'diff': 33725, 'calculated_rate': 4047.0}\n\n                filterd_brackets.append(bracket)\n                continue\n            # returning valid filtered brackets\n            return filterd_brackets\n        # returning valid filtered brackets\n        return filterd_brackets\n\n    # filter_brackets method/function will sort out the brackets\n\n    # for example for the 189000 yearly income come in the 32% group,\n    # so the final the max considered as min(231250,189000) which is 189000\n    brackets = [\n        {\"rate\": 10, \"min\": 0, \"max\": min(11000, yearly_income)},\n        {\"rate\": 12, \"min\": 11000, \"max\": min(44725, yearly_income)},\n        {\"rate\": 22, \"min\": 44725, \"max\": min(95375, yearly_income)},\n        {\"rate\": 24, \"min\": 95375, \"max\": min(182100, yearly_income)},\n        {\"rate\": 32, \"min\": 182100, \"max\": min(231250, yearly_income)},\n        {\"rate\": 35, \"min\": 231250, \"max\": min(578125, yearly_income)},\n        {\"rate\": 37, \"min\": 578125, \"max\": max(578125, yearly_income)},\n    ]\n\n    # filtering the brackets to actual range\n    brackets = filter_brackets(brackets=brackets)\n\n    # finding yearly taxable amount\n    taxable_amount = sum(bracket[\"calculated_rate\"] for bracket in brackets)\n\n    \"\"\"\n    use formated_result method to print the table\n    \"\"\"\n    # formated_result(brackets=brackets, taxable_amount=taxable_amount)\n\n    # returning the taxable amount later on the yearly taxable amount-\n    # is converted to daily and calculate federal tax for the total days between the\n    # Payslip period\n    return taxable_amount\n\n\ndef formated_result(brackets: dict, taxable_amount: float) -> None:\n    \"\"\"\n    It will print the brackets such a formated way\n    \"\"\"\n    col_width = 7\n    print(\"----------------------Brackets----------------------\")\n    print(\n        f\"|{'Rate':<{col_width}}  |{'Min':<{col_width}} |{'Max':<{col_width}}  |{'Taxable':<{col_width}}  |{'Bracket Tax':<{col_width}} |\"\n    )\n\n    for bracket in brackets:\n        print(\n            f\"|{bracket['rate']:<{col_width}}% |{bracket['min']:<{col_width}} | {bracket['max']:<{col_width}} | {bracket['diff']:<{col_width}} | {round(bracket['calculated_rate'],2):<{col_width + 3}} |\"\n        )\n\n    print(f\"|             YEARLY TAXABLE INCOME    | {taxable_amount}    |\")\n    print(\"----------------------------------------------------\")\n\n\nmonth_taxable = calcluate_federal_tax(YEARLY_TAXABLE_INCOME)\nprint(\"YEARLY TAXABLE AMOUNT\", month_taxable)"], "description": ["None", ""], "contracts": ["None", "payroll.Contract.None"], "id": ["None", "4"], "created_at": ["None", "2024-11-21 08:42:40.096000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: 1
object_repr: House Rent Allowance (HRA)
timestamp: 2024-12-26 11:44:53.583387
remote_addr: 127.0.0.1
changes:
  {"only_show_under_employee": ["None", "False"], "is_loan": ["None", "False"], "work_type_per_attendance_amount": ["None", "0.0"], "created_at": ["None", "2024-11-21 08:35:27.289000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"], "title": ["None", "House Rent Allowance (HRA)"], "include_active_employees": ["None", "True"], "is_taxable": ["None", "True"], "is_condition_based": ["None", "False"], "id": ["None", "1"], "is_fixed": ["None", "False"], "based_on": ["None", "basic_pay"], "rate": ["None", "4.5"], "per_attendance_fixed_amount": ["None", "0.0"], "per_children_fixed_amount": ["None", "0.0"], "shift_per_attendance_amount": ["None", "0.0"], "amount_per_one_hr": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"]}


object_pk: 1
object_repr: House Rent Allowance (HRA)
timestamp: 2024-12-26 11:44:53.596622
remote_addr: 127.0.0.1
changes:
  {"specific_employees": {"type": "m2m", "operation": "add", "objects": ["Christopher Miller (PEP12)", "Daniel Foster (PEP06)", "David King (PEP10)", "Demetria Abbey (PEP123)", "Dewitt Borger (PEP110)", "Ethan Gonzalez (PEP30)", "Etta Hurn (PEP82)", "Evelyn Garcia (PEP29)", "Harper Edwards (PEP27)", "Hazel Adams (PEP57)", "Henry Lewis (PEP36)", "Holly Eudy (PEP97)"]}}


object_pk: 2
object_repr: Meal Allowance
timestamp: 2024-12-26 11:44:53.608924
remote_addr: 127.0.0.1
changes:
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object_pk: 4
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object_pk: 5
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object_repr: Emergency Loan - 2025-01-01
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object_pk: 12
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object_pk: 13
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object_pk: 14
object_repr: Emergency Loan - 2025-11-01
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object_pk: 16
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object_pk: 18
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object_pk: 19
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object_pk: 20
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remote_addr: 127.0.0.1
changes:
  {"only_show_under_employee": ["None", "True"], "is_loan": ["None", "True"], "work_type_per_attendance_amount": ["None", "0.0"], "created_at": ["None", "2024-12-26 11:44:54.114219"], "is_active": ["None", "True"], "title": ["None", "Medical Loan"], "one_time_date": ["None", "2024-12-01"], "include_active_employees": ["None", "False"], "is_taxable": ["None", "True"], "is_condition_based": ["None", "False"], "id": ["None", "5"], "is_fixed": ["None", "True"], "amount": ["None", "60000.0"], "based_on": ["None", "basic_pay"], "per_attendance_fixed_amount": ["None", "0.0"], "per_children_fixed_amount": ["None", "0.0"], "shift_per_attendance_amount": ["None", "0.0"], "amount_per_one_hr": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"]}


object_pk: 22
object_repr: Medical Loan - 2025-01-01
timestamp: 2024-12-26 11:44:54.177168
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-01-01"], "one_time_date": ["None", "2025-01-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.176149"], "is_active": ["None", "True"], "id": ["None", "22"]}


object_pk: 23
object_repr: Medical Loan - 2025-02-01
timestamp: 2024-12-26 11:44:54.206333
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-02-01"], "one_time_date": ["None", "2025-02-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.205335"], "is_active": ["None", "True"], "id": ["None", "23"]}


object_pk: 24
object_repr: Medical Loan - 2025-03-01
timestamp: 2024-12-26 11:44:54.228311
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-03-01"], "one_time_date": ["None", "2025-03-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.228311"], "is_active": ["None", "True"], "id": ["None", "24"]}


object_pk: 25
object_repr: Medical Loan - 2025-04-01
timestamp: 2024-12-26 11:44:54.249048
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-04-01"], "one_time_date": ["None", "2025-04-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.248529"], "is_active": ["None", "True"], "id": ["None", "25"]}


object_pk: 26
object_repr: Medical Loan - 2025-05-01
timestamp: 2024-12-26 11:44:54.265151
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-05-01"], "one_time_date": ["None", "2025-05-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.263484"], "is_active": ["None", "True"], "id": ["None", "26"]}


object_pk: 27
object_repr: Medical Loan - 2025-06-01
timestamp: 2024-12-26 11:44:54.290565
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-06-01"], "one_time_date": ["None", "2025-06-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.289566"], "is_active": ["None", "True"], "id": ["None", "27"]}


object_pk: 28
object_repr: Medical Loan - 2025-07-01
timestamp: 2024-12-26 11:44:54.314766
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-07-01"], "one_time_date": ["None", "2025-07-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.312251"], "is_active": ["None", "True"], "id": ["None", "28"]}


object_pk: 29
object_repr: Medical Loan - 2025-08-01
timestamp: 2024-12-26 11:44:54.346091
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-08-01"], "one_time_date": ["None", "2025-08-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.345099"], "is_active": ["None", "True"], "id": ["None", "29"]}


object_pk: 30
object_repr: Medical Loan - 2025-09-01
timestamp: 2024-12-26 11:44:54.365640
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-09-01"], "one_time_date": ["None", "2025-09-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.364629"], "is_active": ["None", "True"], "id": ["None", "30"]}


object_pk: 31
object_repr: Medical Loan - 2025-10-01
timestamp: 2024-12-26 11:44:54.385880
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-10-01"], "one_time_date": ["None", "2025-10-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.383769"], "is_active": ["None", "True"], "id": ["None", "31"]}


object_pk: 32
object_repr: Medical Loan - 2025-11-01
timestamp: 2024-12-26 11:44:54.409425
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-11-01"], "one_time_date": ["None", "2025-11-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.408260"], "is_active": ["None", "True"], "id": ["None", "32"]}


object_pk: 33
object_repr: Medical Loan - 2025-12-01
timestamp: 2024-12-26 11:44:54.439157
remote_addr: 127.0.0.1
changes:
  {"title": ["None", "Medical Loan - 2025-12-01"], "one_time_date": ["None", "2025-12-01"], "include_active_employees": ["None", "False"], "is_tax": ["None", "False"], "is_pretax": ["None", "True"], "is_condition_based": ["None", "False"], "is_fixed": ["None", "True"], "amount": ["None", "5000.0"], "rate": ["None", "0.0"], "employer_rate": ["None", "0.0"], "has_max_limit": ["None", "False"], "maximum_unit": ["None", "month_working_days"], "if_choice": ["None", "basic_pay"], "if_condition": ["None", "gt"], "if_amount": ["None", "0.0"], "only_show_under_employee": ["None", "True"], "is_installment": ["None", "True"], "created_at": ["None", "2024-12-26 11:44:54.436143"], "is_active": ["None", "True"], "id": ["None", "33"]}


object_pk: 1
object_repr: Medical Loan - Grace Allen (PEP21)
timestamp: 2024-12-26 11:44:54.508796
remote_addr: 127.0.0.1
changes:
  {"deduction_ids": {"type": "m2m", "operation": "add", "objects": ["Medical Loan - 2025-01-01", "Medical Loan - 2025-02-01", "Medical Loan - 2025-03-01", "Medical Loan - 2025-04-01", "Medical Loan - 2025-05-01", "Medical Loan - 2025-06-01", "Medical Loan - 2025-07-01", "Medical Loan - 2025-08-01", "Medical Loan - 2025-09-01", "Medical Loan - 2025-10-01", "Medical Loan - 2025-11-01", "Medical Loan - 2025-12-01"]}}


object_pk: 1
object_repr: Medical Loan - Grace Allen (PEP21)
timestamp: 2024-12-26 11:44:54.510735
remote_addr: 127.0.0.1
changes:
  {"type": ["None", "loan"], "title": ["None", "Medical Loan"], "employee_id": ["None", "18"], "loan_amount": ["None", "60000.0"], "provided_date": ["None", "2024-12-01"], "allowance_id": ["None", "5"], "description": ["None", "Loan for parents medical case"], "is_fixed": ["None", "True"], "rate": ["None", "0.0"], "installment_amount": ["None", "5000.0"], "installments": ["None", "12"], "installment_start_date": ["None", "2025-01-01"], "apply_on": ["None", "end_of_month"], "settled": ["None", "False"], "created_at": ["None", "2024-12-12 09:45:26.097000"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"], "id": ["None", "1"]}


object_pk: 6f1h31mp2e0dnyzp8b77y3ji26vvfqdz
object_repr: 6f1h31mp2e0dnyzp8b77y3ji26vvfqdz
timestamp: 2024-12-26 11:44:54.610555
changes:
  {"expire_date": ["None", "2025-01-09 11:44:54.607009"], "session_key": ["None", "6f1h31mp2e0dnyzp8b77y3ji26vvfqdz"], "session_data": ["None", "eyJ0aXRsZSI6IkRBU0hCT0FSRCJ9:1tQmIQ:FV1YLcy0J0uiQADoonrAxwK8fk2tmnGPeSWCxvS9YGg"]}


object_pk: xlvaa4q8x2ack4lh6al9nkx1qfevgtbx
object_repr: xlvaa4q8x2ack4lh6al9nkx1qfevgtbx
timestamp: 2024-12-26 11:45:04.250393
remote_addr: 127.0.0.1
changes:
  {"expire_date": ["None", "2025-01-09 11:45:04.238684"], "session_key": ["None", "xlvaa4q8x2ack4lh6al9nkx1qfevgtbx"], "session_data": ["None", "e30:1tQmIa:TlhxMZNVtfT0n-3cXRt264vcX_LcnFYAt1elix3q88U"]}


object_pk: 2
object_repr: AttendanceGeneralSetting object (2)
timestamp: 2024-12-26 11:45:04.806148
remote_addr: 127.0.0.1
changes:
  {"id": ["None", "2"], "time_runner": ["None", "True"], "enable_check_in": ["None", "True"], "company_id": ["None", "1"], "created_at": ["None", "2024-12-26 11:45:04.804779"], "created_by": ["None", "1"], "modified_by": ["None", "1"], "is_active": ["None", "True"]}


object_pk: ezev93fq35fnqlxbrxfanx531vlgb6ah
object_repr: ezev93fq35fnqlxbrxfanx531vlgb6ah
timestamp: 2024-12-26 11:45:11.092405
changes:
  {"expire_date": ["None", "2025-01-09 11:45:11.082461"], "session_key": ["None", "ezev93fq35fnqlxbrxfanx531vlgb6ah"], "session_data": ["None", "eyJ0aXRsZSI6IkFUVEVOREFOQ0UifQ:1tQmIh:uK5GdmqbwzSzviihG2y4NQnqBXXcVRmumRhWdOdU300"]}


object_pk: dhwnw1xc4f9immxyctvqwxoa9jicjnba
object_repr: dhwnw1xc4f9immxyctvqwxoa9jicjnba
timestamp: 2024-12-26 11:46:26.522147
changes:
  {"expire_date": ["None", "2025-01-09 11:46:26.519316"], "session_key": ["None", "dhwnw1xc4f9immxyctvqwxoa9jicjnba"], "session_data": ["None", "eyJ0aXRsZSI6IlBBWVJPTEwifQ:1tQmJu:mea78ZZ-GIXJFlfYFs_KoqsXqU79eAIVRdRzpDYwX98"]}


# base_dashboardemployeecharts

created_at: 2024-11-21 11:23:17.664000
charts:
  ["overall_leave_chart", "attendance_analytic", "hours_chart", "employees_chart", "department_chart", "gender_chart", "objective_status", "key_result_status", "feedback_status"]


# base_horillamailtemplate

created_at: 2024-11-05 09:39:13.733000
title: Offer letter
body:
  <p style="font-size: 12.8px; text-align: center;"><span style="font-weight: bolder;"><span style="font-family: &quot;Courier New&quot;; font-size: 24px;">Congratulations! Job Offer at {{instance.get_company}}</span></span></p><p style="font-size: 12.8px;">username:{{instance.get_email}}</p><p style="font-size: 12.8px;">password:{{instance.phone}}</p><p style="font-size: 12.8px;"><i><span style="font-size: 14px;">Dear {{instance.get_full_name}},</span></i></p><p style="font-size: 12.8px;">&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; I am delighted to extend an official offer of employment to you for the position of [Job Title] at [Company Name]. We were thoroughly impressed with your skills, experience, and the passion you demonstrated during the interview process.</p><p style="font-size: 12.8px;"><span style="font-size: 12.8px;">Here are the details of your job offer:&nbsp;</span></p><p style="font-size: 12.8px;"><span style="font-size: 12.8px;">&nbsp; &nbsp; Job Position: {{instance.get_job_position}}</span></p><p style="font-size: 12.8px;"><span style="font-size: 12.8px;">We believe that your unique talents will make a significant contribution to our team, and we are thrilled about the prospect of you joining us. Please take the time to review the attached detailed job description, as well as the terms and conditions outlined in the employment contract.</span><br></p><p style="font-size: 12.8px;"><span style="font-size: 12.8px;">To signify your acceptance of this job offer, please confirm your agreement by [Date to Respond]. If you have any questions or need further clarification, feel free to contact me directly</span><br></p><p style="font-size: 12.8px;"><span style="font-size: 12.8px;">We are excited about the value you will bring to [Company Name], and we eagerly anticipate the positive impact you'll have on our team.</span><br></p><p style="font-size: 12.8px;"><span style="font-size: 12.8px;">Welcome aboard, and we look forward to a successful and fulfilling working relationship!</span><br></p><p style="font-size: 12.8px;"><span style="font-size: 12.8px;">Warm regards,</span></p>


created_at: 2024-12-12 10:23:52.188000
title: Leave Request Mail
body:
  <p>Dear,</p><p>This is to inform you that {{ model_instance.employee_id }} has submitted a leave request for {{model_instance.requested_days}} days. Please take the necessary actions to review and process the request at your earliest convenience.<br><br>If you require any additional information or updates, feel free to communicate directly with {{ model_instance.employee_id }}.<br><br>Thank you for your prompt attention to this matter.</p>


# helpdesk_faq

created_at: 2024-12-12 03:45:00
question: What is the Attendance Module used for?
answer:
  The Attendance Module tracks and manages employee attendance, including check-ins, check-outs, and biometric integration.


created_at: 2024-12-12 03:45:00
question: What is the purpose of Biometric Devices?
answer:
  Biometric devices, such as ZKTeco,Matrix COSEC & Anviz synchronize attendance data automatically for accurate tracking.


created_at: 2024-12-12 04:00:00
question: What is the Employee Profile view used for?
answer:
  The Employee Profile view displays all details about an employee, including personal, work, bank information, and more. It also allows employees to customize visible tabs.


created_at: 2024-12-12 04:00:00
question: How can an employee request a shift change?
answer:
  Employees can request a shift change through the 'Reallocate Shift' option in the Work Type & Shift tab. Admin approval is required for changes.


created_at: 2024-12-12 04:00:00
question: What actions are available in the Employee Directory?
answer:
  The Employee Directory allows actions like importing, exporting, bulk archiving, unarchiving, updating, and deleting employee data.


created_at: 2024-12-12 04:00:00
question: How are document requests handled?
answer:
  Admins or managers create document requests specifying details like title, format, and size. Employees upload documents directly from their profile.


created_at: 2024-12-12 04:00:00
question: What is the Shift Request feature?
answer:
  The Shift Request feature allows employees to request temporary or permanent shift changes. Approval by a manager or admin is required.


created_at: 2024-12-12 04:00:00
question: What is a Rotating Work Type Assign?
answer:
  A Rotating Work Type Assign automates frequent changes in work types based on conditions like intervals, weekends, or specific dates.


created_at: 2024-12-12 04:00:00
question: How can employees manage disciplinary actions?
answer:
  Admins can create disciplinary actions like warnings or suspensions, and these may block employee logins for the specified period.


created_at: 2024-12-12 04:00:00
question: What is the Organization Chart feature?
answer:
  The Organization Chart provides a visual representation of reporting structures, helping to identify team members and managers.


created_at: 2024-12-12 04:00:00
question: What is the Recruitment module in Horilla HRMS?
answer:
  The Recruitment module allows HR professionals to create and manage job postings, receive and review resumes, manage interviews, and track candidate progress throughout the hiring process.


created_at: 2024-12-12 04:00:00
question: What is the Recruitment Pipeline feature?
answer:
  The Recruitment Pipeline is a comprehensive feature that organizes candidates through various stages using tabular and Kanban views. It supports multiple recruitment drives, each represented as a tab for easy management.


created_at: 2024-12-12 04:00:00
question: How can I create a new recruitment in Horilla?
answer:
  To create a new recruitment, click on the '+ Create' button from Recruitment > Recruitments , specify the job position, description, vacancies, managers, start and end dates, and select a recruitment survey.


created_at: 2024-12-12 04:00:00
question: What are the main stage types in the recruitment process?
answer:
  The main stage types are Initial, Interview, Hired, and Cancelled. Each type serves a specific purpose, such as automatically registering candidates or marking them as hired.


created_at: 2024-12-12 04:00:00
question: How do I add a new stage to the recruitment process?
answer:
  To add a new stage, click on the '+ Stage' button from Recruitment Pipeline, provide the stage title, assign stage managers, and specify the stage type (e.g., Initial, Interview, Hired).


created_at: 2024-12-12 04:00:00
question: What is Resume Shortlisting and how does it work?
answer:
  Resume Shortlisting is a feature that uses skill-based keyword optimization to rank resumes. The system calculates scores for each resume based on matching skills and displays them in descending order.


created_at: 2024-12-12 04:00:00
question: What is the Skill Zone feature?
answer:
  The Skill Zone categorizes candidates based on their skills, helping recruiters match them to relevant job positions more efficiently.


created_at: 2024-12-12 04:00:00
question: How can I manage interviews within the Recruitment module?
answer:
  You can manage interviews through the 'Scheduled Interviews' page, where you can add, edit, or delete interviews, assign interviewers, and track the status of interviews.


created_at: 2024-12-12 04:00:00
question: Can I customize application forms in Horilla HRMS?
answer:
  Yes, the Recruitment Survey feature allows HR managers to create custom questionnaires for candidates, which are integrated into the application forms.


created_at: 2024-12-12 04:00:00
question: What are the available views for managing candidates?
answer:
  Candidates can be managed using the Kanban view, list view, and detailed view. These views allow for filtering, grouping, and performing actions like editing, exporting, or converting candidates to employees.


created_at: 2024-12-12 04:00:00
question: What is the Payroll module in Horilla HRMS?
answer:
  The Payroll module in Horilla HRMS enables businesses to manage employee allowances, deductions, taxes, and generate accurate payslips, ensuring streamlined and efficient payroll processes.


created_at: 2024-12-12 04:00:00
question: What features does the Payroll Dashboard offer?
answer:
  The Payroll Dashboard provides visual insights into payroll processes, including charts for payslips, contract details, and department-wise payslips. Managers can also download data as Excel files.


created_at: 2024-12-12 04:00:00
question: How does Contract Management work in Horilla?
answer:
  Contract Management allows users to create contracts, define compensation, set contract duration, and manage leave settings. It supports various wage types for customized work arrangements.


created_at: 2024-12-12 04:00:00
question: What is the Allowance Management feature?
answer:
  Allowance Management enables users to create and customize allowances, set eligibility conditions, and specify fixed or variable allowances. It simplifies targeting allowances to employee groups and ensures fairness.


created_at: 2024-12-12 04:00:00
question: How are deductions managed in Horilla?
answer:
  The Deduction Management feature allows users to create and personalize deductions, set eligibility conditions, and choose fixed or variable amounts. It ensures streamlined deductions and fair practices.


created_at: 2024-12-12 04:00:00
question: What is the Loan and Advance Salary module?
answer:
  This module helps manage employee loans, installments, and advance salary transactions, ensuring accurate and transparent financial dealings.


created_at: 2024-12-12 04:00:00
question: What does the Encashments & Reimbursements feature offer?
answer:
  This feature supports reimbursements for company-related expenses, leave encashments, and bonus point encashments, simplifying the process for diverse employee needs.


created_at: 2024-12-12 04:00:00
question: How does the Federal Tax feature work?
answer:
  The Federal Tax feature automates tax calculations, defines tax brackets, and sets rates based on income. It ensures compliance and smooth payroll processing.


created_at: 2024-12-12 04:00:00
question: How are payslips generated in Horilla?
answer:
  The Payslip Generation feature calculates salaries, including allowances, deductions, and taxes, and creates accurate and detailed payslips for each pay period.


created_at: 2024-12-12 04:00:00
question: What is the Asset Management System in Horilla HRMS?
answer:
  The Asset Management System enables employees to request and manage work-related assets like computers and equipment. It categorizes assets, tracks requests, and ensures efficient allocation.


created_at: 2024-12-12 04:00:00
question: What features are available on the Asset Dashboard?
answer:
  The Asset Dashboard displays the total number of assets, asset requests, and assets in use. It includes pie charts and tables for asset allocation and provides tools for admins to approve requests and allocate assets directly.


created_at: 2024-12-12 04:00:00
question: How can admin search for assets in Horilla HRMS?
answer:
  Admin can search for specific asset categories or individual assets using the search bar. The system dynamically filters results based on the search term.


created_at: 2024-12-12 04:00:00
question: What is the Asset Import feature?
answer:
  The Asset Import feature allows admin to upload large amounts of asset data, such as names, purchase dates, and categories, from an external file like Excel, improving efficiency in asset management.


created_at: 2024-12-12 04:00:00
question: What is the purpose of the Asset Export feature?
answer:
  The Asset Export feature enables admin to download asset data, either filtered or in full, for reporting or further processing.


created_at: 2024-12-12 04:00:00
question: How can asset categories be managed in Horilla HRMS?
answer:
  Admin can create, update, and delete asset categories. Categories can only be deleted if they are empty, ensuring no associated assets remain in use.


created_at: 2024-12-12 04:00:00
question: What is the Asset Request and Allocation feature?
answer:
  This feature allows employees to request new assets or return allocated ones, while admins can allocate or reallocate assets based on requests and availability.


created_at: 2024-12-12 04:00:00
question: What details can be updated in the Asset Updation form?
answer:
  Admin can update details like asset name, description, tracking ID, purchase date, cost, status, and expiry date. Notifications can also be set for upcoming expiry dates.


created_at: 2024-12-12 04:00:00
question: How does Asset History tracking work?
answer:
  The Asset History feature tracks details of returned assets, allowing admin to filter, group, and sort asset usage data as needed.


# recruitment_surveytemplate

created_at: 2024-11-15 04:08:07.657000
title: Odoo Developer Template
description:
  For an Odoo developer interview exam, here are some types of questions that can be asked using the provided


# offboarding_resignationletter

created_at: 2024-11-15 03:45:33.566000
title: Resignation
planned_to_leave_on: 2024-11-30
status: requested
description:
  <p>After much consideration, I have decided to pursue a new opportunity that aligns with my career goals and personal aspirations. Working at Horilla has been an incredibly rewarding experience, and I deeply appreciate the support, guidance, and opportunities for growth provided by the company and my colleagues.</p><p>I am committed to ensuring a smooth transition and will do my best to complete my ongoing tasks and assist in handing over responsibilities. Please let me know how I can support the transition process.</p><p>I want to express my gratitude to the entire team at Horilla for the collaboration, learning, and support throughout my time here. I will cherish the experience and the relationships I have built.</p><p>Thank you once again for the opportunity to be a part of Horilla, and I wish the company continued success in the future.</p>


created_at: 2024-11-15 03:46:37.925000
title: Resignation Letter
planned_to_leave_on: 2024-11-30
status: requested
description:
  <p>This was not an easy decision, but after careful thought, I believe it is the right time for me to explore new professional challenges. My time at Horilla has been an enriching journey, and I am truly grateful for the opportunities I have had to contribute and grow, both professionally and personally.</p><p>I will do my best to ensure a smooth transition and am happy to assist in handing over my current projects or training a replacement if necessary. Please feel free to guide me on how I can assist during this period.</p><p>Thank you once again for the support and for allowing me to be part of such a fantastic team. I wish Horilla continued growth and success, and I look forward to staying connected in the future.</p>


# payroll_filingstatus

created_at: 2024-11-21 08:42:22.725000
filing_status: Single Filers
based_on: taxable_gross_pay
python_code:
  """
  federal_tax.py
  """

  YEARLY_TAXABLE_INCOME = 189000.52


  def calcluate_federal_tax(yearly_income: int, **kwargs) -> float:
      """
      Federal Tax calculation method

      yearly_income: The early converted 'based on' amount

      eg: yearly_income-> 189000 then taxable_amount-> 39312.0 (yearly)
      """

      def filter_brackets(brackets: list) -> list:
          """
          This method to filter out the actual brackets/brackets range
          """
          # brackets that contains actual bracket range, calculated_rate, and diff amount
          filterd_brackets = []
          for bracket in brackets:
              if bracket["max"] > bracket["min"]:

                  # bracket: {'rate': 12, 'min': 11000, 'max': 44725}

                  # finding diff amount and adding to the bracket
                  bracket["diff"] = bracket["max"] - bracket["min"]
                  # find bracket rate from the difference and adding to bracket
                  bracket["calculated_rate"] = (bracket["rate"] / 100) * bracket["diff"]

                  # bracket: {'rate': 12, 'min': 11000, 'max': 44725, 'diff': 33725, 'calculated_rate': 4047.0}

                  filterd_brackets.append(bracket)
                  continue
              # returning valid filtered brackets
              return filterd_brackets
          # returning valid filtered brackets
          return filterd_brackets

      # filter_brackets method/function will sort out the brackets

      # for example for the 189000 yearly income come in the 32% group,
      # so the final the max considered as min(231250,189000) which is 189000
      brackets = [
          {"rate": 10, "min": 0, "max": min(11000, yearly_income)},
          {"rate": 12, "min": 11000, "max": min(44725, yearly_income)},
          {"rate": 22, "min": 44725, "max": min(95375, yearly_income)},
          {"rate": 24, "min": 95375, "max": min(182100, yearly_income)},
          {"rate": 32, "min": 182100, "max": min(231250, yearly_income)},
          {"rate": 35, "min": 231250, "max": min(578125, yearly_income)},
          {"rate": 37, "min": 578125, "max": max(578125, yearly_income)},
      ]

      # filtering the brackets to actual range
      brackets = filter_brackets(brackets=brackets)

      # finding yearly taxable amount
      taxable_amount = sum(bracket["calculated_rate"] for bracket in brackets)

      """
      use formated_result method to print the table
      """
      # formated_result(brackets=brackets, taxable_amount=taxable_amount)

      # returning the taxable amount later on the yearly taxable amount-
      # is converted to daily and calculate federal tax for the total days between the
      # Payslip period
      return taxable_amount


  def formated_result(brackets: dict, taxable_amount: float) -> None:
      """
      It will print the brackets such a formated way
      """
      col_width = 7
      print("----------------------Brackets----------------------")
      print(
          f"|{'Rate':<{col_width}}  |{'Min':<{col_width}} |{'Max':<{col_width}}  |{'Taxable':<{col_width}}  |{'Bracket Tax':<{col_width}} |"
      )

      for bracket in brackets:
          print(
              f"|{bracket['rate']:<{col_width}}% |{bracket['min']:<{col_width}} | {bracket['max']:<{col_width}} | {bracket['diff']:<{col_width}} | {round(bracket['calculated_rate'],2):<{col_width + 3}} |"
          )

      print(f"|             YEARLY TAXABLE INCOME    | {taxable_amount}    |")
      print("----------------------------------------------------")


  month_taxable = calcluate_federal_tax(YEARLY_TAXABLE_INCOME)
  print("YEARLY TAXABLE AMOUNT", month_taxable)


# recruitment_recruitment

created_at: 2024-11-22 08:48:40.136000
title: Recruitment Drive
start_date: 2024-11-01
end_date: 2024-11-30
description:
  <p><b><u><span style="font-size: 18px;">Position: Django Developer &amp; ODOO dev</span></u></b></p><p><b>Job Description:</b></p><p>We are seeking a skilled Django Developers and ODOO developers to join our dynamic team. The ideal candidate will have a strong background in web development with a focus on the Django framework. You will be responsible for designing, building, and maintaining high-performance web applications that are scalable and secure.</p><p><b>Key Responsibilities:</b></p><p>Develop and maintain web applications using Django.</p><p>Write clean, maintainable, and efficient code.</p><p>Design and implement robust APIs.</p><p>Collaborate with front-end developers to integrate user-facing elements.</p><p>Optimize applications for maximum speed and scalability.</p><p>Participate in code reviews to maintain code quality and share knowledge.</p><p>Stay updated with the latest industry trends and technologies.</p><p><b>Requirements:</b></p><p>Proven experience as a Django Developer.</p><p>Proficient in Python and Django framework.</p><p>Familiarity with front-end technologies (JavaScript, HTML5, CSS3).</p><p>Experience with relational databases (PostgreSQL, MySQL).</p><p>Knowledge of version control systems (Git).</p><p>Understanding of RESTful APIs and web services.</p><p>Strong problem-solving skills and attention to detail.</p><p>Excellent communication and teamwork skills.</p><p>BachelorÆs degree in Computer Science, Engineering, or a related field.</p><p><b>Preferred Qualifications:</b></p><p>Experience with cloud platforms (AWS, Azure, GCP).</p><p>Knowledge of containerization and orchestration (Docker, Kubernetes).</p><p>Familiarity with Agile development methodologies.</p>


created_at: 2024-11-22 08:55:43.899000
title: FutureForce Recruitment
start_date: 2024-11-01
end_date: 2024-11-30
description:
  <p>We are looking for a motivated and dynamic <b>Salesman</b> to join our team. The ideal candidate will have a passion for <b>sales, excellent communication skills, and a knack for building relationships with customers</b>. You will play a key role in driving our business growth by meeting sales targets and providing outstanding customer service.<br></p>


created_at: 2024-11-22 09:03:26.892000
title: Hiring Employees
start_date: 2024-11-01
end_date: 2024-11-30
description:
  <p>We are seeking a skilled Django Developer to join our dynamic team. The ideal candidate will have a strong background in web development with a focus on the Django framework. You will be responsible for designing, building, and maintaining high-performance web applications that are scalable and secure.<br></p>


# django_session

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expire_date: 2025-01-09 11:45:11.655477
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expire_date: 2025-01-09 11:46:26.590220
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