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project_management/urls.py
|
wambozaAllan/Sybyl-Service-Desk-Web
| 1
|
6625751
|
<filename>project_management/urls.py
from django.urls import path, re_path
from . import views
# app_name = 'project_management'
urlpatterns = [
path('projects/', views.load_all_projects, name='full_project_list'),
path('ongoing/', views.ProjectListView.as_view(), name='project_list'),
path('ajax/load_selected_projects/', views.load_selected_projects, name='load_selected_projects'),
path('projectdoc', views.model_form_upload, name='model_form_upload'),
path('projectdocs/', views.load_project_documents, name='projectdocs_list'),
path('<int:pk>/', views.ProjectDetailView.as_view(), name='project_details'),
path('complete/', views.CompleteProjectListView.as_view(), name='complete_project_list'),
path('terminated/', views.TerminatedProjectListView.as_view(), name='terminated_project_list'),
path('new/', views.ProjectCreateView.as_view(), name='new_project'),
path('update/<int:pk>/', views.ProjectUpdateView.as_view(), name='update_project'),
path('download-project-csv/', views.projects_download, name='download_projects_csv'),
path('download-project-excel/', views.export_projects_xls, name='export_projects_xls'),
path('milestones/', views.project_milestones_by_user, name='milestone_list'),
path('milestone/detail/<int:pk>/', views.MilestoneDetailView.as_view(), name='milestone_details'),
path('listProjectMilestones/', views.list_project_milestones, name='listProjectMilestones'),
path('populateMilestone/', views.populate_milestone_view, name='populateMilestone'),
path('populateMilestoneStatus/', views.populate_milestone_status, name='populateMilestoneStatus'),
path('saveMilestone', views.save_milestone, name='saveMilestone'),
path('validateMilestoneName', views.validateMilestoneName, name='validateMilestoneName'),
path('updateProjectMilestone/<int:pk>', views.UpdateProjectMilestone.as_view(), name='updateProjectMilestone'),
path('updateOpenMilestone/<int:pk>', views.UpdateOpenMilestone.as_view(), name='updateOpenMilestone'),
path('updateOnholdMilestone/<int:pk>', views.UpdateOnholdMilestone.as_view(), name='updateOnholdMilestone'),
path('updateTerminatedMilestone/<int:pk>', views.UpdateTerminatedMilestone.as_view(), name='updateTerminatedMilestone'),
path('updateCompletedMilestone/<int:pk>', views.UpdateCompletedMilestone.as_view(), name='updateCompletedMilestone'),
path('detailsProjectMilestone/<int:pk>', views.DetailsProjectMilestone.as_view(), name='detailsProjectMilestone'),
path('checkMilestoneStatus/', views.check_milestone_status, name='checkMilestoneStatus'),
path('deleteProjectMilestone/', views.delete_project_milestone, name='deleteProjectMilestone'),
path('onholdMilestones/', views.onhold_project_milestones, name='onholdMilestones'),
path('openMilestones/', views.open_milestones, name='openMilestones'),
path('terminatedMilestones/', views.terminated_project_milestones, name='terminatedMilestones'),
path('completedMilestones/', views.completed_project_milestones, name='completedMilestones'),
path('saveupdateProjectMilestone/<int:pk>', views.save_update_milestone, name='saveupdateProjectMilestone'),
path('milestoneCount/', views.milestone_count, name='milestoneCount'),
path('milestonesContainer/', views.milestone_container, name='milestonesContainer'),
path('populateTaskView', views.populate_task_view, name='populateTaskView'),
path('createTask', views.create_tasks_by_project, name="createTask"),
path('tasks_list/', views.task_list_by_users, name='task_list'),
path('task/<int:pk>/', views.TaskDetailView.as_view(), name='task_details'),
# re_path(r'^tasks-project/(?P<project_id>\d+)/$', views.task_list_by_project, name='project_task_list'),
re_path(r'^tasks-milestone/(?P<milestone_id>\d+)/$', views.task_list_by_milestone, name='milestone_task_list'),
path('tasks/new/', views.TaskCreateView.as_view(), name='new_task'),
path('task-update/<int:pk>/', views.TaskUpdateView.as_view(), name='update_task'),
path('listProjectTasks', views.tasklist_by_project, name='listProjectTasks'),
path('validateTaskName/', views.validateTaskName, name='validateTaskName'),
path('saveProjectTask', views.save_project_tasks, name='saveProjectTask'),
path('milestoneTasks', views.view_tasks_under_milestone, name='milestoneTasks'),
path('addMilestoneTask', views.add_milestone_specific_task, name='addMilestoneTask'),
path('addMilestoneTasks', views.add_milestone_tasks, name='addMilestoneTasks'),
path('saveMilestoneTask', views.save_milestone_tasks, name='saveMilestoneTask'),
path('updateProjectTask/<int:pk>', views.UpdateProjectTask.as_view(), name='updateProjectTask'),
path('updateMilestoneTask/<int:pk>', views.UpdateMilestoneTask.as_view(), name='updateMilestoneTask'),
path('detailsProjectTask/<int:pk>', views.DetailsProjectTask.as_view(), name='detailsProjectTask'),
path('deleteTask/', views.delete_task, name='deleteTask'),
path('openTasks/', views.open_project_tasks, name="openTasks"),
path('onholdTasks/', views.onhold_tasks, name="onholdTasks"),
path('terminatedTasks/', views.terminated_tasks, name="terminatedTasks"),
path('completedTasks/', views.completed_tasks, name="completedTasks"),
path('updateOpenTask/<int:pk>', views.UpdateOpenTask.as_view(), name='updateOpenTask'),
path('updateCompletedTask/<int:pk>', views.UpdateCompletedTask.as_view(), name='updateCompletedTask'),
path('updateOnholdTask/<int:pk>', views.UpdateOnholdTask.as_view(), name='updateOnholdTask'),
path('updateTerminatedTask/<int:pk>', views.UpdateTerminatedTask.as_view(), name='updateTerminatedTask'),
path('saveupdateProjectTask/<int:pk>', views.save_update_task, name='saveupdateProjectTask'),
path('taskCount/', views.task_count, name='taskCount'),
path('assignedTaskMembers/', views.assigned_task_members, name="assignedTaskMembers"),
path('assignedTaskMembersMilestone/', views.assigned_task_members_milestone, name="assignedTaskMembersMilestone"),
path('assignTaskMembers/', views.assign_task_members, name="assignTaskMembers"),
path('deassignTaskMembers/', views.deassign_task_members, name="deassignTaskMembers"),
path('deassignTaskMembersMilestone/', views.deassign_task_members_milestone, name="deassignTaskMembersMilestone"),
path('checkTeamMembers/', views.check_team_members, name="checkTeamMembers"),
path('checkAssignedTaskMembers/', views.check_assigned_task_members, name="checkAssignedTaskMembers"),
path('saveMembersAssignedTask/', views.save_members_assigned_task, name="saveMembersAssignedTask"),
path('tasks/', views.tasks_container, name="tasksContainer"),
path('saveTeamTasks', views.save_team_project_tasks, name='saveTeamTasks'),
path('addIncident/', views.AddIncident.as_view(), name='addIncident'),
path('addProjectIncident/', views.AddProjectIncident.as_view(), name='addProjectIncident'),
path('incident_list/', views.list_incidents_by_project, name='listIncidents'),
path('listProjectIncidents', views.list_project_incidents, name='listProjectIncidents'),
path('detailsIncident/<int:pk>/', views.DetailsIncident.as_view(), name='detailsIncident'),
path('detailsProjectIncident/<int:pk>/', views.DetailsProjectIncident.as_view(), name='detailsProjectIncident'),
path('updateIncident/<int:pk>/', views.UpdateIncident.as_view(), name='updateIncident'),
path('updateProjectIncident/<int:pk>/', views.UpdateProjectIncident.as_view(), name='updateProjectIncident'),
path('addComment/', views.add_comment, name="addComment"),
path('listIncidentComments/', views.list_incident_comments, name="listIncidentComments"),
path('onholdIncidents/', views.onhold_project_incidents, name="onholdIncidents"),
path('terminatedIncidents/', views.terminated_project_incidents, name="terminatedIncidents"),
path('completedIncidents/', views.completed_project_incidents, name="completedIncidents"),
path('listIncidents/', views.incident_container, name="incidentContainer"),
path('createIncident/', views.create_incident, name="createIncident"),
path('saveIncident/', views.save_incident, name="saveIncident"),
path('listAllPriorities/', views.ListAllPriorities.as_view(), name='listAllPriorities'),
path('addPriority/', views.AddPriority.as_view(), name='addPriority'),
path('updatePriority/<int:pk>/', views.UpdatePriority.as_view(), name='updatePriority'),
path('deletePriority/<int:pk>', views.DeletePriority.as_view(), name="deletePriority"),
path('validatePriorityName/', views.validatePriorityName, name='validatePriorityName'),
path('listAllStatuses/', views.ListAllStatuses.as_view(), name='listAllStatuses'),
path('addStatus/', views.AddStatus.as_view(), name='addStatus'),
path('updateStatus/<int:pk>/', views.UpdateStatus.as_view(), name='updateStatus'),
path('deleteStatus/<int:pk>/', views.DeleteStatus.as_view(), name="deleteStatus"),
path('validateStatusName/', views.ValidateStatusName, name='validateStatusName'),
path('addProject/', views.addProject, name='addProject'),
# path('listProjects/', views.ListProjects.as_view(), name='listProjects'),
path('listProjects/', views.list_projects, name='listProjects'),
path('updateProject/<int:pk>', views.UpdateProject.as_view(), name='updateProject'),
path('detailsProject/<int:pk>', views.DetailProject.as_view(), name='detailsProject'),
path('validateProjectName/', views.validateProjectName, name='validateProjectName'),
path('uploadDocument/', views.upload_document, name="uploadDocument" ),
path('addProjectTeam/', views.add_project_team, name='addProjectTeam'),
path('adminAddProjectTeam/', views.AdminAddProjectTeam.as_view(), name='adminAddProjectTeam'),
path('listProjectTeams/', views.ListProjectTeams.as_view(), name='listProjectTeams'),
path('updateProjectTeam/<int:pk>', views.UpdateProjectTeam.as_view(), name='updateProjectTeam'),
path('deleteProjectTeam/<int:pk>', views.DeleteProjectTeam.as_view(), name='deleteProjectTeam'),
path('validateProjectTeamName/', views.validateProjectTeamName, name='validateProjectTeamName'),
path('validateProjectAssigned/', views.validateProjectAssigned, name='validateProjectAssigned'),
path('addProjectTeamMember/', views.add_project_team_member, name='addProjectTeamMember'),
path('adminAddProjectTeamMember/', views.admin_add_project_team_member, name='adminAddProjectTeamMember'),
path('listProjectTeamMembers/', views.ListProjectTeamMembers.as_view(), name='listProjectTeamMembers'),
path('detailProjectTeamMembers/', views.detail_team_member, name='detailProjectTeamMembers'),
path('adminDetailProjectTeamMembers/', views.admin_detail_team_member, name='adminDetailProjectTeamMembers'),
path('deleteProjectTeamMember/', views.remove_project_team_member, name='deleteProjectTeamMember'),
path('validateProjectTeamAssigned/', views.validateProjectTeamAssigned, name='validateProjectTeamAssigned'),
path('saveTeamMember/', views.save_team_member, name='saveTeamMember'),
path('getTeamMembers/', views.get_team_members, name='getTeamMembers'),
path('setColorCode/', views.set_priority_color_code, name='setColorCode'),
path('projectForum/', views.project_forum, name='tabProjectForum'),
path('createForum/', views.create_project_forum, name='createProjectForum'),
path('forumReplies/', views.manage_forum_replies, name='manageForumReplies'),
path('deleteChatMessage/', views.delete_forum_message, name='deleteChatMessage'),
path('deleteReply/', views.delete_forum_reply, name='deleteChatReply'),
path('listTeam/', views.list_project_team, name='tabListTeam'),
path('viewAssignedMembers/', views.view_assigned_members, name='viewAssignedMembers'),
path('auditlogs/', views.view_audit_logs, name='listauditlogs'),
path('auditlogsfilter/', views.filter_audit_logs, name='auditlogsfilter'),
path('auditlogsfilter2/', views.all_companies_filter_auditlogs, name='auditlogsfilterallcomp'),
# TIMESHEETS
path('addTimesheet/', views.add_new_timesheet, name='addNewTimesheet'),
path('addTimesheetOnCalender/', views.add_new_timesheet_from_calender, name='addTimesheetOnCalender'),
path('addTimesheetOnDatePaginator/', views.add_new_timesheet_from_datepaginator, name='addTimesheetOnDatePaginator'),
path('projectMilestone', views.fetch_milestones_by_project, name='selectMilestonesByProject'),
path('tasksMilestone', views.fetch_tasks_by_milestone, name='selectTasksByMilestone'),
path('myTimesheets/', views.daily_timesheets_pane, name='myTimesheets'),
path('approveTimesheets/', views.approve_timesheet_pane, name='approveTimesheets'),
path('saveTimeSheet', views.save_new_timesheet, name='saveTimeSheet'),
path('updateTimesheet', views.update_timesheet, name='updateTimesheet'),
path('updateTimesheetPaginator', views.update_timesheet_paginator, name='updateTimesheetPaginator'),
path('saveUpdateTimesheet', views.save_update_timesheet, name='saveUpdateTimesheet'),
path('deleteTimesheet', views.delete_timesheet, name='deleteTimesheet'),
path('deleteTimesheetPaginator', views.delete_timesheet_in_paginator, name='deleteTimesheetPaginator'),
path('sendTimesheet', views.send_timesheet_for_approval, name='sendTimesheetForApproval'),
path('sendPaginatorTimesheetForApproval', views.send_timesheet_for_approval_paginator, name='sendPaginatorTimesheetForApproval'),
path('pendingApproval', views.timesheet_pending_approval, name='timesheetPendingApproval'),
path('saveTimesheetApprovals', views.save_timesheet_approvals, name='saveTimesheetApprovals'),
path('approvedTimesheetsTab', views.manage_approved_timesheets, name='approvedTimesheetsTab'),
path('updateTimesheetApproval', views.update_timesheet_approval, name='updateTimesheetApproval'),
path('userApprovedTimesheets', views.view_user_approved_timesheets, name='userApprovedTimesheets'),
path('filterPenddingTimesheets', views.filter_pending_daily_timesheets_by_date, name='filterPendingTimesheets'),
path('filterDailyProvedTimesheets', views.filter_daily_proved_timesheets, name='filterDailyProvedTimesheets'),
path('filterAllUsersPendingTMs', views.filter_all_member_unapproved_timesheets, name='filterAllUsersPendingTMs'),
path('filterAllUsersApprovedTMs', views.filter_all_member_approved_timesheets, name='filterAllUsersApprovedTMs'),
path('analyseAllTimesheets', views.timesheets_report, name='analyseAllTimesheets'),
path('userGeneralTimesheetReport', views.user_general_timesheet_report, name='userGeneralTimesheetReport'),
path('viewTaskDetails/<int:pk>', views.DetailsProjectTask.as_view(), name='viewTaskDetails'),
path('userRejectedTimesheets', views.manage_rejected_timesheets, name='userRejectedTimesheets'),
path('resubmitTimesheet', views.resubmit_timesheet, name='resubmitTimesheet'),
path('saveResentTimesheet', views.save_resent_timesheet, name='saveResentTimesheet'),
path('paginatorResubmitTimesheet', views.paginator_resubmit_timesheet, name='paginatorResubmitTimesheet'),
path('saveResentPaginatorTimesheet', views.save_resent_paginator_timesheet, name='saveResentPaginatorTimesheet'),
path('viewTimesheetResubmissions', views.manage_timesheet_resubmissions, name='viewTimesheetResubmissions'),
path('updateApproverComment', views.update_approver_comment, name='updateApproverComment'),
path('savecalenderTimeSheet', views.save_calender_timesheet, name='savecalenderTimeSheet'),
path('savePaginatorTimeSheet', views.save_paginator_timesheet, name='savePaginatorTimeSheet'),
path('calenderTimesheetView', views.calenderTimesheetView, name='calenderTimesheetView'),
path('timesheetWeeklyReport', views.timesheets_weekly_report, name='timesheetWeeklyReport'),
path('filterTimesheetsByWeek', views.filter_users_timesheets_by_week, name='filterTimesheetsByWeek'),
path('filterTimesheetsByDate', views.filter_timesheets_by_date, name='filterTimesheetsByDate'),
path('tableTimesheetView', views.table_timesheet_view, name='tableTimesheetView'),
path('listTimesheetView', views.list_timesheet_view, name='listTimesheetView'),
path('saveUpdateTimesheetPaginator', views.save_update_paginator_timesheet, name='saveUpdateTimesheetPaginator'),
path('timesheetProjectReport', views.timesheets_project_report, name='timesheetProjectReport'),
path('filterProjectTimesheetsByWeek', views.filter_project_timesheets_by_week, name='filterProjectTimesheetsByWeek'),
path('selectDailyTimesheetsByUser', views.select_daily_timesheets_by_user, name='selectDailyTimesheetsByUser'),
path('selectTableTimesheetsByUser', views.select_table_timesheets_by_user, name='selectTableTimesheetsByUser'),
path('timesheetMonthlyReport', views.timesheet_monthly_report, name='timesheetMonthlyReport'),
path('filterMonthlyTimesheets', views.filter_monthly_timesheets, name='filterMonthlyTimesheets'),
path('filterMonthlyTimesheetsByDate', views.filter_monthly_timesheets_by_date, name='filterMonthlyTimesheetsByDate'),
# Schedules plans
path('schedulePlan', views.timesheets_schedule_pane, name='schedulePlan'),
# REPORTS
path('staffUtilization/', views.staff_utilization, name="staffUtilization"),
path('staffUtilizationReport/', views.staff_utilization_report, name="staffUtilizationReport"),
path('exportReport/', views.export_staff_utilization, name="exportReport"),
path('exportPdf/', views.export_pdf_utilization, name="exportPdf"),
path('taskReport/', views.task_report_page, name="taskReport"),
path('exportTaskReport/', views.export_task_report, name="exportTaskReport"),
path('previewTaskReport/', views.preview_task_report, name="previewTaskReport"),
# Project code
path('listCodeFormat/', views.ListCodeFormat.as_view(), name='listCodeFormat'),
path('addCodeFormat/', views.AddCodeFormat.as_view(), name='addCodeFormat'),
path('updateCodeFormat/<int:pk>/', views.UpdateCodeFormat.as_view(), name='updateCodeFormat'),
path('deleteCodeFormat/<int:pk>', views.DeleteCodeFormat.as_view(), name="deleteCodeFormat"),
path('validateProjectCode/', views.validate_project_code, name='validateProjectCode'),
path('checkProjectCodeExist/', views.check_project_code_exists, name='checkProjectCodeExist'),
path('populateUpload/', views.populate_upload_document, name='populateUpload'),
path('addMilestone/', views.load_add_milestone, name='addMilestone'),
path('selectMembersByProject', views.fetch_members_by_project, name='selectMembersByProject'),
path('customerRequests/', views.customer_request_home, name="customerRequests"),
path('addCustomerRequest/', views.AddCustomerRequest.as_view(), name="addCustomerRequest"),
path('saveCustomerRequest/', views.save_customer_request, name='saveCustomerRequest'),
path('updateCustomerRequest/<int:pk>/', views.UpdateCustomerRequest.as_view(), name='updateCustomerRequest'),
path('saveRequestupdate/', views.save_customer_request_update, name='saveRequestupdate'),
path('viewCustomerRequest/<int:pk>/', views.ViewCustomerRequest.as_view(), name='viewCustomerRequest'),
path('deleteCustomerRequest', views.delete_customer_request, name='deleteCustomerRequest'),
path('fowardRequests', views.foward_customer_requests, name='fowardRequests'),
path('manageCustomerViewRequests/', views.manager_view_customer_requests, name="manageCustomerViewRequests"),
path('SLAsByCustomer', views.fetch_SLAs_by_customer, name='SLAsByCustomer'),
path('requestsBySLA', views.fetch_requests_by_sla, name='requestsBySLA'),
# CUSTOMER URLS
path('listCustomerProjects/', views.list_customer_projects, name='listCustomerProjects'),
path('addCustomerProjects/', views.add_customer_projects, name='addCustomerProjects'),
path('returnStatus/', views.return_status, name='returnStatus'),
path('saveProject/', views.save_project, name='saveProject'),
path('assignedUsers/', views.assigned_users, name='assignedUsers'),
path('updateCustomerProject/<int:pk>', views.UpdateCustomerProject.as_view(), name='updateCustomerProject'),
path('listCustomerServiceRequests/', views.list_customer_service_requests, name='listCustomerServiceRequests'),
path('listCustomerSLAs/', views.list_customer_sla, name='listCustomerSLAs'),
path('checkTask/', views.check_task, name='checkTask'),
path('assignRequests', views.assign_customer_request, name='assignRequests'),
path('dailyTimesheetRReport', views.timesheet_daily_report, name='dailyTimesheetRReport'),
path('filterDailyTimesheetRReport', views.filter_timesheet_daily_report, name='filterDailyTimesheetRReport'),
path('exportDailyTMReport', views.export_daily_tm_report, name='exportDailyTMReport'),
path('exportEmailDailyTMReport', views.export_and_send_email_daily_tm_report, name='exportEmailDailyTMReport'),
path('detailedTaskReport', views.detailed_task_report_pane, name='detailedTaskReport'),
path('filterDetailedTaskTimesheetRReport', views.filter_detailed_task_timesheet_report, name='filterDetailedTaskTimesheetRReport'),
path('exportTimesheetTaskReport', views.export_timesheet_task_report, name='exportTimesheetTaskReport'),
path('exportEmailTimesheetTaskReport', views.export_email_timesheet_task_report, name='exportEmailTimesheetTaskReport'),
path('timesheetDefaulterList', views.timesheet_defaulter_list, name='timesheetDefaulterList'),
path('sendTimesheetEmailReminder', views.send_timesheet_email_reminder, name='sendTimesheetEmailReminder'),
]
|
<filename>project_management/urls.py
from django.urls import path, re_path
from . import views
# app_name = 'project_management'
urlpatterns = [
path('projects/', views.load_all_projects, name='full_project_list'),
path('ongoing/', views.ProjectListView.as_view(), name='project_list'),
path('ajax/load_selected_projects/', views.load_selected_projects, name='load_selected_projects'),
path('projectdoc', views.model_form_upload, name='model_form_upload'),
path('projectdocs/', views.load_project_documents, name='projectdocs_list'),
path('<int:pk>/', views.ProjectDetailView.as_view(), name='project_details'),
path('complete/', views.CompleteProjectListView.as_view(), name='complete_project_list'),
path('terminated/', views.TerminatedProjectListView.as_view(), name='terminated_project_list'),
path('new/', views.ProjectCreateView.as_view(), name='new_project'),
path('update/<int:pk>/', views.ProjectUpdateView.as_view(), name='update_project'),
path('download-project-csv/', views.projects_download, name='download_projects_csv'),
path('download-project-excel/', views.export_projects_xls, name='export_projects_xls'),
path('milestones/', views.project_milestones_by_user, name='milestone_list'),
path('milestone/detail/<int:pk>/', views.MilestoneDetailView.as_view(), name='milestone_details'),
path('listProjectMilestones/', views.list_project_milestones, name='listProjectMilestones'),
path('populateMilestone/', views.populate_milestone_view, name='populateMilestone'),
path('populateMilestoneStatus/', views.populate_milestone_status, name='populateMilestoneStatus'),
path('saveMilestone', views.save_milestone, name='saveMilestone'),
path('validateMilestoneName', views.validateMilestoneName, name='validateMilestoneName'),
path('updateProjectMilestone/<int:pk>', views.UpdateProjectMilestone.as_view(), name='updateProjectMilestone'),
path('updateOpenMilestone/<int:pk>', views.UpdateOpenMilestone.as_view(), name='updateOpenMilestone'),
path('updateOnholdMilestone/<int:pk>', views.UpdateOnholdMilestone.as_view(), name='updateOnholdMilestone'),
path('updateTerminatedMilestone/<int:pk>', views.UpdateTerminatedMilestone.as_view(), name='updateTerminatedMilestone'),
path('updateCompletedMilestone/<int:pk>', views.UpdateCompletedMilestone.as_view(), name='updateCompletedMilestone'),
path('detailsProjectMilestone/<int:pk>', views.DetailsProjectMilestone.as_view(), name='detailsProjectMilestone'),
path('checkMilestoneStatus/', views.check_milestone_status, name='checkMilestoneStatus'),
path('deleteProjectMilestone/', views.delete_project_milestone, name='deleteProjectMilestone'),
path('onholdMilestones/', views.onhold_project_milestones, name='onholdMilestones'),
path('openMilestones/', views.open_milestones, name='openMilestones'),
path('terminatedMilestones/', views.terminated_project_milestones, name='terminatedMilestones'),
path('completedMilestones/', views.completed_project_milestones, name='completedMilestones'),
path('saveupdateProjectMilestone/<int:pk>', views.save_update_milestone, name='saveupdateProjectMilestone'),
path('milestoneCount/', views.milestone_count, name='milestoneCount'),
path('milestonesContainer/', views.milestone_container, name='milestonesContainer'),
path('populateTaskView', views.populate_task_view, name='populateTaskView'),
path('createTask', views.create_tasks_by_project, name="createTask"),
path('tasks_list/', views.task_list_by_users, name='task_list'),
path('task/<int:pk>/', views.TaskDetailView.as_view(), name='task_details'),
# re_path(r'^tasks-project/(?P<project_id>\d+)/$', views.task_list_by_project, name='project_task_list'),
re_path(r'^tasks-milestone/(?P<milestone_id>\d+)/$', views.task_list_by_milestone, name='milestone_task_list'),
path('tasks/new/', views.TaskCreateView.as_view(), name='new_task'),
path('task-update/<int:pk>/', views.TaskUpdateView.as_view(), name='update_task'),
path('listProjectTasks', views.tasklist_by_project, name='listProjectTasks'),
path('validateTaskName/', views.validateTaskName, name='validateTaskName'),
path('saveProjectTask', views.save_project_tasks, name='saveProjectTask'),
path('milestoneTasks', views.view_tasks_under_milestone, name='milestoneTasks'),
path('addMilestoneTask', views.add_milestone_specific_task, name='addMilestoneTask'),
path('addMilestoneTasks', views.add_milestone_tasks, name='addMilestoneTasks'),
path('saveMilestoneTask', views.save_milestone_tasks, name='saveMilestoneTask'),
path('updateProjectTask/<int:pk>', views.UpdateProjectTask.as_view(), name='updateProjectTask'),
path('updateMilestoneTask/<int:pk>', views.UpdateMilestoneTask.as_view(), name='updateMilestoneTask'),
path('detailsProjectTask/<int:pk>', views.DetailsProjectTask.as_view(), name='detailsProjectTask'),
path('deleteTask/', views.delete_task, name='deleteTask'),
path('openTasks/', views.open_project_tasks, name="openTasks"),
path('onholdTasks/', views.onhold_tasks, name="onholdTasks"),
path('terminatedTasks/', views.terminated_tasks, name="terminatedTasks"),
path('completedTasks/', views.completed_tasks, name="completedTasks"),
path('updateOpenTask/<int:pk>', views.UpdateOpenTask.as_view(), name='updateOpenTask'),
path('updateCompletedTask/<int:pk>', views.UpdateCompletedTask.as_view(), name='updateCompletedTask'),
path('updateOnholdTask/<int:pk>', views.UpdateOnholdTask.as_view(), name='updateOnholdTask'),
path('updateTerminatedTask/<int:pk>', views.UpdateTerminatedTask.as_view(), name='updateTerminatedTask'),
path('saveupdateProjectTask/<int:pk>', views.save_update_task, name='saveupdateProjectTask'),
path('taskCount/', views.task_count, name='taskCount'),
path('assignedTaskMembers/', views.assigned_task_members, name="assignedTaskMembers"),
path('assignedTaskMembersMilestone/', views.assigned_task_members_milestone, name="assignedTaskMembersMilestone"),
path('assignTaskMembers/', views.assign_task_members, name="assignTaskMembers"),
path('deassignTaskMembers/', views.deassign_task_members, name="deassignTaskMembers"),
path('deassignTaskMembersMilestone/', views.deassign_task_members_milestone, name="deassignTaskMembersMilestone"),
path('checkTeamMembers/', views.check_team_members, name="checkTeamMembers"),
path('checkAssignedTaskMembers/', views.check_assigned_task_members, name="checkAssignedTaskMembers"),
path('saveMembersAssignedTask/', views.save_members_assigned_task, name="saveMembersAssignedTask"),
path('tasks/', views.tasks_container, name="tasksContainer"),
path('saveTeamTasks', views.save_team_project_tasks, name='saveTeamTasks'),
path('addIncident/', views.AddIncident.as_view(), name='addIncident'),
path('addProjectIncident/', views.AddProjectIncident.as_view(), name='addProjectIncident'),
path('incident_list/', views.list_incidents_by_project, name='listIncidents'),
path('listProjectIncidents', views.list_project_incidents, name='listProjectIncidents'),
path('detailsIncident/<int:pk>/', views.DetailsIncident.as_view(), name='detailsIncident'),
path('detailsProjectIncident/<int:pk>/', views.DetailsProjectIncident.as_view(), name='detailsProjectIncident'),
path('updateIncident/<int:pk>/', views.UpdateIncident.as_view(), name='updateIncident'),
path('updateProjectIncident/<int:pk>/', views.UpdateProjectIncident.as_view(), name='updateProjectIncident'),
path('addComment/', views.add_comment, name="addComment"),
path('listIncidentComments/', views.list_incident_comments, name="listIncidentComments"),
path('onholdIncidents/', views.onhold_project_incidents, name="onholdIncidents"),
path('terminatedIncidents/', views.terminated_project_incidents, name="terminatedIncidents"),
path('completedIncidents/', views.completed_project_incidents, name="completedIncidents"),
path('listIncidents/', views.incident_container, name="incidentContainer"),
path('createIncident/', views.create_incident, name="createIncident"),
path('saveIncident/', views.save_incident, name="saveIncident"),
path('listAllPriorities/', views.ListAllPriorities.as_view(), name='listAllPriorities'),
path('addPriority/', views.AddPriority.as_view(), name='addPriority'),
path('updatePriority/<int:pk>/', views.UpdatePriority.as_view(), name='updatePriority'),
path('deletePriority/<int:pk>', views.DeletePriority.as_view(), name="deletePriority"),
path('validatePriorityName/', views.validatePriorityName, name='validatePriorityName'),
path('listAllStatuses/', views.ListAllStatuses.as_view(), name='listAllStatuses'),
path('addStatus/', views.AddStatus.as_view(), name='addStatus'),
path('updateStatus/<int:pk>/', views.UpdateStatus.as_view(), name='updateStatus'),
path('deleteStatus/<int:pk>/', views.DeleteStatus.as_view(), name="deleteStatus"),
path('validateStatusName/', views.ValidateStatusName, name='validateStatusName'),
path('addProject/', views.addProject, name='addProject'),
# path('listProjects/', views.ListProjects.as_view(), name='listProjects'),
path('listProjects/', views.list_projects, name='listProjects'),
path('updateProject/<int:pk>', views.UpdateProject.as_view(), name='updateProject'),
path('detailsProject/<int:pk>', views.DetailProject.as_view(), name='detailsProject'),
path('validateProjectName/', views.validateProjectName, name='validateProjectName'),
path('uploadDocument/', views.upload_document, name="uploadDocument" ),
path('addProjectTeam/', views.add_project_team, name='addProjectTeam'),
path('adminAddProjectTeam/', views.AdminAddProjectTeam.as_view(), name='adminAddProjectTeam'),
path('listProjectTeams/', views.ListProjectTeams.as_view(), name='listProjectTeams'),
path('updateProjectTeam/<int:pk>', views.UpdateProjectTeam.as_view(), name='updateProjectTeam'),
path('deleteProjectTeam/<int:pk>', views.DeleteProjectTeam.as_view(), name='deleteProjectTeam'),
path('validateProjectTeamName/', views.validateProjectTeamName, name='validateProjectTeamName'),
path('validateProjectAssigned/', views.validateProjectAssigned, name='validateProjectAssigned'),
path('addProjectTeamMember/', views.add_project_team_member, name='addProjectTeamMember'),
path('adminAddProjectTeamMember/', views.admin_add_project_team_member, name='adminAddProjectTeamMember'),
path('listProjectTeamMembers/', views.ListProjectTeamMembers.as_view(), name='listProjectTeamMembers'),
path('detailProjectTeamMembers/', views.detail_team_member, name='detailProjectTeamMembers'),
path('adminDetailProjectTeamMembers/', views.admin_detail_team_member, name='adminDetailProjectTeamMembers'),
path('deleteProjectTeamMember/', views.remove_project_team_member, name='deleteProjectTeamMember'),
path('validateProjectTeamAssigned/', views.validateProjectTeamAssigned, name='validateProjectTeamAssigned'),
path('saveTeamMember/', views.save_team_member, name='saveTeamMember'),
path('getTeamMembers/', views.get_team_members, name='getTeamMembers'),
path('setColorCode/', views.set_priority_color_code, name='setColorCode'),
path('projectForum/', views.project_forum, name='tabProjectForum'),
path('createForum/', views.create_project_forum, name='createProjectForum'),
path('forumReplies/', views.manage_forum_replies, name='manageForumReplies'),
path('deleteChatMessage/', views.delete_forum_message, name='deleteChatMessage'),
path('deleteReply/', views.delete_forum_reply, name='deleteChatReply'),
path('listTeam/', views.list_project_team, name='tabListTeam'),
path('viewAssignedMembers/', views.view_assigned_members, name='viewAssignedMembers'),
path('auditlogs/', views.view_audit_logs, name='listauditlogs'),
path('auditlogsfilter/', views.filter_audit_logs, name='auditlogsfilter'),
path('auditlogsfilter2/', views.all_companies_filter_auditlogs, name='auditlogsfilterallcomp'),
# TIMESHEETS
path('addTimesheet/', views.add_new_timesheet, name='addNewTimesheet'),
path('addTimesheetOnCalender/', views.add_new_timesheet_from_calender, name='addTimesheetOnCalender'),
path('addTimesheetOnDatePaginator/', views.add_new_timesheet_from_datepaginator, name='addTimesheetOnDatePaginator'),
path('projectMilestone', views.fetch_milestones_by_project, name='selectMilestonesByProject'),
path('tasksMilestone', views.fetch_tasks_by_milestone, name='selectTasksByMilestone'),
path('myTimesheets/', views.daily_timesheets_pane, name='myTimesheets'),
path('approveTimesheets/', views.approve_timesheet_pane, name='approveTimesheets'),
path('saveTimeSheet', views.save_new_timesheet, name='saveTimeSheet'),
path('updateTimesheet', views.update_timesheet, name='updateTimesheet'),
path('updateTimesheetPaginator', views.update_timesheet_paginator, name='updateTimesheetPaginator'),
path('saveUpdateTimesheet', views.save_update_timesheet, name='saveUpdateTimesheet'),
path('deleteTimesheet', views.delete_timesheet, name='deleteTimesheet'),
path('deleteTimesheetPaginator', views.delete_timesheet_in_paginator, name='deleteTimesheetPaginator'),
path('sendTimesheet', views.send_timesheet_for_approval, name='sendTimesheetForApproval'),
path('sendPaginatorTimesheetForApproval', views.send_timesheet_for_approval_paginator, name='sendPaginatorTimesheetForApproval'),
path('pendingApproval', views.timesheet_pending_approval, name='timesheetPendingApproval'),
path('saveTimesheetApprovals', views.save_timesheet_approvals, name='saveTimesheetApprovals'),
path('approvedTimesheetsTab', views.manage_approved_timesheets, name='approvedTimesheetsTab'),
path('updateTimesheetApproval', views.update_timesheet_approval, name='updateTimesheetApproval'),
path('userApprovedTimesheets', views.view_user_approved_timesheets, name='userApprovedTimesheets'),
path('filterPenddingTimesheets', views.filter_pending_daily_timesheets_by_date, name='filterPendingTimesheets'),
path('filterDailyProvedTimesheets', views.filter_daily_proved_timesheets, name='filterDailyProvedTimesheets'),
path('filterAllUsersPendingTMs', views.filter_all_member_unapproved_timesheets, name='filterAllUsersPendingTMs'),
path('filterAllUsersApprovedTMs', views.filter_all_member_approved_timesheets, name='filterAllUsersApprovedTMs'),
path('analyseAllTimesheets', views.timesheets_report, name='analyseAllTimesheets'),
path('userGeneralTimesheetReport', views.user_general_timesheet_report, name='userGeneralTimesheetReport'),
path('viewTaskDetails/<int:pk>', views.DetailsProjectTask.as_view(), name='viewTaskDetails'),
path('userRejectedTimesheets', views.manage_rejected_timesheets, name='userRejectedTimesheets'),
path('resubmitTimesheet', views.resubmit_timesheet, name='resubmitTimesheet'),
path('saveResentTimesheet', views.save_resent_timesheet, name='saveResentTimesheet'),
path('paginatorResubmitTimesheet', views.paginator_resubmit_timesheet, name='paginatorResubmitTimesheet'),
path('saveResentPaginatorTimesheet', views.save_resent_paginator_timesheet, name='saveResentPaginatorTimesheet'),
path('viewTimesheetResubmissions', views.manage_timesheet_resubmissions, name='viewTimesheetResubmissions'),
path('updateApproverComment', views.update_approver_comment, name='updateApproverComment'),
path('savecalenderTimeSheet', views.save_calender_timesheet, name='savecalenderTimeSheet'),
path('savePaginatorTimeSheet', views.save_paginator_timesheet, name='savePaginatorTimeSheet'),
path('calenderTimesheetView', views.calenderTimesheetView, name='calenderTimesheetView'),
path('timesheetWeeklyReport', views.timesheets_weekly_report, name='timesheetWeeklyReport'),
path('filterTimesheetsByWeek', views.filter_users_timesheets_by_week, name='filterTimesheetsByWeek'),
path('filterTimesheetsByDate', views.filter_timesheets_by_date, name='filterTimesheetsByDate'),
path('tableTimesheetView', views.table_timesheet_view, name='tableTimesheetView'),
path('listTimesheetView', views.list_timesheet_view, name='listTimesheetView'),
path('saveUpdateTimesheetPaginator', views.save_update_paginator_timesheet, name='saveUpdateTimesheetPaginator'),
path('timesheetProjectReport', views.timesheets_project_report, name='timesheetProjectReport'),
path('filterProjectTimesheetsByWeek', views.filter_project_timesheets_by_week, name='filterProjectTimesheetsByWeek'),
path('selectDailyTimesheetsByUser', views.select_daily_timesheets_by_user, name='selectDailyTimesheetsByUser'),
path('selectTableTimesheetsByUser', views.select_table_timesheets_by_user, name='selectTableTimesheetsByUser'),
path('timesheetMonthlyReport', views.timesheet_monthly_report, name='timesheetMonthlyReport'),
path('filterMonthlyTimesheets', views.filter_monthly_timesheets, name='filterMonthlyTimesheets'),
path('filterMonthlyTimesheetsByDate', views.filter_monthly_timesheets_by_date, name='filterMonthlyTimesheetsByDate'),
# Schedules plans
path('schedulePlan', views.timesheets_schedule_pane, name='schedulePlan'),
# REPORTS
path('staffUtilization/', views.staff_utilization, name="staffUtilization"),
path('staffUtilizationReport/', views.staff_utilization_report, name="staffUtilizationReport"),
path('exportReport/', views.export_staff_utilization, name="exportReport"),
path('exportPdf/', views.export_pdf_utilization, name="exportPdf"),
path('taskReport/', views.task_report_page, name="taskReport"),
path('exportTaskReport/', views.export_task_report, name="exportTaskReport"),
path('previewTaskReport/', views.preview_task_report, name="previewTaskReport"),
# Project code
path('listCodeFormat/', views.ListCodeFormat.as_view(), name='listCodeFormat'),
path('addCodeFormat/', views.AddCodeFormat.as_view(), name='addCodeFormat'),
path('updateCodeFormat/<int:pk>/', views.UpdateCodeFormat.as_view(), name='updateCodeFormat'),
path('deleteCodeFormat/<int:pk>', views.DeleteCodeFormat.as_view(), name="deleteCodeFormat"),
path('validateProjectCode/', views.validate_project_code, name='validateProjectCode'),
path('checkProjectCodeExist/', views.check_project_code_exists, name='checkProjectCodeExist'),
path('populateUpload/', views.populate_upload_document, name='populateUpload'),
path('addMilestone/', views.load_add_milestone, name='addMilestone'),
path('selectMembersByProject', views.fetch_members_by_project, name='selectMembersByProject'),
path('customerRequests/', views.customer_request_home, name="customerRequests"),
path('addCustomerRequest/', views.AddCustomerRequest.as_view(), name="addCustomerRequest"),
path('saveCustomerRequest/', views.save_customer_request, name='saveCustomerRequest'),
path('updateCustomerRequest/<int:pk>/', views.UpdateCustomerRequest.as_view(), name='updateCustomerRequest'),
path('saveRequestupdate/', views.save_customer_request_update, name='saveRequestupdate'),
path('viewCustomerRequest/<int:pk>/', views.ViewCustomerRequest.as_view(), name='viewCustomerRequest'),
path('deleteCustomerRequest', views.delete_customer_request, name='deleteCustomerRequest'),
path('fowardRequests', views.foward_customer_requests, name='fowardRequests'),
path('manageCustomerViewRequests/', views.manager_view_customer_requests, name="manageCustomerViewRequests"),
path('SLAsByCustomer', views.fetch_SLAs_by_customer, name='SLAsByCustomer'),
path('requestsBySLA', views.fetch_requests_by_sla, name='requestsBySLA'),
# CUSTOMER URLS
path('listCustomerProjects/', views.list_customer_projects, name='listCustomerProjects'),
path('addCustomerProjects/', views.add_customer_projects, name='addCustomerProjects'),
path('returnStatus/', views.return_status, name='returnStatus'),
path('saveProject/', views.save_project, name='saveProject'),
path('assignedUsers/', views.assigned_users, name='assignedUsers'),
path('updateCustomerProject/<int:pk>', views.UpdateCustomerProject.as_view(), name='updateCustomerProject'),
path('listCustomerServiceRequests/', views.list_customer_service_requests, name='listCustomerServiceRequests'),
path('listCustomerSLAs/', views.list_customer_sla, name='listCustomerSLAs'),
path('checkTask/', views.check_task, name='checkTask'),
path('assignRequests', views.assign_customer_request, name='assignRequests'),
path('dailyTimesheetRReport', views.timesheet_daily_report, name='dailyTimesheetRReport'),
path('filterDailyTimesheetRReport', views.filter_timesheet_daily_report, name='filterDailyTimesheetRReport'),
path('exportDailyTMReport', views.export_daily_tm_report, name='exportDailyTMReport'),
path('exportEmailDailyTMReport', views.export_and_send_email_daily_tm_report, name='exportEmailDailyTMReport'),
path('detailedTaskReport', views.detailed_task_report_pane, name='detailedTaskReport'),
path('filterDetailedTaskTimesheetRReport', views.filter_detailed_task_timesheet_report, name='filterDetailedTaskTimesheetRReport'),
path('exportTimesheetTaskReport', views.export_timesheet_task_report, name='exportTimesheetTaskReport'),
path('exportEmailTimesheetTaskReport', views.export_email_timesheet_task_report, name='exportEmailTimesheetTaskReport'),
path('timesheetDefaulterList', views.timesheet_defaulter_list, name='timesheetDefaulterList'),
path('sendTimesheetEmailReminder', views.send_timesheet_email_reminder, name='sendTimesheetEmailReminder'),
]
|
en
| 0.462898
|
# app_name = 'project_management' # re_path(r'^tasks-project/(?P<project_id>\d+)/$', views.task_list_by_project, name='project_task_list'), # path('listProjects/', views.ListProjects.as_view(), name='listProjects'), # TIMESHEETS # Schedules plans # REPORTS # Project code # CUSTOMER URLS
| 2.001275
| 2
|
detection/scrfd/mmdet/models/detectors/base.py
|
qaz734913414/insightface
| 12,377
|
6625752
|
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import mmcv
import numpy as np
import torch
import torch.distributed as dist
import torch.nn as nn
from mmcv.runner import auto_fp16
from mmcv.utils import print_log
from mmdet.utils import get_root_logger
class BaseDetector(nn.Module, metaclass=ABCMeta):
"""Base class for detectors."""
def __init__(self):
super(BaseDetector, self).__init__()
self.fp16_enabled = False
@property
def with_neck(self):
"""bool: whether the detector has a neck"""
return hasattr(self, 'neck') and self.neck is not None
# TODO: these properties need to be carefully handled
# for both single stage & two stage detectors
@property
def with_shared_head(self):
"""bool: whether the detector has a shared head in the RoI Head"""
return hasattr(self, 'roi_head') and self.roi_head.with_shared_head
@property
def with_bbox(self):
"""bool: whether the detector has a bbox head"""
return ((hasattr(self, 'roi_head') and self.roi_head.with_bbox)
or (hasattr(self, 'bbox_head') and self.bbox_head is not None))
@property
def with_mask(self):
"""bool: whether the detector has a mask head"""
return ((hasattr(self, 'roi_head') and self.roi_head.with_mask)
or (hasattr(self, 'mask_head') and self.mask_head is not None))
@abstractmethod
def extract_feat(self, imgs):
"""Extract features from images."""
pass
def extract_feats(self, imgs):
"""Extract features from multiple images.
Args:
imgs (list[torch.Tensor]): A list of images. The images are
augmented from the same image but in different ways.
Returns:
list[torch.Tensor]: Features of different images
"""
assert isinstance(imgs, list)
return [self.extract_feat(img) for img in imgs]
def forward_train(self, imgs, img_metas, **kwargs):
"""
Args:
img (list[Tensor]): List of tensors of shape (1, C, H, W).
Typically these should be mean centered and std scaled.
img_metas (list[dict]): List of image info dict where each dict
has: 'img_shape', 'scale_factor', 'flip', and may also contain
'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.
For details on the values of these keys, see
:class:`mmdet.datasets.pipelines.Collect`.
kwargs (keyword arguments): Specific to concrete implementation.
"""
# NOTE the batched image size information may be useful, e.g.
# in DETR, this is needed for the construction of masks, which is
# then used for the transformer_head.
batch_input_shape = tuple(imgs[0].size()[-2:])
for img_meta in img_metas:
img_meta['batch_input_shape'] = batch_input_shape
async def async_simple_test(self, img, img_metas, **kwargs):
raise NotImplementedError
@abstractmethod
def simple_test(self, img, img_metas, **kwargs):
pass
@abstractmethod
def aug_test(self, imgs, img_metas, **kwargs):
"""Test function with test time augmentation."""
pass
def init_weights(self, pretrained=None):
"""Initialize the weights in detector.
Args:
pretrained (str, optional): Path to pre-trained weights.
Defaults to None.
"""
if pretrained is not None:
logger = get_root_logger()
print_log(f'load model from: {pretrained}', logger=logger)
async def aforward_test(self, *, img, img_metas, **kwargs):
for var, name in [(img, 'img'), (img_metas, 'img_metas')]:
if not isinstance(var, list):
raise TypeError(f'{name} must be a list, but got {type(var)}')
num_augs = len(img)
if num_augs != len(img_metas):
raise ValueError(f'num of augmentations ({len(img)}) '
f'!= num of image metas ({len(img_metas)})')
# TODO: remove the restriction of samples_per_gpu == 1 when prepared
samples_per_gpu = img[0].size(0)
assert samples_per_gpu == 1
if num_augs == 1:
return await self.async_simple_test(img[0], img_metas[0], **kwargs)
else:
raise NotImplementedError
def forward_test(self, imgs, img_metas, **kwargs):
"""
Args:
imgs (List[Tensor]): the outer list indicates test-time
augmentations and inner Tensor should have a shape NxCxHxW,
which contains all images in the batch.
img_metas (List[List[dict]]): the outer list indicates test-time
augs (multiscale, flip, etc.) and the inner list indicates
images in a batch.
"""
for var, name in [(imgs, 'imgs'), (img_metas, 'img_metas')]:
if not isinstance(var, list):
raise TypeError(f'{name} must be a list, but got {type(var)}')
num_augs = len(imgs)
if num_augs != len(img_metas):
raise ValueError(f'num of augmentations ({len(imgs)}) '
f'!= num of image meta ({len(img_metas)})')
# NOTE the batched image size information may be useful, e.g.
# in DETR, this is needed for the construction of masks, which is
# then used for the transformer_head.
for img, img_meta in zip(imgs, img_metas):
batch_size = len(img_meta)
for img_id in range(batch_size):
img_meta[img_id]['batch_input_shape'] = tuple(img.size()[-2:])
if num_augs == 1:
# proposals (List[List[Tensor]]): the outer list indicates
# test-time augs (multiscale, flip, etc.) and the inner list
# indicates images in a batch.
# The Tensor should have a shape Px4, where P is the number of
# proposals.
if 'proposals' in kwargs:
kwargs['proposals'] = kwargs['proposals'][0]
return self.simple_test(imgs[0], img_metas[0], **kwargs)
else:
assert imgs[0].size(0) == 1, 'aug test does not support ' \
'inference with batch size ' \
f'{imgs[0].size(0)}'
# TODO: support test augmentation for predefined proposals
assert 'proposals' not in kwargs
return self.aug_test(imgs, img_metas, **kwargs)
@auto_fp16(apply_to=('img', ))
def forward(self, img, img_metas, return_loss=True, **kwargs):
"""Calls either :func:`forward_train` or :func:`forward_test` depending
on whether ``return_loss`` is ``True``.
Note this setting will change the expected inputs. When
``return_loss=True``, img and img_meta are single-nested (i.e. Tensor
and List[dict]), and when ``resturn_loss=False``, img and img_meta
should be double nested (i.e. List[Tensor], List[List[dict]]), with
the outer list indicating test time augmentations.
"""
if return_loss:
return self.forward_train(img, img_metas, **kwargs)
else:
return self.forward_test(img, img_metas, **kwargs)
def _parse_losses(self, losses):
"""Parse the raw outputs (losses) of the network.
Args:
losses (dict): Raw output of the network, which usually contain
losses and other necessary infomation.
Returns:
tuple[Tensor, dict]: (loss, log_vars), loss is the loss tensor \
which may be a weighted sum of all losses, log_vars contains \
all the variables to be sent to the logger.
"""
log_vars = OrderedDict()
for loss_name, loss_value in losses.items():
if isinstance(loss_value, torch.Tensor):
log_vars[loss_name] = loss_value.mean()
elif isinstance(loss_value, list):
log_vars[loss_name] = sum(_loss.mean() for _loss in loss_value)
else:
raise TypeError(
f'{loss_name} is not a tensor or list of tensors')
loss = sum(_value for _key, _value in log_vars.items()
if 'loss' in _key)
log_vars['loss'] = loss
for loss_name, loss_value in log_vars.items():
# reduce loss when distributed training
if dist.is_available() and dist.is_initialized():
loss_value = loss_value.data.clone()
dist.all_reduce(loss_value.div_(dist.get_world_size()))
log_vars[loss_name] = loss_value.item()
return loss, log_vars
def train_step(self, data, optimizer):
"""The iteration step during training.
This method defines an iteration step during training, except for the
back propagation and optimizer updating, which are done in an optimizer
hook. Note that in some complicated cases or models, the whole process
including back propagation and optimizer updating is also defined in
this method, such as GAN.
Args:
data (dict): The output of dataloader.
optimizer (:obj:`torch.optim.Optimizer` | dict): The optimizer of
runner is passed to ``train_step()``. This argument is unused
and reserved.
Returns:
dict: It should contain at least 3 keys: ``loss``, ``log_vars``, \
``num_samples``.
- ``loss`` is a tensor for back propagation, which can be a \
weighted sum of multiple losses.
- ``log_vars`` contains all the variables to be sent to the
logger.
- ``num_samples`` indicates the batch size (when the model is \
DDP, it means the batch size on each GPU), which is used for \
averaging the logs.
"""
losses = self(**data)
loss, log_vars = self._parse_losses(losses)
outputs = dict(
loss=loss, log_vars=log_vars, num_samples=len(data['img_metas']))
return outputs
def val_step(self, data, optimizer):
"""The iteration step during validation.
This method shares the same signature as :func:`train_step`, but used
during val epochs. Note that the evaluation after training epochs is
not implemented with this method, but an evaluation hook.
"""
losses = self(**data)
loss, log_vars = self._parse_losses(losses)
outputs = dict(
loss=loss, log_vars=log_vars, num_samples=len(data['img_metas']))
return outputs
def show_result(self,
img,
result,
score_thr=0.3,
bbox_color='green',
text_color='green',
thickness=1,
font_scale=0.5,
win_name='',
show=False,
wait_time=0,
out_file=None):
"""Draw `result` over `img`.
Args:
img (str or Tensor): The image to be displayed.
result (Tensor or tuple): The results to draw over `img`
bbox_result or (bbox_result, segm_result).
score_thr (float, optional): Minimum score of bboxes to be shown.
Default: 0.3.
bbox_color (str or tuple or :obj:`Color`): Color of bbox lines.
text_color (str or tuple or :obj:`Color`): Color of texts.
thickness (int): Thickness of lines.
font_scale (float): Font scales of texts.
win_name (str): The window name.
wait_time (int): Value of waitKey param.
Default: 0.
show (bool): Whether to show the image.
Default: False.
out_file (str or None): The filename to write the image.
Default: None.
Returns:
img (Tensor): Only if not `show` or `out_file`
"""
img = mmcv.imread(img)
img = img.copy()
if isinstance(result, tuple):
bbox_result, segm_result = result
if isinstance(segm_result, tuple):
segm_result = segm_result[0] # ms rcnn
else:
bbox_result, segm_result = result, None
bboxes = np.vstack(bbox_result)
labels = [
np.full(bbox.shape[0], i, dtype=np.int32)
for i, bbox in enumerate(bbox_result)
]
labels = np.concatenate(labels)
# draw segmentation masks
if segm_result is not None and len(labels) > 0: # non empty
segms = mmcv.concat_list(segm_result)
inds = np.where(bboxes[:, -1] > score_thr)[0]
np.random.seed(42)
color_masks = [
np.random.randint(0, 256, (1, 3), dtype=np.uint8)
for _ in range(max(labels) + 1)
]
for i in inds:
i = int(i)
color_mask = color_masks[labels[i]]
sg = segms[i]
if isinstance(sg, torch.Tensor):
sg = sg.detach().cpu().numpy()
mask = sg.astype(bool)
img[mask] = img[mask] * 0.5 + color_mask * 0.5
# if out_file specified, do not show image in window
if out_file is not None:
show = False
# draw bounding boxes
mmcv.imshow_det_bboxes(
img,
bboxes,
labels,
class_names=self.CLASSES,
score_thr=score_thr,
bbox_color=bbox_color,
text_color=text_color,
thickness=thickness,
font_scale=font_scale,
win_name=win_name,
show=show,
wait_time=wait_time,
out_file=out_file)
if not (show or out_file):
return img
|
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import mmcv
import numpy as np
import torch
import torch.distributed as dist
import torch.nn as nn
from mmcv.runner import auto_fp16
from mmcv.utils import print_log
from mmdet.utils import get_root_logger
class BaseDetector(nn.Module, metaclass=ABCMeta):
"""Base class for detectors."""
def __init__(self):
super(BaseDetector, self).__init__()
self.fp16_enabled = False
@property
def with_neck(self):
"""bool: whether the detector has a neck"""
return hasattr(self, 'neck') and self.neck is not None
# TODO: these properties need to be carefully handled
# for both single stage & two stage detectors
@property
def with_shared_head(self):
"""bool: whether the detector has a shared head in the RoI Head"""
return hasattr(self, 'roi_head') and self.roi_head.with_shared_head
@property
def with_bbox(self):
"""bool: whether the detector has a bbox head"""
return ((hasattr(self, 'roi_head') and self.roi_head.with_bbox)
or (hasattr(self, 'bbox_head') and self.bbox_head is not None))
@property
def with_mask(self):
"""bool: whether the detector has a mask head"""
return ((hasattr(self, 'roi_head') and self.roi_head.with_mask)
or (hasattr(self, 'mask_head') and self.mask_head is not None))
@abstractmethod
def extract_feat(self, imgs):
"""Extract features from images."""
pass
def extract_feats(self, imgs):
"""Extract features from multiple images.
Args:
imgs (list[torch.Tensor]): A list of images. The images are
augmented from the same image but in different ways.
Returns:
list[torch.Tensor]: Features of different images
"""
assert isinstance(imgs, list)
return [self.extract_feat(img) for img in imgs]
def forward_train(self, imgs, img_metas, **kwargs):
"""
Args:
img (list[Tensor]): List of tensors of shape (1, C, H, W).
Typically these should be mean centered and std scaled.
img_metas (list[dict]): List of image info dict where each dict
has: 'img_shape', 'scale_factor', 'flip', and may also contain
'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.
For details on the values of these keys, see
:class:`mmdet.datasets.pipelines.Collect`.
kwargs (keyword arguments): Specific to concrete implementation.
"""
# NOTE the batched image size information may be useful, e.g.
# in DETR, this is needed for the construction of masks, which is
# then used for the transformer_head.
batch_input_shape = tuple(imgs[0].size()[-2:])
for img_meta in img_metas:
img_meta['batch_input_shape'] = batch_input_shape
async def async_simple_test(self, img, img_metas, **kwargs):
raise NotImplementedError
@abstractmethod
def simple_test(self, img, img_metas, **kwargs):
pass
@abstractmethod
def aug_test(self, imgs, img_metas, **kwargs):
"""Test function with test time augmentation."""
pass
def init_weights(self, pretrained=None):
"""Initialize the weights in detector.
Args:
pretrained (str, optional): Path to pre-trained weights.
Defaults to None.
"""
if pretrained is not None:
logger = get_root_logger()
print_log(f'load model from: {pretrained}', logger=logger)
async def aforward_test(self, *, img, img_metas, **kwargs):
for var, name in [(img, 'img'), (img_metas, 'img_metas')]:
if not isinstance(var, list):
raise TypeError(f'{name} must be a list, but got {type(var)}')
num_augs = len(img)
if num_augs != len(img_metas):
raise ValueError(f'num of augmentations ({len(img)}) '
f'!= num of image metas ({len(img_metas)})')
# TODO: remove the restriction of samples_per_gpu == 1 when prepared
samples_per_gpu = img[0].size(0)
assert samples_per_gpu == 1
if num_augs == 1:
return await self.async_simple_test(img[0], img_metas[0], **kwargs)
else:
raise NotImplementedError
def forward_test(self, imgs, img_metas, **kwargs):
"""
Args:
imgs (List[Tensor]): the outer list indicates test-time
augmentations and inner Tensor should have a shape NxCxHxW,
which contains all images in the batch.
img_metas (List[List[dict]]): the outer list indicates test-time
augs (multiscale, flip, etc.) and the inner list indicates
images in a batch.
"""
for var, name in [(imgs, 'imgs'), (img_metas, 'img_metas')]:
if not isinstance(var, list):
raise TypeError(f'{name} must be a list, but got {type(var)}')
num_augs = len(imgs)
if num_augs != len(img_metas):
raise ValueError(f'num of augmentations ({len(imgs)}) '
f'!= num of image meta ({len(img_metas)})')
# NOTE the batched image size information may be useful, e.g.
# in DETR, this is needed for the construction of masks, which is
# then used for the transformer_head.
for img, img_meta in zip(imgs, img_metas):
batch_size = len(img_meta)
for img_id in range(batch_size):
img_meta[img_id]['batch_input_shape'] = tuple(img.size()[-2:])
if num_augs == 1:
# proposals (List[List[Tensor]]): the outer list indicates
# test-time augs (multiscale, flip, etc.) and the inner list
# indicates images in a batch.
# The Tensor should have a shape Px4, where P is the number of
# proposals.
if 'proposals' in kwargs:
kwargs['proposals'] = kwargs['proposals'][0]
return self.simple_test(imgs[0], img_metas[0], **kwargs)
else:
assert imgs[0].size(0) == 1, 'aug test does not support ' \
'inference with batch size ' \
f'{imgs[0].size(0)}'
# TODO: support test augmentation for predefined proposals
assert 'proposals' not in kwargs
return self.aug_test(imgs, img_metas, **kwargs)
@auto_fp16(apply_to=('img', ))
def forward(self, img, img_metas, return_loss=True, **kwargs):
"""Calls either :func:`forward_train` or :func:`forward_test` depending
on whether ``return_loss`` is ``True``.
Note this setting will change the expected inputs. When
``return_loss=True``, img and img_meta are single-nested (i.e. Tensor
and List[dict]), and when ``resturn_loss=False``, img and img_meta
should be double nested (i.e. List[Tensor], List[List[dict]]), with
the outer list indicating test time augmentations.
"""
if return_loss:
return self.forward_train(img, img_metas, **kwargs)
else:
return self.forward_test(img, img_metas, **kwargs)
def _parse_losses(self, losses):
"""Parse the raw outputs (losses) of the network.
Args:
losses (dict): Raw output of the network, which usually contain
losses and other necessary infomation.
Returns:
tuple[Tensor, dict]: (loss, log_vars), loss is the loss tensor \
which may be a weighted sum of all losses, log_vars contains \
all the variables to be sent to the logger.
"""
log_vars = OrderedDict()
for loss_name, loss_value in losses.items():
if isinstance(loss_value, torch.Tensor):
log_vars[loss_name] = loss_value.mean()
elif isinstance(loss_value, list):
log_vars[loss_name] = sum(_loss.mean() for _loss in loss_value)
else:
raise TypeError(
f'{loss_name} is not a tensor or list of tensors')
loss = sum(_value for _key, _value in log_vars.items()
if 'loss' in _key)
log_vars['loss'] = loss
for loss_name, loss_value in log_vars.items():
# reduce loss when distributed training
if dist.is_available() and dist.is_initialized():
loss_value = loss_value.data.clone()
dist.all_reduce(loss_value.div_(dist.get_world_size()))
log_vars[loss_name] = loss_value.item()
return loss, log_vars
def train_step(self, data, optimizer):
"""The iteration step during training.
This method defines an iteration step during training, except for the
back propagation and optimizer updating, which are done in an optimizer
hook. Note that in some complicated cases or models, the whole process
including back propagation and optimizer updating is also defined in
this method, such as GAN.
Args:
data (dict): The output of dataloader.
optimizer (:obj:`torch.optim.Optimizer` | dict): The optimizer of
runner is passed to ``train_step()``. This argument is unused
and reserved.
Returns:
dict: It should contain at least 3 keys: ``loss``, ``log_vars``, \
``num_samples``.
- ``loss`` is a tensor for back propagation, which can be a \
weighted sum of multiple losses.
- ``log_vars`` contains all the variables to be sent to the
logger.
- ``num_samples`` indicates the batch size (when the model is \
DDP, it means the batch size on each GPU), which is used for \
averaging the logs.
"""
losses = self(**data)
loss, log_vars = self._parse_losses(losses)
outputs = dict(
loss=loss, log_vars=log_vars, num_samples=len(data['img_metas']))
return outputs
def val_step(self, data, optimizer):
"""The iteration step during validation.
This method shares the same signature as :func:`train_step`, but used
during val epochs. Note that the evaluation after training epochs is
not implemented with this method, but an evaluation hook.
"""
losses = self(**data)
loss, log_vars = self._parse_losses(losses)
outputs = dict(
loss=loss, log_vars=log_vars, num_samples=len(data['img_metas']))
return outputs
def show_result(self,
img,
result,
score_thr=0.3,
bbox_color='green',
text_color='green',
thickness=1,
font_scale=0.5,
win_name='',
show=False,
wait_time=0,
out_file=None):
"""Draw `result` over `img`.
Args:
img (str or Tensor): The image to be displayed.
result (Tensor or tuple): The results to draw over `img`
bbox_result or (bbox_result, segm_result).
score_thr (float, optional): Minimum score of bboxes to be shown.
Default: 0.3.
bbox_color (str or tuple or :obj:`Color`): Color of bbox lines.
text_color (str or tuple or :obj:`Color`): Color of texts.
thickness (int): Thickness of lines.
font_scale (float): Font scales of texts.
win_name (str): The window name.
wait_time (int): Value of waitKey param.
Default: 0.
show (bool): Whether to show the image.
Default: False.
out_file (str or None): The filename to write the image.
Default: None.
Returns:
img (Tensor): Only if not `show` or `out_file`
"""
img = mmcv.imread(img)
img = img.copy()
if isinstance(result, tuple):
bbox_result, segm_result = result
if isinstance(segm_result, tuple):
segm_result = segm_result[0] # ms rcnn
else:
bbox_result, segm_result = result, None
bboxes = np.vstack(bbox_result)
labels = [
np.full(bbox.shape[0], i, dtype=np.int32)
for i, bbox in enumerate(bbox_result)
]
labels = np.concatenate(labels)
# draw segmentation masks
if segm_result is not None and len(labels) > 0: # non empty
segms = mmcv.concat_list(segm_result)
inds = np.where(bboxes[:, -1] > score_thr)[0]
np.random.seed(42)
color_masks = [
np.random.randint(0, 256, (1, 3), dtype=np.uint8)
for _ in range(max(labels) + 1)
]
for i in inds:
i = int(i)
color_mask = color_masks[labels[i]]
sg = segms[i]
if isinstance(sg, torch.Tensor):
sg = sg.detach().cpu().numpy()
mask = sg.astype(bool)
img[mask] = img[mask] * 0.5 + color_mask * 0.5
# if out_file specified, do not show image in window
if out_file is not None:
show = False
# draw bounding boxes
mmcv.imshow_det_bboxes(
img,
bboxes,
labels,
class_names=self.CLASSES,
score_thr=score_thr,
bbox_color=bbox_color,
text_color=text_color,
thickness=thickness,
font_scale=font_scale,
win_name=win_name,
show=show,
wait_time=wait_time,
out_file=out_file)
if not (show or out_file):
return img
|
en
| 0.787981
|
Base class for detectors. bool: whether the detector has a neck # TODO: these properties need to be carefully handled # for both single stage & two stage detectors bool: whether the detector has a shared head in the RoI Head bool: whether the detector has a bbox head bool: whether the detector has a mask head Extract features from images. Extract features from multiple images. Args: imgs (list[torch.Tensor]): A list of images. The images are augmented from the same image but in different ways. Returns: list[torch.Tensor]: Features of different images Args: img (list[Tensor]): List of tensors of shape (1, C, H, W). Typically these should be mean centered and std scaled. img_metas (list[dict]): List of image info dict where each dict has: 'img_shape', 'scale_factor', 'flip', and may also contain 'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'. For details on the values of these keys, see :class:`mmdet.datasets.pipelines.Collect`. kwargs (keyword arguments): Specific to concrete implementation. # NOTE the batched image size information may be useful, e.g. # in DETR, this is needed for the construction of masks, which is # then used for the transformer_head. Test function with test time augmentation. Initialize the weights in detector. Args: pretrained (str, optional): Path to pre-trained weights. Defaults to None. # TODO: remove the restriction of samples_per_gpu == 1 when prepared Args: imgs (List[Tensor]): the outer list indicates test-time augmentations and inner Tensor should have a shape NxCxHxW, which contains all images in the batch. img_metas (List[List[dict]]): the outer list indicates test-time augs (multiscale, flip, etc.) and the inner list indicates images in a batch. # NOTE the batched image size information may be useful, e.g. # in DETR, this is needed for the construction of masks, which is # then used for the transformer_head. # proposals (List[List[Tensor]]): the outer list indicates # test-time augs (multiscale, flip, etc.) and the inner list # indicates images in a batch. # The Tensor should have a shape Px4, where P is the number of # proposals. # TODO: support test augmentation for predefined proposals Calls either :func:`forward_train` or :func:`forward_test` depending on whether ``return_loss`` is ``True``. Note this setting will change the expected inputs. When ``return_loss=True``, img and img_meta are single-nested (i.e. Tensor and List[dict]), and when ``resturn_loss=False``, img and img_meta should be double nested (i.e. List[Tensor], List[List[dict]]), with the outer list indicating test time augmentations. Parse the raw outputs (losses) of the network. Args: losses (dict): Raw output of the network, which usually contain losses and other necessary infomation. Returns: tuple[Tensor, dict]: (loss, log_vars), loss is the loss tensor \ which may be a weighted sum of all losses, log_vars contains \ all the variables to be sent to the logger. # reduce loss when distributed training The iteration step during training. This method defines an iteration step during training, except for the back propagation and optimizer updating, which are done in an optimizer hook. Note that in some complicated cases or models, the whole process including back propagation and optimizer updating is also defined in this method, such as GAN. Args: data (dict): The output of dataloader. optimizer (:obj:`torch.optim.Optimizer` | dict): The optimizer of runner is passed to ``train_step()``. This argument is unused and reserved. Returns: dict: It should contain at least 3 keys: ``loss``, ``log_vars``, \ ``num_samples``. - ``loss`` is a tensor for back propagation, which can be a \ weighted sum of multiple losses. - ``log_vars`` contains all the variables to be sent to the logger. - ``num_samples`` indicates the batch size (when the model is \ DDP, it means the batch size on each GPU), which is used for \ averaging the logs. The iteration step during validation. This method shares the same signature as :func:`train_step`, but used during val epochs. Note that the evaluation after training epochs is not implemented with this method, but an evaluation hook. Draw `result` over `img`. Args: img (str or Tensor): The image to be displayed. result (Tensor or tuple): The results to draw over `img` bbox_result or (bbox_result, segm_result). score_thr (float, optional): Minimum score of bboxes to be shown. Default: 0.3. bbox_color (str or tuple or :obj:`Color`): Color of bbox lines. text_color (str or tuple or :obj:`Color`): Color of texts. thickness (int): Thickness of lines. font_scale (float): Font scales of texts. win_name (str): The window name. wait_time (int): Value of waitKey param. Default: 0. show (bool): Whether to show the image. Default: False. out_file (str or None): The filename to write the image. Default: None. Returns: img (Tensor): Only if not `show` or `out_file` # ms rcnn # draw segmentation masks # non empty # if out_file specified, do not show image in window # draw bounding boxes
| 2.115427
| 2
|
platform/gsutil/gslib/commands/cors.py
|
bopopescu/SDK
| 0
|
6625753
|
# -*- coding: utf-8 -*-
# Copyright 2012 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Implementation of cors configuration command for GCS buckets."""
from __future__ import absolute_import
import sys
from gslib.command import Command
from gslib.command_argument import CommandArgument
from gslib.cs_api_map import ApiSelector
from gslib.exception import CommandException
from gslib.exception import NO_URLS_MATCHED_TARGET
from gslib.help_provider import CreateHelpText
from gslib.storage_url import StorageUrlFromString
from gslib.third_party.storage_apitools import storage_v1_messages as apitools_messages
from gslib.translation_helper import CorsTranslation
from gslib.translation_helper import REMOVE_CORS_CONFIG
from gslib.util import NO_MAX
from gslib.util import UrlsAreForSingleProvider
_GET_SYNOPSIS = """
gsutil cors get url
"""
_SET_SYNOPSIS = """
gsutil cors set cors-json-file url...
"""
_GET_DESCRIPTION = """
<B>GET</B>
Gets the CORS configuration for a single bucket. The output from
"cors get" can be redirected into a file, edited and then updated using
"cors set".
"""
_SET_DESCRIPTION = """
<B>SET</B>
Sets the CORS configuration for one or more buckets. The
cors-json-file specified on the command line should be a path to a local
file containing a JSON document as described above.
"""
_SYNOPSIS = _SET_SYNOPSIS + _GET_SYNOPSIS.lstrip('\n') + '\n\n'
_DESCRIPTION = ("""
Gets or sets the Cross-Origin Resource Sharing (CORS) configuration on one or
more buckets. This command is supported for buckets only, not objects. An
example CORS JSON document looks like the folllowing:
[
{
"origin": ["http://origin1.example.com"],
"responseHeader": ["Content-Type"],
"method": ["GET"],
"maxAgeSeconds": 3600
}
]
The above JSON document explicitly allows cross-origin GET requests from
http://origin1.example.com and may include the Content-Type response header.
The preflight request may be cached for 1 hour.
The following (empty) CORS JSON document removes all CORS configuration for
a bucket:
[]
The cors command has two sub-commands:
""" + '\n'.join([_GET_DESCRIPTION, _SET_DESCRIPTION]) + """
For more info about CORS, see http://www.w3.org/TR/cors/.
""")
_DETAILED_HELP_TEXT = CreateHelpText(_SYNOPSIS, _DESCRIPTION)
_get_help_text = CreateHelpText(_GET_SYNOPSIS, _GET_DESCRIPTION)
_set_help_text = CreateHelpText(_SET_SYNOPSIS, _SET_DESCRIPTION)
class CorsCommand(Command):
"""Implementation of gsutil cors command."""
# Command specification. See base class for documentation.
command_spec = Command.CreateCommandSpec(
'cors',
command_name_aliases=['getcors', 'setcors'],
usage_synopsis=_SYNOPSIS,
min_args=2,
max_args=NO_MAX,
supported_sub_args='',
file_url_ok=False,
provider_url_ok=False,
urls_start_arg=1,
gs_api_support=[ApiSelector.XML, ApiSelector.JSON],
gs_default_api=ApiSelector.JSON,
argparse_arguments={
'set': [
CommandArgument.MakeNFileURLsArgument(1),
CommandArgument.MakeZeroOrMoreCloudBucketURLsArgument()
],
'get': [
CommandArgument.MakeNCloudBucketURLsArgument(1)
]
}
)
# Help specification. See help_provider.py for documentation.
help_spec = Command.HelpSpec(
help_name='cors',
help_name_aliases=['getcors', 'setcors', 'cross-origin'],
help_type='command_help',
help_one_line_summary=(
'Set a CORS JSON document for one or more buckets'),
help_text=_DETAILED_HELP_TEXT,
subcommand_help_text={'get': _get_help_text, 'set': _set_help_text},
)
def _CalculateUrlsStartArg(self):
if not self.args:
self.RaiseWrongNumberOfArgumentsException()
if self.args[0].lower() == 'set':
return 2
else:
return 1
def _SetCors(self):
"""Sets CORS configuration on a Google Cloud Storage bucket."""
cors_arg = self.args[0]
url_args = self.args[1:]
# Disallow multi-provider 'cors set' requests.
if not UrlsAreForSingleProvider(url_args):
raise CommandException('"%s" command spanning providers not allowed.' %
self.command_name)
# Open, read and parse file containing JSON document.
cors_file = open(cors_arg, 'r')
cors_txt = cors_file.read()
cors_file.close()
self.api = self.gsutil_api.GetApiSelector(
StorageUrlFromString(url_args[0]).scheme)
# Iterate over URLs, expanding wildcards and setting the CORS on each.
some_matched = False
for url_str in url_args:
bucket_iter = self.GetBucketUrlIterFromArg(url_str, bucket_fields=['id'])
for blr in bucket_iter:
url = blr.storage_url
some_matched = True
self.logger.info('Setting CORS on %s...', blr)
if url.scheme == 's3':
self.gsutil_api.XmlPassThroughSetCors(
cors_txt, url, provider=url.scheme)
else:
cors = CorsTranslation.JsonCorsToMessageEntries(cors_txt)
if not cors:
cors = REMOVE_CORS_CONFIG
bucket_metadata = apitools_messages.Bucket(cors=cors)
self.gsutil_api.PatchBucket(url.bucket_name, bucket_metadata,
provider=url.scheme, fields=['id'])
if not some_matched:
raise CommandException(NO_URLS_MATCHED_TARGET % list(url_args))
return 0
def _GetCors(self):
"""Gets CORS configuration for a Google Cloud Storage bucket."""
bucket_url, bucket_metadata = self.GetSingleBucketUrlFromArg(
self.args[0], bucket_fields=['cors'])
if bucket_url.scheme == 's3':
sys.stdout.write(self.gsutil_api.XmlPassThroughGetCors(
bucket_url, provider=bucket_url.scheme))
else:
if bucket_metadata.cors:
sys.stdout.write(
CorsTranslation.MessageEntriesToJson(bucket_metadata.cors))
else:
sys.stdout.write('%s has no CORS configuration.\n' % bucket_url)
return 0
def RunCommand(self):
"""Command entry point for the cors command."""
action_subcommand = self.args.pop(0)
if action_subcommand == 'get':
func = self._GetCors
elif action_subcommand == 'set':
func = self._SetCors
else:
raise CommandException(('Invalid subcommand "%s" for the %s command.\n'
'See "gsutil help cors".') %
(action_subcommand, self.command_name))
return func()
|
# -*- coding: utf-8 -*-
# Copyright 2012 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Implementation of cors configuration command for GCS buckets."""
from __future__ import absolute_import
import sys
from gslib.command import Command
from gslib.command_argument import CommandArgument
from gslib.cs_api_map import ApiSelector
from gslib.exception import CommandException
from gslib.exception import NO_URLS_MATCHED_TARGET
from gslib.help_provider import CreateHelpText
from gslib.storage_url import StorageUrlFromString
from gslib.third_party.storage_apitools import storage_v1_messages as apitools_messages
from gslib.translation_helper import CorsTranslation
from gslib.translation_helper import REMOVE_CORS_CONFIG
from gslib.util import NO_MAX
from gslib.util import UrlsAreForSingleProvider
_GET_SYNOPSIS = """
gsutil cors get url
"""
_SET_SYNOPSIS = """
gsutil cors set cors-json-file url...
"""
_GET_DESCRIPTION = """
<B>GET</B>
Gets the CORS configuration for a single bucket. The output from
"cors get" can be redirected into a file, edited and then updated using
"cors set".
"""
_SET_DESCRIPTION = """
<B>SET</B>
Sets the CORS configuration for one or more buckets. The
cors-json-file specified on the command line should be a path to a local
file containing a JSON document as described above.
"""
_SYNOPSIS = _SET_SYNOPSIS + _GET_SYNOPSIS.lstrip('\n') + '\n\n'
_DESCRIPTION = ("""
Gets or sets the Cross-Origin Resource Sharing (CORS) configuration on one or
more buckets. This command is supported for buckets only, not objects. An
example CORS JSON document looks like the folllowing:
[
{
"origin": ["http://origin1.example.com"],
"responseHeader": ["Content-Type"],
"method": ["GET"],
"maxAgeSeconds": 3600
}
]
The above JSON document explicitly allows cross-origin GET requests from
http://origin1.example.com and may include the Content-Type response header.
The preflight request may be cached for 1 hour.
The following (empty) CORS JSON document removes all CORS configuration for
a bucket:
[]
The cors command has two sub-commands:
""" + '\n'.join([_GET_DESCRIPTION, _SET_DESCRIPTION]) + """
For more info about CORS, see http://www.w3.org/TR/cors/.
""")
_DETAILED_HELP_TEXT = CreateHelpText(_SYNOPSIS, _DESCRIPTION)
_get_help_text = CreateHelpText(_GET_SYNOPSIS, _GET_DESCRIPTION)
_set_help_text = CreateHelpText(_SET_SYNOPSIS, _SET_DESCRIPTION)
class CorsCommand(Command):
"""Implementation of gsutil cors command."""
# Command specification. See base class for documentation.
command_spec = Command.CreateCommandSpec(
'cors',
command_name_aliases=['getcors', 'setcors'],
usage_synopsis=_SYNOPSIS,
min_args=2,
max_args=NO_MAX,
supported_sub_args='',
file_url_ok=False,
provider_url_ok=False,
urls_start_arg=1,
gs_api_support=[ApiSelector.XML, ApiSelector.JSON],
gs_default_api=ApiSelector.JSON,
argparse_arguments={
'set': [
CommandArgument.MakeNFileURLsArgument(1),
CommandArgument.MakeZeroOrMoreCloudBucketURLsArgument()
],
'get': [
CommandArgument.MakeNCloudBucketURLsArgument(1)
]
}
)
# Help specification. See help_provider.py for documentation.
help_spec = Command.HelpSpec(
help_name='cors',
help_name_aliases=['getcors', 'setcors', 'cross-origin'],
help_type='command_help',
help_one_line_summary=(
'Set a CORS JSON document for one or more buckets'),
help_text=_DETAILED_HELP_TEXT,
subcommand_help_text={'get': _get_help_text, 'set': _set_help_text},
)
def _CalculateUrlsStartArg(self):
if not self.args:
self.RaiseWrongNumberOfArgumentsException()
if self.args[0].lower() == 'set':
return 2
else:
return 1
def _SetCors(self):
"""Sets CORS configuration on a Google Cloud Storage bucket."""
cors_arg = self.args[0]
url_args = self.args[1:]
# Disallow multi-provider 'cors set' requests.
if not UrlsAreForSingleProvider(url_args):
raise CommandException('"%s" command spanning providers not allowed.' %
self.command_name)
# Open, read and parse file containing JSON document.
cors_file = open(cors_arg, 'r')
cors_txt = cors_file.read()
cors_file.close()
self.api = self.gsutil_api.GetApiSelector(
StorageUrlFromString(url_args[0]).scheme)
# Iterate over URLs, expanding wildcards and setting the CORS on each.
some_matched = False
for url_str in url_args:
bucket_iter = self.GetBucketUrlIterFromArg(url_str, bucket_fields=['id'])
for blr in bucket_iter:
url = blr.storage_url
some_matched = True
self.logger.info('Setting CORS on %s...', blr)
if url.scheme == 's3':
self.gsutil_api.XmlPassThroughSetCors(
cors_txt, url, provider=url.scheme)
else:
cors = CorsTranslation.JsonCorsToMessageEntries(cors_txt)
if not cors:
cors = REMOVE_CORS_CONFIG
bucket_metadata = apitools_messages.Bucket(cors=cors)
self.gsutil_api.PatchBucket(url.bucket_name, bucket_metadata,
provider=url.scheme, fields=['id'])
if not some_matched:
raise CommandException(NO_URLS_MATCHED_TARGET % list(url_args))
return 0
def _GetCors(self):
"""Gets CORS configuration for a Google Cloud Storage bucket."""
bucket_url, bucket_metadata = self.GetSingleBucketUrlFromArg(
self.args[0], bucket_fields=['cors'])
if bucket_url.scheme == 's3':
sys.stdout.write(self.gsutil_api.XmlPassThroughGetCors(
bucket_url, provider=bucket_url.scheme))
else:
if bucket_metadata.cors:
sys.stdout.write(
CorsTranslation.MessageEntriesToJson(bucket_metadata.cors))
else:
sys.stdout.write('%s has no CORS configuration.\n' % bucket_url)
return 0
def RunCommand(self):
"""Command entry point for the cors command."""
action_subcommand = self.args.pop(0)
if action_subcommand == 'get':
func = self._GetCors
elif action_subcommand == 'set':
func = self._SetCors
else:
raise CommandException(('Invalid subcommand "%s" for the %s command.\n'
'See "gsutil help cors".') %
(action_subcommand, self.command_name))
return func()
|
en
| 0.734944
|
# -*- coding: utf-8 -*- # Copyright 2012 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. Implementation of cors configuration command for GCS buckets. gsutil cors get url gsutil cors set cors-json-file url... <B>GET</B> Gets the CORS configuration for a single bucket. The output from "cors get" can be redirected into a file, edited and then updated using "cors set". <B>SET</B> Sets the CORS configuration for one or more buckets. The cors-json-file specified on the command line should be a path to a local file containing a JSON document as described above. Gets or sets the Cross-Origin Resource Sharing (CORS) configuration on one or more buckets. This command is supported for buckets only, not objects. An example CORS JSON document looks like the folllowing: [ { "origin": ["http://origin1.example.com"], "responseHeader": ["Content-Type"], "method": ["GET"], "maxAgeSeconds": 3600 } ] The above JSON document explicitly allows cross-origin GET requests from http://origin1.example.com and may include the Content-Type response header. The preflight request may be cached for 1 hour. The following (empty) CORS JSON document removes all CORS configuration for a bucket: [] The cors command has two sub-commands: For more info about CORS, see http://www.w3.org/TR/cors/. Implementation of gsutil cors command. # Command specification. See base class for documentation. # Help specification. See help_provider.py for documentation. Sets CORS configuration on a Google Cloud Storage bucket. # Disallow multi-provider 'cors set' requests. # Open, read and parse file containing JSON document. # Iterate over URLs, expanding wildcards and setting the CORS on each. Gets CORS configuration for a Google Cloud Storage bucket. Command entry point for the cors command.
| 1.77858
| 2
|
azure-mgmt-botservice/azure/mgmt/botservice/models/azure_bot_service_enums.py
|
Christina-Kang/azure-sdk-for-python
| 1
|
6625754
|
<filename>azure-mgmt-botservice/azure/mgmt/botservice/models/azure_bot_service_enums.py
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from enum import Enum
class SkuName(Enum):
f0 = "F0"
s1 = "S1"
class SkuTier(Enum):
free = "Free"
standard = "Standard"
class Kind(Enum):
sdk = "sdk"
designer = "designer"
bot = "bot"
function = "function"
class ChannelName(Enum):
facebook_channel = "FacebookChannel"
email_channel = "EmailChannel"
|
<filename>azure-mgmt-botservice/azure/mgmt/botservice/models/azure_bot_service_enums.py
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from enum import Enum
class SkuName(Enum):
f0 = "F0"
s1 = "S1"
class SkuTier(Enum):
free = "Free"
standard = "Standard"
class Kind(Enum):
sdk = "sdk"
designer = "designer"
bot = "bot"
function = "function"
class ChannelName(Enum):
facebook_channel = "FacebookChannel"
email_channel = "EmailChannel"
|
en
| 0.583126
|
# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # --------------------------------------------------------------------------
| 1.813247
| 2
|
example2.py
|
elplatt/repsci
| 2
|
6625755
|
<gh_stars>1-10
# Import the logging library
import repsci
# Create a config
import configparser
config = configparser.ConfigParser()
config['DEFAULT'] = {
'message': 'Hello, World!'
}
# Create an experiment
exp_name = "hello_config"
exp = repsci.Experiment(exp_name, config=config)
# Get the logger and write a log message
log = exp.get_logger()
log.info(config['DEFAULT']['message'])
# Create an output file in the unique output directory
filename = exp.get_filename('output.csv')
with open(filename, "w") as f:
f.write(config['DEFAULT']['message'] + '\n')
|
# Import the logging library
import repsci
# Create a config
import configparser
config = configparser.ConfigParser()
config['DEFAULT'] = {
'message': 'Hello, World!'
}
# Create an experiment
exp_name = "hello_config"
exp = repsci.Experiment(exp_name, config=config)
# Get the logger and write a log message
log = exp.get_logger()
log.info(config['DEFAULT']['message'])
# Create an output file in the unique output directory
filename = exp.get_filename('output.csv')
with open(filename, "w") as f:
f.write(config['DEFAULT']['message'] + '\n')
|
en
| 0.591657
|
# Import the logging library # Create a config # Create an experiment # Get the logger and write a log message # Create an output file in the unique output directory
| 2.829704
| 3
|
bioconda_utils/docker_utils.py
|
grst/bioconda-utils
| 0
|
6625756
|
#!/usr/bin/env python
"""
To ensure conda packages are built in the most compatible manner, we can use
a docker container. This module supports using a docker container to build
conda packages in the local channel which can later be uploaded to anaconda.
Note that we cannot simply bind the host's conda-bld directory to the
container's conda-bld directory because during building/testing, symlinks are
made to the conda-pkgs dir which is not necessarily bound. Nor should it be, if
we want to retain isolation from the host when building.
To solve this, we mount the host's conda-bld dir to a temporary directory in
the container. Once the container successfully builds a package, the
corresponding package is copied over to the temporary directory (the host's
conda-bld directory) so that the built package appears on the host.
In the end the workflow is:
- build a custom docker container (assumed to already have conda installed)
where the requirements in
``bioconda-utils/bioconda-utils_requirements.txt`` have been conda
installed.
- mount the host's conda-bld to a read/write temporary dir in the container
(configured in the RecipeBuilder)
- in the container, add this directory as a local channel so that all
previously-built packages can be used as dependencies.
- mount the host's recipe dir to a read-only dir in the container
(configured in the RecipeBuilder)
- build, mount, and run a custom script that conda-builds the mounted
recipe and if successful copies the built package to the mounted host's
conda-bld directory.
Other notes:
- Most communication with the host (conda-bld options; host's UID) is via
environmental variables passed to the container.
- The build script is custom generated each run, providing lots of flexibility.
Most magic happens here.
"""
import os
import os.path
from shlex import quote
import shutil
import subprocess as sp
import tempfile
import pwd
import grp
from textwrap import dedent
import pkg_resources
import re
from distutils.version import LooseVersion
import conda
import conda_build
from . import utils
import logging
logger = logging.getLogger(__name__)
# ----------------------------------------------------------------------------
# BUILD_SCRIPT_TEMPLATE
# ----------------------------------------------------------------------------
#
# The following script is the default that will be regenerated on each call to
# RecipeBuilder.build_recipe() and mounted at container run time when building
# a recipe. It can be overridden by providing a different template when calling
# RecipeBuilder.build_recipe().
#
# It will be filled in using BUILD_SCRIPT_TEMPLATE.format(self=self), so you
# can add additional attributes to the RecipeBuilder instance and have them
# filled in here.
#
BUILD_SCRIPT_TEMPLATE = \
"""
#!/bin/bash
set -eo pipefail
# Add the host's mounted conda-bld dir so that we can use its contents as
# dependencies for building this recipe.
#
# Note that if the directory didn't exist on the host, then the staging area
# will exist in the container but will be empty. Channels expect at least
# a linux-64 and noarch directory within that directory, so we make sure it
# exists before adding the channel.
mkdir -p {self.container_staging}/linux-64
mkdir -p {self.container_staging}/noarch
conda config --add channels file://{self.container_staging} 2> >(
grep -vF "Warning: 'file://{self.container_staging}' already in 'channels' list, moving to the top" >&2
)
# The actual building...
# we explicitly point to the meta.yaml, in order to keep
# conda-build from building all subdirectories
conda build {self.conda_build_args} {self.container_recipe}/meta.yaml 2>&1
# copy all built packages to the staging area
cp `conda build {self.conda_build_args} {self.container_recipe}/meta.yaml --output` {self.container_staging}/{arch}
# Ensure permissions are correct on the host.
HOST_USER={self.user_info[uid]}
chown $HOST_USER:$HOST_USER {self.container_staging}/{arch}/*
""" # noqa: E501,E122: line too long, continuation line missing indentation or outdented
# ----------------------------------------------------------------------------
# DOCKERFILE_TEMPLATE
# ----------------------------------------------------------------------------
#
# This template can be used for last-minute changes to the docker image, such
# as adding proxies.
#
# The default image is created automatically on DockerHub using the Dockerfile
# in the bioconda-utils repo.
DOCKERFILE_TEMPLATE = \
"""
FROM {docker_base_image}
{proxies}
RUN /opt/conda/bin/conda install -y conda={conda_ver} conda-build={conda_build_ver}
""" # noqa: E122 continuation line missing indentation or outdented
class DockerCalledProcessError(sp.CalledProcessError):
pass
class DockerBuildError(Exception):
pass
def get_host_conda_bld():
"""
Identifies the conda-bld directory on the host.
Assumes that conda-build is installed.
"""
# v0.16.2: this used to have a side effect, calling conda build purge
# hopefully, it's not actually needed.
build_conf = utils.load_conda_build_config()
return build_conf.build_folder
class RecipeBuilder(object):
def __init__(
self,
tag='tmp-bioconda-builder',
container_recipe='/opt/recipe',
container_staging="/opt/host-conda-bld",
requirements=None,
build_script_template=BUILD_SCRIPT_TEMPLATE,
dockerfile_template=DOCKERFILE_TEMPLATE,
use_host_conda_bld=False,
pkg_dir=None,
keep_image=False,
build_image=False,
image_build_dir=None,
docker_base_image='bioconda/bioconda-utils-build-env:latest'
):
"""
Class to handle building a custom docker container that can be used for
building conda recipes.
Parameters
----------
tag : str
Tag to be used for the custom-build docker container. Mostly for
debugging purposes when you need to inspect the container.
container_recipe : str
Directory to which the host's recipe will be exported. Will be
read-only.
container_staging : str
Directory to which the host's conda-bld dir will be mounted so that
the container can use previously-built packages as dependencies.
Upon successful building container-built packages will be copied
over. Mounted as read-write.
requirements : None or str
Path to a "requirements.txt" file which will be installed with
conda in a newly-created container. If None, then use the default
installed with bioconda_utils.
build_script_template : str
Template that will be filled in with .format(self=self) and that
will be run in the container each time build_recipe() is called. If
not specified, uses docker_utils.BUILD_SCRIPT_TEMPLATE.
dockerfile_template : str
Template that will be filled in with .format(self=self) and that
will be used to build a custom image. Uses
docker_utils.DOCKERFILE_TEMPLATE by default.
use_host_conda_bld : bool
If True, then use the host's conda-bld directory. This will export
the host's existing conda-bld directory to the docker container,
and any recipes successfully built by the container will be added
here.
Otherwise, use **pkg_dir** as a common host directory used across
multiple runs of this RecipeBuilder object.
pkg_dir : str or None
Specify where packages should appear on the host.
If **pkg_dir** is None, then a temporary directory will be
created once for each `RecipeBuilder` instance and that directory
will be used for each call to `RecipeBuilder.build_recipe()`. This allows
subsequent recipes built by the container to see previous built
recipes without polluting the host's conda-bld directory.
If **pkg_dir** is a string, then it will be created if needed and
this directory will be used store all built packages on the host
instead of the temp dir.
If the above argument **use_host_conda_bld** is `True`, then the value
of **pkg_dir** will be ignored and the host's conda-bld directory
will be used.
In all cases, **pkg_dir** will be mounted to **container_staging** in
the container.
build_image : bool
Build a local layer on top of the **docker_base_image** layer using
**dockerfile_template**. This can be used to adjust the versions of
conda and conda-build in the build container.
keep_image : bool
By default, the built docker image will be removed when done,
freeing up storage space. Set ``keep_image=True`` to disable this
behavior.
image_build_dir : str or None
If not None, use an existing directory as a docker image context
instead of a temporary one. For testing purposes only.
docker_base_image : str or None
Name of base image that can be used in **dockerfile_template**.
Defaults to 'bioconda/bioconda-utils-build-env:latest'
"""
self.requirements = requirements
self.conda_build_args = ""
self.build_script_template = build_script_template
self.dockerfile_template = dockerfile_template
self.keep_image = keep_image
self.build_image = build_image
self.image_build_dir = image_build_dir
self.docker_base_image = docker_base_image
self.docker_temp_image = tag
# find and store user info
uid = os.getuid()
usr = pwd.getpwuid(uid)
self.user_info = dict(
uid=uid,
gid=usr.pw_gid,
groupname=grp.getgrgid(usr.pw_gid).gr_name,
username=usr.pw_name)
self.container_recipe = container_recipe
self.container_staging = container_staging
self.host_conda_bld = get_host_conda_bld()
if use_host_conda_bld:
self.pkg_dir = self.host_conda_bld
else:
if pkg_dir is None:
self.pkg_dir = tempfile.mkdtemp()
else:
if not os.path.exists(pkg_dir):
os.makedirs(pkg_dir)
self.pkg_dir = pkg_dir
# Copy the conda build config files to the staging directory that is
# visible in the container
for i, config_file in enumerate(utils.get_conda_build_config_files()):
dst_file = self._get_config_path(self.pkg_dir, i, config_file)
shutil.copyfile(config_file.path, dst_file)
if self.build_image:
self._build_image()
def _get_config_path(self, staging_prefix, i, config_file):
src_basename = os.path.basename(config_file.path)
dst_basename = 'conda_build_config_{}_{}_{}'.format(i, config_file.arg, src_basename)
return os.path.join(staging_prefix, dst_basename)
def __del__(self):
self.cleanup()
def _find_proxy_settings(self):
res = {}
for var in ('http_proxy', 'https_proxy'):
values = set([
os.environ.get(var, None),
os.environ.get(var.upper(), None)
]).difference([None])
if len(values) == 1:
res[var] = next(iter(values))
elif len(values) > 1:
raise ValueError(f"{var} and {var.upper()} have different values")
return res
def _build_image(self):
"""
Builds a new image with requirements installed.
"""
if self.image_build_dir is None:
# Create a temporary build directory since we'll be copying the
# requirements file over
build_dir = tempfile.mkdtemp()
else:
build_dir = self.image_build_dir
logger.info('DOCKER: Building image "%s" from %s', self.docker_temp_image, build_dir)
with open(os.path.join(build_dir, 'requirements.txt'), 'w') as fout:
if self.requirements:
fout.write(open(self.requirements).read())
else:
fout.write(open(pkg_resources.resource_filename(
'bioconda_utils',
'bioconda_utils-requirements.txt')
).read())
proxies = "\n".join("ENV {} {}".format(k, v)
for k, v in self._find_proxy_settings())
with open(os.path.join(build_dir, "Dockerfile"), 'w') as fout:
fout.write(self.dockerfile_template.format(
docker_base_image=self.docker_base_image,
proxies=proxies,
conda_ver=conda.__version__,
conda_build_ver=conda_build.__version__)
)
logger.debug('Dockerfile:\n' + open(fout.name).read())
# Check if the installed version of docker supports the --network flag
# (requires version >= 1.13.0)
# Parse output of `docker --version` since the format of the
# `docker version` command (note the missing dashes) is not consistent
# between different docker versions. The --version string is the same
# for docker 1.6.2 and 1.12.6
try:
s = sp.check_output(["docker", "--version"]).decode()
except FileNotFoundError:
logger.error('DOCKER FAILED: Error checking docker version, is it installed?')
raise
except sp.CalledProcessError:
logger.error('DOCKER FAILED: Error checking docker version.')
raise
p = re.compile(r"\d+\.\d+\.\d+") # three groups of at least on digit separated by dots
version_string = re.search(p, s).group(0)
if LooseVersion(version_string) >= LooseVersion("1.13.0"):
cmd = [
'docker', 'build',
# xref #5027
'--network', 'host',
'-t', self.docker_temp_image,
build_dir
]
else:
# Network flag was added in 1.13.0, do not add it for lower versions. xref #5387
cmd = [
'docker', 'build',
'-t', self.docker_temp_image,
build_dir
]
try:
with utils.Progress():
p = utils.run(cmd, mask=False)
except sp.CalledProcessError as e:
logger.error(
'DOCKER FAILED: Error building docker container %s. ',
self.docker_temp_image)
raise e
logger.info('DOCKER: Built docker image tag=%s', self.docker_temp_image)
if self.image_build_dir is None:
shutil.rmtree(build_dir)
return p
def build_recipe(self, recipe_dir, build_args, env, noarch=False):
"""
Build a single recipe.
Parameters
----------
recipe_dir : str
Path to recipe that contains meta.yaml
build_args : str
Additional arguments to ``conda build``. For example --channel,
--skip-existing, etc
env : dict
Environmental variables
noarch: bool
Has to be set to true if this is a noarch build
Note that the binds are set up automatically to match the expectations
of the build script, and will use the currently-configured
self.container_staging and self.container_recipe.
"""
# Attach the build args to self so that it can be filled in by the
# template.
if not isinstance(build_args, str):
raise ValueError('build_args must be str')
build_args_list = [build_args]
for i, config_file in enumerate(utils.get_conda_build_config_files()):
dst_file = self._get_config_path(self.container_staging, i, config_file)
build_args_list.extend([config_file.arg, quote(dst_file)])
self.conda_build_args = ' '.join(build_args_list)
# Write build script to tempfile
build_dir = os.path.realpath(tempfile.mkdtemp())
script = self.build_script_template.format(
self=self, arch='noarch' if noarch else 'linux-64')
with open(os.path.join(build_dir, 'build_script.bash'), 'w') as fout:
fout.write(script)
build_script = fout.name
logger.debug('DOCKER: Container build script: \n%s', open(fout.name).read())
# Build the args for env vars. Note can also write these to tempfile
# and use --env-file arg, but using -e seems clearer in debug output.
env_list = []
for k, v in env.items():
env_list.append('-e')
env_list.append('{0}={1}'.format(k, v))
env_list.append('-e')
env_list.append('{0}={1}'.format('HOST_USER_ID', self.user_info['uid']))
cmd = [
'docker', 'run', '-t',
'--net', 'host',
'--rm',
'-v', '{0}:/opt/build_script.bash'.format(build_script),
'-v', '{0}:{1}'.format(self.pkg_dir, self.container_staging),
'-v', '{0}:{1}'.format(recipe_dir, self.container_recipe),
]
cmd += env_list
if self.build_image:
cmd += [self.docker_temp_image]
else:
cmd += [self.docker_base_image]
cmd += ['/bin/bash', '/opt/build_script.bash']
logger.debug('DOCKER: cmd: %s', cmd)
with utils.Progress():
p = utils.run(cmd, mask=False)
return p
def cleanup(self):
if self.build_image and not self.keep_image:
cmd = ['docker', 'rmi', self.docker_temp_image]
utils.run(cmd, mask=False)
|
#!/usr/bin/env python
"""
To ensure conda packages are built in the most compatible manner, we can use
a docker container. This module supports using a docker container to build
conda packages in the local channel which can later be uploaded to anaconda.
Note that we cannot simply bind the host's conda-bld directory to the
container's conda-bld directory because during building/testing, symlinks are
made to the conda-pkgs dir which is not necessarily bound. Nor should it be, if
we want to retain isolation from the host when building.
To solve this, we mount the host's conda-bld dir to a temporary directory in
the container. Once the container successfully builds a package, the
corresponding package is copied over to the temporary directory (the host's
conda-bld directory) so that the built package appears on the host.
In the end the workflow is:
- build a custom docker container (assumed to already have conda installed)
where the requirements in
``bioconda-utils/bioconda-utils_requirements.txt`` have been conda
installed.
- mount the host's conda-bld to a read/write temporary dir in the container
(configured in the RecipeBuilder)
- in the container, add this directory as a local channel so that all
previously-built packages can be used as dependencies.
- mount the host's recipe dir to a read-only dir in the container
(configured in the RecipeBuilder)
- build, mount, and run a custom script that conda-builds the mounted
recipe and if successful copies the built package to the mounted host's
conda-bld directory.
Other notes:
- Most communication with the host (conda-bld options; host's UID) is via
environmental variables passed to the container.
- The build script is custom generated each run, providing lots of flexibility.
Most magic happens here.
"""
import os
import os.path
from shlex import quote
import shutil
import subprocess as sp
import tempfile
import pwd
import grp
from textwrap import dedent
import pkg_resources
import re
from distutils.version import LooseVersion
import conda
import conda_build
from . import utils
import logging
logger = logging.getLogger(__name__)
# ----------------------------------------------------------------------------
# BUILD_SCRIPT_TEMPLATE
# ----------------------------------------------------------------------------
#
# The following script is the default that will be regenerated on each call to
# RecipeBuilder.build_recipe() and mounted at container run time when building
# a recipe. It can be overridden by providing a different template when calling
# RecipeBuilder.build_recipe().
#
# It will be filled in using BUILD_SCRIPT_TEMPLATE.format(self=self), so you
# can add additional attributes to the RecipeBuilder instance and have them
# filled in here.
#
BUILD_SCRIPT_TEMPLATE = \
"""
#!/bin/bash
set -eo pipefail
# Add the host's mounted conda-bld dir so that we can use its contents as
# dependencies for building this recipe.
#
# Note that if the directory didn't exist on the host, then the staging area
# will exist in the container but will be empty. Channels expect at least
# a linux-64 and noarch directory within that directory, so we make sure it
# exists before adding the channel.
mkdir -p {self.container_staging}/linux-64
mkdir -p {self.container_staging}/noarch
conda config --add channels file://{self.container_staging} 2> >(
grep -vF "Warning: 'file://{self.container_staging}' already in 'channels' list, moving to the top" >&2
)
# The actual building...
# we explicitly point to the meta.yaml, in order to keep
# conda-build from building all subdirectories
conda build {self.conda_build_args} {self.container_recipe}/meta.yaml 2>&1
# copy all built packages to the staging area
cp `conda build {self.conda_build_args} {self.container_recipe}/meta.yaml --output` {self.container_staging}/{arch}
# Ensure permissions are correct on the host.
HOST_USER={self.user_info[uid]}
chown $HOST_USER:$HOST_USER {self.container_staging}/{arch}/*
""" # noqa: E501,E122: line too long, continuation line missing indentation or outdented
# ----------------------------------------------------------------------------
# DOCKERFILE_TEMPLATE
# ----------------------------------------------------------------------------
#
# This template can be used for last-minute changes to the docker image, such
# as adding proxies.
#
# The default image is created automatically on DockerHub using the Dockerfile
# in the bioconda-utils repo.
DOCKERFILE_TEMPLATE = \
"""
FROM {docker_base_image}
{proxies}
RUN /opt/conda/bin/conda install -y conda={conda_ver} conda-build={conda_build_ver}
""" # noqa: E122 continuation line missing indentation or outdented
class DockerCalledProcessError(sp.CalledProcessError):
pass
class DockerBuildError(Exception):
pass
def get_host_conda_bld():
"""
Identifies the conda-bld directory on the host.
Assumes that conda-build is installed.
"""
# v0.16.2: this used to have a side effect, calling conda build purge
# hopefully, it's not actually needed.
build_conf = utils.load_conda_build_config()
return build_conf.build_folder
class RecipeBuilder(object):
def __init__(
self,
tag='tmp-bioconda-builder',
container_recipe='/opt/recipe',
container_staging="/opt/host-conda-bld",
requirements=None,
build_script_template=BUILD_SCRIPT_TEMPLATE,
dockerfile_template=DOCKERFILE_TEMPLATE,
use_host_conda_bld=False,
pkg_dir=None,
keep_image=False,
build_image=False,
image_build_dir=None,
docker_base_image='bioconda/bioconda-utils-build-env:latest'
):
"""
Class to handle building a custom docker container that can be used for
building conda recipes.
Parameters
----------
tag : str
Tag to be used for the custom-build docker container. Mostly for
debugging purposes when you need to inspect the container.
container_recipe : str
Directory to which the host's recipe will be exported. Will be
read-only.
container_staging : str
Directory to which the host's conda-bld dir will be mounted so that
the container can use previously-built packages as dependencies.
Upon successful building container-built packages will be copied
over. Mounted as read-write.
requirements : None or str
Path to a "requirements.txt" file which will be installed with
conda in a newly-created container. If None, then use the default
installed with bioconda_utils.
build_script_template : str
Template that will be filled in with .format(self=self) and that
will be run in the container each time build_recipe() is called. If
not specified, uses docker_utils.BUILD_SCRIPT_TEMPLATE.
dockerfile_template : str
Template that will be filled in with .format(self=self) and that
will be used to build a custom image. Uses
docker_utils.DOCKERFILE_TEMPLATE by default.
use_host_conda_bld : bool
If True, then use the host's conda-bld directory. This will export
the host's existing conda-bld directory to the docker container,
and any recipes successfully built by the container will be added
here.
Otherwise, use **pkg_dir** as a common host directory used across
multiple runs of this RecipeBuilder object.
pkg_dir : str or None
Specify where packages should appear on the host.
If **pkg_dir** is None, then a temporary directory will be
created once for each `RecipeBuilder` instance and that directory
will be used for each call to `RecipeBuilder.build_recipe()`. This allows
subsequent recipes built by the container to see previous built
recipes without polluting the host's conda-bld directory.
If **pkg_dir** is a string, then it will be created if needed and
this directory will be used store all built packages on the host
instead of the temp dir.
If the above argument **use_host_conda_bld** is `True`, then the value
of **pkg_dir** will be ignored and the host's conda-bld directory
will be used.
In all cases, **pkg_dir** will be mounted to **container_staging** in
the container.
build_image : bool
Build a local layer on top of the **docker_base_image** layer using
**dockerfile_template**. This can be used to adjust the versions of
conda and conda-build in the build container.
keep_image : bool
By default, the built docker image will be removed when done,
freeing up storage space. Set ``keep_image=True`` to disable this
behavior.
image_build_dir : str or None
If not None, use an existing directory as a docker image context
instead of a temporary one. For testing purposes only.
docker_base_image : str or None
Name of base image that can be used in **dockerfile_template**.
Defaults to 'bioconda/bioconda-utils-build-env:latest'
"""
self.requirements = requirements
self.conda_build_args = ""
self.build_script_template = build_script_template
self.dockerfile_template = dockerfile_template
self.keep_image = keep_image
self.build_image = build_image
self.image_build_dir = image_build_dir
self.docker_base_image = docker_base_image
self.docker_temp_image = tag
# find and store user info
uid = os.getuid()
usr = pwd.getpwuid(uid)
self.user_info = dict(
uid=uid,
gid=usr.pw_gid,
groupname=grp.getgrgid(usr.pw_gid).gr_name,
username=usr.pw_name)
self.container_recipe = container_recipe
self.container_staging = container_staging
self.host_conda_bld = get_host_conda_bld()
if use_host_conda_bld:
self.pkg_dir = self.host_conda_bld
else:
if pkg_dir is None:
self.pkg_dir = tempfile.mkdtemp()
else:
if not os.path.exists(pkg_dir):
os.makedirs(pkg_dir)
self.pkg_dir = pkg_dir
# Copy the conda build config files to the staging directory that is
# visible in the container
for i, config_file in enumerate(utils.get_conda_build_config_files()):
dst_file = self._get_config_path(self.pkg_dir, i, config_file)
shutil.copyfile(config_file.path, dst_file)
if self.build_image:
self._build_image()
def _get_config_path(self, staging_prefix, i, config_file):
src_basename = os.path.basename(config_file.path)
dst_basename = 'conda_build_config_{}_{}_{}'.format(i, config_file.arg, src_basename)
return os.path.join(staging_prefix, dst_basename)
def __del__(self):
self.cleanup()
def _find_proxy_settings(self):
res = {}
for var in ('http_proxy', 'https_proxy'):
values = set([
os.environ.get(var, None),
os.environ.get(var.upper(), None)
]).difference([None])
if len(values) == 1:
res[var] = next(iter(values))
elif len(values) > 1:
raise ValueError(f"{var} and {var.upper()} have different values")
return res
def _build_image(self):
"""
Builds a new image with requirements installed.
"""
if self.image_build_dir is None:
# Create a temporary build directory since we'll be copying the
# requirements file over
build_dir = tempfile.mkdtemp()
else:
build_dir = self.image_build_dir
logger.info('DOCKER: Building image "%s" from %s', self.docker_temp_image, build_dir)
with open(os.path.join(build_dir, 'requirements.txt'), 'w') as fout:
if self.requirements:
fout.write(open(self.requirements).read())
else:
fout.write(open(pkg_resources.resource_filename(
'bioconda_utils',
'bioconda_utils-requirements.txt')
).read())
proxies = "\n".join("ENV {} {}".format(k, v)
for k, v in self._find_proxy_settings())
with open(os.path.join(build_dir, "Dockerfile"), 'w') as fout:
fout.write(self.dockerfile_template.format(
docker_base_image=self.docker_base_image,
proxies=proxies,
conda_ver=conda.__version__,
conda_build_ver=conda_build.__version__)
)
logger.debug('Dockerfile:\n' + open(fout.name).read())
# Check if the installed version of docker supports the --network flag
# (requires version >= 1.13.0)
# Parse output of `docker --version` since the format of the
# `docker version` command (note the missing dashes) is not consistent
# between different docker versions. The --version string is the same
# for docker 1.6.2 and 1.12.6
try:
s = sp.check_output(["docker", "--version"]).decode()
except FileNotFoundError:
logger.error('DOCKER FAILED: Error checking docker version, is it installed?')
raise
except sp.CalledProcessError:
logger.error('DOCKER FAILED: Error checking docker version.')
raise
p = re.compile(r"\d+\.\d+\.\d+") # three groups of at least on digit separated by dots
version_string = re.search(p, s).group(0)
if LooseVersion(version_string) >= LooseVersion("1.13.0"):
cmd = [
'docker', 'build',
# xref #5027
'--network', 'host',
'-t', self.docker_temp_image,
build_dir
]
else:
# Network flag was added in 1.13.0, do not add it for lower versions. xref #5387
cmd = [
'docker', 'build',
'-t', self.docker_temp_image,
build_dir
]
try:
with utils.Progress():
p = utils.run(cmd, mask=False)
except sp.CalledProcessError as e:
logger.error(
'DOCKER FAILED: Error building docker container %s. ',
self.docker_temp_image)
raise e
logger.info('DOCKER: Built docker image tag=%s', self.docker_temp_image)
if self.image_build_dir is None:
shutil.rmtree(build_dir)
return p
def build_recipe(self, recipe_dir, build_args, env, noarch=False):
"""
Build a single recipe.
Parameters
----------
recipe_dir : str
Path to recipe that contains meta.yaml
build_args : str
Additional arguments to ``conda build``. For example --channel,
--skip-existing, etc
env : dict
Environmental variables
noarch: bool
Has to be set to true if this is a noarch build
Note that the binds are set up automatically to match the expectations
of the build script, and will use the currently-configured
self.container_staging and self.container_recipe.
"""
# Attach the build args to self so that it can be filled in by the
# template.
if not isinstance(build_args, str):
raise ValueError('build_args must be str')
build_args_list = [build_args]
for i, config_file in enumerate(utils.get_conda_build_config_files()):
dst_file = self._get_config_path(self.container_staging, i, config_file)
build_args_list.extend([config_file.arg, quote(dst_file)])
self.conda_build_args = ' '.join(build_args_list)
# Write build script to tempfile
build_dir = os.path.realpath(tempfile.mkdtemp())
script = self.build_script_template.format(
self=self, arch='noarch' if noarch else 'linux-64')
with open(os.path.join(build_dir, 'build_script.bash'), 'w') as fout:
fout.write(script)
build_script = fout.name
logger.debug('DOCKER: Container build script: \n%s', open(fout.name).read())
# Build the args for env vars. Note can also write these to tempfile
# and use --env-file arg, but using -e seems clearer in debug output.
env_list = []
for k, v in env.items():
env_list.append('-e')
env_list.append('{0}={1}'.format(k, v))
env_list.append('-e')
env_list.append('{0}={1}'.format('HOST_USER_ID', self.user_info['uid']))
cmd = [
'docker', 'run', '-t',
'--net', 'host',
'--rm',
'-v', '{0}:/opt/build_script.bash'.format(build_script),
'-v', '{0}:{1}'.format(self.pkg_dir, self.container_staging),
'-v', '{0}:{1}'.format(recipe_dir, self.container_recipe),
]
cmd += env_list
if self.build_image:
cmd += [self.docker_temp_image]
else:
cmd += [self.docker_base_image]
cmd += ['/bin/bash', '/opt/build_script.bash']
logger.debug('DOCKER: cmd: %s', cmd)
with utils.Progress():
p = utils.run(cmd, mask=False)
return p
def cleanup(self):
if self.build_image and not self.keep_image:
cmd = ['docker', 'rmi', self.docker_temp_image]
utils.run(cmd, mask=False)
|
en
| 0.77908
|
#!/usr/bin/env python To ensure conda packages are built in the most compatible manner, we can use a docker container. This module supports using a docker container to build conda packages in the local channel which can later be uploaded to anaconda. Note that we cannot simply bind the host's conda-bld directory to the container's conda-bld directory because during building/testing, symlinks are made to the conda-pkgs dir which is not necessarily bound. Nor should it be, if we want to retain isolation from the host when building. To solve this, we mount the host's conda-bld dir to a temporary directory in the container. Once the container successfully builds a package, the corresponding package is copied over to the temporary directory (the host's conda-bld directory) so that the built package appears on the host. In the end the workflow is: - build a custom docker container (assumed to already have conda installed) where the requirements in ``bioconda-utils/bioconda-utils_requirements.txt`` have been conda installed. - mount the host's conda-bld to a read/write temporary dir in the container (configured in the RecipeBuilder) - in the container, add this directory as a local channel so that all previously-built packages can be used as dependencies. - mount the host's recipe dir to a read-only dir in the container (configured in the RecipeBuilder) - build, mount, and run a custom script that conda-builds the mounted recipe and if successful copies the built package to the mounted host's conda-bld directory. Other notes: - Most communication with the host (conda-bld options; host's UID) is via environmental variables passed to the container. - The build script is custom generated each run, providing lots of flexibility. Most magic happens here. # ---------------------------------------------------------------------------- # BUILD_SCRIPT_TEMPLATE # ---------------------------------------------------------------------------- # # The following script is the default that will be regenerated on each call to # RecipeBuilder.build_recipe() and mounted at container run time when building # a recipe. It can be overridden by providing a different template when calling # RecipeBuilder.build_recipe(). # # It will be filled in using BUILD_SCRIPT_TEMPLATE.format(self=self), so you # can add additional attributes to the RecipeBuilder instance and have them # filled in here. # #!/bin/bash set -eo pipefail # Add the host's mounted conda-bld dir so that we can use its contents as # dependencies for building this recipe. # # Note that if the directory didn't exist on the host, then the staging area # will exist in the container but will be empty. Channels expect at least # a linux-64 and noarch directory within that directory, so we make sure it # exists before adding the channel. mkdir -p {self.container_staging}/linux-64 mkdir -p {self.container_staging}/noarch conda config --add channels file://{self.container_staging} 2> >( grep -vF "Warning: 'file://{self.container_staging}' already in 'channels' list, moving to the top" >&2 ) # The actual building... # we explicitly point to the meta.yaml, in order to keep # conda-build from building all subdirectories conda build {self.conda_build_args} {self.container_recipe}/meta.yaml 2>&1 # copy all built packages to the staging area cp `conda build {self.conda_build_args} {self.container_recipe}/meta.yaml --output` {self.container_staging}/{arch} # Ensure permissions are correct on the host. HOST_USER={self.user_info[uid]} chown $HOST_USER:$HOST_USER {self.container_staging}/{arch}/* # noqa: E501,E122: line too long, continuation line missing indentation or outdented # ---------------------------------------------------------------------------- # DOCKERFILE_TEMPLATE # ---------------------------------------------------------------------------- # # This template can be used for last-minute changes to the docker image, such # as adding proxies. # # The default image is created automatically on DockerHub using the Dockerfile # in the bioconda-utils repo. FROM {docker_base_image} {proxies} RUN /opt/conda/bin/conda install -y conda={conda_ver} conda-build={conda_build_ver} # noqa: E122 continuation line missing indentation or outdented Identifies the conda-bld directory on the host. Assumes that conda-build is installed. # v0.16.2: this used to have a side effect, calling conda build purge # hopefully, it's not actually needed. Class to handle building a custom docker container that can be used for building conda recipes. Parameters ---------- tag : str Tag to be used for the custom-build docker container. Mostly for debugging purposes when you need to inspect the container. container_recipe : str Directory to which the host's recipe will be exported. Will be read-only. container_staging : str Directory to which the host's conda-bld dir will be mounted so that the container can use previously-built packages as dependencies. Upon successful building container-built packages will be copied over. Mounted as read-write. requirements : None or str Path to a "requirements.txt" file which will be installed with conda in a newly-created container. If None, then use the default installed with bioconda_utils. build_script_template : str Template that will be filled in with .format(self=self) and that will be run in the container each time build_recipe() is called. If not specified, uses docker_utils.BUILD_SCRIPT_TEMPLATE. dockerfile_template : str Template that will be filled in with .format(self=self) and that will be used to build a custom image. Uses docker_utils.DOCKERFILE_TEMPLATE by default. use_host_conda_bld : bool If True, then use the host's conda-bld directory. This will export the host's existing conda-bld directory to the docker container, and any recipes successfully built by the container will be added here. Otherwise, use **pkg_dir** as a common host directory used across multiple runs of this RecipeBuilder object. pkg_dir : str or None Specify where packages should appear on the host. If **pkg_dir** is None, then a temporary directory will be created once for each `RecipeBuilder` instance and that directory will be used for each call to `RecipeBuilder.build_recipe()`. This allows subsequent recipes built by the container to see previous built recipes without polluting the host's conda-bld directory. If **pkg_dir** is a string, then it will be created if needed and this directory will be used store all built packages on the host instead of the temp dir. If the above argument **use_host_conda_bld** is `True`, then the value of **pkg_dir** will be ignored and the host's conda-bld directory will be used. In all cases, **pkg_dir** will be mounted to **container_staging** in the container. build_image : bool Build a local layer on top of the **docker_base_image** layer using **dockerfile_template**. This can be used to adjust the versions of conda and conda-build in the build container. keep_image : bool By default, the built docker image will be removed when done, freeing up storage space. Set ``keep_image=True`` to disable this behavior. image_build_dir : str or None If not None, use an existing directory as a docker image context instead of a temporary one. For testing purposes only. docker_base_image : str or None Name of base image that can be used in **dockerfile_template**. Defaults to 'bioconda/bioconda-utils-build-env:latest' # find and store user info # Copy the conda build config files to the staging directory that is # visible in the container Builds a new image with requirements installed. # Create a temporary build directory since we'll be copying the # requirements file over # Check if the installed version of docker supports the --network flag # (requires version >= 1.13.0) # Parse output of `docker --version` since the format of the # `docker version` command (note the missing dashes) is not consistent # between different docker versions. The --version string is the same # for docker 1.6.2 and 1.12.6 # three groups of at least on digit separated by dots # xref #5027 # Network flag was added in 1.13.0, do not add it for lower versions. xref #5387 Build a single recipe. Parameters ---------- recipe_dir : str Path to recipe that contains meta.yaml build_args : str Additional arguments to ``conda build``. For example --channel, --skip-existing, etc env : dict Environmental variables noarch: bool Has to be set to true if this is a noarch build Note that the binds are set up automatically to match the expectations of the build script, and will use the currently-configured self.container_staging and self.container_recipe. # Attach the build args to self so that it can be filled in by the # template. # Write build script to tempfile # Build the args for env vars. Note can also write these to tempfile # and use --env-file arg, but using -e seems clearer in debug output.
| 2.419465
| 2
|
examples/schedulers/sync.py
|
sasirajpuvvada/apscheduler
| 4,294
|
6625757
|
<gh_stars>1000+
import logging
from apscheduler.schedulers.sync import Scheduler
from apscheduler.triggers.interval import IntervalTrigger
from apscheduler.workers.sync import Worker
def say_hello():
print('Hello!')
logging.basicConfig(level=logging.DEBUG)
try:
with Scheduler() as scheduler, Worker(scheduler.data_store, portal=scheduler.portal):
scheduler.add_schedule(say_hello, IntervalTrigger(seconds=1))
scheduler.wait_until_stopped()
except (KeyboardInterrupt, SystemExit):
pass
|
import logging
from apscheduler.schedulers.sync import Scheduler
from apscheduler.triggers.interval import IntervalTrigger
from apscheduler.workers.sync import Worker
def say_hello():
print('Hello!')
logging.basicConfig(level=logging.DEBUG)
try:
with Scheduler() as scheduler, Worker(scheduler.data_store, portal=scheduler.portal):
scheduler.add_schedule(say_hello, IntervalTrigger(seconds=1))
scheduler.wait_until_stopped()
except (KeyboardInterrupt, SystemExit):
pass
|
none
| 1
| 2.335916
| 2
|
|
adblocker.py
|
iam-shanmukha/adlocker
| 3
|
6625758
|
<filename>adblocker.py
#!/usr/bin/python
import os,sys, platform
import datetime
hosts = ["https://adaway.org/hosts.txt",
"https://raw.githubusercontent.com/StevenBlack/hosts/master/hosts"]
WINDOWS_ETC = "c:\\Windows\\System32\\Drivers\\etc\\"
WINDOWS_HOSTS = "c:\\Windows\\System32\\Drivers\\etc\\hosts"
count = 1
print(r'''
_ _ _ _
__ _ __| | |__ | | ___ ___| | _____ _ __ _ __ _ _
/ _` |/ _` | '_ \| |/ _ \ / __| |/ / _ \ '__| | '_ \| | | |
| (_| | (_| | |_) | | (_) | (__| < __/ | _ | |_) | |_| |
\__,_|\__,_|_.__/|_|\___/ \___|_|\_\___|_| (_) | .__/ \__, |
|_| |___/
@gitub.com/iam-shanmukha
''')
basename = "hosts_"
suffix = datetime.datetime.now().strftime("%d%m%y_%H%M%S")
filename = "_".join([basename, suffix])
def execute():
global count
os.system(cmd)
print(f'completed {count}/{len(hosts)}')
count = count+1
if platform.system() == 'Linux':
print("Starting Script on Linux")
try:
if os.geteuid() !=0:
raise PermissionError
os.system(r"sudo cp /etc/hosts /etc/{}".format(filename))
print("Backup success \nBackup file --> /etc/{}".format(filename))
open('/etc/hosts', 'w').close()
for i in hosts:
cmd = f'sudo curl -s {i} >> /etc/hosts'
execute()
print("Successfully Blocked Ad's")
sys.exit()
except PermissionError:
print("Please run as root \nsudo python adblocker.py")
sys.exit()
elif platform.system() == 'Windows':
print("starting Script on Windows")
try:
os.system(f'copy {WINDOWS_HOSTS} {WINDOWS_ETC}{filename} /y')
print(f'Backup success \nBackup file --> {WINDOWS_ETC}{filename}')
open(f'{WINDOWS_HOSTS}','w').close()
for i in hosts:
cmd = f'curl -s {i} >> {WINDOWS_HOSTS}'
execute()
print("Successfully Blocked AD's")
sys.exit()
except PermissionError:
print("Abort! Please run as Administrator")
sys.exit()
else:
print("Sorry! Platform Not Supported")
|
<filename>adblocker.py
#!/usr/bin/python
import os,sys, platform
import datetime
hosts = ["https://adaway.org/hosts.txt",
"https://raw.githubusercontent.com/StevenBlack/hosts/master/hosts"]
WINDOWS_ETC = "c:\\Windows\\System32\\Drivers\\etc\\"
WINDOWS_HOSTS = "c:\\Windows\\System32\\Drivers\\etc\\hosts"
count = 1
print(r'''
_ _ _ _
__ _ __| | |__ | | ___ ___| | _____ _ __ _ __ _ _
/ _` |/ _` | '_ \| |/ _ \ / __| |/ / _ \ '__| | '_ \| | | |
| (_| | (_| | |_) | | (_) | (__| < __/ | _ | |_) | |_| |
\__,_|\__,_|_.__/|_|\___/ \___|_|\_\___|_| (_) | .__/ \__, |
|_| |___/
@gitub.com/iam-shanmukha
''')
basename = "hosts_"
suffix = datetime.datetime.now().strftime("%d%m%y_%H%M%S")
filename = "_".join([basename, suffix])
def execute():
global count
os.system(cmd)
print(f'completed {count}/{len(hosts)}')
count = count+1
if platform.system() == 'Linux':
print("Starting Script on Linux")
try:
if os.geteuid() !=0:
raise PermissionError
os.system(r"sudo cp /etc/hosts /etc/{}".format(filename))
print("Backup success \nBackup file --> /etc/{}".format(filename))
open('/etc/hosts', 'w').close()
for i in hosts:
cmd = f'sudo curl -s {i} >> /etc/hosts'
execute()
print("Successfully Blocked Ad's")
sys.exit()
except PermissionError:
print("Please run as root \nsudo python adblocker.py")
sys.exit()
elif platform.system() == 'Windows':
print("starting Script on Windows")
try:
os.system(f'copy {WINDOWS_HOSTS} {WINDOWS_ETC}{filename} /y')
print(f'Backup success \nBackup file --> {WINDOWS_ETC}{filename}')
open(f'{WINDOWS_HOSTS}','w').close()
for i in hosts:
cmd = f'curl -s {i} >> {WINDOWS_HOSTS}'
execute()
print("Successfully Blocked AD's")
sys.exit()
except PermissionError:
print("Abort! Please run as Administrator")
sys.exit()
else:
print("Sorry! Platform Not Supported")
|
en
| 0.310139
|
#!/usr/bin/python _ _ _ _ __ _ __| | |__ | | ___ ___| | _____ _ __ _ __ _ _ / _` |/ _` | '_ \| |/ _ \ / __| |/ / _ \ '__| | '_ \| | | | | (_| | (_| | |_) | | (_) | (__| < __/ | _ | |_) | |_| | \__,_|\__,_|_.__/|_|\___/ \___|_|\_\___|_| (_) | .__/ \__, | |_| |___/ @gitub.com/iam-shanmukha
| 2.382369
| 2
|
cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_infra_dumper_cfg.py
|
tkamata-test/ydk-py
| 0
|
6625759
|
<filename>cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_infra_dumper_cfg.py
""" Cisco_IOS_XR_infra_dumper_cfg
This module contains a collection of YANG definitions
for Cisco IOS\-XR infra\-dumper package configuration.
This module contains definitions
for the following management objects\:
exception\: Core dump configuration commands
Copyright (c) 2013\-2016 by Cisco Systems, Inc.
All rights reserved.
"""
import re
import collections
from enum import Enum
from ydk.types import Empty, YList, YLeafList, DELETE, Decimal64, FixedBitsDict
from ydk.errors import YPYError, YPYModelError
class Exception(object):
"""
Core dump configuration commands
.. attribute:: choice1
Preference of the dump location
**type**\: :py:class:`Choice1 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice1>`
.. attribute:: choice2
Preference of the dump location
**type**\: :py:class:`Choice2 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice2>`
.. attribute:: choice3
Preference of the dump location
**type**\: :py:class:`Choice3 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice3>`
.. attribute:: kernel_debugger
Enable kernel debugger
**type**\: :py:class:`Empty<ydk.types.Empty>`
.. attribute:: packet_memory
Specify 'true' to dump packet memory for all process, 'false' to disable dump of packet memory
**type**\: bool
.. attribute:: sparse
Specify 'true' to enable sparse core dump, 'false' to disable sparse core dump
**type**\: bool
.. attribute:: sparse_size
Switch to sparse core dump at this size
**type**\: int
**range:** 1..4095
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.choice1 = Exception.Choice1()
self.choice1.parent = self
self.choice2 = Exception.Choice2()
self.choice2.parent = self
self.choice3 = Exception.Choice3()
self.choice3.parent = self
self.kernel_debugger = None
self.packet_memory = None
self.sparse = None
self.sparse_size = None
class Choice1(object):
"""
Preference of the dump location
.. attribute:: compress
Specify 'true' to compress core files dumped on this path, 'false' to not compress
**type**\: bool
.. attribute:: file_path
Protocol and directory
**type**\: str
.. attribute:: filename
Dump filename
**type**\: str
.. attribute:: higher_limit
Higher limit. This is required if Filename is specified
**type**\: int
**range:** 5..64
.. attribute:: lower_limit
Lower limit. This is required if Filename is specified
**type**\: int
**range:** 0..4
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.parent = None
self.compress = None
self.file_path = None
self.filename = None
self.higher_limit = None
self.lower_limit = None
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception/Cisco-IOS-XR-infra-dumper-cfg:choice1'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.compress is not None:
return True
if self.file_path is not None:
return True
if self.filename is not None:
return True
if self.higher_limit is not None:
return True
if self.lower_limit is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception.Choice1']['meta_info']
class Choice3(object):
"""
Preference of the dump location
.. attribute:: compress
Specify 'true' to compress core files dumped on this path, 'false' to not compress
**type**\: bool
.. attribute:: file_path
Protocol and directory
**type**\: str
.. attribute:: filename
Dump filename
**type**\: str
.. attribute:: higher_limit
Higher limit. This is required if Filename is specified
**type**\: int
**range:** 5..64
.. attribute:: lower_limit
Lower limit. This is required if Filename is specified
**type**\: int
**range:** 0..4
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.parent = None
self.compress = None
self.file_path = None
self.filename = None
self.higher_limit = None
self.lower_limit = None
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception/Cisco-IOS-XR-infra-dumper-cfg:choice3'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.compress is not None:
return True
if self.file_path is not None:
return True
if self.filename is not None:
return True
if self.higher_limit is not None:
return True
if self.lower_limit is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception.Choice3']['meta_info']
class Choice2(object):
"""
Preference of the dump location
.. attribute:: compress
Specify 'true' to compress core files dumped on this path, 'false' to not compress
**type**\: bool
.. attribute:: file_path
Protocol and directory
**type**\: str
.. attribute:: filename
Dump filename
**type**\: str
.. attribute:: higher_limit
Higher limit. This is required if Filename is specified
**type**\: int
**range:** 5..64
.. attribute:: lower_limit
Lower limit. This is required if Filename is specified
**type**\: int
**range:** 0..4
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.parent = None
self.compress = None
self.file_path = None
self.filename = None
self.higher_limit = None
self.lower_limit = None
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception/Cisco-IOS-XR-infra-dumper-cfg:choice2'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.compress is not None:
return True
if self.file_path is not None:
return True
if self.filename is not None:
return True
if self.higher_limit is not None:
return True
if self.lower_limit is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception.Choice2']['meta_info']
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.choice1 is not None and self.choice1._has_data():
return True
if self.choice2 is not None and self.choice2._has_data():
return True
if self.choice3 is not None and self.choice3._has_data():
return True
if self.kernel_debugger is not None:
return True
if self.packet_memory is not None:
return True
if self.sparse is not None:
return True
if self.sparse_size is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception']['meta_info']
|
<filename>cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_infra_dumper_cfg.py
""" Cisco_IOS_XR_infra_dumper_cfg
This module contains a collection of YANG definitions
for Cisco IOS\-XR infra\-dumper package configuration.
This module contains definitions
for the following management objects\:
exception\: Core dump configuration commands
Copyright (c) 2013\-2016 by Cisco Systems, Inc.
All rights reserved.
"""
import re
import collections
from enum import Enum
from ydk.types import Empty, YList, YLeafList, DELETE, Decimal64, FixedBitsDict
from ydk.errors import YPYError, YPYModelError
class Exception(object):
"""
Core dump configuration commands
.. attribute:: choice1
Preference of the dump location
**type**\: :py:class:`Choice1 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice1>`
.. attribute:: choice2
Preference of the dump location
**type**\: :py:class:`Choice2 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice2>`
.. attribute:: choice3
Preference of the dump location
**type**\: :py:class:`Choice3 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice3>`
.. attribute:: kernel_debugger
Enable kernel debugger
**type**\: :py:class:`Empty<ydk.types.Empty>`
.. attribute:: packet_memory
Specify 'true' to dump packet memory for all process, 'false' to disable dump of packet memory
**type**\: bool
.. attribute:: sparse
Specify 'true' to enable sparse core dump, 'false' to disable sparse core dump
**type**\: bool
.. attribute:: sparse_size
Switch to sparse core dump at this size
**type**\: int
**range:** 1..4095
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.choice1 = Exception.Choice1()
self.choice1.parent = self
self.choice2 = Exception.Choice2()
self.choice2.parent = self
self.choice3 = Exception.Choice3()
self.choice3.parent = self
self.kernel_debugger = None
self.packet_memory = None
self.sparse = None
self.sparse_size = None
class Choice1(object):
"""
Preference of the dump location
.. attribute:: compress
Specify 'true' to compress core files dumped on this path, 'false' to not compress
**type**\: bool
.. attribute:: file_path
Protocol and directory
**type**\: str
.. attribute:: filename
Dump filename
**type**\: str
.. attribute:: higher_limit
Higher limit. This is required if Filename is specified
**type**\: int
**range:** 5..64
.. attribute:: lower_limit
Lower limit. This is required if Filename is specified
**type**\: int
**range:** 0..4
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.parent = None
self.compress = None
self.file_path = None
self.filename = None
self.higher_limit = None
self.lower_limit = None
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception/Cisco-IOS-XR-infra-dumper-cfg:choice1'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.compress is not None:
return True
if self.file_path is not None:
return True
if self.filename is not None:
return True
if self.higher_limit is not None:
return True
if self.lower_limit is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception.Choice1']['meta_info']
class Choice3(object):
"""
Preference of the dump location
.. attribute:: compress
Specify 'true' to compress core files dumped on this path, 'false' to not compress
**type**\: bool
.. attribute:: file_path
Protocol and directory
**type**\: str
.. attribute:: filename
Dump filename
**type**\: str
.. attribute:: higher_limit
Higher limit. This is required if Filename is specified
**type**\: int
**range:** 5..64
.. attribute:: lower_limit
Lower limit. This is required if Filename is specified
**type**\: int
**range:** 0..4
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.parent = None
self.compress = None
self.file_path = None
self.filename = None
self.higher_limit = None
self.lower_limit = None
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception/Cisco-IOS-XR-infra-dumper-cfg:choice3'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.compress is not None:
return True
if self.file_path is not None:
return True
if self.filename is not None:
return True
if self.higher_limit is not None:
return True
if self.lower_limit is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception.Choice3']['meta_info']
class Choice2(object):
"""
Preference of the dump location
.. attribute:: compress
Specify 'true' to compress core files dumped on this path, 'false' to not compress
**type**\: bool
.. attribute:: file_path
Protocol and directory
**type**\: str
.. attribute:: filename
Dump filename
**type**\: str
.. attribute:: higher_limit
Higher limit. This is required if Filename is specified
**type**\: int
**range:** 5..64
.. attribute:: lower_limit
Lower limit. This is required if Filename is specified
**type**\: int
**range:** 0..4
"""
_prefix = 'infra-dumper-cfg'
_revision = '2015-11-09'
def __init__(self):
self.parent = None
self.compress = None
self.file_path = None
self.filename = None
self.higher_limit = None
self.lower_limit = None
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception/Cisco-IOS-XR-infra-dumper-cfg:choice2'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.compress is not None:
return True
if self.file_path is not None:
return True
if self.filename is not None:
return True
if self.higher_limit is not None:
return True
if self.lower_limit is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception.Choice2']['meta_info']
@property
def _common_path(self):
return '/Cisco-IOS-XR-infra-dumper-cfg:exception'
def is_config(self):
''' Returns True if this instance represents config data else returns False '''
return True
def _has_data(self):
if not self.is_config():
return False
if self.choice1 is not None and self.choice1._has_data():
return True
if self.choice2 is not None and self.choice2._has_data():
return True
if self.choice3 is not None and self.choice3._has_data():
return True
if self.kernel_debugger is not None:
return True
if self.packet_memory is not None:
return True
if self.sparse is not None:
return True
if self.sparse_size is not None:
return True
return False
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_infra_dumper_cfg as meta
return meta._meta_table['Exception']['meta_info']
|
en
| 0.405607
|
Cisco_IOS_XR_infra_dumper_cfg This module contains a collection of YANG definitions for Cisco IOS\-XR infra\-dumper package configuration. This module contains definitions for the following management objects\: exception\: Core dump configuration commands Copyright (c) 2013\-2016 by Cisco Systems, Inc. All rights reserved. Core dump configuration commands .. attribute:: choice1 Preference of the dump location **type**\: :py:class:`Choice1 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice1>` .. attribute:: choice2 Preference of the dump location **type**\: :py:class:`Choice2 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice2>` .. attribute:: choice3 Preference of the dump location **type**\: :py:class:`Choice3 <ydk.models.cisco_ios_xr.Cisco_IOS_XR_infra_dumper_cfg.Exception.Choice3>` .. attribute:: kernel_debugger Enable kernel debugger **type**\: :py:class:`Empty<ydk.types.Empty>` .. attribute:: packet_memory Specify 'true' to dump packet memory for all process, 'false' to disable dump of packet memory **type**\: bool .. attribute:: sparse Specify 'true' to enable sparse core dump, 'false' to disable sparse core dump **type**\: bool .. attribute:: sparse_size Switch to sparse core dump at this size **type**\: int **range:** 1..4095 Preference of the dump location .. attribute:: compress Specify 'true' to compress core files dumped on this path, 'false' to not compress **type**\: bool .. attribute:: file_path Protocol and directory **type**\: str .. attribute:: filename Dump filename **type**\: str .. attribute:: higher_limit Higher limit. This is required if Filename is specified **type**\: int **range:** 5..64 .. attribute:: lower_limit Lower limit. This is required if Filename is specified **type**\: int **range:** 0..4 Returns True if this instance represents config data else returns False Preference of the dump location .. attribute:: compress Specify 'true' to compress core files dumped on this path, 'false' to not compress **type**\: bool .. attribute:: file_path Protocol and directory **type**\: str .. attribute:: filename Dump filename **type**\: str .. attribute:: higher_limit Higher limit. This is required if Filename is specified **type**\: int **range:** 5..64 .. attribute:: lower_limit Lower limit. This is required if Filename is specified **type**\: int **range:** 0..4 Returns True if this instance represents config data else returns False Preference of the dump location .. attribute:: compress Specify 'true' to compress core files dumped on this path, 'false' to not compress **type**\: bool .. attribute:: file_path Protocol and directory **type**\: str .. attribute:: filename Dump filename **type**\: str .. attribute:: higher_limit Higher limit. This is required if Filename is specified **type**\: int **range:** 5..64 .. attribute:: lower_limit Lower limit. This is required if Filename is specified **type**\: int **range:** 0..4 Returns True if this instance represents config data else returns False Returns True if this instance represents config data else returns False
| 1.858802
| 2
|
signalProcessing/backscatter_expt_040716.py
|
macoskey/backscatter
| 0
|
6625760
|
# <NAME>, U of Michigan, I-GUTL, April 2017
# backscatter analysis of signals from 250 kHz 256-element array
# Objective: observe bubble cloud migration on high-speed camera and compare to
# ACE peak arrival (and edge detection) signal.
import numpy as np
import scipi.io as sio
import matplotlib.pyplot as plt
class array():
def __init__(self):
coords = sio.loadmat('256x2cm_Hemispherical_Array_CAD_Coordinates.mat')
X = coords['XCAD'][7:]
Y = coords['YCAD'][7:]
self.z = coords['ZCAD'][7:]
t1 = np.arctan2(Y,X)-0.75*pi
rr1 = (X**2+Y**2)**0.5
self.x = rr1*np.cos(t1)
self.y = rr1*np.sin(t1)
self.z = rr1*np.tan(t1)
class bSignals():
def FTsig(self,signal,interval)
insig = signal(interval)
ft = np.fftshift(np.fft(insig))
return ft
fig = plt.figure()
plt.plot(ft)
plt.show()
|
# <NAME>, U of Michigan, I-GUTL, April 2017
# backscatter analysis of signals from 250 kHz 256-element array
# Objective: observe bubble cloud migration on high-speed camera and compare to
# ACE peak arrival (and edge detection) signal.
import numpy as np
import scipi.io as sio
import matplotlib.pyplot as plt
class array():
def __init__(self):
coords = sio.loadmat('256x2cm_Hemispherical_Array_CAD_Coordinates.mat')
X = coords['XCAD'][7:]
Y = coords['YCAD'][7:]
self.z = coords['ZCAD'][7:]
t1 = np.arctan2(Y,X)-0.75*pi
rr1 = (X**2+Y**2)**0.5
self.x = rr1*np.cos(t1)
self.y = rr1*np.sin(t1)
self.z = rr1*np.tan(t1)
class bSignals():
def FTsig(self,signal,interval)
insig = signal(interval)
ft = np.fftshift(np.fft(insig))
return ft
fig = plt.figure()
plt.plot(ft)
plt.show()
|
en
| 0.837807
|
# <NAME>, U of Michigan, I-GUTL, April 2017 # backscatter analysis of signals from 250 kHz 256-element array # Objective: observe bubble cloud migration on high-speed camera and compare to # ACE peak arrival (and edge detection) signal.
| 2.350068
| 2
|
SNCKPE19/BUDDYNIM.py
|
Chhekur/codechef-solutions
| 1
|
6625761
|
<gh_stars>1-10
for _ in range(int(input())):
n,m = [int(x) for x in input().split()]
a = [int(x) for x in input().split()]
b = [int(x) for x in input().split()]
e,f = [],[]
c,d = 0,0
n1,n2 = 0,0
for i in a:
if(i > 0):
e.append(i)
c += 1
if(i == 1):n1 += 1
for i in b:
if(i > 0):
f.append(i)
d += 1
if(i == 1):n2 += 1
e.sort()
f.sort()
if(c == 0 and d == 0):print('Bob')
elif(len(e) != len(f)):print('Alice')
elif(len(e) == len(f) and e == f):print('Bob')
else:print('Alice')
|
for _ in range(int(input())):
n,m = [int(x) for x in input().split()]
a = [int(x) for x in input().split()]
b = [int(x) for x in input().split()]
e,f = [],[]
c,d = 0,0
n1,n2 = 0,0
for i in a:
if(i > 0):
e.append(i)
c += 1
if(i == 1):n1 += 1
for i in b:
if(i > 0):
f.append(i)
d += 1
if(i == 1):n2 += 1
e.sort()
f.sort()
if(c == 0 and d == 0):print('Bob')
elif(len(e) != len(f)):print('Alice')
elif(len(e) == len(f) and e == f):print('Bob')
else:print('Alice')
|
none
| 1
| 2.880741
| 3
|
|
setup.py
|
ZYunH/Convert-Into-Command
| 5
|
6625762
|
#!/usr/bin/env python
import os
import sys
from setuptools import setup, find_packages
# 'setup.py publish' shortcut.
if sys.argv[-1] == 'publish':
os.system('pip3 install twine')
os.system('pip3 install wheel')
os.system('python3 setup.py sdist bdist_wheel')
os.system('twine upload dist/*')
os.system('rm -rf build dist .egg zmail.egg-info')
sys.exit()
PROJECT_NAME = 'python-script-converter'
MODULE_NAME = 'psc'
setup(
name='python-script-converter',
version='1.2',
author='ZhangYunHao',
author_email='<EMAIL>',
description='This is a tiny tool used to convert a python script to a executable file(only for Mac and Linux).',
long_description='This is a tiny tool used to convert a python script to a executable file(only for Mac and Linux)',
keywords='python tool converter',
url='https://github.com/ZYunH/Python-script-converter',
license="MIT Licence",
platforms='Mac Linux',
packages=find_packages(),
include_package_data=True,
entry_points={
'console_scripts': [
'psc = psc.__main__:main'
]
}
)
|
#!/usr/bin/env python
import os
import sys
from setuptools import setup, find_packages
# 'setup.py publish' shortcut.
if sys.argv[-1] == 'publish':
os.system('pip3 install twine')
os.system('pip3 install wheel')
os.system('python3 setup.py sdist bdist_wheel')
os.system('twine upload dist/*')
os.system('rm -rf build dist .egg zmail.egg-info')
sys.exit()
PROJECT_NAME = 'python-script-converter'
MODULE_NAME = 'psc'
setup(
name='python-script-converter',
version='1.2',
author='ZhangYunHao',
author_email='<EMAIL>',
description='This is a tiny tool used to convert a python script to a executable file(only for Mac and Linux).',
long_description='This is a tiny tool used to convert a python script to a executable file(only for Mac and Linux)',
keywords='python tool converter',
url='https://github.com/ZYunH/Python-script-converter',
license="MIT Licence",
platforms='Mac Linux',
packages=find_packages(),
include_package_data=True,
entry_points={
'console_scripts': [
'psc = psc.__main__:main'
]
}
)
|
en
| 0.151061
|
#!/usr/bin/env python # 'setup.py publish' shortcut.
| 2.17891
| 2
|
model.py
|
lmm6895071/leo
| 0
|
6625763
|
# Copyright 2018 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Code defining LEO inner loop.
See "Meta-Learning with Latent Embedding Optimization" by Rusu et al.
(https://arxiv.org/pdf/1807.05960.pdf).
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from six.moves import range
from six.moves import zip
import sonnet as snt
import tensorflow as tf
import tensorflow_probability as tfp
import data as data_module
def get_orthogonality_regularizer(orthogonality_penalty_weight):
"""Returns the orthogonality regularizer."""
def orthogonality(weight):
"""Calculates the layer-wise penalty encouraging orthogonality."""
with tf.name_scope(None, "orthogonality", [weight]) as name:
w2 = tf.matmul(weight, weight, transpose_b=True)
wn = tf.norm(weight, ord=2, axis=1, keepdims=True) + 1e-32
correlation_matrix = w2 / tf.matmul(wn, wn, transpose_b=True)
matrix_size = correlation_matrix.get_shape().as_list()[0]
base_dtype = weight.dtype.base_dtype
identity = tf.eye(matrix_size, dtype=base_dtype)
weight_corr = tf.reduce_mean(
tf.squared_difference(correlation_matrix, identity))
return tf.multiply(
tf.cast(orthogonality_penalty_weight, base_dtype),
weight_corr,
name=name)
return orthogonality
class LEO(snt.AbstractModule):
"""Sonnet module implementing the inner loop of LEO."""
def __init__(self, config=None, use_64bits_dtype=True, name="leo"):
super(LEO, self).__init__(name=name)
self._float_dtype = tf.float64 if use_64bits_dtype else tf.float32
self._int_dtype = tf.int64 if use_64bits_dtype else tf.int32
self._inner_unroll_length = config["inner_unroll_length"]
self._finetuning_unroll_length = config["finetuning_unroll_length"]
self._inner_lr_init = config["inner_lr_init"]
self._finetuning_lr_init = config["finetuning_lr_init"]
self._num_latents = config["num_latents"]
self._dropout_rate = config["dropout_rate"]
self._kl_weight = config["kl_weight"] # beta
self._encoder_penalty_weight = config["encoder_penalty_weight"] # gamma
self._l2_penalty_weight = config["l2_penalty_weight"] # lambda_1
# lambda_2
self._orthogonality_penalty_weight = config["orthogonality_penalty_weight"]
assert self._inner_unroll_length > 0, ("Positive unroll length is necessary"
" to create the graph")
def _build(self, data, is_meta_training=True):
"""Connects the LEO module to the graph, creating the variables.
Args:
data: A data_module.ProblemInstance constaining Tensors with the
following shapes:
- tr_input: (N, K, dim)
- tr_output: (N, K, 1)
- tr_info: (N, K)
- val_input: (N, K_valid, dim)
- val_output: (N, K_valid, 1)
- val_info: (N, K_valid)
where N is the number of classes (as in N-way) and K and the and
K_valid are numbers of training and validation examples within a
problem instance correspondingly (as in K-shot), and dim is the
dimensionality of the embedding.
is_meta_training: A boolean describing whether we run in the training
mode.
Returns:
Tensor with the inner validation loss of LEO (include both adaptation in
the latent space and finetuning).
"""
if isinstance(data, list):
data = data_module.ProblemInstance(*data)
self.is_meta_training = is_meta_training
self.save_problem_instance_stats(data.tr_input)
latents, kl = self.forward_encoder(data)
tr_loss, adapted_classifier_weights, encoder_penalty = self.leo_inner_loop(
data, latents)
val_loss, val_accuracy = self.finetuning_inner_loop(
data, tr_loss, adapted_classifier_weights)
val_loss += self._kl_weight * kl
val_loss += self._encoder_penalty_weight * encoder_penalty
# The l2 regularization is is already added to the graph when constructing
# the snt.Linear modules. We pass the orthogonality regularizer separately,
# because it is not used in self.grads_and_vars.
regularization_penalty = (
self._l2_regularization + self._decoder_orthogonality_reg)
batch_val_loss = tf.reduce_mean(val_loss)
batch_val_accuracy = tf.reduce_mean(val_accuracy)
return batch_val_loss + regularization_penalty, batch_val_accuracy
@snt.reuse_variables
def leo_inner_loop(self, data, latents):
with tf.variable_scope("leo_inner"):
inner_lr = tf.get_variable(
"lr", [1, 1, self._num_latents],
dtype=self._float_dtype,
initializer=tf.constant_initializer(self._inner_lr_init))
starting_latents = latents
loss, _ = self.forward_decoder(data, latents)
for _ in range(self._inner_unroll_length):
loss_grad = tf.gradients(loss, latents) # dLtrain/dz
latents -= inner_lr * loss_grad[0]
loss, classifier_weights = self.forward_decoder(data, latents)
if self.is_meta_training:
encoder_penalty = tf.losses.mean_squared_error(
labels=tf.stop_gradient(latents), predictions=starting_latents)
encoder_penalty = tf.cast(encoder_penalty, self._float_dtype)
else:
encoder_penalty = tf.constant(0., self._float_dtype)
return loss, classifier_weights, encoder_penalty
@snt.reuse_variables
def finetuning_inner_loop(self, data, leo_loss, classifier_weights):
tr_loss = leo_loss
with tf.variable_scope("finetuning"):
finetuning_lr = tf.get_variable(
"lr", [1, 1, self.embedding_dim],
dtype=self._float_dtype,
initializer=tf.constant_initializer(self._finetuning_lr_init))
for _ in range(self._finetuning_unroll_length):
loss_grad = tf.gradients(tr_loss, classifier_weights)
classifier_weights -= finetuning_lr * loss_grad[0]
tr_loss, _ = self.calculate_inner_loss(data.tr_input, data.tr_output,
classifier_weights)
val_loss, val_accuracy = self.calculate_inner_loss(
data.val_input, data.val_output, classifier_weights)
return val_loss, val_accuracy
@snt.reuse_variables
def forward_encoder(self, data):
encoder_outputs = self.encoder(data.tr_input)
relation_network_outputs = self.relation_network(encoder_outputs)
latent_dist_params = self.average_codes_per_class(relation_network_outputs)
latents, kl = self.possibly_sample(latent_dist_params)
return latents, kl
@snt.reuse_variables
def forward_decoder(self, data, latents):
weights_dist_params = self.decoder(latents)
# Default to glorot_initialization and not stddev=1.
fan_in = self.embedding_dim.value
fan_out = self.num_classes.value
stddev_offset = np.sqrt(2. / (fan_out + fan_in))
classifier_weights, _ = self.possibly_sample(weights_dist_params,
stddev_offset=stddev_offset)
tr_loss, _ = self.calculate_inner_loss(data.tr_input, data.tr_output,
classifier_weights)
return tr_loss, classifier_weights
@snt.reuse_variables
def encoder(self, inputs):
with tf.variable_scope("encoder"):
after_dropout = tf.nn.dropout(inputs, keep_prob=self.dropout_rate)
regularizer = tf.contrib.layers.l2_regularizer(self._l2_penalty_weight)
initializer = tf.initializers.glorot_uniform(dtype=self._float_dtype)
encoder_module = snt.Linear(
self._num_latents,
use_bias=False,
regularizers={"w": regularizer},
initializers={"w": initializer},
)
outputs = snt.BatchApply(encoder_module)(after_dropout)
return outputs
@snt.reuse_variables
def relation_network(self, inputs):
with tf.variable_scope("relation_network"):
regularizer = tf.contrib.layers.l2_regularizer(self._l2_penalty_weight)
initializer = tf.initializers.glorot_uniform(dtype=self._float_dtype)
relation_network_module = snt.nets.MLP(
[2 * self._num_latents] * 3,
use_bias=False,
regularizers={"w": regularizer},
initializers={"w": initializer},
)
total_num_examples = self.num_examples_per_class*self.num_classes
inputs = tf.reshape(inputs, [total_num_examples, self._num_latents])
left = tf.tile(tf.expand_dims(inputs, 1), [1, total_num_examples, 1])
right = tf.tile(tf.expand_dims(inputs, 0), [total_num_examples, 1, 1])
concat_codes = tf.concat([left, right], axis=-1)
outputs = snt.BatchApply(relation_network_module)(concat_codes)
outputs = tf.reduce_mean(outputs, axis=1)
# 2 * latents, because we are returning means and variances of a Gaussian
outputs = tf.reshape(outputs, [self.num_classes,
self.num_examples_per_class,
2 * self._num_latents])
return outputs
@snt.reuse_variables
def decoder(self, inputs):
with tf.variable_scope("decoder"):
l2_regularizer = tf.contrib.layers.l2_regularizer(self._l2_penalty_weight)
orthogonality_reg = get_orthogonality_regularizer(
self._orthogonality_penalty_weight)
initializer = tf.initializers.glorot_uniform(dtype=self._float_dtype)
# 2 * embedding_dim, because we are returning means and variances
decoder_module = snt.Linear(
2 * self.embedding_dim,
use_bias=False,
regularizers={"w": l2_regularizer},
initializers={"w": initializer},
)
outputs = snt.BatchApply(decoder_module)(inputs)
self._orthogonality_reg = orthogonality_reg(decoder_module.w)
return outputs
def average_codes_per_class(self, codes):
codes = tf.reduce_mean(codes, axis=1, keep_dims=True) # K dimension
# Keep the shape (N, K, *)
codes = tf.tile(codes, [1, self.num_examples_per_class, 1])
return codes
def possibly_sample(self, distribution_params, stddev_offset=0.):
means, unnormalized_stddev = tf.split(distribution_params, 2, axis=-1)
stddev = tf.exp(unnormalized_stddev)
stddev -= (1. - stddev_offset)
stddev = tf.maximum(stddev, 1e-10)
distribution = tfp.distributions.Normal(loc=means, scale=stddev)
if not self.is_meta_training:
return means, tf.constant(0., dtype=self._float_dtype)
samples = distribution.sample()
kl_divergence = self.kl_divergence(samples, distribution)
return samples, kl_divergence
def kl_divergence(self, samples, normal_distribution):
random_prior = tfp.distributions.Normal(
loc=tf.zeros_like(samples), scale=tf.ones_like(samples))
kl = tf.reduce_mean(
normal_distribution.log_prob(samples) - random_prior.log_prob(samples))
return kl
def predict(self, inputs, weights):
after_dropout = tf.nn.dropout(inputs, keep_prob=self.dropout_rate)
# This is 3-dimensional equivalent of a matrix product, where we sum over
# the last (embedding_dim) dimension. We get [N, K, N, K] tensor as output.
per_image_predictions = tf.einsum("ijk,lmk->ijlm", after_dropout, weights)
# Predictions have shape [N, K, N]: for each image ([N, K] of them), what
# is the probability of a given class (N)?
predictions = tf.reduce_mean(per_image_predictions, axis=-1)
return predictions
def calculate_inner_loss(self, inputs, true_outputs, classifier_weights):
model_outputs = self.predict(inputs, classifier_weights)
model_predictions = tf.argmax(
model_outputs, -1, output_type=self._int_dtype)
accuracy = tf.contrib.metrics.accuracy(model_predictions,
tf.squeeze(true_outputs, axis=-1))
return self.loss_fn(model_outputs, true_outputs), accuracy
def save_problem_instance_stats(self, instance):
num_classes, num_examples_per_class, embedding_dim = instance.get_shape()
if hasattr(self, "num_classes"):
assert self.num_classes == num_classes, (
"Given different number of classes (N in N-way) in consecutive runs.")
if hasattr(self, "num_examples_per_class"):
assert self.num_examples_per_class == num_examples_per_class, (
"Given different number of examples (K in K-shot) in consecutive"
"runs.")
if hasattr(self, "embedding_dim"):
assert self.embedding_dim == embedding_dim, (
"Given different embedding dimension in consecutive runs.")
self.num_classes = num_classes
self.num_examples_per_class = num_examples_per_class
self.embedding_dim = embedding_dim
@property
def dropout_rate(self):
return self._dropout_rate if self.is_meta_training else 0.01
def loss_fn(self, model_outputs, original_classes):
original_classes = tf.squeeze(original_classes, axis=-1)
# Tensorflow doesn't handle second order gradients of a sparse_softmax yet.
one_hot_outputs = tf.one_hot(original_classes, depth=self.num_classes)
return tf.nn.softmax_cross_entropy_with_logits_v2(
labels=one_hot_outputs, logits=model_outputs)
def grads_and_vars(self, metatrain_loss):
"""Computes gradients of metatrain_loss, avoiding NaN.
Uses a fixed penalty of 1e-4 to enforce only the l2 regularization (and not
minimize the loss) when metatrain_loss or any of its gradients with respect
to trainable_vars are NaN. In practice, this approach pulls the variables
back into a feasible region of the space when the loss or its gradients are
not defined.
Args:
metatrain_loss: A tensor with the LEO meta-training loss.
Returns:
A tuple with:
metatrain_gradients: A list of gradient tensors.
metatrain_variables: A list of variables for this LEO model.
"""
metatrain_variables = self.trainable_variables
metatrain_gradients = tf.gradients(metatrain_loss, metatrain_variables)
nan_loss_or_grad = tf.logical_or(
tf.is_nan(metatrain_loss),
tf.reduce_any([tf.reduce_any(tf.is_nan(g))
for g in metatrain_gradients]))
regularization_penalty = (
1e-4 / self._l2_penalty_weight * self._l2_regularization)
zero_or_regularization_gradients = [
g if g is not None else tf.zeros_like(v)
for v, g in zip(tf.gradients(regularization_penalty,
metatrain_variables), metatrain_variables)]
metatrain_gradients = tf.cond(nan_loss_or_grad,
lambda: zero_or_regularization_gradients,
lambda: metatrain_gradients, strict=True)
return metatrain_gradients, metatrain_variables
@property
def _l2_regularization(self):
return tf.cast(
tf.reduce_sum(tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)),
dtype=self._float_dtype)
@property
def _decoder_orthogonality_reg(self):
return self._orthogonality_reg
|
# Copyright 2018 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Code defining LEO inner loop.
See "Meta-Learning with Latent Embedding Optimization" by Rusu et al.
(https://arxiv.org/pdf/1807.05960.pdf).
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from six.moves import range
from six.moves import zip
import sonnet as snt
import tensorflow as tf
import tensorflow_probability as tfp
import data as data_module
def get_orthogonality_regularizer(orthogonality_penalty_weight):
"""Returns the orthogonality regularizer."""
def orthogonality(weight):
"""Calculates the layer-wise penalty encouraging orthogonality."""
with tf.name_scope(None, "orthogonality", [weight]) as name:
w2 = tf.matmul(weight, weight, transpose_b=True)
wn = tf.norm(weight, ord=2, axis=1, keepdims=True) + 1e-32
correlation_matrix = w2 / tf.matmul(wn, wn, transpose_b=True)
matrix_size = correlation_matrix.get_shape().as_list()[0]
base_dtype = weight.dtype.base_dtype
identity = tf.eye(matrix_size, dtype=base_dtype)
weight_corr = tf.reduce_mean(
tf.squared_difference(correlation_matrix, identity))
return tf.multiply(
tf.cast(orthogonality_penalty_weight, base_dtype),
weight_corr,
name=name)
return orthogonality
class LEO(snt.AbstractModule):
"""Sonnet module implementing the inner loop of LEO."""
def __init__(self, config=None, use_64bits_dtype=True, name="leo"):
super(LEO, self).__init__(name=name)
self._float_dtype = tf.float64 if use_64bits_dtype else tf.float32
self._int_dtype = tf.int64 if use_64bits_dtype else tf.int32
self._inner_unroll_length = config["inner_unroll_length"]
self._finetuning_unroll_length = config["finetuning_unroll_length"]
self._inner_lr_init = config["inner_lr_init"]
self._finetuning_lr_init = config["finetuning_lr_init"]
self._num_latents = config["num_latents"]
self._dropout_rate = config["dropout_rate"]
self._kl_weight = config["kl_weight"] # beta
self._encoder_penalty_weight = config["encoder_penalty_weight"] # gamma
self._l2_penalty_weight = config["l2_penalty_weight"] # lambda_1
# lambda_2
self._orthogonality_penalty_weight = config["orthogonality_penalty_weight"]
assert self._inner_unroll_length > 0, ("Positive unroll length is necessary"
" to create the graph")
def _build(self, data, is_meta_training=True):
"""Connects the LEO module to the graph, creating the variables.
Args:
data: A data_module.ProblemInstance constaining Tensors with the
following shapes:
- tr_input: (N, K, dim)
- tr_output: (N, K, 1)
- tr_info: (N, K)
- val_input: (N, K_valid, dim)
- val_output: (N, K_valid, 1)
- val_info: (N, K_valid)
where N is the number of classes (as in N-way) and K and the and
K_valid are numbers of training and validation examples within a
problem instance correspondingly (as in K-shot), and dim is the
dimensionality of the embedding.
is_meta_training: A boolean describing whether we run in the training
mode.
Returns:
Tensor with the inner validation loss of LEO (include both adaptation in
the latent space and finetuning).
"""
if isinstance(data, list):
data = data_module.ProblemInstance(*data)
self.is_meta_training = is_meta_training
self.save_problem_instance_stats(data.tr_input)
latents, kl = self.forward_encoder(data)
tr_loss, adapted_classifier_weights, encoder_penalty = self.leo_inner_loop(
data, latents)
val_loss, val_accuracy = self.finetuning_inner_loop(
data, tr_loss, adapted_classifier_weights)
val_loss += self._kl_weight * kl
val_loss += self._encoder_penalty_weight * encoder_penalty
# The l2 regularization is is already added to the graph when constructing
# the snt.Linear modules. We pass the orthogonality regularizer separately,
# because it is not used in self.grads_and_vars.
regularization_penalty = (
self._l2_regularization + self._decoder_orthogonality_reg)
batch_val_loss = tf.reduce_mean(val_loss)
batch_val_accuracy = tf.reduce_mean(val_accuracy)
return batch_val_loss + regularization_penalty, batch_val_accuracy
@snt.reuse_variables
def leo_inner_loop(self, data, latents):
with tf.variable_scope("leo_inner"):
inner_lr = tf.get_variable(
"lr", [1, 1, self._num_latents],
dtype=self._float_dtype,
initializer=tf.constant_initializer(self._inner_lr_init))
starting_latents = latents
loss, _ = self.forward_decoder(data, latents)
for _ in range(self._inner_unroll_length):
loss_grad = tf.gradients(loss, latents) # dLtrain/dz
latents -= inner_lr * loss_grad[0]
loss, classifier_weights = self.forward_decoder(data, latents)
if self.is_meta_training:
encoder_penalty = tf.losses.mean_squared_error(
labels=tf.stop_gradient(latents), predictions=starting_latents)
encoder_penalty = tf.cast(encoder_penalty, self._float_dtype)
else:
encoder_penalty = tf.constant(0., self._float_dtype)
return loss, classifier_weights, encoder_penalty
@snt.reuse_variables
def finetuning_inner_loop(self, data, leo_loss, classifier_weights):
tr_loss = leo_loss
with tf.variable_scope("finetuning"):
finetuning_lr = tf.get_variable(
"lr", [1, 1, self.embedding_dim],
dtype=self._float_dtype,
initializer=tf.constant_initializer(self._finetuning_lr_init))
for _ in range(self._finetuning_unroll_length):
loss_grad = tf.gradients(tr_loss, classifier_weights)
classifier_weights -= finetuning_lr * loss_grad[0]
tr_loss, _ = self.calculate_inner_loss(data.tr_input, data.tr_output,
classifier_weights)
val_loss, val_accuracy = self.calculate_inner_loss(
data.val_input, data.val_output, classifier_weights)
return val_loss, val_accuracy
@snt.reuse_variables
def forward_encoder(self, data):
encoder_outputs = self.encoder(data.tr_input)
relation_network_outputs = self.relation_network(encoder_outputs)
latent_dist_params = self.average_codes_per_class(relation_network_outputs)
latents, kl = self.possibly_sample(latent_dist_params)
return latents, kl
@snt.reuse_variables
def forward_decoder(self, data, latents):
weights_dist_params = self.decoder(latents)
# Default to glorot_initialization and not stddev=1.
fan_in = self.embedding_dim.value
fan_out = self.num_classes.value
stddev_offset = np.sqrt(2. / (fan_out + fan_in))
classifier_weights, _ = self.possibly_sample(weights_dist_params,
stddev_offset=stddev_offset)
tr_loss, _ = self.calculate_inner_loss(data.tr_input, data.tr_output,
classifier_weights)
return tr_loss, classifier_weights
@snt.reuse_variables
def encoder(self, inputs):
with tf.variable_scope("encoder"):
after_dropout = tf.nn.dropout(inputs, keep_prob=self.dropout_rate)
regularizer = tf.contrib.layers.l2_regularizer(self._l2_penalty_weight)
initializer = tf.initializers.glorot_uniform(dtype=self._float_dtype)
encoder_module = snt.Linear(
self._num_latents,
use_bias=False,
regularizers={"w": regularizer},
initializers={"w": initializer},
)
outputs = snt.BatchApply(encoder_module)(after_dropout)
return outputs
@snt.reuse_variables
def relation_network(self, inputs):
with tf.variable_scope("relation_network"):
regularizer = tf.contrib.layers.l2_regularizer(self._l2_penalty_weight)
initializer = tf.initializers.glorot_uniform(dtype=self._float_dtype)
relation_network_module = snt.nets.MLP(
[2 * self._num_latents] * 3,
use_bias=False,
regularizers={"w": regularizer},
initializers={"w": initializer},
)
total_num_examples = self.num_examples_per_class*self.num_classes
inputs = tf.reshape(inputs, [total_num_examples, self._num_latents])
left = tf.tile(tf.expand_dims(inputs, 1), [1, total_num_examples, 1])
right = tf.tile(tf.expand_dims(inputs, 0), [total_num_examples, 1, 1])
concat_codes = tf.concat([left, right], axis=-1)
outputs = snt.BatchApply(relation_network_module)(concat_codes)
outputs = tf.reduce_mean(outputs, axis=1)
# 2 * latents, because we are returning means and variances of a Gaussian
outputs = tf.reshape(outputs, [self.num_classes,
self.num_examples_per_class,
2 * self._num_latents])
return outputs
@snt.reuse_variables
def decoder(self, inputs):
with tf.variable_scope("decoder"):
l2_regularizer = tf.contrib.layers.l2_regularizer(self._l2_penalty_weight)
orthogonality_reg = get_orthogonality_regularizer(
self._orthogonality_penalty_weight)
initializer = tf.initializers.glorot_uniform(dtype=self._float_dtype)
# 2 * embedding_dim, because we are returning means and variances
decoder_module = snt.Linear(
2 * self.embedding_dim,
use_bias=False,
regularizers={"w": l2_regularizer},
initializers={"w": initializer},
)
outputs = snt.BatchApply(decoder_module)(inputs)
self._orthogonality_reg = orthogonality_reg(decoder_module.w)
return outputs
def average_codes_per_class(self, codes):
codes = tf.reduce_mean(codes, axis=1, keep_dims=True) # K dimension
# Keep the shape (N, K, *)
codes = tf.tile(codes, [1, self.num_examples_per_class, 1])
return codes
def possibly_sample(self, distribution_params, stddev_offset=0.):
means, unnormalized_stddev = tf.split(distribution_params, 2, axis=-1)
stddev = tf.exp(unnormalized_stddev)
stddev -= (1. - stddev_offset)
stddev = tf.maximum(stddev, 1e-10)
distribution = tfp.distributions.Normal(loc=means, scale=stddev)
if not self.is_meta_training:
return means, tf.constant(0., dtype=self._float_dtype)
samples = distribution.sample()
kl_divergence = self.kl_divergence(samples, distribution)
return samples, kl_divergence
def kl_divergence(self, samples, normal_distribution):
random_prior = tfp.distributions.Normal(
loc=tf.zeros_like(samples), scale=tf.ones_like(samples))
kl = tf.reduce_mean(
normal_distribution.log_prob(samples) - random_prior.log_prob(samples))
return kl
def predict(self, inputs, weights):
after_dropout = tf.nn.dropout(inputs, keep_prob=self.dropout_rate)
# This is 3-dimensional equivalent of a matrix product, where we sum over
# the last (embedding_dim) dimension. We get [N, K, N, K] tensor as output.
per_image_predictions = tf.einsum("ijk,lmk->ijlm", after_dropout, weights)
# Predictions have shape [N, K, N]: for each image ([N, K] of them), what
# is the probability of a given class (N)?
predictions = tf.reduce_mean(per_image_predictions, axis=-1)
return predictions
def calculate_inner_loss(self, inputs, true_outputs, classifier_weights):
model_outputs = self.predict(inputs, classifier_weights)
model_predictions = tf.argmax(
model_outputs, -1, output_type=self._int_dtype)
accuracy = tf.contrib.metrics.accuracy(model_predictions,
tf.squeeze(true_outputs, axis=-1))
return self.loss_fn(model_outputs, true_outputs), accuracy
def save_problem_instance_stats(self, instance):
num_classes, num_examples_per_class, embedding_dim = instance.get_shape()
if hasattr(self, "num_classes"):
assert self.num_classes == num_classes, (
"Given different number of classes (N in N-way) in consecutive runs.")
if hasattr(self, "num_examples_per_class"):
assert self.num_examples_per_class == num_examples_per_class, (
"Given different number of examples (K in K-shot) in consecutive"
"runs.")
if hasattr(self, "embedding_dim"):
assert self.embedding_dim == embedding_dim, (
"Given different embedding dimension in consecutive runs.")
self.num_classes = num_classes
self.num_examples_per_class = num_examples_per_class
self.embedding_dim = embedding_dim
@property
def dropout_rate(self):
return self._dropout_rate if self.is_meta_training else 0.01
def loss_fn(self, model_outputs, original_classes):
original_classes = tf.squeeze(original_classes, axis=-1)
# Tensorflow doesn't handle second order gradients of a sparse_softmax yet.
one_hot_outputs = tf.one_hot(original_classes, depth=self.num_classes)
return tf.nn.softmax_cross_entropy_with_logits_v2(
labels=one_hot_outputs, logits=model_outputs)
def grads_and_vars(self, metatrain_loss):
"""Computes gradients of metatrain_loss, avoiding NaN.
Uses a fixed penalty of 1e-4 to enforce only the l2 regularization (and not
minimize the loss) when metatrain_loss or any of its gradients with respect
to trainable_vars are NaN. In practice, this approach pulls the variables
back into a feasible region of the space when the loss or its gradients are
not defined.
Args:
metatrain_loss: A tensor with the LEO meta-training loss.
Returns:
A tuple with:
metatrain_gradients: A list of gradient tensors.
metatrain_variables: A list of variables for this LEO model.
"""
metatrain_variables = self.trainable_variables
metatrain_gradients = tf.gradients(metatrain_loss, metatrain_variables)
nan_loss_or_grad = tf.logical_or(
tf.is_nan(metatrain_loss),
tf.reduce_any([tf.reduce_any(tf.is_nan(g))
for g in metatrain_gradients]))
regularization_penalty = (
1e-4 / self._l2_penalty_weight * self._l2_regularization)
zero_or_regularization_gradients = [
g if g is not None else tf.zeros_like(v)
for v, g in zip(tf.gradients(regularization_penalty,
metatrain_variables), metatrain_variables)]
metatrain_gradients = tf.cond(nan_loss_or_grad,
lambda: zero_or_regularization_gradients,
lambda: metatrain_gradients, strict=True)
return metatrain_gradients, metatrain_variables
@property
def _l2_regularization(self):
return tf.cast(
tf.reduce_sum(tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)),
dtype=self._float_dtype)
@property
def _decoder_orthogonality_reg(self):
return self._orthogonality_reg
|
en
| 0.818106
|
# Copyright 2018 DeepMind Technologies Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ Code defining LEO inner loop. See "Meta-Learning with Latent Embedding Optimization" by Rusu et al. (https://arxiv.org/pdf/1807.05960.pdf). Returns the orthogonality regularizer. Calculates the layer-wise penalty encouraging orthogonality. Sonnet module implementing the inner loop of LEO. # beta # gamma # lambda_1 # lambda_2 Connects the LEO module to the graph, creating the variables. Args: data: A data_module.ProblemInstance constaining Tensors with the following shapes: - tr_input: (N, K, dim) - tr_output: (N, K, 1) - tr_info: (N, K) - val_input: (N, K_valid, dim) - val_output: (N, K_valid, 1) - val_info: (N, K_valid) where N is the number of classes (as in N-way) and K and the and K_valid are numbers of training and validation examples within a problem instance correspondingly (as in K-shot), and dim is the dimensionality of the embedding. is_meta_training: A boolean describing whether we run in the training mode. Returns: Tensor with the inner validation loss of LEO (include both adaptation in the latent space and finetuning). # The l2 regularization is is already added to the graph when constructing # the snt.Linear modules. We pass the orthogonality regularizer separately, # because it is not used in self.grads_and_vars. # dLtrain/dz # Default to glorot_initialization and not stddev=1. # 2 * latents, because we are returning means and variances of a Gaussian # 2 * embedding_dim, because we are returning means and variances # K dimension # Keep the shape (N, K, *) # This is 3-dimensional equivalent of a matrix product, where we sum over # the last (embedding_dim) dimension. We get [N, K, N, K] tensor as output. # Predictions have shape [N, K, N]: for each image ([N, K] of them), what # is the probability of a given class (N)? # Tensorflow doesn't handle second order gradients of a sparse_softmax yet. Computes gradients of metatrain_loss, avoiding NaN. Uses a fixed penalty of 1e-4 to enforce only the l2 regularization (and not minimize the loss) when metatrain_loss or any of its gradients with respect to trainable_vars are NaN. In practice, this approach pulls the variables back into a feasible region of the space when the loss or its gradients are not defined. Args: metatrain_loss: A tensor with the LEO meta-training loss. Returns: A tuple with: metatrain_gradients: A list of gradient tensors. metatrain_variables: A list of variables for this LEO model.
| 2.056504
| 2
|
tests/integrationv2/test_well_known_endpoints.py
|
glaubitz/s2n
| 0
|
6625764
|
<reponame>glaubitz/s2n
import copy
import os
import pytest
from constants import TRUST_STORE_BUNDLE
from configuration import available_ports, PROTOCOLS
from common import ProviderOptions, Protocols, Ciphers
from fixtures import managed_process
from global_flags import get_flag, S2N_NO_PQ, S2N_FIPS_MODE
from providers import Provider, S2N
from utils import invalid_test_parameters, get_parameter_name
ENDPOINTS = [
{"endpoint": "amazon.com"},
{"endpoint": "facebook.com"},
{"endpoint": "google.com"},
{"endpoint": "netflix.com"},
{"endpoint": "s3.amazonaws.com"},
{"endpoint": "twitter.com"},
{"endpoint": "wikipedia.org"},
{"endpoint": "yahoo.com"},
]
if get_flag(S2N_NO_PQ, False) is False:
# If PQ was compiled into S2N, test the PQ preferences against KMS
pq_endpoints = [
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.KMS_PQ_TLS_1_0_2019_06,
"expected_cipher": "ECDHE-BIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "BIKE1r1-Level1",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.PQ_SIKE_TEST_TLS_1_0_2019_11,
"expected_cipher": "ECDHE-SIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "SIKEp503r1-KEM",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.KMS_PQ_TLS_1_0_2020_07,
"expected_cipher": "ECDHE-KYBER-RSA-AES256-GCM-SHA384",
"expected_kem": "kyber512r2",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.KMS_PQ_TLS_1_0_2020_02,
"expected_cipher": "ECDHE-BIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "BIKE1r2-Level1",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.PQ_SIKE_TEST_TLS_1_0_2020_02,
"expected_cipher": "ECDHE-SIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "SIKEp434r2-KEM",
},
]
ENDPOINTS.extend(pq_endpoints)
@pytest.mark.uncollect_if(func=invalid_test_parameters)
@pytest.mark.parametrize("protocol", PROTOCOLS, ids=get_parameter_name)
@pytest.mark.parametrize("endpoint", ENDPOINTS, ids=lambda x: "{}-{}".format(x['endpoint'], x.get('cipher_preference_version', 'Default')))
def test_well_known_endpoints(managed_process, protocol, endpoint):
port = "443"
client_options = ProviderOptions(
mode=Provider.ClientMode,
host=endpoint['endpoint'],
port=port,
insecure=False,
client_trust_store=TRUST_STORE_BUNDLE,
protocol=protocol)
if get_flag(S2N_FIPS_MODE) is True:
client_options.client_trust_store = "../integration/trust-store/ca-bundle.trust.crt"
else:
client_options.client_trust_store = "../integration/trust-store/ca-bundle.crt"
if 'cipher_preference_version' in endpoint:
client_options.cipher = endpoint['cipher_preference_version']
client = managed_process(S2N, client_options, timeout=5)
for results in client.get_results():
assert results.exception is None
assert results.exit_code == 0
if 'expected_cipher' in endpoint:
assert bytes(endpoint['expected_cipher'].encode('utf-8')) in results.stdout
if 'expected_kem' in endpoint:
assert bytes(endpoint['expected_kem'].encode('utf-8')) in results.stdout
|
import copy
import os
import pytest
from constants import TRUST_STORE_BUNDLE
from configuration import available_ports, PROTOCOLS
from common import ProviderOptions, Protocols, Ciphers
from fixtures import managed_process
from global_flags import get_flag, S2N_NO_PQ, S2N_FIPS_MODE
from providers import Provider, S2N
from utils import invalid_test_parameters, get_parameter_name
ENDPOINTS = [
{"endpoint": "amazon.com"},
{"endpoint": "facebook.com"},
{"endpoint": "google.com"},
{"endpoint": "netflix.com"},
{"endpoint": "s3.amazonaws.com"},
{"endpoint": "twitter.com"},
{"endpoint": "wikipedia.org"},
{"endpoint": "yahoo.com"},
]
if get_flag(S2N_NO_PQ, False) is False:
# If PQ was compiled into S2N, test the PQ preferences against KMS
pq_endpoints = [
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.KMS_PQ_TLS_1_0_2019_06,
"expected_cipher": "ECDHE-BIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "BIKE1r1-Level1",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.PQ_SIKE_TEST_TLS_1_0_2019_11,
"expected_cipher": "ECDHE-SIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "SIKEp503r1-KEM",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.KMS_PQ_TLS_1_0_2020_07,
"expected_cipher": "ECDHE-KYBER-RSA-AES256-GCM-SHA384",
"expected_kem": "kyber512r2",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.KMS_PQ_TLS_1_0_2020_02,
"expected_cipher": "ECDHE-BIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "BIKE1r2-Level1",
},
{
"endpoint": "kms.us-east-1.amazonaws.com",
"cipher_preference_version": Ciphers.PQ_SIKE_TEST_TLS_1_0_2020_02,
"expected_cipher": "ECDHE-SIKE-RSA-AES256-GCM-SHA384",
"expected_kem": "SIKEp434r2-KEM",
},
]
ENDPOINTS.extend(pq_endpoints)
@pytest.mark.uncollect_if(func=invalid_test_parameters)
@pytest.mark.parametrize("protocol", PROTOCOLS, ids=get_parameter_name)
@pytest.mark.parametrize("endpoint", ENDPOINTS, ids=lambda x: "{}-{}".format(x['endpoint'], x.get('cipher_preference_version', 'Default')))
def test_well_known_endpoints(managed_process, protocol, endpoint):
port = "443"
client_options = ProviderOptions(
mode=Provider.ClientMode,
host=endpoint['endpoint'],
port=port,
insecure=False,
client_trust_store=TRUST_STORE_BUNDLE,
protocol=protocol)
if get_flag(S2N_FIPS_MODE) is True:
client_options.client_trust_store = "../integration/trust-store/ca-bundle.trust.crt"
else:
client_options.client_trust_store = "../integration/trust-store/ca-bundle.crt"
if 'cipher_preference_version' in endpoint:
client_options.cipher = endpoint['cipher_preference_version']
client = managed_process(S2N, client_options, timeout=5)
for results in client.get_results():
assert results.exception is None
assert results.exit_code == 0
if 'expected_cipher' in endpoint:
assert bytes(endpoint['expected_cipher'].encode('utf-8')) in results.stdout
if 'expected_kem' in endpoint:
assert bytes(endpoint['expected_kem'].encode('utf-8')) in results.stdout
|
en
| 0.987002
|
# If PQ was compiled into S2N, test the PQ preferences against KMS
| 1.840452
| 2
|
examples/gurobipy/metrorail/metrorail.py
|
adampkehoe/ticdat
| 0
|
6625765
|
<gh_stars>0
#
# Models Tallys Yunes Metrorail tickets problem.
# https://orbythebeach.wordpress.com/2018/03/01/buying-metrorail-tickets-in-miami/
# https://www.linkedin.com/pulse/miami-metrorail-meets-python-peter-cacioppi/
#
# Implement core functionality needed to achieve modularity.
# 1. Define the input data schema
# 2. Define the output data schema
# 3. Create a solve function that accepts a data set consistent with the input
# schema and (if possible) returns a data set consistent with the output schema.
#
# Provides command line interface via ticdat.standard_main
# For example, typing
# python metrorail.py -i metrorail_sample_data.json -o metrorail_solution_data.json
# will read from a model stored in the file metrorail_sample_data.json and write the
# solution to metrorail_solution_data.json.
try: # if you don't have gurobipy installed, the code will still load and then fail on solve
import gurobipy as gu
except:
gu = None
from ticdat import TicDatFactory, standard_main
from itertools import product
# ------------------------ define the input schema --------------------------------
input_schema = TicDatFactory (
parameters=[["Parameter"], ["Value"]],
load_amounts=[["Amount"],[]],
number_of_one_way_trips=[["Number"],[]],
amount_leftover=[["Amount"], []])
input_schema.set_data_type("load_amounts", "Amount", min=0, max=float("inf"),
inclusive_min=False, inclusive_max=False)
input_schema.set_data_type("number_of_one_way_trips", "Number", min=0, max=float("inf"),
inclusive_min=False, inclusive_max=False, must_be_int=True)
input_schema.set_data_type("amount_leftover", "Amount", min=0, max=float("inf"),
inclusive_min=True, inclusive_max=False)
input_schema.add_parameter("One Way Price", default_value=2.25, min=0, max=float("inf"), inclusive_min=True,
inclusive_max=False)
input_schema.add_parameter("Amount Leftover Constraint", default_value="Upper Bound", number_allowed=False,
strings_allowed=["Equality", "Upper Bound", "Upper Bound With Leftover Multiple Rule"])
# ---------------------------------------------------------------------------------
# ------------------------ define the output schema -------------------------------
solution_schema = TicDatFactory(
load_amount_details=[["Number One Way Trips", "Amount Leftover", "Load Amount"],
["Number Of Visits"]],
load_amount_summary=[["Number One Way Trips", "Amount Leftover"],["Number Of Visits"]])
# ---------------------------------------------------------------------------------
# ------------------------ create a solve function --------------------------------
def solve(dat):
"""
core solving routine
:param dat: a good ticdat for the input_schema
:return: a good ticdat for the solution_schema, or None
"""
assert input_schema.good_tic_dat_object(dat)
assert not input_schema.find_foreign_key_failures(dat)
assert not input_schema.find_data_type_failures(dat)
assert not input_schema.find_data_row_failures(dat)
full_parameters = input_schema.create_full_parameters_dict(dat)
sln = solution_schema.TicDat() # create an empty solution'
# solve a distinct MIP for each pair of (# of one-way-trips, amount leftover)
for number_trips, amount_leftover in product(dat.number_of_one_way_trips, dat.amount_leftover):
mdl = gu.Model("metrorail")
# Create decision variables
number_vists = {la:mdl.addVar(vtype = gu.GRB.INTEGER, name="load_amount_%s"%la)
for la in dat.load_amounts}
amount_leftover_var = mdl.addVar(name="amount_leftover", lb=0, ub=amount_leftover)
# an equality constraint is modeled here as amount_leftover_var.lb = amount_leftover_var.ub
if full_parameters["Amount Leftover Constraint"] == "Equality":
amount_leftover_var.lb = amount_leftover
# for left-over is multiple, we will still respect the amount leftover upper bound
# but will also enforce that the amount leftover is a multiple of the one way price
if full_parameters["Amount Leftover Constraint"] == "Upper Bound With Leftover Multiple Rule":
leftover_multiple = mdl.addVar(vtype = gu.GRB.INTEGER, name="leftover_multiple")
mdl.addConstr(amount_leftover_var == full_parameters["One Way Price"] * leftover_multiple,
name="set_leftover_multiple")
# add a constraint to set the amount leftover
mdl.addConstr(amount_leftover_var ==
gu.quicksum(la * number_vists[la] for la in dat.load_amounts) -
full_parameters["One Way Price"] * number_trips,
name="set_amount_leftover")
# minimize the total number of visits to the ticket office
mdl.setObjective(gu.quicksum(number_vists.values()), sense=gu.GRB.MINIMIZE)
mdl.optimize()
if mdl.status in [gu.GRB.OPTIMAL, gu.GRB.SUBOPTIMAL]:
# store the results if and only if the model is feasible
for la,x in number_vists.items():
if round(x.x) > 0:
sln.load_amount_details[number_trips, amount_leftover, la] = round(x.x)
sln.load_amount_summary[number_trips, amount_leftover]["Number Of Visits"]\
+= round(x.x)
return sln
# ---------------------------------------------------------------------------------
# ------------------------ provide stand-alone functionality ----------------------
# when run from the command line, will read/write json/xls/csv/db/sql/mdb files
if __name__ == "__main__":
standard_main(input_schema, solution_schema, solve)
# ---------------------------------------------------------------------------------
|
#
# Models Tallys Yunes Metrorail tickets problem.
# https://orbythebeach.wordpress.com/2018/03/01/buying-metrorail-tickets-in-miami/
# https://www.linkedin.com/pulse/miami-metrorail-meets-python-peter-cacioppi/
#
# Implement core functionality needed to achieve modularity.
# 1. Define the input data schema
# 2. Define the output data schema
# 3. Create a solve function that accepts a data set consistent with the input
# schema and (if possible) returns a data set consistent with the output schema.
#
# Provides command line interface via ticdat.standard_main
# For example, typing
# python metrorail.py -i metrorail_sample_data.json -o metrorail_solution_data.json
# will read from a model stored in the file metrorail_sample_data.json and write the
# solution to metrorail_solution_data.json.
try: # if you don't have gurobipy installed, the code will still load and then fail on solve
import gurobipy as gu
except:
gu = None
from ticdat import TicDatFactory, standard_main
from itertools import product
# ------------------------ define the input schema --------------------------------
input_schema = TicDatFactory (
parameters=[["Parameter"], ["Value"]],
load_amounts=[["Amount"],[]],
number_of_one_way_trips=[["Number"],[]],
amount_leftover=[["Amount"], []])
input_schema.set_data_type("load_amounts", "Amount", min=0, max=float("inf"),
inclusive_min=False, inclusive_max=False)
input_schema.set_data_type("number_of_one_way_trips", "Number", min=0, max=float("inf"),
inclusive_min=False, inclusive_max=False, must_be_int=True)
input_schema.set_data_type("amount_leftover", "Amount", min=0, max=float("inf"),
inclusive_min=True, inclusive_max=False)
input_schema.add_parameter("One Way Price", default_value=2.25, min=0, max=float("inf"), inclusive_min=True,
inclusive_max=False)
input_schema.add_parameter("Amount Leftover Constraint", default_value="Upper Bound", number_allowed=False,
strings_allowed=["Equality", "Upper Bound", "Upper Bound With Leftover Multiple Rule"])
# ---------------------------------------------------------------------------------
# ------------------------ define the output schema -------------------------------
solution_schema = TicDatFactory(
load_amount_details=[["Number One Way Trips", "Amount Leftover", "Load Amount"],
["Number Of Visits"]],
load_amount_summary=[["Number One Way Trips", "Amount Leftover"],["Number Of Visits"]])
# ---------------------------------------------------------------------------------
# ------------------------ create a solve function --------------------------------
def solve(dat):
"""
core solving routine
:param dat: a good ticdat for the input_schema
:return: a good ticdat for the solution_schema, or None
"""
assert input_schema.good_tic_dat_object(dat)
assert not input_schema.find_foreign_key_failures(dat)
assert not input_schema.find_data_type_failures(dat)
assert not input_schema.find_data_row_failures(dat)
full_parameters = input_schema.create_full_parameters_dict(dat)
sln = solution_schema.TicDat() # create an empty solution'
# solve a distinct MIP for each pair of (# of one-way-trips, amount leftover)
for number_trips, amount_leftover in product(dat.number_of_one_way_trips, dat.amount_leftover):
mdl = gu.Model("metrorail")
# Create decision variables
number_vists = {la:mdl.addVar(vtype = gu.GRB.INTEGER, name="load_amount_%s"%la)
for la in dat.load_amounts}
amount_leftover_var = mdl.addVar(name="amount_leftover", lb=0, ub=amount_leftover)
# an equality constraint is modeled here as amount_leftover_var.lb = amount_leftover_var.ub
if full_parameters["Amount Leftover Constraint"] == "Equality":
amount_leftover_var.lb = amount_leftover
# for left-over is multiple, we will still respect the amount leftover upper bound
# but will also enforce that the amount leftover is a multiple of the one way price
if full_parameters["Amount Leftover Constraint"] == "Upper Bound With Leftover Multiple Rule":
leftover_multiple = mdl.addVar(vtype = gu.GRB.INTEGER, name="leftover_multiple")
mdl.addConstr(amount_leftover_var == full_parameters["One Way Price"] * leftover_multiple,
name="set_leftover_multiple")
# add a constraint to set the amount leftover
mdl.addConstr(amount_leftover_var ==
gu.quicksum(la * number_vists[la] for la in dat.load_amounts) -
full_parameters["One Way Price"] * number_trips,
name="set_amount_leftover")
# minimize the total number of visits to the ticket office
mdl.setObjective(gu.quicksum(number_vists.values()), sense=gu.GRB.MINIMIZE)
mdl.optimize()
if mdl.status in [gu.GRB.OPTIMAL, gu.GRB.SUBOPTIMAL]:
# store the results if and only if the model is feasible
for la,x in number_vists.items():
if round(x.x) > 0:
sln.load_amount_details[number_trips, amount_leftover, la] = round(x.x)
sln.load_amount_summary[number_trips, amount_leftover]["Number Of Visits"]\
+= round(x.x)
return sln
# ---------------------------------------------------------------------------------
# ------------------------ provide stand-alone functionality ----------------------
# when run from the command line, will read/write json/xls/csv/db/sql/mdb files
if __name__ == "__main__":
standard_main(input_schema, solution_schema, solve)
# ---------------------------------------------------------------------------------
|
en
| 0.551666
|
# # Models Tallys Yunes Metrorail tickets problem. # https://orbythebeach.wordpress.com/2018/03/01/buying-metrorail-tickets-in-miami/ # https://www.linkedin.com/pulse/miami-metrorail-meets-python-peter-cacioppi/ # # Implement core functionality needed to achieve modularity. # 1. Define the input data schema # 2. Define the output data schema # 3. Create a solve function that accepts a data set consistent with the input # schema and (if possible) returns a data set consistent with the output schema. # # Provides command line interface via ticdat.standard_main # For example, typing # python metrorail.py -i metrorail_sample_data.json -o metrorail_solution_data.json # will read from a model stored in the file metrorail_sample_data.json and write the # solution to metrorail_solution_data.json. # if you don't have gurobipy installed, the code will still load and then fail on solve # ------------------------ define the input schema -------------------------------- # --------------------------------------------------------------------------------- # ------------------------ define the output schema ------------------------------- # --------------------------------------------------------------------------------- # ------------------------ create a solve function -------------------------------- core solving routine :param dat: a good ticdat for the input_schema :return: a good ticdat for the solution_schema, or None # create an empty solution' # solve a distinct MIP for each pair of (# of one-way-trips, amount leftover) # Create decision variables # an equality constraint is modeled here as amount_leftover_var.lb = amount_leftover_var.ub # for left-over is multiple, we will still respect the amount leftover upper bound # but will also enforce that the amount leftover is a multiple of the one way price # add a constraint to set the amount leftover # minimize the total number of visits to the ticket office # store the results if and only if the model is feasible # --------------------------------------------------------------------------------- # ------------------------ provide stand-alone functionality ---------------------- # when run from the command line, will read/write json/xls/csv/db/sql/mdb files # ---------------------------------------------------------------------------------
| 2.710314
| 3
|
genetic-tuner/lib/listtools.py
|
windstrip/Genetic-Algorithm-PID-Controller-Tuner
| 39
|
6625766
|
<reponame>windstrip/Genetic-Algorithm-PID-Controller-Tuner
# Reference:
# http://code.activestate.com/recipes/278258/
def sumList(L):
return reduce(lambda x,y:x+y, L)
def avgList(L):
return reduce(lambda x,y:x+y, L) /(len(L)*1.0)
def normList(L, normalizeTo=1):
'''normalize values of a list to make its max = normalizeTo'''
vMax = max(L)
return [ x/(vMax*1.0)*normalizeTo for x in L]
def normListSumTo(L, sumTo=1):
'''normalize values of a list to make it sum = sumTo'''
sum = reduce(lambda x,y:x+y, L)
return [ x/(sum*1.0)*sumTo for x in L]
def accumList(L, normalizeTo=None):
''' L= [1, 2, 3, 4, 5]: accumList(L)=> [1, 3, 6, 10, 15]
L= [0.25, 0.25, 0.25, 0.25]: accumList(L)=> [0.25, 0.50, 0.75, 1.00]
normalizeTo: set the last number of the returned list to this value
'''
if normalizeTo: LL = normListSumTo(L, sumTo=normalizeTo)
else: LL = L[:]
r = range(1, len(LL))
newList=[LL[0]]
for i in r:
newList.append( newList[-1]+ LL[i] )
return newList
def findIndex(sortedList, x, indexBuffer=0):
''' Given a sortedList and value x, return the index i where
sortedList[i-1] <= x < sortedList[i]
Which means,
sortedList.insert( findIndex(sortedList, x), x )
will give a sorted list
'''
if len(sortedList)==2:
if x==sortedList[-1]: return indexBuffer+2
elif x>=sortedList[0]: return indexBuffer+1
else:
L = len(sortedList)
firstHalf = sortedList[:L/2+1]
secondHalf = sortedList[(L/2):]
if secondHalf[-1]<=x:
return indexBuffer + len(sortedList)
elif x< firstHalf[0]:
return indexBuffer
else:
if firstHalf[-1] < x:
return findIndex(secondHalf, x, indexBuffer=L/2+indexBuffer)
else:
return findIndex(firstHalf,x, indexBuffer=indexBuffer)
def randomPickList(L):
''' given a list L, with all values are numbers,
randomly pick an item and return it's index according
to the percentage of all values'''
return findIndex(accumList(L,1), random.random())
def deepList(LString):
'''
Given string representation of a nested list tree,
return a list containing all the deepest list contents.
For example:
'[[1,[2, 2a]],[[3,3b],4]]'
==> ['2, 2a', '3,3b']
'[[[1,[2, 2a]],[[3,3b],4]],6]'
==> ['2, 2a', '3,3b']
'[[[[a1,a2],out],o1],[o2,o3]]'
==> ['a1,a2', 'o2,o3']
'[[[[[a1,a2], out], [o1,o2]],[o3,o4]],[o5,o6]]'
==> ['a1,a2', 'o1,o2', 'o3,o4', 'o5,o6']
The code: [x.split(']') for x in code.split('[')]
returns something like:
[[''], [''], [''], [''], [''], ['a1,a2', ', out', ', '],
['o1,o2', '', ','], ['o3,o4', '', ','], ['o5,o6', '', '']]
'''
result= [x[0] for x in \
[x.split(']') for x in LString.split('[')] \
if len(x)>1]
if result==['']: result =[]
return result
def getListStartsWith(aList, startsWith, isStrip=1):
''' for a list: L= ['abcdef', 'kkddff', 'xyz', '0wer'...],
getListStartWith(L, 'kk') will return:
['kkddff', 'xyz', '0wer'...],
getListStartWith(L, 'xy') will return:
['xyz', '0wer'...],
if isStrip: any item ' xyz' will be considered 'xyz'
else: the spaces in ' xyz' count.
'''
tmp = aList[:]
if isStrip: tmp = [x.strip() for x in tmp]
startLineIndex = 0
for i in range(len(tmp)):
if tmp[i].startswith(startsWith):
startLineIndex = i
return aList[startLineIndex:]
def rezip(aList):
''' d = [[1, 5, 8, 3], [2, 2, 3, 9], [3, 2, 4, 6]]
rezip(d):
[(1, 2, 3), (5, 2, 2), (8, 3, 4), (3, 9, 6)]
If a =[1, 5, 8], b=[2, 2, 3], c=[3, 2, 4]
then it's eazy to: zip(a,b,c) = [(1, 2, 3), (5, 2, 2), (8, 3, 4)]
But it's hard for d = [[1, 5, 8], [2, 2, 3], [3, 2, 4]]
'''
tmp = [ [] for x in range(len(aList[0])) ]
for i in range(len(aList[0])):
for j in range(len(aList)):
tmp[i].append(aList[j][i])
return tmp
def sumInList(complexList):
''' Given a complexList [ [a1,b1,c1], [a2,b2,c2], [a3,b3,c3] ],
return a list [ a, b, c] where a = a1+a2+a3, etc.'''
d = rezip(complexList)
return [ reduce(lambda x,y:x+y, z) for z in d ]
def avgInList(complexList):
''' Given a complexList [ [a1,b1,c1], [a2,b2,c2], [a3,b3,c3] ],
return a list [ a, b, c] where a = avg of a1, a2, a3, etc.'''
d = rezip(complexList)
return [ reduce(lambda x,y:x+y, z)/(len(z)*1.0) for z in d ]
## requires positive values (0 counts)
def max_value_in_list(list):
max_index = 0
max_value = -1
for i in range(len(list)):
if list[i] > max_value:
max_value = list[i]
max_index = i
return max_value
def max_index_in_list(list):
max_index = 0
max_value = -1
for i in range(len(list)):
if list[i] > max_value:
max_value = list[i]
max_index = i
return max_index
def min_value_in_list(list):
min_index = 0
min_value = 99999999
for i in range(len(list)):
if list[i] < min_value:
min_value = list[i]
return min_value
|
# Reference:
# http://code.activestate.com/recipes/278258/
def sumList(L):
return reduce(lambda x,y:x+y, L)
def avgList(L):
return reduce(lambda x,y:x+y, L) /(len(L)*1.0)
def normList(L, normalizeTo=1):
'''normalize values of a list to make its max = normalizeTo'''
vMax = max(L)
return [ x/(vMax*1.0)*normalizeTo for x in L]
def normListSumTo(L, sumTo=1):
'''normalize values of a list to make it sum = sumTo'''
sum = reduce(lambda x,y:x+y, L)
return [ x/(sum*1.0)*sumTo for x in L]
def accumList(L, normalizeTo=None):
''' L= [1, 2, 3, 4, 5]: accumList(L)=> [1, 3, 6, 10, 15]
L= [0.25, 0.25, 0.25, 0.25]: accumList(L)=> [0.25, 0.50, 0.75, 1.00]
normalizeTo: set the last number of the returned list to this value
'''
if normalizeTo: LL = normListSumTo(L, sumTo=normalizeTo)
else: LL = L[:]
r = range(1, len(LL))
newList=[LL[0]]
for i in r:
newList.append( newList[-1]+ LL[i] )
return newList
def findIndex(sortedList, x, indexBuffer=0):
''' Given a sortedList and value x, return the index i where
sortedList[i-1] <= x < sortedList[i]
Which means,
sortedList.insert( findIndex(sortedList, x), x )
will give a sorted list
'''
if len(sortedList)==2:
if x==sortedList[-1]: return indexBuffer+2
elif x>=sortedList[0]: return indexBuffer+1
else:
L = len(sortedList)
firstHalf = sortedList[:L/2+1]
secondHalf = sortedList[(L/2):]
if secondHalf[-1]<=x:
return indexBuffer + len(sortedList)
elif x< firstHalf[0]:
return indexBuffer
else:
if firstHalf[-1] < x:
return findIndex(secondHalf, x, indexBuffer=L/2+indexBuffer)
else:
return findIndex(firstHalf,x, indexBuffer=indexBuffer)
def randomPickList(L):
''' given a list L, with all values are numbers,
randomly pick an item and return it's index according
to the percentage of all values'''
return findIndex(accumList(L,1), random.random())
def deepList(LString):
'''
Given string representation of a nested list tree,
return a list containing all the deepest list contents.
For example:
'[[1,[2, 2a]],[[3,3b],4]]'
==> ['2, 2a', '3,3b']
'[[[1,[2, 2a]],[[3,3b],4]],6]'
==> ['2, 2a', '3,3b']
'[[[[a1,a2],out],o1],[o2,o3]]'
==> ['a1,a2', 'o2,o3']
'[[[[[a1,a2], out], [o1,o2]],[o3,o4]],[o5,o6]]'
==> ['a1,a2', 'o1,o2', 'o3,o4', 'o5,o6']
The code: [x.split(']') for x in code.split('[')]
returns something like:
[[''], [''], [''], [''], [''], ['a1,a2', ', out', ', '],
['o1,o2', '', ','], ['o3,o4', '', ','], ['o5,o6', '', '']]
'''
result= [x[0] for x in \
[x.split(']') for x in LString.split('[')] \
if len(x)>1]
if result==['']: result =[]
return result
def getListStartsWith(aList, startsWith, isStrip=1):
''' for a list: L= ['abcdef', 'kkddff', 'xyz', '0wer'...],
getListStartWith(L, 'kk') will return:
['kkddff', 'xyz', '0wer'...],
getListStartWith(L, 'xy') will return:
['xyz', '0wer'...],
if isStrip: any item ' xyz' will be considered 'xyz'
else: the spaces in ' xyz' count.
'''
tmp = aList[:]
if isStrip: tmp = [x.strip() for x in tmp]
startLineIndex = 0
for i in range(len(tmp)):
if tmp[i].startswith(startsWith):
startLineIndex = i
return aList[startLineIndex:]
def rezip(aList):
''' d = [[1, 5, 8, 3], [2, 2, 3, 9], [3, 2, 4, 6]]
rezip(d):
[(1, 2, 3), (5, 2, 2), (8, 3, 4), (3, 9, 6)]
If a =[1, 5, 8], b=[2, 2, 3], c=[3, 2, 4]
then it's eazy to: zip(a,b,c) = [(1, 2, 3), (5, 2, 2), (8, 3, 4)]
But it's hard for d = [[1, 5, 8], [2, 2, 3], [3, 2, 4]]
'''
tmp = [ [] for x in range(len(aList[0])) ]
for i in range(len(aList[0])):
for j in range(len(aList)):
tmp[i].append(aList[j][i])
return tmp
def sumInList(complexList):
''' Given a complexList [ [a1,b1,c1], [a2,b2,c2], [a3,b3,c3] ],
return a list [ a, b, c] where a = a1+a2+a3, etc.'''
d = rezip(complexList)
return [ reduce(lambda x,y:x+y, z) for z in d ]
def avgInList(complexList):
''' Given a complexList [ [a1,b1,c1], [a2,b2,c2], [a3,b3,c3] ],
return a list [ a, b, c] where a = avg of a1, a2, a3, etc.'''
d = rezip(complexList)
return [ reduce(lambda x,y:x+y, z)/(len(z)*1.0) for z in d ]
## requires positive values (0 counts)
def max_value_in_list(list):
max_index = 0
max_value = -1
for i in range(len(list)):
if list[i] > max_value:
max_value = list[i]
max_index = i
return max_value
def max_index_in_list(list):
max_index = 0
max_value = -1
for i in range(len(list)):
if list[i] > max_value:
max_value = list[i]
max_index = i
return max_index
def min_value_in_list(list):
min_index = 0
min_value = 99999999
for i in range(len(list)):
if list[i] < min_value:
min_value = list[i]
return min_value
|
en
| 0.466604
|
# Reference: # http://code.activestate.com/recipes/278258/ normalize values of a list to make its max = normalizeTo normalize values of a list to make it sum = sumTo L= [1, 2, 3, 4, 5]: accumList(L)=> [1, 3, 6, 10, 15] L= [0.25, 0.25, 0.25, 0.25]: accumList(L)=> [0.25, 0.50, 0.75, 1.00] normalizeTo: set the last number of the returned list to this value Given a sortedList and value x, return the index i where sortedList[i-1] <= x < sortedList[i] Which means, sortedList.insert( findIndex(sortedList, x), x ) will give a sorted list given a list L, with all values are numbers, randomly pick an item and return it's index according to the percentage of all values Given string representation of a nested list tree, return a list containing all the deepest list contents. For example: '[[1,[2, 2a]],[[3,3b],4]]' ==> ['2, 2a', '3,3b'] '[[[1,[2, 2a]],[[3,3b],4]],6]' ==> ['2, 2a', '3,3b'] '[[[[a1,a2],out],o1],[o2,o3]]' ==> ['a1,a2', 'o2,o3'] '[[[[[a1,a2], out], [o1,o2]],[o3,o4]],[o5,o6]]' ==> ['a1,a2', 'o1,o2', 'o3,o4', 'o5,o6'] The code: [x.split(']') for x in code.split('[')] returns something like: [[''], [''], [''], [''], [''], ['a1,a2', ', out', ', '], ['o1,o2', '', ','], ['o3,o4', '', ','], ['o5,o6', '', '']] for a list: L= ['abcdef', 'kkddff', 'xyz', '0wer'...], getListStartWith(L, 'kk') will return: ['kkddff', 'xyz', '0wer'...], getListStartWith(L, 'xy') will return: ['xyz', '0wer'...], if isStrip: any item ' xyz' will be considered 'xyz' else: the spaces in ' xyz' count. d = [[1, 5, 8, 3], [2, 2, 3, 9], [3, 2, 4, 6]] rezip(d): [(1, 2, 3), (5, 2, 2), (8, 3, 4), (3, 9, 6)] If a =[1, 5, 8], b=[2, 2, 3], c=[3, 2, 4] then it's eazy to: zip(a,b,c) = [(1, 2, 3), (5, 2, 2), (8, 3, 4)] But it's hard for d = [[1, 5, 8], [2, 2, 3], [3, 2, 4]] Given a complexList [ [a1,b1,c1], [a2,b2,c2], [a3,b3,c3] ], return a list [ a, b, c] where a = a1+a2+a3, etc. Given a complexList [ [a1,b1,c1], [a2,b2,c2], [a3,b3,c3] ], return a list [ a, b, c] where a = avg of a1, a2, a3, etc. ## requires positive values (0 counts)
| 3.32148
| 3
|
appspotify/pytify/core/album.py
|
DiegoSantosWS/spotfy-py
| 0
|
6625767
|
<reponame>DiegoSantosWS/spotfy-py<filename>appspotify/pytify/core/album.py
from .parameter import prepare_params
from .request import execute_request
def get_album_tracks(album_id, auth, params=None):
if album_id is None or album_id is '':
raise AttributeError(
'Parameter `album_id` cannot be `None` or empty.')
url_template = '{base_url}/{area}/{albumid}/{postfix}{query}'
url_params = {
'query': prepare_params(params),
'area': 'albums',
'albumid': album_id,
'postfix': 'tracks',
}
return execute_request(url_template, auth, url_params)
|
from .parameter import prepare_params
from .request import execute_request
def get_album_tracks(album_id, auth, params=None):
if album_id is None or album_id is '':
raise AttributeError(
'Parameter `album_id` cannot be `None` or empty.')
url_template = '{base_url}/{area}/{albumid}/{postfix}{query}'
url_params = {
'query': prepare_params(params),
'area': 'albums',
'albumid': album_id,
'postfix': 'tracks',
}
return execute_request(url_template, auth, url_params)
|
none
| 1
| 2.423047
| 2
|
|
collection/clientlib/base.py
|
WilkinsonK/python-collections
| 0
|
6625768
|
<reponame>WilkinsonK/python-collections<filename>collection/clientlib/base.py
import functools
from abc import ABC, abstractmethod
from clientlib.enums import Method
from clientlib.errors import HTTPError
from clientlib.mixins import ClientInitMixIn, ClientValidationMixIn
from clientlib.typedefs import Response, Session
def not_implemented(method):
"""
Raise a not implemented error if method
returns 'NotImplemented' type.
"""
@functools.wraps(method)
def inner(*args, **kwargs):
result = method(*args, **kwargs)
if result is NotImplemented:
raise_not_implemented()
return result
def raise_not_implemented():
message = f"method {method!r} has not been implemented yet!"
raise NotImplementedError(message)
return inner
class BaseClient(ClientInitMixIn, ClientValidationMixIn, ABC):
def _init(self, *args, **kwargs):
super()._init(*args, **kwargs)
self.healthcheck()
def _send(self, method, endpoint, **kwargs):
root_url, timeout, kwargs = self._parse_send_kwargs(**kwargs)
method, address = self._parse_send_args(method, root_url, endpoint)
return self.session.request(
method, url=address, timeout=timeout, **kwargs)
def _parse_send_address(self, root_url, endpoint):
address = "/".join([root_url, endpoint or ""])
return address
def _parse_send_args(self, method, root_url, endpoint):
address = self._parse_send_address(root_url, endpoint)
method = self._parse_send_method(method)
return method, address
def _parse_send_kwargs(self, **kwargs):
timeout = kwargs.pop("max_timeout", self.max_timeout)
root_url = kwargs.pop("root_url", self.root_url)
return root_url, timeout, kwargs
def _parse_send_method(self, method):
if method.__class__ in (str, Method):
return str(method)
return NotImplemented
@property
def session(self) -> Session:
return self._session
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
self.session.close()
@abstractmethod
@not_implemented
def handle_http_error(self, error: HTTPError, resp: Response = None) -> None:
"""
Not implemented here.
Handle http protocol errors.
"""
return NotImplemented
@abstractmethod
@not_implemented
def healthcheck(self) -> int:
"""
Not implemented here.
Send a health check ping to api reference.
"""
return NotImplemented
@abstractmethod
@not_implemented
def refresh(self, **kwargs) -> None:
"""
Not implemented here.
Reset the client session.
"""
return NotImplemented
@abstractmethod
@not_implemented
def send(self, method: Method, endpoint: str = None, data: dict = None, **kwargs) -> Response:
"""
Not implemented here.
Send a request using the ApiClient settings.
"""
return NotImplemented
|
import functools
from abc import ABC, abstractmethod
from clientlib.enums import Method
from clientlib.errors import HTTPError
from clientlib.mixins import ClientInitMixIn, ClientValidationMixIn
from clientlib.typedefs import Response, Session
def not_implemented(method):
"""
Raise a not implemented error if method
returns 'NotImplemented' type.
"""
@functools.wraps(method)
def inner(*args, **kwargs):
result = method(*args, **kwargs)
if result is NotImplemented:
raise_not_implemented()
return result
def raise_not_implemented():
message = f"method {method!r} has not been implemented yet!"
raise NotImplementedError(message)
return inner
class BaseClient(ClientInitMixIn, ClientValidationMixIn, ABC):
def _init(self, *args, **kwargs):
super()._init(*args, **kwargs)
self.healthcheck()
def _send(self, method, endpoint, **kwargs):
root_url, timeout, kwargs = self._parse_send_kwargs(**kwargs)
method, address = self._parse_send_args(method, root_url, endpoint)
return self.session.request(
method, url=address, timeout=timeout, **kwargs)
def _parse_send_address(self, root_url, endpoint):
address = "/".join([root_url, endpoint or ""])
return address
def _parse_send_args(self, method, root_url, endpoint):
address = self._parse_send_address(root_url, endpoint)
method = self._parse_send_method(method)
return method, address
def _parse_send_kwargs(self, **kwargs):
timeout = kwargs.pop("max_timeout", self.max_timeout)
root_url = kwargs.pop("root_url", self.root_url)
return root_url, timeout, kwargs
def _parse_send_method(self, method):
if method.__class__ in (str, Method):
return str(method)
return NotImplemented
@property
def session(self) -> Session:
return self._session
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
self.session.close()
@abstractmethod
@not_implemented
def handle_http_error(self, error: HTTPError, resp: Response = None) -> None:
"""
Not implemented here.
Handle http protocol errors.
"""
return NotImplemented
@abstractmethod
@not_implemented
def healthcheck(self) -> int:
"""
Not implemented here.
Send a health check ping to api reference.
"""
return NotImplemented
@abstractmethod
@not_implemented
def refresh(self, **kwargs) -> None:
"""
Not implemented here.
Reset the client session.
"""
return NotImplemented
@abstractmethod
@not_implemented
def send(self, method: Method, endpoint: str = None, data: dict = None, **kwargs) -> Response:
"""
Not implemented here.
Send a request using the ApiClient settings.
"""
return NotImplemented
|
en
| 0.701957
|
Raise a not implemented error if method returns 'NotImplemented' type. Not implemented here. Handle http protocol errors. Not implemented here. Send a health check ping to api reference. Not implemented here. Reset the client session. Not implemented here. Send a request using the ApiClient settings.
| 2.349908
| 2
|
simulation_ws/src/ros2_robot_simulation/launch/launch.py
|
samuk/ANI717_Robotics
| 0
|
6625769
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""ROS2 Robot Simulation Launch File.
This script simulates a robot in Gazebo simulation.
Revision History:
2021-10-23 (Animesh): Baseline Software.
Example:
$ colcon build && source install/setup.bash && ros2 launch ros2_robot_simulation launch.py
$ source install/setup.bash && ros2 launch ros2_robot_simulation launch.py
$ ros2 launch ros2_robot_simulation launch.py
"""
#___Import Modules:
import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.substitutions import LaunchConfiguration
from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch_ros.actions import Node
#___Function:
def generate_launch_description():
# Get the package directory
ros2_world_simulation_dir = get_package_share_directory('ros2_world_simulation')
ros2_robot_simulation_dir = get_package_share_directory('ros2_robot_simulation')
# Create launch configuration variables
use_simulator = LaunchConfiguration('use_simulator')
headless = LaunchConfiguration('headless')
world = LaunchConfiguration('world')
x_pos = LaunchConfiguration('x_pos')
y_pos = LaunchConfiguration('y_pos')
z_pos = LaunchConfiguration('z_pos')
roll = LaunchConfiguration('roll')
pitch = LaunchConfiguration('pitch')
yaw = LaunchConfiguration('yaw')
urdf_file = LaunchConfiguration('urdf_file')
# Declare the launch arguments
declare_use_simulator_cmd = DeclareLaunchArgument(
'use_simulator',
default_value='True',
description='Whether to start the simulator')
declare_simulator_cmd = DeclareLaunchArgument(
'headless',
default_value='False',
description='Whether to execute gzclient)')
declare_world_cmd = DeclareLaunchArgument(
'world',
default_value=os.path.join(ros2_world_simulation_dir, 'worlds', 'empty.world'),
description='Full path to world model file to load')
declare_x_pos_cmd = DeclareLaunchArgument(
'x_pos',
default_value='0.0')
declare_y_pos_cmd = DeclareLaunchArgument(
'y_pos',
default_value='0.0')
declare_z_pos_cmd = DeclareLaunchArgument(
'z_pos',
default_value='0.0')
declare_roll_cmd = DeclareLaunchArgument(
'roll',
default_value='0.0')
declare_pitch_cmd = DeclareLaunchArgument(
'pitch',
default_value='0.0')
declare_yaw_cmd = DeclareLaunchArgument(
'yaw',
default_value='0.0')
declare_urdf_file_cmd = DeclareLaunchArgument(
'urdf_file',
default_value='jetbot.urdf')
# Specify the actions
world_launch_cmd = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(ros2_world_simulation_dir, 'launch', 'launch.py')),
launch_arguments={'use_simulator': use_simulator,
'headless': headless,
'world': world}.items())
spawn_robot_cmd = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(ros2_robot_simulation_dir, 'launch', 'spawn.py')),
launch_arguments={'x_pos': x_pos,
'y_pos': y_pos,
'z_pos': z_pos,
'roll': roll,
'pitch': pitch,
'yaw': yaw,
'urdf': urdf_file}.items())
robot_states_cmd = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(ros2_robot_simulation_dir, 'launch', 'states.py')),
launch_arguments={'urdf': urdf_file,}.items())
# Create the launch description and populate
ld = LaunchDescription()
# Declare the launch options
ld.add_action(declare_use_simulator_cmd)
ld.add_action(declare_simulator_cmd)
ld.add_action(declare_world_cmd)
ld.add_action(declare_x_pos_cmd)
ld.add_action(declare_y_pos_cmd)
ld.add_action(declare_z_pos_cmd)
ld.add_action(declare_roll_cmd)
ld.add_action(declare_pitch_cmd)
ld.add_action(declare_yaw_cmd)
ld.add_action(declare_urdf_file_cmd)
# Add all actions
ld.add_action(world_launch_cmd)
ld.add_action(spawn_robot_cmd)
ld.add_action(robot_states_cmd)
return ld
#
# end of file
"""ANI717"""
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""ROS2 Robot Simulation Launch File.
This script simulates a robot in Gazebo simulation.
Revision History:
2021-10-23 (Animesh): Baseline Software.
Example:
$ colcon build && source install/setup.bash && ros2 launch ros2_robot_simulation launch.py
$ source install/setup.bash && ros2 launch ros2_robot_simulation launch.py
$ ros2 launch ros2_robot_simulation launch.py
"""
#___Import Modules:
import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.substitutions import LaunchConfiguration
from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch_ros.actions import Node
#___Function:
def generate_launch_description():
# Get the package directory
ros2_world_simulation_dir = get_package_share_directory('ros2_world_simulation')
ros2_robot_simulation_dir = get_package_share_directory('ros2_robot_simulation')
# Create launch configuration variables
use_simulator = LaunchConfiguration('use_simulator')
headless = LaunchConfiguration('headless')
world = LaunchConfiguration('world')
x_pos = LaunchConfiguration('x_pos')
y_pos = LaunchConfiguration('y_pos')
z_pos = LaunchConfiguration('z_pos')
roll = LaunchConfiguration('roll')
pitch = LaunchConfiguration('pitch')
yaw = LaunchConfiguration('yaw')
urdf_file = LaunchConfiguration('urdf_file')
# Declare the launch arguments
declare_use_simulator_cmd = DeclareLaunchArgument(
'use_simulator',
default_value='True',
description='Whether to start the simulator')
declare_simulator_cmd = DeclareLaunchArgument(
'headless',
default_value='False',
description='Whether to execute gzclient)')
declare_world_cmd = DeclareLaunchArgument(
'world',
default_value=os.path.join(ros2_world_simulation_dir, 'worlds', 'empty.world'),
description='Full path to world model file to load')
declare_x_pos_cmd = DeclareLaunchArgument(
'x_pos',
default_value='0.0')
declare_y_pos_cmd = DeclareLaunchArgument(
'y_pos',
default_value='0.0')
declare_z_pos_cmd = DeclareLaunchArgument(
'z_pos',
default_value='0.0')
declare_roll_cmd = DeclareLaunchArgument(
'roll',
default_value='0.0')
declare_pitch_cmd = DeclareLaunchArgument(
'pitch',
default_value='0.0')
declare_yaw_cmd = DeclareLaunchArgument(
'yaw',
default_value='0.0')
declare_urdf_file_cmd = DeclareLaunchArgument(
'urdf_file',
default_value='jetbot.urdf')
# Specify the actions
world_launch_cmd = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(ros2_world_simulation_dir, 'launch', 'launch.py')),
launch_arguments={'use_simulator': use_simulator,
'headless': headless,
'world': world}.items())
spawn_robot_cmd = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(ros2_robot_simulation_dir, 'launch', 'spawn.py')),
launch_arguments={'x_pos': x_pos,
'y_pos': y_pos,
'z_pos': z_pos,
'roll': roll,
'pitch': pitch,
'yaw': yaw,
'urdf': urdf_file}.items())
robot_states_cmd = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(ros2_robot_simulation_dir, 'launch', 'states.py')),
launch_arguments={'urdf': urdf_file,}.items())
# Create the launch description and populate
ld = LaunchDescription()
# Declare the launch options
ld.add_action(declare_use_simulator_cmd)
ld.add_action(declare_simulator_cmd)
ld.add_action(declare_world_cmd)
ld.add_action(declare_x_pos_cmd)
ld.add_action(declare_y_pos_cmd)
ld.add_action(declare_z_pos_cmd)
ld.add_action(declare_roll_cmd)
ld.add_action(declare_pitch_cmd)
ld.add_action(declare_yaw_cmd)
ld.add_action(declare_urdf_file_cmd)
# Add all actions
ld.add_action(world_launch_cmd)
ld.add_action(spawn_robot_cmd)
ld.add_action(robot_states_cmd)
return ld
#
# end of file
"""ANI717"""
|
en
| 0.511068
|
#!/usr/bin/env python # -*- coding: utf-8 -*- ROS2 Robot Simulation Launch File. This script simulates a robot in Gazebo simulation. Revision History: 2021-10-23 (Animesh): Baseline Software. Example: $ colcon build && source install/setup.bash && ros2 launch ros2_robot_simulation launch.py $ source install/setup.bash && ros2 launch ros2_robot_simulation launch.py $ ros2 launch ros2_robot_simulation launch.py #___Import Modules: #___Function: # Get the package directory # Create launch configuration variables # Declare the launch arguments # Specify the actions # Create the launch description and populate # Declare the launch options # Add all actions # # end of file ANI717
| 2.215135
| 2
|
zillowdb/packages/sfm/str_encoding.py
|
MacHu-GWU/zillowdb-project
| 0
|
6625770
|
<reponame>MacHu-GWU/zillowdb-project
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import base64
def encode_base64_urlsafe(text):
"""Convert any utf-8 string to url safe string using base64 encoding.
**中文文档**
将任意utf-8字符串用base64编码算法编码为纯数字和字母。
"""
return base64.urlsafe_b64encode(text.encode("utf-8")).decode("utf-8")
def decode_base64_urlsafe(text):
"""Reverse operation of :func:`encode_base64_urlsafe`.
**中文文档**
将base64字符串解码为原字符串。
"""
return base64.urlsafe_b64decode(text.encode("utf-8")).decode("utf-8")
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import base64
def encode_base64_urlsafe(text):
"""Convert any utf-8 string to url safe string using base64 encoding.
**中文文档**
将任意utf-8字符串用base64编码算法编码为纯数字和字母。
"""
return base64.urlsafe_b64encode(text.encode("utf-8")).decode("utf-8")
def decode_base64_urlsafe(text):
"""Reverse operation of :func:`encode_base64_urlsafe`.
**中文文档**
将base64字符串解码为原字符串。
"""
return base64.urlsafe_b64decode(text.encode("utf-8")).decode("utf-8")
|
zh
| 0.478128
|
#!/usr/bin/env python # -*- coding: utf-8 -*- Convert any utf-8 string to url safe string using base64 encoding. **中文文档** 将任意utf-8字符串用base64编码算法编码为纯数字和字母。 Reverse operation of :func:`encode_base64_urlsafe`. **中文文档** 将base64字符串解码为原字符串。
| 2.961841
| 3
|
unit_tests.py
|
ccubed/OTPy
| 2
|
6625771
|
import unittest
from otpy.hotp import hotp
from otpy.totp import totp
class TestHotp(unittest.TestCase):
def setUp(self):
self.expected = [755224, 287082, 359152, 969429, 338314, 254676, 287922, 162583, 399871, 520489]
self.instance = hotp("12345678901234567890", 0, 6)
def test_rfc4226(self):
for x in range(10):
self.assertEqual(self.instance.at(x), str(self.expected[x]))
for x in range(10):
self.assertEqual(self.instance.next(), str(self.expected[x]))
for x in range(10):
self.assertTrue(self.instance.verify(str(self.expected[x]), x))
self.assertEqual(self.instance.drift(3, 1, 1), ['359152', '969429', '338314'])
class TestTotp(unittest.TestCase):
def setUp(self):
self.instance = totp("12345678901234567890", 15108406016, 30, 8)
def test_rfc6238_sha1(self):
self.assertTrue(self.instance.verify_seconds("94287082", 59))
self.assertTrue(self.instance.verify_seconds("07081804", 1111111109))
self.assertTrue(self.instance.verify_seconds("14050471", 1111111111))
self.assertTrue(self.instance.verify_seconds("89005924", 1234567890))
self.assertTrue(self.instance.verify_seconds("69279037", 2000000000))
self.assertTrue(self.instance.verify_seconds("65353130", 20000000000))
|
import unittest
from otpy.hotp import hotp
from otpy.totp import totp
class TestHotp(unittest.TestCase):
def setUp(self):
self.expected = [755224, 287082, 359152, 969429, 338314, 254676, 287922, 162583, 399871, 520489]
self.instance = hotp("12345678901234567890", 0, 6)
def test_rfc4226(self):
for x in range(10):
self.assertEqual(self.instance.at(x), str(self.expected[x]))
for x in range(10):
self.assertEqual(self.instance.next(), str(self.expected[x]))
for x in range(10):
self.assertTrue(self.instance.verify(str(self.expected[x]), x))
self.assertEqual(self.instance.drift(3, 1, 1), ['359152', '969429', '338314'])
class TestTotp(unittest.TestCase):
def setUp(self):
self.instance = totp("12345678901234567890", 15108406016, 30, 8)
def test_rfc6238_sha1(self):
self.assertTrue(self.instance.verify_seconds("94287082", 59))
self.assertTrue(self.instance.verify_seconds("07081804", 1111111109))
self.assertTrue(self.instance.verify_seconds("14050471", 1111111111))
self.assertTrue(self.instance.verify_seconds("89005924", 1234567890))
self.assertTrue(self.instance.verify_seconds("69279037", 2000000000))
self.assertTrue(self.instance.verify_seconds("65353130", 20000000000))
|
none
| 1
| 2.639287
| 3
|
|
cinder/zonemanager/drivers/cisco/cisco_fc_zone_driver.py
|
hashsos/hashcloudos-cinder
| 0
|
6625772
|
<filename>cinder/zonemanager/drivers/cisco/cisco_fc_zone_driver.py<gh_stars>0
# (c) Copyright 2014 Cisco Systems Inc.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
"""
Cisco Zone Driver is responsible to manage access control using FC zoning
for Cisco FC fabrics.
This is a concrete implementation of FCZoneDriver interface implementing
add_connection and delete_connection interfaces.
**Related Flags**
:zone_activate: Used by: class: 'FCZoneDriver'. Defaults to True
:zone_name_prefix: Used by: class: 'FCZoneDriver'. Defaults to 'openstack'
"""
from oslo_concurrency import lockutils
from oslo_config import cfg
from oslo_log import log as logging
from oslo_utils import excutils
from oslo_utils import importutils
import six
import string
from cinder import exception
from cinder.i18n import _
from cinder import interface
from cinder.zonemanager.drivers.cisco import cisco_fabric_opts as fabric_opts
from cinder.zonemanager.drivers.cisco import fc_zone_constants as ZoneConstant
from cinder.zonemanager.drivers import driver_utils
from cinder.zonemanager.drivers import fc_zone_driver
from cinder.zonemanager import utils as zm_utils
LOG = logging.getLogger(__name__)
SUPPORTED_CHARS = string.ascii_letters + string.digits + '$' + '-' + '^' + '_'
cisco_opts = [
cfg.StrOpt('cisco_sb_connector',
default='cinder.zonemanager.drivers.cisco'
'.cisco_fc_zone_client_cli.CiscoFCZoneClientCLI',
help='Southbound connector for zoning operation'),
]
CONF = cfg.CONF
CONF.register_opts(cisco_opts, group='fc-zone-manager')
@interface.fczmdriver
class CiscoFCZoneDriver(fc_zone_driver.FCZoneDriver):
"""Cisco FC zone driver implementation.
OpenStack Fibre Channel zone driver to manage FC zoning in
Cisco SAN fabrics.
Version history:
1.0 - Initial Cisco FC zone driver
1.1 - Added friendly zone name support
"""
VERSION = "1.1.0"
# ThirdPartySystems wiki name
CI_WIKI_NAME = "Cisco_ZM_CI"
# TODO(jsbryant) Remove driver in Rocky if CI is not fixed
SUPPORTED = False
def __init__(self, **kwargs):
super(CiscoFCZoneDriver, self).__init__(**kwargs)
self.configuration = kwargs.get('configuration', None)
if self.configuration:
self.configuration.append_config_values(cisco_opts)
# Adding a hack to handle parameters from super classes
# in case configured with multi backends.
fabric_names = self.configuration.safe_get('fc_fabric_names')
activate = self.configuration.safe_get('cisco_zone_activate')
prefix = self.configuration.safe_get('cisco_zone_name_prefix')
base_san_opts = []
if not fabric_names:
base_san_opts.append(
cfg.StrOpt('fc_fabric_names',
help='Comma separated list of fibre channel '
'fabric names. This list of names is used to'
' retrieve other SAN credentials for connecting'
' to each SAN fabric'
))
if not activate:
base_san_opts.append(
cfg.BoolOpt('cisco_zone_activate',
default=True,
help='Indicates whether zone should '
'be activated or not'))
if not prefix:
base_san_opts.append(
cfg.StrOpt('cisco_zone_name_prefix',
default="openstack",
help="A prefix to be used when naming zone"))
if len(base_san_opts) > 0:
CONF.register_opts(base_san_opts)
self.configuration.append_config_values(base_san_opts)
fabric_names = [x.strip() for x in self.
configuration.fc_fabric_names.split(',')]
# There can be more than one SAN in the network and we need to
# get credentials for each SAN.
if fabric_names:
self.fabric_configs = fabric_opts.load_fabric_configurations(
fabric_names)
@lockutils.synchronized('cisco', 'fcfabric-', True)
def add_connection(self, fabric, initiator_target_map, host_name=None,
storage_system=None):
"""Concrete implementation of add_connection.
Based on zoning policy and state of each I-T pair, list of zone
members are created and pushed to the fabric to add zones. The
new zones created or zones updated are activated based on isActivate
flag set in cinder.conf returned by volume driver after attach
operation.
:param fabric: Fabric name from cinder.conf file
:param initiator_target_map: Mapping of initiator to list of targets
"""
LOG.debug("Add connection for Fabric: %s", fabric)
LOG.info("CiscoFCZoneDriver - Add connection "
"for I-T map: %s", initiator_target_map)
fabric_ip = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_address')
fabric_user = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_user')
fabric_pwd = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_password')
fabric_port = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_port')
zoning_policy = self.configuration.zoning_policy
zoning_policy_fab = self.fabric_configs[fabric].safe_get(
'cisco_zoning_policy')
if zoning_policy_fab:
zoning_policy = zoning_policy_fab
zoning_vsan = self.fabric_configs[fabric].safe_get('cisco_zoning_vsan')
LOG.info("Zoning policy for Fabric %s", zoning_policy)
statusmap_from_fabric = self.get_zoning_status(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
if statusmap_from_fabric.get('session') == 'none':
cfgmap_from_fabric = self.get_active_zone_set(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
zone_names = []
if cfgmap_from_fabric.get('zones'):
zone_names = cfgmap_from_fabric['zones'].keys()
# based on zoning policy, create zone member list and
# push changes to fabric.
for initiator_key in initiator_target_map.keys():
zone_map = {}
zone_update_map = {}
initiator = initiator_key.lower()
t_list = initiator_target_map[initiator_key]
if zoning_policy == 'initiator-target':
for t in t_list:
target = t.lower()
zone_members = [
zm_utils.get_formatted_wwn(initiator),
zm_utils.get_formatted_wwn(target)]
zone_name = (
driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS))
if (len(cfgmap_from_fabric) == 0 or (
zone_name not in zone_names)):
zone_map[zone_name] = zone_members
else:
# This is I-T zoning, skip if zone exists.
LOG.info("Zone exists in I-T mode. "
"Skipping zone creation %s",
zone_name)
elif zoning_policy == 'initiator':
zone_members = [
zm_utils.get_formatted_wwn(initiator)]
for t in t_list:
target = t.lower()
zone_members.append(
zm_utils.get_formatted_wwn(target))
zone_name = (
driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS))
# If zone exists, then perform an update_zone and add
# new members into existing zone.
if zone_name and (zone_name in zone_names):
zone_members = filter(
lambda x: x not in
cfgmap_from_fabric['zones'][zone_name],
zone_members)
if zone_members:
zone_update_map[zone_name] = zone_members
else:
zone_map[zone_name] = zone_members
else:
msg = _("Zoning Policy: %s, not"
" recognized") % zoning_policy
LOG.error(msg)
raise exception.FCZoneDriverException(msg)
LOG.info("Zone map to add: %(zone_map)s",
{'zone_map': zone_map})
LOG.info("Zone map to update add: %(zone_update_map)s",
{'zone_update_map': zone_update_map})
if zone_map or zone_update_map:
conn = None
try:
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip,
username=fabric_user,
password=<PASSWORD>,
port=fabric_port,
vsan=zoning_vsan)
if zone_map:
conn.add_zones(
zone_map,
self.configuration.cisco_zone_activate,
zoning_vsan, cfgmap_from_fabric,
statusmap_from_fabric)
if zone_update_map:
conn.update_zones(
zone_update_map,
self.configuration.cisco_zone_activate,
zoning_vsan, ZoneConstant.ZONE_ADD,
cfgmap_from_fabric,
statusmap_from_fabric)
conn.cleanup()
except exception.CiscoZoningCliException as cisco_ex:
msg = _("Exception: %s") % six.text_type(cisco_ex)
raise exception.FCZoneDriverException(msg)
except Exception:
msg = _("Failed to add zoning configuration.")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Zones added successfully: %s", zone_map)
else:
LOG.debug("Zones already exist - Initiator Target Map: %s",
initiator_target_map)
else:
LOG.debug("Zoning session exists VSAN: %s", zoning_vsan)
@lockutils.synchronized('cisco', 'fcfabric-', True)
def delete_connection(self, fabric, initiator_target_map, host_name=None,
storage_system=None):
"""Concrete implementation of delete_connection.
Based on zoning policy and state of each I-T pair, list of zones
are created for deletion. The zones are either updated deleted based
on the policy and attach/detach state of each I-T pair.
:param fabric: Fabric name from cinder.conf file
:param initiator_target_map: Mapping of initiator to list of targets
"""
LOG.debug("Delete connection for fabric: %s", fabric)
LOG.info("CiscoFCZoneDriver - Delete connection for I-T map: %s",
initiator_target_map)
fabric_ip = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_address')
fabric_user = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_user')
fabric_pwd = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_password')
fabric_port = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_port')
zoning_policy = self.configuration.zoning_policy
zoning_policy_fab = self.fabric_configs[fabric].safe_get(
'cisco_zoning_policy')
if zoning_policy_fab:
zoning_policy = zoning_policy_fab
zoning_vsan = self.fabric_configs[fabric].safe_get('cisco_zoning_vsan')
LOG.info("Zoning policy for fabric %s", zoning_policy)
statusmap_from_fabric = self.get_zoning_status(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
if statusmap_from_fabric.get('session') == 'none':
cfgmap_from_fabric = self.get_active_zone_set(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
zone_names = []
if cfgmap_from_fabric.get('zones'):
zone_names = cfgmap_from_fabric['zones'].keys()
# Based on zoning policy, get zone member list and push
# changes to fabric. This operation could result in an update
# for zone config with new member list or deleting zones from
# active cfg.
LOG.debug("zone config from Fabric: %s", cfgmap_from_fabric)
for initiator_key in initiator_target_map.keys():
initiator = initiator_key.lower()
formatted_initiator = zm_utils.get_formatted_wwn(initiator)
zone_update_map = {}
zones_to_delete = []
t_list = initiator_target_map[initiator_key]
if zoning_policy == 'initiator-target':
# In this case, zone needs to be deleted.
for t in t_list:
target = t.lower()
zone_name = (
driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS))
LOG.debug("Zone name to del: %s", zone_name)
if (len(zone_names) > 0 and (zone_name in zone_names)):
# delete zone.
LOG.debug("Added zone to delete to list: %s",
zone_name)
zones_to_delete.append(zone_name)
elif zoning_policy == 'initiator':
zone_members = [formatted_initiator]
for t in t_list:
target = t.lower()
zone_members.append(
zm_utils.get_formatted_wwn(target))
zone_name = driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS)
# Check if there are zone members leftover after removal
if (zone_names and (zone_name in zone_names)):
filtered_members = filter(
lambda x: x not in zone_members,
cfgmap_from_fabric['zones'][zone_name])
# The assumption here is that initiator is always
# there in the zone as it is 'initiator' policy.
# If filtered list is empty, we remove that zone.
# If there are other members leftover, then perform
# update_zone to remove targets
LOG.debug("Zone delete - I mode: filtered targets: %s",
filtered_members)
if filtered_members:
remove_members = filter(
lambda x: x in
cfgmap_from_fabric['zones'][zone_name],
zone_members)
if remove_members:
# Do not want to remove the initiator
remove_members.remove(formatted_initiator)
LOG.debug("Zone members to remove: %s",
remove_members)
zone_update_map[zone_name] = remove_members
LOG.debug("Filtered zone Map to update: %s",
zone_update_map)
else:
zones_to_delete.append(zone_name)
else:
LOG.info("Zoning Policy: %s, not recognized",
zoning_policy)
LOG.debug("Zone map to remove update: %s", zone_update_map)
LOG.debug("Final Zone list to delete: %s", zones_to_delete)
conn = None
try:
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip,
username=fabric_user,
password=<PASSWORD>,
port=fabric_port,
vsan=zoning_vsan)
# Update zone membership.
if zone_update_map:
conn.update_zones(
zone_update_map,
self.configuration.cisco_zone_activate,
zoning_vsan, ZoneConstant.ZONE_REMOVE,
cfgmap_from_fabric, statusmap_from_fabric)
# Delete zones ~sk.
if zones_to_delete:
zone_name_string = ''
num_zones = len(zones_to_delete)
for i in range(0, num_zones):
if i == 0:
zone_name_string = ('%s%s' % (
zone_name_string,
zones_to_delete[i]))
else:
zone_name_string = ('%s%s%s' % (
zone_name_string, ';',
zones_to_delete[i]))
conn.delete_zones(zone_name_string,
self.configuration.
cisco_zone_activate,
zoning_vsan, cfgmap_from_fabric,
statusmap_from_fabric)
conn.cleanup()
except Exception:
msg = _("Failed to update or delete zoning configuration")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Zones deleted successfully: %s", zone_update_map)
else:
LOG.debug("Zoning session exists VSAN: %s", zoning_vsan)
def get_san_context(self, target_wwn_list):
"""Lookup SAN context for visible end devices.
Look up each SAN configured and return a map of SAN (fabric IP) to
list of target WWNs visible to the fabric.
"""
formatted_target_list = []
fabric_map = {}
fabrics = [x.strip() for x in self.
configuration.fc_fabric_names.split(',')]
LOG.debug("Fabric List: %s", fabrics)
LOG.debug("Target wwn List: %s", target_wwn_list)
if len(fabrics) > 0:
for t in target_wwn_list:
formatted_target_list.append(
zm_utils.get_formatted_wwn(t.lower()))
LOG.debug("Formatted Target wwn List: %s", formatted_target_list)
for fabric_name in fabrics:
fabric_ip = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_address')
fabric_user = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_user')
fabric_pwd = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_password')
fabric_port = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_port')
zoning_vsan = self.fabric_configs[fabric_name].safe_get(
'cisco_zoning_vsan')
# Get name server data from fabric and get the targets
# logged in.
nsinfo = None
try:
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip,
username=fabric_user,
password=<PASSWORD>, port=fabric_port,
vsan=zoning_vsan)
nsinfo = conn.get_nameserver_info()
LOG.debug("show fcns database info from fabric: %s",
nsinfo)
conn.cleanup()
except exception.CiscoZoningCliException:
with excutils.save_and_reraise_exception():
LOG.exception("Error getting show fcns database info.")
except Exception:
msg = _("Failed to get show fcns database info.")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
visible_targets = filter(
lambda x: x in formatted_target_list, nsinfo)
if visible_targets:
LOG.info("Filtered targets for SAN is: %s",
{fabric_name: visible_targets})
# getting rid of the ':' before returning
for idx, elem in enumerate(visible_targets):
visible_targets[idx] = six.text_type(
visible_targets[idx]).replace(':', '')
fabric_map[fabric_name] = visible_targets
else:
LOG.debug("No targets are in the fcns info for SAN %s",
fabric_name)
LOG.debug("Return SAN context output: %s", fabric_map)
return fabric_map
def get_active_zone_set(self, fabric_ip,
fabric_user, fabric_pwd, fabric_port,
zoning_vsan):
"""Gets active zoneset config for vsan."""
cfgmap = {}
conn = None
try:
LOG.debug("Southbound connector: %s",
self.configuration.cisco_sb_connector)
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip, username=fabric_user,
password=<PASSWORD>, port=fabric_port, vsan=zoning_vsan)
cfgmap = conn.get_active_zone_set()
conn.cleanup()
except Exception:
msg = _("Failed to access active zoning configuration.")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Active zone set from fabric: %s", cfgmap)
return cfgmap
def get_zoning_status(self, fabric_ip, fabric_user, fabric_pwd,
fabric_port, zoning_vsan):
"""Gets zoneset status and mode."""
statusmap = {}
conn = None
try:
LOG.debug("Southbound connector: %s",
self.configuration.cisco_sb_connector)
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip, username=fabric_user,
password=<PASSWORD>, port=fabric_port, vsan=zoning_vsan)
statusmap = conn.get_zoning_status()
conn.cleanup()
except Exception:
msg = _("Failed to access zoneset status:%s")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Zoneset status from fabric: %s", statusmap)
return statusmap
|
<filename>cinder/zonemanager/drivers/cisco/cisco_fc_zone_driver.py<gh_stars>0
# (c) Copyright 2014 Cisco Systems Inc.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
"""
Cisco Zone Driver is responsible to manage access control using FC zoning
for Cisco FC fabrics.
This is a concrete implementation of FCZoneDriver interface implementing
add_connection and delete_connection interfaces.
**Related Flags**
:zone_activate: Used by: class: 'FCZoneDriver'. Defaults to True
:zone_name_prefix: Used by: class: 'FCZoneDriver'. Defaults to 'openstack'
"""
from oslo_concurrency import lockutils
from oslo_config import cfg
from oslo_log import log as logging
from oslo_utils import excutils
from oslo_utils import importutils
import six
import string
from cinder import exception
from cinder.i18n import _
from cinder import interface
from cinder.zonemanager.drivers.cisco import cisco_fabric_opts as fabric_opts
from cinder.zonemanager.drivers.cisco import fc_zone_constants as ZoneConstant
from cinder.zonemanager.drivers import driver_utils
from cinder.zonemanager.drivers import fc_zone_driver
from cinder.zonemanager import utils as zm_utils
LOG = logging.getLogger(__name__)
SUPPORTED_CHARS = string.ascii_letters + string.digits + '$' + '-' + '^' + '_'
cisco_opts = [
cfg.StrOpt('cisco_sb_connector',
default='cinder.zonemanager.drivers.cisco'
'.cisco_fc_zone_client_cli.CiscoFCZoneClientCLI',
help='Southbound connector for zoning operation'),
]
CONF = cfg.CONF
CONF.register_opts(cisco_opts, group='fc-zone-manager')
@interface.fczmdriver
class CiscoFCZoneDriver(fc_zone_driver.FCZoneDriver):
"""Cisco FC zone driver implementation.
OpenStack Fibre Channel zone driver to manage FC zoning in
Cisco SAN fabrics.
Version history:
1.0 - Initial Cisco FC zone driver
1.1 - Added friendly zone name support
"""
VERSION = "1.1.0"
# ThirdPartySystems wiki name
CI_WIKI_NAME = "Cisco_ZM_CI"
# TODO(jsbryant) Remove driver in Rocky if CI is not fixed
SUPPORTED = False
def __init__(self, **kwargs):
super(CiscoFCZoneDriver, self).__init__(**kwargs)
self.configuration = kwargs.get('configuration', None)
if self.configuration:
self.configuration.append_config_values(cisco_opts)
# Adding a hack to handle parameters from super classes
# in case configured with multi backends.
fabric_names = self.configuration.safe_get('fc_fabric_names')
activate = self.configuration.safe_get('cisco_zone_activate')
prefix = self.configuration.safe_get('cisco_zone_name_prefix')
base_san_opts = []
if not fabric_names:
base_san_opts.append(
cfg.StrOpt('fc_fabric_names',
help='Comma separated list of fibre channel '
'fabric names. This list of names is used to'
' retrieve other SAN credentials for connecting'
' to each SAN fabric'
))
if not activate:
base_san_opts.append(
cfg.BoolOpt('cisco_zone_activate',
default=True,
help='Indicates whether zone should '
'be activated or not'))
if not prefix:
base_san_opts.append(
cfg.StrOpt('cisco_zone_name_prefix',
default="openstack",
help="A prefix to be used when naming zone"))
if len(base_san_opts) > 0:
CONF.register_opts(base_san_opts)
self.configuration.append_config_values(base_san_opts)
fabric_names = [x.strip() for x in self.
configuration.fc_fabric_names.split(',')]
# There can be more than one SAN in the network and we need to
# get credentials for each SAN.
if fabric_names:
self.fabric_configs = fabric_opts.load_fabric_configurations(
fabric_names)
@lockutils.synchronized('cisco', 'fcfabric-', True)
def add_connection(self, fabric, initiator_target_map, host_name=None,
storage_system=None):
"""Concrete implementation of add_connection.
Based on zoning policy and state of each I-T pair, list of zone
members are created and pushed to the fabric to add zones. The
new zones created or zones updated are activated based on isActivate
flag set in cinder.conf returned by volume driver after attach
operation.
:param fabric: Fabric name from cinder.conf file
:param initiator_target_map: Mapping of initiator to list of targets
"""
LOG.debug("Add connection for Fabric: %s", fabric)
LOG.info("CiscoFCZoneDriver - Add connection "
"for I-T map: %s", initiator_target_map)
fabric_ip = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_address')
fabric_user = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_user')
fabric_pwd = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_password')
fabric_port = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_port')
zoning_policy = self.configuration.zoning_policy
zoning_policy_fab = self.fabric_configs[fabric].safe_get(
'cisco_zoning_policy')
if zoning_policy_fab:
zoning_policy = zoning_policy_fab
zoning_vsan = self.fabric_configs[fabric].safe_get('cisco_zoning_vsan')
LOG.info("Zoning policy for Fabric %s", zoning_policy)
statusmap_from_fabric = self.get_zoning_status(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
if statusmap_from_fabric.get('session') == 'none':
cfgmap_from_fabric = self.get_active_zone_set(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
zone_names = []
if cfgmap_from_fabric.get('zones'):
zone_names = cfgmap_from_fabric['zones'].keys()
# based on zoning policy, create zone member list and
# push changes to fabric.
for initiator_key in initiator_target_map.keys():
zone_map = {}
zone_update_map = {}
initiator = initiator_key.lower()
t_list = initiator_target_map[initiator_key]
if zoning_policy == 'initiator-target':
for t in t_list:
target = t.lower()
zone_members = [
zm_utils.get_formatted_wwn(initiator),
zm_utils.get_formatted_wwn(target)]
zone_name = (
driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS))
if (len(cfgmap_from_fabric) == 0 or (
zone_name not in zone_names)):
zone_map[zone_name] = zone_members
else:
# This is I-T zoning, skip if zone exists.
LOG.info("Zone exists in I-T mode. "
"Skipping zone creation %s",
zone_name)
elif zoning_policy == 'initiator':
zone_members = [
zm_utils.get_formatted_wwn(initiator)]
for t in t_list:
target = t.lower()
zone_members.append(
zm_utils.get_formatted_wwn(target))
zone_name = (
driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS))
# If zone exists, then perform an update_zone and add
# new members into existing zone.
if zone_name and (zone_name in zone_names):
zone_members = filter(
lambda x: x not in
cfgmap_from_fabric['zones'][zone_name],
zone_members)
if zone_members:
zone_update_map[zone_name] = zone_members
else:
zone_map[zone_name] = zone_members
else:
msg = _("Zoning Policy: %s, not"
" recognized") % zoning_policy
LOG.error(msg)
raise exception.FCZoneDriverException(msg)
LOG.info("Zone map to add: %(zone_map)s",
{'zone_map': zone_map})
LOG.info("Zone map to update add: %(zone_update_map)s",
{'zone_update_map': zone_update_map})
if zone_map or zone_update_map:
conn = None
try:
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip,
username=fabric_user,
password=<PASSWORD>,
port=fabric_port,
vsan=zoning_vsan)
if zone_map:
conn.add_zones(
zone_map,
self.configuration.cisco_zone_activate,
zoning_vsan, cfgmap_from_fabric,
statusmap_from_fabric)
if zone_update_map:
conn.update_zones(
zone_update_map,
self.configuration.cisco_zone_activate,
zoning_vsan, ZoneConstant.ZONE_ADD,
cfgmap_from_fabric,
statusmap_from_fabric)
conn.cleanup()
except exception.CiscoZoningCliException as cisco_ex:
msg = _("Exception: %s") % six.text_type(cisco_ex)
raise exception.FCZoneDriverException(msg)
except Exception:
msg = _("Failed to add zoning configuration.")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Zones added successfully: %s", zone_map)
else:
LOG.debug("Zones already exist - Initiator Target Map: %s",
initiator_target_map)
else:
LOG.debug("Zoning session exists VSAN: %s", zoning_vsan)
@lockutils.synchronized('cisco', 'fcfabric-', True)
def delete_connection(self, fabric, initiator_target_map, host_name=None,
storage_system=None):
"""Concrete implementation of delete_connection.
Based on zoning policy and state of each I-T pair, list of zones
are created for deletion. The zones are either updated deleted based
on the policy and attach/detach state of each I-T pair.
:param fabric: Fabric name from cinder.conf file
:param initiator_target_map: Mapping of initiator to list of targets
"""
LOG.debug("Delete connection for fabric: %s", fabric)
LOG.info("CiscoFCZoneDriver - Delete connection for I-T map: %s",
initiator_target_map)
fabric_ip = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_address')
fabric_user = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_user')
fabric_pwd = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_password')
fabric_port = self.fabric_configs[fabric].safe_get(
'cisco_fc_fabric_port')
zoning_policy = self.configuration.zoning_policy
zoning_policy_fab = self.fabric_configs[fabric].safe_get(
'cisco_zoning_policy')
if zoning_policy_fab:
zoning_policy = zoning_policy_fab
zoning_vsan = self.fabric_configs[fabric].safe_get('cisco_zoning_vsan')
LOG.info("Zoning policy for fabric %s", zoning_policy)
statusmap_from_fabric = self.get_zoning_status(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
if statusmap_from_fabric.get('session') == 'none':
cfgmap_from_fabric = self.get_active_zone_set(
fabric_ip, fabric_user, fabric_pwd, fabric_port, zoning_vsan)
zone_names = []
if cfgmap_from_fabric.get('zones'):
zone_names = cfgmap_from_fabric['zones'].keys()
# Based on zoning policy, get zone member list and push
# changes to fabric. This operation could result in an update
# for zone config with new member list or deleting zones from
# active cfg.
LOG.debug("zone config from Fabric: %s", cfgmap_from_fabric)
for initiator_key in initiator_target_map.keys():
initiator = initiator_key.lower()
formatted_initiator = zm_utils.get_formatted_wwn(initiator)
zone_update_map = {}
zones_to_delete = []
t_list = initiator_target_map[initiator_key]
if zoning_policy == 'initiator-target':
# In this case, zone needs to be deleted.
for t in t_list:
target = t.lower()
zone_name = (
driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS))
LOG.debug("Zone name to del: %s", zone_name)
if (len(zone_names) > 0 and (zone_name in zone_names)):
# delete zone.
LOG.debug("Added zone to delete to list: %s",
zone_name)
zones_to_delete.append(zone_name)
elif zoning_policy == 'initiator':
zone_members = [formatted_initiator]
for t in t_list:
target = t.lower()
zone_members.append(
zm_utils.get_formatted_wwn(target))
zone_name = driver_utils.get_friendly_zone_name(
zoning_policy,
initiator,
target,
host_name,
storage_system,
self.configuration.cisco_zone_name_prefix,
SUPPORTED_CHARS)
# Check if there are zone members leftover after removal
if (zone_names and (zone_name in zone_names)):
filtered_members = filter(
lambda x: x not in zone_members,
cfgmap_from_fabric['zones'][zone_name])
# The assumption here is that initiator is always
# there in the zone as it is 'initiator' policy.
# If filtered list is empty, we remove that zone.
# If there are other members leftover, then perform
# update_zone to remove targets
LOG.debug("Zone delete - I mode: filtered targets: %s",
filtered_members)
if filtered_members:
remove_members = filter(
lambda x: x in
cfgmap_from_fabric['zones'][zone_name],
zone_members)
if remove_members:
# Do not want to remove the initiator
remove_members.remove(formatted_initiator)
LOG.debug("Zone members to remove: %s",
remove_members)
zone_update_map[zone_name] = remove_members
LOG.debug("Filtered zone Map to update: %s",
zone_update_map)
else:
zones_to_delete.append(zone_name)
else:
LOG.info("Zoning Policy: %s, not recognized",
zoning_policy)
LOG.debug("Zone map to remove update: %s", zone_update_map)
LOG.debug("Final Zone list to delete: %s", zones_to_delete)
conn = None
try:
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip,
username=fabric_user,
password=<PASSWORD>,
port=fabric_port,
vsan=zoning_vsan)
# Update zone membership.
if zone_update_map:
conn.update_zones(
zone_update_map,
self.configuration.cisco_zone_activate,
zoning_vsan, ZoneConstant.ZONE_REMOVE,
cfgmap_from_fabric, statusmap_from_fabric)
# Delete zones ~sk.
if zones_to_delete:
zone_name_string = ''
num_zones = len(zones_to_delete)
for i in range(0, num_zones):
if i == 0:
zone_name_string = ('%s%s' % (
zone_name_string,
zones_to_delete[i]))
else:
zone_name_string = ('%s%s%s' % (
zone_name_string, ';',
zones_to_delete[i]))
conn.delete_zones(zone_name_string,
self.configuration.
cisco_zone_activate,
zoning_vsan, cfgmap_from_fabric,
statusmap_from_fabric)
conn.cleanup()
except Exception:
msg = _("Failed to update or delete zoning configuration")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Zones deleted successfully: %s", zone_update_map)
else:
LOG.debug("Zoning session exists VSAN: %s", zoning_vsan)
def get_san_context(self, target_wwn_list):
"""Lookup SAN context for visible end devices.
Look up each SAN configured and return a map of SAN (fabric IP) to
list of target WWNs visible to the fabric.
"""
formatted_target_list = []
fabric_map = {}
fabrics = [x.strip() for x in self.
configuration.fc_fabric_names.split(',')]
LOG.debug("Fabric List: %s", fabrics)
LOG.debug("Target wwn List: %s", target_wwn_list)
if len(fabrics) > 0:
for t in target_wwn_list:
formatted_target_list.append(
zm_utils.get_formatted_wwn(t.lower()))
LOG.debug("Formatted Target wwn List: %s", formatted_target_list)
for fabric_name in fabrics:
fabric_ip = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_address')
fabric_user = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_user')
fabric_pwd = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_password')
fabric_port = self.fabric_configs[fabric_name].safe_get(
'cisco_fc_fabric_port')
zoning_vsan = self.fabric_configs[fabric_name].safe_get(
'cisco_zoning_vsan')
# Get name server data from fabric and get the targets
# logged in.
nsinfo = None
try:
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip,
username=fabric_user,
password=<PASSWORD>, port=fabric_port,
vsan=zoning_vsan)
nsinfo = conn.get_nameserver_info()
LOG.debug("show fcns database info from fabric: %s",
nsinfo)
conn.cleanup()
except exception.CiscoZoningCliException:
with excutils.save_and_reraise_exception():
LOG.exception("Error getting show fcns database info.")
except Exception:
msg = _("Failed to get show fcns database info.")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
visible_targets = filter(
lambda x: x in formatted_target_list, nsinfo)
if visible_targets:
LOG.info("Filtered targets for SAN is: %s",
{fabric_name: visible_targets})
# getting rid of the ':' before returning
for idx, elem in enumerate(visible_targets):
visible_targets[idx] = six.text_type(
visible_targets[idx]).replace(':', '')
fabric_map[fabric_name] = visible_targets
else:
LOG.debug("No targets are in the fcns info for SAN %s",
fabric_name)
LOG.debug("Return SAN context output: %s", fabric_map)
return fabric_map
def get_active_zone_set(self, fabric_ip,
fabric_user, fabric_pwd, fabric_port,
zoning_vsan):
"""Gets active zoneset config for vsan."""
cfgmap = {}
conn = None
try:
LOG.debug("Southbound connector: %s",
self.configuration.cisco_sb_connector)
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip, username=fabric_user,
password=<PASSWORD>, port=fabric_port, vsan=zoning_vsan)
cfgmap = conn.get_active_zone_set()
conn.cleanup()
except Exception:
msg = _("Failed to access active zoning configuration.")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Active zone set from fabric: %s", cfgmap)
return cfgmap
def get_zoning_status(self, fabric_ip, fabric_user, fabric_pwd,
fabric_port, zoning_vsan):
"""Gets zoneset status and mode."""
statusmap = {}
conn = None
try:
LOG.debug("Southbound connector: %s",
self.configuration.cisco_sb_connector)
conn = importutils.import_object(
self.configuration.cisco_sb_connector,
ipaddress=fabric_ip, username=fabric_user,
password=<PASSWORD>, port=fabric_port, vsan=zoning_vsan)
statusmap = conn.get_zoning_status()
conn.cleanup()
except Exception:
msg = _("Failed to access zoneset status:%s")
LOG.exception(msg)
raise exception.FCZoneDriverException(msg)
LOG.debug("Zoneset status from fabric: %s", statusmap)
return statusmap
|
en
| 0.859524
|
# (c) Copyright 2014 Cisco Systems Inc. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # Cisco Zone Driver is responsible to manage access control using FC zoning for Cisco FC fabrics. This is a concrete implementation of FCZoneDriver interface implementing add_connection and delete_connection interfaces. **Related Flags** :zone_activate: Used by: class: 'FCZoneDriver'. Defaults to True :zone_name_prefix: Used by: class: 'FCZoneDriver'. Defaults to 'openstack' Cisco FC zone driver implementation. OpenStack Fibre Channel zone driver to manage FC zoning in Cisco SAN fabrics. Version history: 1.0 - Initial Cisco FC zone driver 1.1 - Added friendly zone name support # ThirdPartySystems wiki name # TODO(jsbryant) Remove driver in Rocky if CI is not fixed # Adding a hack to handle parameters from super classes # in case configured with multi backends. # There can be more than one SAN in the network and we need to # get credentials for each SAN. Concrete implementation of add_connection. Based on zoning policy and state of each I-T pair, list of zone members are created and pushed to the fabric to add zones. The new zones created or zones updated are activated based on isActivate flag set in cinder.conf returned by volume driver after attach operation. :param fabric: Fabric name from cinder.conf file :param initiator_target_map: Mapping of initiator to list of targets # based on zoning policy, create zone member list and # push changes to fabric. # This is I-T zoning, skip if zone exists. # If zone exists, then perform an update_zone and add # new members into existing zone. Concrete implementation of delete_connection. Based on zoning policy and state of each I-T pair, list of zones are created for deletion. The zones are either updated deleted based on the policy and attach/detach state of each I-T pair. :param fabric: Fabric name from cinder.conf file :param initiator_target_map: Mapping of initiator to list of targets # Based on zoning policy, get zone member list and push # changes to fabric. This operation could result in an update # for zone config with new member list or deleting zones from # active cfg. # In this case, zone needs to be deleted. # delete zone. # Check if there are zone members leftover after removal # The assumption here is that initiator is always # there in the zone as it is 'initiator' policy. # If filtered list is empty, we remove that zone. # If there are other members leftover, then perform # update_zone to remove targets # Do not want to remove the initiator # Update zone membership. # Delete zones ~sk. Lookup SAN context for visible end devices. Look up each SAN configured and return a map of SAN (fabric IP) to list of target WWNs visible to the fabric. # Get name server data from fabric and get the targets # logged in. # getting rid of the ':' before returning Gets active zoneset config for vsan. Gets zoneset status and mode.
| 1.942299
| 2
|
template/_base_typedef_pyi.py
|
Amourspirit/ooo_uno_tmpl
| 0
|
6625773
|
<gh_stars>0
# coding: utf-8
from _base_typedef import BaseTypeDef
from _base_json import EventArgs
class BaseTypeDefPyi(BaseTypeDef):
def on_after_init_data(self, args: EventArgs) -> None:
super().on_after_init_data(args=args)
|
# coding: utf-8
from _base_typedef import BaseTypeDef
from _base_json import EventArgs
class BaseTypeDefPyi(BaseTypeDef):
def on_after_init_data(self, args: EventArgs) -> None:
super().on_after_init_data(args=args)
|
en
| 0.833554
|
# coding: utf-8
| 2.205923
| 2
|
icetray/resources/test/no_such_library.py
|
hschwane/offline_production
| 1
|
6625774
|
#!/usr/bin/env python
from I3Tray import *
tray = I3Tray()
try:
from icecube import no_such_library
tray.AddModule("BottomlessSource")
tray.AddModule("NoSuchModule")
tray.Execute(5)
except:
print("Good. It threw.")
sys.exit(0) # indicate success.
else:
print("should have thrown")
sys.exit(1)
|
#!/usr/bin/env python
from I3Tray import *
tray = I3Tray()
try:
from icecube import no_such_library
tray.AddModule("BottomlessSource")
tray.AddModule("NoSuchModule")
tray.Execute(5)
except:
print("Good. It threw.")
sys.exit(0) # indicate success.
else:
print("should have thrown")
sys.exit(1)
|
en
| 0.378994
|
#!/usr/bin/env python # indicate success.
| 1.968271
| 2
|
data/wordstat.py
|
barzerman/barzer
| 1
|
6625775
|
<reponame>barzerman/barzer
#!/usr/bin/python
# -*- coding: utf-8 -*-
import fileinput,codecs, sys, re
#reads in the file in CLASS|SUBCLASS|ID|name format
#and produces statements
writer = codecs.getwriter('utf-8')(sys.stdout)
reader = codecs.getreader('utf-8')(sys.stdin)
utf8_re=re.compile(u'[^а-яА-Я]+',re.UNICODE)
wordcnt={}
for line in reader:
if len(line)<3:
continue
fld=utf8_re.split(line)
for i in fld:
if len(i)>1 and i[0] != ' ':
if not i in wordcnt:
wordcnt[i]=1
else:
wordcnt[i]+=1
writer = codecs.getwriter('utf-8')(sys.stdout)
#handling capitalized words - discovering proper names
for i in wordcnt:
if len(i)>1 and i[0] != i[0].lower() and i[1] == i[1].lower():
tolc=i
tolc=tolc[0].lower()+tolc[1:]
cnt=wordcnt[i]
if tolc not in wordcnt and cnt>1:
writer.write(i)
print ",",cnt
if False:
for i in wordcnt:
if wordcnt[i]>5:
writer.write(i)
print ",",wordcnt[i]
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
import fileinput,codecs, sys, re
#reads in the file in CLASS|SUBCLASS|ID|name format
#and produces statements
writer = codecs.getwriter('utf-8')(sys.stdout)
reader = codecs.getreader('utf-8')(sys.stdin)
utf8_re=re.compile(u'[^а-яА-Я]+',re.UNICODE)
wordcnt={}
for line in reader:
if len(line)<3:
continue
fld=utf8_re.split(line)
for i in fld:
if len(i)>1 and i[0] != ' ':
if not i in wordcnt:
wordcnt[i]=1
else:
wordcnt[i]+=1
writer = codecs.getwriter('utf-8')(sys.stdout)
#handling capitalized words - discovering proper names
for i in wordcnt:
if len(i)>1 and i[0] != i[0].lower() and i[1] == i[1].lower():
tolc=i
tolc=tolc[0].lower()+tolc[1:]
cnt=wordcnt[i]
if tolc not in wordcnt and cnt>1:
writer.write(i)
print ",",cnt
if False:
for i in wordcnt:
if wordcnt[i]>5:
writer.write(i)
print ",",wordcnt[i]
|
en
| 0.625077
|
#!/usr/bin/python # -*- coding: utf-8 -*- #reads in the file in CLASS|SUBCLASS|ID|name format #and produces statements #handling capitalized words - discovering proper names
| 3.862461
| 4
|
setup.py
|
plaplant/SSINS
| 4
|
6625776
|
from __future__ import absolute_import, division, print_function
from setuptools import setup
import os
import sys
import json
sys.path.append('SSINS')
def package_files(package_dir, subdirectory):
# walk the input package_dir/subdirectory
# return a package_data list
paths = []
directory = os.path.join(package_dir, subdirectory)
for (path, directories, filenames) in os.walk(directory):
for filename in filenames:
path = path.replace(package_dir + '/', '')
paths.append(os.path.join(path, filename))
return paths
data_files = package_files('SSINS', 'data')
setup_args = {
'name': 'SSINS',
'author': '<NAME>',
'url': 'https://github.com/mwilensky768/SSINS',
'license': 'BSD',
'description': 'Sky-Subtracted Incoherent Noise Spectra',
'package_dir': {'SSINS': 'SSINS'},
'packages': ['SSINS'],
'include_package_data': True,
'scripts': ['scripts/Run_HERA_SSINS.py', 'scripts/MWA_EoR_High_Flag.py',
'scripts/MWA_gpubox_to_SSINS_on_Pawsey.sh', 'scripts/MWA_vis_to_SSINS.py',
'scripts/occ_csv.py'],
'package_data': {'SSINS': data_files},
'setup_requires': ['setuptools_scm'],
'use_scm_version': True,
'install_requires': ['pyuvdata', 'h5py', 'pyyaml'],
'zip_safe': False,
}
if __name__ == '__main__':
setup(**setup_args)
|
from __future__ import absolute_import, division, print_function
from setuptools import setup
import os
import sys
import json
sys.path.append('SSINS')
def package_files(package_dir, subdirectory):
# walk the input package_dir/subdirectory
# return a package_data list
paths = []
directory = os.path.join(package_dir, subdirectory)
for (path, directories, filenames) in os.walk(directory):
for filename in filenames:
path = path.replace(package_dir + '/', '')
paths.append(os.path.join(path, filename))
return paths
data_files = package_files('SSINS', 'data')
setup_args = {
'name': 'SSINS',
'author': '<NAME>',
'url': 'https://github.com/mwilensky768/SSINS',
'license': 'BSD',
'description': 'Sky-Subtracted Incoherent Noise Spectra',
'package_dir': {'SSINS': 'SSINS'},
'packages': ['SSINS'],
'include_package_data': True,
'scripts': ['scripts/Run_HERA_SSINS.py', 'scripts/MWA_EoR_High_Flag.py',
'scripts/MWA_gpubox_to_SSINS_on_Pawsey.sh', 'scripts/MWA_vis_to_SSINS.py',
'scripts/occ_csv.py'],
'package_data': {'SSINS': data_files},
'setup_requires': ['setuptools_scm'],
'use_scm_version': True,
'install_requires': ['pyuvdata', 'h5py', 'pyyaml'],
'zip_safe': False,
}
if __name__ == '__main__':
setup(**setup_args)
|
en
| 0.343599
|
# walk the input package_dir/subdirectory # return a package_data list
| 1.949172
| 2
|
ansible/venv/lib/python2.7/site-packages/ansible/module_utils/service_now.py
|
gvashchenkolineate/gvashchenkolineate_infra_trytravis
| 17
|
6625777
|
<filename>ansible/venv/lib/python2.7/site-packages/ansible/module_utils/service_now.py
# -*- coding: utf-8 -*-
# Copyright: (c) 2019, Ansible Project
# Copyright: (c) 2017, <NAME> <<EMAIL>>
# Simplified BSD License (see licenses/simplified_bsd.txt or https://opensource.org/licenses/BSD-2-Clause)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
import traceback
from ansible.module_utils.basic import env_fallback, missing_required_lib
# Pull in pysnow
HAS_PYSNOW = False
PYSNOW_IMP_ERR = None
try:
import pysnow
HAS_PYSNOW = True
except ImportError:
PYSNOW_IMP_ERR = traceback.format_exc()
class ServiceNowClient(object):
def __init__(self, module):
"""
Constructor
"""
if not HAS_PYSNOW:
module.fail_json(msg=missing_required_lib('pysnow'), exception=PYSNOW_IMP_ERR)
self.module = module
self.params = module.params
self.client_id = self.params['client_id']
self.client_secret = self.params['client_secret']
self.username = self.params['username']
self.password = self.params['password']
self.instance = self.params['instance']
self.session = {'token': None}
self.conn = None
def login(self):
result = dict(
changed=False
)
if self.params['client_id'] is not None:
try:
self.conn = pysnow.OAuthClient(client_id=self.client_id,
client_secret=self.client_secret,
token_updater=self.updater,
instance=self.instance)
except Exception as detail:
self.module.fail_json(msg='Could not connect to ServiceNow: {0}'.format(str(detail)), **result)
if not self.session['token']:
# No previous token exists, Generate new.
try:
self.session['token'] = self.conn.generate_token(self.username, self.password)
except pysnow.exceptions.TokenCreateError as detail:
self.module.fail_json(msg='Unable to generate a new token: {0}'.format(str(detail)), **result)
self.conn.set_token(self.session['token'])
elif self.username is not None:
try:
self.conn = pysnow.Client(instance=self.instance,
user=self.username,
password=self.password)
except Exception as detail:
self.module.fail_json(msg='Could not connect to ServiceNow: {0}'.format(str(detail)), **result)
else:
snow_error = "Must specify username/password. Also client_id/client_secret if using OAuth."
self.module.fail_json(msg=snow_error, **result)
def updater(self, new_token):
self.session['token'] = new_token
self.conn = pysnow.OAuthClient(client_id=self.client_id,
client_secret=self.client_secret,
token_updater=self.updater,
instance=self.instance)
try:
self.conn.set_token(self.session['token'])
except pysnow.exceptions.MissingToken:
snow_error = "Token is missing"
self.module.fail_json(msg=snow_error)
except Exception as detail:
self.module.fail_json(msg='Could not refresh token: {0}'.format(str(detail)))
@staticmethod
def snow_argument_spec():
return dict(
instance=dict(type='str', required=False, fallback=(env_fallback, ['SN_INSTANCE'])),
username=dict(type='str', required=False, fallback=(env_fallback, ['SN_USERNAME'])),
password=dict(type='str', required=False, no_log=True, fallback=(env_fallback, ['SN_PASSWORD'])),
client_id=dict(type='str', no_log=True),
client_secret=dict(type='str', no_log=True),
)
|
<filename>ansible/venv/lib/python2.7/site-packages/ansible/module_utils/service_now.py
# -*- coding: utf-8 -*-
# Copyright: (c) 2019, Ansible Project
# Copyright: (c) 2017, <NAME> <<EMAIL>>
# Simplified BSD License (see licenses/simplified_bsd.txt or https://opensource.org/licenses/BSD-2-Clause)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
import traceback
from ansible.module_utils.basic import env_fallback, missing_required_lib
# Pull in pysnow
HAS_PYSNOW = False
PYSNOW_IMP_ERR = None
try:
import pysnow
HAS_PYSNOW = True
except ImportError:
PYSNOW_IMP_ERR = traceback.format_exc()
class ServiceNowClient(object):
def __init__(self, module):
"""
Constructor
"""
if not HAS_PYSNOW:
module.fail_json(msg=missing_required_lib('pysnow'), exception=PYSNOW_IMP_ERR)
self.module = module
self.params = module.params
self.client_id = self.params['client_id']
self.client_secret = self.params['client_secret']
self.username = self.params['username']
self.password = self.params['password']
self.instance = self.params['instance']
self.session = {'token': None}
self.conn = None
def login(self):
result = dict(
changed=False
)
if self.params['client_id'] is not None:
try:
self.conn = pysnow.OAuthClient(client_id=self.client_id,
client_secret=self.client_secret,
token_updater=self.updater,
instance=self.instance)
except Exception as detail:
self.module.fail_json(msg='Could not connect to ServiceNow: {0}'.format(str(detail)), **result)
if not self.session['token']:
# No previous token exists, Generate new.
try:
self.session['token'] = self.conn.generate_token(self.username, self.password)
except pysnow.exceptions.TokenCreateError as detail:
self.module.fail_json(msg='Unable to generate a new token: {0}'.format(str(detail)), **result)
self.conn.set_token(self.session['token'])
elif self.username is not None:
try:
self.conn = pysnow.Client(instance=self.instance,
user=self.username,
password=self.password)
except Exception as detail:
self.module.fail_json(msg='Could not connect to ServiceNow: {0}'.format(str(detail)), **result)
else:
snow_error = "Must specify username/password. Also client_id/client_secret if using OAuth."
self.module.fail_json(msg=snow_error, **result)
def updater(self, new_token):
self.session['token'] = new_token
self.conn = pysnow.OAuthClient(client_id=self.client_id,
client_secret=self.client_secret,
token_updater=self.updater,
instance=self.instance)
try:
self.conn.set_token(self.session['token'])
except pysnow.exceptions.MissingToken:
snow_error = "Token is missing"
self.module.fail_json(msg=snow_error)
except Exception as detail:
self.module.fail_json(msg='Could not refresh token: {0}'.format(str(detail)))
@staticmethod
def snow_argument_spec():
return dict(
instance=dict(type='str', required=False, fallback=(env_fallback, ['SN_INSTANCE'])),
username=dict(type='str', required=False, fallback=(env_fallback, ['SN_USERNAME'])),
password=dict(type='str', required=False, no_log=True, fallback=(env_fallback, ['SN_PASSWORD'])),
client_id=dict(type='str', no_log=True),
client_secret=dict(type='str', no_log=True),
)
|
en
| 0.680558
|
# -*- coding: utf-8 -*- # Copyright: (c) 2019, Ansible Project # Copyright: (c) 2017, <NAME> <<EMAIL>> # Simplified BSD License (see licenses/simplified_bsd.txt or https://opensource.org/licenses/BSD-2-Clause) # Pull in pysnow Constructor # No previous token exists, Generate new.
| 2.025828
| 2
|
housekeeping/urls.py
|
aptivate/Arkestra
| 1
|
6625778
|
from django.conf.urls.defaults import *
from django.contrib import admin
urlpatterns = patterns('',
(r"^housekeeping/statistics/", "housekeeping.statistics.stats"),
# /housekeeping/repair_mptt/contacts_and_people.Entity/
(r"^housekeeping/repair_mptt/(?P<slug>[-\w\.]+)/$", "housekeeping.repair_mptt.fix"),
# then, try to match /housekeeping/<task>/<execute>
(r"^housekeeping/(?P<task>[^/]+)/(?P<action>[^/]+)/$", "housekeeping.tasks.tasks"),
# # no match?
(r"^housekeeping/", "housekeeping.tasks.tasks"),
# (r"^housekeeping/clean_plugins/", "housekeeping.clean_plugins.clean"),
#
#
# (r"^statistics/user/(?P<slug>[-\w]+)$", "housekeeping.statistics.userstats"),
)
|
from django.conf.urls.defaults import *
from django.contrib import admin
urlpatterns = patterns('',
(r"^housekeeping/statistics/", "housekeeping.statistics.stats"),
# /housekeeping/repair_mptt/contacts_and_people.Entity/
(r"^housekeeping/repair_mptt/(?P<slug>[-\w\.]+)/$", "housekeeping.repair_mptt.fix"),
# then, try to match /housekeeping/<task>/<execute>
(r"^housekeeping/(?P<task>[^/]+)/(?P<action>[^/]+)/$", "housekeeping.tasks.tasks"),
# # no match?
(r"^housekeeping/", "housekeeping.tasks.tasks"),
# (r"^housekeeping/clean_plugins/", "housekeeping.clean_plugins.clean"),
#
#
# (r"^statistics/user/(?P<slug>[-\w]+)$", "housekeeping.statistics.userstats"),
)
|
en
| 0.706029
|
# /housekeeping/repair_mptt/contacts_and_people.Entity/ # then, try to match /housekeeping/<task>/<execute> # # no match? # (r"^housekeeping/clean_plugins/", "housekeeping.clean_plugins.clean"), # # # (r"^statistics/user/(?P<slug>[-\w]+)$", "housekeeping.statistics.userstats"),
| 1.864911
| 2
|
modules/plugin_social_auth/social/apps/cherrypy_app/models.py
|
KallyMilton/w2p-social-auth
| 1
|
6625779
|
"""Flask SQLAlchemy ORM models for Social Auth"""
import cherrypy
from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy.orm import relationship
from sqlalchemy.schema import UniqueConstraint
from sqlalchemy.ext.declarative import declarative_base
from social.utils import setting_name, module_member
from social.storage.sqlalchemy_orm import SQLAlchemyUserMixin, \
SQLAlchemyAssociationMixin, \
SQLAlchemyNonceMixin, \
BaseSQLAlchemyStorage
from social.apps.flask_app.fields import JSONType
SocialBase = declarative_base()
DB_SESSION_ATTR = cherrypy.config.get(setting_name('DB_SESSION_ATTR'), 'db')
UID_LENGTH = cherrypy.config.get(setting_name('UID_LENGTH'), 255)
User = module_member(cherrypy.config[setting_name('USER_MODEL')])
class CherryPySocialBase(object):
@classmethod
def _session(cls):
return getattr(cherrypy.request, DB_SESSION_ATTR)
class UserSocialAuth(CherryPySocialBase, SQLAlchemyUserMixin, SocialBase):
"""Social Auth association model"""
__tablename__ = 'social_auth_usersocialauth'
__table_args__ = (UniqueConstraint('provider', 'uid'),)
id = Column(Integer, primary_key=True)
provider = Column(String(32))
uid = Column(String(UID_LENGTH))
extra_data = Column(JSONType)
user_id = Column(Integer, ForeignKey(User.id),
nullable=False, index=True)
user = relationship(User, backref='social_auth')
@classmethod
def username_max_length(cls):
return User.__table__.columns.get('username').type.length
@classmethod
def user_model(cls):
return User
class Nonce(CherryPySocialBase, SQLAlchemyNonceMixin, SocialBase):
"""One use numbers"""
__tablename__ = 'social_auth_nonce'
__table_args__ = (UniqueConstraint('server_url', 'timestamp', 'salt'),)
id = Column(Integer, primary_key=True)
server_url = Column(String(255))
timestamp = Column(Integer)
salt = Column(String(40))
class Association(CherryPySocialBase, SQLAlchemyAssociationMixin, SocialBase):
"""OpenId account association"""
__tablename__ = 'social_auth_association'
__table_args__ = (UniqueConstraint('server_url', 'handle'),)
id = Column(Integer, primary_key=True)
server_url = Column(String(255))
handle = Column(String(255))
secret = Column(String(255)) # base64 encoded
issued = Column(Integer)
lifetime = Column(Integer)
assoc_type = Column(String(64))
class CherryPyStorage(BaseSQLAlchemyStorage):
user = UserSocialAuth
nonce = Nonce
association = Association
|
"""Flask SQLAlchemy ORM models for Social Auth"""
import cherrypy
from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy.orm import relationship
from sqlalchemy.schema import UniqueConstraint
from sqlalchemy.ext.declarative import declarative_base
from social.utils import setting_name, module_member
from social.storage.sqlalchemy_orm import SQLAlchemyUserMixin, \
SQLAlchemyAssociationMixin, \
SQLAlchemyNonceMixin, \
BaseSQLAlchemyStorage
from social.apps.flask_app.fields import JSONType
SocialBase = declarative_base()
DB_SESSION_ATTR = cherrypy.config.get(setting_name('DB_SESSION_ATTR'), 'db')
UID_LENGTH = cherrypy.config.get(setting_name('UID_LENGTH'), 255)
User = module_member(cherrypy.config[setting_name('USER_MODEL')])
class CherryPySocialBase(object):
@classmethod
def _session(cls):
return getattr(cherrypy.request, DB_SESSION_ATTR)
class UserSocialAuth(CherryPySocialBase, SQLAlchemyUserMixin, SocialBase):
"""Social Auth association model"""
__tablename__ = 'social_auth_usersocialauth'
__table_args__ = (UniqueConstraint('provider', 'uid'),)
id = Column(Integer, primary_key=True)
provider = Column(String(32))
uid = Column(String(UID_LENGTH))
extra_data = Column(JSONType)
user_id = Column(Integer, ForeignKey(User.id),
nullable=False, index=True)
user = relationship(User, backref='social_auth')
@classmethod
def username_max_length(cls):
return User.__table__.columns.get('username').type.length
@classmethod
def user_model(cls):
return User
class Nonce(CherryPySocialBase, SQLAlchemyNonceMixin, SocialBase):
"""One use numbers"""
__tablename__ = 'social_auth_nonce'
__table_args__ = (UniqueConstraint('server_url', 'timestamp', 'salt'),)
id = Column(Integer, primary_key=True)
server_url = Column(String(255))
timestamp = Column(Integer)
salt = Column(String(40))
class Association(CherryPySocialBase, SQLAlchemyAssociationMixin, SocialBase):
"""OpenId account association"""
__tablename__ = 'social_auth_association'
__table_args__ = (UniqueConstraint('server_url', 'handle'),)
id = Column(Integer, primary_key=True)
server_url = Column(String(255))
handle = Column(String(255))
secret = Column(String(255)) # base64 encoded
issued = Column(Integer)
lifetime = Column(Integer)
assoc_type = Column(String(64))
class CherryPyStorage(BaseSQLAlchemyStorage):
user = UserSocialAuth
nonce = Nonce
association = Association
|
en
| 0.673991
|
Flask SQLAlchemy ORM models for Social Auth Social Auth association model One use numbers OpenId account association # base64 encoded
| 2.71294
| 3
|
src/sima/simo/liftlinecoupling.py
|
SINTEF/simapy
| 0
|
6625780
|
<filename>src/sima/simo/liftlinecoupling.py
# This an autogenerated file
#
# Generated with LiftLineCoupling
from __future__ import annotations
from typing import Dict,Sequence,List
from dmt.entity import Entity
from dmt.blueprint import Blueprint
from .blueprints.liftlinecoupling import LiftLineCouplingBlueprint
from typing import Dict
from sima.sima.scriptablevalue import ScriptableValue
from sima.simo.activationfailuremode import ActivationFailureMode
from sima.simo.simplecoupling import SimpleCoupling
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from sima.simo.simobodypoint import SIMOBodyPoint
class LiftLineCoupling(SimpleCoupling):
"""
Keyword arguments
-----------------
name : str
(default "")
description : str
(default "")
_id : str
(default "")
scriptableValues : List[ScriptableValue]
endPoint1 : SIMOBodyPoint
endPoint2 : SIMOBodyPoint
failureMode : ActivationFailureMode
Failure mode of coupling element
failureTime : float
Earliest possible time of failure(default 0.0)
breakingStrength : float
Breaking strength(default 0.0)
numElements : int
Number of elements(default 0)
accIncluded : bool
Flag for including acceleration of the line(default True)
diameter : float
Segment diameter(default 0.0)
eMod : float
Modulus of elasticity(default 0.0)
emFac : int
Factor of elasticity - 2 for chains - 1 for other segment types(default 1)
length : float
Initial, unstretched wire length(default 0.0)
flexibility : float
Connection flexibility(default 0.0)
damping : float
Material damping(default 0.0)
uwia : float
Unit weight in air(default 0.0)
watfac : float
The ratio of weight in water to weight in air(default 0.0)
transverseDrag : float
Transverse drag coefficient(default 0.0)
longitudinalDrag : float
Longitudinal drag coefficient(default 0.0)
"""
def __init__(self , name="", description="", _id="", failureMode=ActivationFailureMode.NONE, failureTime=0.0, breakingStrength=0.0, numElements=0, accIncluded=True, diameter=0.0, eMod=0.0, emFac=1, length=0.0, flexibility=0.0, damping=0.0, uwia=0.0, watfac=0.0, transverseDrag=0.0, longitudinalDrag=0.0, **kwargs):
super().__init__(**kwargs)
self.name = name
self.description = description
self._id = _id
self.scriptableValues = list()
self.endPoint1 = None
self.endPoint2 = None
self.failureMode = failureMode
self.failureTime = failureTime
self.breakingStrength = breakingStrength
self.numElements = numElements
self.accIncluded = accIncluded
self.diameter = diameter
self.eMod = eMod
self.emFac = emFac
self.length = length
self.flexibility = flexibility
self.damping = damping
self.uwia = uwia
self.watfac = watfac
self.transverseDrag = transverseDrag
self.longitudinalDrag = longitudinalDrag
for key, value in kwargs.items():
if not isinstance(value, Dict):
setattr(self, key, value)
@property
def blueprint(self) -> Blueprint:
"""Return blueprint that this entity represents"""
return LiftLineCouplingBlueprint()
@property
def name(self) -> str:
""""""
return self.__name
@name.setter
def name(self, value: str):
"""Set name"""
self.__name = str(value)
@property
def description(self) -> str:
""""""
return self.__description
@description.setter
def description(self, value: str):
"""Set description"""
self.__description = str(value)
@property
def _id(self) -> str:
""""""
return self.___id
@_id.setter
def _id(self, value: str):
"""Set _id"""
self.___id = str(value)
@property
def scriptableValues(self) -> List[ScriptableValue]:
""""""
return self.__scriptableValues
@scriptableValues.setter
def scriptableValues(self, value: List[ScriptableValue]):
"""Set scriptableValues"""
if not isinstance(value, Sequence):
raise Exception("Expected sequense, but was " , type(value))
self.__scriptableValues = value
@property
def endPoint1(self) -> SIMOBodyPoint:
""""""
return self.__endPoint1
@endPoint1.setter
def endPoint1(self, value: SIMOBodyPoint):
"""Set endPoint1"""
self.__endPoint1 = value
@property
def endPoint2(self) -> SIMOBodyPoint:
""""""
return self.__endPoint2
@endPoint2.setter
def endPoint2(self, value: SIMOBodyPoint):
"""Set endPoint2"""
self.__endPoint2 = value
@property
def failureMode(self) -> ActivationFailureMode:
"""Failure mode of coupling element"""
return self.__failureMode
@failureMode.setter
def failureMode(self, value: ActivationFailureMode):
"""Set failureMode"""
self.__failureMode = value
@property
def failureTime(self) -> float:
"""Earliest possible time of failure"""
return self.__failureTime
@failureTime.setter
def failureTime(self, value: float):
"""Set failureTime"""
self.__failureTime = float(value)
@property
def breakingStrength(self) -> float:
"""Breaking strength"""
return self.__breakingStrength
@breakingStrength.setter
def breakingStrength(self, value: float):
"""Set breakingStrength"""
self.__breakingStrength = float(value)
@property
def numElements(self) -> int:
"""Number of elements"""
return self.__numElements
@numElements.setter
def numElements(self, value: int):
"""Set numElements"""
self.__numElements = int(value)
@property
def accIncluded(self) -> bool:
"""Flag for including acceleration of the line"""
return self.__accIncluded
@accIncluded.setter
def accIncluded(self, value: bool):
"""Set accIncluded"""
self.__accIncluded = bool(value)
@property
def diameter(self) -> float:
"""Segment diameter"""
return self.__diameter
@diameter.setter
def diameter(self, value: float):
"""Set diameter"""
self.__diameter = float(value)
@property
def eMod(self) -> float:
"""Modulus of elasticity"""
return self.__eMod
@eMod.setter
def eMod(self, value: float):
"""Set eMod"""
self.__eMod = float(value)
@property
def emFac(self) -> int:
"""Factor of elasticity - 2 for chains - 1 for other segment types"""
return self.__emFac
@emFac.setter
def emFac(self, value: int):
"""Set emFac"""
self.__emFac = int(value)
@property
def length(self) -> float:
"""Initial, unstretched wire length"""
return self.__length
@length.setter
def length(self, value: float):
"""Set length"""
self.__length = float(value)
@property
def flexibility(self) -> float:
"""Connection flexibility"""
return self.__flexibility
@flexibility.setter
def flexibility(self, value: float):
"""Set flexibility"""
self.__flexibility = float(value)
@property
def damping(self) -> float:
"""Material damping"""
return self.__damping
@damping.setter
def damping(self, value: float):
"""Set damping"""
self.__damping = float(value)
@property
def uwia(self) -> float:
"""Unit weight in air"""
return self.__uwia
@uwia.setter
def uwia(self, value: float):
"""Set uwia"""
self.__uwia = float(value)
@property
def watfac(self) -> float:
"""The ratio of weight in water to weight in air"""
return self.__watfac
@watfac.setter
def watfac(self, value: float):
"""Set watfac"""
self.__watfac = float(value)
@property
def transverseDrag(self) -> float:
"""Transverse drag coefficient"""
return self.__transverseDrag
@transverseDrag.setter
def transverseDrag(self, value: float):
"""Set transverseDrag"""
self.__transverseDrag = float(value)
@property
def longitudinalDrag(self) -> float:
"""Longitudinal drag coefficient"""
return self.__longitudinalDrag
@longitudinalDrag.setter
def longitudinalDrag(self, value: float):
"""Set longitudinalDrag"""
self.__longitudinalDrag = float(value)
|
<filename>src/sima/simo/liftlinecoupling.py
# This an autogenerated file
#
# Generated with LiftLineCoupling
from __future__ import annotations
from typing import Dict,Sequence,List
from dmt.entity import Entity
from dmt.blueprint import Blueprint
from .blueprints.liftlinecoupling import LiftLineCouplingBlueprint
from typing import Dict
from sima.sima.scriptablevalue import ScriptableValue
from sima.simo.activationfailuremode import ActivationFailureMode
from sima.simo.simplecoupling import SimpleCoupling
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from sima.simo.simobodypoint import SIMOBodyPoint
class LiftLineCoupling(SimpleCoupling):
"""
Keyword arguments
-----------------
name : str
(default "")
description : str
(default "")
_id : str
(default "")
scriptableValues : List[ScriptableValue]
endPoint1 : SIMOBodyPoint
endPoint2 : SIMOBodyPoint
failureMode : ActivationFailureMode
Failure mode of coupling element
failureTime : float
Earliest possible time of failure(default 0.0)
breakingStrength : float
Breaking strength(default 0.0)
numElements : int
Number of elements(default 0)
accIncluded : bool
Flag for including acceleration of the line(default True)
diameter : float
Segment diameter(default 0.0)
eMod : float
Modulus of elasticity(default 0.0)
emFac : int
Factor of elasticity - 2 for chains - 1 for other segment types(default 1)
length : float
Initial, unstretched wire length(default 0.0)
flexibility : float
Connection flexibility(default 0.0)
damping : float
Material damping(default 0.0)
uwia : float
Unit weight in air(default 0.0)
watfac : float
The ratio of weight in water to weight in air(default 0.0)
transverseDrag : float
Transverse drag coefficient(default 0.0)
longitudinalDrag : float
Longitudinal drag coefficient(default 0.0)
"""
def __init__(self , name="", description="", _id="", failureMode=ActivationFailureMode.NONE, failureTime=0.0, breakingStrength=0.0, numElements=0, accIncluded=True, diameter=0.0, eMod=0.0, emFac=1, length=0.0, flexibility=0.0, damping=0.0, uwia=0.0, watfac=0.0, transverseDrag=0.0, longitudinalDrag=0.0, **kwargs):
super().__init__(**kwargs)
self.name = name
self.description = description
self._id = _id
self.scriptableValues = list()
self.endPoint1 = None
self.endPoint2 = None
self.failureMode = failureMode
self.failureTime = failureTime
self.breakingStrength = breakingStrength
self.numElements = numElements
self.accIncluded = accIncluded
self.diameter = diameter
self.eMod = eMod
self.emFac = emFac
self.length = length
self.flexibility = flexibility
self.damping = damping
self.uwia = uwia
self.watfac = watfac
self.transverseDrag = transverseDrag
self.longitudinalDrag = longitudinalDrag
for key, value in kwargs.items():
if not isinstance(value, Dict):
setattr(self, key, value)
@property
def blueprint(self) -> Blueprint:
"""Return blueprint that this entity represents"""
return LiftLineCouplingBlueprint()
@property
def name(self) -> str:
""""""
return self.__name
@name.setter
def name(self, value: str):
"""Set name"""
self.__name = str(value)
@property
def description(self) -> str:
""""""
return self.__description
@description.setter
def description(self, value: str):
"""Set description"""
self.__description = str(value)
@property
def _id(self) -> str:
""""""
return self.___id
@_id.setter
def _id(self, value: str):
"""Set _id"""
self.___id = str(value)
@property
def scriptableValues(self) -> List[ScriptableValue]:
""""""
return self.__scriptableValues
@scriptableValues.setter
def scriptableValues(self, value: List[ScriptableValue]):
"""Set scriptableValues"""
if not isinstance(value, Sequence):
raise Exception("Expected sequense, but was " , type(value))
self.__scriptableValues = value
@property
def endPoint1(self) -> SIMOBodyPoint:
""""""
return self.__endPoint1
@endPoint1.setter
def endPoint1(self, value: SIMOBodyPoint):
"""Set endPoint1"""
self.__endPoint1 = value
@property
def endPoint2(self) -> SIMOBodyPoint:
""""""
return self.__endPoint2
@endPoint2.setter
def endPoint2(self, value: SIMOBodyPoint):
"""Set endPoint2"""
self.__endPoint2 = value
@property
def failureMode(self) -> ActivationFailureMode:
"""Failure mode of coupling element"""
return self.__failureMode
@failureMode.setter
def failureMode(self, value: ActivationFailureMode):
"""Set failureMode"""
self.__failureMode = value
@property
def failureTime(self) -> float:
"""Earliest possible time of failure"""
return self.__failureTime
@failureTime.setter
def failureTime(self, value: float):
"""Set failureTime"""
self.__failureTime = float(value)
@property
def breakingStrength(self) -> float:
"""Breaking strength"""
return self.__breakingStrength
@breakingStrength.setter
def breakingStrength(self, value: float):
"""Set breakingStrength"""
self.__breakingStrength = float(value)
@property
def numElements(self) -> int:
"""Number of elements"""
return self.__numElements
@numElements.setter
def numElements(self, value: int):
"""Set numElements"""
self.__numElements = int(value)
@property
def accIncluded(self) -> bool:
"""Flag for including acceleration of the line"""
return self.__accIncluded
@accIncluded.setter
def accIncluded(self, value: bool):
"""Set accIncluded"""
self.__accIncluded = bool(value)
@property
def diameter(self) -> float:
"""Segment diameter"""
return self.__diameter
@diameter.setter
def diameter(self, value: float):
"""Set diameter"""
self.__diameter = float(value)
@property
def eMod(self) -> float:
"""Modulus of elasticity"""
return self.__eMod
@eMod.setter
def eMod(self, value: float):
"""Set eMod"""
self.__eMod = float(value)
@property
def emFac(self) -> int:
"""Factor of elasticity - 2 for chains - 1 for other segment types"""
return self.__emFac
@emFac.setter
def emFac(self, value: int):
"""Set emFac"""
self.__emFac = int(value)
@property
def length(self) -> float:
"""Initial, unstretched wire length"""
return self.__length
@length.setter
def length(self, value: float):
"""Set length"""
self.__length = float(value)
@property
def flexibility(self) -> float:
"""Connection flexibility"""
return self.__flexibility
@flexibility.setter
def flexibility(self, value: float):
"""Set flexibility"""
self.__flexibility = float(value)
@property
def damping(self) -> float:
"""Material damping"""
return self.__damping
@damping.setter
def damping(self, value: float):
"""Set damping"""
self.__damping = float(value)
@property
def uwia(self) -> float:
"""Unit weight in air"""
return self.__uwia
@uwia.setter
def uwia(self, value: float):
"""Set uwia"""
self.__uwia = float(value)
@property
def watfac(self) -> float:
"""The ratio of weight in water to weight in air"""
return self.__watfac
@watfac.setter
def watfac(self, value: float):
"""Set watfac"""
self.__watfac = float(value)
@property
def transverseDrag(self) -> float:
"""Transverse drag coefficient"""
return self.__transverseDrag
@transverseDrag.setter
def transverseDrag(self, value: float):
"""Set transverseDrag"""
self.__transverseDrag = float(value)
@property
def longitudinalDrag(self) -> float:
"""Longitudinal drag coefficient"""
return self.__longitudinalDrag
@longitudinalDrag.setter
def longitudinalDrag(self, value: float):
"""Set longitudinalDrag"""
self.__longitudinalDrag = float(value)
|
en
| 0.417639
|
# This an autogenerated file # # Generated with LiftLineCoupling Keyword arguments ----------------- name : str (default "") description : str (default "") _id : str (default "") scriptableValues : List[ScriptableValue] endPoint1 : SIMOBodyPoint endPoint2 : SIMOBodyPoint failureMode : ActivationFailureMode Failure mode of coupling element failureTime : float Earliest possible time of failure(default 0.0) breakingStrength : float Breaking strength(default 0.0) numElements : int Number of elements(default 0) accIncluded : bool Flag for including acceleration of the line(default True) diameter : float Segment diameter(default 0.0) eMod : float Modulus of elasticity(default 0.0) emFac : int Factor of elasticity - 2 for chains - 1 for other segment types(default 1) length : float Initial, unstretched wire length(default 0.0) flexibility : float Connection flexibility(default 0.0) damping : float Material damping(default 0.0) uwia : float Unit weight in air(default 0.0) watfac : float The ratio of weight in water to weight in air(default 0.0) transverseDrag : float Transverse drag coefficient(default 0.0) longitudinalDrag : float Longitudinal drag coefficient(default 0.0) Return blueprint that this entity represents Set name Set description Set _id Set scriptableValues Set endPoint1 Set endPoint2 Failure mode of coupling element Set failureMode Earliest possible time of failure Set failureTime Breaking strength Set breakingStrength Number of elements Set numElements Flag for including acceleration of the line Set accIncluded Segment diameter Set diameter Modulus of elasticity Set eMod Factor of elasticity - 2 for chains - 1 for other segment types Set emFac Initial, unstretched wire length Set length Connection flexibility Set flexibility Material damping Set damping Unit weight in air Set uwia The ratio of weight in water to weight in air Set watfac Transverse drag coefficient Set transverseDrag Longitudinal drag coefficient Set longitudinalDrag
| 2.182281
| 2
|
src/tests/ftest/erasurecode/ec_offline_rebuild.py
|
Junkrat-boommm/daos
| 0
|
6625781
|
#!/usr/bin/python
'''
(C) Copyright 2020-2021 Intel Corporation.
SPDX-License-Identifier: BSD-2-Clause-Patent
'''
from ec_utils import ErasureCodeIor
from apricot import skipForTicket
class EcOfflineRebuild(ErasureCodeIor):
# pylint: disable=too-many-ancestors
"""
Test Class Description: To validate Erasure code object data after killing
single server (offline rebuild).
:avocado: recursive
"""
def __init__(self, *args, **kwargs):
"""Initialize a ErasureCodeIor object."""
super(EcOfflineRebuild, self).__init__(*args, **kwargs)
def setUp(self):
"""Set up for test case."""
super(EcOfflineRebuild, self).setUp()
@skipForTicket("DAOS-6450")
def test_ec_offline_rebuild(self):
"""Jira ID: DAOS-5894.
Test Description: Test Erasure code object with IOR.
Use Case: Create the pool, run IOR with supported
EC object type class for small and large transfer sizes.
kill single server, Wait to finish rebuild,
verify all IOR read data and verified.
:avocado: tags=all,hw,large,ib2,full_regression
:avocado: tags=ec,ec_offline_rebuild
"""
#Write IOR data set with different EC object and different sizes
self.ior_write_dataset()
# Kill the last server rank
self.get_dmg_command().system_stop(True, self.server_count - 1)
# Wait for rebuild to start
self.pool.wait_for_rebuild(True)
# Wait for rebuild to complete
self.pool.wait_for_rebuild(False)
#Read IOR data and verify for different EC object and different sizes
#written before killing the single server
self.ior_read_dataset()
# Kill the another server rank
self.get_dmg_command().system_stop(True, self.server_count - 2)
# Wait for rebuild to start
self.pool.wait_for_rebuild(True)
# Wait for rebuild to complete
self.pool.wait_for_rebuild(False)
#Read IOR data and verify for different EC object and different sizes
#written before killing the second server.
#Only +2 (Parity) data will be intact so read and verify only +2 IOR
#data set
self.ior_read_dataset(parity=2)
|
#!/usr/bin/python
'''
(C) Copyright 2020-2021 Intel Corporation.
SPDX-License-Identifier: BSD-2-Clause-Patent
'''
from ec_utils import ErasureCodeIor
from apricot import skipForTicket
class EcOfflineRebuild(ErasureCodeIor):
# pylint: disable=too-many-ancestors
"""
Test Class Description: To validate Erasure code object data after killing
single server (offline rebuild).
:avocado: recursive
"""
def __init__(self, *args, **kwargs):
"""Initialize a ErasureCodeIor object."""
super(EcOfflineRebuild, self).__init__(*args, **kwargs)
def setUp(self):
"""Set up for test case."""
super(EcOfflineRebuild, self).setUp()
@skipForTicket("DAOS-6450")
def test_ec_offline_rebuild(self):
"""Jira ID: DAOS-5894.
Test Description: Test Erasure code object with IOR.
Use Case: Create the pool, run IOR with supported
EC object type class for small and large transfer sizes.
kill single server, Wait to finish rebuild,
verify all IOR read data and verified.
:avocado: tags=all,hw,large,ib2,full_regression
:avocado: tags=ec,ec_offline_rebuild
"""
#Write IOR data set with different EC object and different sizes
self.ior_write_dataset()
# Kill the last server rank
self.get_dmg_command().system_stop(True, self.server_count - 1)
# Wait for rebuild to start
self.pool.wait_for_rebuild(True)
# Wait for rebuild to complete
self.pool.wait_for_rebuild(False)
#Read IOR data and verify for different EC object and different sizes
#written before killing the single server
self.ior_read_dataset()
# Kill the another server rank
self.get_dmg_command().system_stop(True, self.server_count - 2)
# Wait for rebuild to start
self.pool.wait_for_rebuild(True)
# Wait for rebuild to complete
self.pool.wait_for_rebuild(False)
#Read IOR data and verify for different EC object and different sizes
#written before killing the second server.
#Only +2 (Parity) data will be intact so read and verify only +2 IOR
#data set
self.ior_read_dataset(parity=2)
|
en
| 0.681471
|
#!/usr/bin/python (C) Copyright 2020-2021 Intel Corporation. SPDX-License-Identifier: BSD-2-Clause-Patent # pylint: disable=too-many-ancestors Test Class Description: To validate Erasure code object data after killing single server (offline rebuild). :avocado: recursive Initialize a ErasureCodeIor object. Set up for test case. Jira ID: DAOS-5894. Test Description: Test Erasure code object with IOR. Use Case: Create the pool, run IOR with supported EC object type class for small and large transfer sizes. kill single server, Wait to finish rebuild, verify all IOR read data and verified. :avocado: tags=all,hw,large,ib2,full_regression :avocado: tags=ec,ec_offline_rebuild #Write IOR data set with different EC object and different sizes # Kill the last server rank # Wait for rebuild to start # Wait for rebuild to complete #Read IOR data and verify for different EC object and different sizes #written before killing the single server # Kill the another server rank # Wait for rebuild to start # Wait for rebuild to complete #Read IOR data and verify for different EC object and different sizes #written before killing the second server. #Only +2 (Parity) data will be intact so read and verify only +2 IOR #data set
| 2.117483
| 2
|
pynab/helpers.py
|
idwagner/pynab
| 0
|
6625782
|
<filename>pynab/helpers.py<gh_stars>0
import re
import click
from pynab.client import YNABClient, get_credentials
from pynab import exceptions
RE_UUID = re.compile(r'^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$')
def get_client():
try:
credentials = get_credentials()
client = YNABClient(credentials)
except exceptions.CredentialsNotFoundException:
click.echo('ERROR: Credentials not found. Set your YNAB API token as environment '
'variable YNAB_TOKEN.')
return client
def is_uuid(uuid: str):
"""Check if string is an UUID."""
return True if RE_UUID.search(uuid) else False
def match_by_name_or_id(identifier: str, data: list) -> str:
RE_BY_NAME = re.compile(identifier, re.IGNORECASE)
identifier = identifier.lower()
exact_match = [x for x in data if identifier == x.name.lower()]
match = [x for x in data if RE_BY_NAME.search(x.name)]
if len(exact_match) == 1:
return exact_match[0].id
if len(match) == 1:
return match[0].id
if exact_match or match:
# There were multiple matches
raise exceptions.AmbiguousBudgetException
return None
def select_budget(identifier: str) -> str:
if is_uuid(identifier):
return identifier
client = get_client()
items = client.budgets.get_budgets()
data = items.data.budgets
return match_by_name_or_id(identifier, data)
def select_category(budget_id, identifier: str) -> str:
data = []
if is_uuid(identifier):
return identifier
client = get_client()
items = client.categories.get_categories(budget_id=budget_id)
for group in items.data.category_groups:
data.extend([x for x in group.categories])
return match_by_name_or_id(identifier, data)
|
<filename>pynab/helpers.py<gh_stars>0
import re
import click
from pynab.client import YNABClient, get_credentials
from pynab import exceptions
RE_UUID = re.compile(r'^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$')
def get_client():
try:
credentials = get_credentials()
client = YNABClient(credentials)
except exceptions.CredentialsNotFoundException:
click.echo('ERROR: Credentials not found. Set your YNAB API token as environment '
'variable YNAB_TOKEN.')
return client
def is_uuid(uuid: str):
"""Check if string is an UUID."""
return True if RE_UUID.search(uuid) else False
def match_by_name_or_id(identifier: str, data: list) -> str:
RE_BY_NAME = re.compile(identifier, re.IGNORECASE)
identifier = identifier.lower()
exact_match = [x for x in data if identifier == x.name.lower()]
match = [x for x in data if RE_BY_NAME.search(x.name)]
if len(exact_match) == 1:
return exact_match[0].id
if len(match) == 1:
return match[0].id
if exact_match or match:
# There were multiple matches
raise exceptions.AmbiguousBudgetException
return None
def select_budget(identifier: str) -> str:
if is_uuid(identifier):
return identifier
client = get_client()
items = client.budgets.get_budgets()
data = items.data.budgets
return match_by_name_or_id(identifier, data)
def select_category(budget_id, identifier: str) -> str:
data = []
if is_uuid(identifier):
return identifier
client = get_client()
items = client.categories.get_categories(budget_id=budget_id)
for group in items.data.category_groups:
data.extend([x for x in group.categories])
return match_by_name_or_id(identifier, data)
|
en
| 0.968603
|
Check if string is an UUID. # There were multiple matches
| 2.578122
| 3
|
py/desigal/__init__.py
|
biprateep/DESI-stack
| 1
|
6625783
|
from .redshift import redshift
from .resample import resample
from .normalize import normalize
from .coadd_cameras import coadd_cameras
from .resample import resample
from .sky import get_sky
from .model_ivar import model_ivar
from .stack import stack_spectra
|
from .redshift import redshift
from .resample import resample
from .normalize import normalize
from .coadd_cameras import coadd_cameras
from .resample import resample
from .sky import get_sky
from .model_ivar import model_ivar
from .stack import stack_spectra
|
none
| 1
| 1.054106
| 1
|
|
misc/carbon-relay/web.py
|
Krylon360/evernote-graphite-web
| 8
|
6625784
|
#!/usr/bin/env python
"""Copyright 2008 Orbitz WorldWide
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License."""
import os, posix, time
from cPickle import dumps
from twisted.web.resource import Resource
class CacheQueryService(Resource):
isLeaf = True
def __init__(self,cluster):
Resource.__init__(self)
self.cluster = cluster
for cache in self.cluster.caches.values():
cache.cacheQueries = 0
def render_GET(self,req):
metric = req.path[1:]
cache = self.cluster.selectCache(metric)
points = cache.get(metric,[])
print 'CacheQuery for %s returning %d points' % (metric,len(points))
cache.cacheQueries += 1
return dumps( points )
class WebConsole(Resource):
isLeaf = True
def __init__(self,pypes,cluster,agents):
Resource.__init__(self)
self.pypes = pypes
self.cluster = cluster
self.agents = agents
self.cpuUsage = -1.0
self.memUsage = 0
self.lastCalcTime = time.time()
self.lastCpuVal = 0.0
self.templates = {}
for tmpl in os.listdir('templates'):
if not tmpl.endswith('.tmpl'): continue
self.templates[ tmpl[:-5] ] = open('templates/%s' % tmpl).read()
def render_GET(self,req):
if req.path == '/':
return self.mainPage()
if req.path == '/web.css':
return open('web.css').read()
def mainPage(self):
if self.cpuUsage > 100 or self.cpuUsage < 0:
cpuUsage = "..."
else:
cpuUsage = "%%%.2f" % self.cpuUsage
memUsage = self.memUsage
page = self.templates['main'] % locals()
return page
def updateUsage(self):
now = time.time()
t = posix.times()
curCpuVal = t[0] + t[1]
dt = now - self.lastCalcTime
dv = curCpuVal - self.lastCpuVal
self.cpuUsage = (dv / dt) * 100.0
self.lastCalcTime = now
self.lastCpuVal = curCpuVal
#self.memUsage = int(open('/proc/self/status').readlines()[12].split()[1])
|
#!/usr/bin/env python
"""Copyright 2008 Orbitz WorldWide
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License."""
import os, posix, time
from cPickle import dumps
from twisted.web.resource import Resource
class CacheQueryService(Resource):
isLeaf = True
def __init__(self,cluster):
Resource.__init__(self)
self.cluster = cluster
for cache in self.cluster.caches.values():
cache.cacheQueries = 0
def render_GET(self,req):
metric = req.path[1:]
cache = self.cluster.selectCache(metric)
points = cache.get(metric,[])
print 'CacheQuery for %s returning %d points' % (metric,len(points))
cache.cacheQueries += 1
return dumps( points )
class WebConsole(Resource):
isLeaf = True
def __init__(self,pypes,cluster,agents):
Resource.__init__(self)
self.pypes = pypes
self.cluster = cluster
self.agents = agents
self.cpuUsage = -1.0
self.memUsage = 0
self.lastCalcTime = time.time()
self.lastCpuVal = 0.0
self.templates = {}
for tmpl in os.listdir('templates'):
if not tmpl.endswith('.tmpl'): continue
self.templates[ tmpl[:-5] ] = open('templates/%s' % tmpl).read()
def render_GET(self,req):
if req.path == '/':
return self.mainPage()
if req.path == '/web.css':
return open('web.css').read()
def mainPage(self):
if self.cpuUsage > 100 or self.cpuUsage < 0:
cpuUsage = "..."
else:
cpuUsage = "%%%.2f" % self.cpuUsage
memUsage = self.memUsage
page = self.templates['main'] % locals()
return page
def updateUsage(self):
now = time.time()
t = posix.times()
curCpuVal = t[0] + t[1]
dt = now - self.lastCalcTime
dv = curCpuVal - self.lastCpuVal
self.cpuUsage = (dv / dt) * 100.0
self.lastCalcTime = now
self.lastCpuVal = curCpuVal
#self.memUsage = int(open('/proc/self/status').readlines()[12].split()[1])
|
en
| 0.783037
|
#!/usr/bin/env python Copyright 2008 Orbitz WorldWide Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. #self.memUsage = int(open('/proc/self/status').readlines()[12].split()[1])
| 1.917176
| 2
|
src/pretalx/submission/models/review.py
|
mberube/pretalx
| 0
|
6625785
|
from django.db import models
from django.utils.functional import cached_property
from django.utils.translation import gettext_lazy as _
from django_scopes import ScopedManager
from i18nfield.fields import I18nCharField
from pretalx.common.urls import EventUrls
class ReviewScoreCategory(models.Model):
event = models.ForeignKey(
to="event.Event", related_name="score_categories", on_delete=models.CASCADE
)
name = I18nCharField()
weight = models.DecimalField(max_digits=4, decimal_places=1, default=1)
required = models.BooleanField(default=False)
active = models.BooleanField(default=True)
limit_tracks = models.ManyToManyField(
to="submission.Track",
verbose_name=_("Limit to tracks"),
blank=True,
help_text=_("Leave empty to use this category for all tracks."),
)
objects = ScopedManager(event="event")
@classmethod
def recalculate_scores(cls, event):
for review in event.reviews.all():
review.save(update_score=True)
class ReviewScore(models.Model):
category = models.ForeignKey(
to=ReviewScoreCategory, related_name="scores", on_delete=models.CASCADE
)
value = models.DecimalField(max_digits=3, decimal_places=1)
label = models.CharField(null=True, blank=True, max_length=100)
objects = ScopedManager(event="category__event")
def __str__(self):
value = self.value
if int(value) == value:
value = int(value)
if self.label:
return f"{self.label} ({value})"
return str(value)
class Meta:
ordering = ("value",)
class Review(models.Model):
"""Reviews model the opinion of reviewers of a.
:class:`~pretalx.submission.models.submission.Submission`.
They can, but don't have to, include a score and a text.
:param text: The review itself. May be empty.
:param score: This score is calculated from all the related ``scores``
and their weights. Do not set it directly, use the ``update_score``
method instead.
"""
submission = models.ForeignKey(
to="submission.Submission", related_name="reviews", on_delete=models.CASCADE
)
user = models.ForeignKey(
to="person.User", related_name="reviews", on_delete=models.CASCADE
)
text = models.TextField(verbose_name=_("What do you think?"), null=True, blank=True)
score = models.DecimalField(
max_digits=10, decimal_places=2, verbose_name=_("Score"), null=True, blank=True
)
scores = models.ManyToManyField(to=ReviewScore, related_name="reviews")
created = models.DateTimeField(auto_now_add=True)
updated = models.DateTimeField(auto_now=True)
objects = ScopedManager(event="submission__event")
def __str__(self):
return f"Review(event={self.submission.event.slug}, submission={self.submission.title}, user={self.user.get_display_name}, score={self.score})"
@classmethod
def find_missing_reviews(cls, event, user, ignore=None):
"""Returns all.
:class:`~pretalx.submission.models.submission.Submission` objects this
:class:`~pretalx.person.models.user.User` still has to review for the
given :class:`~pretalx.event.models.event.Event`.
Excludes submissions this user has submitted, and takes track
:class:`~pretalx.event.models.organiser.Team` permissions into account.
The result is ordered by review count.
:type event: :class:`~pretalx.event.models.event.Event`
:type user: :class:`~pretalx.person.models.user.User`
:rtype: Queryset of :class:`~pretalx.submission.models.submission.Submission` objects
"""
from pretalx.submission.models import SubmissionStates
queryset = (
event.submissions.filter(state=SubmissionStates.SUBMITTED)
.exclude(reviews__user=user)
.exclude(speakers__in=[user])
.annotate(review_count=models.Count("reviews"))
)
limit_tracks = user.teams.filter(
models.Q(all_events=True)
| models.Q(models.Q(all_events=False) & models.Q(limit_events__in=[event])),
limit_tracks__isnull=False,
)
if limit_tracks.exists():
tracks = set()
for team in limit_tracks:
tracks.update(team.limit_tracks.filter(event=event))
queryset = queryset.filter(track__in=tracks)
if ignore:
queryset = queryset.exclude(pk__in=ignore)
# This is not randomised, because order_by("review_count", "?") sets all annotated
# review_count values to 1.
return queryset.order_by("review_count")
@classmethod
def calculate_score(cls, scores):
if not scores:
return None
return sum(score.value * score.category.weight for score in scores)
@cached_property
def event(self):
return self.submission.event
@cached_property
def display_score(self) -> str:
"""Helper method to get a display string of the review's score."""
if self.score is None:
return "×"
if int(self.score) == self.score:
return str(int(self.score))
return str(self.score)
def update_score(self):
track = self.submission.track
track_filter = models.Q(category__limit_tracks__isnull=True)
if track:
track_filter |= models.Q(category__limit_tracks__in=[track])
scores = (
self.scores.all()
.select_related("category")
.filter(track_filter, category__active=True)
)
self.score = self.calculate_score(scores)
def save(self, *args, update_score=True, **kwargs):
if self.id and update_score:
self.update_score()
return super().save(*args, **kwargs)
class urls(EventUrls):
base = "{self.submission.orga_urls.reviews}"
delete = "{base}{self.pk}/delete"
class ReviewPhase(models.Model):
"""ReviewPhases determine reviewer access rights during a (potentially
open) time frame.
:param is_active: Is this phase currently active? There can be only one
active phase per event. Use the ``activate`` method to activate a
review phase, as it will take care of this limitation.
:param position: Helper field to deal with relative positioning of review
phases next to each other.
"""
event = models.ForeignKey(
to="event.Event", related_name="review_phases", on_delete=models.CASCADE
)
name = models.CharField(verbose_name=_("Name"), max_length=100)
start = models.DateTimeField(verbose_name=_("Phase start"), null=True, blank=True)
end = models.DateTimeField(verbose_name=_("Phase end"), null=True, blank=True)
position = models.PositiveIntegerField(default=0)
is_active = models.BooleanField(default=False)
can_review = models.BooleanField(
verbose_name=_("Reviewers can write and edit reviews"),
default=True,
)
can_see_other_reviews = models.CharField(
verbose_name=_("Reviewers can see other reviews"),
max_length=12,
choices=(
("always", _("Always")),
("never", _("Never")),
("after_review", _("After reviewing the submission")),
),
default="after_review",
)
can_see_speaker_names = models.BooleanField(
verbose_name=_("Reviewers can see speaker names"),
default=True,
)
can_see_reviewer_names = models.BooleanField(
verbose_name=_("Reviewers can see the names of other reviewers"),
default=True,
)
can_change_submission_state = models.BooleanField(
verbose_name=_("Reviewers can accept and reject submissions"),
default=False,
)
can_tag_submissions = models.CharField(
verbose_name=_("Reviewers can tag submissions"),
max_length=12,
choices=(
("never", _("Never")),
("use_tags", _("Add and remove existing tags")),
("create_tags", _("Add, remove and create tags")),
),
default="never",
)
speakers_can_change_submissions = models.BooleanField(
verbose_name=_("Speakers can modify their submissions before acceptance"),
help_text=_(
"By default, modification of submissions is locked after the CfP ends, and is re-enabled once the submission was accepted."
),
default=False,
)
objects = ScopedManager(event="event")
class Meta:
ordering = ("position",)
class urls(EventUrls):
base = "{self.event.orga_urls.review_settings}phase/{self.pk}/"
delete = "{base}delete"
up = "{base}up"
down = "{base}down"
activate = "{base}activate"
def activate(self) -> None:
"""Activates this review phase and deactivates all others in this
event."""
self.event.review_phases.all().update(is_active=False)
self.is_active = True
self.save()
activate.alters_data = True
|
from django.db import models
from django.utils.functional import cached_property
from django.utils.translation import gettext_lazy as _
from django_scopes import ScopedManager
from i18nfield.fields import I18nCharField
from pretalx.common.urls import EventUrls
class ReviewScoreCategory(models.Model):
event = models.ForeignKey(
to="event.Event", related_name="score_categories", on_delete=models.CASCADE
)
name = I18nCharField()
weight = models.DecimalField(max_digits=4, decimal_places=1, default=1)
required = models.BooleanField(default=False)
active = models.BooleanField(default=True)
limit_tracks = models.ManyToManyField(
to="submission.Track",
verbose_name=_("Limit to tracks"),
blank=True,
help_text=_("Leave empty to use this category for all tracks."),
)
objects = ScopedManager(event="event")
@classmethod
def recalculate_scores(cls, event):
for review in event.reviews.all():
review.save(update_score=True)
class ReviewScore(models.Model):
category = models.ForeignKey(
to=ReviewScoreCategory, related_name="scores", on_delete=models.CASCADE
)
value = models.DecimalField(max_digits=3, decimal_places=1)
label = models.CharField(null=True, blank=True, max_length=100)
objects = ScopedManager(event="category__event")
def __str__(self):
value = self.value
if int(value) == value:
value = int(value)
if self.label:
return f"{self.label} ({value})"
return str(value)
class Meta:
ordering = ("value",)
class Review(models.Model):
"""Reviews model the opinion of reviewers of a.
:class:`~pretalx.submission.models.submission.Submission`.
They can, but don't have to, include a score and a text.
:param text: The review itself. May be empty.
:param score: This score is calculated from all the related ``scores``
and their weights. Do not set it directly, use the ``update_score``
method instead.
"""
submission = models.ForeignKey(
to="submission.Submission", related_name="reviews", on_delete=models.CASCADE
)
user = models.ForeignKey(
to="person.User", related_name="reviews", on_delete=models.CASCADE
)
text = models.TextField(verbose_name=_("What do you think?"), null=True, blank=True)
score = models.DecimalField(
max_digits=10, decimal_places=2, verbose_name=_("Score"), null=True, blank=True
)
scores = models.ManyToManyField(to=ReviewScore, related_name="reviews")
created = models.DateTimeField(auto_now_add=True)
updated = models.DateTimeField(auto_now=True)
objects = ScopedManager(event="submission__event")
def __str__(self):
return f"Review(event={self.submission.event.slug}, submission={self.submission.title}, user={self.user.get_display_name}, score={self.score})"
@classmethod
def find_missing_reviews(cls, event, user, ignore=None):
"""Returns all.
:class:`~pretalx.submission.models.submission.Submission` objects this
:class:`~pretalx.person.models.user.User` still has to review for the
given :class:`~pretalx.event.models.event.Event`.
Excludes submissions this user has submitted, and takes track
:class:`~pretalx.event.models.organiser.Team` permissions into account.
The result is ordered by review count.
:type event: :class:`~pretalx.event.models.event.Event`
:type user: :class:`~pretalx.person.models.user.User`
:rtype: Queryset of :class:`~pretalx.submission.models.submission.Submission` objects
"""
from pretalx.submission.models import SubmissionStates
queryset = (
event.submissions.filter(state=SubmissionStates.SUBMITTED)
.exclude(reviews__user=user)
.exclude(speakers__in=[user])
.annotate(review_count=models.Count("reviews"))
)
limit_tracks = user.teams.filter(
models.Q(all_events=True)
| models.Q(models.Q(all_events=False) & models.Q(limit_events__in=[event])),
limit_tracks__isnull=False,
)
if limit_tracks.exists():
tracks = set()
for team in limit_tracks:
tracks.update(team.limit_tracks.filter(event=event))
queryset = queryset.filter(track__in=tracks)
if ignore:
queryset = queryset.exclude(pk__in=ignore)
# This is not randomised, because order_by("review_count", "?") sets all annotated
# review_count values to 1.
return queryset.order_by("review_count")
@classmethod
def calculate_score(cls, scores):
if not scores:
return None
return sum(score.value * score.category.weight for score in scores)
@cached_property
def event(self):
return self.submission.event
@cached_property
def display_score(self) -> str:
"""Helper method to get a display string of the review's score."""
if self.score is None:
return "×"
if int(self.score) == self.score:
return str(int(self.score))
return str(self.score)
def update_score(self):
track = self.submission.track
track_filter = models.Q(category__limit_tracks__isnull=True)
if track:
track_filter |= models.Q(category__limit_tracks__in=[track])
scores = (
self.scores.all()
.select_related("category")
.filter(track_filter, category__active=True)
)
self.score = self.calculate_score(scores)
def save(self, *args, update_score=True, **kwargs):
if self.id and update_score:
self.update_score()
return super().save(*args, **kwargs)
class urls(EventUrls):
base = "{self.submission.orga_urls.reviews}"
delete = "{base}{self.pk}/delete"
class ReviewPhase(models.Model):
"""ReviewPhases determine reviewer access rights during a (potentially
open) time frame.
:param is_active: Is this phase currently active? There can be only one
active phase per event. Use the ``activate`` method to activate a
review phase, as it will take care of this limitation.
:param position: Helper field to deal with relative positioning of review
phases next to each other.
"""
event = models.ForeignKey(
to="event.Event", related_name="review_phases", on_delete=models.CASCADE
)
name = models.CharField(verbose_name=_("Name"), max_length=100)
start = models.DateTimeField(verbose_name=_("Phase start"), null=True, blank=True)
end = models.DateTimeField(verbose_name=_("Phase end"), null=True, blank=True)
position = models.PositiveIntegerField(default=0)
is_active = models.BooleanField(default=False)
can_review = models.BooleanField(
verbose_name=_("Reviewers can write and edit reviews"),
default=True,
)
can_see_other_reviews = models.CharField(
verbose_name=_("Reviewers can see other reviews"),
max_length=12,
choices=(
("always", _("Always")),
("never", _("Never")),
("after_review", _("After reviewing the submission")),
),
default="after_review",
)
can_see_speaker_names = models.BooleanField(
verbose_name=_("Reviewers can see speaker names"),
default=True,
)
can_see_reviewer_names = models.BooleanField(
verbose_name=_("Reviewers can see the names of other reviewers"),
default=True,
)
can_change_submission_state = models.BooleanField(
verbose_name=_("Reviewers can accept and reject submissions"),
default=False,
)
can_tag_submissions = models.CharField(
verbose_name=_("Reviewers can tag submissions"),
max_length=12,
choices=(
("never", _("Never")),
("use_tags", _("Add and remove existing tags")),
("create_tags", _("Add, remove and create tags")),
),
default="never",
)
speakers_can_change_submissions = models.BooleanField(
verbose_name=_("Speakers can modify their submissions before acceptance"),
help_text=_(
"By default, modification of submissions is locked after the CfP ends, and is re-enabled once the submission was accepted."
),
default=False,
)
objects = ScopedManager(event="event")
class Meta:
ordering = ("position",)
class urls(EventUrls):
base = "{self.event.orga_urls.review_settings}phase/{self.pk}/"
delete = "{base}delete"
up = "{base}up"
down = "{base}down"
activate = "{base}activate"
def activate(self) -> None:
"""Activates this review phase and deactivates all others in this
event."""
self.event.review_phases.all().update(is_active=False)
self.is_active = True
self.save()
activate.alters_data = True
|
en
| 0.817119
|
Reviews model the opinion of reviewers of a. :class:`~pretalx.submission.models.submission.Submission`. They can, but don't have to, include a score and a text. :param text: The review itself. May be empty. :param score: This score is calculated from all the related ``scores`` and their weights. Do not set it directly, use the ``update_score`` method instead. Returns all. :class:`~pretalx.submission.models.submission.Submission` objects this :class:`~pretalx.person.models.user.User` still has to review for the given :class:`~pretalx.event.models.event.Event`. Excludes submissions this user has submitted, and takes track :class:`~pretalx.event.models.organiser.Team` permissions into account. The result is ordered by review count. :type event: :class:`~pretalx.event.models.event.Event` :type user: :class:`~pretalx.person.models.user.User` :rtype: Queryset of :class:`~pretalx.submission.models.submission.Submission` objects # This is not randomised, because order_by("review_count", "?") sets all annotated # review_count values to 1. Helper method to get a display string of the review's score. ReviewPhases determine reviewer access rights during a (potentially open) time frame. :param is_active: Is this phase currently active? There can be only one active phase per event. Use the ``activate`` method to activate a review phase, as it will take care of this limitation. :param position: Helper field to deal with relative positioning of review phases next to each other. Activates this review phase and deactivates all others in this event.
| 1.950302
| 2
|
Martel/test/testformats/delimiter.py
|
eoc21/biopython
| 3
|
6625786
|
<reponame>eoc21/biopython<filename>Martel/test/testformats/delimiter.py
"""Example of using Martel on a simple delimited file
"""
import Martel
from Martel import RecordReader
def delimiter(delim):
assert len(delim) == 1, \
"delimiter can only be a single character long, not %s" % repr(delim)
assert delim not in "\n\r", "Cannot use %s as a delimiter" % repr(delim)
field = Martel.Group("field", Martel.Rep(Martel.AnyBut(delim + "\r\n")))
line = field + Martel.Rep(Martel.Str(delim) + field) + Martel.AnyEol()
record = Martel.Group("record", line)
format = Martel.ParseRecords("delimited", {}, record,
RecordReader.CountLines, (1,))
return format
tabformat = delimiter("\t")
spaceformat = delimiter(" ")
colonformat = delimiter(":")
commaformat = delimiter(",")
if __name__ == "__main__":
from xml.sax import saxutils
parser = colonformat.make_parser()
parser.setContentHandler(saxutils.XMLGenerator())
parser.parseFile(open("/etc/passwd"))
|
"""Example of using Martel on a simple delimited file
"""
import Martel
from Martel import RecordReader
def delimiter(delim):
assert len(delim) == 1, \
"delimiter can only be a single character long, not %s" % repr(delim)
assert delim not in "\n\r", "Cannot use %s as a delimiter" % repr(delim)
field = Martel.Group("field", Martel.Rep(Martel.AnyBut(delim + "\r\n")))
line = field + Martel.Rep(Martel.Str(delim) + field) + Martel.AnyEol()
record = Martel.Group("record", line)
format = Martel.ParseRecords("delimited", {}, record,
RecordReader.CountLines, (1,))
return format
tabformat = delimiter("\t")
spaceformat = delimiter(" ")
colonformat = delimiter(":")
commaformat = delimiter(",")
if __name__ == "__main__":
from xml.sax import saxutils
parser = colonformat.make_parser()
parser.setContentHandler(saxutils.XMLGenerator())
parser.parseFile(open("/etc/passwd"))
|
en
| 0.710825
|
Example of using Martel on a simple delimited file
| 3.426341
| 3
|
wagtail_hooks.py
|
bobslee/django_commerce_wagtail
| 3
|
6625787
|
from django.contrib.admin.utils import quote
from django.templatetags.static import static
from django.urls import reverse
from django.utils.html import format_html, format_html_join
from django.utils.translation import ugettext_lazy as _
from wagtail.wagtailcore import hooks
from wagtail.wagtailadmin import widgets as wagtailadmin_widgets
from wagtail.contrib.modeladmin.options import modeladmin_register
from .admin import has_admin_perm
from .models import ProductPage
from .modeladmin import CommerceModelAdminGroup
modeladmin_register(CommerceModelAdminGroup)
@hooks.register('register_page_listing_buttons')
def page_listing_buttons(page, page_perms, is_parent=False):
admin_url = 'wagtailcommerce_product_modeladmin_edit'
# TODO if user has_permission for (django)admin product_change
if isinstance(page.specific, ProductPage) and hasattr(page, 'product'):
url = reverse(admin_url,
args=(quote(page.product.pk),),
current_app='wagtailcommerce',
)
yield wagtailadmin_widgets.PageListingButton(
"product",
url,
classes=('icon', 'icon-fa-product-hunt'),
attrs={'title': _('Edit product in the Commerce admin ')},
priority=100,
)
@hooks.register('insert_editor_js')
def editor_js():
js_files = [
static('wagtailcommerce/js/page-chooser-or-create.js'),
]
js_includes = format_html_join(
'\n', '<script src="{0}"></script>',
((filename, ) for filename in js_files)
)
return js_includes
@hooks.register('insert_global_admin_css')
def global_admin_css():
css_files = [
static('wagtailcommerce/css/wagtailadmin/core.css')
]
css_includes = format_html_join(
'\n',
'<link rel="stylesheet" href="{}">',
((filename, ) for filename in css_files)
)
return css_includes
|
from django.contrib.admin.utils import quote
from django.templatetags.static import static
from django.urls import reverse
from django.utils.html import format_html, format_html_join
from django.utils.translation import ugettext_lazy as _
from wagtail.wagtailcore import hooks
from wagtail.wagtailadmin import widgets as wagtailadmin_widgets
from wagtail.contrib.modeladmin.options import modeladmin_register
from .admin import has_admin_perm
from .models import ProductPage
from .modeladmin import CommerceModelAdminGroup
modeladmin_register(CommerceModelAdminGroup)
@hooks.register('register_page_listing_buttons')
def page_listing_buttons(page, page_perms, is_parent=False):
admin_url = 'wagtailcommerce_product_modeladmin_edit'
# TODO if user has_permission for (django)admin product_change
if isinstance(page.specific, ProductPage) and hasattr(page, 'product'):
url = reverse(admin_url,
args=(quote(page.product.pk),),
current_app='wagtailcommerce',
)
yield wagtailadmin_widgets.PageListingButton(
"product",
url,
classes=('icon', 'icon-fa-product-hunt'),
attrs={'title': _('Edit product in the Commerce admin ')},
priority=100,
)
@hooks.register('insert_editor_js')
def editor_js():
js_files = [
static('wagtailcommerce/js/page-chooser-or-create.js'),
]
js_includes = format_html_join(
'\n', '<script src="{0}"></script>',
((filename, ) for filename in js_files)
)
return js_includes
@hooks.register('insert_global_admin_css')
def global_admin_css():
css_files = [
static('wagtailcommerce/css/wagtailadmin/core.css')
]
css_includes = format_html_join(
'\n',
'<link rel="stylesheet" href="{}">',
((filename, ) for filename in css_files)
)
return css_includes
|
en
| 0.349119
|
# TODO if user has_permission for (django)admin product_change
| 2.009243
| 2
|
Bugscan_exploits-master/exp_list/exp－2625.py
|
csadsl/poc_exp
| 11
|
6625788
|
<gh_stars>10-100
#!/usr/bin/evn python
#--coding:utf-8--*--
#Name:北京网达信联通用型电子采购系统多处SQL注入打包
#Refer:http://www.wooyun.org/bugs/wooyun-2010-0122276
#Author:xq17
def assign(service, arg):
if service == '1caitong':
return True, arg
def audit(arg):
urls = [
"Rat/ebid/viewInvite3.asp?InviteId=0000002852",
"Rat/ebid/viewInvite4.asp?InviteId=0000002852",
"Rat/ebid/viewInvite5.asp?InviteId=0000002852",
"Rat/ebid/viewInvite6.asp?InviteId=0000002852",
"Rat/ebid/viewInvite2.asp?InviteId=0000002852",
"Rat/ebid/viewInvite1.asp?InviteId=0000002852",
"Rat/EBid/ViewClarify1.asp?InviteId=11",
"Rat/EBid/ViewClarify.asp?InviteId=11",
"Rat/EBid/AuditForm/AuditForm_ExpertForm.asp?InviteId=11",
]
data = "%27%20and%20(CHAR(126)%2BCHAR(116)%2BCHAR(101)%2BCHAR(115)%2BCHAR(116)%2BCHAR(88)%2BCHAR(81)%2BCHAR(49)%2BCHAR(55))%3E0--"
for url in urls:
vul = arg + url + data
code, head, res, errcode, _ = curl.curl2(vul)
if code!=0 and 'testXQ17' in res:
security_hole(arg + url)
if __name__ == '__main__':
from dummy import *
audit(assign('1caitong','http://tycg.jiigoo.com/')[1])
# audit(assign('1caitong','http://zhaobiao.cdjcc.com/')[1])
# audit(assign('1caitong','http://eps.myande.com/')[1])
# audit(assign('1caitong','http://caigou.irico.com.cn/')[1])
|
#!/usr/bin/evn python
#--coding:utf-8--*--
#Name:北京网达信联通用型电子采购系统多处SQL注入打包
#Refer:http://www.wooyun.org/bugs/wooyun-2010-0122276
#Author:xq17
def assign(service, arg):
if service == '1caitong':
return True, arg
def audit(arg):
urls = [
"Rat/ebid/viewInvite3.asp?InviteId=0000002852",
"Rat/ebid/viewInvite4.asp?InviteId=0000002852",
"Rat/ebid/viewInvite5.asp?InviteId=0000002852",
"Rat/ebid/viewInvite6.asp?InviteId=0000002852",
"Rat/ebid/viewInvite2.asp?InviteId=0000002852",
"Rat/ebid/viewInvite1.asp?InviteId=0000002852",
"Rat/EBid/ViewClarify1.asp?InviteId=11",
"Rat/EBid/ViewClarify.asp?InviteId=11",
"Rat/EBid/AuditForm/AuditForm_ExpertForm.asp?InviteId=11",
]
data = "%27%20and%20(CHAR(126)%2BCHAR(116)%2BCHAR(101)%2BCHAR(115)%2BCHAR(116)%2BCHAR(88)%2BCHAR(81)%2BCHAR(49)%2BCHAR(55))%3E0--"
for url in urls:
vul = arg + url + data
code, head, res, errcode, _ = curl.curl2(vul)
if code!=0 and 'testXQ17' in res:
security_hole(arg + url)
if __name__ == '__main__':
from dummy import *
audit(assign('1caitong','http://tycg.jiigoo.com/')[1])
# audit(assign('1caitong','http://zhaobiao.cdjcc.com/')[1])
# audit(assign('1caitong','http://eps.myande.com/')[1])
# audit(assign('1caitong','http://caigou.irico.com.cn/')[1])
|
en
| 0.179071
|
#!/usr/bin/evn python #--coding:utf-8--*-- #Name:北京网达信联通用型电子采购系统多处SQL注入打包 #Refer:http://www.wooyun.org/bugs/wooyun-2010-0122276 #Author:xq17 # audit(assign('1caitong','http://zhaobiao.cdjcc.com/')[1]) # audit(assign('1caitong','http://eps.myande.com/')[1]) # audit(assign('1caitong','http://caigou.irico.com.cn/')[1])
| 2.083378
| 2
|
update_readme.py
|
montib/rays1bench
| 0
|
6625789
|
import os
import glob
import shutil
import fileinput
def replace_text_in_file(file_to_search, text_to_search, results):
with fileinput.FileInput(file_to_search, inplace=True) as file:
for line in file:
print(line.replace(text_to_search, results), end='')
def parse(dirs, size, add_table_header=False):
baseline_mrays = -1.0
if add_table_header:
results = '\n|scene|version|time|total rays|performance|speedup|\n|--|--|--|--|--|--|\n'
else:
results = ''
for i in dirs:
os.chdir(i)
# print('parsing: ' + i + '/' + str(size))
f = open('out_' + size + '.txt','rt')
results += '|' + size + '|' + i[4:] + ': '
line = f.readline()
results += line
tokens = line.split('|') # 123.45 mrays/s
mrays = float(tokens[3].split()[0]) # 123.45
if baseline_mrays < 0:
baseline_mrays = mrays
mrays_str = '{:.2f}'.format(mrays / baseline_mrays)
if i == dirs[-1]:
mrays_str = '**' + mrays_str + '**' # last value is in bold
results += mrays_str + '|\n'
f.close
os.chdir('../..')
# print('RESULTS = \n' + results + '\n')
return results
dirs = ['src/step1', 'src/step2', 'src/step3', 'src/step4', 'src/step5', 'src/step6', 'src/step7', 'src/step8', 'src/step9', 'src/step10', 'src/step11', 'src/step12', 'src/step13']
# all results
shutil.copyfile('README_template.md', 'README.md')
replace_text_in_file('README.md', '__RESULTS_MSVC2019_X64__', parse(dirs, 'large', True) + parse(dirs, 'medium', True) + parse(dirs, 'small', True))
# step1
steps_to_cmp = ['src/step1']
replace_text_in_file('README.md', '__RESULTS_MSVC2019_X64_step1__', parse(steps_to_cmp, 'large', True) + parse(steps_to_cmp, 'medium') + parse(steps_to_cmp, 'small'))
# stepPREV -> stepCURRENT
prev = dirs[0]
for i in dirs[1:]:
step_name = i[4:]
to_replace = '__RESULTS_MSVC2019_X64_' + step_name + '__'
steps_to_cmp = [prev, i]
replace_text_in_file('README.md', to_replace, parse(steps_to_cmp, 'large', True) + parse(steps_to_cmp, 'medium') + parse(steps_to_cmp, 'small'))
prev = i
|
import os
import glob
import shutil
import fileinput
def replace_text_in_file(file_to_search, text_to_search, results):
with fileinput.FileInput(file_to_search, inplace=True) as file:
for line in file:
print(line.replace(text_to_search, results), end='')
def parse(dirs, size, add_table_header=False):
baseline_mrays = -1.0
if add_table_header:
results = '\n|scene|version|time|total rays|performance|speedup|\n|--|--|--|--|--|--|\n'
else:
results = ''
for i in dirs:
os.chdir(i)
# print('parsing: ' + i + '/' + str(size))
f = open('out_' + size + '.txt','rt')
results += '|' + size + '|' + i[4:] + ': '
line = f.readline()
results += line
tokens = line.split('|') # 123.45 mrays/s
mrays = float(tokens[3].split()[0]) # 123.45
if baseline_mrays < 0:
baseline_mrays = mrays
mrays_str = '{:.2f}'.format(mrays / baseline_mrays)
if i == dirs[-1]:
mrays_str = '**' + mrays_str + '**' # last value is in bold
results += mrays_str + '|\n'
f.close
os.chdir('../..')
# print('RESULTS = \n' + results + '\n')
return results
dirs = ['src/step1', 'src/step2', 'src/step3', 'src/step4', 'src/step5', 'src/step6', 'src/step7', 'src/step8', 'src/step9', 'src/step10', 'src/step11', 'src/step12', 'src/step13']
# all results
shutil.copyfile('README_template.md', 'README.md')
replace_text_in_file('README.md', '__RESULTS_MSVC2019_X64__', parse(dirs, 'large', True) + parse(dirs, 'medium', True) + parse(dirs, 'small', True))
# step1
steps_to_cmp = ['src/step1']
replace_text_in_file('README.md', '__RESULTS_MSVC2019_X64_step1__', parse(steps_to_cmp, 'large', True) + parse(steps_to_cmp, 'medium') + parse(steps_to_cmp, 'small'))
# stepPREV -> stepCURRENT
prev = dirs[0]
for i in dirs[1:]:
step_name = i[4:]
to_replace = '__RESULTS_MSVC2019_X64_' + step_name + '__'
steps_to_cmp = [prev, i]
replace_text_in_file('README.md', to_replace, parse(steps_to_cmp, 'large', True) + parse(steps_to_cmp, 'medium') + parse(steps_to_cmp, 'small'))
prev = i
|
en
| 0.422473
|
# print('parsing: ' + i + '/' + str(size)) # 123.45 mrays/s # 123.45 # last value is in bold # print('RESULTS = \n' + results + '\n') # all results # step1 # stepPREV -> stepCURRENT
| 3.249587
| 3
|
azure_monitor/tests/auto_collection/test_metrics_span_processor.py
|
yao-cqc/opentelemetry-azure-monitor-python
| 13
|
6625790
|
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import unittest
from opentelemetry.sdk.trace import Span
from opentelemetry.trace import SpanContext, SpanKind
from opentelemetry.trace.status import Status, StatusCanonicalCode
from azure_monitor.sdk.auto_collection.metrics_span_processor import (
AzureMetricsSpanProcessor,
)
# pylint: disable=protected-access
class TestMetricsSpanProcessor(unittest.TestCase):
def test_document_collection(self):
"""Test the document collection."""
span_processor = AzureMetricsSpanProcessor()
span_processor.is_collecting_documents = True
test_span = Span(
name="test",
kind=SpanKind.SERVER,
context=SpanContext(
trace_id=36873507687745823477771305566750195431,
span_id=12030755672171557338,
is_remote=False,
),
)
test_span.set_status(Status(StatusCanonicalCode.INTERNAL, "test"))
test_span._start_time = 5000000
test_span._end_time = 15000000
span_processor.on_end(test_span)
document = span_processor.documents.pop()
self.assertIsNotNone(document)
self.assertEqual(
document.name, "Microsoft.ApplicationInsights.Request"
)
|
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import unittest
from opentelemetry.sdk.trace import Span
from opentelemetry.trace import SpanContext, SpanKind
from opentelemetry.trace.status import Status, StatusCanonicalCode
from azure_monitor.sdk.auto_collection.metrics_span_processor import (
AzureMetricsSpanProcessor,
)
# pylint: disable=protected-access
class TestMetricsSpanProcessor(unittest.TestCase):
def test_document_collection(self):
"""Test the document collection."""
span_processor = AzureMetricsSpanProcessor()
span_processor.is_collecting_documents = True
test_span = Span(
name="test",
kind=SpanKind.SERVER,
context=SpanContext(
trace_id=36873507687745823477771305566750195431,
span_id=12030755672171557338,
is_remote=False,
),
)
test_span.set_status(Status(StatusCanonicalCode.INTERNAL, "test"))
test_span._start_time = 5000000
test_span._end_time = 15000000
span_processor.on_end(test_span)
document = span_processor.documents.pop()
self.assertIsNotNone(document)
self.assertEqual(
document.name, "Microsoft.ApplicationInsights.Request"
)
|
en
| 0.720511
|
# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. # pylint: disable=protected-access Test the document collection.
| 2.113647
| 2
|
votacoes/views.py
|
JeanSchnorr/votaluno
| 0
|
6625791
|
<filename>votacoes/views.py
from django.contrib.auth.decorators import login_required
from django.http import HttpResponseRedirect
from django.contrib.auth.models import User
from .models import Aluno, AvaliacaoTurma, AvaliacaoAluno, Turma, OfertaDisciplina, Conselho,UsuarioConselho, Votacao, Voto
from django.shortcuts import render, redirect
from datetime import datetime
from .avaliacoes import *
@login_required
def home(request):
context = {}
conselhos_professor=[]
conselhos_abertos = []
conselhos = request.user.conselhos_usuario.all()
for conselho in conselhos:
conselhos_professor.append(conselho.conselho)
for conselho in Conselho.objects.filter(situacao=True):
if conselho in conselhos_professor:
conselhos_abertos.append(conselho)
if request.user.is_superuser:
context['conselhos_abertos'] = Conselho.objects.filter(situacao=True)
else:
context['conselhos_abertos'] = conselhos_abertos
return render(request, 'home.html',context)
# Views que manipulam as avaliações das turmas
@login_required
def avaliacoesTurmas(request):
context = {}
avaliacoes=[]
avaliacoes_lancadas=[]
ofertas = OfertaDisciplina.objects.filter(professor=request.user)
for oferta in ofertas:
avs = AvaliacaoTurma.objects.filter(oferta_disciplina=oferta).filter(status=True)
avs_lancadas = AvaliacaoTurma.objects.filter(oferta_disciplina=oferta).filter(status=False)[:10]
if len(avs_lancadas) > 0:
for avaliacoesLancadas in avs_lancadas:
avaliacoes_lancadas.append(avaliacoesLancadas)
if len(avs) > 0:
for avaliacoesDisciplina in avs:
avaliacoes.append(avaliacoesDisciplina)
context['avaliacoes'] = avaliacoes
context['avaliacoes_lancadas'] = avaliacoes_lancadas
return render(request,'avaliacoes/avaliacoesTurmas.html',context)
@login_required
def criarAvaliacaoTurma(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoTurma.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = DICT_TURMA
return render(request,'avaliacoes/avaliarTurma.html', context)
@login_required
def lancarAvaliacaoTurma(request, avaliacao_id):
soma = 0
selecionadas = request.POST.getlist('checks')
for opcao in selecionadas:
soma += int(opcao)
avaliacao = AvaliacaoTurma.objects.get(pk=avaliacao_id)
avaliacao.status = False
avaliacao.avaliacao = soma
avaliacao.outros_avaliacao = request.POST.get('outros')
avaliacao.save()
return avaliacoesTurmas(request)
@login_required
def visualizarAvaliacaoTurma(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoTurma.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = get_array_turma(avaliacao.avaliacao)
return render(request,'avaliacoes/visualizarAvaliacaoTurma.html', context)
#Views que manipulam as avaliações dos alunos
@login_required
def gerarAvaliacoesTurma(request):
turma = Turma.objects.get(id=request.POST.get("turma"))
bimestre = request.POST.get("bimestre")
alunos = Aluno.objects.filter(turma=turma)
ofertaDisciplinas_turma = OfertaDisciplina.objects.filter(turma=turma)
for disciplina in ofertaDisciplinas_turma:
avaliacaoTurma = AvaliacaoTurma(oferta_disciplina=disciplina,bimestre=bimestre,ano=int(datetime.now().year))
avaliacaoTurma.save()
for aluno in alunos:
avaliacaoAluno = AvaliacaoAluno(oferta_disciplina=disciplina,aluno=aluno,bimestre=bimestre,ano=int(datetime.now().year))
avaliacaoAluno.save()
return administracao(request)
@login_required
def avaliacoesAlunos(request):
context = {}
avaliacoes=[]
avaliacoes_lancadas=[]
ofertas = OfertaDisciplina.objects.filter(professor=request.user)
for oferta in ofertas:
avs = AvaliacaoAluno.objects.filter(oferta_disciplina=oferta).filter(status=True)
avs_lancadas = AvaliacaoAluno.objects.filter(oferta_disciplina=oferta).filter(status=False)[:10]
if len(avs_lancadas) > 0:
for avaliacoesLancadas in avs_lancadas:
avaliacoes_lancadas.append(avaliacoesLancadas)
if len(avs) > 0:
for avaliacoesDisciplina in avs:
avaliacoes.append(avaliacoesDisciplina)
context['avaliacoes'] = avaliacoes
context['avaliacoes_lancadas'] = avaliacoes_lancadas
return render(request,'avaliacoes/avaliacoesAlunos.html',context)
@login_required
def criarAvaliacaoAluno(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoAluno.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = DICT_ALUNO
return render(request,'avaliacoes/avaliarAluno.html', context)
@login_required
def lancarAvaliacaoAluno(request, avaliacao_id):
soma = 0
selecionadas = request.POST.getlist('checks')
for opcao in selecionadas:
soma += int(opcao)
avaliacao = AvaliacaoAluno.objects.get(pk=avaliacao_id)
avaliacao.status = False
avaliacao.avaliacao = soma
avaliacao.outros_avaliacao = request.POST.get('outros')
avaliacao.save()
return avaliacoesAlunos(request)
@login_required
def visualizarAvaliacaoAluno(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoAluno.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = get_array_aluno(avaliacao.avaliacao)
return render(request,'avaliacoes/visualizarAvaliacaoAluno.html', context)
#Views que manipulam a administração
@login_required
def administracao(request):
context = {}
turmas = Turma.objects.all()
conselhosFechados = Conselho.objects.filter(situacao=False)
conselhosAbertos = Conselho.objects.filter(situacao=True)
context['turmas'] = turmas
context['conselhosFechados'] = conselhosFechados
context['conselhosAbertos'] = conselhosAbertos
return render(request,'administracao.html', context)
@login_required
def admin(request):
return HttpResponseRedirect('/admin')
#Views para Conselhos
@login_required
def gerarConselho(request):
# Gerar conselho
turma = Turma.objects.get(id=request.POST.get("turma"))
data = request.POST.get("data")
conselho = Conselho.objects.create(
turma= turma,
data= data,
situacao = False,
)
conselho.save()
#Criar e popular lista de professores que dão aula para essa turma
professores = []
for disciplina in turma.disciplinas_turma.all():
if not disciplina.professor in professores:
professores.append(disciplina.professor)
# Gerar relacionamento UsuarioConselho
if professores:
print(professores)
for professor in professores:
usuario_conselho = UsuarioConselho(usuario=professor,conselho=conselho)
usuario_conselho.save()
# Gerar votacoes dos alunos da turma deste conselho
alunos = Aluno.objects.filter(turma=turma)
for aluno in alunos:
votacao_aluno = Votacao(aluno=aluno,conselho=conselho)
votacao_aluno.save()
#Gerar votos em branco para os professores deste conselho
for professor in professores:
voto_branco = Voto(usuario=professor,votacao=votacao_aluno)
voto_branco.save()
return administracao(request)
@login_required
def iniciarConselho(request):
# Pesquisar e iniciar o conselho
conselho_id = request.POST.get("conselho")
conselho = Conselho.objects.get(id=conselho_id)
conselho.situacao = True
conselho.save()
# Pesquisar e iniciar as votações dos alunos que pertencem à turma deste conselho
alunos = Aluno.objects.filter(turma=conselho.turma)
for aluno in alunos:
votacao_aluno = Votacao.objects.get(aluno=aluno,conselho=conselho)
votacao_aluno.situacao = True
votacao_aluno.save()
return administracao(request)
@login_required
def encerrrarConselho(request):
# Pesquisar e encerrar o conselho
conselho_id = request.POST.get("select")
conselho = Conselho.objects.get(id=conselho_id)
conselho.situacao = False
conselho.save()
# Pesquisar e encerrar as votações dos alunos que pertencem à turma deste conselho
alunos = Aluno.objects.filter(turma=conselho.turma)
for aluno in alunos:
votacao_aluno = Votacao.objects.get(aluno=aluno,conselho=conselho)
votacao_aluno.situacao = False
votacao_aluno.save()
return administracao(request)
def exibirConselho(request, conselho_id):
context = {}
conselho = Conselho.objects.get(id = conselho_id)
votacoes_conselho = conselho.votacoes_conselho.all()
votos_usuario = request.user.votos_usuario.all()
votos_conselho = []
for votacao in votacoes_conselho:
for voto in votacao.votos_votacao.filter(usuario=request.user).filter(votado=False):
votos_conselho.append(voto)
if request.user.is_superuser:
context['votacoes_conselho'] = votacoes_conselho
context['conselho'] = conselho
context['votos_conselho'] = votos_conselho
return render(request,'votacoes/exibirConselho.html',context)
#Views para Votacões
def exibirVoto(request,votacao_id):
context = {}
votacao = Votacao.objects.get(id=votacao_id)
if request.user.is_superuser:
context['votos_aprovar'] = len(votacao.votos_votacao.filter(votado=True).filter(situacao="Aprovar"))
context['votos_reprovar'] = len(votacao.votos_votacao.filter(votado=True).filter(situacao="Reprovar"))
context['votos_abster'] = len(votacao.votos_votacao.filter(votado=True).filter(situacao="Abster"))
context['votos_usuarios'] = votacao.votos_votacao.filter(votado=True)
else:
context['voto'] = votacao.votos_votacao.filter(usuario=request.user).filter(votado=False)[0]
context['votacao'] = votacao
context['conselho'] = votacao.conselho
return render(request,'votacoes/voto.html',context)
def gerarHistoricoAluno(id_aluno):
historico = {}
aluno = Aluno.objects.get(id=aluno_id)
aluno.avaliacoes_aluno.all()
for avaliacao in avaliacoes_aluno:
a+b
return historico
def gerarHistoricoTurma(id_turma):
historico = {}
return historico
def lancarVoto(request,voto_id):
context = {}
voto = Voto.objects.get(id=voto_id)
conselho = voto.votacao.conselho
alunos_conselho = conselho.turma.alunos_turma.all()
voto.situacao = request.POST.get('botao')
voto.votado = True
voto.save()
return exibirConselho(request, conselho.id)
#erros
def error404(request,exception):
return render(request, '404.html', status=404)
def error500(request):
return render(request, '500.html', status=500)
def faq(request):
return render(request, 'faq.html')
|
<filename>votacoes/views.py
from django.contrib.auth.decorators import login_required
from django.http import HttpResponseRedirect
from django.contrib.auth.models import User
from .models import Aluno, AvaliacaoTurma, AvaliacaoAluno, Turma, OfertaDisciplina, Conselho,UsuarioConselho, Votacao, Voto
from django.shortcuts import render, redirect
from datetime import datetime
from .avaliacoes import *
@login_required
def home(request):
context = {}
conselhos_professor=[]
conselhos_abertos = []
conselhos = request.user.conselhos_usuario.all()
for conselho in conselhos:
conselhos_professor.append(conselho.conselho)
for conselho in Conselho.objects.filter(situacao=True):
if conselho in conselhos_professor:
conselhos_abertos.append(conselho)
if request.user.is_superuser:
context['conselhos_abertos'] = Conselho.objects.filter(situacao=True)
else:
context['conselhos_abertos'] = conselhos_abertos
return render(request, 'home.html',context)
# Views que manipulam as avaliações das turmas
@login_required
def avaliacoesTurmas(request):
context = {}
avaliacoes=[]
avaliacoes_lancadas=[]
ofertas = OfertaDisciplina.objects.filter(professor=request.user)
for oferta in ofertas:
avs = AvaliacaoTurma.objects.filter(oferta_disciplina=oferta).filter(status=True)
avs_lancadas = AvaliacaoTurma.objects.filter(oferta_disciplina=oferta).filter(status=False)[:10]
if len(avs_lancadas) > 0:
for avaliacoesLancadas in avs_lancadas:
avaliacoes_lancadas.append(avaliacoesLancadas)
if len(avs) > 0:
for avaliacoesDisciplina in avs:
avaliacoes.append(avaliacoesDisciplina)
context['avaliacoes'] = avaliacoes
context['avaliacoes_lancadas'] = avaliacoes_lancadas
return render(request,'avaliacoes/avaliacoesTurmas.html',context)
@login_required
def criarAvaliacaoTurma(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoTurma.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = DICT_TURMA
return render(request,'avaliacoes/avaliarTurma.html', context)
@login_required
def lancarAvaliacaoTurma(request, avaliacao_id):
soma = 0
selecionadas = request.POST.getlist('checks')
for opcao in selecionadas:
soma += int(opcao)
avaliacao = AvaliacaoTurma.objects.get(pk=avaliacao_id)
avaliacao.status = False
avaliacao.avaliacao = soma
avaliacao.outros_avaliacao = request.POST.get('outros')
avaliacao.save()
return avaliacoesTurmas(request)
@login_required
def visualizarAvaliacaoTurma(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoTurma.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = get_array_turma(avaliacao.avaliacao)
return render(request,'avaliacoes/visualizarAvaliacaoTurma.html', context)
#Views que manipulam as avaliações dos alunos
@login_required
def gerarAvaliacoesTurma(request):
turma = Turma.objects.get(id=request.POST.get("turma"))
bimestre = request.POST.get("bimestre")
alunos = Aluno.objects.filter(turma=turma)
ofertaDisciplinas_turma = OfertaDisciplina.objects.filter(turma=turma)
for disciplina in ofertaDisciplinas_turma:
avaliacaoTurma = AvaliacaoTurma(oferta_disciplina=disciplina,bimestre=bimestre,ano=int(datetime.now().year))
avaliacaoTurma.save()
for aluno in alunos:
avaliacaoAluno = AvaliacaoAluno(oferta_disciplina=disciplina,aluno=aluno,bimestre=bimestre,ano=int(datetime.now().year))
avaliacaoAluno.save()
return administracao(request)
@login_required
def avaliacoesAlunos(request):
context = {}
avaliacoes=[]
avaliacoes_lancadas=[]
ofertas = OfertaDisciplina.objects.filter(professor=request.user)
for oferta in ofertas:
avs = AvaliacaoAluno.objects.filter(oferta_disciplina=oferta).filter(status=True)
avs_lancadas = AvaliacaoAluno.objects.filter(oferta_disciplina=oferta).filter(status=False)[:10]
if len(avs_lancadas) > 0:
for avaliacoesLancadas in avs_lancadas:
avaliacoes_lancadas.append(avaliacoesLancadas)
if len(avs) > 0:
for avaliacoesDisciplina in avs:
avaliacoes.append(avaliacoesDisciplina)
context['avaliacoes'] = avaliacoes
context['avaliacoes_lancadas'] = avaliacoes_lancadas
return render(request,'avaliacoes/avaliacoesAlunos.html',context)
@login_required
def criarAvaliacaoAluno(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoAluno.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = DICT_ALUNO
return render(request,'avaliacoes/avaliarAluno.html', context)
@login_required
def lancarAvaliacaoAluno(request, avaliacao_id):
soma = 0
selecionadas = request.POST.getlist('checks')
for opcao in selecionadas:
soma += int(opcao)
avaliacao = AvaliacaoAluno.objects.get(pk=avaliacao_id)
avaliacao.status = False
avaliacao.avaliacao = soma
avaliacao.outros_avaliacao = request.POST.get('outros')
avaliacao.save()
return avaliacoesAlunos(request)
@login_required
def visualizarAvaliacaoAluno(request, avaliacao_id):
context = {}
avaliacao = AvaliacaoAluno.objects.get(id=avaliacao_id)
context['avaliacao'] = avaliacao
context['opcoes'] = get_array_aluno(avaliacao.avaliacao)
return render(request,'avaliacoes/visualizarAvaliacaoAluno.html', context)
#Views que manipulam a administração
@login_required
def administracao(request):
context = {}
turmas = Turma.objects.all()
conselhosFechados = Conselho.objects.filter(situacao=False)
conselhosAbertos = Conselho.objects.filter(situacao=True)
context['turmas'] = turmas
context['conselhosFechados'] = conselhosFechados
context['conselhosAbertos'] = conselhosAbertos
return render(request,'administracao.html', context)
@login_required
def admin(request):
return HttpResponseRedirect('/admin')
#Views para Conselhos
@login_required
def gerarConselho(request):
# Gerar conselho
turma = Turma.objects.get(id=request.POST.get("turma"))
data = request.POST.get("data")
conselho = Conselho.objects.create(
turma= turma,
data= data,
situacao = False,
)
conselho.save()
#Criar e popular lista de professores que dão aula para essa turma
professores = []
for disciplina in turma.disciplinas_turma.all():
if not disciplina.professor in professores:
professores.append(disciplina.professor)
# Gerar relacionamento UsuarioConselho
if professores:
print(professores)
for professor in professores:
usuario_conselho = UsuarioConselho(usuario=professor,conselho=conselho)
usuario_conselho.save()
# Gerar votacoes dos alunos da turma deste conselho
alunos = Aluno.objects.filter(turma=turma)
for aluno in alunos:
votacao_aluno = Votacao(aluno=aluno,conselho=conselho)
votacao_aluno.save()
#Gerar votos em branco para os professores deste conselho
for professor in professores:
voto_branco = Voto(usuario=professor,votacao=votacao_aluno)
voto_branco.save()
return administracao(request)
@login_required
def iniciarConselho(request):
# Pesquisar e iniciar o conselho
conselho_id = request.POST.get("conselho")
conselho = Conselho.objects.get(id=conselho_id)
conselho.situacao = True
conselho.save()
# Pesquisar e iniciar as votações dos alunos que pertencem à turma deste conselho
alunos = Aluno.objects.filter(turma=conselho.turma)
for aluno in alunos:
votacao_aluno = Votacao.objects.get(aluno=aluno,conselho=conselho)
votacao_aluno.situacao = True
votacao_aluno.save()
return administracao(request)
@login_required
def encerrrarConselho(request):
# Pesquisar e encerrar o conselho
conselho_id = request.POST.get("select")
conselho = Conselho.objects.get(id=conselho_id)
conselho.situacao = False
conselho.save()
# Pesquisar e encerrar as votações dos alunos que pertencem à turma deste conselho
alunos = Aluno.objects.filter(turma=conselho.turma)
for aluno in alunos:
votacao_aluno = Votacao.objects.get(aluno=aluno,conselho=conselho)
votacao_aluno.situacao = False
votacao_aluno.save()
return administracao(request)
def exibirConselho(request, conselho_id):
context = {}
conselho = Conselho.objects.get(id = conselho_id)
votacoes_conselho = conselho.votacoes_conselho.all()
votos_usuario = request.user.votos_usuario.all()
votos_conselho = []
for votacao in votacoes_conselho:
for voto in votacao.votos_votacao.filter(usuario=request.user).filter(votado=False):
votos_conselho.append(voto)
if request.user.is_superuser:
context['votacoes_conselho'] = votacoes_conselho
context['conselho'] = conselho
context['votos_conselho'] = votos_conselho
return render(request,'votacoes/exibirConselho.html',context)
#Views para Votacões
def exibirVoto(request,votacao_id):
context = {}
votacao = Votacao.objects.get(id=votacao_id)
if request.user.is_superuser:
context['votos_aprovar'] = len(votacao.votos_votacao.filter(votado=True).filter(situacao="Aprovar"))
context['votos_reprovar'] = len(votacao.votos_votacao.filter(votado=True).filter(situacao="Reprovar"))
context['votos_abster'] = len(votacao.votos_votacao.filter(votado=True).filter(situacao="Abster"))
context['votos_usuarios'] = votacao.votos_votacao.filter(votado=True)
else:
context['voto'] = votacao.votos_votacao.filter(usuario=request.user).filter(votado=False)[0]
context['votacao'] = votacao
context['conselho'] = votacao.conselho
return render(request,'votacoes/voto.html',context)
def gerarHistoricoAluno(id_aluno):
historico = {}
aluno = Aluno.objects.get(id=aluno_id)
aluno.avaliacoes_aluno.all()
for avaliacao in avaliacoes_aluno:
a+b
return historico
def gerarHistoricoTurma(id_turma):
historico = {}
return historico
def lancarVoto(request,voto_id):
context = {}
voto = Voto.objects.get(id=voto_id)
conselho = voto.votacao.conselho
alunos_conselho = conselho.turma.alunos_turma.all()
voto.situacao = request.POST.get('botao')
voto.votado = True
voto.save()
return exibirConselho(request, conselho.id)
#erros
def error404(request,exception):
return render(request, '404.html', status=404)
def error500(request):
return render(request, '500.html', status=500)
def faq(request):
return render(request, 'faq.html')
|
pt
| 0.954273
|
# Views que manipulam as avaliações das turmas #Views que manipulam as avaliações dos alunos #Views que manipulam a administração #Views para Conselhos # Gerar conselho #Criar e popular lista de professores que dão aula para essa turma # Gerar relacionamento UsuarioConselho # Gerar votacoes dos alunos da turma deste conselho #Gerar votos em branco para os professores deste conselho # Pesquisar e iniciar o conselho # Pesquisar e iniciar as votações dos alunos que pertencem à turma deste conselho # Pesquisar e encerrar o conselho # Pesquisar e encerrar as votações dos alunos que pertencem à turma deste conselho #Views para Votacões #erros
| 2.155288
| 2
|
clippercard/parser.py
|
timroesner/clippercard-python
| 1
|
6625792
|
"""
Copyright (c) 2012-2017 (https://github.com/clippercard/clippercard-python)
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
the Software, and to permit persons to whom the Software is furnished to do so,
subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
import bs4
import collections
import itertools
import re
# === Simple Objects for ClipperCard data ===
_profile_fields = [
'name',
'email',
'address',
'phone'
]
class Profile(collections.namedtuple('Profile', _profile_fields)):
def __str__(self):
return '\n'.join([
'Name: {name}',
'Email: {email}',
'Phone: {phone}',
'Address: {address}'
]).format(**self._asdict())
_product_fields = [
'name', # e.g. Cash value, BART HVD 60/64
'value'
]
class CardProduct(collections.namedtuple('CardProduct', _product_fields)):
def __str__(self):
return '{name}: {value}'.format(**self._asdict())
_card_fields = [
'serial_number',
'nickname',
'type', # Adult, Senior, Youth, Disabled Discount
'status', # Active, Inactive
'products' # a list of CardProduct
]
class Card(collections.namedtuple('Card', _card_fields)):
def __str__(self):
lines = ['{serial_number} "{nickname}" ({type} - {status})'.format(**self._asdict())]
for p in self.products:
lines.append(' - {0}'.format(str(p)))
return '\n'.join(lines)
# === Helpers ===
REGEX_BLING = re.compile('^\$')
REGEX_WHITESPACE = re.compile('\s+')
def cleanup_whitespace(text_content):
"""clean up junk whitespace that comes with every table cell"""
return re.sub(REGEX_WHITESPACE, ' ', text_content.strip())
def get_next_sibling_text(element):
return list(element.next_siblings)[1].get_text()
def get_inner_display_text(element):
return list(element.next_siblings)[1].find(
'span',
attrs={'class': 'displayName'}
).get_text()
def find_values(soup, label_text, value_getter):
values = []
for label_elem in soup.find_all('div', text=label_text):
values.append(value_getter(label_elem))
return values
# === Section Parsers ===
def parse_profile_data(account_page_content):
"""
Parse user profile from /ClipperCard/dashboard.jsf
"""
soup = bs4.BeautifulSoup(account_page_content, "html.parser")
profile_data = soup.find('div', attrs={'class': 'profileData'})
fields = profile_data.find_all('div', attrs={'class': 'fieldData'})
values = [cleanup_whitespace(f.get_text()) for f in fields]
return Profile(
name=values[0],
email=values[1],
address=' '.join(values[2:5]),
phone=values[5]
)
def parse_card_products(card_soup):
"""
Parse card product names and balances from /ClipperCard/dashboard.jsf
"""
section_products = []
for card_section in card_soup.find_all('div', attrs={'class': 'whiteGreyCardBox'}):
products = []
blings = card_section.find_all('div', text=REGEX_BLING)
for value_node in blings:
name = list(value_node.previous_siblings)[1].get_text().strip(':')
products.append(CardProduct(name=name, value=value_node.get_text()))
caltrain = card_section.find_all('div', text=re.compile('^Valid till'))
for value_train in caltrain:
name = list(value_train.previous_siblings)[1].get_text().strip(':')
value_time = value_train.get_text()
products.append(CardProduct(name=name, value=value_time))
section_products.append(products)
return section_products
def parse_cards(account_page_content):
"""
Parse card metadata and product balances from /ClipperCard/dashboard.jsf
"""
begin = account_page_content.index(b'<!--YOUR CLIPPER CARDS-->')
end = account_page_content.index(b'<!--END YOUR CLIPPER CARDS-->')
card_soup = bs4.BeautifulSoup(account_page_content[begin:end], "html.parser")
serial_numbers = find_values(card_soup, 'Serial Number:', get_next_sibling_text)
nicknames = find_values(card_soup, 'Card Nickname:', get_inner_display_text)
types = find_values(card_soup, 'Type:', get_next_sibling_text)
statuses = find_values(card_soup, 'Status:', get_next_sibling_text)
products = parse_card_products(card_soup)
cards = []
for sn, nn, tp, st, pd in zip(serial_numbers, nicknames, types, statuses, products):
cards.append(Card(serial_number=sn, nickname=nn, type=tp, status=st, products=pd))
return cards
|
"""
Copyright (c) 2012-2017 (https://github.com/clippercard/clippercard-python)
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
the Software, and to permit persons to whom the Software is furnished to do so,
subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
import bs4
import collections
import itertools
import re
# === Simple Objects for ClipperCard data ===
_profile_fields = [
'name',
'email',
'address',
'phone'
]
class Profile(collections.namedtuple('Profile', _profile_fields)):
def __str__(self):
return '\n'.join([
'Name: {name}',
'Email: {email}',
'Phone: {phone}',
'Address: {address}'
]).format(**self._asdict())
_product_fields = [
'name', # e.g. Cash value, BART HVD 60/64
'value'
]
class CardProduct(collections.namedtuple('CardProduct', _product_fields)):
def __str__(self):
return '{name}: {value}'.format(**self._asdict())
_card_fields = [
'serial_number',
'nickname',
'type', # Adult, Senior, Youth, Disabled Discount
'status', # Active, Inactive
'products' # a list of CardProduct
]
class Card(collections.namedtuple('Card', _card_fields)):
def __str__(self):
lines = ['{serial_number} "{nickname}" ({type} - {status})'.format(**self._asdict())]
for p in self.products:
lines.append(' - {0}'.format(str(p)))
return '\n'.join(lines)
# === Helpers ===
REGEX_BLING = re.compile('^\$')
REGEX_WHITESPACE = re.compile('\s+')
def cleanup_whitespace(text_content):
"""clean up junk whitespace that comes with every table cell"""
return re.sub(REGEX_WHITESPACE, ' ', text_content.strip())
def get_next_sibling_text(element):
return list(element.next_siblings)[1].get_text()
def get_inner_display_text(element):
return list(element.next_siblings)[1].find(
'span',
attrs={'class': 'displayName'}
).get_text()
def find_values(soup, label_text, value_getter):
values = []
for label_elem in soup.find_all('div', text=label_text):
values.append(value_getter(label_elem))
return values
# === Section Parsers ===
def parse_profile_data(account_page_content):
"""
Parse user profile from /ClipperCard/dashboard.jsf
"""
soup = bs4.BeautifulSoup(account_page_content, "html.parser")
profile_data = soup.find('div', attrs={'class': 'profileData'})
fields = profile_data.find_all('div', attrs={'class': 'fieldData'})
values = [cleanup_whitespace(f.get_text()) for f in fields]
return Profile(
name=values[0],
email=values[1],
address=' '.join(values[2:5]),
phone=values[5]
)
def parse_card_products(card_soup):
"""
Parse card product names and balances from /ClipperCard/dashboard.jsf
"""
section_products = []
for card_section in card_soup.find_all('div', attrs={'class': 'whiteGreyCardBox'}):
products = []
blings = card_section.find_all('div', text=REGEX_BLING)
for value_node in blings:
name = list(value_node.previous_siblings)[1].get_text().strip(':')
products.append(CardProduct(name=name, value=value_node.get_text()))
caltrain = card_section.find_all('div', text=re.compile('^Valid till'))
for value_train in caltrain:
name = list(value_train.previous_siblings)[1].get_text().strip(':')
value_time = value_train.get_text()
products.append(CardProduct(name=name, value=value_time))
section_products.append(products)
return section_products
def parse_cards(account_page_content):
"""
Parse card metadata and product balances from /ClipperCard/dashboard.jsf
"""
begin = account_page_content.index(b'<!--YOUR CLIPPER CARDS-->')
end = account_page_content.index(b'<!--END YOUR CLIPPER CARDS-->')
card_soup = bs4.BeautifulSoup(account_page_content[begin:end], "html.parser")
serial_numbers = find_values(card_soup, 'Serial Number:', get_next_sibling_text)
nicknames = find_values(card_soup, 'Card Nickname:', get_inner_display_text)
types = find_values(card_soup, 'Type:', get_next_sibling_text)
statuses = find_values(card_soup, 'Status:', get_next_sibling_text)
products = parse_card_products(card_soup)
cards = []
for sn, nn, tp, st, pd in zip(serial_numbers, nicknames, types, statuses, products):
cards.append(Card(serial_number=sn, nickname=nn, type=tp, status=st, products=pd))
return cards
|
en
| 0.749832
|
Copyright (c) 2012-2017 (https://github.com/clippercard/clippercard-python) Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # === Simple Objects for ClipperCard data === # e.g. Cash value, BART HVD 60/64 # Adult, Senior, Youth, Disabled Discount # Active, Inactive # a list of CardProduct # === Helpers === clean up junk whitespace that comes with every table cell # === Section Parsers === Parse user profile from /ClipperCard/dashboard.jsf Parse card product names and balances from /ClipperCard/dashboard.jsf Parse card metadata and product balances from /ClipperCard/dashboard.jsf
| 2.242225
| 2
|
examples/et312-info.py
|
nannook206/buttshock-py
| 1
|
6625793
|
#!/bin/python3
#
# Examples:
# python3 info.py -p /dev/ttyUSB0
#
import sys
import fcntl
import argparse
from time import sleep
sys.path.append("../")
import buttshock.et312
def main():
modes = {0x76:"Waves", 0x77:"Stroke", 0x78:"Climb", 0x79:"Combo", 0x7a:"Intense", 0x7b:"Rhythm",
0x7c:"Audio1",0x7d:"Audio2", 0x7e:"Audio3", 0x80:"Random1", 0x81:"Random2", 0x82:"Toggle",
0x83:"Orgasm",0x84:"Torment",0x85:"Phase1",0x86:"Phase2",0x87:"Phase3",
0x88:"User1",0x89:"User2",0x8a:"User3",0x8b:"User4",0x8c:"User5",0:"None", 0x7f:"Split"}
powerlevels = {1:"Low (1)",2:"Normal (2)",3:"High (3)"}
parser = argparse.ArgumentParser()
parser.add_argument("-p","--port",dest="port",help="Port for ET312 (default /dev/ttyUSB0)")
args = parser.parse_args()
port = "/dev/ttyUSB0" # lazy default
if (args.port):
port = args.port
# Lock the serial port while we use it, wait a few seconds
connected = False
for _ in range(10):
try:
et312 = buttshock.et312.ET312SerialSync(port)
if et312.port.isOpen():
fcntl.flock(et312.port.fileno(), fcntl.LOCK_EX | fcntl.LOCK_NB)
connected = True
break
except Exception as e:
print(e)
sleep(.2)
if (not connected):
print ("Failed")
return
try:
print ("[+] connected")
# no need to do a handshake unless we want to poke
# print ("[+] trying handshake")
# et312.perform_handshake()
# print ("[+] handshake ok")
print("ADC0 (current sense)\t\t: {0:#x}".format(et312.read(0x4060)))
print("ADC1 (MA knob)\t\t\t: {0:#x}".format(et312.read(0x4061)))
print("\tMA scaled value\t\t: %d (mode range %d-%d)" %(et312.read(0x420d),et312.read(0x4086),et312.read(0x4087)))
print("ADC2 (PSU voltage)\t\t: {0:#x}".format(et312.read(0x4062)))
print("ADC3 (Battery voltage)\t\t: {0:#x}".format(et312.read(0x4063)))
print("\tBattery at boot\t\t: {0:.1f}%".format((et312.read(0x4203))*100/256))
print("ADC4 (Level A knob)\t\t: {0:#x}".format(et312.read(0x4064)))
print("ADC5 (Level B knob)\t\t: {0:#x}".format(et312.read(0x4065)))
currentmode =et312.read(0x407b)
print("Power Level\t\t\t: "+powerlevels[et312.read(0x41f4)])
usermodes = et312.read(0x41f3)-0x87
print("User programs loaded\t\t: {0:#d}".format(usermodes))
for i in range (0,usermodes):
startmodule = et312.read(0x8018+i)
if (startmodule < 0xa0):
programlookup = et312.read(0x8000+startmodule-0x60)
programblockstart = 0x8040+programlookup
else:
programlookup = et312.read(0x8000+startmodule-0xa0)
programblockstart = 0x8100+programlookup
print("\tUser %d is module 0x%02x\t: 0x%04x (eeprom)"%(i+1,startmodule,programblockstart))
print("Current Mode\t\t\t: "+modes[currentmode])
if (currentmode == 0x7f):
print("\tSplit Mode A\t\t: "+modes[et312.read(0x41f5)])
print("\tSplit Mode B\t\t: "+modes[et312.read(0x41f6)])
if (currentmode == 0x80):
print("\tCurrent Random Mode\t: "+modes[et312.read(0x4074)])
timeleft = et312.read(0x4075) - et312.read(0x406a)
if (timeleft<0):
timeleft+=256
print("\tTime until change mode\t: {0:#d} seconds ".format(int(timeleft/1.91)))
print("\tMode has been running\t: {0:#d} seconds".format(int((et312.read(0x4089)+et312.read(0x408a)*256)*1.048)))
except Exception as e:
print(e)
if (et312):
print("[+] resetting key")
et312.reset_key() # reset cipher key so easy resync next time
et312.close()
if __name__ == "__main__":
main()
|
#!/bin/python3
#
# Examples:
# python3 info.py -p /dev/ttyUSB0
#
import sys
import fcntl
import argparse
from time import sleep
sys.path.append("../")
import buttshock.et312
def main():
modes = {0x76:"Waves", 0x77:"Stroke", 0x78:"Climb", 0x79:"Combo", 0x7a:"Intense", 0x7b:"Rhythm",
0x7c:"Audio1",0x7d:"Audio2", 0x7e:"Audio3", 0x80:"Random1", 0x81:"Random2", 0x82:"Toggle",
0x83:"Orgasm",0x84:"Torment",0x85:"Phase1",0x86:"Phase2",0x87:"Phase3",
0x88:"User1",0x89:"User2",0x8a:"User3",0x8b:"User4",0x8c:"User5",0:"None", 0x7f:"Split"}
powerlevels = {1:"Low (1)",2:"Normal (2)",3:"High (3)"}
parser = argparse.ArgumentParser()
parser.add_argument("-p","--port",dest="port",help="Port for ET312 (default /dev/ttyUSB0)")
args = parser.parse_args()
port = "/dev/ttyUSB0" # lazy default
if (args.port):
port = args.port
# Lock the serial port while we use it, wait a few seconds
connected = False
for _ in range(10):
try:
et312 = buttshock.et312.ET312SerialSync(port)
if et312.port.isOpen():
fcntl.flock(et312.port.fileno(), fcntl.LOCK_EX | fcntl.LOCK_NB)
connected = True
break
except Exception as e:
print(e)
sleep(.2)
if (not connected):
print ("Failed")
return
try:
print ("[+] connected")
# no need to do a handshake unless we want to poke
# print ("[+] trying handshake")
# et312.perform_handshake()
# print ("[+] handshake ok")
print("ADC0 (current sense)\t\t: {0:#x}".format(et312.read(0x4060)))
print("ADC1 (MA knob)\t\t\t: {0:#x}".format(et312.read(0x4061)))
print("\tMA scaled value\t\t: %d (mode range %d-%d)" %(et312.read(0x420d),et312.read(0x4086),et312.read(0x4087)))
print("ADC2 (PSU voltage)\t\t: {0:#x}".format(et312.read(0x4062)))
print("ADC3 (Battery voltage)\t\t: {0:#x}".format(et312.read(0x4063)))
print("\tBattery at boot\t\t: {0:.1f}%".format((et312.read(0x4203))*100/256))
print("ADC4 (Level A knob)\t\t: {0:#x}".format(et312.read(0x4064)))
print("ADC5 (Level B knob)\t\t: {0:#x}".format(et312.read(0x4065)))
currentmode =et312.read(0x407b)
print("Power Level\t\t\t: "+powerlevels[et312.read(0x41f4)])
usermodes = et312.read(0x41f3)-0x87
print("User programs loaded\t\t: {0:#d}".format(usermodes))
for i in range (0,usermodes):
startmodule = et312.read(0x8018+i)
if (startmodule < 0xa0):
programlookup = et312.read(0x8000+startmodule-0x60)
programblockstart = 0x8040+programlookup
else:
programlookup = et312.read(0x8000+startmodule-0xa0)
programblockstart = 0x8100+programlookup
print("\tUser %d is module 0x%02x\t: 0x%04x (eeprom)"%(i+1,startmodule,programblockstart))
print("Current Mode\t\t\t: "+modes[currentmode])
if (currentmode == 0x7f):
print("\tSplit Mode A\t\t: "+modes[et312.read(0x41f5)])
print("\tSplit Mode B\t\t: "+modes[et312.read(0x41f6)])
if (currentmode == 0x80):
print("\tCurrent Random Mode\t: "+modes[et312.read(0x4074)])
timeleft = et312.read(0x4075) - et312.read(0x406a)
if (timeleft<0):
timeleft+=256
print("\tTime until change mode\t: {0:#d} seconds ".format(int(timeleft/1.91)))
print("\tMode has been running\t: {0:#d} seconds".format(int((et312.read(0x4089)+et312.read(0x408a)*256)*1.048)))
except Exception as e:
print(e)
if (et312):
print("[+] resetting key")
et312.reset_key() # reset cipher key so easy resync next time
et312.close()
if __name__ == "__main__":
main()
|
en
| 0.208008
|
#!/bin/python3 # # Examples: # python3 info.py -p /dev/ttyUSB0 # # lazy default # Lock the serial port while we use it, wait a few seconds # no need to do a handshake unless we want to poke # print ("[+] trying handshake") # et312.perform_handshake() # print ("[+] handshake ok") #x}".format(et312.read(0x4060))) #x}".format(et312.read(0x4061))) #x}".format(et312.read(0x4062))) #x}".format(et312.read(0x4063))) #x}".format(et312.read(0x4064))) #x}".format(et312.read(0x4065))) #d}".format(usermodes)) #d} seconds ".format(int(timeleft/1.91))) #d} seconds".format(int((et312.read(0x4089)+et312.read(0x408a)*256)*1.048))) # reset cipher key so easy resync next time
| 2.446251
| 2
|
blackjack_test.py
|
coolioasjulio/reinforcement-learning-playground
| 0
|
6625794
|
from keras.models import load_model
import gym
import numpy as np
model = load_model('models/dqn_Blackjack-v0-43.h5')
ENV_NAME = 'Blackjack-v0'
# Get the environment and extract the number of actions.
env = gym.make(ENV_NAME)
def debug(msg, enabled):
if enabled:
print(msg)
def play_game(debug_enabled=True):
done = False
score, dealer, usable = env.reset()
reward = 0
debug('Start!\nScore: %s, Dealer: %s, Usable Ace: %s' % (score, dealer, bool(usable)), debug_enabled)
while not done:
action = np.argmax(model.predict(np.expand_dims([[score, dealer, usable]], axis=0))[0])
(score, dealer, usable), reward, done, _ = env.step(action)
debug('\nAction: %s' % ('hit' if action == 1 else 'stick'), debug_enabled)
debug('Score: %s, Dealer: %s, Usable Ace: %s' % (score, dealer, bool(usable)), debug_enabled)
if reward < 0:
debug('Lost!', debug_enabled)
elif reward > 0:
debug('Won!', debug_enabled)
else:
debug('Tie!', debug_enabled)
return reward > 0, reward == 0, reward < 0
win_sum, tie_sum, lose_sum = 0, 0, 0
n_games = 1000
for i in range(n_games):
result = play_game(False)
win_sum += 1 if result[0] else 0
tie_sum += 1 if result[1] else 0
lose_sum += 1 if result[2] else 0
print('Win: %.2f, Tie: %.2f, Lose: %.2f' % (100 * win_sum / n_games, 100 * tie_sum / n_games, 100 * lose_sum / n_games))
|
from keras.models import load_model
import gym
import numpy as np
model = load_model('models/dqn_Blackjack-v0-43.h5')
ENV_NAME = 'Blackjack-v0'
# Get the environment and extract the number of actions.
env = gym.make(ENV_NAME)
def debug(msg, enabled):
if enabled:
print(msg)
def play_game(debug_enabled=True):
done = False
score, dealer, usable = env.reset()
reward = 0
debug('Start!\nScore: %s, Dealer: %s, Usable Ace: %s' % (score, dealer, bool(usable)), debug_enabled)
while not done:
action = np.argmax(model.predict(np.expand_dims([[score, dealer, usable]], axis=0))[0])
(score, dealer, usable), reward, done, _ = env.step(action)
debug('\nAction: %s' % ('hit' if action == 1 else 'stick'), debug_enabled)
debug('Score: %s, Dealer: %s, Usable Ace: %s' % (score, dealer, bool(usable)), debug_enabled)
if reward < 0:
debug('Lost!', debug_enabled)
elif reward > 0:
debug('Won!', debug_enabled)
else:
debug('Tie!', debug_enabled)
return reward > 0, reward == 0, reward < 0
win_sum, tie_sum, lose_sum = 0, 0, 0
n_games = 1000
for i in range(n_games):
result = play_game(False)
win_sum += 1 if result[0] else 0
tie_sum += 1 if result[1] else 0
lose_sum += 1 if result[2] else 0
print('Win: %.2f, Tie: %.2f, Lose: %.2f' % (100 * win_sum / n_games, 100 * tie_sum / n_games, 100 * lose_sum / n_games))
|
en
| 0.877973
|
# Get the environment and extract the number of actions.
| 2.480184
| 2
|
tests/__init__.py
|
OpenEntityMap/oem-client
| 0
|
6625795
|
from __future__ import absolute_import, division, print_function
import logging
logging.basicConfig(level=logging.DEBUG)
|
from __future__ import absolute_import, division, print_function
import logging
logging.basicConfig(level=logging.DEBUG)
|
none
| 1
| 1.214142
| 1
|
|
examples/wrappers.py
|
paolodelia99/py-pacman
| 4
|
6625796
|
<filename>examples/wrappers.py
import gym
import torch
import numpy as np
import torchvision.transforms as T
from gym.spaces import Box
class SkipFrame(gym.Wrapper):
def __init__(self, env, skip):
"""Return only every `skip`-th frame"""
super().__init__(env)
self._skip = skip
def step(self, action):
"""Repeat action, and sum reward"""
total_reward = 0.0
done = False
for i in range(self._skip):
# Accumulate reward and repeat the same action
obs, reward, done, info = self.env.step(action)
total_reward += reward
if done:
break
return obs, total_reward, done, info
class GrayScaleObservation(gym.ObservationWrapper):
def __init__(self, env):
super().__init__(env)
obs_shape = self.observation_space.shape[:2]
self.observation_space = Box(low=0, high=255, shape=obs_shape, dtype=np.uint8)
def permute_orientation(self, observation):
# permute [H, W, C] array to [C, H, W] tensor
observation = np.transpose(observation, (2, 0, 1))
observation = torch.tensor(observation.copy(), dtype=torch.float)
return observation
def observation(self, observation):
observation = self.permute_orientation(observation)
transform = T.Grayscale()
observation = transform(observation)
return observation
class ResizeObservation(gym.ObservationWrapper):
def __init__(self, env, shape):
super().__init__(env)
if isinstance(shape, int):
self.shape = (shape, shape)
else:
self.shape = tuple(shape)
obs_shape = self.shape + self.observation_space.shape[2:]
self.observation_space = Box(low=0, high=255, shape=obs_shape, dtype=np.uint8)
def observation(self, observation):
transforms = T.Compose(
[T.Resize(self.shape), T.Normalize(0, 255)]
)
observation = transforms(observation).squeeze(0)
return observation
|
<filename>examples/wrappers.py
import gym
import torch
import numpy as np
import torchvision.transforms as T
from gym.spaces import Box
class SkipFrame(gym.Wrapper):
def __init__(self, env, skip):
"""Return only every `skip`-th frame"""
super().__init__(env)
self._skip = skip
def step(self, action):
"""Repeat action, and sum reward"""
total_reward = 0.0
done = False
for i in range(self._skip):
# Accumulate reward and repeat the same action
obs, reward, done, info = self.env.step(action)
total_reward += reward
if done:
break
return obs, total_reward, done, info
class GrayScaleObservation(gym.ObservationWrapper):
def __init__(self, env):
super().__init__(env)
obs_shape = self.observation_space.shape[:2]
self.observation_space = Box(low=0, high=255, shape=obs_shape, dtype=np.uint8)
def permute_orientation(self, observation):
# permute [H, W, C] array to [C, H, W] tensor
observation = np.transpose(observation, (2, 0, 1))
observation = torch.tensor(observation.copy(), dtype=torch.float)
return observation
def observation(self, observation):
observation = self.permute_orientation(observation)
transform = T.Grayscale()
observation = transform(observation)
return observation
class ResizeObservation(gym.ObservationWrapper):
def __init__(self, env, shape):
super().__init__(env)
if isinstance(shape, int):
self.shape = (shape, shape)
else:
self.shape = tuple(shape)
obs_shape = self.shape + self.observation_space.shape[2:]
self.observation_space = Box(low=0, high=255, shape=obs_shape, dtype=np.uint8)
def observation(self, observation):
transforms = T.Compose(
[T.Resize(self.shape), T.Normalize(0, 255)]
)
observation = transforms(observation).squeeze(0)
return observation
|
en
| 0.71435
|
Return only every `skip`-th frame Repeat action, and sum reward # Accumulate reward and repeat the same action # permute [H, W, C] array to [C, H, W] tensor
| 2.494882
| 2
|
idseq_pipeline/commands/postprocess_functions.py
|
cdebourcy/idseq-pipeline
| 0
|
6625797
|
<filename>idseq_pipeline/commands/postprocess_functions.py
import os
import subprocess
import json
import shelve
import logging
import idseq_pipeline.commands.accessionid2seq_functions as accessionid2seq_functions
from .common import * #pylint: disable=wildcard-import
# data directories
# from common import ROOT_DIR
# from common import REF_DIR
DEST_DIR = ROOT_DIR + '/idseq/data' # generated data go here
TEMP_DIR = ROOT_DIR + '/tmp' # tmp directory with a lot of space for sorting large files
# arguments from environment variables
INPUT_BUCKET = os.environ.get('INPUT_BUCKET')
OUTPUT_BUCKET = os.environ.get('OUTPUT_BUCKET')
AWS_BATCH_JOB_ID = os.environ.get('AWS_BATCH_JOB_ID', 'local')
SAMPLE_S3_INPUT_PATH = INPUT_BUCKET.rstrip('/')
SAMPLE_S3_OUTPUT_PATH = OUTPUT_BUCKET.rstrip('/')
sample_name = SAMPLE_S3_INPUT_PATH[5:].rstrip('/').replace('/', '-')
SAMPLE_DIR = DEST_DIR + '/' + sample_name
INPUT_DIR = SAMPLE_DIR + '/inputs'
RESULT_DIR = SAMPLE_DIR + '/results'
NT_LOC_DB = os.environ.get('NT_LOC_DB',
"s3://idseq-database/20170824/blast_db/nt_loc.db")
NT_DB = os.environ.get('NT_DB', "s3://idseq-database/20170824/blast_db/nt")
# input files
ACCESSION_ANNOTATED_FASTA = 'accessions.rapsearch2.gsnapl.fasta'
GSNAP_M8_FILE = 'dedup.multihit.gsnapl.unmapped.bowtie2.lzw.cdhitdup.priceseqfilter.unmapped.star.m8'
SUMMARY_MULTIHIT_GSNAPL_OUT = 'summary.multihit.gsnapl.unmapped.bowtie2.lzw.cdhitdup.priceseqfilter.unmapped.star.tab'
SUMMARY_MULTIHIT_RAPSEARCH_OUT = 'summary.multihit.rapsearch2.filter.deuterostomes.taxids.gsnapl.unmapped.bowtie2.lzw.cdhitdup.priceseqfilter.unmapped.star.tab'
# output files
TAXID_ANNOT_FASTA = 'taxid_annot.fasta'
TAXID_ANNOT_SORTED_FASTA_NT = 'taxid_annot_sorted_nt.fasta'
TAXID_ANNOT_SORTED_FASTA_NR = 'taxid_annot_sorted_nr.fasta'
TAXID_ANNOT_SORTED_FASTA_GENUS_NT = 'taxid_annot_sorted_genus_nt.fasta'
TAXID_ANNOT_SORTED_FASTA_GENUS_NR = 'taxid_annot_sorted_genus_nr.fasta'
TAXID_ANNOT_SORTED_FASTA_FAMILY_NT = 'taxid_annot_sorted_family_nt.fasta'
TAXID_ANNOT_SORTED_FASTA_FAMILY_NR = 'taxid_annot_sorted_family_nr.fasta'
TAXID_LOCATIONS_JSON_NT = 'taxid_locations_nt.json'
TAXID_LOCATIONS_JSON_NR = 'taxid_locations_nr.json'
TAXID_LOCATIONS_JSON_GENUS_NT = 'taxid_locations_genus_nt.json'
TAXID_LOCATIONS_JSON_GENUS_NR = 'taxid_locations_genus_nr.json'
TAXID_LOCATIONS_JSON_FAMILY_NT = 'taxid_locations_family_nt.json'
TAXID_LOCATIONS_JSON_FAMILY_NR = 'taxid_locations_family_nr.json'
TAXID_LOCATIONS_JSON_ALL = 'taxid_locations_combined.json'
LOGS_OUT_BASENAME = 'postprocess-log'
ALIGN_VIZ_DIR = 'align_viz'
# target outputs by task
TARGET_OUTPUTS = {
"run_generate_taxid_fasta_from_hit_summaries":
[os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA)],
"run_generate_taxid_locator__1": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NT)
],
"run_generate_taxid_locator__2": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NR)
],
"run_generate_taxid_locator__3": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NT)
],
"run_generate_taxid_locator__4": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NR)
],
"run_generate_taxid_locator__5": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NT)
],
"run_generate_taxid_locator__6": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NR)
],
"run_combine_json": [os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_ALL)],
"run_generate_align_viz":
[os.path.join(RESULT_DIR, "%s.summary" % ALIGN_VIZ_DIR)]
}
# Processing functions
def remove_annotation(read_id):
result = re.sub(r'NT:(.*?):', '', read_id)
result = re.sub(r'NR:(.*?):', '', result)
return result
def parse_hits(hit_summary_files):
"""Return map of {NT, NR} => read_id => (hit_taxid_str, hit_level_str)"""
valid_hits = {}
for count_type, summary_file in hit_summary_files.items():
hits = {}
with open(summary_file, "rb") as sf:
for hit_line in sf:
hit_line_columns = hit_line.strip().split("\t")
if len(hit_line_columns) >= 3:
hit_read_id = hit_line_columns[0]
hit_level_str = hit_line_columns[1]
hit_taxid_str = hit_line_columns[2]
hits[hit_read_id] = (hit_taxid_str, hit_level_str)
valid_hits[count_type] = hits
return valid_hits
def generate_taxid_fasta_from_hit_summaries(
input_fasta_file, hit_summary_files, lineage_path, output_fasta_file):
"""Intermediate conversion step that includes handling of non-specific
hits with artificial tax_ids.
"""
lineage_map = shelve.open(lineage_path)
valid_hits = parse_hits(hit_summary_files)
def get_valid_lineage(read_id, count_type):
# If the read aligned to something, then it would be present in the
# summary file for count type, and correspondingly in valid_hits[
# count_type], even if the hits disagree so much that the
# "valid_hits" entry is just ("-1", "-1"). If the read didn't align
# to anything, we also represent that with ("-1", "-1"). This ("-1",
# "-1") gets translated to NULL_LINEAGE.
hit_taxid_str, hit_level_str = valid_hits[count_type].get(
read_id, ("-1", "-1"))
hit_lineage = lineage_map.get(hit_taxid_str, NULL_LINEAGE)
return validate_taxid_lineage(hit_lineage, hit_taxid_str,
hit_level_str)
input_fasta_f = open(input_fasta_file, 'rb')
output_fasta_f = open(output_fasta_file, 'wb')
sequence_name = input_fasta_f.readline()
sequence_data = input_fasta_f.readline()
while len(sequence_name) > 0 and len(sequence_data) > 0:
# Example read_id: "NR::NT:CP010376.2:NB501961:14:HM7TLBGX2:1:23109
# :12720:8743/2"
# Translate the read information into our custom format with fake
# taxids.
accession_annotated_read_id = sequence_name.rstrip().lstrip('>')
read_id = accession_annotated_read_id.split(":", 4)[-1]
nr_taxid_species, nr_taxid_genus, nr_taxid_family = get_valid_lineage(
read_id, 'NR')
nt_taxid_species, nt_taxid_genus, nt_taxid_family = get_valid_lineage(
read_id, 'NT')
family_str = 'family_nr:' + nr_taxid_family + ':family_nt:' + nt_taxid_family
genus_str = ':genus_nr:' + nr_taxid_genus + ':genus_nt:' + nt_taxid_genus
species_str = ':species_nr:' + nr_taxid_species + ':species_nt:' + nt_taxid_species
new_read_name = (family_str + genus_str + species_str + ':' +
accession_annotated_read_id)
output_fasta_f.write(">%s\n" % new_read_name)
output_fasta_f.write(sequence_data)
sequence_name = input_fasta_f.readline()
sequence_data = input_fasta_f.readline()
input_fasta_f.close()
output_fasta_f.close()
def get_taxid(sequence_name, taxid_field):
parts = sequence_name.replace('>', ':').split(":%s:" % taxid_field)
if len(parts) <= 1:
# Sequence_name empty or taxid_field not found
return 'none'
taxid = parts[1].split(":")[0]
# Example sequence_name: ">nr:-100:nt:684552:NR::NT:LT629734.1:HWI-ST640
# :828:H917FADXX:2:1101:1424:15119/1"
return taxid
def get_taxid_field_num(taxid_field, input_fasta):
with open(input_fasta) as f:
sequence_name = f.readline()
return sequence_name.replace('>', ':').split(":").index(taxid_field) + 1
def generate_taxid_locator(input_fasta, taxid_field, hit_type, output_fasta,
output_json):
taxid_field_num = get_taxid_field_num(taxid_field, input_fasta)
# Put every 2-line fasta record on a single line with delimiter
# ":lineseparator:":
cmd = "awk 'NR % 2 == 1 { o=$0 ; next } { print o \":lineseparator:\" $0 }' " + input_fasta
# Sort the records based on the field containing the taxids
cmd += " | sort -T %s --key %s --field-separator ':' --numeric-sort" % (
TEMP_DIR, taxid_field_num)
# Split every record back over 2 lines
cmd += " | sed 's/:lineseparator:/\\n/g' > %s" % output_fasta
subprocess.check_output(cmd, shell=True)
# Make JSON file giving the byte range of the file corresponding to each
# taxid
taxon_sequence_locations = []
f = open(output_fasta, 'rb')
sequence_name = f.readline()
sequence_data = f.readline()
taxid = get_taxid(sequence_name, taxid_field)
first_byte = 0
end_byte = first_byte + len(sequence_name) + len(sequence_data)
while len(sequence_name) > 0 and len(sequence_data) > 0:
sequence_name = f.readline()
sequence_data = f.readline()
new_taxid = get_taxid(sequence_name, taxid_field)
if new_taxid != taxid:
# Note on boundary condition: when end of file is reached, then
# sequence_name == '' => new_taxid == 'none' => new_taxid != taxid
# so last record will be written to output correctly.
taxon_sequence_locations.append({
'taxid': int(taxid),
'first_byte': first_byte,
'last_byte': end_byte - 1,
'hit_type': hit_type
})
taxid = new_taxid
first_byte = end_byte
end_byte = first_byte + len(sequence_name) + len(sequence_data)
else:
end_byte += len(sequence_name) + len(sequence_data)
f.close()
with open(output_json, 'wb') as f:
json.dump(taxon_sequence_locations, f)
def combine_json(input_json_list, output_json):
output = []
for input_json in input_json_list:
with open(input_json) as f:
output.extend(json.load(f))
with open(output_json, 'wb') as outf:
json.dump(output, outf)
# Job functions
def run_generate_align_viz(input_fasta, input_m8, output_dir):
write_to_log("Generating alignment visualization...")
nt_loc_db = fetch_reference(NT_LOC_DB)
summary_file_name = accessionid2seq_functions.generate_alignment_viz_json(
NT_DB, nt_loc_db, "NT", input_m8, input_fasta, output_dir)
# Copy the data over
cmd = "aws s3 cp --quiet %s %s/align_viz --recursive" % (
output_dir, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
cmd = "aws s3 cp --quiet %s %s/" % (summary_file_name,
SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_generate_taxid_fasta_from_hit_summaries(input_fasta, hit_summary_files,
output_fasta):
write_to_log("Generating tax_id FASTA from hit summaries...")
lineage_path = fetch_reference(LINEAGE_SHELF)
generate_taxid_fasta_from_hit_summaries(input_fasta, hit_summary_files,
lineage_path, output_fasta)
logging.getLogger().info("finished job")
cmd = "aws s3 cp --quiet %s %s/" % (output_fasta, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_generate_taxid_locator(input_fasta, taxid_field, hit_type,
output_fasta, output_json):
write_to_log("Generating tax_id locator...")
generate_taxid_locator(input_fasta, taxid_field, hit_type, output_fasta,
output_json)
logging.getLogger().info("finished job")
cmd = "aws s3 cp --quiet %s %s/" % (output_fasta, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
cmd = "aws s3 cp --quiet %s %s/" % (output_json, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_combine_json(input_json_list, output_json):
write_to_log("Combining JSON files...")
combine_json(input_json_list, output_json)
logging.getLogger().info("finished job")
cmd = "aws s3 cp --quiet %s %s/" % (output_json, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_stage3(lazy_run=False):
assert not lazy_run, "run_stage3 was called with lazy_run"
# Make data directories
execute_command("mkdir -p %s %s %s %s" % (SAMPLE_DIR, RESULT_DIR, REF_DIR,
TEMP_DIR))
# Configure logger
log_file = "%s/%s.%s.txt" % (RESULT_DIR, LOGS_OUT_BASENAME,
AWS_BATCH_JOB_ID)
configure_logger(log_file)
print("Starting stage...")
# Download input
execute_command("aws s3 cp --quiet %s/%s %s/" %
(SAMPLE_S3_INPUT_PATH, ACCESSION_ANNOTATED_FASTA,
INPUT_DIR))
input_file = os.path.join(INPUT_DIR, ACCESSION_ANNOTATED_FASTA)
# Download m8
execute_command("aws s3 cp --quiet %s/%s %s/" % (SAMPLE_S3_INPUT_PATH,
GSNAP_M8_FILE, INPUT_DIR))
input_m8 = os.path.join(INPUT_DIR, GSNAP_M8_FILE)
# Download hit level files
hit_summary_files = {
'NT': os.path.join(INPUT_DIR, SUMMARY_MULTIHIT_GSNAPL_OUT),
'NR': os.path.join(INPUT_DIR, SUMMARY_MULTIHIT_RAPSEARCH_OUT)
}
for local_file in hit_summary_files.values():
execute_command("aws s3 cp --quiet %s/%s %s/" %
(SAMPLE_S3_INPUT_PATH, os.path.basename(local_file),
INPUT_DIR))
def s3_out_and_title(title):
return {"sample_s3_output_path": SAMPLE_S3_OUTPUT_PATH, "title": title}
# Ex: run_and_log(log_params, target_outputs, lazy_run, func_name, *args)
# TODO: Get rid of run_and_log pattern for simplification
# Generate taxid fasta
log_params = s3_out_and_title(
"run_generate_taxid_fasta_from_hit_summaries")
run_and_log(log_params,
TARGET_OUTPUTS["run_generate_taxid_fasta_from_hit_summaries"],
False, run_generate_taxid_fasta_from_hit_summaries, input_file,
hit_summary_files, os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA))
# SPECIES level
# Generate taxid locator for NT
log_params = s3_out_and_title(
"run_generate_taxid_locator for NT")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__1"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR,
TAXID_ANNOT_FASTA), 'species_nt', 'NT',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NT))
# Generate taxid locator for NR
log_params = s3_out_and_title(
"run_generate_taxid_locator for NR")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__2"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR,
TAXID_ANNOT_FASTA), 'species_nr', 'NR',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NR))
# GENUS level
# Generate taxid locator for NT
log_params = s3_out_and_title(
"run_generate_taxid_locator for NT")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__3"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'genus_nt', 'NT',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NT))
# Generate taxid locator for NR
log_params = s3_out_and_title(
"run_generate_taxid_locator for NR")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__4"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'genus_nr', 'NR',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NR))
# FAMILY level
# Generate taxid locator for NT
log_params = s3_out_and_title(
"run_generate_taxid_locator for NT")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__5"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'family_nt', 'NT',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NT))
# Generate taxid locator for NR
log_params = s3_out_and_title(
"run_generate_taxid_locator for NR")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__6"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'family_nr', 'NR',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NR))
# Generate alignment visualization
log_params = s3_out_and_title("run_generate_align_viz")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_align_viz"], False,
run_generate_align_viz,
os.path.join(RESULT_DIR,
TAXID_ANNOT_SORTED_FASTA_NT), input_m8,
os.path.join(RESULT_DIR, ALIGN_VIZ_DIR))
# Combine results
log_params = s3_out_and_title("run_combine_json")
input_files_basenames = [
TAXID_LOCATIONS_JSON_NT, TAXID_LOCATIONS_JSON_NR,
TAXID_LOCATIONS_JSON_GENUS_NT, TAXID_LOCATIONS_JSON_GENUS_NR,
TAXID_LOCATIONS_JSON_FAMILY_NT, TAXID_LOCATIONS_JSON_FAMILY_NR
]
input_files = [os.path.join(RESULT_DIR, f) for f in input_files_basenames]
run_and_log(log_params, TARGET_OUTPUTS["run_combine_json"], False,
run_combine_json, input_files,
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_ALL))
|
<filename>idseq_pipeline/commands/postprocess_functions.py
import os
import subprocess
import json
import shelve
import logging
import idseq_pipeline.commands.accessionid2seq_functions as accessionid2seq_functions
from .common import * #pylint: disable=wildcard-import
# data directories
# from common import ROOT_DIR
# from common import REF_DIR
DEST_DIR = ROOT_DIR + '/idseq/data' # generated data go here
TEMP_DIR = ROOT_DIR + '/tmp' # tmp directory with a lot of space for sorting large files
# arguments from environment variables
INPUT_BUCKET = os.environ.get('INPUT_BUCKET')
OUTPUT_BUCKET = os.environ.get('OUTPUT_BUCKET')
AWS_BATCH_JOB_ID = os.environ.get('AWS_BATCH_JOB_ID', 'local')
SAMPLE_S3_INPUT_PATH = INPUT_BUCKET.rstrip('/')
SAMPLE_S3_OUTPUT_PATH = OUTPUT_BUCKET.rstrip('/')
sample_name = SAMPLE_S3_INPUT_PATH[5:].rstrip('/').replace('/', '-')
SAMPLE_DIR = DEST_DIR + '/' + sample_name
INPUT_DIR = SAMPLE_DIR + '/inputs'
RESULT_DIR = SAMPLE_DIR + '/results'
NT_LOC_DB = os.environ.get('NT_LOC_DB',
"s3://idseq-database/20170824/blast_db/nt_loc.db")
NT_DB = os.environ.get('NT_DB', "s3://idseq-database/20170824/blast_db/nt")
# input files
ACCESSION_ANNOTATED_FASTA = 'accessions.rapsearch2.gsnapl.fasta'
GSNAP_M8_FILE = 'dedup.multihit.gsnapl.unmapped.bowtie2.lzw.cdhitdup.priceseqfilter.unmapped.star.m8'
SUMMARY_MULTIHIT_GSNAPL_OUT = 'summary.multihit.gsnapl.unmapped.bowtie2.lzw.cdhitdup.priceseqfilter.unmapped.star.tab'
SUMMARY_MULTIHIT_RAPSEARCH_OUT = 'summary.multihit.rapsearch2.filter.deuterostomes.taxids.gsnapl.unmapped.bowtie2.lzw.cdhitdup.priceseqfilter.unmapped.star.tab'
# output files
TAXID_ANNOT_FASTA = 'taxid_annot.fasta'
TAXID_ANNOT_SORTED_FASTA_NT = 'taxid_annot_sorted_nt.fasta'
TAXID_ANNOT_SORTED_FASTA_NR = 'taxid_annot_sorted_nr.fasta'
TAXID_ANNOT_SORTED_FASTA_GENUS_NT = 'taxid_annot_sorted_genus_nt.fasta'
TAXID_ANNOT_SORTED_FASTA_GENUS_NR = 'taxid_annot_sorted_genus_nr.fasta'
TAXID_ANNOT_SORTED_FASTA_FAMILY_NT = 'taxid_annot_sorted_family_nt.fasta'
TAXID_ANNOT_SORTED_FASTA_FAMILY_NR = 'taxid_annot_sorted_family_nr.fasta'
TAXID_LOCATIONS_JSON_NT = 'taxid_locations_nt.json'
TAXID_LOCATIONS_JSON_NR = 'taxid_locations_nr.json'
TAXID_LOCATIONS_JSON_GENUS_NT = 'taxid_locations_genus_nt.json'
TAXID_LOCATIONS_JSON_GENUS_NR = 'taxid_locations_genus_nr.json'
TAXID_LOCATIONS_JSON_FAMILY_NT = 'taxid_locations_family_nt.json'
TAXID_LOCATIONS_JSON_FAMILY_NR = 'taxid_locations_family_nr.json'
TAXID_LOCATIONS_JSON_ALL = 'taxid_locations_combined.json'
LOGS_OUT_BASENAME = 'postprocess-log'
ALIGN_VIZ_DIR = 'align_viz'
# target outputs by task
TARGET_OUTPUTS = {
"run_generate_taxid_fasta_from_hit_summaries":
[os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA)],
"run_generate_taxid_locator__1": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NT)
],
"run_generate_taxid_locator__2": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NR)
],
"run_generate_taxid_locator__3": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NT)
],
"run_generate_taxid_locator__4": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NR)
],
"run_generate_taxid_locator__5": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NT)
],
"run_generate_taxid_locator__6": [
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NR)
],
"run_combine_json": [os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_ALL)],
"run_generate_align_viz":
[os.path.join(RESULT_DIR, "%s.summary" % ALIGN_VIZ_DIR)]
}
# Processing functions
def remove_annotation(read_id):
result = re.sub(r'NT:(.*?):', '', read_id)
result = re.sub(r'NR:(.*?):', '', result)
return result
def parse_hits(hit_summary_files):
"""Return map of {NT, NR} => read_id => (hit_taxid_str, hit_level_str)"""
valid_hits = {}
for count_type, summary_file in hit_summary_files.items():
hits = {}
with open(summary_file, "rb") as sf:
for hit_line in sf:
hit_line_columns = hit_line.strip().split("\t")
if len(hit_line_columns) >= 3:
hit_read_id = hit_line_columns[0]
hit_level_str = hit_line_columns[1]
hit_taxid_str = hit_line_columns[2]
hits[hit_read_id] = (hit_taxid_str, hit_level_str)
valid_hits[count_type] = hits
return valid_hits
def generate_taxid_fasta_from_hit_summaries(
input_fasta_file, hit_summary_files, lineage_path, output_fasta_file):
"""Intermediate conversion step that includes handling of non-specific
hits with artificial tax_ids.
"""
lineage_map = shelve.open(lineage_path)
valid_hits = parse_hits(hit_summary_files)
def get_valid_lineage(read_id, count_type):
# If the read aligned to something, then it would be present in the
# summary file for count type, and correspondingly in valid_hits[
# count_type], even if the hits disagree so much that the
# "valid_hits" entry is just ("-1", "-1"). If the read didn't align
# to anything, we also represent that with ("-1", "-1"). This ("-1",
# "-1") gets translated to NULL_LINEAGE.
hit_taxid_str, hit_level_str = valid_hits[count_type].get(
read_id, ("-1", "-1"))
hit_lineage = lineage_map.get(hit_taxid_str, NULL_LINEAGE)
return validate_taxid_lineage(hit_lineage, hit_taxid_str,
hit_level_str)
input_fasta_f = open(input_fasta_file, 'rb')
output_fasta_f = open(output_fasta_file, 'wb')
sequence_name = input_fasta_f.readline()
sequence_data = input_fasta_f.readline()
while len(sequence_name) > 0 and len(sequence_data) > 0:
# Example read_id: "NR::NT:CP010376.2:NB501961:14:HM7TLBGX2:1:23109
# :12720:8743/2"
# Translate the read information into our custom format with fake
# taxids.
accession_annotated_read_id = sequence_name.rstrip().lstrip('>')
read_id = accession_annotated_read_id.split(":", 4)[-1]
nr_taxid_species, nr_taxid_genus, nr_taxid_family = get_valid_lineage(
read_id, 'NR')
nt_taxid_species, nt_taxid_genus, nt_taxid_family = get_valid_lineage(
read_id, 'NT')
family_str = 'family_nr:' + nr_taxid_family + ':family_nt:' + nt_taxid_family
genus_str = ':genus_nr:' + nr_taxid_genus + ':genus_nt:' + nt_taxid_genus
species_str = ':species_nr:' + nr_taxid_species + ':species_nt:' + nt_taxid_species
new_read_name = (family_str + genus_str + species_str + ':' +
accession_annotated_read_id)
output_fasta_f.write(">%s\n" % new_read_name)
output_fasta_f.write(sequence_data)
sequence_name = input_fasta_f.readline()
sequence_data = input_fasta_f.readline()
input_fasta_f.close()
output_fasta_f.close()
def get_taxid(sequence_name, taxid_field):
parts = sequence_name.replace('>', ':').split(":%s:" % taxid_field)
if len(parts) <= 1:
# Sequence_name empty or taxid_field not found
return 'none'
taxid = parts[1].split(":")[0]
# Example sequence_name: ">nr:-100:nt:684552:NR::NT:LT629734.1:HWI-ST640
# :828:H917FADXX:2:1101:1424:15119/1"
return taxid
def get_taxid_field_num(taxid_field, input_fasta):
with open(input_fasta) as f:
sequence_name = f.readline()
return sequence_name.replace('>', ':').split(":").index(taxid_field) + 1
def generate_taxid_locator(input_fasta, taxid_field, hit_type, output_fasta,
output_json):
taxid_field_num = get_taxid_field_num(taxid_field, input_fasta)
# Put every 2-line fasta record on a single line with delimiter
# ":lineseparator:":
cmd = "awk 'NR % 2 == 1 { o=$0 ; next } { print o \":lineseparator:\" $0 }' " + input_fasta
# Sort the records based on the field containing the taxids
cmd += " | sort -T %s --key %s --field-separator ':' --numeric-sort" % (
TEMP_DIR, taxid_field_num)
# Split every record back over 2 lines
cmd += " | sed 's/:lineseparator:/\\n/g' > %s" % output_fasta
subprocess.check_output(cmd, shell=True)
# Make JSON file giving the byte range of the file corresponding to each
# taxid
taxon_sequence_locations = []
f = open(output_fasta, 'rb')
sequence_name = f.readline()
sequence_data = f.readline()
taxid = get_taxid(sequence_name, taxid_field)
first_byte = 0
end_byte = first_byte + len(sequence_name) + len(sequence_data)
while len(sequence_name) > 0 and len(sequence_data) > 0:
sequence_name = f.readline()
sequence_data = f.readline()
new_taxid = get_taxid(sequence_name, taxid_field)
if new_taxid != taxid:
# Note on boundary condition: when end of file is reached, then
# sequence_name == '' => new_taxid == 'none' => new_taxid != taxid
# so last record will be written to output correctly.
taxon_sequence_locations.append({
'taxid': int(taxid),
'first_byte': first_byte,
'last_byte': end_byte - 1,
'hit_type': hit_type
})
taxid = new_taxid
first_byte = end_byte
end_byte = first_byte + len(sequence_name) + len(sequence_data)
else:
end_byte += len(sequence_name) + len(sequence_data)
f.close()
with open(output_json, 'wb') as f:
json.dump(taxon_sequence_locations, f)
def combine_json(input_json_list, output_json):
output = []
for input_json in input_json_list:
with open(input_json) as f:
output.extend(json.load(f))
with open(output_json, 'wb') as outf:
json.dump(output, outf)
# Job functions
def run_generate_align_viz(input_fasta, input_m8, output_dir):
write_to_log("Generating alignment visualization...")
nt_loc_db = fetch_reference(NT_LOC_DB)
summary_file_name = accessionid2seq_functions.generate_alignment_viz_json(
NT_DB, nt_loc_db, "NT", input_m8, input_fasta, output_dir)
# Copy the data over
cmd = "aws s3 cp --quiet %s %s/align_viz --recursive" % (
output_dir, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
cmd = "aws s3 cp --quiet %s %s/" % (summary_file_name,
SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_generate_taxid_fasta_from_hit_summaries(input_fasta, hit_summary_files,
output_fasta):
write_to_log("Generating tax_id FASTA from hit summaries...")
lineage_path = fetch_reference(LINEAGE_SHELF)
generate_taxid_fasta_from_hit_summaries(input_fasta, hit_summary_files,
lineage_path, output_fasta)
logging.getLogger().info("finished job")
cmd = "aws s3 cp --quiet %s %s/" % (output_fasta, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_generate_taxid_locator(input_fasta, taxid_field, hit_type,
output_fasta, output_json):
write_to_log("Generating tax_id locator...")
generate_taxid_locator(input_fasta, taxid_field, hit_type, output_fasta,
output_json)
logging.getLogger().info("finished job")
cmd = "aws s3 cp --quiet %s %s/" % (output_fasta, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
cmd = "aws s3 cp --quiet %s %s/" % (output_json, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_combine_json(input_json_list, output_json):
write_to_log("Combining JSON files...")
combine_json(input_json_list, output_json)
logging.getLogger().info("finished job")
cmd = "aws s3 cp --quiet %s %s/" % (output_json, SAMPLE_S3_OUTPUT_PATH)
execute_command(cmd)
def run_stage3(lazy_run=False):
assert not lazy_run, "run_stage3 was called with lazy_run"
# Make data directories
execute_command("mkdir -p %s %s %s %s" % (SAMPLE_DIR, RESULT_DIR, REF_DIR,
TEMP_DIR))
# Configure logger
log_file = "%s/%s.%s.txt" % (RESULT_DIR, LOGS_OUT_BASENAME,
AWS_BATCH_JOB_ID)
configure_logger(log_file)
print("Starting stage...")
# Download input
execute_command("aws s3 cp --quiet %s/%s %s/" %
(SAMPLE_S3_INPUT_PATH, ACCESSION_ANNOTATED_FASTA,
INPUT_DIR))
input_file = os.path.join(INPUT_DIR, ACCESSION_ANNOTATED_FASTA)
# Download m8
execute_command("aws s3 cp --quiet %s/%s %s/" % (SAMPLE_S3_INPUT_PATH,
GSNAP_M8_FILE, INPUT_DIR))
input_m8 = os.path.join(INPUT_DIR, GSNAP_M8_FILE)
# Download hit level files
hit_summary_files = {
'NT': os.path.join(INPUT_DIR, SUMMARY_MULTIHIT_GSNAPL_OUT),
'NR': os.path.join(INPUT_DIR, SUMMARY_MULTIHIT_RAPSEARCH_OUT)
}
for local_file in hit_summary_files.values():
execute_command("aws s3 cp --quiet %s/%s %s/" %
(SAMPLE_S3_INPUT_PATH, os.path.basename(local_file),
INPUT_DIR))
def s3_out_and_title(title):
return {"sample_s3_output_path": SAMPLE_S3_OUTPUT_PATH, "title": title}
# Ex: run_and_log(log_params, target_outputs, lazy_run, func_name, *args)
# TODO: Get rid of run_and_log pattern for simplification
# Generate taxid fasta
log_params = s3_out_and_title(
"run_generate_taxid_fasta_from_hit_summaries")
run_and_log(log_params,
TARGET_OUTPUTS["run_generate_taxid_fasta_from_hit_summaries"],
False, run_generate_taxid_fasta_from_hit_summaries, input_file,
hit_summary_files, os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA))
# SPECIES level
# Generate taxid locator for NT
log_params = s3_out_and_title(
"run_generate_taxid_locator for NT")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__1"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR,
TAXID_ANNOT_FASTA), 'species_nt', 'NT',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NT))
# Generate taxid locator for NR
log_params = s3_out_and_title(
"run_generate_taxid_locator for NR")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__2"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR,
TAXID_ANNOT_FASTA), 'species_nr', 'NR',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_NR))
# GENUS level
# Generate taxid locator for NT
log_params = s3_out_and_title(
"run_generate_taxid_locator for NT")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__3"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'genus_nt', 'NT',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NT))
# Generate taxid locator for NR
log_params = s3_out_and_title(
"run_generate_taxid_locator for NR")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__4"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'genus_nr', 'NR',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_GENUS_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_GENUS_NR))
# FAMILY level
# Generate taxid locator for NT
log_params = s3_out_and_title(
"run_generate_taxid_locator for NT")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__5"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'family_nt', 'NT',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NT),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NT))
# Generate taxid locator for NR
log_params = s3_out_and_title(
"run_generate_taxid_locator for NR")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_taxid_locator__6"],
False, run_generate_taxid_locator,
os.path.join(RESULT_DIR, TAXID_ANNOT_FASTA), 'family_nr', 'NR',
os.path.join(RESULT_DIR, TAXID_ANNOT_SORTED_FASTA_FAMILY_NR),
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_FAMILY_NR))
# Generate alignment visualization
log_params = s3_out_and_title("run_generate_align_viz")
run_and_log(log_params, TARGET_OUTPUTS["run_generate_align_viz"], False,
run_generate_align_viz,
os.path.join(RESULT_DIR,
TAXID_ANNOT_SORTED_FASTA_NT), input_m8,
os.path.join(RESULT_DIR, ALIGN_VIZ_DIR))
# Combine results
log_params = s3_out_and_title("run_combine_json")
input_files_basenames = [
TAXID_LOCATIONS_JSON_NT, TAXID_LOCATIONS_JSON_NR,
TAXID_LOCATIONS_JSON_GENUS_NT, TAXID_LOCATIONS_JSON_GENUS_NR,
TAXID_LOCATIONS_JSON_FAMILY_NT, TAXID_LOCATIONS_JSON_FAMILY_NR
]
input_files = [os.path.join(RESULT_DIR, f) for f in input_files_basenames]
run_and_log(log_params, TARGET_OUTPUTS["run_combine_json"], False,
run_combine_json, input_files,
os.path.join(RESULT_DIR, TAXID_LOCATIONS_JSON_ALL))
|
en
| 0.786436
|
#pylint: disable=wildcard-import # data directories # from common import ROOT_DIR # from common import REF_DIR # generated data go here # tmp directory with a lot of space for sorting large files # arguments from environment variables # input files # output files # target outputs by task # Processing functions Return map of {NT, NR} => read_id => (hit_taxid_str, hit_level_str) Intermediate conversion step that includes handling of non-specific hits with artificial tax_ids. # If the read aligned to something, then it would be present in the # summary file for count type, and correspondingly in valid_hits[ # count_type], even if the hits disagree so much that the # "valid_hits" entry is just ("-1", "-1"). If the read didn't align # to anything, we also represent that with ("-1", "-1"). This ("-1", # "-1") gets translated to NULL_LINEAGE. # Example read_id: "NR::NT:CP010376.2:NB501961:14:HM7TLBGX2:1:23109 # :12720:8743/2" # Translate the read information into our custom format with fake # taxids. # Sequence_name empty or taxid_field not found # Example sequence_name: ">nr:-100:nt:684552:NR::NT:LT629734.1:HWI-ST640 # :828:H917FADXX:2:1101:1424:15119/1" # Put every 2-line fasta record on a single line with delimiter # ":lineseparator:": # Sort the records based on the field containing the taxids # Split every record back over 2 lines # Make JSON file giving the byte range of the file corresponding to each # taxid # Note on boundary condition: when end of file is reached, then # sequence_name == '' => new_taxid == 'none' => new_taxid != taxid # so last record will be written to output correctly. # Job functions # Copy the data over # Make data directories # Configure logger # Download input # Download m8 # Download hit level files # Ex: run_and_log(log_params, target_outputs, lazy_run, func_name, *args) # TODO: Get rid of run_and_log pattern for simplification # Generate taxid fasta # SPECIES level # Generate taxid locator for NT # Generate taxid locator for NR # GENUS level # Generate taxid locator for NT # Generate taxid locator for NR # FAMILY level # Generate taxid locator for NT # Generate taxid locator for NR # Generate alignment visualization # Combine results
| 2.172007
| 2
|
test/format/conftest.py
|
di/pip-audit
| 1
|
6625798
|
<reponame>di/pip-audit
from typing import Dict, List
import pytest
from packaging.version import Version
import pip_audit.service as service
_TEST_VULN_DATA: Dict[service.Dependency, List[service.VulnerabilityResult]] = {
service.Dependency(package="foo", version="1.0"): [
service.VulnerabilityResult(
id="VULN-0",
description="The first vulnerability",
version_range=[
service.VersionRange(introduced=Version("0.9"), fixed=Version("1.1")),
service.VersionRange(introduced=None, fixed=Version("1.4")),
],
),
service.VulnerabilityResult(
id="VULN-1",
description="The second vulnerability",
version_range=[service.VersionRange(introduced=Version("0.5"), fixed=Version("1.0"))],
),
],
service.Dependency(package="bar", version="0.1"): [
service.VulnerabilityResult(
id="VULN-2",
description="The third vulnerability",
version_range=[service.VersionRange(introduced=Version("0.1"), fixed=None)],
)
],
}
@pytest.fixture(autouse=True)
def vuln_data():
return _TEST_VULN_DATA
|
from typing import Dict, List
import pytest
from packaging.version import Version
import pip_audit.service as service
_TEST_VULN_DATA: Dict[service.Dependency, List[service.VulnerabilityResult]] = {
service.Dependency(package="foo", version="1.0"): [
service.VulnerabilityResult(
id="VULN-0",
description="The first vulnerability",
version_range=[
service.VersionRange(introduced=Version("0.9"), fixed=Version("1.1")),
service.VersionRange(introduced=None, fixed=Version("1.4")),
],
),
service.VulnerabilityResult(
id="VULN-1",
description="The second vulnerability",
version_range=[service.VersionRange(introduced=Version("0.5"), fixed=Version("1.0"))],
),
],
service.Dependency(package="bar", version="0.1"): [
service.VulnerabilityResult(
id="VULN-2",
description="The third vulnerability",
version_range=[service.VersionRange(introduced=Version("0.1"), fixed=None)],
)
],
}
@pytest.fixture(autouse=True)
def vuln_data():
return _TEST_VULN_DATA
|
none
| 1
| 2.137778
| 2
|
|
Day - 3 - Binary Diagnostic/input.py
|
HarshRaj2717/AOC-2021-Solutions
| 0
|
6625799
|
<reponame>HarshRaj2717/AOC-2021-Solutions
input_text = '''00100
11110
10110
10111
10101
01111
00111
11100
10000
11001
00010
01010'''
input_text = list(input_text.split("\n"))
|
input_text = '''00100
11110
10110
10111
10101
01111
00111
11100
10000
11001
00010
01010'''
input_text = list(input_text.split("\n"))
|
es
| 0.077664
|
00100 11110 10110 10111 10101 01111 00111 11100 10000 11001 00010 01010
| 2.172735
| 2
|
cookieproject/tests/test_data.py
|
Markussorensen/mlops_exercises
| 0
|
6625800
|
<filename>cookieproject/tests/test_data.py<gh_stars>0
import numpy as np
import torch
from torch.utils.data import DataLoader
from src.data.make_dataset import MNISTDataset
import hydra
@hydra.main(config_path="../configs", config_name="config.yaml")
def main(config):
N_train = 25000
N_test = 5000
train_data = torch.load(config["folders"]["project"] + "data/processed/train.pt")
test_data = torch.load(config["folders"]["project"] + "data/processed/test.pt")
trainloader = DataLoader(train_data, batch_size=config["hyperparameters"]["batch_size"], shuffle=True)
testloader = DataLoader(test_data, batch_size=config["hyperparameters"]["batch_size"], shuffle=True)
assert len(train_data) == N_train and len(test_data) == N_test
for images, labels in trainloader:
assert images.shape[1] == 784
for images, labels in testloader:
assert images.shape[1] == 784
represented_train_labels = set(train_data[:][1].numpy())
represented_test_labels = set(test_data[:][1].numpy())
for i in range(10):
assert i in represented_train_labels
assert i in represented_test_labels
if __name__ == '__main__':
main()
|
<filename>cookieproject/tests/test_data.py<gh_stars>0
import numpy as np
import torch
from torch.utils.data import DataLoader
from src.data.make_dataset import MNISTDataset
import hydra
@hydra.main(config_path="../configs", config_name="config.yaml")
def main(config):
N_train = 25000
N_test = 5000
train_data = torch.load(config["folders"]["project"] + "data/processed/train.pt")
test_data = torch.load(config["folders"]["project"] + "data/processed/test.pt")
trainloader = DataLoader(train_data, batch_size=config["hyperparameters"]["batch_size"], shuffle=True)
testloader = DataLoader(test_data, batch_size=config["hyperparameters"]["batch_size"], shuffle=True)
assert len(train_data) == N_train and len(test_data) == N_test
for images, labels in trainloader:
assert images.shape[1] == 784
for images, labels in testloader:
assert images.shape[1] == 784
represented_train_labels = set(train_data[:][1].numpy())
represented_test_labels = set(test_data[:][1].numpy())
for i in range(10):
assert i in represented_train_labels
assert i in represented_test_labels
if __name__ == '__main__':
main()
|
none
| 1
| 2.392794
| 2
|
|
src/diskpool/azext_diskpool/vendored_sdks/storagepool/models/_models_py3.py
|
wwendyc/azure-cli-extensions
| 1
|
6625801
|
<filename>src/diskpool/azext_diskpool/vendored_sdks/storagepool/models/_models_py3.py<gh_stars>1-10
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
import datetime
from typing import Dict, List, Optional, Union
from azure.core.exceptions import HttpResponseError
import msrest.serialization
from ._storage_pool_management_enums import *
class Acl(msrest.serialization.Model):
"""Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
All required parameters must be populated in order to send to Azure.
:param initiator_iqn: Required. iSCSI initiator IQN (iSCSI Qualified Name); example:
"iqn.2005-03.org.iscsi:client".
:type initiator_iqn: str
:param mapped_luns: Required. List of LUN names mapped to the ACL.
:type mapped_luns: list[str]
"""
_validation = {
'initiator_iqn': {'required': True},
'mapped_luns': {'required': True},
}
_attribute_map = {
'initiator_iqn': {'key': 'initiatorIqn', 'type': 'str'},
'mapped_luns': {'key': 'mappedLuns', 'type': '[str]'},
}
def __init__(
self,
*,
initiator_iqn: str,
mapped_luns: List[str],
**kwargs
):
super(Acl, self).__init__(**kwargs)
self.initiator_iqn = initiator_iqn
self.mapped_luns = mapped_luns
class Disk(msrest.serialization.Model):
"""Azure Managed Disk to attach to the Disk Pool.
All required parameters must be populated in order to send to Azure.
:param id: Required. Unique Azure Resource ID of the Managed Disk.
:type id: str
"""
_validation = {
'id': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
}
def __init__(
self,
*,
id: str,
**kwargs
):
super(Disk, self).__init__(**kwargs)
self.id = id
class Resource(msrest.serialization.Model):
"""ARM resource model definition.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
super(Resource, self).__init__(**kwargs)
self.id = None
self.name = None
self.type = None
class TrackedResource(Resource):
"""The resource model definition for a ARM tracked top level resource.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param location: Required. The geo-location where the resource lives.
:type location: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'location': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
}
def __init__(
self,
*,
location: str,
tags: Optional[Dict[str, str]] = None,
**kwargs
):
super(TrackedResource, self).__init__(**kwargs)
self.tags = tags
self.location = location
class DiskPool(TrackedResource):
"""Response for Disk Pool request.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param location: Required. The geo-location where the resource lives.
:type location: str
:ivar system_data: Resource metadata required by ARM RPC.
:vartype system_data: ~storage_pool_management.models.SystemMetadata
:ivar provisioning_state: Required. State of the operation on the resource. Possible values
include: "Invalid", "Succeeded", "Failed", "Canceled", "Pending", "Creating", "Updating",
"Deleting".
:vartype provisioning_state: str or ~storage_pool_management.models.ProvisioningStates
:param availability_zones: Required. Logical zone for Disk Pool resource; example: ["1"].
:type availability_zones: list[str]
:param status: Required. Operational status of the Disk Pool. Possible values include:
"Invalid", "Unknown", "Healthy", "Unhealthy", "Updating", "Running", "Stopped", "Stopped
(deallocated)".
:type status: str or ~storage_pool_management.models.OperationalStatus
:param disks: List of Azure Managed Disks to attach to a Disk Pool.
:type disks: list[~storage_pool_management.models.Disk]
:param subnet_id: Required. Azure Resource ID of a Subnet for the Disk Pool.
:type subnet_id: str
:param additional_capabilities: List of additional capabilities for Disk Pool.
:type additional_capabilities: list[str]
:param name_sku_name: Sku name.
:type name_sku_name: str
:param tier: Sku tier.
:type tier: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'location': {'required': True},
'system_data': {'readonly': True},
'provisioning_state': {'required': True, 'readonly': True},
'availability_zones': {'required': True},
'status': {'required': True},
'subnet_id': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
'system_data': {'key': 'systemData', 'type': 'SystemMetadata'},
'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'},
'availability_zones': {'key': 'properties.availabilityZones', 'type': '[str]'},
'status': {'key': 'properties.status', 'type': 'str'},
'disks': {'key': 'properties.disks', 'type': '[Disk]'},
'subnet_id': {'key': 'properties.subnetId', 'type': 'str'},
'additional_capabilities': {'key': 'properties.additionalCapabilities', 'type': '[str]'},
'name_sku_name': {'key': 'sku.name', 'type': 'str'},
'tier': {'key': 'sku.tier', 'type': 'str'},
}
def __init__(
self,
*,
location: str,
availability_zones: List[str],
status: Union[str, "OperationalStatus"],
subnet_id: str,
tags: Optional[Dict[str, str]] = None,
disks: Optional[List["Disk"]] = None,
additional_capabilities: Optional[List[str]] = None,
name_sku_name: Optional[str] = None,
tier: Optional[str] = None,
**kwargs
):
super(DiskPool, self).__init__(tags=tags, location=location, **kwargs)
self.system_data = None
self.provisioning_state = None
self.availability_zones = availability_zones
self.status = status
self.disks = disks
self.subnet_id = subnet_id
self.additional_capabilities = additional_capabilities
self.name_sku_name = name_sku_name
self.tier = tier
class DiskPoolCreate(msrest.serialization.Model):
"""Request payload for create or update Disk Pool request.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param sku: Required. Determines the SKU of the Disk Pool.
:type sku: ~storage_pool_management.models.Sku
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param location: Required. The geo-location where the resource lives.
:type location: str
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param availability_zones: Logical zone for Disk Pool resource; example: ["1"].
:type availability_zones: list[str]
:param disks: List of Azure Managed Disks to attach to a Disk Pool.
:type disks: list[~storage_pool_management.models.Disk]
:param subnet_id: Required. Azure Resource ID of a Subnet for the Disk Pool.
:type subnet_id: str
:param additional_capabilities: List of additional capabilities for a Disk Pool.
:type additional_capabilities: list[str]
"""
_validation = {
'sku': {'required': True},
'location': {'required': True},
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'subnet_id': {'required': True},
}
_attribute_map = {
'sku': {'key': 'sku', 'type': 'Sku'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'availability_zones': {'key': 'properties.availabilityZones', 'type': '[str]'},
'disks': {'key': 'properties.disks', 'type': '[Disk]'},
'subnet_id': {'key': 'properties.subnetId', 'type': 'str'},
'additional_capabilities': {'key': 'properties.additionalCapabilities', 'type': '[str]'},
}
def __init__(
self,
*,
sku: "Sku",
location: str,
subnet_id: str,
tags: Optional[Dict[str, str]] = None,
availability_zones: Optional[List[str]] = None,
disks: Optional[List["Disk"]] = None,
additional_capabilities: Optional[List[str]] = None,
**kwargs
):
super(DiskPoolCreate, self).__init__(**kwargs)
self.sku = sku
self.tags = tags
self.location = location
self.id = None
self.name = None
self.type = None
self.availability_zones = availability_zones
self.disks = disks
self.subnet_id = subnet_id
self.additional_capabilities = additional_capabilities
class DiskPoolListResult(msrest.serialization.Model):
"""List of Disk Pools.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param value: Required. An array of Disk pool objects.
:type value: list[~storage_pool_management.models.DiskPool]
:ivar next_link: URI to fetch the next section of the paginated response.
:vartype next_link: str
"""
_validation = {
'value': {'required': True},
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[DiskPool]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["DiskPool"],
**kwargs
):
super(DiskPoolListResult, self).__init__(**kwargs)
self.value = value
self.next_link = None
class DiskPoolUpdate(msrest.serialization.Model):
"""Request payload for Update Disk Pool request.
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param disks: List of Azure Managed Disks to attach to a Disk Pool.
:type disks: list[~storage_pool_management.models.Disk]
"""
_attribute_map = {
'tags': {'key': 'tags', 'type': '{str}'},
'disks': {'key': 'properties.disks', 'type': '[Disk]'},
}
def __init__(
self,
*,
tags: Optional[Dict[str, str]] = None,
disks: Optional[List["Disk"]] = None,
**kwargs
):
super(DiskPoolUpdate, self).__init__(**kwargs)
self.tags = tags
self.disks = disks
class DiskPoolZoneInfo(msrest.serialization.Model):
"""Disk Pool Sku Details.
:param availability_zones: Logical zone for Disk Pool resource; example: ["1"].
:type availability_zones: list[str]
:param additional_capabilities: List of additional capabilities for Disk Pool.
:type additional_capabilities: list[str]
:param sku: Determines the SKU of VM deployed for Disk Pool.
:type sku: ~storage_pool_management.models.Sku
"""
_attribute_map = {
'availability_zones': {'key': 'availabilityZones', 'type': '[str]'},
'additional_capabilities': {'key': 'additionalCapabilities', 'type': '[str]'},
'sku': {'key': 'sku', 'type': 'Sku'},
}
def __init__(
self,
*,
availability_zones: Optional[List[str]] = None,
additional_capabilities: Optional[List[str]] = None,
sku: Optional["Sku"] = None,
**kwargs
):
super(DiskPoolZoneInfo, self).__init__(**kwargs)
self.availability_zones = availability_zones
self.additional_capabilities = additional_capabilities
self.sku = sku
class DiskPoolZoneListResult(msrest.serialization.Model):
"""List Disk Pool skus operation response.
:param value: The list of Disk Pool Skus.
:type value: list[~storage_pool_management.models.DiskPoolZoneInfo]
:param next_link: URI to fetch the next section of the paginated response.
:type next_link: str
"""
_attribute_map = {
'value': {'key': 'value', 'type': '[DiskPoolZoneInfo]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["DiskPoolZoneInfo"]] = None,
next_link: Optional[str] = None,
**kwargs
):
super(DiskPoolZoneListResult, self).__init__(**kwargs)
self.value = value
self.next_link = next_link
class EndpointDependency(msrest.serialization.Model):
"""A domain name that a service is reached at, including details of the current connection status.
:param domain_name: The domain name of the dependency.
:type domain_name: str
:param endpoint_details: The IP Addresses and Ports used when connecting to DomainName.
:type endpoint_details: list[~storage_pool_management.models.EndpointDetail]
"""
_attribute_map = {
'domain_name': {'key': 'domainName', 'type': 'str'},
'endpoint_details': {'key': 'endpointDetails', 'type': '[EndpointDetail]'},
}
def __init__(
self,
*,
domain_name: Optional[str] = None,
endpoint_details: Optional[List["EndpointDetail"]] = None,
**kwargs
):
super(EndpointDependency, self).__init__(**kwargs)
self.domain_name = domain_name
self.endpoint_details = endpoint_details
class EndpointDetail(msrest.serialization.Model):
"""Current TCP connectivity information from the App Service Environment to a single endpoint.
:param ip_address: An IP Address that Domain Name currently resolves to.
:type ip_address: str
:param port: The port an endpoint is connected to.
:type port: int
:param latency: The time in milliseconds it takes for a TCP connection to be created from the
App Service Environment to this IpAddress at this Port.
:type latency: float
:param is_accessible: Whether it is possible to create a TCP connection from the App Service
Environment to this IpAddress at this Port.
:type is_accessible: bool
"""
_attribute_map = {
'ip_address': {'key': 'ipAddress', 'type': 'str'},
'port': {'key': 'port', 'type': 'int'},
'latency': {'key': 'latency', 'type': 'float'},
'is_accessible': {'key': 'isAccessible', 'type': 'bool'},
}
def __init__(
self,
*,
ip_address: Optional[str] = None,
port: Optional[int] = None,
latency: Optional[float] = None,
is_accessible: Optional[bool] = None,
**kwargs
):
super(EndpointDetail, self).__init__(**kwargs)
self.ip_address = ip_address
self.port = port
self.latency = latency
self.is_accessible = is_accessible
class Error(msrest.serialization.Model):
"""The resource management error response.
:param error: RP error response.
:type error: ~storage_pool_management.models.ErrorResponse
"""
_attribute_map = {
'error': {'key': 'error', 'type': 'ErrorResponse'},
}
def __init__(
self,
*,
error: Optional["ErrorResponse"] = None,
**kwargs
):
super(Error, self).__init__(**kwargs)
self.error = error
class ErrorAdditionalInfo(msrest.serialization.Model):
"""The resource management error additional info.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar type: The additional info type.
:vartype type: str
:ivar info: The additional info.
:vartype info: object
"""
_validation = {
'type': {'readonly': True},
'info': {'readonly': True},
}
_attribute_map = {
'type': {'key': 'type', 'type': 'str'},
'info': {'key': 'info', 'type': 'object'},
}
def __init__(
self,
**kwargs
):
super(ErrorAdditionalInfo, self).__init__(**kwargs)
self.type = None
self.info = None
class ErrorResponse(msrest.serialization.Model):
"""The resource management error response.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar code: The error code.
:vartype code: str
:ivar message: The error message.
:vartype message: str
:ivar target: The error target.
:vartype target: str
:ivar details: The error details.
:vartype details: list[~storage_pool_management.models.ErrorResponse]
:ivar additional_info: The error additional info.
:vartype additional_info: list[~storage_pool_management.models.ErrorAdditionalInfo]
"""
_validation = {
'code': {'readonly': True},
'message': {'readonly': True},
'target': {'readonly': True},
'details': {'readonly': True},
'additional_info': {'readonly': True},
}
_attribute_map = {
'code': {'key': 'code', 'type': 'str'},
'message': {'key': 'message', 'type': 'str'},
'target': {'key': 'target', 'type': 'str'},
'details': {'key': 'details', 'type': '[ErrorResponse]'},
'additional_info': {'key': 'additionalInfo', 'type': '[ErrorAdditionalInfo]'},
}
def __init__(
self,
**kwargs
):
super(ErrorResponse, self).__init__(**kwargs)
self.code = None
self.message = None
self.target = None
self.details = None
self.additional_info = None
class IscsiLun(msrest.serialization.Model):
"""LUN to expose the Azure Managed Disk.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param name: Required. User defined name for iSCSI LUN; example: "lun0".
:type name: str
:param managed_disk_azure_resource_id: Required. Azure Resource ID of the Managed Disk.
:type managed_disk_azure_resource_id: str
:ivar lun: Specifies the Logical Unit Number of the iSCSI LUN.
:vartype lun: int
"""
_validation = {
'name': {'required': True},
'managed_disk_azure_resource_id': {'required': True},
'lun': {'readonly': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'managed_disk_azure_resource_id': {'key': 'managedDiskAzureResourceId', 'type': 'str'},
'lun': {'key': 'lun', 'type': 'int'},
}
def __init__(
self,
*,
name: str,
managed_disk_azure_resource_id: str,
**kwargs
):
super(IscsiLun, self).__init__(**kwargs)
self.name = name
self.managed_disk_azure_resource_id = managed_disk_azure_resource_id
self.lun = None
class IscsiTarget(Resource):
"""Response for iSCSI Target requests.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:ivar system_data: Resource metadata required by ARM RPC.
:vartype system_data: ~storage_pool_management.models.SystemMetadata
:param acl_mode: Required. Mode for Target connectivity. Possible values include: "Dynamic",
"Static".
:type acl_mode: str or ~storage_pool_management.models.IscsiTargetAclMode
:param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
:type static_acls: list[~storage_pool_management.models.Acl]
:param luns: List of LUNs to be exposed through iSCSI Target.
:type luns: list[~storage_pool_management.models.IscsiLun]
:param target_iqn: Required. iSCSI Target IQN (iSCSI Qualified Name); example:
"iqn.2005-03.org.iscsi:server".
:type target_iqn: str
:ivar provisioning_state: Required. State of the operation on the resource. Possible values
include: "Invalid", "Succeeded", "Failed", "Canceled", "Pending", "Creating", "Updating",
"Deleting".
:vartype provisioning_state: str or ~storage_pool_management.models.ProvisioningStates
:param status: Required. Operational status of the iSCSI Target. Possible values include:
"Invalid", "Unknown", "Healthy", "Unhealthy", "Updating", "Running", "Stopped", "Stopped
(deallocated)".
:type status: str or ~storage_pool_management.models.OperationalStatus
:param endpoints: List of private IPv4 addresses to connect to the iSCSI Target.
:type endpoints: list[str]
:param port: The port used by iSCSI Target portal group.
:type port: int
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'system_data': {'readonly': True},
'acl_mode': {'required': True},
'target_iqn': {'required': True},
'provisioning_state': {'required': True, 'readonly': True},
'status': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'system_data': {'key': 'systemData', 'type': 'SystemMetadata'},
'acl_mode': {'key': 'properties.aclMode', 'type': 'str'},
'static_acls': {'key': 'properties.staticAcls', 'type': '[Acl]'},
'luns': {'key': 'properties.luns', 'type': '[IscsiLun]'},
'target_iqn': {'key': 'properties.targetIqn', 'type': 'str'},
'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'},
'status': {'key': 'properties.status', 'type': 'str'},
'endpoints': {'key': 'properties.endpoints', 'type': '[str]'},
'port': {'key': 'properties.port', 'type': 'int'},
}
def __init__(
self,
*,
acl_mode: Union[str, "IscsiTargetAclMode"],
target_iqn: str,
status: Union[str, "OperationalStatus"],
static_acls: Optional[List["Acl"]] = None,
luns: Optional[List["IscsiLun"]] = None,
endpoints: Optional[List[str]] = None,
port: Optional[int] = None,
**kwargs
):
super(IscsiTarget, self).__init__(**kwargs)
self.system_data = None
self.acl_mode = acl_mode
self.static_acls = static_acls
self.luns = luns
self.target_iqn = target_iqn
self.provisioning_state = None
self.status = status
self.endpoints = endpoints
self.port = port
class IscsiTargetCreate(Resource):
"""Payload for iSCSI Target create or update requests.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param acl_mode: Required. Mode for Target connectivity. Possible values include: "Dynamic",
"Static".
:type acl_mode: str or ~storage_pool_management.models.IscsiTargetAclMode
:param target_iqn: iSCSI Target IQN (iSCSI Qualified Name); example:
"iqn.2005-03.org.iscsi:server".
:type target_iqn: str
:param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
:type static_acls: list[~storage_pool_management.models.Acl]
:param luns: List of LUNs to be exposed through iSCSI Target.
:type luns: list[~storage_pool_management.models.IscsiLun]
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'acl_mode': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'acl_mode': {'key': 'properties.aclMode', 'type': 'str'},
'target_iqn': {'key': 'properties.targetIqn', 'type': 'str'},
'static_acls': {'key': 'properties.staticAcls', 'type': '[Acl]'},
'luns': {'key': 'properties.luns', 'type': '[IscsiLun]'},
}
def __init__(
self,
*,
acl_mode: Union[str, "IscsiTargetAclMode"],
target_iqn: Optional[str] = None,
static_acls: Optional[List["Acl"]] = None,
luns: Optional[List["IscsiLun"]] = None,
**kwargs
):
super(IscsiTargetCreate, self).__init__(**kwargs)
self.acl_mode = acl_mode
self.target_iqn = target_iqn
self.static_acls = static_acls
self.luns = luns
class IscsiTargetList(msrest.serialization.Model):
"""List of iSCSI Targets.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param value: Required. An array of iSCSI Targets in a Disk Pool.
:type value: list[~storage_pool_management.models.IscsiTarget]
:ivar next_link: URI to fetch the next section of the paginated response.
:vartype next_link: str
"""
_validation = {
'value': {'required': True},
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[IscsiTarget]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["IscsiTarget"],
**kwargs
):
super(IscsiTargetList, self).__init__(**kwargs)
self.value = value
self.next_link = None
class IscsiTargetUpdate(Resource):
"""Payload for iSCSI Target update requests.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
:type static_acls: list[~storage_pool_management.models.Acl]
:param luns: List of LUNs to be exposed through iSCSI Target.
:type luns: list[~storage_pool_management.models.IscsiLun]
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'static_acls': {'key': 'properties.staticAcls', 'type': '[Acl]'},
'luns': {'key': 'properties.luns', 'type': '[IscsiLun]'},
}
def __init__(
self,
*,
static_acls: Optional[List["Acl"]] = None,
luns: Optional[List["IscsiLun"]] = None,
**kwargs
):
super(IscsiTargetUpdate, self).__init__(**kwargs)
self.static_acls = static_acls
self.luns = luns
class OutboundEnvironmentEndpoint(msrest.serialization.Model):
"""Endpoints accessed for a common purpose that the App Service Environment requires outbound network access to.
:param category: The type of service accessed by the App Service Environment, e.g., Azure
Storage, Azure SQL Database, and Azure Active Directory.
:type category: str
:param endpoints: The endpoints that the App Service Environment reaches the service at.
:type endpoints: list[~storage_pool_management.models.EndpointDependency]
"""
_attribute_map = {
'category': {'key': 'category', 'type': 'str'},
'endpoints': {'key': 'endpoints', 'type': '[EndpointDependency]'},
}
def __init__(
self,
*,
category: Optional[str] = None,
endpoints: Optional[List["EndpointDependency"]] = None,
**kwargs
):
super(OutboundEnvironmentEndpoint, self).__init__(**kwargs)
self.category = category
self.endpoints = endpoints
class OutboundEnvironmentEndpointList(msrest.serialization.Model):
"""Collection of Outbound Environment Endpoints.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param value: Required. Collection of resources.
:type value: list[~storage_pool_management.models.OutboundEnvironmentEndpoint]
:ivar next_link: Link to next page of resources.
:vartype next_link: str
"""
_validation = {
'value': {'required': True},
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[OutboundEnvironmentEndpoint]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["OutboundEnvironmentEndpoint"],
**kwargs
):
super(OutboundEnvironmentEndpointList, self).__init__(**kwargs)
self.value = value
self.next_link = None
class ProxyResource(Resource):
"""The resource model definition for a ARM proxy resource. It will have everything other than required location and tags.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
super(ProxyResource, self).__init__(**kwargs)
class Sku(msrest.serialization.Model):
"""Sku for ARM resource.
All required parameters must be populated in order to send to Azure.
:param name: Required. Sku name.
:type name: str
:param tier: Sku tier.
:type tier: str
"""
_validation = {
'name': {'required': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'tier': {'key': 'tier', 'type': 'str'},
}
def __init__(
self,
*,
name: str,
tier: Optional[str] = None,
**kwargs
):
super(Sku, self).__init__(**kwargs)
self.name = name
self.tier = tier
class StoragePoolOperationDisplay(msrest.serialization.Model):
"""Metadata about an operation.
All required parameters must be populated in order to send to Azure.
:param provider: Required. Localized friendly form of the resource provider name.
:type provider: str
:param resource: Required. Localized friendly form of the resource type related to this
action/operation.
:type resource: str
:param operation: Required. Localized friendly name for the operation, as it should be shown to
the user.
:type operation: str
:param description: Required. Localized friendly description for the operation, as it should be
shown to the user.
:type description: str
"""
_validation = {
'provider': {'required': True},
'resource': {'required': True},
'operation': {'required': True},
'description': {'required': True},
}
_attribute_map = {
'provider': {'key': 'provider', 'type': 'str'},
'resource': {'key': 'resource', 'type': 'str'},
'operation': {'key': 'operation', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
}
def __init__(
self,
*,
provider: str,
resource: str,
operation: str,
description: str,
**kwargs
):
super(StoragePoolOperationDisplay, self).__init__(**kwargs)
self.provider = provider
self.resource = resource
self.operation = operation
self.description = description
class StoragePoolOperationListResult(msrest.serialization.Model):
"""List of operations supported by the RP.
All required parameters must be populated in order to send to Azure.
:param value: Required. An array of operations supported by the StoragePool RP.
:type value: list[~storage_pool_management.models.StoragePoolRpOperation]
:param next_link: URI to fetch the next section of the paginated response.
:type next_link: str
"""
_validation = {
'value': {'required': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[StoragePoolRpOperation]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["StoragePoolRpOperation"],
next_link: Optional[str] = None,
**kwargs
):
super(StoragePoolOperationListResult, self).__init__(**kwargs)
self.value = value
self.next_link = next_link
class StoragePoolRpOperation(msrest.serialization.Model):
"""Description of a StoragePool RP Operation.
All required parameters must be populated in order to send to Azure.
:param name: Required. The name of the operation being performed on this particular object.
:type name: str
:param is_data_action: Required. Indicates whether the operation applies to data-plane.
:type is_data_action: bool
:param action_type: Indicates the action type.
:type action_type: str
:param display: Required. Additional metadata about RP operation.
:type display: ~storage_pool_management.models.StoragePoolOperationDisplay
:param origin: The intended executor of the operation; governs the display of the operation in
the RBAC UX and the audit logs UX.
:type origin: str
"""
_validation = {
'name': {'required': True},
'is_data_action': {'required': True},
'display': {'required': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'is_data_action': {'key': 'isDataAction', 'type': 'bool'},
'action_type': {'key': 'actionType', 'type': 'str'},
'display': {'key': 'display', 'type': 'StoragePoolOperationDisplay'},
'origin': {'key': 'origin', 'type': 'str'},
}
def __init__(
self,
*,
name: str,
is_data_action: bool,
display: "StoragePoolOperationDisplay",
action_type: Optional[str] = None,
origin: Optional[str] = None,
**kwargs
):
super(StoragePoolRpOperation, self).__init__(**kwargs)
self.name = name
self.is_data_action = is_data_action
self.action_type = action_type
self.display = display
self.origin = origin
class SystemMetadata(msrest.serialization.Model):
"""Metadata pertaining to creation and last modification of the resource.
:param created_by: The identity that created the resource.
:type created_by: str
:param created_by_type: The type of identity that created the resource. Possible values
include: "User", "Application", "ManagedIdentity", "Key".
:type created_by_type: str or ~storage_pool_management.models.CreatedByType
:param created_at: The timestamp of resource creation (UTC).
:type created_at: ~datetime.datetime
:param last_modified_by: The identity that last modified the resource.
:type last_modified_by: str
:param last_modified_by_type: The type of identity that last modified the resource. Possible
values include: "User", "Application", "ManagedIdentity", "Key".
:type last_modified_by_type: str or ~storage_pool_management.models.CreatedByType
:param last_modified_at: The type of identity that last modified the resource.
:type last_modified_at: ~datetime.datetime
"""
_attribute_map = {
'created_by': {'key': 'createdBy', 'type': 'str'},
'created_by_type': {'key': 'createdByType', 'type': 'str'},
'created_at': {'key': 'createdAt', 'type': 'iso-8601'},
'last_modified_by': {'key': 'lastModifiedBy', 'type': 'str'},
'last_modified_by_type': {'key': 'lastModifiedByType', 'type': 'str'},
'last_modified_at': {'key': 'lastModifiedAt', 'type': 'iso-8601'},
}
def __init__(
self,
*,
created_by: Optional[str] = None,
created_by_type: Optional[Union[str, "CreatedByType"]] = None,
created_at: Optional[datetime.datetime] = None,
last_modified_by: Optional[str] = None,
last_modified_by_type: Optional[Union[str, "CreatedByType"]] = None,
last_modified_at: Optional[datetime.datetime] = None,
**kwargs
):
super(SystemMetadata, self).__init__(**kwargs)
self.created_by = created_by
self.created_by_type = created_by_type
self.created_at = created_at
self.last_modified_by = last_modified_by
self.last_modified_by_type = last_modified_by_type
self.last_modified_at = last_modified_at
|
<filename>src/diskpool/azext_diskpool/vendored_sdks/storagepool/models/_models_py3.py<gh_stars>1-10
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
import datetime
from typing import Dict, List, Optional, Union
from azure.core.exceptions import HttpResponseError
import msrest.serialization
from ._storage_pool_management_enums import *
class Acl(msrest.serialization.Model):
"""Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
All required parameters must be populated in order to send to Azure.
:param initiator_iqn: Required. iSCSI initiator IQN (iSCSI Qualified Name); example:
"iqn.2005-03.org.iscsi:client".
:type initiator_iqn: str
:param mapped_luns: Required. List of LUN names mapped to the ACL.
:type mapped_luns: list[str]
"""
_validation = {
'initiator_iqn': {'required': True},
'mapped_luns': {'required': True},
}
_attribute_map = {
'initiator_iqn': {'key': 'initiatorIqn', 'type': 'str'},
'mapped_luns': {'key': 'mappedLuns', 'type': '[str]'},
}
def __init__(
self,
*,
initiator_iqn: str,
mapped_luns: List[str],
**kwargs
):
super(Acl, self).__init__(**kwargs)
self.initiator_iqn = initiator_iqn
self.mapped_luns = mapped_luns
class Disk(msrest.serialization.Model):
"""Azure Managed Disk to attach to the Disk Pool.
All required parameters must be populated in order to send to Azure.
:param id: Required. Unique Azure Resource ID of the Managed Disk.
:type id: str
"""
_validation = {
'id': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
}
def __init__(
self,
*,
id: str,
**kwargs
):
super(Disk, self).__init__(**kwargs)
self.id = id
class Resource(msrest.serialization.Model):
"""ARM resource model definition.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
super(Resource, self).__init__(**kwargs)
self.id = None
self.name = None
self.type = None
class TrackedResource(Resource):
"""The resource model definition for a ARM tracked top level resource.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param location: Required. The geo-location where the resource lives.
:type location: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'location': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
}
def __init__(
self,
*,
location: str,
tags: Optional[Dict[str, str]] = None,
**kwargs
):
super(TrackedResource, self).__init__(**kwargs)
self.tags = tags
self.location = location
class DiskPool(TrackedResource):
"""Response for Disk Pool request.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param location: Required. The geo-location where the resource lives.
:type location: str
:ivar system_data: Resource metadata required by ARM RPC.
:vartype system_data: ~storage_pool_management.models.SystemMetadata
:ivar provisioning_state: Required. State of the operation on the resource. Possible values
include: "Invalid", "Succeeded", "Failed", "Canceled", "Pending", "Creating", "Updating",
"Deleting".
:vartype provisioning_state: str or ~storage_pool_management.models.ProvisioningStates
:param availability_zones: Required. Logical zone for Disk Pool resource; example: ["1"].
:type availability_zones: list[str]
:param status: Required. Operational status of the Disk Pool. Possible values include:
"Invalid", "Unknown", "Healthy", "Unhealthy", "Updating", "Running", "Stopped", "Stopped
(deallocated)".
:type status: str or ~storage_pool_management.models.OperationalStatus
:param disks: List of Azure Managed Disks to attach to a Disk Pool.
:type disks: list[~storage_pool_management.models.Disk]
:param subnet_id: Required. Azure Resource ID of a Subnet for the Disk Pool.
:type subnet_id: str
:param additional_capabilities: List of additional capabilities for Disk Pool.
:type additional_capabilities: list[str]
:param name_sku_name: Sku name.
:type name_sku_name: str
:param tier: Sku tier.
:type tier: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'location': {'required': True},
'system_data': {'readonly': True},
'provisioning_state': {'required': True, 'readonly': True},
'availability_zones': {'required': True},
'status': {'required': True},
'subnet_id': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
'system_data': {'key': 'systemData', 'type': 'SystemMetadata'},
'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'},
'availability_zones': {'key': 'properties.availabilityZones', 'type': '[str]'},
'status': {'key': 'properties.status', 'type': 'str'},
'disks': {'key': 'properties.disks', 'type': '[Disk]'},
'subnet_id': {'key': 'properties.subnetId', 'type': 'str'},
'additional_capabilities': {'key': 'properties.additionalCapabilities', 'type': '[str]'},
'name_sku_name': {'key': 'sku.name', 'type': 'str'},
'tier': {'key': 'sku.tier', 'type': 'str'},
}
def __init__(
self,
*,
location: str,
availability_zones: List[str],
status: Union[str, "OperationalStatus"],
subnet_id: str,
tags: Optional[Dict[str, str]] = None,
disks: Optional[List["Disk"]] = None,
additional_capabilities: Optional[List[str]] = None,
name_sku_name: Optional[str] = None,
tier: Optional[str] = None,
**kwargs
):
super(DiskPool, self).__init__(tags=tags, location=location, **kwargs)
self.system_data = None
self.provisioning_state = None
self.availability_zones = availability_zones
self.status = status
self.disks = disks
self.subnet_id = subnet_id
self.additional_capabilities = additional_capabilities
self.name_sku_name = name_sku_name
self.tier = tier
class DiskPoolCreate(msrest.serialization.Model):
"""Request payload for create or update Disk Pool request.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param sku: Required. Determines the SKU of the Disk Pool.
:type sku: ~storage_pool_management.models.Sku
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param location: Required. The geo-location where the resource lives.
:type location: str
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param availability_zones: Logical zone for Disk Pool resource; example: ["1"].
:type availability_zones: list[str]
:param disks: List of Azure Managed Disks to attach to a Disk Pool.
:type disks: list[~storage_pool_management.models.Disk]
:param subnet_id: Required. Azure Resource ID of a Subnet for the Disk Pool.
:type subnet_id: str
:param additional_capabilities: List of additional capabilities for a Disk Pool.
:type additional_capabilities: list[str]
"""
_validation = {
'sku': {'required': True},
'location': {'required': True},
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'subnet_id': {'required': True},
}
_attribute_map = {
'sku': {'key': 'sku', 'type': 'Sku'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'availability_zones': {'key': 'properties.availabilityZones', 'type': '[str]'},
'disks': {'key': 'properties.disks', 'type': '[Disk]'},
'subnet_id': {'key': 'properties.subnetId', 'type': 'str'},
'additional_capabilities': {'key': 'properties.additionalCapabilities', 'type': '[str]'},
}
def __init__(
self,
*,
sku: "Sku",
location: str,
subnet_id: str,
tags: Optional[Dict[str, str]] = None,
availability_zones: Optional[List[str]] = None,
disks: Optional[List["Disk"]] = None,
additional_capabilities: Optional[List[str]] = None,
**kwargs
):
super(DiskPoolCreate, self).__init__(**kwargs)
self.sku = sku
self.tags = tags
self.location = location
self.id = None
self.name = None
self.type = None
self.availability_zones = availability_zones
self.disks = disks
self.subnet_id = subnet_id
self.additional_capabilities = additional_capabilities
class DiskPoolListResult(msrest.serialization.Model):
"""List of Disk Pools.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param value: Required. An array of Disk pool objects.
:type value: list[~storage_pool_management.models.DiskPool]
:ivar next_link: URI to fetch the next section of the paginated response.
:vartype next_link: str
"""
_validation = {
'value': {'required': True},
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[DiskPool]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["DiskPool"],
**kwargs
):
super(DiskPoolListResult, self).__init__(**kwargs)
self.value = value
self.next_link = None
class DiskPoolUpdate(msrest.serialization.Model):
"""Request payload for Update Disk Pool request.
:param tags: A set of tags. Resource tags.
:type tags: dict[str, str]
:param disks: List of Azure Managed Disks to attach to a Disk Pool.
:type disks: list[~storage_pool_management.models.Disk]
"""
_attribute_map = {
'tags': {'key': 'tags', 'type': '{str}'},
'disks': {'key': 'properties.disks', 'type': '[Disk]'},
}
def __init__(
self,
*,
tags: Optional[Dict[str, str]] = None,
disks: Optional[List["Disk"]] = None,
**kwargs
):
super(DiskPoolUpdate, self).__init__(**kwargs)
self.tags = tags
self.disks = disks
class DiskPoolZoneInfo(msrest.serialization.Model):
"""Disk Pool Sku Details.
:param availability_zones: Logical zone for Disk Pool resource; example: ["1"].
:type availability_zones: list[str]
:param additional_capabilities: List of additional capabilities for Disk Pool.
:type additional_capabilities: list[str]
:param sku: Determines the SKU of VM deployed for Disk Pool.
:type sku: ~storage_pool_management.models.Sku
"""
_attribute_map = {
'availability_zones': {'key': 'availabilityZones', 'type': '[str]'},
'additional_capabilities': {'key': 'additionalCapabilities', 'type': '[str]'},
'sku': {'key': 'sku', 'type': 'Sku'},
}
def __init__(
self,
*,
availability_zones: Optional[List[str]] = None,
additional_capabilities: Optional[List[str]] = None,
sku: Optional["Sku"] = None,
**kwargs
):
super(DiskPoolZoneInfo, self).__init__(**kwargs)
self.availability_zones = availability_zones
self.additional_capabilities = additional_capabilities
self.sku = sku
class DiskPoolZoneListResult(msrest.serialization.Model):
"""List Disk Pool skus operation response.
:param value: The list of Disk Pool Skus.
:type value: list[~storage_pool_management.models.DiskPoolZoneInfo]
:param next_link: URI to fetch the next section of the paginated response.
:type next_link: str
"""
_attribute_map = {
'value': {'key': 'value', 'type': '[DiskPoolZoneInfo]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["DiskPoolZoneInfo"]] = None,
next_link: Optional[str] = None,
**kwargs
):
super(DiskPoolZoneListResult, self).__init__(**kwargs)
self.value = value
self.next_link = next_link
class EndpointDependency(msrest.serialization.Model):
"""A domain name that a service is reached at, including details of the current connection status.
:param domain_name: The domain name of the dependency.
:type domain_name: str
:param endpoint_details: The IP Addresses and Ports used when connecting to DomainName.
:type endpoint_details: list[~storage_pool_management.models.EndpointDetail]
"""
_attribute_map = {
'domain_name': {'key': 'domainName', 'type': 'str'},
'endpoint_details': {'key': 'endpointDetails', 'type': '[EndpointDetail]'},
}
def __init__(
self,
*,
domain_name: Optional[str] = None,
endpoint_details: Optional[List["EndpointDetail"]] = None,
**kwargs
):
super(EndpointDependency, self).__init__(**kwargs)
self.domain_name = domain_name
self.endpoint_details = endpoint_details
class EndpointDetail(msrest.serialization.Model):
"""Current TCP connectivity information from the App Service Environment to a single endpoint.
:param ip_address: An IP Address that Domain Name currently resolves to.
:type ip_address: str
:param port: The port an endpoint is connected to.
:type port: int
:param latency: The time in milliseconds it takes for a TCP connection to be created from the
App Service Environment to this IpAddress at this Port.
:type latency: float
:param is_accessible: Whether it is possible to create a TCP connection from the App Service
Environment to this IpAddress at this Port.
:type is_accessible: bool
"""
_attribute_map = {
'ip_address': {'key': 'ipAddress', 'type': 'str'},
'port': {'key': 'port', 'type': 'int'},
'latency': {'key': 'latency', 'type': 'float'},
'is_accessible': {'key': 'isAccessible', 'type': 'bool'},
}
def __init__(
self,
*,
ip_address: Optional[str] = None,
port: Optional[int] = None,
latency: Optional[float] = None,
is_accessible: Optional[bool] = None,
**kwargs
):
super(EndpointDetail, self).__init__(**kwargs)
self.ip_address = ip_address
self.port = port
self.latency = latency
self.is_accessible = is_accessible
class Error(msrest.serialization.Model):
"""The resource management error response.
:param error: RP error response.
:type error: ~storage_pool_management.models.ErrorResponse
"""
_attribute_map = {
'error': {'key': 'error', 'type': 'ErrorResponse'},
}
def __init__(
self,
*,
error: Optional["ErrorResponse"] = None,
**kwargs
):
super(Error, self).__init__(**kwargs)
self.error = error
class ErrorAdditionalInfo(msrest.serialization.Model):
"""The resource management error additional info.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar type: The additional info type.
:vartype type: str
:ivar info: The additional info.
:vartype info: object
"""
_validation = {
'type': {'readonly': True},
'info': {'readonly': True},
}
_attribute_map = {
'type': {'key': 'type', 'type': 'str'},
'info': {'key': 'info', 'type': 'object'},
}
def __init__(
self,
**kwargs
):
super(ErrorAdditionalInfo, self).__init__(**kwargs)
self.type = None
self.info = None
class ErrorResponse(msrest.serialization.Model):
"""The resource management error response.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar code: The error code.
:vartype code: str
:ivar message: The error message.
:vartype message: str
:ivar target: The error target.
:vartype target: str
:ivar details: The error details.
:vartype details: list[~storage_pool_management.models.ErrorResponse]
:ivar additional_info: The error additional info.
:vartype additional_info: list[~storage_pool_management.models.ErrorAdditionalInfo]
"""
_validation = {
'code': {'readonly': True},
'message': {'readonly': True},
'target': {'readonly': True},
'details': {'readonly': True},
'additional_info': {'readonly': True},
}
_attribute_map = {
'code': {'key': 'code', 'type': 'str'},
'message': {'key': 'message', 'type': 'str'},
'target': {'key': 'target', 'type': 'str'},
'details': {'key': 'details', 'type': '[ErrorResponse]'},
'additional_info': {'key': 'additionalInfo', 'type': '[ErrorAdditionalInfo]'},
}
def __init__(
self,
**kwargs
):
super(ErrorResponse, self).__init__(**kwargs)
self.code = None
self.message = None
self.target = None
self.details = None
self.additional_info = None
class IscsiLun(msrest.serialization.Model):
"""LUN to expose the Azure Managed Disk.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param name: Required. User defined name for iSCSI LUN; example: "lun0".
:type name: str
:param managed_disk_azure_resource_id: Required. Azure Resource ID of the Managed Disk.
:type managed_disk_azure_resource_id: str
:ivar lun: Specifies the Logical Unit Number of the iSCSI LUN.
:vartype lun: int
"""
_validation = {
'name': {'required': True},
'managed_disk_azure_resource_id': {'required': True},
'lun': {'readonly': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'managed_disk_azure_resource_id': {'key': 'managedDiskAzureResourceId', 'type': 'str'},
'lun': {'key': 'lun', 'type': 'int'},
}
def __init__(
self,
*,
name: str,
managed_disk_azure_resource_id: str,
**kwargs
):
super(IscsiLun, self).__init__(**kwargs)
self.name = name
self.managed_disk_azure_resource_id = managed_disk_azure_resource_id
self.lun = None
class IscsiTarget(Resource):
"""Response for iSCSI Target requests.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:ivar system_data: Resource metadata required by ARM RPC.
:vartype system_data: ~storage_pool_management.models.SystemMetadata
:param acl_mode: Required. Mode for Target connectivity. Possible values include: "Dynamic",
"Static".
:type acl_mode: str or ~storage_pool_management.models.IscsiTargetAclMode
:param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
:type static_acls: list[~storage_pool_management.models.Acl]
:param luns: List of LUNs to be exposed through iSCSI Target.
:type luns: list[~storage_pool_management.models.IscsiLun]
:param target_iqn: Required. iSCSI Target IQN (iSCSI Qualified Name); example:
"iqn.2005-03.org.iscsi:server".
:type target_iqn: str
:ivar provisioning_state: Required. State of the operation on the resource. Possible values
include: "Invalid", "Succeeded", "Failed", "Canceled", "Pending", "Creating", "Updating",
"Deleting".
:vartype provisioning_state: str or ~storage_pool_management.models.ProvisioningStates
:param status: Required. Operational status of the iSCSI Target. Possible values include:
"Invalid", "Unknown", "Healthy", "Unhealthy", "Updating", "Running", "Stopped", "Stopped
(deallocated)".
:type status: str or ~storage_pool_management.models.OperationalStatus
:param endpoints: List of private IPv4 addresses to connect to the iSCSI Target.
:type endpoints: list[str]
:param port: The port used by iSCSI Target portal group.
:type port: int
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'system_data': {'readonly': True},
'acl_mode': {'required': True},
'target_iqn': {'required': True},
'provisioning_state': {'required': True, 'readonly': True},
'status': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'system_data': {'key': 'systemData', 'type': 'SystemMetadata'},
'acl_mode': {'key': 'properties.aclMode', 'type': 'str'},
'static_acls': {'key': 'properties.staticAcls', 'type': '[Acl]'},
'luns': {'key': 'properties.luns', 'type': '[IscsiLun]'},
'target_iqn': {'key': 'properties.targetIqn', 'type': 'str'},
'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'},
'status': {'key': 'properties.status', 'type': 'str'},
'endpoints': {'key': 'properties.endpoints', 'type': '[str]'},
'port': {'key': 'properties.port', 'type': 'int'},
}
def __init__(
self,
*,
acl_mode: Union[str, "IscsiTargetAclMode"],
target_iqn: str,
status: Union[str, "OperationalStatus"],
static_acls: Optional[List["Acl"]] = None,
luns: Optional[List["IscsiLun"]] = None,
endpoints: Optional[List[str]] = None,
port: Optional[int] = None,
**kwargs
):
super(IscsiTarget, self).__init__(**kwargs)
self.system_data = None
self.acl_mode = acl_mode
self.static_acls = static_acls
self.luns = luns
self.target_iqn = target_iqn
self.provisioning_state = None
self.status = status
self.endpoints = endpoints
self.port = port
class IscsiTargetCreate(Resource):
"""Payload for iSCSI Target create or update requests.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param acl_mode: Required. Mode for Target connectivity. Possible values include: "Dynamic",
"Static".
:type acl_mode: str or ~storage_pool_management.models.IscsiTargetAclMode
:param target_iqn: iSCSI Target IQN (iSCSI Qualified Name); example:
"iqn.2005-03.org.iscsi:server".
:type target_iqn: str
:param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
:type static_acls: list[~storage_pool_management.models.Acl]
:param luns: List of LUNs to be exposed through iSCSI Target.
:type luns: list[~storage_pool_management.models.IscsiLun]
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'acl_mode': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'acl_mode': {'key': 'properties.aclMode', 'type': 'str'},
'target_iqn': {'key': 'properties.targetIqn', 'type': 'str'},
'static_acls': {'key': 'properties.staticAcls', 'type': '[Acl]'},
'luns': {'key': 'properties.luns', 'type': '[IscsiLun]'},
}
def __init__(
self,
*,
acl_mode: Union[str, "IscsiTargetAclMode"],
target_iqn: Optional[str] = None,
static_acls: Optional[List["Acl"]] = None,
luns: Optional[List["IscsiLun"]] = None,
**kwargs
):
super(IscsiTargetCreate, self).__init__(**kwargs)
self.acl_mode = acl_mode
self.target_iqn = target_iqn
self.static_acls = static_acls
self.luns = luns
class IscsiTargetList(msrest.serialization.Model):
"""List of iSCSI Targets.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param value: Required. An array of iSCSI Targets in a Disk Pool.
:type value: list[~storage_pool_management.models.IscsiTarget]
:ivar next_link: URI to fetch the next section of the paginated response.
:vartype next_link: str
"""
_validation = {
'value': {'required': True},
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[IscsiTarget]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["IscsiTarget"],
**kwargs
):
super(IscsiTargetList, self).__init__(**kwargs)
self.value = value
self.next_link = None
class IscsiTargetUpdate(Resource):
"""Payload for iSCSI Target update requests.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
:param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy.
:type static_acls: list[~storage_pool_management.models.Acl]
:param luns: List of LUNs to be exposed through iSCSI Target.
:type luns: list[~storage_pool_management.models.IscsiLun]
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'static_acls': {'key': 'properties.staticAcls', 'type': '[Acl]'},
'luns': {'key': 'properties.luns', 'type': '[IscsiLun]'},
}
def __init__(
self,
*,
static_acls: Optional[List["Acl"]] = None,
luns: Optional[List["IscsiLun"]] = None,
**kwargs
):
super(IscsiTargetUpdate, self).__init__(**kwargs)
self.static_acls = static_acls
self.luns = luns
class OutboundEnvironmentEndpoint(msrest.serialization.Model):
"""Endpoints accessed for a common purpose that the App Service Environment requires outbound network access to.
:param category: The type of service accessed by the App Service Environment, e.g., Azure
Storage, Azure SQL Database, and Azure Active Directory.
:type category: str
:param endpoints: The endpoints that the App Service Environment reaches the service at.
:type endpoints: list[~storage_pool_management.models.EndpointDependency]
"""
_attribute_map = {
'category': {'key': 'category', 'type': 'str'},
'endpoints': {'key': 'endpoints', 'type': '[EndpointDependency]'},
}
def __init__(
self,
*,
category: Optional[str] = None,
endpoints: Optional[List["EndpointDependency"]] = None,
**kwargs
):
super(OutboundEnvironmentEndpoint, self).__init__(**kwargs)
self.category = category
self.endpoints = endpoints
class OutboundEnvironmentEndpointList(msrest.serialization.Model):
"""Collection of Outbound Environment Endpoints.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:param value: Required. Collection of resources.
:type value: list[~storage_pool_management.models.OutboundEnvironmentEndpoint]
:ivar next_link: Link to next page of resources.
:vartype next_link: str
"""
_validation = {
'value': {'required': True},
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[OutboundEnvironmentEndpoint]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["OutboundEnvironmentEndpoint"],
**kwargs
):
super(OutboundEnvironmentEndpointList, self).__init__(**kwargs)
self.value = value
self.next_link = None
class ProxyResource(Resource):
"""The resource model definition for a ARM proxy resource. It will have everything other than required location and tags.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource Id for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or
Microsoft.Storage/storageAccounts.
:vartype type: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
super(ProxyResource, self).__init__(**kwargs)
class Sku(msrest.serialization.Model):
"""Sku for ARM resource.
All required parameters must be populated in order to send to Azure.
:param name: Required. Sku name.
:type name: str
:param tier: Sku tier.
:type tier: str
"""
_validation = {
'name': {'required': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'tier': {'key': 'tier', 'type': 'str'},
}
def __init__(
self,
*,
name: str,
tier: Optional[str] = None,
**kwargs
):
super(Sku, self).__init__(**kwargs)
self.name = name
self.tier = tier
class StoragePoolOperationDisplay(msrest.serialization.Model):
"""Metadata about an operation.
All required parameters must be populated in order to send to Azure.
:param provider: Required. Localized friendly form of the resource provider name.
:type provider: str
:param resource: Required. Localized friendly form of the resource type related to this
action/operation.
:type resource: str
:param operation: Required. Localized friendly name for the operation, as it should be shown to
the user.
:type operation: str
:param description: Required. Localized friendly description for the operation, as it should be
shown to the user.
:type description: str
"""
_validation = {
'provider': {'required': True},
'resource': {'required': True},
'operation': {'required': True},
'description': {'required': True},
}
_attribute_map = {
'provider': {'key': 'provider', 'type': 'str'},
'resource': {'key': 'resource', 'type': 'str'},
'operation': {'key': 'operation', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
}
def __init__(
self,
*,
provider: str,
resource: str,
operation: str,
description: str,
**kwargs
):
super(StoragePoolOperationDisplay, self).__init__(**kwargs)
self.provider = provider
self.resource = resource
self.operation = operation
self.description = description
class StoragePoolOperationListResult(msrest.serialization.Model):
"""List of operations supported by the RP.
All required parameters must be populated in order to send to Azure.
:param value: Required. An array of operations supported by the StoragePool RP.
:type value: list[~storage_pool_management.models.StoragePoolRpOperation]
:param next_link: URI to fetch the next section of the paginated response.
:type next_link: str
"""
_validation = {
'value': {'required': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[StoragePoolRpOperation]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: List["StoragePoolRpOperation"],
next_link: Optional[str] = None,
**kwargs
):
super(StoragePoolOperationListResult, self).__init__(**kwargs)
self.value = value
self.next_link = next_link
class StoragePoolRpOperation(msrest.serialization.Model):
"""Description of a StoragePool RP Operation.
All required parameters must be populated in order to send to Azure.
:param name: Required. The name of the operation being performed on this particular object.
:type name: str
:param is_data_action: Required. Indicates whether the operation applies to data-plane.
:type is_data_action: bool
:param action_type: Indicates the action type.
:type action_type: str
:param display: Required. Additional metadata about RP operation.
:type display: ~storage_pool_management.models.StoragePoolOperationDisplay
:param origin: The intended executor of the operation; governs the display of the operation in
the RBAC UX and the audit logs UX.
:type origin: str
"""
_validation = {
'name': {'required': True},
'is_data_action': {'required': True},
'display': {'required': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'is_data_action': {'key': 'isDataAction', 'type': 'bool'},
'action_type': {'key': 'actionType', 'type': 'str'},
'display': {'key': 'display', 'type': 'StoragePoolOperationDisplay'},
'origin': {'key': 'origin', 'type': 'str'},
}
def __init__(
self,
*,
name: str,
is_data_action: bool,
display: "StoragePoolOperationDisplay",
action_type: Optional[str] = None,
origin: Optional[str] = None,
**kwargs
):
super(StoragePoolRpOperation, self).__init__(**kwargs)
self.name = name
self.is_data_action = is_data_action
self.action_type = action_type
self.display = display
self.origin = origin
class SystemMetadata(msrest.serialization.Model):
"""Metadata pertaining to creation and last modification of the resource.
:param created_by: The identity that created the resource.
:type created_by: str
:param created_by_type: The type of identity that created the resource. Possible values
include: "User", "Application", "ManagedIdentity", "Key".
:type created_by_type: str or ~storage_pool_management.models.CreatedByType
:param created_at: The timestamp of resource creation (UTC).
:type created_at: ~datetime.datetime
:param last_modified_by: The identity that last modified the resource.
:type last_modified_by: str
:param last_modified_by_type: The type of identity that last modified the resource. Possible
values include: "User", "Application", "ManagedIdentity", "Key".
:type last_modified_by_type: str or ~storage_pool_management.models.CreatedByType
:param last_modified_at: The type of identity that last modified the resource.
:type last_modified_at: ~datetime.datetime
"""
_attribute_map = {
'created_by': {'key': 'createdBy', 'type': 'str'},
'created_by_type': {'key': 'createdByType', 'type': 'str'},
'created_at': {'key': 'createdAt', 'type': 'iso-8601'},
'last_modified_by': {'key': 'lastModifiedBy', 'type': 'str'},
'last_modified_by_type': {'key': 'lastModifiedByType', 'type': 'str'},
'last_modified_at': {'key': 'lastModifiedAt', 'type': 'iso-8601'},
}
def __init__(
self,
*,
created_by: Optional[str] = None,
created_by_type: Optional[Union[str, "CreatedByType"]] = None,
created_at: Optional[datetime.datetime] = None,
last_modified_by: Optional[str] = None,
last_modified_by_type: Optional[Union[str, "CreatedByType"]] = None,
last_modified_at: Optional[datetime.datetime] = None,
**kwargs
):
super(SystemMetadata, self).__init__(**kwargs)
self.created_by = created_by
self.created_by_type = created_by_type
self.created_at = created_at
self.last_modified_by = last_modified_by
self.last_modified_by_type = last_modified_by_type
self.last_modified_at = last_modified_at
|
en
| 0.692329
|
# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- Access Control List (ACL) for an iSCSI Target; defines LUN masking policy. All required parameters must be populated in order to send to Azure. :param initiator_iqn: Required. iSCSI initiator IQN (iSCSI Qualified Name); example: "iqn.2005-03.org.iscsi:client". :type initiator_iqn: str :param mapped_luns: Required. List of LUN names mapped to the ACL. :type mapped_luns: list[str] Azure Managed Disk to attach to the Disk Pool. All required parameters must be populated in order to send to Azure. :param id: Required. Unique Azure Resource ID of the Managed Disk. :type id: str ARM resource model definition. Variables are only populated by the server, and will be ignored when sending a request. :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str The resource model definition for a ARM tracked top level resource. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str :param tags: A set of tags. Resource tags. :type tags: dict[str, str] :param location: Required. The geo-location where the resource lives. :type location: str Response for Disk Pool request. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str :param tags: A set of tags. Resource tags. :type tags: dict[str, str] :param location: Required. The geo-location where the resource lives. :type location: str :ivar system_data: Resource metadata required by ARM RPC. :vartype system_data: ~storage_pool_management.models.SystemMetadata :ivar provisioning_state: Required. State of the operation on the resource. Possible values include: "Invalid", "Succeeded", "Failed", "Canceled", "Pending", "Creating", "Updating", "Deleting". :vartype provisioning_state: str or ~storage_pool_management.models.ProvisioningStates :param availability_zones: Required. Logical zone for Disk Pool resource; example: ["1"]. :type availability_zones: list[str] :param status: Required. Operational status of the Disk Pool. Possible values include: "Invalid", "Unknown", "Healthy", "Unhealthy", "Updating", "Running", "Stopped", "Stopped (deallocated)". :type status: str or ~storage_pool_management.models.OperationalStatus :param disks: List of Azure Managed Disks to attach to a Disk Pool. :type disks: list[~storage_pool_management.models.Disk] :param subnet_id: Required. Azure Resource ID of a Subnet for the Disk Pool. :type subnet_id: str :param additional_capabilities: List of additional capabilities for Disk Pool. :type additional_capabilities: list[str] :param name_sku_name: Sku name. :type name_sku_name: str :param tier: Sku tier. :type tier: str Request payload for create or update Disk Pool request. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :param sku: Required. Determines the SKU of the Disk Pool. :type sku: ~storage_pool_management.models.Sku :param tags: A set of tags. Resource tags. :type tags: dict[str, str] :param location: Required. The geo-location where the resource lives. :type location: str :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str :param availability_zones: Logical zone for Disk Pool resource; example: ["1"]. :type availability_zones: list[str] :param disks: List of Azure Managed Disks to attach to a Disk Pool. :type disks: list[~storage_pool_management.models.Disk] :param subnet_id: Required. Azure Resource ID of a Subnet for the Disk Pool. :type subnet_id: str :param additional_capabilities: List of additional capabilities for a Disk Pool. :type additional_capabilities: list[str] List of Disk Pools. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :param value: Required. An array of Disk pool objects. :type value: list[~storage_pool_management.models.DiskPool] :ivar next_link: URI to fetch the next section of the paginated response. :vartype next_link: str Request payload for Update Disk Pool request. :param tags: A set of tags. Resource tags. :type tags: dict[str, str] :param disks: List of Azure Managed Disks to attach to a Disk Pool. :type disks: list[~storage_pool_management.models.Disk] Disk Pool Sku Details. :param availability_zones: Logical zone for Disk Pool resource; example: ["1"]. :type availability_zones: list[str] :param additional_capabilities: List of additional capabilities for Disk Pool. :type additional_capabilities: list[str] :param sku: Determines the SKU of VM deployed for Disk Pool. :type sku: ~storage_pool_management.models.Sku List Disk Pool skus operation response. :param value: The list of Disk Pool Skus. :type value: list[~storage_pool_management.models.DiskPoolZoneInfo] :param next_link: URI to fetch the next section of the paginated response. :type next_link: str A domain name that a service is reached at, including details of the current connection status. :param domain_name: The domain name of the dependency. :type domain_name: str :param endpoint_details: The IP Addresses and Ports used when connecting to DomainName. :type endpoint_details: list[~storage_pool_management.models.EndpointDetail] Current TCP connectivity information from the App Service Environment to a single endpoint. :param ip_address: An IP Address that Domain Name currently resolves to. :type ip_address: str :param port: The port an endpoint is connected to. :type port: int :param latency: The time in milliseconds it takes for a TCP connection to be created from the App Service Environment to this IpAddress at this Port. :type latency: float :param is_accessible: Whether it is possible to create a TCP connection from the App Service Environment to this IpAddress at this Port. :type is_accessible: bool The resource management error response. :param error: RP error response. :type error: ~storage_pool_management.models.ErrorResponse The resource management error additional info. Variables are only populated by the server, and will be ignored when sending a request. :ivar type: The additional info type. :vartype type: str :ivar info: The additional info. :vartype info: object The resource management error response. Variables are only populated by the server, and will be ignored when sending a request. :ivar code: The error code. :vartype code: str :ivar message: The error message. :vartype message: str :ivar target: The error target. :vartype target: str :ivar details: The error details. :vartype details: list[~storage_pool_management.models.ErrorResponse] :ivar additional_info: The error additional info. :vartype additional_info: list[~storage_pool_management.models.ErrorAdditionalInfo] LUN to expose the Azure Managed Disk. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :param name: Required. User defined name for iSCSI LUN; example: "lun0". :type name: str :param managed_disk_azure_resource_id: Required. Azure Resource ID of the Managed Disk. :type managed_disk_azure_resource_id: str :ivar lun: Specifies the Logical Unit Number of the iSCSI LUN. :vartype lun: int Response for iSCSI Target requests. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str :ivar system_data: Resource metadata required by ARM RPC. :vartype system_data: ~storage_pool_management.models.SystemMetadata :param acl_mode: Required. Mode for Target connectivity. Possible values include: "Dynamic", "Static". :type acl_mode: str or ~storage_pool_management.models.IscsiTargetAclMode :param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy. :type static_acls: list[~storage_pool_management.models.Acl] :param luns: List of LUNs to be exposed through iSCSI Target. :type luns: list[~storage_pool_management.models.IscsiLun] :param target_iqn: Required. iSCSI Target IQN (iSCSI Qualified Name); example: "iqn.2005-03.org.iscsi:server". :type target_iqn: str :ivar provisioning_state: Required. State of the operation on the resource. Possible values include: "Invalid", "Succeeded", "Failed", "Canceled", "Pending", "Creating", "Updating", "Deleting". :vartype provisioning_state: str or ~storage_pool_management.models.ProvisioningStates :param status: Required. Operational status of the iSCSI Target. Possible values include: "Invalid", "Unknown", "Healthy", "Unhealthy", "Updating", "Running", "Stopped", "Stopped (deallocated)". :type status: str or ~storage_pool_management.models.OperationalStatus :param endpoints: List of private IPv4 addresses to connect to the iSCSI Target. :type endpoints: list[str] :param port: The port used by iSCSI Target portal group. :type port: int Payload for iSCSI Target create or update requests. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str :param acl_mode: Required. Mode for Target connectivity. Possible values include: "Dynamic", "Static". :type acl_mode: str or ~storage_pool_management.models.IscsiTargetAclMode :param target_iqn: iSCSI Target IQN (iSCSI Qualified Name); example: "iqn.2005-03.org.iscsi:server". :type target_iqn: str :param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy. :type static_acls: list[~storage_pool_management.models.Acl] :param luns: List of LUNs to be exposed through iSCSI Target. :type luns: list[~storage_pool_management.models.IscsiLun] List of iSCSI Targets. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :param value: Required. An array of iSCSI Targets in a Disk Pool. :type value: list[~storage_pool_management.models.IscsiTarget] :ivar next_link: URI to fetch the next section of the paginated response. :vartype next_link: str Payload for iSCSI Target update requests. Variables are only populated by the server, and will be ignored when sending a request. :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str :param static_acls: Access Control List (ACL) for an iSCSI Target; defines LUN masking policy. :type static_acls: list[~storage_pool_management.models.Acl] :param luns: List of LUNs to be exposed through iSCSI Target. :type luns: list[~storage_pool_management.models.IscsiLun] Endpoints accessed for a common purpose that the App Service Environment requires outbound network access to. :param category: The type of service accessed by the App Service Environment, e.g., Azure Storage, Azure SQL Database, and Azure Active Directory. :type category: str :param endpoints: The endpoints that the App Service Environment reaches the service at. :type endpoints: list[~storage_pool_management.models.EndpointDependency] Collection of Outbound Environment Endpoints. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :param value: Required. Collection of resources. :type value: list[~storage_pool_management.models.OutboundEnvironmentEndpoint] :ivar next_link: Link to next page of resources. :vartype next_link: str The resource model definition for a ARM proxy resource. It will have everything other than required location and tags. Variables are only populated by the server, and will be ignored when sending a request. :ivar id: Fully qualified resource Id for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}. :vartype id: str :ivar name: The name of the resource. :vartype name: str :ivar type: The type of the resource. Ex- Microsoft.Compute/virtualMachines or Microsoft.Storage/storageAccounts. :vartype type: str Sku for ARM resource. All required parameters must be populated in order to send to Azure. :param name: Required. Sku name. :type name: str :param tier: Sku tier. :type tier: str Metadata about an operation. All required parameters must be populated in order to send to Azure. :param provider: Required. Localized friendly form of the resource provider name. :type provider: str :param resource: Required. Localized friendly form of the resource type related to this action/operation. :type resource: str :param operation: Required. Localized friendly name for the operation, as it should be shown to the user. :type operation: str :param description: Required. Localized friendly description for the operation, as it should be shown to the user. :type description: str List of operations supported by the RP. All required parameters must be populated in order to send to Azure. :param value: Required. An array of operations supported by the StoragePool RP. :type value: list[~storage_pool_management.models.StoragePoolRpOperation] :param next_link: URI to fetch the next section of the paginated response. :type next_link: str Description of a StoragePool RP Operation. All required parameters must be populated in order to send to Azure. :param name: Required. The name of the operation being performed on this particular object. :type name: str :param is_data_action: Required. Indicates whether the operation applies to data-plane. :type is_data_action: bool :param action_type: Indicates the action type. :type action_type: str :param display: Required. Additional metadata about RP operation. :type display: ~storage_pool_management.models.StoragePoolOperationDisplay :param origin: The intended executor of the operation; governs the display of the operation in the RBAC UX and the audit logs UX. :type origin: str Metadata pertaining to creation and last modification of the resource. :param created_by: The identity that created the resource. :type created_by: str :param created_by_type: The type of identity that created the resource. Possible values include: "User", "Application", "ManagedIdentity", "Key". :type created_by_type: str or ~storage_pool_management.models.CreatedByType :param created_at: The timestamp of resource creation (UTC). :type created_at: ~datetime.datetime :param last_modified_by: The identity that last modified the resource. :type last_modified_by: str :param last_modified_by_type: The type of identity that last modified the resource. Possible values include: "User", "Application", "ManagedIdentity", "Key". :type last_modified_by_type: str or ~storage_pool_management.models.CreatedByType :param last_modified_at: The type of identity that last modified the resource. :type last_modified_at: ~datetime.datetime
| 1.829022
| 2
|
src/spn/structure/leaves/histogram/Moment.py
|
tkrons/SPFlow_topdownrules
| 199
|
6625802
|
<gh_stars>100-1000
"""
Created on April 15, 2018
@author: <NAME>
@author: <NAME>
"""
import numpy as np
from spn.algorithms.stats.Moments import add_node_moment
from spn.structure.StatisticalTypes import MetaType
from spn.structure.leaves.histogram.Histograms import Histogram
import logging
logger = logging.getLogger(__name__)
def histogram_moment(node, order=1):
exp = 0
for i in range(len(node.breaks) - 1):
a = node.breaks[i]
b = node.breaks[i + 1]
d = node.densities[i]
if node.meta_type == MetaType.DISCRETE:
sum_x = a ** order
else:
sum_x = (b ** (order + 1) - a ** (order + 1)) / (order + 1)
exp += d * sum_x
return exp
def add_histogram_moment_support():
add_node_moment(Histogram, histogram_moment)
|
"""
Created on April 15, 2018
@author: <NAME>
@author: <NAME>
"""
import numpy as np
from spn.algorithms.stats.Moments import add_node_moment
from spn.structure.StatisticalTypes import MetaType
from spn.structure.leaves.histogram.Histograms import Histogram
import logging
logger = logging.getLogger(__name__)
def histogram_moment(node, order=1):
exp = 0
for i in range(len(node.breaks) - 1):
a = node.breaks[i]
b = node.breaks[i + 1]
d = node.densities[i]
if node.meta_type == MetaType.DISCRETE:
sum_x = a ** order
else:
sum_x = (b ** (order + 1) - a ** (order + 1)) / (order + 1)
exp += d * sum_x
return exp
def add_histogram_moment_support():
add_node_moment(Histogram, histogram_moment)
|
en
| 0.771292
|
Created on April 15, 2018 @author: <NAME> @author: <NAME>
| 2.86622
| 3
|
tests/test_Actuation.py
|
landrs-toolkit/PySOSA
| 1
|
6625803
|
<reponame>landrs-toolkit/PySOSA
import unittest
from PySOSA import Actuation
from PySOSA import FeatureOfInterest
class MyTestCase(unittest.TestCase):
def test_add_featureOfInterest(self):
"""
creates an FOI object and test add feature of interest to Actuation
"""
a1 = Actuation("Actuation 1", "switch on thermometer")
feature = FeatureOfInterest("Feature 1", "temperature")
a1.add_featureOfInterest(feature)
if __name__ == '__main__':
unittest.main()
|
import unittest
from PySOSA import Actuation
from PySOSA import FeatureOfInterest
class MyTestCase(unittest.TestCase):
def test_add_featureOfInterest(self):
"""
creates an FOI object and test add feature of interest to Actuation
"""
a1 = Actuation("Actuation 1", "switch on thermometer")
feature = FeatureOfInterest("Feature 1", "temperature")
a1.add_featureOfInterest(feature)
if __name__ == '__main__':
unittest.main()
|
en
| 0.775985
|
creates an FOI object and test add feature of interest to Actuation
| 3.062022
| 3
|
app/main.py
|
chiatk/tforty-api
| 0
|
6625804
|
<reponame>chiatk/tforty-api<gh_stars>0
from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.middleware.cors import CORSMiddleware
from .routes.user import user
from .routes.campaign import campaign
from .routes.perk import perk
from .routes.donation import donation
app = FastAPI()
app.mount("/media", StaticFiles(directory="assets"), name="assets")
origins = ["*"]
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get('/')
def main():
return { "message": "Welcome to the api" }
app.include_router(user)
app.include_router(campaign)
app.include_router(perk)
app.include_router(donation)
|
from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.middleware.cors import CORSMiddleware
from .routes.user import user
from .routes.campaign import campaign
from .routes.perk import perk
from .routes.donation import donation
app = FastAPI()
app.mount("/media", StaticFiles(directory="assets"), name="assets")
origins = ["*"]
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get('/')
def main():
return { "message": "Welcome to the api" }
app.include_router(user)
app.include_router(campaign)
app.include_router(perk)
app.include_router(donation)
|
none
| 1
| 1.966469
| 2
|
|
statsmodels/datasets/scotland/data.py
|
yarikoptic/statsmodels
| 1
|
6625805
|
"""Taxation Powers Vote for the Scottish Parliament 1997 dataset."""
__docformat__ = 'restructuredtext'
COPYRIGHT = """Used with express permission from the original author,
who retains all rights."""
TITLE = "Taxation Powers Vote for the Scottish Parliamant 1997"
SOURCE = """
<NAME>'s `Generalized Linear Models: A Unified Approach`
http://jgill.wustl.edu/research/books.html
"""
DESCRSHORT = """Taxation Powers' Yes Vote for Scottish Parliamanet-1997"""
DESCRLONG = """
This data is based on the example in Gill and describes the proportion of
voters who voted Yes to grant the Scottish Parliament taxation powers.
The data are divided into 32 council districts. This example's explanatory
variables include the amount of council tax collected in pounds sterling as
of April 1997 per two adults before adjustments, the female percentage of
total claims for unemployment benefits as of January, 1998, the standardized
mortality rate (UK is 100), the percentage of labor force participation,
regional GDP, the percentage of children aged 5 to 15, and an interaction term
between female unemployment and the council tax.
The original source files and variable information are included in
/scotland/src/
"""
NOTE = """::
Number of Observations - 32 (1 for each Scottish district)
Number of Variables - 8
Variable name definitions::
YES - Proportion voting yes to granting taxation powers to the
Scottish parliament.
COUTAX - Amount of council tax collected in pounds steling as of
April '97
UNEMPF - Female percentage of total unemployment benefits claims as of
January 1998
MOR - The standardized mortality rate (UK is 100)
ACT - Labor force participation (Short for active)
GDP - GDP per county
AGE - Percentage of children aged 5 to 15 in the county
COUTAX_FEMALEUNEMP - Interaction between COUTAX and UNEMPF
Council district names are included in the data file, though are not
returned by load.
"""
import numpy as np
from statsmodels.datasets import utils as du
from os.path import dirname, abspath
def load():
"""
Load the Scotvote data and returns a Dataset instance.
Returns
-------
Dataset instance:
See DATASET_PROPOSAL.txt for more information.
"""
data = _get_data()
return du.process_recarray(data, endog_idx=0, dtype=float)
def load_pandas():
"""
Load the Scotvote data and returns a Dataset instance.
Returns
-------
Dataset instance:
See DATASET_PROPOSAL.txt for more information.
"""
data = _get_data()
return du.process_recarray_pandas(data, endog_idx=0, dtype=float)
def _get_data():
filepath = dirname(abspath(__file__))
with open(filepath + '/scotvote.csv',"rb") as f:
data = np.recfromtxt(f, delimiter=",",
names=True, dtype=float, usecols=(1,2,3,4,5,6,7,8))
return data
|
"""Taxation Powers Vote for the Scottish Parliament 1997 dataset."""
__docformat__ = 'restructuredtext'
COPYRIGHT = """Used with express permission from the original author,
who retains all rights."""
TITLE = "Taxation Powers Vote for the Scottish Parliamant 1997"
SOURCE = """
<NAME>'s `Generalized Linear Models: A Unified Approach`
http://jgill.wustl.edu/research/books.html
"""
DESCRSHORT = """Taxation Powers' Yes Vote for Scottish Parliamanet-1997"""
DESCRLONG = """
This data is based on the example in Gill and describes the proportion of
voters who voted Yes to grant the Scottish Parliament taxation powers.
The data are divided into 32 council districts. This example's explanatory
variables include the amount of council tax collected in pounds sterling as
of April 1997 per two adults before adjustments, the female percentage of
total claims for unemployment benefits as of January, 1998, the standardized
mortality rate (UK is 100), the percentage of labor force participation,
regional GDP, the percentage of children aged 5 to 15, and an interaction term
between female unemployment and the council tax.
The original source files and variable information are included in
/scotland/src/
"""
NOTE = """::
Number of Observations - 32 (1 for each Scottish district)
Number of Variables - 8
Variable name definitions::
YES - Proportion voting yes to granting taxation powers to the
Scottish parliament.
COUTAX - Amount of council tax collected in pounds steling as of
April '97
UNEMPF - Female percentage of total unemployment benefits claims as of
January 1998
MOR - The standardized mortality rate (UK is 100)
ACT - Labor force participation (Short for active)
GDP - GDP per county
AGE - Percentage of children aged 5 to 15 in the county
COUTAX_FEMALEUNEMP - Interaction between COUTAX and UNEMPF
Council district names are included in the data file, though are not
returned by load.
"""
import numpy as np
from statsmodels.datasets import utils as du
from os.path import dirname, abspath
def load():
"""
Load the Scotvote data and returns a Dataset instance.
Returns
-------
Dataset instance:
See DATASET_PROPOSAL.txt for more information.
"""
data = _get_data()
return du.process_recarray(data, endog_idx=0, dtype=float)
def load_pandas():
"""
Load the Scotvote data and returns a Dataset instance.
Returns
-------
Dataset instance:
See DATASET_PROPOSAL.txt for more information.
"""
data = _get_data()
return du.process_recarray_pandas(data, endog_idx=0, dtype=float)
def _get_data():
filepath = dirname(abspath(__file__))
with open(filepath + '/scotvote.csv',"rb") as f:
data = np.recfromtxt(f, delimiter=",",
names=True, dtype=float, usecols=(1,2,3,4,5,6,7,8))
return data
|
en
| 0.899116
|
Taxation Powers Vote for the Scottish Parliament 1997 dataset. Used with express permission from the original author, who retains all rights. <NAME>'s `Generalized Linear Models: A Unified Approach` http://jgill.wustl.edu/research/books.html Taxation Powers' Yes Vote for Scottish Parliamanet-1997 This data is based on the example in Gill and describes the proportion of voters who voted Yes to grant the Scottish Parliament taxation powers. The data are divided into 32 council districts. This example's explanatory variables include the amount of council tax collected in pounds sterling as of April 1997 per two adults before adjustments, the female percentage of total claims for unemployment benefits as of January, 1998, the standardized mortality rate (UK is 100), the percentage of labor force participation, regional GDP, the percentage of children aged 5 to 15, and an interaction term between female unemployment and the council tax. The original source files and variable information are included in /scotland/src/ :: Number of Observations - 32 (1 for each Scottish district) Number of Variables - 8 Variable name definitions:: YES - Proportion voting yes to granting taxation powers to the Scottish parliament. COUTAX - Amount of council tax collected in pounds steling as of April '97 UNEMPF - Female percentage of total unemployment benefits claims as of January 1998 MOR - The standardized mortality rate (UK is 100) ACT - Labor force participation (Short for active) GDP - GDP per county AGE - Percentage of children aged 5 to 15 in the county COUTAX_FEMALEUNEMP - Interaction between COUTAX and UNEMPF Council district names are included in the data file, though are not returned by load. Load the Scotvote data and returns a Dataset instance. Returns ------- Dataset instance: See DATASET_PROPOSAL.txt for more information. Load the Scotvote data and returns a Dataset instance. Returns ------- Dataset instance: See DATASET_PROPOSAL.txt for more information.
| 2.483541
| 2
|
Lib/strategies/zscore_trend.py
|
DylanScotney/cryptocurrency_backtesting
| 0
|
6625806
|
<reponame>DylanScotney/cryptocurrency_backtesting
from matplotlib import pyplot as plt
import pandas as pd
from .abstract_MA import movingAverageTrader
from ..types.zscore import zScore
class zScoreTrader(movingAverageTrader):
"""
A class that backtests a z score and MA based trading algorithm
which attempts to capitalise on the over compensation of moves in
the cryptocurrency market.
Returns are stored under df['returns']. Refer to base class,
movingAverageTrading for more details.
Uses a (typically longer) moving average to determine the overall
trend. Only longs (shorts) trades will be executed if asset is in
uptrend (downtrend).
A second (typically shorter) lookback period is used to determine
the zscore of the asset and execute trading logic.
Initialisation:
- df: pandas dataframe containing asset price history
- asset_symbol: header of asset price history in df
- slow_MA: period of a moving average that is used to
to determine the trend
- zscore_period: lookback period for calculating z score
- bandwidth: bandwidth of zscore values on which trading
logic is executed.
- fast_MA: A MA period shorter than slow_MA that will
determine trend. If not specified period=0
(i.e. spotprice is used)
Members:
- self.df: df (see initialisation)
- self.sym: asset_symbol (see initialisation)
- self.trading_fee: tradine_fee (see initialisation)
- self.position: (Position) Custom position object to handle
trade positions.
- self.fastMA: (moving average) custom moving average type
object that handles moving average of series.
- self.slowMA: moving average with longer period than
self.fastMA.
- self.zscore: (zScore) custom zScore object that handles
z score of corresponding series.
- self.bandwidth: (float) bandwidth for trading logic
- self.opentimes: (list, int) holds indeces of trade opening times
- self.closetimes: (list, int) holds indeces of trade closing times
Notes:
- Currently designed to only open one positon at a time
"""
def __init__(self, df, asset_symbol, MA_type, slow_MA, zscore_period,
bandwidth, fast_MA=1, trading_fee=0.0):
if not isinstance(zscore_period, int) or zscore_period <= 0:
raise ValueError("Z score period must be positive integer")
args = (df, asset_symbol, MA_type, slow_MA)
kwargs = {"fast_MA": fast_MA, "trading_fee": trading_fee}
super(zScoreTrader, self).__init__(*args, **kwargs)
self.zscore = zScore(df[self.sym], zscore_period)
self.bandwith = bandwidth
self.opentimes = []
self.closetimes = []
def trade(self, plot=False):
"""
Executes all trades from the earliest value that the SMA can be
determined.
Inputs:
- plot: (bool) optional arg to plot trading results
"""
self.opentimes = []
self.closetimes = []
for t in range(self.slowMA.period, self.df.shape[0]):
slowMA_t = self.slowMA.getValue(t)
fastMA_t = self.fastMA.getValue(t)
Z_t = self.zscore.getValue(t)
Z_t_1 = self.zscore.getValue(t-1)
if fastMA_t > slowMA_t:
uptrend = True
else:
uptrend = False
# Open position logic
# -----------------------------------------------------------------
if uptrend and self.position.position == 0:
if Z_t > -self.bandwith and Z_t_1 < -self.bandwith:
self.openPosition(t, 'L')
self.opentimes.append(t)
if not uptrend and self.position.position == 0:
if Z_t < self.bandwith and Z_t_1 > self.bandwith:
self.openPosition(t, 'S')
self.opentimes.append(t)
# -----------------------------------------------------------------
# Close position logic
# -----------------------------------------------------------------
if self.position.position == 1 and Z_t > 0 and Z_t_1 < 0:
self.closePosition(t)
self.closetimes.append(t)
if self.position.position == -1 and Z_t < 0 and Z_t_1 > 0:
self.closePosition(t)
self.closetimes.append(t)
# -----------------------------------------------------------------
if plot:
self.plotTrading()
return self.df['returns'].cumsum().iloc[-1]
def plotTrading(self):
"""
Plots the executed trading.
3x1 subplots:
subplot 1: asset price w/ longer MA to dictate trend
and shorter MA to determine moves via zscore
subplot 2: Z score with specified bandwidths
subplot 3: Cumulative returns
Notes:
- All three plots have green and red verticle lines indicating
opening and closing positions
- Will only open longs in uptrend (spotprice > longer MA)
and only enter shorts in downtrend (spotprice < longer MA)
"""
bw = self.bandwith
t0 = self.slowMA.period
T = self.df.shape[0]
zscore_MA = (self.df[self.sym]
.rolling(window=self.zscore.period)
.mean())
plt.subplot(311)
self.df.loc[t0:T, self.sym].plot(label=self.sym)
self.slowMA.values.loc[t0:T].plot(label=self.slowMA.name)
zscore_MA.loc[t0:T].plot(label=self.zscore.name)
if self.fastMA.period > 1:
self.fastMA.values.loc[t0:T].plot(label=self.fastMA.name)
plt.ylabel('{}/BTC'.format(self.sym))
[plt.axvline(x, c='g', lw=0.5, ls='--') for x in self.opentimes]
[plt.axvline(x, c='r', lw=0.5, ls='--') for x in self.closetimes]
plt.legend()
plt.subplot(312)
self.zscore.values.loc[t0:T].plot()
plt.plot([t0, T], [bw, bw], c='k', ls='--', lw=0.5)
plt.plot([t0, T], [-bw, -bw], c='k', ls='--', lw=0.5)
plt.plot([t0, T], [0, 0], c='k', ls='--', lw=0.5)
[plt.axvline(x, c='g', lw=0.5, ls='--') for x in self.opentimes]
[plt.axvline(x, c='r', lw=0.5, ls='--') for x in self.closetimes]
plt.ylabel('Z Score')
plt.subplot(313)
returns = self.df.loc[t0:T, 'returns'].cumsum()*100
returns.plot()
plt.ylabel('Returns (%)')
plt.xlabel('Hours')
plt.show()
|
from matplotlib import pyplot as plt
import pandas as pd
from .abstract_MA import movingAverageTrader
from ..types.zscore import zScore
class zScoreTrader(movingAverageTrader):
"""
A class that backtests a z score and MA based trading algorithm
which attempts to capitalise on the over compensation of moves in
the cryptocurrency market.
Returns are stored under df['returns']. Refer to base class,
movingAverageTrading for more details.
Uses a (typically longer) moving average to determine the overall
trend. Only longs (shorts) trades will be executed if asset is in
uptrend (downtrend).
A second (typically shorter) lookback period is used to determine
the zscore of the asset and execute trading logic.
Initialisation:
- df: pandas dataframe containing asset price history
- asset_symbol: header of asset price history in df
- slow_MA: period of a moving average that is used to
to determine the trend
- zscore_period: lookback period for calculating z score
- bandwidth: bandwidth of zscore values on which trading
logic is executed.
- fast_MA: A MA period shorter than slow_MA that will
determine trend. If not specified period=0
(i.e. spotprice is used)
Members:
- self.df: df (see initialisation)
- self.sym: asset_symbol (see initialisation)
- self.trading_fee: tradine_fee (see initialisation)
- self.position: (Position) Custom position object to handle
trade positions.
- self.fastMA: (moving average) custom moving average type
object that handles moving average of series.
- self.slowMA: moving average with longer period than
self.fastMA.
- self.zscore: (zScore) custom zScore object that handles
z score of corresponding series.
- self.bandwidth: (float) bandwidth for trading logic
- self.opentimes: (list, int) holds indeces of trade opening times
- self.closetimes: (list, int) holds indeces of trade closing times
Notes:
- Currently designed to only open one positon at a time
"""
def __init__(self, df, asset_symbol, MA_type, slow_MA, zscore_period,
bandwidth, fast_MA=1, trading_fee=0.0):
if not isinstance(zscore_period, int) or zscore_period <= 0:
raise ValueError("Z score period must be positive integer")
args = (df, asset_symbol, MA_type, slow_MA)
kwargs = {"fast_MA": fast_MA, "trading_fee": trading_fee}
super(zScoreTrader, self).__init__(*args, **kwargs)
self.zscore = zScore(df[self.sym], zscore_period)
self.bandwith = bandwidth
self.opentimes = []
self.closetimes = []
def trade(self, plot=False):
"""
Executes all trades from the earliest value that the SMA can be
determined.
Inputs:
- plot: (bool) optional arg to plot trading results
"""
self.opentimes = []
self.closetimes = []
for t in range(self.slowMA.period, self.df.shape[0]):
slowMA_t = self.slowMA.getValue(t)
fastMA_t = self.fastMA.getValue(t)
Z_t = self.zscore.getValue(t)
Z_t_1 = self.zscore.getValue(t-1)
if fastMA_t > slowMA_t:
uptrend = True
else:
uptrend = False
# Open position logic
# -----------------------------------------------------------------
if uptrend and self.position.position == 0:
if Z_t > -self.bandwith and Z_t_1 < -self.bandwith:
self.openPosition(t, 'L')
self.opentimes.append(t)
if not uptrend and self.position.position == 0:
if Z_t < self.bandwith and Z_t_1 > self.bandwith:
self.openPosition(t, 'S')
self.opentimes.append(t)
# -----------------------------------------------------------------
# Close position logic
# -----------------------------------------------------------------
if self.position.position == 1 and Z_t > 0 and Z_t_1 < 0:
self.closePosition(t)
self.closetimes.append(t)
if self.position.position == -1 and Z_t < 0 and Z_t_1 > 0:
self.closePosition(t)
self.closetimes.append(t)
# -----------------------------------------------------------------
if plot:
self.plotTrading()
return self.df['returns'].cumsum().iloc[-1]
def plotTrading(self):
"""
Plots the executed trading.
3x1 subplots:
subplot 1: asset price w/ longer MA to dictate trend
and shorter MA to determine moves via zscore
subplot 2: Z score with specified bandwidths
subplot 3: Cumulative returns
Notes:
- All three plots have green and red verticle lines indicating
opening and closing positions
- Will only open longs in uptrend (spotprice > longer MA)
and only enter shorts in downtrend (spotprice < longer MA)
"""
bw = self.bandwith
t0 = self.slowMA.period
T = self.df.shape[0]
zscore_MA = (self.df[self.sym]
.rolling(window=self.zscore.period)
.mean())
plt.subplot(311)
self.df.loc[t0:T, self.sym].plot(label=self.sym)
self.slowMA.values.loc[t0:T].plot(label=self.slowMA.name)
zscore_MA.loc[t0:T].plot(label=self.zscore.name)
if self.fastMA.period > 1:
self.fastMA.values.loc[t0:T].plot(label=self.fastMA.name)
plt.ylabel('{}/BTC'.format(self.sym))
[plt.axvline(x, c='g', lw=0.5, ls='--') for x in self.opentimes]
[plt.axvline(x, c='r', lw=0.5, ls='--') for x in self.closetimes]
plt.legend()
plt.subplot(312)
self.zscore.values.loc[t0:T].plot()
plt.plot([t0, T], [bw, bw], c='k', ls='--', lw=0.5)
plt.plot([t0, T], [-bw, -bw], c='k', ls='--', lw=0.5)
plt.plot([t0, T], [0, 0], c='k', ls='--', lw=0.5)
[plt.axvline(x, c='g', lw=0.5, ls='--') for x in self.opentimes]
[plt.axvline(x, c='r', lw=0.5, ls='--') for x in self.closetimes]
plt.ylabel('Z Score')
plt.subplot(313)
returns = self.df.loc[t0:T, 'returns'].cumsum()*100
returns.plot()
plt.ylabel('Returns (%)')
plt.xlabel('Hours')
plt.show()
|
en
| 0.732089
|
A class that backtests a z score and MA based trading algorithm which attempts to capitalise on the over compensation of moves in the cryptocurrency market. Returns are stored under df['returns']. Refer to base class, movingAverageTrading for more details. Uses a (typically longer) moving average to determine the overall trend. Only longs (shorts) trades will be executed if asset is in uptrend (downtrend). A second (typically shorter) lookback period is used to determine the zscore of the asset and execute trading logic. Initialisation: - df: pandas dataframe containing asset price history - asset_symbol: header of asset price history in df - slow_MA: period of a moving average that is used to to determine the trend - zscore_period: lookback period for calculating z score - bandwidth: bandwidth of zscore values on which trading logic is executed. - fast_MA: A MA period shorter than slow_MA that will determine trend. If not specified period=0 (i.e. spotprice is used) Members: - self.df: df (see initialisation) - self.sym: asset_symbol (see initialisation) - self.trading_fee: tradine_fee (see initialisation) - self.position: (Position) Custom position object to handle trade positions. - self.fastMA: (moving average) custom moving average type object that handles moving average of series. - self.slowMA: moving average with longer period than self.fastMA. - self.zscore: (zScore) custom zScore object that handles z score of corresponding series. - self.bandwidth: (float) bandwidth for trading logic - self.opentimes: (list, int) holds indeces of trade opening times - self.closetimes: (list, int) holds indeces of trade closing times Notes: - Currently designed to only open one positon at a time Executes all trades from the earliest value that the SMA can be determined. Inputs: - plot: (bool) optional arg to plot trading results # Open position logic # ----------------------------------------------------------------- # ----------------------------------------------------------------- # Close position logic # ----------------------------------------------------------------- # ----------------------------------------------------------------- Plots the executed trading. 3x1 subplots: subplot 1: asset price w/ longer MA to dictate trend and shorter MA to determine moves via zscore subplot 2: Z score with specified bandwidths subplot 3: Cumulative returns Notes: - All three plots have green and red verticle lines indicating opening and closing positions - Will only open longs in uptrend (spotprice > longer MA) and only enter shorts in downtrend (spotprice < longer MA)
| 3.169036
| 3
|
utilities/statistics_utilities/episode_statistics.py
|
bootml/agent
| 0
|
6625807
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = 'cnheider'
import numpy as np
class EpisodeStatistics(object):
def __init__(self):
super().__init__()
durations = []
signals = []
def moving_average(self, window_size=100):
signal_ma = np.mean(self.signals[-window_size:])
duration_ma = np.mean(self.durations[-window_size:])
return signal_ma, duration_ma
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = 'cnheider'
import numpy as np
class EpisodeStatistics(object):
def __init__(self):
super().__init__()
durations = []
signals = []
def moving_average(self, window_size=100):
signal_ma = np.mean(self.signals[-window_size:])
duration_ma = np.mean(self.durations[-window_size:])
return signal_ma, duration_ma
|
en
| 0.308914
|
#!/usr/bin/env python3 # -*- coding: utf-8 -*-
| 2.667539
| 3
|
LSTM/lstm_model.py
|
dannytse/crypto-priceanalysis
| 1
|
6625808
|
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers as layers
from keras.models import Sequential
from keras.layers import Activation, Dense, Dropout, LSTM
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from sklearn.metrics import mean_absolute_error
def lstm(features, labels, dropout, neurons, dense_units, technicals):
'''
batch_size = tf.shape(features)[0]
n_outputs = tf.shape(labels)[1]
initial_state = tf.zeros([batch_size, num_layers * cell_size])
# RNN
cells = layers.StackedRNNCells([layers.GRUCell(cell_size) for _ in range(num_layers)])
rnn_layer = layers.RNN(cells)
rnn_output = rnn_layer(features, initial_state=initial_state)
# Dropout
dropout = layers.Dropout(rate=dropout)
dropout_output = dropout(rnn_output)
# Dense Layers
dense_layer = layers.Dense(dense_units, activation=tf.nn.selu)
dense_layer_output = dense_layer(dropout_output)
final = layers.Dense(n_outputs,activation=tf.sigmoid)
final_output = final(dense_layer_output)
'''
n_outputs = tf.shape(labels)[1]
# cells = layers.StackedRNNCells([layers.LSTMCell(cell_size) for _ in range(num_layers)])
model = tf.keras.Sequential()
model.add(layers.LSTM(neurons, input_shape=(features.shape[1], features.shape[2])))
# model.add(layers.LSTM(neurons, input_shape=(22, 27)))
model.add(layers.Dropout(rate=dropout))
model.add(layers.Activation(activation=tf.sigmoid))
model.add(layers.Dense(dense_units, activation=tf.nn.selu))
model.add(layers.Dense(n_outputs,activation=tf.sigmoid))
model.compile(optimizer='adam', loss='mse')
return model
'''
def lstm(features, labels, dropout, num_layers, cell_size, dense_units, technicals):
batch_size = tf.shape(features)[0]
n_outputs = tf.shape(labels)[1]
initial_state = tf.zeros([batch_size, num_layers * cell_size])
# RNN
cells = layers.StackedRNNCells([layers.LSTMCell(cell_size) for _ in range(num_layers)])
rnn_output = layers.RNN(cells, features)(initial_state=initial_state)
# Dropout
dropout = layers.Dropout(rnn_output[:,-1], keep_prob=1-dropout)
# Dense Layers
dense_layer = layers.Dense(dropout, dense_units, activation=tf.nn.selu)
preds = tf.layers.Dense(dense_layer,n_outputs,activation=tf.sigmoid)
return preds
'''
|
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers as layers
from keras.models import Sequential
from keras.layers import Activation, Dense, Dropout, LSTM
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from sklearn.metrics import mean_absolute_error
def lstm(features, labels, dropout, neurons, dense_units, technicals):
'''
batch_size = tf.shape(features)[0]
n_outputs = tf.shape(labels)[1]
initial_state = tf.zeros([batch_size, num_layers * cell_size])
# RNN
cells = layers.StackedRNNCells([layers.GRUCell(cell_size) for _ in range(num_layers)])
rnn_layer = layers.RNN(cells)
rnn_output = rnn_layer(features, initial_state=initial_state)
# Dropout
dropout = layers.Dropout(rate=dropout)
dropout_output = dropout(rnn_output)
# Dense Layers
dense_layer = layers.Dense(dense_units, activation=tf.nn.selu)
dense_layer_output = dense_layer(dropout_output)
final = layers.Dense(n_outputs,activation=tf.sigmoid)
final_output = final(dense_layer_output)
'''
n_outputs = tf.shape(labels)[1]
# cells = layers.StackedRNNCells([layers.LSTMCell(cell_size) for _ in range(num_layers)])
model = tf.keras.Sequential()
model.add(layers.LSTM(neurons, input_shape=(features.shape[1], features.shape[2])))
# model.add(layers.LSTM(neurons, input_shape=(22, 27)))
model.add(layers.Dropout(rate=dropout))
model.add(layers.Activation(activation=tf.sigmoid))
model.add(layers.Dense(dense_units, activation=tf.nn.selu))
model.add(layers.Dense(n_outputs,activation=tf.sigmoid))
model.compile(optimizer='adam', loss='mse')
return model
'''
def lstm(features, labels, dropout, num_layers, cell_size, dense_units, technicals):
batch_size = tf.shape(features)[0]
n_outputs = tf.shape(labels)[1]
initial_state = tf.zeros([batch_size, num_layers * cell_size])
# RNN
cells = layers.StackedRNNCells([layers.LSTMCell(cell_size) for _ in range(num_layers)])
rnn_output = layers.RNN(cells, features)(initial_state=initial_state)
# Dropout
dropout = layers.Dropout(rnn_output[:,-1], keep_prob=1-dropout)
# Dense Layers
dense_layer = layers.Dense(dropout, dense_units, activation=tf.nn.selu)
preds = tf.layers.Dense(dense_layer,n_outputs,activation=tf.sigmoid)
return preds
'''
|
en
| 0.539719
|
batch_size = tf.shape(features)[0] n_outputs = tf.shape(labels)[1] initial_state = tf.zeros([batch_size, num_layers * cell_size]) # RNN cells = layers.StackedRNNCells([layers.GRUCell(cell_size) for _ in range(num_layers)]) rnn_layer = layers.RNN(cells) rnn_output = rnn_layer(features, initial_state=initial_state) # Dropout dropout = layers.Dropout(rate=dropout) dropout_output = dropout(rnn_output) # Dense Layers dense_layer = layers.Dense(dense_units, activation=tf.nn.selu) dense_layer_output = dense_layer(dropout_output) final = layers.Dense(n_outputs,activation=tf.sigmoid) final_output = final(dense_layer_output) # cells = layers.StackedRNNCells([layers.LSTMCell(cell_size) for _ in range(num_layers)]) # model.add(layers.LSTM(neurons, input_shape=(22, 27))) def lstm(features, labels, dropout, num_layers, cell_size, dense_units, technicals): batch_size = tf.shape(features)[0] n_outputs = tf.shape(labels)[1] initial_state = tf.zeros([batch_size, num_layers * cell_size]) # RNN cells = layers.StackedRNNCells([layers.LSTMCell(cell_size) for _ in range(num_layers)]) rnn_output = layers.RNN(cells, features)(initial_state=initial_state) # Dropout dropout = layers.Dropout(rnn_output[:,-1], keep_prob=1-dropout) # Dense Layers dense_layer = layers.Dense(dropout, dense_units, activation=tf.nn.selu) preds = tf.layers.Dense(dense_layer,n_outputs,activation=tf.sigmoid) return preds
| 3.019412
| 3
|
dask/array/optimization.py
|
callumanoble/dask
| 0
|
6625809
|
<reponame>callumanoble/dask<filename>dask/array/optimization.py
from itertools import zip_longest
from operator import getitem
import numpy as np
from .core import getter, getter_nofancy, getter_inline
from ..blockwise import optimize_blockwise, fuse_roots
from ..core import flatten, reverse_dict
from ..optimization import fuse, inline_functions
from ..utils import ensure_dict
from ..highlevelgraph import HighLevelGraph
from numbers import Integral
# All get* functions the optimizations know about
GETTERS = (getter, getter_nofancy, getter_inline, getitem)
# These get* functions aren't ever completely removed from the graph,
# even if the index should be a no-op by numpy semantics. Some array-like's
# don't completely follow semantics, making indexing always necessary.
GETNOREMOVE = (getter, getter_nofancy)
def optimize(
dsk,
keys,
fuse_keys=None,
fast_functions=None,
inline_functions_fast_functions=(getter_inline,),
rename_fused_keys=True,
**kwargs
):
"""Optimize dask for array computation
1. Cull tasks not necessary to evaluate keys
2. Remove full slicing, e.g. x[:]
3. Inline fast functions like getitem and np.transpose
"""
if not isinstance(keys, (list, set)):
keys = [keys]
keys = list(flatten(keys))
if not isinstance(dsk, HighLevelGraph):
dsk = HighLevelGraph.from_collections(id(dsk), dsk, dependencies=())
dsk = optimize_blockwise(dsk, keys=keys)
dsk = fuse_roots(dsk, keys=keys)
dsk = dsk.cull(set(keys))
dependencies = dsk.get_all_dependencies()
dsk = ensure_dict(dsk)
# Low level task optimizations
if fast_functions is not None:
inline_functions_fast_functions = fast_functions
hold = hold_keys(dsk, dependencies)
dsk, dependencies = fuse(
dsk,
hold + keys + (fuse_keys or []),
dependencies,
rename_keys=rename_fused_keys,
)
if inline_functions_fast_functions:
dsk = inline_functions(
dsk,
keys,
dependencies=dependencies,
fast_functions=inline_functions_fast_functions,
)
return optimize_slices(dsk)
def hold_keys(dsk, dependencies):
"""Find keys to avoid fusion
We don't want to fuse data present in the graph because it is easier to
serialize as a raw value.
We don't want to fuse chains after getitem/GETTERS because we want to
move around only small pieces of data, rather than the underlying arrays.
"""
dependents = reverse_dict(dependencies)
data = {k for k, v in dsk.items() if type(v) not in (tuple, str)}
hold_keys = list(data)
for dat in data:
deps = dependents[dat]
for dep in deps:
task = dsk[dep]
# If the task is a get* function, we walk up the chain, and stop
# when there's either more than one dependent, or the dependent is
# no longer a get* function or an alias. We then add the final
# key to the list of keys not to fuse.
if type(task) is tuple and task and task[0] in GETTERS:
try:
while len(dependents[dep]) == 1:
new_dep = next(iter(dependents[dep]))
new_task = dsk[new_dep]
# If the task is a get* or an alias, continue up the
# linear chain
if new_task[0] in GETTERS or new_task in dsk:
dep = new_dep
else:
break
except (IndexError, TypeError):
pass
hold_keys.append(dep)
return hold_keys
def optimize_slices(dsk):
"""Optimize slices
1. Fuse repeated slices, like x[5:][2:6] -> x[7:11]
2. Remove full slices, like x[:] -> x
See also:
fuse_slice_dict
"""
fancy_ind_types = (list, np.ndarray)
dsk = dsk.copy()
for k, v in dsk.items():
if type(v) is tuple and v[0] in GETTERS and len(v) in (3, 5):
if len(v) == 3:
get, a, a_index = v
# getter defaults to asarray=True, getitem is semantically False
a_asarray = get is not getitem
a_lock = None
else:
get, a, a_index, a_asarray, a_lock = v
while type(a) is tuple and a[0] in GETTERS and len(a) in (3, 5):
if len(a) == 3:
f2, b, b_index = a
b_asarray = f2 is not getitem
b_lock = None
else:
f2, b, b_index, b_asarray, b_lock = a
if a_lock and a_lock is not b_lock:
break
if (type(a_index) is tuple) != (type(b_index) is tuple):
break
if type(a_index) is tuple:
indices = b_index + a_index
if len(a_index) != len(b_index) and any(i is None for i in indices):
break
if f2 is getter_nofancy and any(
isinstance(i, fancy_ind_types) for i in indices
):
break
elif f2 is getter_nofancy and (
type(a_index) in fancy_ind_types or type(b_index) in fancy_ind_types
):
break
try:
c_index = fuse_slice(b_index, a_index)
# rely on fact that nested gets never decrease in
# strictness e.g. `(getter_nofancy, (getter, ...))` never
# happens
get = getter if f2 is getter_inline else f2
except NotImplementedError:
break
a, a_index, a_lock = b, c_index, b_lock
a_asarray |= b_asarray
# Skip the get call if not from from_array and nothing to do
if get not in GETNOREMOVE and (
(
type(a_index) is slice
and not a_index.start
and a_index.stop is None
and a_index.step is None
)
or (
type(a_index) is tuple
and all(
type(s) is slice
and not s.start
and s.stop is None
and s.step is None
for s in a_index
)
)
):
dsk[k] = a
elif get is getitem or (a_asarray and not a_lock):
# default settings are fine, drop the extra parameters Since we
# always fallback to inner `get` functions, `get is getitem`
# can only occur if all gets are getitem, meaning all
# parameters must be getitem defaults.
dsk[k] = (get, a, a_index)
else:
dsk[k] = (get, a, a_index, a_asarray, a_lock)
return dsk
def normalize_slice(s):
"""Replace Nones in slices with integers
>>> normalize_slice(slice(None, None, None))
slice(0, None, 1)
"""
start, stop, step = s.start, s.stop, s.step
if start is None:
start = 0
if step is None:
step = 1
if start < 0 or step < 0 or stop is not None and stop < 0:
raise NotImplementedError()
return slice(start, stop, step)
def check_for_nonfusible_fancy_indexing(fancy, normal):
# Check for fancy indexing and normal indexing, where the fancy
# indexed dimensions != normal indexed dimensions with integers. E.g.:
# disallow things like:
# x[:, [1, 2], :][0, :, :] -> x[0, [1, 2], :] or
# x[0, :, :][:, [1, 2], :] -> x[0, [1, 2], :]
for f, n in zip_longest(fancy, normal, fillvalue=slice(None)):
if type(f) is not list and isinstance(n, Integral):
raise NotImplementedError(
"Can't handle normal indexing with "
"integers and fancy indexing if the "
"integers and fancy indices don't "
"align with the same dimensions."
)
def fuse_slice(a, b):
"""Fuse stacked slices together
Fuse a pair of repeated slices into a single slice:
>>> fuse_slice(slice(1000, 2000), slice(10, 15))
slice(1010, 1015, None)
This also works for tuples of slices
>>> fuse_slice((slice(100, 200), slice(100, 200, 10)),
... (slice(10, 15), [5, 2]))
(slice(110, 115, None), [150, 120])
And a variety of other interesting cases
>>> fuse_slice(slice(1000, 2000), 10) # integers
1010
>>> fuse_slice(slice(1000, 2000, 5), slice(10, 20, 2))
slice(1050, 1100, 10)
>>> fuse_slice(slice(1000, 2000, 5), [1, 2, 3]) # lists
[1005, 1010, 1015]
>>> fuse_slice(None, slice(None, None)) # doctest: +SKIP
None
"""
# None only works if the second side is a full slice
if a is None and isinstance(b, slice) and b == slice(None, None):
return None
# Replace None with 0 and one in start and step
if isinstance(a, slice):
a = normalize_slice(a)
if isinstance(b, slice):
b = normalize_slice(b)
if isinstance(a, slice) and isinstance(b, Integral):
if b < 0:
raise NotImplementedError()
return a.start + b * a.step
if isinstance(a, slice) and isinstance(b, slice):
start = a.start + a.step * b.start
if b.stop is not None:
stop = a.start + a.step * b.stop
else:
stop = None
if a.stop is not None:
if stop is not None:
stop = min(a.stop, stop)
else:
stop = a.stop
step = a.step * b.step
if step == 1:
step = None
return slice(start, stop, step)
if isinstance(b, list):
return [fuse_slice(a, bb) for bb in b]
if isinstance(a, list) and isinstance(b, (Integral, slice)):
return a[b]
if isinstance(a, tuple) and not isinstance(b, tuple):
b = (b,)
# If given two tuples walk through both, being mindful of uneven sizes
# and newaxes
if isinstance(a, tuple) and isinstance(b, tuple):
# Check for non-fusible cases with fancy-indexing
a_has_lists = any(isinstance(item, list) for item in a)
b_has_lists = any(isinstance(item, list) for item in b)
if a_has_lists and b_has_lists:
raise NotImplementedError("Can't handle multiple list indexing")
elif a_has_lists:
check_for_nonfusible_fancy_indexing(a, b)
elif b_has_lists:
check_for_nonfusible_fancy_indexing(b, a)
j = 0
result = list()
for i in range(len(a)):
# axis ceased to exist or we're out of b
if isinstance(a[i], Integral) or j == len(b):
result.append(a[i])
continue
while b[j] is None: # insert any Nones on the rhs
result.append(None)
j += 1
result.append(fuse_slice(a[i], b[j])) # Common case
j += 1
while j < len(b): # anything leftover on the right?
result.append(b[j])
j += 1
return tuple(result)
raise NotImplementedError()
|
from itertools import zip_longest
from operator import getitem
import numpy as np
from .core import getter, getter_nofancy, getter_inline
from ..blockwise import optimize_blockwise, fuse_roots
from ..core import flatten, reverse_dict
from ..optimization import fuse, inline_functions
from ..utils import ensure_dict
from ..highlevelgraph import HighLevelGraph
from numbers import Integral
# All get* functions the optimizations know about
GETTERS = (getter, getter_nofancy, getter_inline, getitem)
# These get* functions aren't ever completely removed from the graph,
# even if the index should be a no-op by numpy semantics. Some array-like's
# don't completely follow semantics, making indexing always necessary.
GETNOREMOVE = (getter, getter_nofancy)
def optimize(
dsk,
keys,
fuse_keys=None,
fast_functions=None,
inline_functions_fast_functions=(getter_inline,),
rename_fused_keys=True,
**kwargs
):
"""Optimize dask for array computation
1. Cull tasks not necessary to evaluate keys
2. Remove full slicing, e.g. x[:]
3. Inline fast functions like getitem and np.transpose
"""
if not isinstance(keys, (list, set)):
keys = [keys]
keys = list(flatten(keys))
if not isinstance(dsk, HighLevelGraph):
dsk = HighLevelGraph.from_collections(id(dsk), dsk, dependencies=())
dsk = optimize_blockwise(dsk, keys=keys)
dsk = fuse_roots(dsk, keys=keys)
dsk = dsk.cull(set(keys))
dependencies = dsk.get_all_dependencies()
dsk = ensure_dict(dsk)
# Low level task optimizations
if fast_functions is not None:
inline_functions_fast_functions = fast_functions
hold = hold_keys(dsk, dependencies)
dsk, dependencies = fuse(
dsk,
hold + keys + (fuse_keys or []),
dependencies,
rename_keys=rename_fused_keys,
)
if inline_functions_fast_functions:
dsk = inline_functions(
dsk,
keys,
dependencies=dependencies,
fast_functions=inline_functions_fast_functions,
)
return optimize_slices(dsk)
def hold_keys(dsk, dependencies):
"""Find keys to avoid fusion
We don't want to fuse data present in the graph because it is easier to
serialize as a raw value.
We don't want to fuse chains after getitem/GETTERS because we want to
move around only small pieces of data, rather than the underlying arrays.
"""
dependents = reverse_dict(dependencies)
data = {k for k, v in dsk.items() if type(v) not in (tuple, str)}
hold_keys = list(data)
for dat in data:
deps = dependents[dat]
for dep in deps:
task = dsk[dep]
# If the task is a get* function, we walk up the chain, and stop
# when there's either more than one dependent, or the dependent is
# no longer a get* function or an alias. We then add the final
# key to the list of keys not to fuse.
if type(task) is tuple and task and task[0] in GETTERS:
try:
while len(dependents[dep]) == 1:
new_dep = next(iter(dependents[dep]))
new_task = dsk[new_dep]
# If the task is a get* or an alias, continue up the
# linear chain
if new_task[0] in GETTERS or new_task in dsk:
dep = new_dep
else:
break
except (IndexError, TypeError):
pass
hold_keys.append(dep)
return hold_keys
def optimize_slices(dsk):
"""Optimize slices
1. Fuse repeated slices, like x[5:][2:6] -> x[7:11]
2. Remove full slices, like x[:] -> x
See also:
fuse_slice_dict
"""
fancy_ind_types = (list, np.ndarray)
dsk = dsk.copy()
for k, v in dsk.items():
if type(v) is tuple and v[0] in GETTERS and len(v) in (3, 5):
if len(v) == 3:
get, a, a_index = v
# getter defaults to asarray=True, getitem is semantically False
a_asarray = get is not getitem
a_lock = None
else:
get, a, a_index, a_asarray, a_lock = v
while type(a) is tuple and a[0] in GETTERS and len(a) in (3, 5):
if len(a) == 3:
f2, b, b_index = a
b_asarray = f2 is not getitem
b_lock = None
else:
f2, b, b_index, b_asarray, b_lock = a
if a_lock and a_lock is not b_lock:
break
if (type(a_index) is tuple) != (type(b_index) is tuple):
break
if type(a_index) is tuple:
indices = b_index + a_index
if len(a_index) != len(b_index) and any(i is None for i in indices):
break
if f2 is getter_nofancy and any(
isinstance(i, fancy_ind_types) for i in indices
):
break
elif f2 is getter_nofancy and (
type(a_index) in fancy_ind_types or type(b_index) in fancy_ind_types
):
break
try:
c_index = fuse_slice(b_index, a_index)
# rely on fact that nested gets never decrease in
# strictness e.g. `(getter_nofancy, (getter, ...))` never
# happens
get = getter if f2 is getter_inline else f2
except NotImplementedError:
break
a, a_index, a_lock = b, c_index, b_lock
a_asarray |= b_asarray
# Skip the get call if not from from_array and nothing to do
if get not in GETNOREMOVE and (
(
type(a_index) is slice
and not a_index.start
and a_index.stop is None
and a_index.step is None
)
or (
type(a_index) is tuple
and all(
type(s) is slice
and not s.start
and s.stop is None
and s.step is None
for s in a_index
)
)
):
dsk[k] = a
elif get is getitem or (a_asarray and not a_lock):
# default settings are fine, drop the extra parameters Since we
# always fallback to inner `get` functions, `get is getitem`
# can only occur if all gets are getitem, meaning all
# parameters must be getitem defaults.
dsk[k] = (get, a, a_index)
else:
dsk[k] = (get, a, a_index, a_asarray, a_lock)
return dsk
def normalize_slice(s):
"""Replace Nones in slices with integers
>>> normalize_slice(slice(None, None, None))
slice(0, None, 1)
"""
start, stop, step = s.start, s.stop, s.step
if start is None:
start = 0
if step is None:
step = 1
if start < 0 or step < 0 or stop is not None and stop < 0:
raise NotImplementedError()
return slice(start, stop, step)
def check_for_nonfusible_fancy_indexing(fancy, normal):
# Check for fancy indexing and normal indexing, where the fancy
# indexed dimensions != normal indexed dimensions with integers. E.g.:
# disallow things like:
# x[:, [1, 2], :][0, :, :] -> x[0, [1, 2], :] or
# x[0, :, :][:, [1, 2], :] -> x[0, [1, 2], :]
for f, n in zip_longest(fancy, normal, fillvalue=slice(None)):
if type(f) is not list and isinstance(n, Integral):
raise NotImplementedError(
"Can't handle normal indexing with "
"integers and fancy indexing if the "
"integers and fancy indices don't "
"align with the same dimensions."
)
def fuse_slice(a, b):
"""Fuse stacked slices together
Fuse a pair of repeated slices into a single slice:
>>> fuse_slice(slice(1000, 2000), slice(10, 15))
slice(1010, 1015, None)
This also works for tuples of slices
>>> fuse_slice((slice(100, 200), slice(100, 200, 10)),
... (slice(10, 15), [5, 2]))
(slice(110, 115, None), [150, 120])
And a variety of other interesting cases
>>> fuse_slice(slice(1000, 2000), 10) # integers
1010
>>> fuse_slice(slice(1000, 2000, 5), slice(10, 20, 2))
slice(1050, 1100, 10)
>>> fuse_slice(slice(1000, 2000, 5), [1, 2, 3]) # lists
[1005, 1010, 1015]
>>> fuse_slice(None, slice(None, None)) # doctest: +SKIP
None
"""
# None only works if the second side is a full slice
if a is None and isinstance(b, slice) and b == slice(None, None):
return None
# Replace None with 0 and one in start and step
if isinstance(a, slice):
a = normalize_slice(a)
if isinstance(b, slice):
b = normalize_slice(b)
if isinstance(a, slice) and isinstance(b, Integral):
if b < 0:
raise NotImplementedError()
return a.start + b * a.step
if isinstance(a, slice) and isinstance(b, slice):
start = a.start + a.step * b.start
if b.stop is not None:
stop = a.start + a.step * b.stop
else:
stop = None
if a.stop is not None:
if stop is not None:
stop = min(a.stop, stop)
else:
stop = a.stop
step = a.step * b.step
if step == 1:
step = None
return slice(start, stop, step)
if isinstance(b, list):
return [fuse_slice(a, bb) for bb in b]
if isinstance(a, list) and isinstance(b, (Integral, slice)):
return a[b]
if isinstance(a, tuple) and not isinstance(b, tuple):
b = (b,)
# If given two tuples walk through both, being mindful of uneven sizes
# and newaxes
if isinstance(a, tuple) and isinstance(b, tuple):
# Check for non-fusible cases with fancy-indexing
a_has_lists = any(isinstance(item, list) for item in a)
b_has_lists = any(isinstance(item, list) for item in b)
if a_has_lists and b_has_lists:
raise NotImplementedError("Can't handle multiple list indexing")
elif a_has_lists:
check_for_nonfusible_fancy_indexing(a, b)
elif b_has_lists:
check_for_nonfusible_fancy_indexing(b, a)
j = 0
result = list()
for i in range(len(a)):
# axis ceased to exist or we're out of b
if isinstance(a[i], Integral) or j == len(b):
result.append(a[i])
continue
while b[j] is None: # insert any Nones on the rhs
result.append(None)
j += 1
result.append(fuse_slice(a[i], b[j])) # Common case
j += 1
while j < len(b): # anything leftover on the right?
result.append(b[j])
j += 1
return tuple(result)
raise NotImplementedError()
|
en
| 0.788073
|
# All get* functions the optimizations know about # These get* functions aren't ever completely removed from the graph, # even if the index should be a no-op by numpy semantics. Some array-like's # don't completely follow semantics, making indexing always necessary. Optimize dask for array computation 1. Cull tasks not necessary to evaluate keys 2. Remove full slicing, e.g. x[:] 3. Inline fast functions like getitem and np.transpose # Low level task optimizations Find keys to avoid fusion We don't want to fuse data present in the graph because it is easier to serialize as a raw value. We don't want to fuse chains after getitem/GETTERS because we want to move around only small pieces of data, rather than the underlying arrays. # If the task is a get* function, we walk up the chain, and stop # when there's either more than one dependent, or the dependent is # no longer a get* function or an alias. We then add the final # key to the list of keys not to fuse. # If the task is a get* or an alias, continue up the # linear chain Optimize slices 1. Fuse repeated slices, like x[5:][2:6] -> x[7:11] 2. Remove full slices, like x[:] -> x See also: fuse_slice_dict # getter defaults to asarray=True, getitem is semantically False # rely on fact that nested gets never decrease in # strictness e.g. `(getter_nofancy, (getter, ...))` never # happens # Skip the get call if not from from_array and nothing to do # default settings are fine, drop the extra parameters Since we # always fallback to inner `get` functions, `get is getitem` # can only occur if all gets are getitem, meaning all # parameters must be getitem defaults. Replace Nones in slices with integers >>> normalize_slice(slice(None, None, None)) slice(0, None, 1) # Check for fancy indexing and normal indexing, where the fancy # indexed dimensions != normal indexed dimensions with integers. E.g.: # disallow things like: # x[:, [1, 2], :][0, :, :] -> x[0, [1, 2], :] or # x[0, :, :][:, [1, 2], :] -> x[0, [1, 2], :] Fuse stacked slices together Fuse a pair of repeated slices into a single slice: >>> fuse_slice(slice(1000, 2000), slice(10, 15)) slice(1010, 1015, None) This also works for tuples of slices >>> fuse_slice((slice(100, 200), slice(100, 200, 10)), ... (slice(10, 15), [5, 2])) (slice(110, 115, None), [150, 120]) And a variety of other interesting cases >>> fuse_slice(slice(1000, 2000), 10) # integers 1010 >>> fuse_slice(slice(1000, 2000, 5), slice(10, 20, 2)) slice(1050, 1100, 10) >>> fuse_slice(slice(1000, 2000, 5), [1, 2, 3]) # lists [1005, 1010, 1015] >>> fuse_slice(None, slice(None, None)) # doctest: +SKIP None # None only works if the second side is a full slice # Replace None with 0 and one in start and step # If given two tuples walk through both, being mindful of uneven sizes # and newaxes # Check for non-fusible cases with fancy-indexing # axis ceased to exist or we're out of b # insert any Nones on the rhs # Common case # anything leftover on the right?
| 2.07661
| 2
|
cle/backends/elf/source_manager.py
|
yuzeming/cle
| 0
|
6625810
|
<filename>cle/backends/elf/source_manager.py
import logging
import os
from elftools.dwarf.dwarfinfo import DWARFInfo
from elftools.elf.elffile import ELFFile
from elftools.dwarf.lineprogram import LineProgramEntry, LineState
l = logging.getLogger(__name__)
class SourceInfoEntry(object):
def __init__(self, fn:str, line:int, col:int, addr: int) -> None:
self.fn = fn
self.line = line
self.col = col
self.addr = addr
def __repr__(self) -> str:
return "%s %d %d: %x" % (self.fn, self.line, self.col, self.addr)
class SourceManager(object):
raw_state = [] # type: list[SourceInfoEntry]
file_list = set()
offset = 0
def __init__(self, dwarf_info: DWARFInfo, binary_path:str) -> None:
binary_dir = os.path.dirname(binary_path)
for cu in dwarf_info.iter_CUs():
l.info('Found a compile unit at offset %s, length %s' % (cu.cu_offset, cu['unit_length']))
line_program = dwarf_info.line_program_for_CU(cu)
if line_program is None:
l.info("DWARF info is missing a line program for this CU")
continue
lp_header = line_program.header
file_entries = lp_header["file_entry"]
file_list = ["_NONE_"]
for file_entry in file_entries:
dir_index = file_entry["dir_index"]
if dir_index == 0:
file_list.append(os.path.join(
binary_dir,
file_entry.name.decode()
))
else:
file_list.append(os.path.join(
lp_header["include_directory"][dir_index - 1],
file_entry.name
).decode())
lp_entries = line_program.get_entries()
for lp_entry in lp_entries:
s = lp_entry.state
if not s or s.file == 0 or not s.is_stmt:
continue
self.raw_state.append(SourceInfoEntry(file_list[s.file], s.line, s.column, s.address))
self.file_list.add(file_list[s.file])
def map_to_address(self, fn: str, line: int, col: int or None=None):
return [s.addr+self.offset for s in self.raw_state if s.fn == fn and s.line == line and (col is None or s.col == col)]
def map_to_source(self, addr:None):
ret = [s for s in self.raw_state if s.addr+self.offset == addr]
if len(ret) == 1:
return (ret[0].fn, ret[0].line, ret[0].col)
return None
def get_breakpoint_line_list(self, fn:str):
return list(set([s.line for s in self.raw_state if s.fn == fn]))
|
<filename>cle/backends/elf/source_manager.py
import logging
import os
from elftools.dwarf.dwarfinfo import DWARFInfo
from elftools.elf.elffile import ELFFile
from elftools.dwarf.lineprogram import LineProgramEntry, LineState
l = logging.getLogger(__name__)
class SourceInfoEntry(object):
def __init__(self, fn:str, line:int, col:int, addr: int) -> None:
self.fn = fn
self.line = line
self.col = col
self.addr = addr
def __repr__(self) -> str:
return "%s %d %d: %x" % (self.fn, self.line, self.col, self.addr)
class SourceManager(object):
raw_state = [] # type: list[SourceInfoEntry]
file_list = set()
offset = 0
def __init__(self, dwarf_info: DWARFInfo, binary_path:str) -> None:
binary_dir = os.path.dirname(binary_path)
for cu in dwarf_info.iter_CUs():
l.info('Found a compile unit at offset %s, length %s' % (cu.cu_offset, cu['unit_length']))
line_program = dwarf_info.line_program_for_CU(cu)
if line_program is None:
l.info("DWARF info is missing a line program for this CU")
continue
lp_header = line_program.header
file_entries = lp_header["file_entry"]
file_list = ["_NONE_"]
for file_entry in file_entries:
dir_index = file_entry["dir_index"]
if dir_index == 0:
file_list.append(os.path.join(
binary_dir,
file_entry.name.decode()
))
else:
file_list.append(os.path.join(
lp_header["include_directory"][dir_index - 1],
file_entry.name
).decode())
lp_entries = line_program.get_entries()
for lp_entry in lp_entries:
s = lp_entry.state
if not s or s.file == 0 or not s.is_stmt:
continue
self.raw_state.append(SourceInfoEntry(file_list[s.file], s.line, s.column, s.address))
self.file_list.add(file_list[s.file])
def map_to_address(self, fn: str, line: int, col: int or None=None):
return [s.addr+self.offset for s in self.raw_state if s.fn == fn and s.line == line and (col is None or s.col == col)]
def map_to_source(self, addr:None):
ret = [s for s in self.raw_state if s.addr+self.offset == addr]
if len(ret) == 1:
return (ret[0].fn, ret[0].line, ret[0].col)
return None
def get_breakpoint_line_list(self, fn:str):
return list(set([s.line for s in self.raw_state if s.fn == fn]))
|
en
| 0.257364
|
# type: list[SourceInfoEntry]
| 2.348353
| 2
|
python/testData/intentions/PythonDemorganLawIntentionTest/complex.py
|
jnthn/intellij-community
| 2
|
6625811
|
<reponame>jnthn/intellij-community<gh_stars>1-10
a = True
b = False
c = True
d = False
#before intention
if a and b and c or<caret> d:
print "before"
|
a = True
b = False
c = True
d = False
#before intention
if a and b and c or<caret> d:
print "before"
|
en
| 0.639194
|
#before intention
| 2.633858
| 3
|
collatz.py
|
danj7/Collatz-Mapper
| 0
|
6625812
|
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.animation as anim
import sys
def collatz_mapper(amax, bmax, div=2, nlim=20):
"""
Returns a Numpy array with the Collatz Map. Utilizes ints to build the map.
Parameters
----------
amax: int
Maximum positive 'a' value of the map (horizontal axis). The map goes
from -amax to amax.
bmax: int
Maximum positive 'b' value of the map (vertical axis). The map goes
from -bmax to bmax.
div: int
Divisor for the generalized Collatz Problem.
nlim: int
Maximimum number of integers to search for convergence.
"""
a_range = range(-amax, amax)
b_range = range(-bmax,bmax)
d = div
collatz_map = np.zeros((len(b_range), len(a_range)))
n_currs = range(1,nlim+1)
n_min_init = 999999 #initialization value for n_min, so that it is bigger than n_curr
n_max = 1000000000
calc_steps = 10
max_mini_steps = 100 #maximum steps in collatz sequence to check for convergence
escape_value = np.pi #value given to list of fixed points if number of steps exceded.
for a in a_range:
for b in b_range:
min_fix = []
for n_curr in n_currs:
#print('a, b, n = ',a, b, n_curr)
step = 1
escaped = False
for _ in range(calc_steps):
if n_curr%d == 0:
if n_curr == 0:
n_min = 0
break
else:
n_curr = n_curr // d
else:
n_curr = a*n_curr + b
n_min = n_curr + n_min_init
while n_min != n_curr:
#print('n_curr=', n_curr, ', n_min=', n_min)
n_min = min(n_min, n_curr)
if n_curr%d == 0:
if n_curr == 0:
n_min = 0
break
else:
n_curr = n_curr // d
else:
n_curr = a*n_curr + b
step += 1
if step > max_mini_steps or abs(n_curr) > n_max:
#print('escaped')
escaped = True
break
if escaped:
min_fix.append(escape_value)
escaped = False
else:
min_fix.append(n_min)
#adding point to map
min_fix_setlist = list(set(min_fix))
if np.pi in min_fix_setlist:
if [np.pi]==min_fix_setlist:
collatz_map[b + bmax, a + amax] = 0
else:
collatz_map[b + bmax, a + amax] = 1
else:
if len(min_fix_setlist) == 1:
collatz_map[b + bmax, a + amax] = 3
else:
collatz_map[b + bmax, a + amax] = 2
#
return collatz_map
#
def collatz_plotter(col_map, div = 0, cmap='inferno', legend=True):
"""
Plots the collatz map.
Parameters
----------
colmap: numpy array
Contains the map.
div: int
Used as figure number and for filename if empty.
save_fig: boolean
Declares whether to save the figure or not.
savename: string
Name of the file where figure will be saved.
cmap: string or colormap
Set by default to 'inferno'.
"""
if div==0:
fig = plt.figure()
div = ''
else:
fig = plt.figure(div)
ax=fig.add_subplot(1,1,1)
values = np.unique(col_map)
image = plt.imshow(col_map, cmap=cmap)
colors = [image.cmap(image.norm(value)) for value in values]
labels = ['no convergence', 'convergence for some', 'convergence for all at diff', 'convergence for all at same']
patches = [mpatches.Patch(color=colors[i], label=labels[i]) for i in range(len(values))]
if legend:
plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
if div!=0:
plt.title('divisor = '+str(div))
plt.axis('off')
plt.show()
#
def collatz_animation(amax, bmax, div):
"""
Returns an animation object and saves it as Gif.
"""
pass
#
if __name__ == '__main__':
int_parameters = []
for arg in sys.argv[1:]:
int_parameters.append(int(arg))
if all([type(elem)==int for elem in int_parameters]):
amax, bmax, div, nlim = int_parameters[:4]
else:
amax, bmax, div, nlim = eval(input('enter all ints with commas: amax, bmax, div, nlim\n'))
#amax, bmax, div, nlim = 1024, 1024, 2, 20
print('parameters: amax=', amax, ', bmax=',bmax, ', div=',div, ', nlim=',nlim)
collatz_map = collatz_mapper(amax, bmax, div, nlim)
#Save collatz map to file
filename = 'collatz_map_a'+str(amax)+'_b'+str(bmax)+'_div'+str(div)+'.colmap'
with open(filename, 'w') as file:
for row in range(2*amax):
for column in range(2*bmax):
file.write(str(collatz_map[row,column])+'\t')
file.write('\n')
#
collatz_plotter(collatz_map, div)
|
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.animation as anim
import sys
def collatz_mapper(amax, bmax, div=2, nlim=20):
"""
Returns a Numpy array with the Collatz Map. Utilizes ints to build the map.
Parameters
----------
amax: int
Maximum positive 'a' value of the map (horizontal axis). The map goes
from -amax to amax.
bmax: int
Maximum positive 'b' value of the map (vertical axis). The map goes
from -bmax to bmax.
div: int
Divisor for the generalized Collatz Problem.
nlim: int
Maximimum number of integers to search for convergence.
"""
a_range = range(-amax, amax)
b_range = range(-bmax,bmax)
d = div
collatz_map = np.zeros((len(b_range), len(a_range)))
n_currs = range(1,nlim+1)
n_min_init = 999999 #initialization value for n_min, so that it is bigger than n_curr
n_max = 1000000000
calc_steps = 10
max_mini_steps = 100 #maximum steps in collatz sequence to check for convergence
escape_value = np.pi #value given to list of fixed points if number of steps exceded.
for a in a_range:
for b in b_range:
min_fix = []
for n_curr in n_currs:
#print('a, b, n = ',a, b, n_curr)
step = 1
escaped = False
for _ in range(calc_steps):
if n_curr%d == 0:
if n_curr == 0:
n_min = 0
break
else:
n_curr = n_curr // d
else:
n_curr = a*n_curr + b
n_min = n_curr + n_min_init
while n_min != n_curr:
#print('n_curr=', n_curr, ', n_min=', n_min)
n_min = min(n_min, n_curr)
if n_curr%d == 0:
if n_curr == 0:
n_min = 0
break
else:
n_curr = n_curr // d
else:
n_curr = a*n_curr + b
step += 1
if step > max_mini_steps or abs(n_curr) > n_max:
#print('escaped')
escaped = True
break
if escaped:
min_fix.append(escape_value)
escaped = False
else:
min_fix.append(n_min)
#adding point to map
min_fix_setlist = list(set(min_fix))
if np.pi in min_fix_setlist:
if [np.pi]==min_fix_setlist:
collatz_map[b + bmax, a + amax] = 0
else:
collatz_map[b + bmax, a + amax] = 1
else:
if len(min_fix_setlist) == 1:
collatz_map[b + bmax, a + amax] = 3
else:
collatz_map[b + bmax, a + amax] = 2
#
return collatz_map
#
def collatz_plotter(col_map, div = 0, cmap='inferno', legend=True):
"""
Plots the collatz map.
Parameters
----------
colmap: numpy array
Contains the map.
div: int
Used as figure number and for filename if empty.
save_fig: boolean
Declares whether to save the figure or not.
savename: string
Name of the file where figure will be saved.
cmap: string or colormap
Set by default to 'inferno'.
"""
if div==0:
fig = plt.figure()
div = ''
else:
fig = plt.figure(div)
ax=fig.add_subplot(1,1,1)
values = np.unique(col_map)
image = plt.imshow(col_map, cmap=cmap)
colors = [image.cmap(image.norm(value)) for value in values]
labels = ['no convergence', 'convergence for some', 'convergence for all at diff', 'convergence for all at same']
patches = [mpatches.Patch(color=colors[i], label=labels[i]) for i in range(len(values))]
if legend:
plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
if div!=0:
plt.title('divisor = '+str(div))
plt.axis('off')
plt.show()
#
def collatz_animation(amax, bmax, div):
"""
Returns an animation object and saves it as Gif.
"""
pass
#
if __name__ == '__main__':
int_parameters = []
for arg in sys.argv[1:]:
int_parameters.append(int(arg))
if all([type(elem)==int for elem in int_parameters]):
amax, bmax, div, nlim = int_parameters[:4]
else:
amax, bmax, div, nlim = eval(input('enter all ints with commas: amax, bmax, div, nlim\n'))
#amax, bmax, div, nlim = 1024, 1024, 2, 20
print('parameters: amax=', amax, ', bmax=',bmax, ', div=',div, ', nlim=',nlim)
collatz_map = collatz_mapper(amax, bmax, div, nlim)
#Save collatz map to file
filename = 'collatz_map_a'+str(amax)+'_b'+str(bmax)+'_div'+str(div)+'.colmap'
with open(filename, 'w') as file:
for row in range(2*amax):
for column in range(2*bmax):
file.write(str(collatz_map[row,column])+'\t')
file.write('\n')
#
collatz_plotter(collatz_map, div)
|
en
| 0.571819
|
Returns a Numpy array with the Collatz Map. Utilizes ints to build the map. Parameters ---------- amax: int Maximum positive 'a' value of the map (horizontal axis). The map goes from -amax to amax. bmax: int Maximum positive 'b' value of the map (vertical axis). The map goes from -bmax to bmax. div: int Divisor for the generalized Collatz Problem. nlim: int Maximimum number of integers to search for convergence. #initialization value for n_min, so that it is bigger than n_curr #maximum steps in collatz sequence to check for convergence #value given to list of fixed points if number of steps exceded. #print('a, b, n = ',a, b, n_curr) #print('n_curr=', n_curr, ', n_min=', n_min) #print('escaped') #adding point to map # # Plots the collatz map. Parameters ---------- colmap: numpy array Contains the map. div: int Used as figure number and for filename if empty. save_fig: boolean Declares whether to save the figure or not. savename: string Name of the file where figure will be saved. cmap: string or colormap Set by default to 'inferno'. # Returns an animation object and saves it as Gif. # #amax, bmax, div, nlim = 1024, 1024, 2, 20 #Save collatz map to file #
| 3.368936
| 3
|
web/api/maestro_api/db/mongo.py
|
Farfetch/maestro
| 21
|
6625813
|
from mongoengine import connect
from maestro_api.db.repo.user import UserRepository
from maestro_api.db.models.user import UserRole
def init_db(flask_app=None):
connect(**flask_app.config["MONGODB_SETTINGS"])
def init_db_data(flask_app):
"Init DB initial data"
if flask_app.config["OAUTH_ENABLED"] is False:
user_repo = UserRepository()
user_repo.create_or_update(
name="Anonymous",
email=flask_app.config["MOCK_AUTH_ANONYMOUS_USER_EMAIL"],
role=UserRole.ADMIN.value,
)
|
from mongoengine import connect
from maestro_api.db.repo.user import UserRepository
from maestro_api.db.models.user import UserRole
def init_db(flask_app=None):
connect(**flask_app.config["MONGODB_SETTINGS"])
def init_db_data(flask_app):
"Init DB initial data"
if flask_app.config["OAUTH_ENABLED"] is False:
user_repo = UserRepository()
user_repo.create_or_update(
name="Anonymous",
email=flask_app.config["MOCK_AUTH_ANONYMOUS_USER_EMAIL"],
role=UserRole.ADMIN.value,
)
|
none
| 1
| 2.074078
| 2
|
|
src/azure-cli/azure/cli/command_modules/acr/_docker_utils.py
|
WCollins3/azure-cli
| 1
|
6625814
|
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# --------------------------------------------------------------------------------------------
try:
from urllib.parse import urlencode, urlparse, urlunparse
except ImportError:
from urllib import urlencode
from urlparse import urlparse, urlunparse
import time
from json import loads
from base64 import b64encode
import requests
from requests import RequestException
from requests.utils import to_native_string
from msrest.http_logger import log_request, log_response
from knack.util import CLIError
from knack.prompting import prompt, prompt_pass, NoTTYException
from knack.log import get_logger
from azure.cli.core.util import should_disable_connection_verify
from azure.cli.core.cloud import CloudSuffixNotSetException
from azure.cli.core._profile import _AZ_LOGIN_MESSAGE
from ._client_factory import cf_acr_registries
from ._constants import get_managed_sku
from ._utils import get_registry_by_name, ResourceNotFound
logger = get_logger(__name__)
EMPTY_GUID = '00000000-0000-0000-0000-000000000000'
ALLOWED_HTTP_METHOD = ['get', 'patch', 'put', 'delete']
ACCESS_TOKEN_PERMISSION = ['pull', 'push', 'delete', 'push,pull', 'delete,pull']
AAD_TOKEN_BASE_ERROR_MESSAGE = "Unable to get AAD authorization tokens with message"
ADMIN_USER_BASE_ERROR_MESSAGE = "Unable to get admin user credentials with message"
def _get_aad_token_after_challenge(cli_ctx,
token_params,
login_server,
only_refresh_token,
repository,
artifact_repository,
permission,
is_diagnostics_context):
authurl = urlparse(token_params['realm'])
authhost = urlunparse((authurl[0], authurl[1], '/oauth2/exchange', '', '', ''))
from azure.cli.core._profile import Profile
profile = Profile(cli_ctx=cli_ctx)
creds, _, tenant = profile.get_raw_token()
headers = {'Content-Type': 'application/x-www-form-urlencoded'}
content = {
'grant_type': 'access_token',
'service': token_params['service'],
'tenant': tenant,
'access_token': creds[1]
}
response = requests.post(authhost, urlencode(content), headers=headers,
verify=(not should_disable_connection_verify()))
if response.status_code not in [200]:
from ._errors import CONNECTIVITY_REFRESH_TOKEN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_REFRESH_TOKEN_ERROR.format_error_message(login_server, response.status_code)
raise CLIError(CONNECTIVITY_REFRESH_TOKEN_ERROR.format_error_message(login_server, response.status_code)
.get_error_message())
refresh_token = loads(response.content.decode("utf-8"))["refresh_token"]
if only_refresh_token:
return refresh_token
authhost = urlunparse((authurl[0], authurl[1], '/oauth2/token', '', '', ''))
if repository:
scope = 'repository:{}:{}'.format(repository, permission)
elif artifact_repository:
scope = 'artifact-repository:{}:{}'.format(artifact_repository, permission)
else:
# catalog only has * as permission, even for a read operation
scope = 'registry:catalog:*'
content = {
'grant_type': 'refresh_token',
'service': login_server,
'scope': scope,
'refresh_token': refresh_token
}
response = requests.post(authhost, urlencode(content), headers=headers,
verify=(not should_disable_connection_verify()))
if response.status_code not in [200]:
from ._errors import CONNECTIVITY_ACCESS_TOKEN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_ACCESS_TOKEN_ERROR.format_error_message(login_server, response.status_code)
raise CLIError(CONNECTIVITY_ACCESS_TOKEN_ERROR.format_error_message(login_server, response.status_code)
.get_error_message())
return loads(response.content.decode("utf-8"))["access_token"]
def _get_aad_token(cli_ctx,
login_server,
only_refresh_token,
repository=None,
artifact_repository=None,
permission=None,
is_diagnostics_context=False):
"""Obtains refresh and access tokens for an AAD-enabled registry.
:param str login_server: The registry login server URL to log in to
:param bool only_refresh_token: Whether to ask for only refresh token, or for both refresh and access tokens
:param str repository: Repository for which the access token is requested
:param str artifact_repository: Artifact repository for which the access token is requested
:param str permission: The requested permission on the repository, '*' or 'pull'
"""
if repository and artifact_repository:
raise ValueError("Only one of repository and artifact_repository can be provided.")
if (repository or artifact_repository) and permission not in ACCESS_TOKEN_PERMISSION:
raise ValueError(
"Permission is required for a repository or artifact_repository. Allowed access token permission: {}"
.format(ACCESS_TOKEN_PERMISSION))
login_server = login_server.rstrip('/')
challenge = requests.get('https://' + login_server + '/v2/', verify=(not should_disable_connection_verify()))
if challenge.status_code not in [401] or 'WWW-Authenticate' not in challenge.headers:
from ._errors import CONNECTIVITY_CHALLENGE_ERROR
if is_diagnostics_context:
return CONNECTIVITY_CHALLENGE_ERROR.format_error_message(login_server)
raise CLIError(CONNECTIVITY_CHALLENGE_ERROR.format_error_message(login_server).get_error_message())
authenticate = challenge.headers['WWW-Authenticate']
tokens = authenticate.split(' ', 2)
if len(tokens) < 2 or tokens[0].lower() != 'bearer':
from ._errors import CONNECTIVITY_AAD_LOGIN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server)
raise CLIError(CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server).get_error_message())
token_params = {y[0]: y[1].strip('"') for y in
(x.strip().split('=', 2) for x in tokens[1].split(','))}
if 'realm' not in token_params or 'service' not in token_params:
from ._errors import CONNECTIVITY_AAD_LOGIN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server)
raise CLIError(CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server).get_error_message())
return _get_aad_token_after_challenge(cli_ctx,
token_params,
login_server,
only_refresh_token,
repository,
artifact_repository,
permission,
is_diagnostics_context)
def _get_credentials(cmd, # pylint: disable=too-many-statements
registry_name,
tenant_suffix,
username,
password,
only_refresh_token,
repository=None,
artifact_repository=None,
permission=None):
"""Try to get AAD authorization tokens or admin user credentials.
:param str registry_name: The name of container registry
:param str tenant_suffix: The registry login server tenant suffix
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
:param bool only_refresh_token: Whether to ask for only refresh token, or for both refresh and access tokens
:param str repository: Repository for which the access token is requested
:param str artifact_repository: Artifact repository for which the access token is requested
:param str permission: The requested permission on the repository, '*' or 'pull'
"""
# Raise an error if password is specified but username isn't
if not username and password:
raise CLIError('Please also specify username if password is specified.')
cli_ctx = cmd.cli_ctx
resource_not_found, registry = None, None
try:
registry, resource_group_name = get_registry_by_name(cli_ctx, registry_name)
login_server = registry.login_server
if tenant_suffix:
logger.warning(
"Obtained registry login server '%s' from service. The specified suffix '%s' is ignored.",
login_server, tenant_suffix)
except (ResourceNotFound, CLIError) as e:
resource_not_found = str(e)
logger.debug("Could not get registry from service. Exception: %s", resource_not_found)
if not isinstance(e, ResourceNotFound) and _AZ_LOGIN_MESSAGE not in resource_not_found:
raise
# Try to use the pre-defined login server suffix to construct login server from registry name.
login_server_suffix = get_login_server_suffix(cli_ctx)
if not login_server_suffix:
raise
login_server = '{}{}{}'.format(
registry_name, '-{}'.format(tenant_suffix) if tenant_suffix else '', login_server_suffix).lower()
# Validate the login server is reachable
url = 'https://' + login_server + '/v2/'
try:
challenge = requests.get(url, verify=(not should_disable_connection_verify()))
if challenge.status_code in [403]:
raise CLIError("Looks like you don't have access to registry '{}'. ".format(login_server) +
"To see configured firewall rules, run" +
" 'az acr show --query networkRuleSet --name {}'. ".format(registry_name) +
"Details: https://docs.microsoft.com/en-us/azure/container-registry/container-registry-health-error-reference#connectivity_forbidden_error") # pylint: disable=line-too-long
except RequestException as e:
logger.debug("Could not connect to registry login server. Exception: %s", str(e))
if resource_not_found:
logger.warning("%s\nUsing '%s' as the default registry login server.", resource_not_found, login_server)
raise CLIError("Could not connect to the registry login server '{}'. ".format(login_server) +
"Please verify that the registry exists and " +
"the URL '{}' is reachable from your environment.".format(url))
# 1. if username was specified, verify that password was also specified
if username:
if not password:
try:
password = prompt_pass(msg='Password: ')
except NoTTYException:
raise CLIError('Please specify both username and password in non-interactive mode.')
return login_server, username, password
# 2. if we don't yet have credentials, attempt to get a refresh token
if not registry or registry.sku.name in get_managed_sku(cmd):
try:
return login_server, EMPTY_GUID, _get_aad_token(
cli_ctx, login_server, only_refresh_token, repository, artifact_repository, permission)
except CLIError as e:
logger.warning("%s: %s", AAD_TOKEN_BASE_ERROR_MESSAGE, str(e))
# 3. if we still don't have credentials, attempt to get the admin credentials (if enabled)
if registry:
if registry.admin_user_enabled:
try:
cred = cf_acr_registries(cli_ctx).list_credentials(resource_group_name, registry_name)
return login_server, cred.username, cred.passwords[0].value
except CLIError as e:
logger.warning("%s: %s", ADMIN_USER_BASE_ERROR_MESSAGE, str(e))
else:
logger.warning("%s: %s", ADMIN_USER_BASE_ERROR_MESSAGE, "Admin user is disabled.")
else:
logger.warning("%s: %s", ADMIN_USER_BASE_ERROR_MESSAGE, resource_not_found)
# 4. if we still don't have credentials, prompt the user
try:
username = prompt('Username: ')
password = <PASSWORD>(msg='Password: ')
return login_server, username, password
except NoTTYException:
raise CLIError(
'Unable to authenticate using AAD or admin login credentials. ' +
'Please specify both username and password in non-interactive mode.')
return login_server, None, None
def get_login_credentials(cmd,
registry_name,
tenant_suffix=None,
username=None,
password=None):
"""Try to get AAD authorization tokens or admin user credentials to log into a registry.
:param str registry_name: The name of container registry
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
"""
return _get_credentials(cmd,
registry_name,
tenant_suffix,
username,
password,
only_refresh_token=True)
def get_access_credentials(cmd,
registry_name,
tenant_suffix=None,
username=None,
password=<PASSWORD>,
repository=None,
artifact_repository=None,
permission=None):
"""Try to get AAD authorization tokens or admin user credentials to access a registry.
:param str registry_name: The name of container registry
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
:param str repository: Repository for which the access token is requested
:param str artifact_repository: Artifact repository for which the access token is requested
:param str permission: The requested permission on the repository
"""
return _get_credentials(cmd,
registry_name,
tenant_suffix,
username,
password,
only_refresh_token=False,
repository=repository,
artifact_repository=artifact_repository,
permission=permission)
def log_registry_response(response):
"""Log the HTTP request and response of a registry API call.
:param Response response: The response object
"""
log_request(None, response.request)
log_response(None, response.request, RegistryResponse(response.request, response))
def get_login_server_suffix(cli_ctx):
"""Get the Azure Container Registry login server suffix in the current cloud."""
try:
return cli_ctx.cloud.suffixes.acr_login_server_endpoint
except CloudSuffixNotSetException as e:
logger.debug("Could not get login server endpoint suffix. Exception: %s", str(e))
# Ignore the error if the suffix is not set, the caller should then try to get login server from server.
return None
def _get_basic_auth_str(username, password):
return 'Basic ' + to_native_string(
b64encode(('%s:%s' % (username, password)).encode('latin1')).strip()
)
def _get_bearer_auth_str(token):
return 'Bearer ' + token
def get_authorization_header(username, password):
"""Get the authorization header as Basic auth if username is provided, or Bearer auth otherwise
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
"""
if username == EMPTY_GUID:
auth = _get_bearer_auth_str(password)
else:
auth = _get_basic_auth_str(username, password)
return {'Authorization': auth}
def request_data_from_registry(http_method,
login_server,
path,
username,
password,
result_index=None,
json_payload=None,
file_payload=None,
params=None,
retry_times=3,
retry_interval=5):
if http_method not in ALLOWED_HTTP_METHOD:
raise ValueError("Allowed http method: {}".format(ALLOWED_HTTP_METHOD))
if json_payload and file_payload:
raise ValueError("One of json_payload and file_payload can be specified.")
if http_method in ['get', 'delete'] and (json_payload or file_payload):
raise ValueError("Empty payload is required for http method: {}".format(http_method))
if http_method in ['patch', 'put'] and not (json_payload or file_payload):
raise ValueError("Non-empty payload is required for http method: {}".format(http_method))
url = 'https://{}{}'.format(login_server, path)
headers = get_authorization_header(username, password)
for i in range(0, retry_times):
errorMessage = None
try:
if file_payload:
with open(file_payload, 'rb') as data_payload:
response = requests.request(
method=http_method,
url=url,
headers=headers,
params=params,
data=data_payload,
verify=(not should_disable_connection_verify())
)
else:
response = requests.request(
method=http_method,
url=url,
headers=headers,
params=params,
json=json_payload,
verify=(not should_disable_connection_verify())
)
log_registry_response(response)
if response.status_code == 200:
result = response.json()[result_index] if result_index else response.json()
next_link = response.headers['link'] if 'link' in response.headers else None
return result, next_link
if response.status_code == 201 or response.status_code == 202:
result = None
try:
result = response.json()[result_index] if result_index else response.json()
except ValueError as e:
logger.debug('Response is empty or is not a valid json. Exception: %s', str(e))
return result, None
if response.status_code == 204:
return None, None
if response.status_code == 401:
raise RegistryException(
parse_error_message('Authentication required.', response),
response.status_code)
if response.status_code == 404:
raise RegistryException(
parse_error_message('The requested data does not exist.', response),
response.status_code)
if response.status_code == 405:
raise RegistryException(
parse_error_message('This operation is not supported.', response),
response.status_code)
if response.status_code == 409:
raise RegistryException(
parse_error_message('Failed to request data due to a conflict.', response),
response.status_code)
raise Exception(parse_error_message('Could not {} the requested data.'.format(http_method), response))
except CLIError:
raise
except Exception as e: # pylint: disable=broad-except
errorMessage = str(e)
logger.debug('Retrying %s with exception %s', i + 1, errorMessage)
time.sleep(retry_interval)
raise CLIError(errorMessage)
def parse_error_message(error_message, response):
import json
try:
server_message = json.loads(response.text)['errors'][0]['message']
error_message = 'Error: {}'.format(server_message) if server_message else error_message
except (ValueError, KeyError, TypeError, IndexError):
pass
if not error_message.endswith('.'):
error_message = '{}.'.format(error_message)
try:
correlation_id = response.headers['x-ms-correlation-request-id']
return '{} Correlation ID: {}.'.format(error_message, correlation_id)
except (KeyError, TypeError, AttributeError):
return error_message
class RegistryException(CLIError):
def __init__(self, message, status_code):
super(RegistryException, self).__init__(message)
self.status_code = status_code
class RegistryResponse(object): # pylint: disable=too-few-public-methods
def __init__(self, request, internal_response):
self.request = request
self.internal_response = internal_response
self.status_code = internal_response.status_code
self.headers = internal_response.headers
self.encoding = internal_response.encoding
self.reason = internal_response.reason
self.content = internal_response.content
def text(self):
return self.content.decode(self.encoding or "utf-8")
|
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# --------------------------------------------------------------------------------------------
try:
from urllib.parse import urlencode, urlparse, urlunparse
except ImportError:
from urllib import urlencode
from urlparse import urlparse, urlunparse
import time
from json import loads
from base64 import b64encode
import requests
from requests import RequestException
from requests.utils import to_native_string
from msrest.http_logger import log_request, log_response
from knack.util import CLIError
from knack.prompting import prompt, prompt_pass, NoTTYException
from knack.log import get_logger
from azure.cli.core.util import should_disable_connection_verify
from azure.cli.core.cloud import CloudSuffixNotSetException
from azure.cli.core._profile import _AZ_LOGIN_MESSAGE
from ._client_factory import cf_acr_registries
from ._constants import get_managed_sku
from ._utils import get_registry_by_name, ResourceNotFound
logger = get_logger(__name__)
EMPTY_GUID = '00000000-0000-0000-0000-000000000000'
ALLOWED_HTTP_METHOD = ['get', 'patch', 'put', 'delete']
ACCESS_TOKEN_PERMISSION = ['pull', 'push', 'delete', 'push,pull', 'delete,pull']
AAD_TOKEN_BASE_ERROR_MESSAGE = "Unable to get AAD authorization tokens with message"
ADMIN_USER_BASE_ERROR_MESSAGE = "Unable to get admin user credentials with message"
def _get_aad_token_after_challenge(cli_ctx,
token_params,
login_server,
only_refresh_token,
repository,
artifact_repository,
permission,
is_diagnostics_context):
authurl = urlparse(token_params['realm'])
authhost = urlunparse((authurl[0], authurl[1], '/oauth2/exchange', '', '', ''))
from azure.cli.core._profile import Profile
profile = Profile(cli_ctx=cli_ctx)
creds, _, tenant = profile.get_raw_token()
headers = {'Content-Type': 'application/x-www-form-urlencoded'}
content = {
'grant_type': 'access_token',
'service': token_params['service'],
'tenant': tenant,
'access_token': creds[1]
}
response = requests.post(authhost, urlencode(content), headers=headers,
verify=(not should_disable_connection_verify()))
if response.status_code not in [200]:
from ._errors import CONNECTIVITY_REFRESH_TOKEN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_REFRESH_TOKEN_ERROR.format_error_message(login_server, response.status_code)
raise CLIError(CONNECTIVITY_REFRESH_TOKEN_ERROR.format_error_message(login_server, response.status_code)
.get_error_message())
refresh_token = loads(response.content.decode("utf-8"))["refresh_token"]
if only_refresh_token:
return refresh_token
authhost = urlunparse((authurl[0], authurl[1], '/oauth2/token', '', '', ''))
if repository:
scope = 'repository:{}:{}'.format(repository, permission)
elif artifact_repository:
scope = 'artifact-repository:{}:{}'.format(artifact_repository, permission)
else:
# catalog only has * as permission, even for a read operation
scope = 'registry:catalog:*'
content = {
'grant_type': 'refresh_token',
'service': login_server,
'scope': scope,
'refresh_token': refresh_token
}
response = requests.post(authhost, urlencode(content), headers=headers,
verify=(not should_disable_connection_verify()))
if response.status_code not in [200]:
from ._errors import CONNECTIVITY_ACCESS_TOKEN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_ACCESS_TOKEN_ERROR.format_error_message(login_server, response.status_code)
raise CLIError(CONNECTIVITY_ACCESS_TOKEN_ERROR.format_error_message(login_server, response.status_code)
.get_error_message())
return loads(response.content.decode("utf-8"))["access_token"]
def _get_aad_token(cli_ctx,
login_server,
only_refresh_token,
repository=None,
artifact_repository=None,
permission=None,
is_diagnostics_context=False):
"""Obtains refresh and access tokens for an AAD-enabled registry.
:param str login_server: The registry login server URL to log in to
:param bool only_refresh_token: Whether to ask for only refresh token, or for both refresh and access tokens
:param str repository: Repository for which the access token is requested
:param str artifact_repository: Artifact repository for which the access token is requested
:param str permission: The requested permission on the repository, '*' or 'pull'
"""
if repository and artifact_repository:
raise ValueError("Only one of repository and artifact_repository can be provided.")
if (repository or artifact_repository) and permission not in ACCESS_TOKEN_PERMISSION:
raise ValueError(
"Permission is required for a repository or artifact_repository. Allowed access token permission: {}"
.format(ACCESS_TOKEN_PERMISSION))
login_server = login_server.rstrip('/')
challenge = requests.get('https://' + login_server + '/v2/', verify=(not should_disable_connection_verify()))
if challenge.status_code not in [401] or 'WWW-Authenticate' not in challenge.headers:
from ._errors import CONNECTIVITY_CHALLENGE_ERROR
if is_diagnostics_context:
return CONNECTIVITY_CHALLENGE_ERROR.format_error_message(login_server)
raise CLIError(CONNECTIVITY_CHALLENGE_ERROR.format_error_message(login_server).get_error_message())
authenticate = challenge.headers['WWW-Authenticate']
tokens = authenticate.split(' ', 2)
if len(tokens) < 2 or tokens[0].lower() != 'bearer':
from ._errors import CONNECTIVITY_AAD_LOGIN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server)
raise CLIError(CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server).get_error_message())
token_params = {y[0]: y[1].strip('"') for y in
(x.strip().split('=', 2) for x in tokens[1].split(','))}
if 'realm' not in token_params or 'service' not in token_params:
from ._errors import CONNECTIVITY_AAD_LOGIN_ERROR
if is_diagnostics_context:
return CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server)
raise CLIError(CONNECTIVITY_AAD_LOGIN_ERROR.format_error_message(login_server).get_error_message())
return _get_aad_token_after_challenge(cli_ctx,
token_params,
login_server,
only_refresh_token,
repository,
artifact_repository,
permission,
is_diagnostics_context)
def _get_credentials(cmd, # pylint: disable=too-many-statements
registry_name,
tenant_suffix,
username,
password,
only_refresh_token,
repository=None,
artifact_repository=None,
permission=None):
"""Try to get AAD authorization tokens or admin user credentials.
:param str registry_name: The name of container registry
:param str tenant_suffix: The registry login server tenant suffix
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
:param bool only_refresh_token: Whether to ask for only refresh token, or for both refresh and access tokens
:param str repository: Repository for which the access token is requested
:param str artifact_repository: Artifact repository for which the access token is requested
:param str permission: The requested permission on the repository, '*' or 'pull'
"""
# Raise an error if password is specified but username isn't
if not username and password:
raise CLIError('Please also specify username if password is specified.')
cli_ctx = cmd.cli_ctx
resource_not_found, registry = None, None
try:
registry, resource_group_name = get_registry_by_name(cli_ctx, registry_name)
login_server = registry.login_server
if tenant_suffix:
logger.warning(
"Obtained registry login server '%s' from service. The specified suffix '%s' is ignored.",
login_server, tenant_suffix)
except (ResourceNotFound, CLIError) as e:
resource_not_found = str(e)
logger.debug("Could not get registry from service. Exception: %s", resource_not_found)
if not isinstance(e, ResourceNotFound) and _AZ_LOGIN_MESSAGE not in resource_not_found:
raise
# Try to use the pre-defined login server suffix to construct login server from registry name.
login_server_suffix = get_login_server_suffix(cli_ctx)
if not login_server_suffix:
raise
login_server = '{}{}{}'.format(
registry_name, '-{}'.format(tenant_suffix) if tenant_suffix else '', login_server_suffix).lower()
# Validate the login server is reachable
url = 'https://' + login_server + '/v2/'
try:
challenge = requests.get(url, verify=(not should_disable_connection_verify()))
if challenge.status_code in [403]:
raise CLIError("Looks like you don't have access to registry '{}'. ".format(login_server) +
"To see configured firewall rules, run" +
" 'az acr show --query networkRuleSet --name {}'. ".format(registry_name) +
"Details: https://docs.microsoft.com/en-us/azure/container-registry/container-registry-health-error-reference#connectivity_forbidden_error") # pylint: disable=line-too-long
except RequestException as e:
logger.debug("Could not connect to registry login server. Exception: %s", str(e))
if resource_not_found:
logger.warning("%s\nUsing '%s' as the default registry login server.", resource_not_found, login_server)
raise CLIError("Could not connect to the registry login server '{}'. ".format(login_server) +
"Please verify that the registry exists and " +
"the URL '{}' is reachable from your environment.".format(url))
# 1. if username was specified, verify that password was also specified
if username:
if not password:
try:
password = prompt_pass(msg='Password: ')
except NoTTYException:
raise CLIError('Please specify both username and password in non-interactive mode.')
return login_server, username, password
# 2. if we don't yet have credentials, attempt to get a refresh token
if not registry or registry.sku.name in get_managed_sku(cmd):
try:
return login_server, EMPTY_GUID, _get_aad_token(
cli_ctx, login_server, only_refresh_token, repository, artifact_repository, permission)
except CLIError as e:
logger.warning("%s: %s", AAD_TOKEN_BASE_ERROR_MESSAGE, str(e))
# 3. if we still don't have credentials, attempt to get the admin credentials (if enabled)
if registry:
if registry.admin_user_enabled:
try:
cred = cf_acr_registries(cli_ctx).list_credentials(resource_group_name, registry_name)
return login_server, cred.username, cred.passwords[0].value
except CLIError as e:
logger.warning("%s: %s", ADMIN_USER_BASE_ERROR_MESSAGE, str(e))
else:
logger.warning("%s: %s", ADMIN_USER_BASE_ERROR_MESSAGE, "Admin user is disabled.")
else:
logger.warning("%s: %s", ADMIN_USER_BASE_ERROR_MESSAGE, resource_not_found)
# 4. if we still don't have credentials, prompt the user
try:
username = prompt('Username: ')
password = <PASSWORD>(msg='Password: ')
return login_server, username, password
except NoTTYException:
raise CLIError(
'Unable to authenticate using AAD or admin login credentials. ' +
'Please specify both username and password in non-interactive mode.')
return login_server, None, None
def get_login_credentials(cmd,
registry_name,
tenant_suffix=None,
username=None,
password=None):
"""Try to get AAD authorization tokens or admin user credentials to log into a registry.
:param str registry_name: The name of container registry
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
"""
return _get_credentials(cmd,
registry_name,
tenant_suffix,
username,
password,
only_refresh_token=True)
def get_access_credentials(cmd,
registry_name,
tenant_suffix=None,
username=None,
password=<PASSWORD>,
repository=None,
artifact_repository=None,
permission=None):
"""Try to get AAD authorization tokens or admin user credentials to access a registry.
:param str registry_name: The name of container registry
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
:param str repository: Repository for which the access token is requested
:param str artifact_repository: Artifact repository for which the access token is requested
:param str permission: The requested permission on the repository
"""
return _get_credentials(cmd,
registry_name,
tenant_suffix,
username,
password,
only_refresh_token=False,
repository=repository,
artifact_repository=artifact_repository,
permission=permission)
def log_registry_response(response):
"""Log the HTTP request and response of a registry API call.
:param Response response: The response object
"""
log_request(None, response.request)
log_response(None, response.request, RegistryResponse(response.request, response))
def get_login_server_suffix(cli_ctx):
"""Get the Azure Container Registry login server suffix in the current cloud."""
try:
return cli_ctx.cloud.suffixes.acr_login_server_endpoint
except CloudSuffixNotSetException as e:
logger.debug("Could not get login server endpoint suffix. Exception: %s", str(e))
# Ignore the error if the suffix is not set, the caller should then try to get login server from server.
return None
def _get_basic_auth_str(username, password):
return 'Basic ' + to_native_string(
b64encode(('%s:%s' % (username, password)).encode('latin1')).strip()
)
def _get_bearer_auth_str(token):
return 'Bearer ' + token
def get_authorization_header(username, password):
"""Get the authorization header as Basic auth if username is provided, or Bearer auth otherwise
:param str username: The username used to log into the container registry
:param str password: The password used to log into the container registry
"""
if username == EMPTY_GUID:
auth = _get_bearer_auth_str(password)
else:
auth = _get_basic_auth_str(username, password)
return {'Authorization': auth}
def request_data_from_registry(http_method,
login_server,
path,
username,
password,
result_index=None,
json_payload=None,
file_payload=None,
params=None,
retry_times=3,
retry_interval=5):
if http_method not in ALLOWED_HTTP_METHOD:
raise ValueError("Allowed http method: {}".format(ALLOWED_HTTP_METHOD))
if json_payload and file_payload:
raise ValueError("One of json_payload and file_payload can be specified.")
if http_method in ['get', 'delete'] and (json_payload or file_payload):
raise ValueError("Empty payload is required for http method: {}".format(http_method))
if http_method in ['patch', 'put'] and not (json_payload or file_payload):
raise ValueError("Non-empty payload is required for http method: {}".format(http_method))
url = 'https://{}{}'.format(login_server, path)
headers = get_authorization_header(username, password)
for i in range(0, retry_times):
errorMessage = None
try:
if file_payload:
with open(file_payload, 'rb') as data_payload:
response = requests.request(
method=http_method,
url=url,
headers=headers,
params=params,
data=data_payload,
verify=(not should_disable_connection_verify())
)
else:
response = requests.request(
method=http_method,
url=url,
headers=headers,
params=params,
json=json_payload,
verify=(not should_disable_connection_verify())
)
log_registry_response(response)
if response.status_code == 200:
result = response.json()[result_index] if result_index else response.json()
next_link = response.headers['link'] if 'link' in response.headers else None
return result, next_link
if response.status_code == 201 or response.status_code == 202:
result = None
try:
result = response.json()[result_index] if result_index else response.json()
except ValueError as e:
logger.debug('Response is empty or is not a valid json. Exception: %s', str(e))
return result, None
if response.status_code == 204:
return None, None
if response.status_code == 401:
raise RegistryException(
parse_error_message('Authentication required.', response),
response.status_code)
if response.status_code == 404:
raise RegistryException(
parse_error_message('The requested data does not exist.', response),
response.status_code)
if response.status_code == 405:
raise RegistryException(
parse_error_message('This operation is not supported.', response),
response.status_code)
if response.status_code == 409:
raise RegistryException(
parse_error_message('Failed to request data due to a conflict.', response),
response.status_code)
raise Exception(parse_error_message('Could not {} the requested data.'.format(http_method), response))
except CLIError:
raise
except Exception as e: # pylint: disable=broad-except
errorMessage = str(e)
logger.debug('Retrying %s with exception %s', i + 1, errorMessage)
time.sleep(retry_interval)
raise CLIError(errorMessage)
def parse_error_message(error_message, response):
import json
try:
server_message = json.loads(response.text)['errors'][0]['message']
error_message = 'Error: {}'.format(server_message) if server_message else error_message
except (ValueError, KeyError, TypeError, IndexError):
pass
if not error_message.endswith('.'):
error_message = '{}.'.format(error_message)
try:
correlation_id = response.headers['x-ms-correlation-request-id']
return '{} Correlation ID: {}.'.format(error_message, correlation_id)
except (KeyError, TypeError, AttributeError):
return error_message
class RegistryException(CLIError):
def __init__(self, message, status_code):
super(RegistryException, self).__init__(message)
self.status_code = status_code
class RegistryResponse(object): # pylint: disable=too-few-public-methods
def __init__(self, request, internal_response):
self.request = request
self.internal_response = internal_response
self.status_code = internal_response.status_code
self.headers = internal_response.headers
self.encoding = internal_response.encoding
self.reason = internal_response.reason
self.content = internal_response.content
def text(self):
return self.content.decode(self.encoding or "utf-8")
|
en
| 0.759035
|
# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- # catalog only has * as permission, even for a read operation Obtains refresh and access tokens for an AAD-enabled registry. :param str login_server: The registry login server URL to log in to :param bool only_refresh_token: Whether to ask for only refresh token, or for both refresh and access tokens :param str repository: Repository for which the access token is requested :param str artifact_repository: Artifact repository for which the access token is requested :param str permission: The requested permission on the repository, '*' or 'pull' # pylint: disable=too-many-statements Try to get AAD authorization tokens or admin user credentials. :param str registry_name: The name of container registry :param str tenant_suffix: The registry login server tenant suffix :param str username: The username used to log into the container registry :param str password: The password used to log into the container registry :param bool only_refresh_token: Whether to ask for only refresh token, or for both refresh and access tokens :param str repository: Repository for which the access token is requested :param str artifact_repository: Artifact repository for which the access token is requested :param str permission: The requested permission on the repository, '*' or 'pull' # Raise an error if password is specified but username isn't # Try to use the pre-defined login server suffix to construct login server from registry name. # Validate the login server is reachable #connectivity_forbidden_error") # pylint: disable=line-too-long # 1. if username was specified, verify that password was also specified # 2. if we don't yet have credentials, attempt to get a refresh token # 3. if we still don't have credentials, attempt to get the admin credentials (if enabled) # 4. if we still don't have credentials, prompt the user Try to get AAD authorization tokens or admin user credentials to log into a registry. :param str registry_name: The name of container registry :param str username: The username used to log into the container registry :param str password: The password used to log into the container registry Try to get AAD authorization tokens or admin user credentials to access a registry. :param str registry_name: The name of container registry :param str username: The username used to log into the container registry :param str password: The password used to log into the container registry :param str repository: Repository for which the access token is requested :param str artifact_repository: Artifact repository for which the access token is requested :param str permission: The requested permission on the repository Log the HTTP request and response of a registry API call. :param Response response: The response object Get the Azure Container Registry login server suffix in the current cloud. # Ignore the error if the suffix is not set, the caller should then try to get login server from server. Get the authorization header as Basic auth if username is provided, or Bearer auth otherwise :param str username: The username used to log into the container registry :param str password: The password used to log into the container registry # pylint: disable=broad-except # pylint: disable=too-few-public-methods
| 1.840435
| 2
|
src/main.py
|
glovguy/survey_cluster
| 0
|
6625815
|
<reponame>glovguy/survey_cluster
import json
from models.surveys import Surveys
from models.clusters import KmeansClusters
from cluster_diagram import generate_diagram
from silouette_scores import find_best_clust_num
data_raw = [
{'survey_text': 'The quick brown fox jumps over the lazy dog', 'surveyid': '1'},
{'survey_text': 'Some days require more coffee than others', 'surveyid': '2'},
{'survey_text': 'coffee makes the world go round', 'surveyid': '3'},
{'survey_text': 'Crazy like a fox', 'surveyid': '4'}
]
infer_num_clusters = False
num_clusters = 2
srvys = Surveys(data_raw)
kmObject = KmeansClusters(srvys)
kmObject.set_num_clusters(num_clusters) if infer_num_clusters else find_best_clust_num(kmObject, save_plot=True)
generate_diagram(srvys, kmObject)
print(json.dumps(kmObject.clusters_to_dict()))
|
import json
from models.surveys import Surveys
from models.clusters import KmeansClusters
from cluster_diagram import generate_diagram
from silouette_scores import find_best_clust_num
data_raw = [
{'survey_text': 'The quick brown fox jumps over the lazy dog', 'surveyid': '1'},
{'survey_text': 'Some days require more coffee than others', 'surveyid': '2'},
{'survey_text': 'coffee makes the world go round', 'surveyid': '3'},
{'survey_text': 'Crazy like a fox', 'surveyid': '4'}
]
infer_num_clusters = False
num_clusters = 2
srvys = Surveys(data_raw)
kmObject = KmeansClusters(srvys)
kmObject.set_num_clusters(num_clusters) if infer_num_clusters else find_best_clust_num(kmObject, save_plot=True)
generate_diagram(srvys, kmObject)
print(json.dumps(kmObject.clusters_to_dict()))
|
none
| 1
| 2.570536
| 3
|
|
lccs_ws/views.py
|
brazil-data-cube/lccs-ws
| 2
|
6625816
|
<filename>lccs_ws/views.py
#
# This file is part of Land Cover Classification System Web Service.
# Copyright (C) 2020-2021 INPE.
#
# Land Cover Classification System Web Service is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""Views of Land Cover Classification System Web Service."""
from bdc_auth_client.decorators import oauth2
from flask import abort, current_app, jsonify, request, send_file
from werkzeug.urls import url_encode
from lccs_ws.forms import (ClassesMappingMetadataSchema, ClassesSchema,
ClassificationSystemMetadataSchema,
ClassMetadataForm, ClassMetadataSchema,
StyleFormatsMetadataSchema, StyleFormatsSchema)
from . import data
from .config import Config
from .utils import language
BASE_URL = Config.LCCS_URL
@current_app.before_request
def before_request():
"""Handle for before request processing."""
request.assets_kwargs = None
if Config.BDC_LCCS_ARGS:
assets_kwargs = {arg: request.args.get(arg) for arg in Config.BDC_LCCS_ARGS.split(",")}
if "access_token" in request.args:
assets_kwargs["access_token"] = request.args.get("access_token")
assets_kwargs = "?" + url_encode(assets_kwargs) if url_encode(assets_kwargs) else ""
request.assets_kwargs = assets_kwargs
if Config.BDC_LCCS_ARGS_I18N:
intern_kwargs = {arg: request.args.get(arg) for arg in Config.BDC_LCCS_ARGS_I18N.split(",")}
if "language" in request.args:
intern_kwargs["language"] = request.args.get("language")
intern_kwargs = "&" + url_encode(intern_kwargs) if url_encode(intern_kwargs) else ""
request.intern_kwargs = intern_kwargs
@current_app.route("/", methods=["GET"])
@oauth2(required=False)
def root(**kwargs):
"""URL Handler for Land User Cover Classification System through REST API."""
links = list()
response = dict()
links += [
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "Link to this document"
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_systems", "type": "application/json",
"title": "Information about Classification Systems",
},
{
"href": f"{BASE_URL}/style_formats{request.assets_kwargs}",
"rel": "style_formats", "type": "application/json",
"title": "Information about Style Formats"
}
]
response["links"] = links
response["application_name"] = "Land Cover Classification System Service"
response["version"] = Config.BDC_LCCS_API_VERSION
return response, 200
@current_app.route("/classification_systems", methods=["GET"])
@oauth2(required=True)
@language()
def get_classification_systems(**kwargs):
"""Retrieve the list of available classification systems in the service."""
classification_systems_list = data.get_classification_systems()
for class_system in classification_systems_list:
links = [
{
"href": f"{BASE_URL}/classification_systems/{class_system['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_system",
"type": "application/json",
"title": "Link to Classification System",
},
{
"href": f"{BASE_URL}/classification_systems/{class_system['id']}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classes",
"type": "application/json",
"title": "Link to Classification System Classes",
},
{
"href": f"{BASE_URL}/classification_systems/{class_system['id']}/style_formats{request.assets_kwargs}",
"rel": "style_formats",
"type": "application/json",
"title": "Link to Available Style Formats",
},
{
"href": f"{BASE_URL}/mappings/{class_system['id']}{request.assets_kwargs}",
"rel": "mappings",
"type": "application/json",
"title": "Link to Classification Mappings",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "Link to this document",
},
]
class_system["links"] = links
return jsonify(classification_systems_list), 200
@current_app.route("/classification_systems/<system_id_or_identifier>", methods=["GET"])
@language()
@oauth2(required=True)
def get_classification_system(system_id_or_identifier, **kwargs):
"""Retrieve information about the classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
classification_system = data.get_classification_system(system_id_or_identifier)
if not classification_system:
abort(404, "Classification System not found.")
links = [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to this document",
},
{
"href": f"{BASE_URL}/classification_systems/{classification_system['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "The classification_system",
},
{
"href": f"{BASE_URL}/classification_systems/{classification_system['id']}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classes",
"type": "application/json",
"title": "The classes related to this item",
},
{
"href": f"{BASE_URL}/classification_systems/{classification_system['id']}/style_formats{request.assets_kwargs}",
"rel": "styles_formats",
"type": "application/json",
"title": "The styles formats related to this item",
},
{
"href": f"{BASE_URL}/mappings/{classification_system['id']}{request.assets_kwargs}",
"rel": "mappings",
"type": "application/json",
"title": "The classification system mappings",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page."
},
]
classification_system["links"] = links
return classification_system, 200
@current_app.route("/classification_systems/<system_id_or_identifier>/classes", methods=["GET"])
@oauth2(required=True)
def classification_systems_classes(system_id_or_identifier, **kwargs):
"""Retrieve the classes of a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
system_id, classes_list = data.get_classification_system_classes(system_id_or_identifier)
links = [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Classes of the classification system {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
if not len(classes_list) > 0:
return jsonify(links)
for system_classes in classes_list:
system_classes["links"] = links
system_classes["links"].append(
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes/{system_classes['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "child",
"type": "application/json",
"title": "Classification System Class",
}
)
return jsonify(classes_list), 200
@current_app.route("/classification_systems/<system_id_or_identifier>/classes/<class_id_or_name>", methods=["GET"])
@oauth2(required=True)
@language()
def classification_systems_class(system_id_or_identifier, class_id_or_name, **kwargs):
"""Retrieve class information from a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
:param class_id_or_name: identifier of a class
"""
system_id, class_info = data.get_classification_system_class(system_id_or_identifier, class_id_or_name)
if not len(class_info) > 0:
abort(404, f"Class not found.")
links = [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes/{class_info['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "Link to this document",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to this document",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_systems",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
class_info["links"] = links
return class_info, 200
@current_app.route("/mappings/<system_id_or_identifier>", methods=["GET"])
@oauth2(required=True)
@language()
def get_mappings(system_id_or_identifier, **kwargs):
"""Retrieve available mappings for a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
system_source, system_target = data.get_mappings(system_id_or_identifier)
if not len(system_target) > 0:
abort(404, f"Mappings not found.")
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
for sys in system_target:
links.append(
{
"href": f"{BASE_URL}/mappings/{system_source.id}/{sys.id}{request.assets_kwargs}",
"rel": "child",
"type": "application/json",
"title": "Mapping",
}
)
return jsonify(links)
@current_app.route("/mappings/<system_id_or_identifier_source>/<system_id_or_identifier_target>", methods=["GET"])
@oauth2(required=True)
@language()
def get_mapping(system_id_or_identifier_source, system_id_or_identifier_target, **kwargs):
"""Retrieve mapping.
:param system_id_or_identifier_source: The id or identifier of source classification system
:param system_id_or_identifier_target: The id or identifier of target classification system
"""
system_id_source, system_id_target, mappings = data.get_mapping(system_id_or_identifier_source,
system_id_or_identifier_target)
for mp in mappings:
links = [
{
"href": f"{BASE_URL}/classification_systems/{system_id_source}/classes/{mp['source_class_id']}{request.assets_kwargs}",
"rel": "item",
"type": "application/json",
"title": "Link to source class",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id_target}/classes/{mp['target_class_id']}{request.assets_kwargs}",
"rel": "item",
"type": "application/json",
"title": "Link to target class",
},
]
if mp["degree_of_similarity"] is not None:
mp["degree_of_similarity"] = float(mp["degree_of_similarity"])
mp["links"] = links
return jsonify(mappings)
@current_app.route("/style_formats", methods=["GET"])
@oauth2(required=True)
def get_styles_formats(**kwargs):
"""Retrieve available style formats in service."""
styles_formats = data.get_style_formats()
for st_f in styles_formats:
links = [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
{
"href": f"{BASE_URL}/style_formats/{st_f['id']}{request.assets_kwargs}",
"rel": "items",
"type": "application/json",
"title": f"Link to style format {st_f['id']}"
}
]
st_f["links"] = links
return jsonify(styles_formats)
@current_app.route("/style_formats/<style_format_id_or_name>", methods=["GET"])
@oauth2(required=True)
def get_style_format(style_format_id_or_name, **kwargs):
"""Retrieve information of a style formats.
:param style_format_id_or_name: The id or name of a style format
"""
styles_format = data.get_style_format(style_format_id_or_name)
if not len(styles_format) > 0:
abort(404, f"Style Format not found.")
links = [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_systems",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
{
"href": f"{BASE_URL}/style_formats/{styles_format['id']}{request.assets_kwargs}",
"rel": "style_format",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/style_formats/{request.assets_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
]
styles_format["links"] = links
return styles_format
@current_app.route("/classification_systems/<system_id_or_identifier>/style_formats", methods=["GET"])
@oauth2(required=True)
def get_style_formats_classification_system(system_id_or_identifier, **kwargs):
"""Retrieve available style formats for a classification system.
:param system_id_or_identifier: The id or identifier of a source classification system
"""
system_id, style_formats_id = data.get_system_style_format(system_id_or_identifier)
if not len(style_formats_id) > 0:
abort(404, f"Style Formats not found.")
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/style_formats{request.assets_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Available style formats for {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
for style_id in style_formats_id:
links.append(
{
"href": f"{BASE_URL}/classification_systems/{system_id}/styles/{style_id[0]}{request.assets_kwargs}",
"rel": "style",
"type": "application/json",
"title": "Link to style",
}
)
return jsonify(links)
@current_app.route("/classification_systems/<system_id_or_identifier>/styles/<style_format_id_or_name>",
methods=["GET"])
@oauth2(required=True)
def style_file(system_id_or_identifier, style_format_id_or_name, **kwargs):
"""Retrieve available styles.
:param system_id_or_identifier: The id or identifier of a classification system
:param style_format_id_or_name: The id or name of a style format
"""
file_name, file = data.get_classification_system_style(system_id_or_identifier=system_id_or_identifier,
style_format_id_or_name=style_format_id_or_name)
if not file:
abort(404, f"Style File not found.")
return send_file(file, mimetype='application/octet-stream', as_attachment=True,
attachment_filename=file_name)
@current_app.route("/classification_systems/search/<system_name>/<system_version>", methods=["GET"])
def classification_system_search(system_name, system_version):
"""Return identifier of a classification system.
:param system_name: name of a classification system
:param system_version: version of a classification system
"""
system = data.get_identifier_system(system_name, system_version)
return system, 200
@current_app.route("/style_formats/search/<style_format_name>", methods=["GET"])
def style_format_search(style_format_name):
"""Return identifier of a style format.
:param style_format_name: name of a style format
"""
style_format = data.get_identifier_style_format(style_format_name)
return style_format, 200
@current_app.route('/classification_systems', defaults={'system_id_or_identifier': None}, methods=["POST"])
@current_app.route("/classification_systems/<system_id_or_identifier>", methods=["PUT", "DELETE"])
@oauth2(roles=[['admin', 'editor']])
@language()
def edit_classification_system(system_id_or_identifier, **kwargs):
"""Create or edit a specific classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
if request.method == "POST":
args = request.get_json()
errors = ClassificationSystemMetadataSchema().validate(args)
if errors:
return abort(400, str(errors))
classification_system = data.create_classification_system(**args)
return classification_system, 201
if request.method == "DELETE":
data.delete_classification_system(system_id_or_identifier)
return {'message': f'{system_id_or_identifier} deleted'}, 204
if request.method == "PUT":
args = request.get_json()
errors = ClassificationSystemMetadataSchema().validate(args, partial=True)
if errors:
return abort(400, str(errors))
classification_system = data.update_classification_system(system_id_or_identifier, args)
return classification_system, 200
@current_app.route("/classification_systems/<system_id_or_identifier>/classes", methods=["POST", "DELETE"])
@oauth2(roles=["admin"])
@language()
def create_delete_classes(system_id_or_identifier, **kwargs):
"""Create classes for a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
if request.method == "DELETE":
data.delete_classes(system_id_or_identifier)
return {'message': f'Classes of {system_id_or_identifier} deleted'}, 204
if request.method == "POST":
args = request.get_json()
errors = ClassMetadataForm().validate(args)
if errors:
return abort(400, str(errors))
classes = data.insert_classes(system_id_or_identifier=system_id_or_identifier, classes_files_json=args['classes'])
result = ClassesSchema(exclude=['classification_system_id']).dump(classes, many=True)
return jsonify(result), 201
@current_app.route("/classification_systems/<system_id_or_identifier>/classes/<class_id_or_name>",
methods=["PUT", "DELETE"])
@oauth2(roles=["admin"])
@language()
def edit_class(system_id_or_identifier, class_id_or_name, **kwargs):
"""Delete class of a specific classification system.
:param system_id_or_identifier: The id or identifier of a classification system
:param class_id_or_name: The id or identifier of a class
"""
if request.method == "DELETE":
data.delete_class(system_id_or_identifier, class_id_or_name)
return {'message': f'{class_id_or_name} deleted'}, 204
if request.method == "PUT":
args = request.get_json()
errors = ClassMetadataSchema().validate(args, partial=True)
if errors:
return abort(400, str(errors))
system_class = data.update_class(system_id_or_identifier, class_id_or_name, args)
return system_class, 200
@current_app.route("/mappings/<system_id_or_identifier_source>/<system_id_or_identifier_target>",
methods=["POST", "PUT", "DELETE"])
@oauth2(roles=['admin'])
def edit_mapping(system_id_or_identifier_source, system_id_or_identifier_target, **kwargs):
"""Create or edit mappings in service.
:param system_id_or_identifier_source: The id or identifier of a source classification system
:param system_id_or_identifier_target: The id or identifier of a target classification system
"""
if request.method == "POST":
args = request.get_json()
errors = ClassesMappingMetadataSchema(many=True).validate(args)
if errors:
return abort(400, str(errors))
mappings = data.insert_mappings(system_id_or_identifier_source, system_id_or_identifier_target, args)
return jsonify(mappings), 201
if request.method == "DELETE":
data.delete_mappings(system_id_or_identifier_source, system_id_or_identifier_target)
return {'message': 'Mapping delete!'}, 204
if request.method == "PUT":
args = request.get_json()
errors = ClassesMappingMetadataSchema().validate(args)
if errors:
return abort(400, str(errors))
mappings = data.update_mapping(system_id_or_identifier_source, system_id_or_identifier_target, **args)
return mappings, 200
@current_app.route("/classification_systems/<system_id_or_identifier>/styles",
defaults={'style_format_id_or_name': None}, methods=["POST"])
@current_app.route("/classification_systems/<system_id_or_identifier>/styles/<style_format_id_or_name>",
methods=["PUT", "DELETE"])
@oauth2(roles=['admin'])
def edit_styles(system_id_or_identifier, style_format_id_or_name, **kwargs):
"""Create or edit styles.
:param system_id_or_identifier: The id or identifier of a specific classification system
:param style_format_id_or_name: The id or identifier of a specific style format.
"""
if request.method == "POST":
if 'style_format' not in request.form:
return abort(404, "Invalid parameter.")
style_format = request.form.get('style_format')
if 'style' not in request.files:
return abort(404, "Invalid parameter.")
file = request.files['style']
system_id, format_id = data.insert_file(style_format_id_or_name=style_format,
system_id_or_identifier=system_id_or_identifier,
file=file)
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/styles/{format_id}{request.assets_kwargs}",
"rel": "style",
"type": "application/json",
"title": "style",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}/style_formats{request.assets_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Styles of the classification system {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
return jsonify(links)
if request.method == "PUT":
if 'style' not in request.files:
return abort(500, "Style File not found!")
file = request.files['style']
system_id, style_format_id = data.update_file(style_format_id_or_name=style_format_id_or_name,
system_id_or_identifier=system_id_or_identifier,
file=file)
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/styles/{style_format_id}{request.assets_kwargs}",
"rel": "style",
"type": "application/json",
"title": "style",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}/style_formats{request.assets_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Styles of the classification system {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
return jsonify(links)
if request.method == "DELETE":
data.delete_file(style_format_id_or_name, system_id_or_identifier)
return {'message': 'deleted!'}, 204
@current_app.route("/style_formats", defaults={'style_format_id_or_name': None}, methods=["POST"])
@current_app.route("/style_formats/<style_format_id_or_name>", methods=["PUT", "DELETE"])
@oauth2(roles=['admin'])
def edit_style_formats(style_format_id_or_name, **kwargs):
"""Create or edit styles formats.
:param style_format_id_or_name: The id or name of a specific style format
"""
if request.method == "POST":
args = request.get_json()
errors = StyleFormatsSchema().validate(args)
if errors:
return abort(400, str(errors))
style_format = data.create_style_format(**args)
return style_format, 201
if request.method == "DELETE":
data.delete_style_format(style_format_id_or_name)
return {'message': 'deleted'}, 204
if request.method == "PUT":
args = request.get_json()
errors = StyleFormatsMetadataSchema().validate(args)
if errors:
return abort(400, str(errors))
style_format = data.update_style_format(style_format_id_or_name, **args)
return style_format, 200
|
<filename>lccs_ws/views.py
#
# This file is part of Land Cover Classification System Web Service.
# Copyright (C) 2020-2021 INPE.
#
# Land Cover Classification System Web Service is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""Views of Land Cover Classification System Web Service."""
from bdc_auth_client.decorators import oauth2
from flask import abort, current_app, jsonify, request, send_file
from werkzeug.urls import url_encode
from lccs_ws.forms import (ClassesMappingMetadataSchema, ClassesSchema,
ClassificationSystemMetadataSchema,
ClassMetadataForm, ClassMetadataSchema,
StyleFormatsMetadataSchema, StyleFormatsSchema)
from . import data
from .config import Config
from .utils import language
BASE_URL = Config.LCCS_URL
@current_app.before_request
def before_request():
"""Handle for before request processing."""
request.assets_kwargs = None
if Config.BDC_LCCS_ARGS:
assets_kwargs = {arg: request.args.get(arg) for arg in Config.BDC_LCCS_ARGS.split(",")}
if "access_token" in request.args:
assets_kwargs["access_token"] = request.args.get("access_token")
assets_kwargs = "?" + url_encode(assets_kwargs) if url_encode(assets_kwargs) else ""
request.assets_kwargs = assets_kwargs
if Config.BDC_LCCS_ARGS_I18N:
intern_kwargs = {arg: request.args.get(arg) for arg in Config.BDC_LCCS_ARGS_I18N.split(",")}
if "language" in request.args:
intern_kwargs["language"] = request.args.get("language")
intern_kwargs = "&" + url_encode(intern_kwargs) if url_encode(intern_kwargs) else ""
request.intern_kwargs = intern_kwargs
@current_app.route("/", methods=["GET"])
@oauth2(required=False)
def root(**kwargs):
"""URL Handler for Land User Cover Classification System through REST API."""
links = list()
response = dict()
links += [
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "Link to this document"
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_systems", "type": "application/json",
"title": "Information about Classification Systems",
},
{
"href": f"{BASE_URL}/style_formats{request.assets_kwargs}",
"rel": "style_formats", "type": "application/json",
"title": "Information about Style Formats"
}
]
response["links"] = links
response["application_name"] = "Land Cover Classification System Service"
response["version"] = Config.BDC_LCCS_API_VERSION
return response, 200
@current_app.route("/classification_systems", methods=["GET"])
@oauth2(required=True)
@language()
def get_classification_systems(**kwargs):
"""Retrieve the list of available classification systems in the service."""
classification_systems_list = data.get_classification_systems()
for class_system in classification_systems_list:
links = [
{
"href": f"{BASE_URL}/classification_systems/{class_system['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_system",
"type": "application/json",
"title": "Link to Classification System",
},
{
"href": f"{BASE_URL}/classification_systems/{class_system['id']}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classes",
"type": "application/json",
"title": "Link to Classification System Classes",
},
{
"href": f"{BASE_URL}/classification_systems/{class_system['id']}/style_formats{request.assets_kwargs}",
"rel": "style_formats",
"type": "application/json",
"title": "Link to Available Style Formats",
},
{
"href": f"{BASE_URL}/mappings/{class_system['id']}{request.assets_kwargs}",
"rel": "mappings",
"type": "application/json",
"title": "Link to Classification Mappings",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "Link to this document",
},
]
class_system["links"] = links
return jsonify(classification_systems_list), 200
@current_app.route("/classification_systems/<system_id_or_identifier>", methods=["GET"])
@language()
@oauth2(required=True)
def get_classification_system(system_id_or_identifier, **kwargs):
"""Retrieve information about the classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
classification_system = data.get_classification_system(system_id_or_identifier)
if not classification_system:
abort(404, "Classification System not found.")
links = [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to this document",
},
{
"href": f"{BASE_URL}/classification_systems/{classification_system['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "The classification_system",
},
{
"href": f"{BASE_URL}/classification_systems/{classification_system['id']}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classes",
"type": "application/json",
"title": "The classes related to this item",
},
{
"href": f"{BASE_URL}/classification_systems/{classification_system['id']}/style_formats{request.assets_kwargs}",
"rel": "styles_formats",
"type": "application/json",
"title": "The styles formats related to this item",
},
{
"href": f"{BASE_URL}/mappings/{classification_system['id']}{request.assets_kwargs}",
"rel": "mappings",
"type": "application/json",
"title": "The classification system mappings",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page."
},
]
classification_system["links"] = links
return classification_system, 200
@current_app.route("/classification_systems/<system_id_or_identifier>/classes", methods=["GET"])
@oauth2(required=True)
def classification_systems_classes(system_id_or_identifier, **kwargs):
"""Retrieve the classes of a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
system_id, classes_list = data.get_classification_system_classes(system_id_or_identifier)
links = [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Classes of the classification system {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
if not len(classes_list) > 0:
return jsonify(links)
for system_classes in classes_list:
system_classes["links"] = links
system_classes["links"].append(
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes/{system_classes['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "child",
"type": "application/json",
"title": "Classification System Class",
}
)
return jsonify(classes_list), 200
@current_app.route("/classification_systems/<system_id_or_identifier>/classes/<class_id_or_name>", methods=["GET"])
@oauth2(required=True)
@language()
def classification_systems_class(system_id_or_identifier, class_id_or_name, **kwargs):
"""Retrieve class information from a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
:param class_id_or_name: identifier of a class
"""
system_id, class_info = data.get_classification_system_class(system_id_or_identifier, class_id_or_name)
if not len(class_info) > 0:
abort(404, f"Class not found.")
links = [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes/{class_info['id']}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "self",
"type": "application/json",
"title": "Link to this document",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}/classes{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to this document",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_systems",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
class_info["links"] = links
return class_info, 200
@current_app.route("/mappings/<system_id_or_identifier>", methods=["GET"])
@oauth2(required=True)
@language()
def get_mappings(system_id_or_identifier, **kwargs):
"""Retrieve available mappings for a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
system_source, system_target = data.get_mappings(system_id_or_identifier)
if not len(system_target) > 0:
abort(404, f"Mappings not found.")
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
for sys in system_target:
links.append(
{
"href": f"{BASE_URL}/mappings/{system_source.id}/{sys.id}{request.assets_kwargs}",
"rel": "child",
"type": "application/json",
"title": "Mapping",
}
)
return jsonify(links)
@current_app.route("/mappings/<system_id_or_identifier_source>/<system_id_or_identifier_target>", methods=["GET"])
@oauth2(required=True)
@language()
def get_mapping(system_id_or_identifier_source, system_id_or_identifier_target, **kwargs):
"""Retrieve mapping.
:param system_id_or_identifier_source: The id or identifier of source classification system
:param system_id_or_identifier_target: The id or identifier of target classification system
"""
system_id_source, system_id_target, mappings = data.get_mapping(system_id_or_identifier_source,
system_id_or_identifier_target)
for mp in mappings:
links = [
{
"href": f"{BASE_URL}/classification_systems/{system_id_source}/classes/{mp['source_class_id']}{request.assets_kwargs}",
"rel": "item",
"type": "application/json",
"title": "Link to source class",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id_target}/classes/{mp['target_class_id']}{request.assets_kwargs}",
"rel": "item",
"type": "application/json",
"title": "Link to target class",
},
]
if mp["degree_of_similarity"] is not None:
mp["degree_of_similarity"] = float(mp["degree_of_similarity"])
mp["links"] = links
return jsonify(mappings)
@current_app.route("/style_formats", methods=["GET"])
@oauth2(required=True)
def get_styles_formats(**kwargs):
"""Retrieve available style formats in service."""
styles_formats = data.get_style_formats()
for st_f in styles_formats:
links = [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
{
"href": f"{BASE_URL}/style_formats/{st_f['id']}{request.assets_kwargs}",
"rel": "items",
"type": "application/json",
"title": f"Link to style format {st_f['id']}"
}
]
st_f["links"] = links
return jsonify(styles_formats)
@current_app.route("/style_formats/<style_format_id_or_name>", methods=["GET"])
@oauth2(required=True)
def get_style_format(style_format_id_or_name, **kwargs):
"""Retrieve information of a style formats.
:param style_format_id_or_name: The id or name of a style format
"""
styles_format = data.get_style_format(style_format_id_or_name)
if not len(styles_format) > 0:
abort(404, f"Style Format not found.")
links = [
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "classification_systems",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
{
"href": f"{BASE_URL}/style_formats/{styles_format['id']}{request.assets_kwargs}",
"rel": "style_format",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/style_formats/{request.assets_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
]
styles_format["links"] = links
return styles_format
@current_app.route("/classification_systems/<system_id_or_identifier>/style_formats", methods=["GET"])
@oauth2(required=True)
def get_style_formats_classification_system(system_id_or_identifier, **kwargs):
"""Retrieve available style formats for a classification system.
:param system_id_or_identifier: The id or identifier of a source classification system
"""
system_id, style_formats_id = data.get_system_style_format(system_id_or_identifier)
if not len(style_formats_id) > 0:
abort(404, f"Style Formats not found.")
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/style_formats{request.assets_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Available style formats for {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
for style_id in style_formats_id:
links.append(
{
"href": f"{BASE_URL}/classification_systems/{system_id}/styles/{style_id[0]}{request.assets_kwargs}",
"rel": "style",
"type": "application/json",
"title": "Link to style",
}
)
return jsonify(links)
@current_app.route("/classification_systems/<system_id_or_identifier>/styles/<style_format_id_or_name>",
methods=["GET"])
@oauth2(required=True)
def style_file(system_id_or_identifier, style_format_id_or_name, **kwargs):
"""Retrieve available styles.
:param system_id_or_identifier: The id or identifier of a classification system
:param style_format_id_or_name: The id or name of a style format
"""
file_name, file = data.get_classification_system_style(system_id_or_identifier=system_id_or_identifier,
style_format_id_or_name=style_format_id_or_name)
if not file:
abort(404, f"Style File not found.")
return send_file(file, mimetype='application/octet-stream', as_attachment=True,
attachment_filename=file_name)
@current_app.route("/classification_systems/search/<system_name>/<system_version>", methods=["GET"])
def classification_system_search(system_name, system_version):
"""Return identifier of a classification system.
:param system_name: name of a classification system
:param system_version: version of a classification system
"""
system = data.get_identifier_system(system_name, system_version)
return system, 200
@current_app.route("/style_formats/search/<style_format_name>", methods=["GET"])
def style_format_search(style_format_name):
"""Return identifier of a style format.
:param style_format_name: name of a style format
"""
style_format = data.get_identifier_style_format(style_format_name)
return style_format, 200
@current_app.route('/classification_systems', defaults={'system_id_or_identifier': None}, methods=["POST"])
@current_app.route("/classification_systems/<system_id_or_identifier>", methods=["PUT", "DELETE"])
@oauth2(roles=[['admin', 'editor']])
@language()
def edit_classification_system(system_id_or_identifier, **kwargs):
"""Create or edit a specific classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
if request.method == "POST":
args = request.get_json()
errors = ClassificationSystemMetadataSchema().validate(args)
if errors:
return abort(400, str(errors))
classification_system = data.create_classification_system(**args)
return classification_system, 201
if request.method == "DELETE":
data.delete_classification_system(system_id_or_identifier)
return {'message': f'{system_id_or_identifier} deleted'}, 204
if request.method == "PUT":
args = request.get_json()
errors = ClassificationSystemMetadataSchema().validate(args, partial=True)
if errors:
return abort(400, str(errors))
classification_system = data.update_classification_system(system_id_or_identifier, args)
return classification_system, 200
@current_app.route("/classification_systems/<system_id_or_identifier>/classes", methods=["POST", "DELETE"])
@oauth2(roles=["admin"])
@language()
def create_delete_classes(system_id_or_identifier, **kwargs):
"""Create classes for a classification system.
:param system_id_or_identifier: The id or identifier of a classification system
"""
if request.method == "DELETE":
data.delete_classes(system_id_or_identifier)
return {'message': f'Classes of {system_id_or_identifier} deleted'}, 204
if request.method == "POST":
args = request.get_json()
errors = ClassMetadataForm().validate(args)
if errors:
return abort(400, str(errors))
classes = data.insert_classes(system_id_or_identifier=system_id_or_identifier, classes_files_json=args['classes'])
result = ClassesSchema(exclude=['classification_system_id']).dump(classes, many=True)
return jsonify(result), 201
@current_app.route("/classification_systems/<system_id_or_identifier>/classes/<class_id_or_name>",
methods=["PUT", "DELETE"])
@oauth2(roles=["admin"])
@language()
def edit_class(system_id_or_identifier, class_id_or_name, **kwargs):
"""Delete class of a specific classification system.
:param system_id_or_identifier: The id or identifier of a classification system
:param class_id_or_name: The id or identifier of a class
"""
if request.method == "DELETE":
data.delete_class(system_id_or_identifier, class_id_or_name)
return {'message': f'{class_id_or_name} deleted'}, 204
if request.method == "PUT":
args = request.get_json()
errors = ClassMetadataSchema().validate(args, partial=True)
if errors:
return abort(400, str(errors))
system_class = data.update_class(system_id_or_identifier, class_id_or_name, args)
return system_class, 200
@current_app.route("/mappings/<system_id_or_identifier_source>/<system_id_or_identifier_target>",
methods=["POST", "PUT", "DELETE"])
@oauth2(roles=['admin'])
def edit_mapping(system_id_or_identifier_source, system_id_or_identifier_target, **kwargs):
"""Create or edit mappings in service.
:param system_id_or_identifier_source: The id or identifier of a source classification system
:param system_id_or_identifier_target: The id or identifier of a target classification system
"""
if request.method == "POST":
args = request.get_json()
errors = ClassesMappingMetadataSchema(many=True).validate(args)
if errors:
return abort(400, str(errors))
mappings = data.insert_mappings(system_id_or_identifier_source, system_id_or_identifier_target, args)
return jsonify(mappings), 201
if request.method == "DELETE":
data.delete_mappings(system_id_or_identifier_source, system_id_or_identifier_target)
return {'message': 'Mapping delete!'}, 204
if request.method == "PUT":
args = request.get_json()
errors = ClassesMappingMetadataSchema().validate(args)
if errors:
return abort(400, str(errors))
mappings = data.update_mapping(system_id_or_identifier_source, system_id_or_identifier_target, **args)
return mappings, 200
@current_app.route("/classification_systems/<system_id_or_identifier>/styles",
defaults={'style_format_id_or_name': None}, methods=["POST"])
@current_app.route("/classification_systems/<system_id_or_identifier>/styles/<style_format_id_or_name>",
methods=["PUT", "DELETE"])
@oauth2(roles=['admin'])
def edit_styles(system_id_or_identifier, style_format_id_or_name, **kwargs):
"""Create or edit styles.
:param system_id_or_identifier: The id or identifier of a specific classification system
:param style_format_id_or_name: The id or identifier of a specific style format.
"""
if request.method == "POST":
if 'style_format' not in request.form:
return abort(404, "Invalid parameter.")
style_format = request.form.get('style_format')
if 'style' not in request.files:
return abort(404, "Invalid parameter.")
file = request.files['style']
system_id, format_id = data.insert_file(style_format_id_or_name=style_format,
system_id_or_identifier=system_id_or_identifier,
file=file)
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/styles/{format_id}{request.assets_kwargs}",
"rel": "style",
"type": "application/json",
"title": "style",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}/style_formats{request.assets_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Styles of the classification system {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
return jsonify(links)
if request.method == "PUT":
if 'style' not in request.files:
return abort(500, "Style File not found!")
file = request.files['style']
system_id, style_format_id = data.update_file(style_format_id_or_name=style_format_id_or_name,
system_id_or_identifier=system_id_or_identifier,
file=file)
links = list()
links += [
{
"href": f"{BASE_URL}/classification_systems/{system_id}/styles/{style_format_id}{request.assets_kwargs}",
"rel": "style",
"type": "application/json",
"title": "style",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}/style_formats{request.assets_kwargs}",
"rel": "self",
"type": "application/json",
"title": f"Styles of the classification system {system_id}{request.assets_kwargs}",
},
{
"href": f"{BASE_URL}/classification_systems/{system_id}{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification system",
},
{
"href": f"{BASE_URL}/classification_systems{request.assets_kwargs}{request.intern_kwargs}",
"rel": "parent",
"type": "application/json",
"title": "Link to classification systems",
},
{
"href": f"{BASE_URL}/{request.assets_kwargs}{request.intern_kwargs}",
"rel": "root",
"type": "application/json",
"title": "API landing page",
},
]
return jsonify(links)
if request.method == "DELETE":
data.delete_file(style_format_id_or_name, system_id_or_identifier)
return {'message': 'deleted!'}, 204
@current_app.route("/style_formats", defaults={'style_format_id_or_name': None}, methods=["POST"])
@current_app.route("/style_formats/<style_format_id_or_name>", methods=["PUT", "DELETE"])
@oauth2(roles=['admin'])
def edit_style_formats(style_format_id_or_name, **kwargs):
"""Create or edit styles formats.
:param style_format_id_or_name: The id or name of a specific style format
"""
if request.method == "POST":
args = request.get_json()
errors = StyleFormatsSchema().validate(args)
if errors:
return abort(400, str(errors))
style_format = data.create_style_format(**args)
return style_format, 201
if request.method == "DELETE":
data.delete_style_format(style_format_id_or_name)
return {'message': 'deleted'}, 204
if request.method == "PUT":
args = request.get_json()
errors = StyleFormatsMetadataSchema().validate(args)
if errors:
return abort(400, str(errors))
style_format = data.update_style_format(style_format_id_or_name, **args)
return style_format, 200
|
en
| 0.549465
|
# # This file is part of Land Cover Classification System Web Service. # Copyright (C) 2020-2021 INPE. # # Land Cover Classification System Web Service is free software; you can redistribute it and/or modify it # under the terms of the MIT License; see LICENSE file for more details. # Views of Land Cover Classification System Web Service. Handle for before request processing. URL Handler for Land User Cover Classification System through REST API. Retrieve the list of available classification systems in the service. Retrieve information about the classification system. :param system_id_or_identifier: The id or identifier of a classification system Retrieve the classes of a classification system. :param system_id_or_identifier: The id or identifier of a classification system Retrieve class information from a classification system. :param system_id_or_identifier: The id or identifier of a classification system :param class_id_or_name: identifier of a class Retrieve available mappings for a classification system. :param system_id_or_identifier: The id or identifier of a classification system Retrieve mapping. :param system_id_or_identifier_source: The id or identifier of source classification system :param system_id_or_identifier_target: The id or identifier of target classification system Retrieve available style formats in service. Retrieve information of a style formats. :param style_format_id_or_name: The id or name of a style format Retrieve available style formats for a classification system. :param system_id_or_identifier: The id or identifier of a source classification system Retrieve available styles. :param system_id_or_identifier: The id or identifier of a classification system :param style_format_id_or_name: The id or name of a style format Return identifier of a classification system. :param system_name: name of a classification system :param system_version: version of a classification system Return identifier of a style format. :param style_format_name: name of a style format Create or edit a specific classification system. :param system_id_or_identifier: The id or identifier of a classification system Create classes for a classification system. :param system_id_or_identifier: The id or identifier of a classification system Delete class of a specific classification system. :param system_id_or_identifier: The id or identifier of a classification system :param class_id_or_name: The id or identifier of a class Create or edit mappings in service. :param system_id_or_identifier_source: The id or identifier of a source classification system :param system_id_or_identifier_target: The id or identifier of a target classification system Create or edit styles. :param system_id_or_identifier: The id or identifier of a specific classification system :param style_format_id_or_name: The id or identifier of a specific style format. Create or edit styles formats. :param style_format_id_or_name: The id or name of a specific style format
| 2.236409
| 2
|
multirun/deps.bzl
|
shiwano/bazel-tools
| 118
|
6625817
|
<reponame>shiwano/bazel-tools
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
load("@bazel_tools//tools/build_defs/repo:utils.bzl", "maybe")
def multirun_dependencies():
maybe(
http_archive,
name = "bazel_skylib",
urls = [
"https://mirror.bazel.build/github.com/bazelbuild/bazel-skylib/releases/download/1.0.2/bazel-skylib-1.0.2.tar.gz",
"https://github.com/bazelbuild/bazel-skylib/releases/download/1.0.2/bazel-skylib-1.0.2.tar.gz",
],
sha256 = "97e70364e9249702246c0e9444bccdc4b847bed1eb03c5a3ece4f83dfe6abc44",
)
|
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
load("@bazel_tools//tools/build_defs/repo:utils.bzl", "maybe")
def multirun_dependencies():
maybe(
http_archive,
name = "bazel_skylib",
urls = [
"https://mirror.bazel.build/github.com/bazelbuild/bazel-skylib/releases/download/1.0.2/bazel-skylib-1.0.2.tar.gz",
"https://github.com/bazelbuild/bazel-skylib/releases/download/1.0.2/bazel-skylib-1.0.2.tar.gz",
],
sha256 = "97e70364e9249702246c0e9444bccdc4b847bed1eb03c5a3ece4f83dfe6abc44",
)
|
none
| 1
| 1.486008
| 1
|
|
plugins/extract/_base.py
|
aaman123/faceswap
| 2
|
6625818
|
<gh_stars>1-10
#!/usr/bin/env python3
""" Base class for Faceswap :mod:`~plugins.extract.detect`, :mod:`~plugins.extract.align` and
:mod:`~plugins.extract.mask` Plugins
"""
import logging
import os
import sys
from tensorflow.python import errors_impl as tf_errors # pylint:disable=no-name-in-module
from lib.multithreading import MultiThread
from lib.queue_manager import queue_manager
from lib.utils import GetModel, FaceswapError
from ._config import Config
from .pipeline import ExtractMedia
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
# TODO CPU mode
# TODO Run with warnings mode
def _get_config(plugin_name, configfile=None):
""" Return the configuration for the requested model
Parameters
----------
plugin_name: str
The module name of the child plugin.
configfile: str, optional
Path to a :file:`./config/<plugin_type>.ini` file for this plugin. Default: use system
configuration.
Returns
-------
config_dict, dict
A dictionary of configuration items from the configuration file
"""
return Config(plugin_name, configfile=configfile).config_dict
class Extractor():
""" Extractor Plugin Object
All ``_base`` classes for Aligners, Detectors and Maskers inherit from this class.
This class sets up a pipeline for working with ML plugins.
Plugins are split into 3 threads, to utilize Numpy and CV2s parallel processing, as well as
allow the predict function of the model to sit in a dedicated thread.
A plugin is expected to have 3 core functions, each in their own thread:
- :func:`process_input()` - Prepare the data for feeding into a model
- :func:`predict` - Feed the data through the model
- :func:`process_output()` - Perform any data post-processing
Parameters
----------
git_model_id: int
The second digit in the github tag that identifies this model. See
https://github.com/deepfakes-models/faceswap-models for more information
model_filename: str
The name of the model file to be loaded
exclude_gpus: list, optional
A list of indices correlating to connected GPUs that Tensorflow should not use. Pass
``None`` to not exclude any GPUs. Default: ``None``
configfile: str, optional
Path to a custom configuration ``ini`` file. Default: Use system configfile
instance: int, optional
If this plugin is being executed multiple times (i.e. multiple pipelines have been
launched), the instance of the plugin must be passed in for naming convention reasons.
Default: 0
The following attributes should be set in the plugin's :func:`__init__` method after
initializing the parent.
Attributes
----------
name: str
Name of this plugin. Used for display purposes.
input_size: int
The input size to the model in pixels across one edge. The input size should always be
square.
color_format: str
Color format for model. Must be ``'BGR'``, ``'RGB'`` or ``'GRAY'``. Defaults to ``'BGR'``
if not explicitly set.
vram: int
Approximate VRAM used by the model at :attr:`input_size`. Used to calculate the
:attr:`batchsize`. Be conservative to avoid OOM.
vram_warnings: int
Approximate VRAM used by the model at :attr:`input_size` that will still run, but generates
warnings. Used to calculate the :attr:`batchsize`. Be conservative to avoid OOM.
vram_per_batch: int
Approximate additional VRAM used by the model for each additional batch. Used to calculate
the :attr:`batchsize`. Be conservative to avoid OOM.
See Also
--------
plugins.extract.detect._base : Detector parent class for extraction plugins.
plugins.extract.align._base : Aligner parent class for extraction plugins.
plugins.extract.mask._base : Masker parent class for extraction plugins.
plugins.extract.pipeline : The extract pipeline that configures and calls all plugins
"""
def __init__(self, git_model_id=None, model_filename=None, exclude_gpus=None, configfile=None,
instance=0):
logger.debug("Initializing %s: (git_model_id: %s, model_filename: %s, exclude_gpus: %s, "
"configfile: %s, instance: %s, )", self.__class__.__name__, git_model_id,
model_filename, exclude_gpus, configfile, instance)
self._instance = instance
self._exclude_gpus = exclude_gpus
self.config = _get_config(".".join(self.__module__.split(".")[-2:]), configfile=configfile)
""" dict: Config for this plugin, loaded from ``extract.ini`` configfile """
self.model_path = self._get_model(git_model_id, model_filename)
""" str or list: Path to the model file(s) (if required). Multiple model files should
be a list of strings """
# << SET THE FOLLOWING IN PLUGINS __init__ IF DIFFERENT FROM DEFAULT >> #
self.name = None
self.input_size = None
self.color_format = "BGR"
self.vram = None
self.vram_warnings = None # Will run at this with warnings
self.vram_per_batch = None
# << THE FOLLOWING ARE SET IN self.initialize METHOD >> #
self.queue_size = 1
""" int: Queue size for all internal queues. Set in :func:`initialize()` """
self.model = None
"""varies: The model for this plugin.
Set in the plugin's :func:`init_model()` method """
# For detectors that support batching, this should be set to the calculated batch size
# that the amount of available VRAM will support.
self.batchsize = 1
""" int: Batchsize for feeding this model. The number of images the model should
feed through at once. """
self._queues = dict()
""" dict: in + out queues and internal queues for this plugin, """
self._threads = []
""" list: Internal threads for this plugin """
self._extract_media = dict()
""" dict: The :class:`plugins.extract.pipeline.ExtractMedia` objects currently being
processed. Stored at input for pairing back up on output of extractor process """
# << THE FOLLOWING PROTECTED ATTRIBUTES ARE SET IN PLUGIN TYPE _base.py >>> #
self._plugin_type = None
""" str: Plugin type. ``detect`` or ``align``
set in ``<plugin_type>._base`` """
logger.debug("Initialized _base %s", self.__class__.__name__)
# <<< OVERIDABLE METHODS >>> #
def init_model(self):
""" **Override method**
Override this method to execute the specific model initialization method """
raise NotImplementedError
def process_input(self, batch):
""" **Override method**
Override this method for specific extractor pre-processing of image
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
Notes
-----
When preparing an input to the model a key ``feed`` must be added
to the :attr:`batch` ``dict`` which contains this input.
"""
raise NotImplementedError
def predict(self, batch):
""" **Override method**
Override this method for specific extractor model prediction function
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
Notes
-----
Input for :func:`predict` should have been set in :func:`process_input` with the addition
of a ``feed`` key to the :attr:`batch` ``dict``.
Output from the model should add the key ``prediction`` to the :attr:`batch` ``dict``.
For Detect:
the expected output for the ``prediction`` key of the :attr:`batch` dict should be a
``list`` of :attr:`batchsize` of detected face points. These points should be either
a ``list``, ``tuple`` or ``numpy.ndarray`` with the first 4 items being the `left`,
`top`, `right`, `bottom` points, in that order
"""
raise NotImplementedError
def process_output(self, batch):
""" **Override method**
Override this method for specific extractor model post predict function
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
Notes
-----
For Align:
The key ``landmarks`` must be returned in the :attr:`batch` ``dict`` from this method.
This should be a ``list`` or ``numpy.ndarray`` of :attr:`batchsize` containing a
``list``, ``tuple`` or ``numpy.ndarray`` of `(x, y)` coordinates of the 68 point
landmarks as calculated from the :attr:`model`.
"""
raise NotImplementedError
def _predict(self, batch):
""" **Override method** (at `<plugin_type>` level)
This method should be overridden at the `<plugin_type>` level (IE.
``plugins.extract.detect._base`` or ``plugins.extract.align._base``) and should not
be overridden within plugins themselves.
It acts as a wrapper for the plugin's ``self.predict`` method and handles any
predict processing that is consistent for all plugins within the `plugin_type`
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
"""
raise NotImplementedError
def finalize(self, batch):
""" **Override method** (at `<plugin_type>` level)
This method should be overridden at the `<plugin_type>` level (IE.
:mod:`plugins.extract.detect._base`, :mod:`plugins.extract.align._base` or
:mod:`plugins.extract.mask._base`) and should not be overridden within plugins themselves.
Handles consistent finalization for all plugins that exist within that plugin type. Its
input is always the output from :func:`process_output()`
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
"""
def get_batch(self, queue):
""" **Override method** (at `<plugin_type>` level)
This method should be overridden at the `<plugin_type>` level (IE.
:mod:`plugins.extract.detect._base`, :mod:`plugins.extract.align._base` or
:mod:`plugins.extract.mask._base`) and should not be overridden within plugins themselves.
Get :class:`~plugins.extract.pipeline.ExtractMedia` items from the queue in batches of
:attr:`batchsize`
Parameters
----------
queue : queue.Queue()
The ``queue`` that the batch will be fed from. This will be the input to the plugin.
"""
raise NotImplementedError
# <<< THREADING METHODS >>> #
def start(self):
""" Start all threads
Exposed for :mod:`~plugins.extract.pipeline` to start plugin's threads
"""
for thread in self._threads:
thread.start()
def join(self):
""" Join all threads
Exposed for :mod:`~plugins.extract.pipeline` to join plugin's threads
"""
for thread in self._threads:
thread.join()
del thread
def check_and_raise_error(self):
""" Check all threads for errors
Exposed for :mod:`~plugins.extract.pipeline` to check plugin's threads for errors
"""
for thread in self._threads:
err = thread.check_and_raise_error()
if err is not None:
logger.debug("thread_error_detected")
return True
return False
# <<< PROTECTED ACCESS METHODS >>> #
# <<< INIT METHODS >>> #
def _get_model(self, git_model_id, model_filename):
""" Check if model is available, if not, download and unzip it """
if model_filename is None:
logger.debug("No model_filename specified. Returning None")
return None
if git_model_id is None:
logger.debug("No git_model_id specified. Returning None")
return None
plugin_path = os.path.join(*self.__module__.split(".")[:-1])
if os.path.basename(plugin_path) in ("detect", "align", "mask", "recognition"):
base_path = os.path.dirname(os.path.realpath(sys.argv[0]))
cache_path = os.path.join(base_path, plugin_path, ".cache")
else:
cache_path = os.path.join(os.path.dirname(__file__), ".cache")
model = GetModel(model_filename, cache_path, git_model_id)
return model.model_path
# <<< PLUGIN INITIALIZATION >>> #
def initialize(self, *args, **kwargs):
""" Initialize the extractor plugin
Should be called from :mod:`~plugins.extract.pipeline`
"""
logger.debug("initialize %s: (args: %s, kwargs: %s)",
self.__class__.__name__, args, kwargs)
logger.info("Initializing %s (%s)...", self.name, self._plugin_type.title())
self.queue_size = 1
name = self.name.replace(" ", "_").lower()
self._add_queues(kwargs["in_queue"],
kwargs["out_queue"],
["predict_{}".format(name), "post_{}".format(name)])
self._compile_threads()
try:
self.init_model()
except tf_errors.UnknownError as err:
if "failed to get convolution algorithm" in str(err).lower():
msg = ("Tensorflow raised an unknown error. This is most likely caused by a "
"failure to launch cuDNN which can occur for some GPU/Tensorflow "
"combinations. You should enable `allow_growth` to attempt to resolve this "
"issue:"
"\nGUI: Go to Settings > Extract Plugins > Global and enable the "
"`allow_growth` option."
"\nCLI: Go to `faceswap/config/extract.ini` and change the `allow_growth "
"option to `True`.")
raise FaceswapError(msg) from err
raise err
logger.info("Initialized %s (%s) with batchsize of %s",
self.name, self._plugin_type.title(), self.batchsize)
def _add_queues(self, in_queue, out_queue, queues):
""" Add the queues
in_queue and out_queue should be previously created queue manager queues.
queues should be a list of queue names """
self._queues["in"] = in_queue
self._queues["out"] = out_queue
for q_name in queues:
self._queues[q_name] = queue_manager.get_queue(
name="{}{}_{}".format(self._plugin_type, self._instance, q_name),
maxsize=self.queue_size)
# <<< THREAD METHODS >>> #
def _compile_threads(self):
""" Compile the threads into self._threads list """
logger.debug("Compiling %s threads", self._plugin_type)
name = self.name.replace(" ", "_").lower()
base_name = "{}_{}".format(self._plugin_type, name)
self._add_thread("{}_input".format(base_name),
self.process_input,
self._queues["in"],
self._queues["predict_{}".format(name)])
self._add_thread("{}_predict".format(base_name),
self._predict,
self._queues["predict_{}".format(name)],
self._queues["post_{}".format(name)])
self._add_thread("{}_output".format(base_name),
self.process_output,
self._queues["post_{}".format(name)],
self._queues["out"])
logger.debug("Compiled %s threads: %s", self._plugin_type, self._threads)
def _add_thread(self, name, function, in_queue, out_queue):
""" Add a MultiThread thread to self._threads """
logger.debug("Adding thread: (name: %s, function: %s, in_queue: %s, out_queue: %s)",
name, function, in_queue, out_queue)
self._threads.append(MultiThread(target=self._thread_process,
name=name,
function=function,
in_queue=in_queue,
out_queue=out_queue))
logger.debug("Added thread: %s", name)
def _thread_process(self, function, in_queue, out_queue):
""" Perform a plugin function in a thread """
func_name = function.__name__
logger.debug("threading: (function: '%s')", func_name)
while True:
if func_name == "process_input":
# Process input items to batches
exhausted, batch = self.get_batch(in_queue)
if exhausted:
if batch:
# Put the final batch
batch = function(batch)
out_queue.put(batch)
break
else:
batch = self._get_item(in_queue)
if batch == "EOF":
break
try:
batch = function(batch)
except tf_errors.UnknownError as err:
if "failed to get convolution algorithm" in str(err).lower():
msg = ("Tensorflow raised an unknown error. This is most likely caused by a "
"failure to launch cuDNN which can occur for some GPU/Tensorflow "
"combinations. You should enable `allow_growth` to attempt to resolve "
"this issue:"
"\nGUI: Go to Settings > Extract Plugins > Global and enable the "
"`allow_growth` option."
"\nCLI: Go to `faceswap/config/extract.ini` and change the "
"`allow_growth option to `True`.")
raise FaceswapError(msg) from err
raise err
if func_name == "process_output":
# Process output items to individual items from batch
for item in self.finalize(batch):
out_queue.put(item)
else:
out_queue.put(batch)
logger.debug("Putting EOF")
out_queue.put("EOF")
# <<< QUEUE METHODS >>> #
def _get_item(self, queue):
""" Yield one item from a queue """
item = queue.get()
if isinstance(item, ExtractMedia):
logger.trace("filename: '%s', image shape: %s, detected_faces: %s, queue: %s, "
"item: %s",
item.filename, item.image_shape, item.detected_faces, queue, item)
self._extract_media[item.filename] = item
else:
logger.trace("item: %s, queue: %s", item, queue)
return item
@staticmethod
def _dict_lists_to_list_dicts(dictionary):
""" Convert a dictionary of lists to a list of dictionaries """
return [dict(zip(dictionary, val)) for val in zip(*dictionary.values())]
|
#!/usr/bin/env python3
""" Base class for Faceswap :mod:`~plugins.extract.detect`, :mod:`~plugins.extract.align` and
:mod:`~plugins.extract.mask` Plugins
"""
import logging
import os
import sys
from tensorflow.python import errors_impl as tf_errors # pylint:disable=no-name-in-module
from lib.multithreading import MultiThread
from lib.queue_manager import queue_manager
from lib.utils import GetModel, FaceswapError
from ._config import Config
from .pipeline import ExtractMedia
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
# TODO CPU mode
# TODO Run with warnings mode
def _get_config(plugin_name, configfile=None):
""" Return the configuration for the requested model
Parameters
----------
plugin_name: str
The module name of the child plugin.
configfile: str, optional
Path to a :file:`./config/<plugin_type>.ini` file for this plugin. Default: use system
configuration.
Returns
-------
config_dict, dict
A dictionary of configuration items from the configuration file
"""
return Config(plugin_name, configfile=configfile).config_dict
class Extractor():
""" Extractor Plugin Object
All ``_base`` classes for Aligners, Detectors and Maskers inherit from this class.
This class sets up a pipeline for working with ML plugins.
Plugins are split into 3 threads, to utilize Numpy and CV2s parallel processing, as well as
allow the predict function of the model to sit in a dedicated thread.
A plugin is expected to have 3 core functions, each in their own thread:
- :func:`process_input()` - Prepare the data for feeding into a model
- :func:`predict` - Feed the data through the model
- :func:`process_output()` - Perform any data post-processing
Parameters
----------
git_model_id: int
The second digit in the github tag that identifies this model. See
https://github.com/deepfakes-models/faceswap-models for more information
model_filename: str
The name of the model file to be loaded
exclude_gpus: list, optional
A list of indices correlating to connected GPUs that Tensorflow should not use. Pass
``None`` to not exclude any GPUs. Default: ``None``
configfile: str, optional
Path to a custom configuration ``ini`` file. Default: Use system configfile
instance: int, optional
If this plugin is being executed multiple times (i.e. multiple pipelines have been
launched), the instance of the plugin must be passed in for naming convention reasons.
Default: 0
The following attributes should be set in the plugin's :func:`__init__` method after
initializing the parent.
Attributes
----------
name: str
Name of this plugin. Used for display purposes.
input_size: int
The input size to the model in pixels across one edge. The input size should always be
square.
color_format: str
Color format for model. Must be ``'BGR'``, ``'RGB'`` or ``'GRAY'``. Defaults to ``'BGR'``
if not explicitly set.
vram: int
Approximate VRAM used by the model at :attr:`input_size`. Used to calculate the
:attr:`batchsize`. Be conservative to avoid OOM.
vram_warnings: int
Approximate VRAM used by the model at :attr:`input_size` that will still run, but generates
warnings. Used to calculate the :attr:`batchsize`. Be conservative to avoid OOM.
vram_per_batch: int
Approximate additional VRAM used by the model for each additional batch. Used to calculate
the :attr:`batchsize`. Be conservative to avoid OOM.
See Also
--------
plugins.extract.detect._base : Detector parent class for extraction plugins.
plugins.extract.align._base : Aligner parent class for extraction plugins.
plugins.extract.mask._base : Masker parent class for extraction plugins.
plugins.extract.pipeline : The extract pipeline that configures and calls all plugins
"""
def __init__(self, git_model_id=None, model_filename=None, exclude_gpus=None, configfile=None,
instance=0):
logger.debug("Initializing %s: (git_model_id: %s, model_filename: %s, exclude_gpus: %s, "
"configfile: %s, instance: %s, )", self.__class__.__name__, git_model_id,
model_filename, exclude_gpus, configfile, instance)
self._instance = instance
self._exclude_gpus = exclude_gpus
self.config = _get_config(".".join(self.__module__.split(".")[-2:]), configfile=configfile)
""" dict: Config for this plugin, loaded from ``extract.ini`` configfile """
self.model_path = self._get_model(git_model_id, model_filename)
""" str or list: Path to the model file(s) (if required). Multiple model files should
be a list of strings """
# << SET THE FOLLOWING IN PLUGINS __init__ IF DIFFERENT FROM DEFAULT >> #
self.name = None
self.input_size = None
self.color_format = "BGR"
self.vram = None
self.vram_warnings = None # Will run at this with warnings
self.vram_per_batch = None
# << THE FOLLOWING ARE SET IN self.initialize METHOD >> #
self.queue_size = 1
""" int: Queue size for all internal queues. Set in :func:`initialize()` """
self.model = None
"""varies: The model for this plugin.
Set in the plugin's :func:`init_model()` method """
# For detectors that support batching, this should be set to the calculated batch size
# that the amount of available VRAM will support.
self.batchsize = 1
""" int: Batchsize for feeding this model. The number of images the model should
feed through at once. """
self._queues = dict()
""" dict: in + out queues and internal queues for this plugin, """
self._threads = []
""" list: Internal threads for this plugin """
self._extract_media = dict()
""" dict: The :class:`plugins.extract.pipeline.ExtractMedia` objects currently being
processed. Stored at input for pairing back up on output of extractor process """
# << THE FOLLOWING PROTECTED ATTRIBUTES ARE SET IN PLUGIN TYPE _base.py >>> #
self._plugin_type = None
""" str: Plugin type. ``detect`` or ``align``
set in ``<plugin_type>._base`` """
logger.debug("Initialized _base %s", self.__class__.__name__)
# <<< OVERIDABLE METHODS >>> #
def init_model(self):
""" **Override method**
Override this method to execute the specific model initialization method """
raise NotImplementedError
def process_input(self, batch):
""" **Override method**
Override this method for specific extractor pre-processing of image
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
Notes
-----
When preparing an input to the model a key ``feed`` must be added
to the :attr:`batch` ``dict`` which contains this input.
"""
raise NotImplementedError
def predict(self, batch):
""" **Override method**
Override this method for specific extractor model prediction function
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
Notes
-----
Input for :func:`predict` should have been set in :func:`process_input` with the addition
of a ``feed`` key to the :attr:`batch` ``dict``.
Output from the model should add the key ``prediction`` to the :attr:`batch` ``dict``.
For Detect:
the expected output for the ``prediction`` key of the :attr:`batch` dict should be a
``list`` of :attr:`batchsize` of detected face points. These points should be either
a ``list``, ``tuple`` or ``numpy.ndarray`` with the first 4 items being the `left`,
`top`, `right`, `bottom` points, in that order
"""
raise NotImplementedError
def process_output(self, batch):
""" **Override method**
Override this method for specific extractor model post predict function
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
Notes
-----
For Align:
The key ``landmarks`` must be returned in the :attr:`batch` ``dict`` from this method.
This should be a ``list`` or ``numpy.ndarray`` of :attr:`batchsize` containing a
``list``, ``tuple`` or ``numpy.ndarray`` of `(x, y)` coordinates of the 68 point
landmarks as calculated from the :attr:`model`.
"""
raise NotImplementedError
def _predict(self, batch):
""" **Override method** (at `<plugin_type>` level)
This method should be overridden at the `<plugin_type>` level (IE.
``plugins.extract.detect._base`` or ``plugins.extract.align._base``) and should not
be overridden within plugins themselves.
It acts as a wrapper for the plugin's ``self.predict`` method and handles any
predict processing that is consistent for all plugins within the `plugin_type`
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
"""
raise NotImplementedError
def finalize(self, batch):
""" **Override method** (at `<plugin_type>` level)
This method should be overridden at the `<plugin_type>` level (IE.
:mod:`plugins.extract.detect._base`, :mod:`plugins.extract.align._base` or
:mod:`plugins.extract.mask._base`) and should not be overridden within plugins themselves.
Handles consistent finalization for all plugins that exist within that plugin type. Its
input is always the output from :func:`process_output()`
Parameters
----------
batch : dict
Contains the batch that is currently being passed through the plugin process
"""
def get_batch(self, queue):
""" **Override method** (at `<plugin_type>` level)
This method should be overridden at the `<plugin_type>` level (IE.
:mod:`plugins.extract.detect._base`, :mod:`plugins.extract.align._base` or
:mod:`plugins.extract.mask._base`) and should not be overridden within plugins themselves.
Get :class:`~plugins.extract.pipeline.ExtractMedia` items from the queue in batches of
:attr:`batchsize`
Parameters
----------
queue : queue.Queue()
The ``queue`` that the batch will be fed from. This will be the input to the plugin.
"""
raise NotImplementedError
# <<< THREADING METHODS >>> #
def start(self):
""" Start all threads
Exposed for :mod:`~plugins.extract.pipeline` to start plugin's threads
"""
for thread in self._threads:
thread.start()
def join(self):
""" Join all threads
Exposed for :mod:`~plugins.extract.pipeline` to join plugin's threads
"""
for thread in self._threads:
thread.join()
del thread
def check_and_raise_error(self):
""" Check all threads for errors
Exposed for :mod:`~plugins.extract.pipeline` to check plugin's threads for errors
"""
for thread in self._threads:
err = thread.check_and_raise_error()
if err is not None:
logger.debug("thread_error_detected")
return True
return False
# <<< PROTECTED ACCESS METHODS >>> #
# <<< INIT METHODS >>> #
def _get_model(self, git_model_id, model_filename):
""" Check if model is available, if not, download and unzip it """
if model_filename is None:
logger.debug("No model_filename specified. Returning None")
return None
if git_model_id is None:
logger.debug("No git_model_id specified. Returning None")
return None
plugin_path = os.path.join(*self.__module__.split(".")[:-1])
if os.path.basename(plugin_path) in ("detect", "align", "mask", "recognition"):
base_path = os.path.dirname(os.path.realpath(sys.argv[0]))
cache_path = os.path.join(base_path, plugin_path, ".cache")
else:
cache_path = os.path.join(os.path.dirname(__file__), ".cache")
model = GetModel(model_filename, cache_path, git_model_id)
return model.model_path
# <<< PLUGIN INITIALIZATION >>> #
def initialize(self, *args, **kwargs):
""" Initialize the extractor plugin
Should be called from :mod:`~plugins.extract.pipeline`
"""
logger.debug("initialize %s: (args: %s, kwargs: %s)",
self.__class__.__name__, args, kwargs)
logger.info("Initializing %s (%s)...", self.name, self._plugin_type.title())
self.queue_size = 1
name = self.name.replace(" ", "_").lower()
self._add_queues(kwargs["in_queue"],
kwargs["out_queue"],
["predict_{}".format(name), "post_{}".format(name)])
self._compile_threads()
try:
self.init_model()
except tf_errors.UnknownError as err:
if "failed to get convolution algorithm" in str(err).lower():
msg = ("Tensorflow raised an unknown error. This is most likely caused by a "
"failure to launch cuDNN which can occur for some GPU/Tensorflow "
"combinations. You should enable `allow_growth` to attempt to resolve this "
"issue:"
"\nGUI: Go to Settings > Extract Plugins > Global and enable the "
"`allow_growth` option."
"\nCLI: Go to `faceswap/config/extract.ini` and change the `allow_growth "
"option to `True`.")
raise FaceswapError(msg) from err
raise err
logger.info("Initialized %s (%s) with batchsize of %s",
self.name, self._plugin_type.title(), self.batchsize)
def _add_queues(self, in_queue, out_queue, queues):
""" Add the queues
in_queue and out_queue should be previously created queue manager queues.
queues should be a list of queue names """
self._queues["in"] = in_queue
self._queues["out"] = out_queue
for q_name in queues:
self._queues[q_name] = queue_manager.get_queue(
name="{}{}_{}".format(self._plugin_type, self._instance, q_name),
maxsize=self.queue_size)
# <<< THREAD METHODS >>> #
def _compile_threads(self):
""" Compile the threads into self._threads list """
logger.debug("Compiling %s threads", self._plugin_type)
name = self.name.replace(" ", "_").lower()
base_name = "{}_{}".format(self._plugin_type, name)
self._add_thread("{}_input".format(base_name),
self.process_input,
self._queues["in"],
self._queues["predict_{}".format(name)])
self._add_thread("{}_predict".format(base_name),
self._predict,
self._queues["predict_{}".format(name)],
self._queues["post_{}".format(name)])
self._add_thread("{}_output".format(base_name),
self.process_output,
self._queues["post_{}".format(name)],
self._queues["out"])
logger.debug("Compiled %s threads: %s", self._plugin_type, self._threads)
def _add_thread(self, name, function, in_queue, out_queue):
""" Add a MultiThread thread to self._threads """
logger.debug("Adding thread: (name: %s, function: %s, in_queue: %s, out_queue: %s)",
name, function, in_queue, out_queue)
self._threads.append(MultiThread(target=self._thread_process,
name=name,
function=function,
in_queue=in_queue,
out_queue=out_queue))
logger.debug("Added thread: %s", name)
def _thread_process(self, function, in_queue, out_queue):
""" Perform a plugin function in a thread """
func_name = function.__name__
logger.debug("threading: (function: '%s')", func_name)
while True:
if func_name == "process_input":
# Process input items to batches
exhausted, batch = self.get_batch(in_queue)
if exhausted:
if batch:
# Put the final batch
batch = function(batch)
out_queue.put(batch)
break
else:
batch = self._get_item(in_queue)
if batch == "EOF":
break
try:
batch = function(batch)
except tf_errors.UnknownError as err:
if "failed to get convolution algorithm" in str(err).lower():
msg = ("Tensorflow raised an unknown error. This is most likely caused by a "
"failure to launch cuDNN which can occur for some GPU/Tensorflow "
"combinations. You should enable `allow_growth` to attempt to resolve "
"this issue:"
"\nGUI: Go to Settings > Extract Plugins > Global and enable the "
"`allow_growth` option."
"\nCLI: Go to `faceswap/config/extract.ini` and change the "
"`allow_growth option to `True`.")
raise FaceswapError(msg) from err
raise err
if func_name == "process_output":
# Process output items to individual items from batch
for item in self.finalize(batch):
out_queue.put(item)
else:
out_queue.put(batch)
logger.debug("Putting EOF")
out_queue.put("EOF")
# <<< QUEUE METHODS >>> #
def _get_item(self, queue):
""" Yield one item from a queue """
item = queue.get()
if isinstance(item, ExtractMedia):
logger.trace("filename: '%s', image shape: %s, detected_faces: %s, queue: %s, "
"item: %s",
item.filename, item.image_shape, item.detected_faces, queue, item)
self._extract_media[item.filename] = item
else:
logger.trace("item: %s, queue: %s", item, queue)
return item
@staticmethod
def _dict_lists_to_list_dicts(dictionary):
""" Convert a dictionary of lists to a list of dictionaries """
return [dict(zip(dictionary, val)) for val in zip(*dictionary.values())]
|
en
| 0.730543
|
#!/usr/bin/env python3 Base class for Faceswap :mod:`~plugins.extract.detect`, :mod:`~plugins.extract.align` and :mod:`~plugins.extract.mask` Plugins # pylint:disable=no-name-in-module # pylint: disable=invalid-name # TODO CPU mode # TODO Run with warnings mode Return the configuration for the requested model Parameters ---------- plugin_name: str The module name of the child plugin. configfile: str, optional Path to a :file:`./config/<plugin_type>.ini` file for this plugin. Default: use system configuration. Returns ------- config_dict, dict A dictionary of configuration items from the configuration file Extractor Plugin Object All ``_base`` classes for Aligners, Detectors and Maskers inherit from this class. This class sets up a pipeline for working with ML plugins. Plugins are split into 3 threads, to utilize Numpy and CV2s parallel processing, as well as allow the predict function of the model to sit in a dedicated thread. A plugin is expected to have 3 core functions, each in their own thread: - :func:`process_input()` - Prepare the data for feeding into a model - :func:`predict` - Feed the data through the model - :func:`process_output()` - Perform any data post-processing Parameters ---------- git_model_id: int The second digit in the github tag that identifies this model. See https://github.com/deepfakes-models/faceswap-models for more information model_filename: str The name of the model file to be loaded exclude_gpus: list, optional A list of indices correlating to connected GPUs that Tensorflow should not use. Pass ``None`` to not exclude any GPUs. Default: ``None`` configfile: str, optional Path to a custom configuration ``ini`` file. Default: Use system configfile instance: int, optional If this plugin is being executed multiple times (i.e. multiple pipelines have been launched), the instance of the plugin must be passed in for naming convention reasons. Default: 0 The following attributes should be set in the plugin's :func:`__init__` method after initializing the parent. Attributes ---------- name: str Name of this plugin. Used for display purposes. input_size: int The input size to the model in pixels across one edge. The input size should always be square. color_format: str Color format for model. Must be ``'BGR'``, ``'RGB'`` or ``'GRAY'``. Defaults to ``'BGR'`` if not explicitly set. vram: int Approximate VRAM used by the model at :attr:`input_size`. Used to calculate the :attr:`batchsize`. Be conservative to avoid OOM. vram_warnings: int Approximate VRAM used by the model at :attr:`input_size` that will still run, but generates warnings. Used to calculate the :attr:`batchsize`. Be conservative to avoid OOM. vram_per_batch: int Approximate additional VRAM used by the model for each additional batch. Used to calculate the :attr:`batchsize`. Be conservative to avoid OOM. See Also -------- plugins.extract.detect._base : Detector parent class for extraction plugins. plugins.extract.align._base : Aligner parent class for extraction plugins. plugins.extract.mask._base : Masker parent class for extraction plugins. plugins.extract.pipeline : The extract pipeline that configures and calls all plugins dict: Config for this plugin, loaded from ``extract.ini`` configfile str or list: Path to the model file(s) (if required). Multiple model files should be a list of strings # << SET THE FOLLOWING IN PLUGINS __init__ IF DIFFERENT FROM DEFAULT >> # # Will run at this with warnings # << THE FOLLOWING ARE SET IN self.initialize METHOD >> # int: Queue size for all internal queues. Set in :func:`initialize()` varies: The model for this plugin. Set in the plugin's :func:`init_model()` method # For detectors that support batching, this should be set to the calculated batch size # that the amount of available VRAM will support. int: Batchsize for feeding this model. The number of images the model should feed through at once. dict: in + out queues and internal queues for this plugin, list: Internal threads for this plugin dict: The :class:`plugins.extract.pipeline.ExtractMedia` objects currently being processed. Stored at input for pairing back up on output of extractor process # << THE FOLLOWING PROTECTED ATTRIBUTES ARE SET IN PLUGIN TYPE _base.py >>> # str: Plugin type. ``detect`` or ``align`` set in ``<plugin_type>._base`` # <<< OVERIDABLE METHODS >>> # **Override method** Override this method to execute the specific model initialization method **Override method** Override this method for specific extractor pre-processing of image Parameters ---------- batch : dict Contains the batch that is currently being passed through the plugin process Notes ----- When preparing an input to the model a key ``feed`` must be added to the :attr:`batch` ``dict`` which contains this input. **Override method** Override this method for specific extractor model prediction function Parameters ---------- batch : dict Contains the batch that is currently being passed through the plugin process Notes ----- Input for :func:`predict` should have been set in :func:`process_input` with the addition of a ``feed`` key to the :attr:`batch` ``dict``. Output from the model should add the key ``prediction`` to the :attr:`batch` ``dict``. For Detect: the expected output for the ``prediction`` key of the :attr:`batch` dict should be a ``list`` of :attr:`batchsize` of detected face points. These points should be either a ``list``, ``tuple`` or ``numpy.ndarray`` with the first 4 items being the `left`, `top`, `right`, `bottom` points, in that order **Override method** Override this method for specific extractor model post predict function Parameters ---------- batch : dict Contains the batch that is currently being passed through the plugin process Notes ----- For Align: The key ``landmarks`` must be returned in the :attr:`batch` ``dict`` from this method. This should be a ``list`` or ``numpy.ndarray`` of :attr:`batchsize` containing a ``list``, ``tuple`` or ``numpy.ndarray`` of `(x, y)` coordinates of the 68 point landmarks as calculated from the :attr:`model`. **Override method** (at `<plugin_type>` level) This method should be overridden at the `<plugin_type>` level (IE. ``plugins.extract.detect._base`` or ``plugins.extract.align._base``) and should not be overridden within plugins themselves. It acts as a wrapper for the plugin's ``self.predict`` method and handles any predict processing that is consistent for all plugins within the `plugin_type` Parameters ---------- batch : dict Contains the batch that is currently being passed through the plugin process **Override method** (at `<plugin_type>` level) This method should be overridden at the `<plugin_type>` level (IE. :mod:`plugins.extract.detect._base`, :mod:`plugins.extract.align._base` or :mod:`plugins.extract.mask._base`) and should not be overridden within plugins themselves. Handles consistent finalization for all plugins that exist within that plugin type. Its input is always the output from :func:`process_output()` Parameters ---------- batch : dict Contains the batch that is currently being passed through the plugin process **Override method** (at `<plugin_type>` level) This method should be overridden at the `<plugin_type>` level (IE. :mod:`plugins.extract.detect._base`, :mod:`plugins.extract.align._base` or :mod:`plugins.extract.mask._base`) and should not be overridden within plugins themselves. Get :class:`~plugins.extract.pipeline.ExtractMedia` items from the queue in batches of :attr:`batchsize` Parameters ---------- queue : queue.Queue() The ``queue`` that the batch will be fed from. This will be the input to the plugin. # <<< THREADING METHODS >>> # Start all threads Exposed for :mod:`~plugins.extract.pipeline` to start plugin's threads Join all threads Exposed for :mod:`~plugins.extract.pipeline` to join plugin's threads Check all threads for errors Exposed for :mod:`~plugins.extract.pipeline` to check plugin's threads for errors # <<< PROTECTED ACCESS METHODS >>> # # <<< INIT METHODS >>> # Check if model is available, if not, download and unzip it # <<< PLUGIN INITIALIZATION >>> # Initialize the extractor plugin Should be called from :mod:`~plugins.extract.pipeline` Add the queues in_queue and out_queue should be previously created queue manager queues. queues should be a list of queue names # <<< THREAD METHODS >>> # Compile the threads into self._threads list Add a MultiThread thread to self._threads Perform a plugin function in a thread # Process input items to batches # Put the final batch # Process output items to individual items from batch # <<< QUEUE METHODS >>> # Yield one item from a queue Convert a dictionary of lists to a list of dictionaries
| 2.176684
| 2
|
pyplan/pyplan/preference_module/serializers.py
|
jorgedouglas71/pyplan-ide
| 17
|
6625819
|
<reponame>jorgedouglas71/pyplan-ide<gh_stars>10-100
from rest_framework import serializers
from .models import PreferenceModule
class PreferenceModuleSerializer(serializers.ModelSerializer):
class Meta:
model = PreferenceModule
fields = '__all__'
|
from rest_framework import serializers
from .models import PreferenceModule
class PreferenceModuleSerializer(serializers.ModelSerializer):
class Meta:
model = PreferenceModule
fields = '__all__'
|
none
| 1
| 1.6972
| 2
|
|
examples/mysql.py
|
vamshi091211/pyinfra
| 1
|
6625820
|
from pyinfra import host, state
from pyinfra.operations import apt, files, mysql, python
SUDO = True
if host.fact.linux_name != 'Debian':
# Raises an exception mid-deploy
python.raise_exception(
{'Ensure we are Debian'},
NotImplementedError,
'`mysql.py` only works on Debian',
)
apt.packages(
{'Install mysql server & client'},
['mysql-server'],
update=True,
cache_time=3600,
)
# Setup a MySQL role & database
#
mysql.user(
{'Create the pyinfra@localhost MySQL user'},
'pyinfra',
password='<PASSWORD>',
)
mysql.database(
{'Create the pyinfra_stuff database'},
'pyinfra_stuff',
user='pyinfra',
user_privileges=['SELECT', 'INSERT'],
charset='utf8',
)
# Upload & import a SQL file into the pyinfra_stuff database
#
filename = 'files/a_db.sql'
temp_filename = state.get_temp_filename(filename)
files.put(
{'Upload the a_db.sql file'},
filename, temp_filename,
)
mysql.load(
{'Import the a_db.sql file'},
temp_filename,
database='pyinfra_stuff',
)
# Now duplicate the pyinfra_stuff database -> pyinfra_stuff_copy
#
mysql.database(
{'Create the pyinfra_stuff_copy database'},
'pyinfra_stuff_copy',
charset='utf8',
)
dump_filename = state.get_temp_filename('mysql_dump')
mysql.dump(
{'Dump the pyinfra_stuff database'},
dump_filename,
database='pyinfra_stuff',
)
mysql.load(
{'Import the pyinfra_stuff dump into pyinfra_stuff_copy'},
dump_filename,
database='pyinfra_stuff_copy',
)
|
from pyinfra import host, state
from pyinfra.operations import apt, files, mysql, python
SUDO = True
if host.fact.linux_name != 'Debian':
# Raises an exception mid-deploy
python.raise_exception(
{'Ensure we are Debian'},
NotImplementedError,
'`mysql.py` only works on Debian',
)
apt.packages(
{'Install mysql server & client'},
['mysql-server'],
update=True,
cache_time=3600,
)
# Setup a MySQL role & database
#
mysql.user(
{'Create the pyinfra@localhost MySQL user'},
'pyinfra',
password='<PASSWORD>',
)
mysql.database(
{'Create the pyinfra_stuff database'},
'pyinfra_stuff',
user='pyinfra',
user_privileges=['SELECT', 'INSERT'],
charset='utf8',
)
# Upload & import a SQL file into the pyinfra_stuff database
#
filename = 'files/a_db.sql'
temp_filename = state.get_temp_filename(filename)
files.put(
{'Upload the a_db.sql file'},
filename, temp_filename,
)
mysql.load(
{'Import the a_db.sql file'},
temp_filename,
database='pyinfra_stuff',
)
# Now duplicate the pyinfra_stuff database -> pyinfra_stuff_copy
#
mysql.database(
{'Create the pyinfra_stuff_copy database'},
'pyinfra_stuff_copy',
charset='utf8',
)
dump_filename = state.get_temp_filename('mysql_dump')
mysql.dump(
{'Dump the pyinfra_stuff database'},
dump_filename,
database='pyinfra_stuff',
)
mysql.load(
{'Import the pyinfra_stuff dump into pyinfra_stuff_copy'},
dump_filename,
database='pyinfra_stuff_copy',
)
|
en
| 0.433261
|
# Raises an exception mid-deploy # Setup a MySQL role & database # # Upload & import a SQL file into the pyinfra_stuff database # # Now duplicate the pyinfra_stuff database -> pyinfra_stuff_copy #
| 2.402385
| 2
|
python/lbann/modules/graph/utils.py
|
aj-prime/lbann
| 0
|
6625821
|
import lbann
from lbann.util import str_list
class GraphVertexData:
def __init__(self, layers, num_features):
"""Object to hold list of layers, where each layer represents a vertex
in a graph.
Args:
layers (iterator of layers): One dimensional iterator of node
features with N number of ndoes
num_features (int) : the number of features per vertex
"""
self.shape = (len(layers), num_features)
self.layers = layers
self.num_nodes = len(layers)
self.num_features = num_features
def __getitem__(self, node):
"""Get the feature vector of the None node represented as an LBANN layer
args: node (int): The node to retrieve the features for.
returns: (Layer) : returns the features of the Vertex <node> of the graph.
"""
return self.layers[node]
def __setitem__(self, node, feature):
"""Set the value of the row-th layer in
args: row (int):
layer (Layer):
"""
self.layers[node] = feature
def update_num_features(self, num_features):
"""Update the internal shapes to keep track of features
Args:
num_features (int): the features per vertex
"""
self.num_features = num_features
self.shape = (len(self.layers), num_features)
def size(self, index = None):
"""Get the size (shape) of the GraphVertexObject, where the size is represented
as a tuple (n,m), where n is the number of nodes and m is the number of
features per node.
args: index (int): 0 to return the number of nodes and 1 to return the number of
features.
returns: (int) or (int,int): Either returns the tuple (n,m) or n or m.
"""
if isinstance(index,int):
return self.shape[index]
else:
return self.shape
def get_mat(self, cols = None):
"""Generates a matrix representation of the graph data.
args: cols (int)
"""
mat = lbann.Concatenation(self.layers)
if (cols):
mat = lbann.Reshape(mat, dims=str_list([self.shape[0], cols]))
else:
mat = lbann.Reshape(mat, dims=str_list([self.shape[0], self.shape[1]]))
return mat
def clone(self):
"""Generates a clone of the GraphVertexData object. Results in a
splitting in the DAG.
"""
cloned_layers = []
for i,node in enumerate(self.layers):
temp = lbann.Split(node)
layers[i] = lbann.Identity(temp)
cloned_layers.append(lbann.Identity(temp))
return GraphVertexData(cloned_layers, self.num_features)
@classmethod
def matrix_to_graph(cls, mat_layer, num_vertices, num_features):
"""Given a 2D matrix of shape (num_vertices, num_features), returns a
GraphVertexData object with num_vertices number of nodes with num_features.
"""
slice_points = str_list([i for i in range(0,num_vertices * num_features + 1, num_features)])
flattened_layer = lbann.Reshape(mat_layer, dims = str(num_vertices * num_features))
sliced_mat_layer = lbann.Slice(flattened_layer, axis = 0, slice_points = slice_points)
list_of_layers = []
for node in range(num_vertices):
temp = lbann.Identity(sliced_mat_layer)
list_of_layers.append(lbann.Reshape(temp, dims=str_list([1, num_features])))
return cls(list_of_layers, num_features)
|
import lbann
from lbann.util import str_list
class GraphVertexData:
def __init__(self, layers, num_features):
"""Object to hold list of layers, where each layer represents a vertex
in a graph.
Args:
layers (iterator of layers): One dimensional iterator of node
features with N number of ndoes
num_features (int) : the number of features per vertex
"""
self.shape = (len(layers), num_features)
self.layers = layers
self.num_nodes = len(layers)
self.num_features = num_features
def __getitem__(self, node):
"""Get the feature vector of the None node represented as an LBANN layer
args: node (int): The node to retrieve the features for.
returns: (Layer) : returns the features of the Vertex <node> of the graph.
"""
return self.layers[node]
def __setitem__(self, node, feature):
"""Set the value of the row-th layer in
args: row (int):
layer (Layer):
"""
self.layers[node] = feature
def update_num_features(self, num_features):
"""Update the internal shapes to keep track of features
Args:
num_features (int): the features per vertex
"""
self.num_features = num_features
self.shape = (len(self.layers), num_features)
def size(self, index = None):
"""Get the size (shape) of the GraphVertexObject, where the size is represented
as a tuple (n,m), where n is the number of nodes and m is the number of
features per node.
args: index (int): 0 to return the number of nodes and 1 to return the number of
features.
returns: (int) or (int,int): Either returns the tuple (n,m) or n or m.
"""
if isinstance(index,int):
return self.shape[index]
else:
return self.shape
def get_mat(self, cols = None):
"""Generates a matrix representation of the graph data.
args: cols (int)
"""
mat = lbann.Concatenation(self.layers)
if (cols):
mat = lbann.Reshape(mat, dims=str_list([self.shape[0], cols]))
else:
mat = lbann.Reshape(mat, dims=str_list([self.shape[0], self.shape[1]]))
return mat
def clone(self):
"""Generates a clone of the GraphVertexData object. Results in a
splitting in the DAG.
"""
cloned_layers = []
for i,node in enumerate(self.layers):
temp = lbann.Split(node)
layers[i] = lbann.Identity(temp)
cloned_layers.append(lbann.Identity(temp))
return GraphVertexData(cloned_layers, self.num_features)
@classmethod
def matrix_to_graph(cls, mat_layer, num_vertices, num_features):
"""Given a 2D matrix of shape (num_vertices, num_features), returns a
GraphVertexData object with num_vertices number of nodes with num_features.
"""
slice_points = str_list([i for i in range(0,num_vertices * num_features + 1, num_features)])
flattened_layer = lbann.Reshape(mat_layer, dims = str(num_vertices * num_features))
sliced_mat_layer = lbann.Slice(flattened_layer, axis = 0, slice_points = slice_points)
list_of_layers = []
for node in range(num_vertices):
temp = lbann.Identity(sliced_mat_layer)
list_of_layers.append(lbann.Reshape(temp, dims=str_list([1, num_features])))
return cls(list_of_layers, num_features)
|
en
| 0.81183
|
Object to hold list of layers, where each layer represents a vertex in a graph. Args: layers (iterator of layers): One dimensional iterator of node features with N number of ndoes num_features (int) : the number of features per vertex Get the feature vector of the None node represented as an LBANN layer args: node (int): The node to retrieve the features for. returns: (Layer) : returns the features of the Vertex <node> of the graph. Set the value of the row-th layer in args: row (int): layer (Layer): Update the internal shapes to keep track of features Args: num_features (int): the features per vertex Get the size (shape) of the GraphVertexObject, where the size is represented as a tuple (n,m), where n is the number of nodes and m is the number of features per node. args: index (int): 0 to return the number of nodes and 1 to return the number of features. returns: (int) or (int,int): Either returns the tuple (n,m) or n or m. Generates a matrix representation of the graph data. args: cols (int) Generates a clone of the GraphVertexData object. Results in a splitting in the DAG. Given a 2D matrix of shape (num_vertices, num_features), returns a GraphVertexData object with num_vertices number of nodes with num_features.
| 3.217636
| 3
|
meta.py
|
mayur295/MetaDesktopAssistant-
| 0
|
6625822
|
#This a python project that focuses on development of basic desktop assistant
#---**********************---
#import module pyttsx3 which is used for coversion of text into speech
# init function to get an engine instance for the speech synthesis (formation)
# sapi5 is API which allows the use of speech recognition(user asks) and speech synthesis (meta replys) within windows application
# say method on the engine that passes the text input to be spoken
# run and wait method, it processes the voice commands.
import pyttsx3
import datetime
import speech_recognition as sr
import wikipedia
import webbrowser
import os
import smtplib
import pyautogui
engine = pyttsx3.init('sapi5')
voices = engine.getProperty('voices') #to get the voice details
# print(voices[1].id) #0 and 1 are the voices available 0- male voice 1- female voice
engine.setProperty('voice',voices[1].id)
def speak(audio):
engine.say(audio)
engine.runAndWait() #Without this command, speech will not be audible to us.
def screenshot():
pic=pyautogui.screenshot()
pic.save('c:/User')
def wishMe():
hour = int(datetime.datetime.now().hour)
if hour>=0 and hour<12:
speak("Good morning!")
elif hour>=12 and hour<=16:
speak("Good afternoon!")
else:
speak("Good evening!")
speak("This is Meta, How may I help you?")
def takecommand():
''' it takes micrphone input from the user and returns string output
'''
# creating a recognizer instance
r = sr.Recognizer()
# taking the audio input from microphone as source audio_data argument
with sr.Microphone() as source:
print("listening...")
r.pause_threshold = 0.8
audio = r.listen(source)
try:
print("Recognizing...")
# method of recognizer instance
query = r.recognize_google(audio, language = 'en-in')#Using google speech recognition api for voice recognition.
# returns the audio in the string format
print(f"user said: {query}\n")
except Exception as e:
# print e
print("sorry, i dont understand")
# return none string when there is some problem
return"None"
return query
def sendEmail(to, content):
server = smtplib.SMTP('smtp.gmail.com', 587)
server.ehlo()
server.starttls()
server.login('<EMAIL>', '<PASSWORD>') #write
server.sendmail('<EMAIL>', to, content) #write
server.close()
if __name__ == "__main__" :
wishMe()
while True:
query = takecommand().lower()
## LOGIC for executing task based on query asked by the user
#To search something in wikipedia
if 'wikipedia' in query:
speak("searching wikipedia")
query = query.replace('wikipedia',"")
results = wikipedia.summary(query, sentences=2)
speak("According to wikipedia")
print(results)
speak(results)
#To open youtube
elif "open youtube" in query:
webbrowser.open("youtube.com")
elif "open google" in query:
webbrowser.open("google.com")
elif 'open Linkedin' in query:
webbrowser.open("Linkedin.com")
elif 'open instagram' in query:
webbrowser.open("instagram.com")
elif 'open whatsapp' in query:
webbrowser.open("https://web.whatsapp.com/")
# this will exit and terminate the program
elif "bye" in query:
speak("Bye. Have A Good Day")
exit()
elif 'screenshot' in query:
screenshot()
#Know time by using datetime() function and storing the current
#or live system into a variable called strTime.
elif 'the time' in query:
strTime = datetime.datetime.now().strftime("%H:%M:%S")
speak(f"The time is {strTime}")
print(strTime)
#To open visual studio code
elif 'open code' in query:
codePath = "C:\\Users\\akanksha\\AppData\Local\\Programs\\Microsoft VS Code\\Code.exe" #mention the target location of app
os.startfile(codePath)
#To send mail
elif 'mail to user' in query:
try:
speak("What should I say?")
content = takecommand()
to = "<EMAIL>"
sendEmail(to, content)
speak("Email has been sent!")
except Exception as e:
print(e)
speak("Sorry, I am not able to send this email")
|
#This a python project that focuses on development of basic desktop assistant
#---**********************---
#import module pyttsx3 which is used for coversion of text into speech
# init function to get an engine instance for the speech synthesis (formation)
# sapi5 is API which allows the use of speech recognition(user asks) and speech synthesis (meta replys) within windows application
# say method on the engine that passes the text input to be spoken
# run and wait method, it processes the voice commands.
import pyttsx3
import datetime
import speech_recognition as sr
import wikipedia
import webbrowser
import os
import smtplib
import pyautogui
engine = pyttsx3.init('sapi5')
voices = engine.getProperty('voices') #to get the voice details
# print(voices[1].id) #0 and 1 are the voices available 0- male voice 1- female voice
engine.setProperty('voice',voices[1].id)
def speak(audio):
engine.say(audio)
engine.runAndWait() #Without this command, speech will not be audible to us.
def screenshot():
pic=pyautogui.screenshot()
pic.save('c:/User')
def wishMe():
hour = int(datetime.datetime.now().hour)
if hour>=0 and hour<12:
speak("Good morning!")
elif hour>=12 and hour<=16:
speak("Good afternoon!")
else:
speak("Good evening!")
speak("This is Meta, How may I help you?")
def takecommand():
''' it takes micrphone input from the user and returns string output
'''
# creating a recognizer instance
r = sr.Recognizer()
# taking the audio input from microphone as source audio_data argument
with sr.Microphone() as source:
print("listening...")
r.pause_threshold = 0.8
audio = r.listen(source)
try:
print("Recognizing...")
# method of recognizer instance
query = r.recognize_google(audio, language = 'en-in')#Using google speech recognition api for voice recognition.
# returns the audio in the string format
print(f"user said: {query}\n")
except Exception as e:
# print e
print("sorry, i dont understand")
# return none string when there is some problem
return"None"
return query
def sendEmail(to, content):
server = smtplib.SMTP('smtp.gmail.com', 587)
server.ehlo()
server.starttls()
server.login('<EMAIL>', '<PASSWORD>') #write
server.sendmail('<EMAIL>', to, content) #write
server.close()
if __name__ == "__main__" :
wishMe()
while True:
query = takecommand().lower()
## LOGIC for executing task based on query asked by the user
#To search something in wikipedia
if 'wikipedia' in query:
speak("searching wikipedia")
query = query.replace('wikipedia',"")
results = wikipedia.summary(query, sentences=2)
speak("According to wikipedia")
print(results)
speak(results)
#To open youtube
elif "open youtube" in query:
webbrowser.open("youtube.com")
elif "open google" in query:
webbrowser.open("google.com")
elif 'open Linkedin' in query:
webbrowser.open("Linkedin.com")
elif 'open instagram' in query:
webbrowser.open("instagram.com")
elif 'open whatsapp' in query:
webbrowser.open("https://web.whatsapp.com/")
# this will exit and terminate the program
elif "bye" in query:
speak("Bye. Have A Good Day")
exit()
elif 'screenshot' in query:
screenshot()
#Know time by using datetime() function and storing the current
#or live system into a variable called strTime.
elif 'the time' in query:
strTime = datetime.datetime.now().strftime("%H:%M:%S")
speak(f"The time is {strTime}")
print(strTime)
#To open visual studio code
elif 'open code' in query:
codePath = "C:\\Users\\akanksha\\AppData\Local\\Programs\\Microsoft VS Code\\Code.exe" #mention the target location of app
os.startfile(codePath)
#To send mail
elif 'mail to user' in query:
try:
speak("What should I say?")
content = takecommand()
to = "<EMAIL>"
sendEmail(to, content)
speak("Email has been sent!")
except Exception as e:
print(e)
speak("Sorry, I am not able to send this email")
|
en
| 0.848647
|
#This a python project that focuses on development of basic desktop assistant #---**********************--- #import module pyttsx3 which is used for coversion of text into speech # init function to get an engine instance for the speech synthesis (formation) # sapi5 is API which allows the use of speech recognition(user asks) and speech synthesis (meta replys) within windows application # say method on the engine that passes the text input to be spoken # run and wait method, it processes the voice commands. #to get the voice details # print(voices[1].id) #0 and 1 are the voices available 0- male voice 1- female voice #Without this command, speech will not be audible to us. it takes micrphone input from the user and returns string output # creating a recognizer instance # taking the audio input from microphone as source audio_data argument # method of recognizer instance #Using google speech recognition api for voice recognition. # returns the audio in the string format # print e # return none string when there is some problem #write #write ## LOGIC for executing task based on query asked by the user #To search something in wikipedia #To open youtube # this will exit and terminate the program #Know time by using datetime() function and storing the current #or live system into a variable called strTime. #To open visual studio code #mention the target location of app #To send mail
| 3.653066
| 4
|
sdk/python/pulumi_azure_nextgen/machinelearning/list_workspace_keys.py
|
pulumi/pulumi-azure-nextgen
| 31
|
6625823
|
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from .. import _utilities, _tables
__all__ = [
'ListWorkspaceKeysResult',
'AwaitableListWorkspaceKeysResult',
'list_workspace_keys',
]
@pulumi.output_type
class ListWorkspaceKeysResult:
"""
Workspace authorization keys for a workspace.
"""
def __init__(__self__, primary_token=None, secondary_token=None):
if primary_token and not isinstance(primary_token, str):
raise TypeError("Expected argument 'primary_token' to be a str")
pulumi.set(__self__, "primary_token", primary_token)
if secondary_token and not isinstance(secondary_token, str):
raise TypeError("Expected argument 'secondary_token' to be a str")
pulumi.set(__self__, "secondary_token", secondary_token)
@property
@pulumi.getter(name="primaryToken")
def primary_token(self) -> Optional[str]:
"""
Primary authorization key for this workspace.
"""
return pulumi.get(self, "primary_token")
@property
@pulumi.getter(name="secondaryToken")
def secondary_token(self) -> Optional[str]:
"""
Secondary authorization key for this workspace.
"""
return pulumi.get(self, "secondary_token")
class AwaitableListWorkspaceKeysResult(ListWorkspaceKeysResult):
# pylint: disable=using-constant-test
def __await__(self):
if False:
yield self
return ListWorkspaceKeysResult(
primary_token=self.primary_token,
secondary_token=self.secondary_token)
def list_workspace_keys(resource_group_name: Optional[str] = None,
workspace_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableListWorkspaceKeysResult:
"""
Workspace authorization keys for a workspace.
API Version: 2016-04-01.
:param str resource_group_name: The name of the resource group to which the machine learning workspace belongs.
:param str workspace_name: The name of the machine learning workspace.
"""
__args__ = dict()
__args__['resourceGroupName'] = resource_group_name
__args__['workspaceName'] = workspace_name
if opts is None:
opts = pulumi.InvokeOptions()
if opts.version is None:
opts.version = _utilities.get_version()
__ret__ = pulumi.runtime.invoke('azure-nextgen:machinelearning:listWorkspaceKeys', __args__, opts=opts, typ=ListWorkspaceKeysResult).value
return AwaitableListWorkspaceKeysResult(
primary_token=__ret__.primary_token,
secondary_token=__ret__.secondary_token)
|
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from .. import _utilities, _tables
__all__ = [
'ListWorkspaceKeysResult',
'AwaitableListWorkspaceKeysResult',
'list_workspace_keys',
]
@pulumi.output_type
class ListWorkspaceKeysResult:
"""
Workspace authorization keys for a workspace.
"""
def __init__(__self__, primary_token=None, secondary_token=None):
if primary_token and not isinstance(primary_token, str):
raise TypeError("Expected argument 'primary_token' to be a str")
pulumi.set(__self__, "primary_token", primary_token)
if secondary_token and not isinstance(secondary_token, str):
raise TypeError("Expected argument 'secondary_token' to be a str")
pulumi.set(__self__, "secondary_token", secondary_token)
@property
@pulumi.getter(name="primaryToken")
def primary_token(self) -> Optional[str]:
"""
Primary authorization key for this workspace.
"""
return pulumi.get(self, "primary_token")
@property
@pulumi.getter(name="secondaryToken")
def secondary_token(self) -> Optional[str]:
"""
Secondary authorization key for this workspace.
"""
return pulumi.get(self, "secondary_token")
class AwaitableListWorkspaceKeysResult(ListWorkspaceKeysResult):
# pylint: disable=using-constant-test
def __await__(self):
if False:
yield self
return ListWorkspaceKeysResult(
primary_token=self.primary_token,
secondary_token=self.secondary_token)
def list_workspace_keys(resource_group_name: Optional[str] = None,
workspace_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableListWorkspaceKeysResult:
"""
Workspace authorization keys for a workspace.
API Version: 2016-04-01.
:param str resource_group_name: The name of the resource group to which the machine learning workspace belongs.
:param str workspace_name: The name of the machine learning workspace.
"""
__args__ = dict()
__args__['resourceGroupName'] = resource_group_name
__args__['workspaceName'] = workspace_name
if opts is None:
opts = pulumi.InvokeOptions()
if opts.version is None:
opts.version = _utilities.get_version()
__ret__ = pulumi.runtime.invoke('azure-nextgen:machinelearning:listWorkspaceKeys', __args__, opts=opts, typ=ListWorkspaceKeysResult).value
return AwaitableListWorkspaceKeysResult(
primary_token=__ret__.primary_token,
secondary_token=__ret__.secondary_token)
|
en
| 0.866014
|
# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** Workspace authorization keys for a workspace. Primary authorization key for this workspace. Secondary authorization key for this workspace. # pylint: disable=using-constant-test Workspace authorization keys for a workspace. API Version: 2016-04-01. :param str resource_group_name: The name of the resource group to which the machine learning workspace belongs. :param str workspace_name: The name of the machine learning workspace.
| 1.758427
| 2
|
l-system_tree.py
|
dangbb/3D_L-System_Tree
| 7
|
6625824
|
<gh_stars>1-10
# Filename: l-system_tree.py
# Author: <NAME> (@def-pri-pub)
# License: BSD 3-Clause (read `./LICENSE` for details)
#
# This script is the logic for generating a Lindenmayer System tree. It's
# needs to be run inside of Blender for it to work. When it's done genrating
# you should be given a tree-like structure made out of cylinders and spheres
import math
import random
import bpy
from mathutils import Vector, Matrix
### Configuration Options ##
# Tree Characteristics
ANGLE = 45 # Angle which new branches come off of (in degrees)
BRANCH_LENGTH = 10 # Length of parent branch
BRANCH_DIVISOR = 1.6 # How much to divide parent branch length by
THICKNESS = 0.25 # How thick the branches should be
DEPTH = 5 # How many levels to render
SOFT_ENDS = True # Add soft ends (spheres) to the branches
# Twist at the A grammar
TWIST = False # Twist the child branches around the parent branch
TWIST_AMOUNT = 45 # How much to twist by
# Mesh Resolution
VERTICES = 16 # For branches (cylinders)
RING_COUNT = 16 # For soft ends (spheres)
SEGMENTS = 16 # For soft ends (spheres)
# Apply some randomness to the tree
VARIATION_MODE = False # apply a random variation to the tree, gives it a more natural feel
BRANCH_LENGTH_VARIATION = .5 # How much to vary the branch length
TWIST_VARIATION = 15 # How much to vary the twist by
ANGLE_VARIATION = 30 # How much to vary the child branche's branch angle by
#random.seed(0) # use this to set a random seed
# class for storing render state
class RenderParams:
__slots__ = (
'max_depth',
'cur_depth',
'branch_length',
'matrix_chain',
)
# sets up the Rendering Parameters
def __init__(self, branch_length=10, max_depth=5):
self.max_depth = max_depth
self.cur_depth = 0
self.branch_length = branch_length
self.matrix_chain = [Matrix.Identity(4)]
# Checks if we are deeper than our current depth or not
def depthGood(self):
return self.cur_depth < self.max_depth
# Multiplies the stored matrx_chain
def computedMatrixChain(self):
m = self.matrix_chain[0]
for i in range(1, len(self.matrix_chain)):
m *= self.matrix_chain[i]
return m
# This is used so that we don't accidentally add more sphere than we need to
_soft_ends_set = set()
# Makes a branch
# branch_length -- a non-negative number, how long each branch should be
# world_matrix -- A Matrix that will be where the placement of the branch starts
def mkBranch(branch_length, world_matrix):
global _soft_ends_set
# For the endpoints
if SOFT_ENDS:
# compute locations
a = world_matrix
b = world_matrix * Matrix.Translation((0, 0, branch_length))
# Get their tranlations (fronzen) (so we don't double add them)
a_loc = a.to_translation().freeze()
b_loc = b.to_translation().freeze()
# first endpoint
if a_loc not in _soft_ends_set:
_soft_ends_set.add(a_loc)
bpy.ops.mesh.primitive_uv_sphere_add(segments=SEGMENTS, ring_count=RING_COUNT, size=THICKNESS)
bpy.context.active_object.matrix_world *= a
# second
if b_loc not in _soft_ends_set:
_soft_ends_set.add(b_loc)
bpy.ops.mesh.primitive_uv_sphere_add(segments=SEGMENTS, ring_count=RING_COUNT, size=THICKNESS)
bpy.context.active_object.matrix_world *= b
# The actual branch
mid = world_matrix * Matrix.Translation((0, 0, branch_length / 2))
cylinder = bpy.ops.mesh.primitive_cylinder_add(
vertices=VERTICES,
radius=THICKNESS,
depth=branch_length,
)
bpy.context.active_object.matrix_world *= mid
# Grammar
# A -> BCDE
# B -> A
# C -> A
# D -> A
# E -> A
# (All these are in the context of having a max render depth
# A = Go forward x units, perform B & C, then back x units
# B = Turn left 45 degrees, perform A, then turn right 45 degrees
# C = Turn right 45 degrees, perform A, then turn left 45 degrees
# A - BCDE
def A(rp):
# Check depth
if not rp.depthGood():
return
# Record the amounts
original_branch_length = rp.branch_length
branch_length = rp.branch_length
twist_amount = TWIST_AMOUNT
# If variations are on, apply some
if VARIATION_MODE:
branch_length += random.uniform(-BRANCH_LENGTH_VARIATION, BRANCH_LENGTH_VARIATION)
twist_amount += random.uniform(-TWIST_VARIATION, TWIST_VARIATION)
# Make the branch
mkBranch(branch_length, rp.computedMatrixChain())
# Increase distance & twist
rp.matrix_chain.append(Matrix.Translation((0, 0, branch_length)))
if TWIST:
rp.matrix_chain.append(Matrix.Rotation(math.radians(twist_amount), 4, 'Z'))
rp.branch_length = branch_length / BRANCH_DIVISOR
# Do the other grammars
rp.cur_depth += 1
B(rp)
C(rp)
D(rp)
E(rp)
rp.cur_depth -= 1
# undo distance increase and twist
rp.branch_length = original_branch_length
if TWIST:
rp.matrix_chain.pop()
rp.matrix_chain.pop()
# B -> A
def B(rp):
# Check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(angle), 4, 'X'))
A(rp)
rp.matrix_chain.pop()
# C -> A
def C(rp):
# Check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(angle), 4, 'Y'))
A(rp)
rp.matrix_chain.pop()
# D -> A
def D(rp):
# check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(-angle), 4, 'X'))
A(rp)
rp.matrix_chain.pop()
# E -> A
def E(rp):
# check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(-angle), 4, 'Y'))
A(rp)
rp.matrix_chain.pop()
# render something
rp = RenderParams(BRANCH_LENGTH, DEPTH)
A(rp)
|
# Filename: l-system_tree.py
# Author: <NAME> (@def-pri-pub)
# License: BSD 3-Clause (read `./LICENSE` for details)
#
# This script is the logic for generating a Lindenmayer System tree. It's
# needs to be run inside of Blender for it to work. When it's done genrating
# you should be given a tree-like structure made out of cylinders and spheres
import math
import random
import bpy
from mathutils import Vector, Matrix
### Configuration Options ##
# Tree Characteristics
ANGLE = 45 # Angle which new branches come off of (in degrees)
BRANCH_LENGTH = 10 # Length of parent branch
BRANCH_DIVISOR = 1.6 # How much to divide parent branch length by
THICKNESS = 0.25 # How thick the branches should be
DEPTH = 5 # How many levels to render
SOFT_ENDS = True # Add soft ends (spheres) to the branches
# Twist at the A grammar
TWIST = False # Twist the child branches around the parent branch
TWIST_AMOUNT = 45 # How much to twist by
# Mesh Resolution
VERTICES = 16 # For branches (cylinders)
RING_COUNT = 16 # For soft ends (spheres)
SEGMENTS = 16 # For soft ends (spheres)
# Apply some randomness to the tree
VARIATION_MODE = False # apply a random variation to the tree, gives it a more natural feel
BRANCH_LENGTH_VARIATION = .5 # How much to vary the branch length
TWIST_VARIATION = 15 # How much to vary the twist by
ANGLE_VARIATION = 30 # How much to vary the child branche's branch angle by
#random.seed(0) # use this to set a random seed
# class for storing render state
class RenderParams:
__slots__ = (
'max_depth',
'cur_depth',
'branch_length',
'matrix_chain',
)
# sets up the Rendering Parameters
def __init__(self, branch_length=10, max_depth=5):
self.max_depth = max_depth
self.cur_depth = 0
self.branch_length = branch_length
self.matrix_chain = [Matrix.Identity(4)]
# Checks if we are deeper than our current depth or not
def depthGood(self):
return self.cur_depth < self.max_depth
# Multiplies the stored matrx_chain
def computedMatrixChain(self):
m = self.matrix_chain[0]
for i in range(1, len(self.matrix_chain)):
m *= self.matrix_chain[i]
return m
# This is used so that we don't accidentally add more sphere than we need to
_soft_ends_set = set()
# Makes a branch
# branch_length -- a non-negative number, how long each branch should be
# world_matrix -- A Matrix that will be where the placement of the branch starts
def mkBranch(branch_length, world_matrix):
global _soft_ends_set
# For the endpoints
if SOFT_ENDS:
# compute locations
a = world_matrix
b = world_matrix * Matrix.Translation((0, 0, branch_length))
# Get their tranlations (fronzen) (so we don't double add them)
a_loc = a.to_translation().freeze()
b_loc = b.to_translation().freeze()
# first endpoint
if a_loc not in _soft_ends_set:
_soft_ends_set.add(a_loc)
bpy.ops.mesh.primitive_uv_sphere_add(segments=SEGMENTS, ring_count=RING_COUNT, size=THICKNESS)
bpy.context.active_object.matrix_world *= a
# second
if b_loc not in _soft_ends_set:
_soft_ends_set.add(b_loc)
bpy.ops.mesh.primitive_uv_sphere_add(segments=SEGMENTS, ring_count=RING_COUNT, size=THICKNESS)
bpy.context.active_object.matrix_world *= b
# The actual branch
mid = world_matrix * Matrix.Translation((0, 0, branch_length / 2))
cylinder = bpy.ops.mesh.primitive_cylinder_add(
vertices=VERTICES,
radius=THICKNESS,
depth=branch_length,
)
bpy.context.active_object.matrix_world *= mid
# Grammar
# A -> BCDE
# B -> A
# C -> A
# D -> A
# E -> A
# (All these are in the context of having a max render depth
# A = Go forward x units, perform B & C, then back x units
# B = Turn left 45 degrees, perform A, then turn right 45 degrees
# C = Turn right 45 degrees, perform A, then turn left 45 degrees
# A - BCDE
def A(rp):
# Check depth
if not rp.depthGood():
return
# Record the amounts
original_branch_length = rp.branch_length
branch_length = rp.branch_length
twist_amount = TWIST_AMOUNT
# If variations are on, apply some
if VARIATION_MODE:
branch_length += random.uniform(-BRANCH_LENGTH_VARIATION, BRANCH_LENGTH_VARIATION)
twist_amount += random.uniform(-TWIST_VARIATION, TWIST_VARIATION)
# Make the branch
mkBranch(branch_length, rp.computedMatrixChain())
# Increase distance & twist
rp.matrix_chain.append(Matrix.Translation((0, 0, branch_length)))
if TWIST:
rp.matrix_chain.append(Matrix.Rotation(math.radians(twist_amount), 4, 'Z'))
rp.branch_length = branch_length / BRANCH_DIVISOR
# Do the other grammars
rp.cur_depth += 1
B(rp)
C(rp)
D(rp)
E(rp)
rp.cur_depth -= 1
# undo distance increase and twist
rp.branch_length = original_branch_length
if TWIST:
rp.matrix_chain.pop()
rp.matrix_chain.pop()
# B -> A
def B(rp):
# Check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(angle), 4, 'X'))
A(rp)
rp.matrix_chain.pop()
# C -> A
def C(rp):
# Check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(angle), 4, 'Y'))
A(rp)
rp.matrix_chain.pop()
# D -> A
def D(rp):
# check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(-angle), 4, 'X'))
A(rp)
rp.matrix_chain.pop()
# E -> A
def E(rp):
# check depth
if not rp.depthGood():
return
# Set the angle
angle = ANGLE
if VARIATION_MODE:
angle += random.uniform(-ANGLE_VARIATION, ANGLE_VARIATION)
# Rotate & go deeper
rp.matrix_chain.append(Matrix.Rotation(math.radians(-angle), 4, 'Y'))
A(rp)
rp.matrix_chain.pop()
# render something
rp = RenderParams(BRANCH_LENGTH, DEPTH)
A(rp)
|
en
| 0.848232
|
# Filename: l-system_tree.py # Author: <NAME> (@def-pri-pub) # License: BSD 3-Clause (read `./LICENSE` for details) # # This script is the logic for generating a Lindenmayer System tree. It's # needs to be run inside of Blender for it to work. When it's done genrating # you should be given a tree-like structure made out of cylinders and spheres ### Configuration Options ## # Tree Characteristics # Angle which new branches come off of (in degrees) # Length of parent branch # How much to divide parent branch length by # How thick the branches should be # How many levels to render # Add soft ends (spheres) to the branches # Twist at the A grammar # Twist the child branches around the parent branch # How much to twist by # Mesh Resolution # For branches (cylinders) # For soft ends (spheres) # For soft ends (spheres) # Apply some randomness to the tree # apply a random variation to the tree, gives it a more natural feel # How much to vary the branch length # How much to vary the twist by # How much to vary the child branche's branch angle by #random.seed(0) # use this to set a random seed # class for storing render state # sets up the Rendering Parameters # Checks if we are deeper than our current depth or not # Multiplies the stored matrx_chain # This is used so that we don't accidentally add more sphere than we need to # Makes a branch # branch_length -- a non-negative number, how long each branch should be # world_matrix -- A Matrix that will be where the placement of the branch starts # For the endpoints # compute locations # Get their tranlations (fronzen) (so we don't double add them) # first endpoint # second # The actual branch # Grammar # A -> BCDE # B -> A # C -> A # D -> A # E -> A # (All these are in the context of having a max render depth # A = Go forward x units, perform B & C, then back x units # B = Turn left 45 degrees, perform A, then turn right 45 degrees # C = Turn right 45 degrees, perform A, then turn left 45 degrees # A - BCDE # Check depth # Record the amounts # If variations are on, apply some # Make the branch # Increase distance & twist # Do the other grammars # undo distance increase and twist # B -> A # Check depth # Set the angle # Rotate & go deeper # C -> A # Check depth # Set the angle # Rotate & go deeper # D -> A # check depth # Set the angle # Rotate & go deeper # E -> A # check depth # Set the angle # Rotate & go deeper # render something
| 2.765174
| 3
|
lnbits/extensions/lnticket/views_api.py
|
pseudozach/lnbits-legend
| 76
|
6625825
|
import re
from http import HTTPStatus
from fastapi import Query
from fastapi.params import Depends
from starlette.exceptions import HTTPException
from lnbits.core.crud import get_user
from lnbits.core.services import create_invoice
from lnbits.core.views.api import api_payment
from lnbits.decorators import WalletTypeInfo, get_key_type
from lnbits.extensions.lnticket.models import CreateFormData, CreateTicketData
from . import lnticket_ext
from .crud import (
create_form,
create_ticket,
delete_form,
delete_ticket,
get_form,
get_forms,
get_ticket,
get_tickets,
set_ticket_paid,
update_form,
)
# FORMS
@lnticket_ext.get("/api/v1/forms")
async def api_forms_get(
all_wallets: bool = Query(False), wallet: WalletTypeInfo = Depends(get_key_type)
):
wallet_ids = [wallet.wallet.id]
if all_wallets:
wallet_ids = (await get_user(wallet.wallet.user)).wallet_ids
return [form.dict() for form in await get_forms(wallet_ids)]
@lnticket_ext.post("/api/v1/forms", status_code=HTTPStatus.CREATED)
@lnticket_ext.put("/api/v1/forms/{form_id}")
async def api_form_create(
data: CreateFormData, form_id=None, wallet: WalletTypeInfo = Depends(get_key_type)
):
if form_id:
form = await get_form(form_id)
if not form:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"Form does not exist."
)
if form.wallet != wallet.wallet.id:
raise HTTPException(
status_code=HTTPStatus.FORBIDDEN, detail=f"Not your form."
)
form = await update_form(form_id, **data.dict())
else:
form = await create_form(data, wallet.wallet)
return form.dict()
@lnticket_ext.delete("/api/v1/forms/{form_id}")
async def api_form_delete(form_id, wallet: WalletTypeInfo = Depends(get_key_type)):
form = await get_form(form_id)
if not form:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"Form does not exist."
)
if form.wallet != wallet.wallet.id:
raise HTTPException(status_code=HTTPStatus.FORBIDDEN, detail=f"Not your form.")
await delete_form(form_id)
raise HTTPException(status_code=HTTPStatus.NO_CONTENT)
#########tickets##########
@lnticket_ext.get("/api/v1/tickets")
async def api_tickets(
all_wallets: bool = Query(False), wallet: WalletTypeInfo = Depends(get_key_type)
):
wallet_ids = [wallet.wallet.id]
if all_wallets:
wallet_ids = (await get_user(wallet.wallet.user)).wallet_ids
return [form.dict() for form in await get_tickets(wallet_ids)]
@lnticket_ext.post("/api/v1/tickets/{form_id}", status_code=HTTPStatus.CREATED)
async def api_ticket_make_ticket(data: CreateTicketData, form_id):
form = await get_form(form_id)
if not form:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"LNTicket does not exist."
)
if data.sats < 1:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"0 invoices not allowed."
)
nwords = len(re.split(r"\s+", data.ltext))
try:
payment_hash, payment_request = await create_invoice(
wallet_id=form.wallet,
amount=data.sats,
memo=f"ticket with {nwords} words on {form_id}",
extra={"tag": "lnticket"},
)
except Exception as e:
raise HTTPException(status_code=HTTPStatus.INTERNAL_SERVER_ERROR, detail=str(e))
ticket = await create_ticket(
payment_hash=payment_hash, wallet=form.wallet, data=data
)
if not ticket:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail="LNTicket could not be fetched."
)
return {"payment_hash": payment_hash, "payment_request": payment_request}
@lnticket_ext.get("/api/v1/tickets/{payment_hash}", status_code=HTTPStatus.OK)
async def api_ticket_send_ticket(payment_hash):
ticket = await get_ticket(payment_hash)
try:
status = await api_payment(payment_hash)
if status["paid"]:
await set_ticket_paid(payment_hash=payment_hash)
return {"paid": True}
except Exception:
return {"paid": False}
return {"paid": False}
@lnticket_ext.delete("/api/v1/tickets/{ticket_id}")
async def api_ticket_delete(ticket_id, wallet: WalletTypeInfo = Depends(get_key_type)):
ticket = await get_ticket(ticket_id)
if not ticket:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"LNTicket does not exist."
)
if ticket.wallet != wallet.wallet.id:
raise HTTPException(status_code=HTTPStatus.FORBIDDEN, detail="Not your ticket.")
await delete_ticket(ticket_id)
raise HTTPException(status_code=HTTPStatus.NO_CONTENT)
|
import re
from http import HTTPStatus
from fastapi import Query
from fastapi.params import Depends
from starlette.exceptions import HTTPException
from lnbits.core.crud import get_user
from lnbits.core.services import create_invoice
from lnbits.core.views.api import api_payment
from lnbits.decorators import WalletTypeInfo, get_key_type
from lnbits.extensions.lnticket.models import CreateFormData, CreateTicketData
from . import lnticket_ext
from .crud import (
create_form,
create_ticket,
delete_form,
delete_ticket,
get_form,
get_forms,
get_ticket,
get_tickets,
set_ticket_paid,
update_form,
)
# FORMS
@lnticket_ext.get("/api/v1/forms")
async def api_forms_get(
all_wallets: bool = Query(False), wallet: WalletTypeInfo = Depends(get_key_type)
):
wallet_ids = [wallet.wallet.id]
if all_wallets:
wallet_ids = (await get_user(wallet.wallet.user)).wallet_ids
return [form.dict() for form in await get_forms(wallet_ids)]
@lnticket_ext.post("/api/v1/forms", status_code=HTTPStatus.CREATED)
@lnticket_ext.put("/api/v1/forms/{form_id}")
async def api_form_create(
data: CreateFormData, form_id=None, wallet: WalletTypeInfo = Depends(get_key_type)
):
if form_id:
form = await get_form(form_id)
if not form:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"Form does not exist."
)
if form.wallet != wallet.wallet.id:
raise HTTPException(
status_code=HTTPStatus.FORBIDDEN, detail=f"Not your form."
)
form = await update_form(form_id, **data.dict())
else:
form = await create_form(data, wallet.wallet)
return form.dict()
@lnticket_ext.delete("/api/v1/forms/{form_id}")
async def api_form_delete(form_id, wallet: WalletTypeInfo = Depends(get_key_type)):
form = await get_form(form_id)
if not form:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"Form does not exist."
)
if form.wallet != wallet.wallet.id:
raise HTTPException(status_code=HTTPStatus.FORBIDDEN, detail=f"Not your form.")
await delete_form(form_id)
raise HTTPException(status_code=HTTPStatus.NO_CONTENT)
#########tickets##########
@lnticket_ext.get("/api/v1/tickets")
async def api_tickets(
all_wallets: bool = Query(False), wallet: WalletTypeInfo = Depends(get_key_type)
):
wallet_ids = [wallet.wallet.id]
if all_wallets:
wallet_ids = (await get_user(wallet.wallet.user)).wallet_ids
return [form.dict() for form in await get_tickets(wallet_ids)]
@lnticket_ext.post("/api/v1/tickets/{form_id}", status_code=HTTPStatus.CREATED)
async def api_ticket_make_ticket(data: CreateTicketData, form_id):
form = await get_form(form_id)
if not form:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"LNTicket does not exist."
)
if data.sats < 1:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"0 invoices not allowed."
)
nwords = len(re.split(r"\s+", data.ltext))
try:
payment_hash, payment_request = await create_invoice(
wallet_id=form.wallet,
amount=data.sats,
memo=f"ticket with {nwords} words on {form_id}",
extra={"tag": "lnticket"},
)
except Exception as e:
raise HTTPException(status_code=HTTPStatus.INTERNAL_SERVER_ERROR, detail=str(e))
ticket = await create_ticket(
payment_hash=payment_hash, wallet=form.wallet, data=data
)
if not ticket:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail="LNTicket could not be fetched."
)
return {"payment_hash": payment_hash, "payment_request": payment_request}
@lnticket_ext.get("/api/v1/tickets/{payment_hash}", status_code=HTTPStatus.OK)
async def api_ticket_send_ticket(payment_hash):
ticket = await get_ticket(payment_hash)
try:
status = await api_payment(payment_hash)
if status["paid"]:
await set_ticket_paid(payment_hash=payment_hash)
return {"paid": True}
except Exception:
return {"paid": False}
return {"paid": False}
@lnticket_ext.delete("/api/v1/tickets/{ticket_id}")
async def api_ticket_delete(ticket_id, wallet: WalletTypeInfo = Depends(get_key_type)):
ticket = await get_ticket(ticket_id)
if not ticket:
raise HTTPException(
status_code=HTTPStatus.NOT_FOUND, detail=f"LNTicket does not exist."
)
if ticket.wallet != wallet.wallet.id:
raise HTTPException(status_code=HTTPStatus.FORBIDDEN, detail="Not your ticket.")
await delete_ticket(ticket_id)
raise HTTPException(status_code=HTTPStatus.NO_CONTENT)
|
de
| 0.442539
|
# FORMS #########tickets##########
| 2.019866
| 2
|
core/acl_old.py
|
Caledor/dl
| 22
|
6625826
|
<gh_stars>10-100
import sys
from core.timeline import now, Timeline
import re
do_act = None
def acl_func_str(acl):
global do_act
s = acl_str(acl_build(acl))
exec(s, globals())
# return do_act_list, s
do_act = do_act_list
return s, do_act_list
class Acl_Action:
INDENT = " "
PREP = """ try:
{act} = self.{act}
except Exception:
raise AttributeError('{act} is not an action')"""
ACT = """{indent}if {act}({args}):
{indent} return '{act}'"""
NONE = "{indent}return 0"
QUEUE_ACT = """{indent}Acl_Control.AQU.append(({act}, compile('{cond}', '<string>', 'eval')))"""
dragon_act = re.compile(r'dragon(form)?.act\(["\']([A-Za-z \*\+\d]+)["\']\)')
def __init__(self, action):
self._act = None
self.args = None
if action.startswith("dragon"):
self.action = "dragonform"
res = self.dragon_act.match(action)
if res:
self.args = res.group(2)
else:
self.action = action
self.depth = 0
def __repr__(self):
return self.action
def prep(self, adv):
if self.action == "dragonform" and self.args is not None:
self._act = lambda: adv.dragonform.act(self.args)
else:
self._act = lambda: getattr(adv, self.action)()
def do(self):
return self._act()
def prepare(self):
if self.action is None:
return False
return self.PREP.format(act=self.action)
def act(self):
if self.action is None:
return self.NONE.format(indent=self.INDENT * self.depth)
return self.ACT.format(
act=self.action, args=self.args or "", indent=self.INDENT * self.depth
)
def queue_act(self, cond, depth_mod=0):
if self.action is None:
raise ValueError("No actions queued")
return self.QUEUE_ACT.format(
act=self.action,
args=self.arguments,
cond=cond,
indent=self.INDENT * (self.depth + depth_mod),
)
class Acl_Condition:
banned = re.compile(
r"(exec|eval|compile|setattr|delattr|memoryview|property|globals|locals|open|print|__[a-zA-Z]+__).*"
)
banned_repl = "True"
assignment = re.compile(r"([^=><!])=([^=])")
assignment_repl = lambda s: s[1] + "==" + s[2]
@staticmethod
def sanitize_qwe_and_his_chunch_legs(condition):
condition = Acl_Condition.banned.sub(Acl_Condition.banned_repl, condition)
condition = Acl_Condition.assignment.sub(
Acl_Condition.assignment_repl, condition
)
return condition
def __init__(self, condition):
self.condition = Acl_Condition.sanitize_qwe_and_his_chunch_legs(condition)
# self.condition = condition
def prep(self):
self._cond = compile(self.condition, "<string>", "eval")
def eval(self):
return self.condition is None or eval(self.condition, Acl_Control.CTX)
class Acl_Control:
INDENT = " "
IF = """{indent}if {cond}:
{block}"""
ELIF = """{indent}elif {cond}:
{block}"""
ELSE = """{indent}else:
{block}"""
QUEUE = """{indent}if len(Acl_Control.AQU)==0 and {cond}:
{block}"""
AQU = []
CTX = None
def __init__(self, condition, depth=0):
self.conditions = [(Acl_Condition(condition), [])]
self._act_cond = None
self.depth = depth
def add_action(self, action):
action.depth = self.depth + 1
self.conditions[-1][-1].append(action)
def add_condition(self, condition, is_else=False):
self.conditions.append((Acl_Condition(condition), []))
def __repr__(self):
return "\n".join(f"\n<{cond}> {acts}" for cond, acts in self.conditions)
def prep(self, adv):
Acl_Control.AQU = []
for cond, acts in self.conditions:
cond.prep()
for a in acts:
a.prep(adv)
if len(self.conditions) == 1:
cond, acts = self.conditions[0]
if len(acts) == 1 and isinstance(acts[0], Acl_Action):
self._act_cond = acts[0], cond
def do(self):
for cond, acts in self.conditions:
if cond.eval():
for a in acts:
if a.do():
return True
break
return False
@staticmethod
def set_ctx(self, e):
this = self
pin, dname, dstat, didx = e.pin, e.dname, e.dstat, e.didx
prev = self.action.getprev()
seq = didx if dname[0] == "x" else 0 if dstat == -2 else -1
cancel = pin == "x" or pin == "fs"
x = didx if pin == "x" else 0
fsc = pin == "fs"
s = (
int(pin[1])
if (pin[0] == "s" and pin[1].isdigit()) or pin[-2:] == "-x"
else 0
)
sp = dname if pin == "sp" else 0
prep = pin == "prep"
sim_duration = self.duration
Acl_Control.CTX = locals()
def __call__(self, adv, e):
Acl_Control.set_ctx(adv, e)
if len(Acl_Control.AQU) > 0:
next_act, next_cond = Acl_Control.AQU[0]
if next_cond.eval() and next_act.do():
return Acl_Control.AQU.pop(0)
self.do()
def prepare(self):
prep_list = []
for _, acts in self.conditions:
prep_list.extend([a.prepare() for a in acts if a.prepare()])
return "\n".join(prep_list)
def act(self):
act_list = []
for idx, value in enumerate(self.conditions):
cond, acts = value
cond = cond.condition
if len(acts) == 0:
continue
if cond.startswith("QUEUE"):
cond = "True" if len(cond) < 6 else cond[6:]
pattern = self.QUEUE
block = [a.queue_act("True") for a in acts]
block.append(
"{indent} return 'queued'".format(
indent=self.INDENT * self.depth
)
)
else:
if idx == 0:
pattern = self.IF
elif cond != "ELSE":
pattern = self.ELIF
else:
pattern = self.ELSE
block = [a.act() for a in acts]
if self.depth == 0:
act_list = block
else:
act_list.append(
pattern.format(
cond=cond,
block="\n".join(block),
indent=self.INDENT * self.depth,
)
)
return "\n".join(act_list)
def queue_act(self, bolb):
act_list = []
for value in self.conditions:
cond, acts = value
cond = cond.condition
if len(acts) == 0:
continue
act_list = [a.queue_act(cond, depth_mod=-1) for a in acts]
return "\n".join(act_list)
class Acl_Queue(Acl_Control):
def do(self):
for cond, acts in self.conditions:
if len(Acl_Control.AQU) == 0 and cond.eval():
for a in acts:
if isinstance(a, Acl_Action):
Acl_Control.AQU.append((a._act, None))
elif a._act_cond:
Acl_Control.AQU.append(a._act_cond)
return False
def acl_build(acl):
root = Acl_Control("True")
node_stack = [root]
real_lines = []
for line in acl.split("\n"):
line = line.strip().replace("`", "")
if len(line) > 0 and line[0] != "#":
if ";" in line:
for s in line.split(";"):
s = s.strip().replace("`", "")
if len(s) > 0 and s[0] != "#":
real_lines.append(s)
else:
real_lines.append(line)
for line in real_lines:
upper = line.upper()
if upper.startswith("IF "):
node = Acl_Control(line[3:])
node_stack[-1].add_action(node)
node_stack.append(node)
elif upper.startswith("QUEUE"):
cond = "True" if upper == "QUEUE" else line[6:]
node = Acl_Queue(cond)
node_stack[-1].add_action(node)
node_stack.append(node)
elif upper.startswith("ELIF "):
node_stack[-1].add_condition(line[5:])
elif upper.startswith("ELSE"):
node_stack[-1].add_condition("True")
elif upper.startswith("END"):
node_stack.pop()
else:
parts = [l.strip() for l in line.split(",")]
if len(parts) == 1 or len(parts[1]) == 0:
action = parts[0]
node = Acl_Action(action)
node_stack[-1].add_action(node)
else:
action = parts[0]
condition = parts[1]
node = Acl_Control(condition)
node_stack[-1].add_action(node)
node.add_action(Acl_Action(action))
return root
def acl_str(root):
acl_base = """
def do_act_list(self, e):
this = self
pin, dname, dstat, didx = e.pin, e.dname, e.dstat, e.didx
prev = self.action.getprev()
seq = didx if dname[0] == 'x' else 0 if dstat == -2 else -1
cancel = pin =='x' or pin == 'fs'
x = didx if pin =='x' else 0
fsc = pin =='fs'
s = int(pin[1]) if (pin[0] == 's' and pin[1] in ('1', '2', '3')) or pin[-2:] == '-x' else 0
sp = dname if pin == 'sp' else 0
prep = pin == 'prep'
sim_duration = self.duration
{act_prep_block}
if len(Acl_Control.AQU) > 0:
next_act, next_cond = Acl_Control.AQU[0]
if eval(next_cond) and next_act():
Acl_Control.AQU.pop(0)
return 'queue'
{act_cond_block}
return 0"""
acl_string = acl_base.format(
act_prep_block=root.prepare(), act_cond_block=root.act()
)
return acl_string
|
import sys
from core.timeline import now, Timeline
import re
do_act = None
def acl_func_str(acl):
global do_act
s = acl_str(acl_build(acl))
exec(s, globals())
# return do_act_list, s
do_act = do_act_list
return s, do_act_list
class Acl_Action:
INDENT = " "
PREP = """ try:
{act} = self.{act}
except Exception:
raise AttributeError('{act} is not an action')"""
ACT = """{indent}if {act}({args}):
{indent} return '{act}'"""
NONE = "{indent}return 0"
QUEUE_ACT = """{indent}Acl_Control.AQU.append(({act}, compile('{cond}', '<string>', 'eval')))"""
dragon_act = re.compile(r'dragon(form)?.act\(["\']([A-Za-z \*\+\d]+)["\']\)')
def __init__(self, action):
self._act = None
self.args = None
if action.startswith("dragon"):
self.action = "dragonform"
res = self.dragon_act.match(action)
if res:
self.args = res.group(2)
else:
self.action = action
self.depth = 0
def __repr__(self):
return self.action
def prep(self, adv):
if self.action == "dragonform" and self.args is not None:
self._act = lambda: adv.dragonform.act(self.args)
else:
self._act = lambda: getattr(adv, self.action)()
def do(self):
return self._act()
def prepare(self):
if self.action is None:
return False
return self.PREP.format(act=self.action)
def act(self):
if self.action is None:
return self.NONE.format(indent=self.INDENT * self.depth)
return self.ACT.format(
act=self.action, args=self.args or "", indent=self.INDENT * self.depth
)
def queue_act(self, cond, depth_mod=0):
if self.action is None:
raise ValueError("No actions queued")
return self.QUEUE_ACT.format(
act=self.action,
args=self.arguments,
cond=cond,
indent=self.INDENT * (self.depth + depth_mod),
)
class Acl_Condition:
banned = re.compile(
r"(exec|eval|compile|setattr|delattr|memoryview|property|globals|locals|open|print|__[a-zA-Z]+__).*"
)
banned_repl = "True"
assignment = re.compile(r"([^=><!])=([^=])")
assignment_repl = lambda s: s[1] + "==" + s[2]
@staticmethod
def sanitize_qwe_and_his_chunch_legs(condition):
condition = Acl_Condition.banned.sub(Acl_Condition.banned_repl, condition)
condition = Acl_Condition.assignment.sub(
Acl_Condition.assignment_repl, condition
)
return condition
def __init__(self, condition):
self.condition = Acl_Condition.sanitize_qwe_and_his_chunch_legs(condition)
# self.condition = condition
def prep(self):
self._cond = compile(self.condition, "<string>", "eval")
def eval(self):
return self.condition is None or eval(self.condition, Acl_Control.CTX)
class Acl_Control:
INDENT = " "
IF = """{indent}if {cond}:
{block}"""
ELIF = """{indent}elif {cond}:
{block}"""
ELSE = """{indent}else:
{block}"""
QUEUE = """{indent}if len(Acl_Control.AQU)==0 and {cond}:
{block}"""
AQU = []
CTX = None
def __init__(self, condition, depth=0):
self.conditions = [(Acl_Condition(condition), [])]
self._act_cond = None
self.depth = depth
def add_action(self, action):
action.depth = self.depth + 1
self.conditions[-1][-1].append(action)
def add_condition(self, condition, is_else=False):
self.conditions.append((Acl_Condition(condition), []))
def __repr__(self):
return "\n".join(f"\n<{cond}> {acts}" for cond, acts in self.conditions)
def prep(self, adv):
Acl_Control.AQU = []
for cond, acts in self.conditions:
cond.prep()
for a in acts:
a.prep(adv)
if len(self.conditions) == 1:
cond, acts = self.conditions[0]
if len(acts) == 1 and isinstance(acts[0], Acl_Action):
self._act_cond = acts[0], cond
def do(self):
for cond, acts in self.conditions:
if cond.eval():
for a in acts:
if a.do():
return True
break
return False
@staticmethod
def set_ctx(self, e):
this = self
pin, dname, dstat, didx = e.pin, e.dname, e.dstat, e.didx
prev = self.action.getprev()
seq = didx if dname[0] == "x" else 0 if dstat == -2 else -1
cancel = pin == "x" or pin == "fs"
x = didx if pin == "x" else 0
fsc = pin == "fs"
s = (
int(pin[1])
if (pin[0] == "s" and pin[1].isdigit()) or pin[-2:] == "-x"
else 0
)
sp = dname if pin == "sp" else 0
prep = pin == "prep"
sim_duration = self.duration
Acl_Control.CTX = locals()
def __call__(self, adv, e):
Acl_Control.set_ctx(adv, e)
if len(Acl_Control.AQU) > 0:
next_act, next_cond = Acl_Control.AQU[0]
if next_cond.eval() and next_act.do():
return Acl_Control.AQU.pop(0)
self.do()
def prepare(self):
prep_list = []
for _, acts in self.conditions:
prep_list.extend([a.prepare() for a in acts if a.prepare()])
return "\n".join(prep_list)
def act(self):
act_list = []
for idx, value in enumerate(self.conditions):
cond, acts = value
cond = cond.condition
if len(acts) == 0:
continue
if cond.startswith("QUEUE"):
cond = "True" if len(cond) < 6 else cond[6:]
pattern = self.QUEUE
block = [a.queue_act("True") for a in acts]
block.append(
"{indent} return 'queued'".format(
indent=self.INDENT * self.depth
)
)
else:
if idx == 0:
pattern = self.IF
elif cond != "ELSE":
pattern = self.ELIF
else:
pattern = self.ELSE
block = [a.act() for a in acts]
if self.depth == 0:
act_list = block
else:
act_list.append(
pattern.format(
cond=cond,
block="\n".join(block),
indent=self.INDENT * self.depth,
)
)
return "\n".join(act_list)
def queue_act(self, bolb):
act_list = []
for value in self.conditions:
cond, acts = value
cond = cond.condition
if len(acts) == 0:
continue
act_list = [a.queue_act(cond, depth_mod=-1) for a in acts]
return "\n".join(act_list)
class Acl_Queue(Acl_Control):
def do(self):
for cond, acts in self.conditions:
if len(Acl_Control.AQU) == 0 and cond.eval():
for a in acts:
if isinstance(a, Acl_Action):
Acl_Control.AQU.append((a._act, None))
elif a._act_cond:
Acl_Control.AQU.append(a._act_cond)
return False
def acl_build(acl):
root = Acl_Control("True")
node_stack = [root]
real_lines = []
for line in acl.split("\n"):
line = line.strip().replace("`", "")
if len(line) > 0 and line[0] != "#":
if ";" in line:
for s in line.split(";"):
s = s.strip().replace("`", "")
if len(s) > 0 and s[0] != "#":
real_lines.append(s)
else:
real_lines.append(line)
for line in real_lines:
upper = line.upper()
if upper.startswith("IF "):
node = Acl_Control(line[3:])
node_stack[-1].add_action(node)
node_stack.append(node)
elif upper.startswith("QUEUE"):
cond = "True" if upper == "QUEUE" else line[6:]
node = Acl_Queue(cond)
node_stack[-1].add_action(node)
node_stack.append(node)
elif upper.startswith("ELIF "):
node_stack[-1].add_condition(line[5:])
elif upper.startswith("ELSE"):
node_stack[-1].add_condition("True")
elif upper.startswith("END"):
node_stack.pop()
else:
parts = [l.strip() for l in line.split(",")]
if len(parts) == 1 or len(parts[1]) == 0:
action = parts[0]
node = Acl_Action(action)
node_stack[-1].add_action(node)
else:
action = parts[0]
condition = parts[1]
node = Acl_Control(condition)
node_stack[-1].add_action(node)
node.add_action(Acl_Action(action))
return root
def acl_str(root):
acl_base = """
def do_act_list(self, e):
this = self
pin, dname, dstat, didx = e.pin, e.dname, e.dstat, e.didx
prev = self.action.getprev()
seq = didx if dname[0] == 'x' else 0 if dstat == -2 else -1
cancel = pin =='x' or pin == 'fs'
x = didx if pin =='x' else 0
fsc = pin =='fs'
s = int(pin[1]) if (pin[0] == 's' and pin[1] in ('1', '2', '3')) or pin[-2:] == '-x' else 0
sp = dname if pin == 'sp' else 0
prep = pin == 'prep'
sim_duration = self.duration
{act_prep_block}
if len(Acl_Control.AQU) > 0:
next_act, next_cond = Acl_Control.AQU[0]
if eval(next_cond) and next_act():
Acl_Control.AQU.pop(0)
return 'queue'
{act_cond_block}
return 0"""
acl_string = acl_base.format(
act_prep_block=root.prepare(), act_cond_block=root.act()
)
return acl_string
|
en
| 0.340939
|
# return do_act_list, s try: {act} = self.{act} except Exception: raise AttributeError('{act} is not an action') {indent}if {act}({args}): {indent} return '{act}' {indent}Acl_Control.AQU.append(({act}, compile('{cond}', '<string>', 'eval'))) # self.condition = condition {indent}if {cond}: {block} {indent}elif {cond}: {block} {indent}else: {block} {indent}if len(Acl_Control.AQU)==0 and {cond}: {block} def do_act_list(self, e): this = self pin, dname, dstat, didx = e.pin, e.dname, e.dstat, e.didx prev = self.action.getprev() seq = didx if dname[0] == 'x' else 0 if dstat == -2 else -1 cancel = pin =='x' or pin == 'fs' x = didx if pin =='x' else 0 fsc = pin =='fs' s = int(pin[1]) if (pin[0] == 's' and pin[1] in ('1', '2', '3')) or pin[-2:] == '-x' else 0 sp = dname if pin == 'sp' else 0 prep = pin == 'prep' sim_duration = self.duration {act_prep_block} if len(Acl_Control.AQU) > 0: next_act, next_cond = Acl_Control.AQU[0] if eval(next_cond) and next_act(): Acl_Control.AQU.pop(0) return 'queue' {act_cond_block} return 0
| 2.915019
| 3
|
pimgen.py
|
rfrandse/phosphor-inventory-manager
| 0
|
6625827
|
#!/usr/bin/env python
'''Phosphor Inventory Manager YAML parser and code generator.
The parser workflow is broken down as follows:
1 - Import YAML files as native python type(s) instance(s).
2 - Create an instance of the Everything class from the
native python type instance(s) with the Everything.load
method.
3 - The Everything class constructor orchestrates conversion of the
native python type(s) instances(s) to render helper types.
Each render helper type constructor imports its attributes
from the native python type(s) instances(s).
4 - Present the converted YAML to the command processing method
requested by the script user.
'''
import sys
import os
import argparse
import subprocess
import yaml
import mako.lookup
import sdbusplus.property
from sdbusplus.namedelement import NamedElement
from sdbusplus.renderer import Renderer
# Global busname for use within classes where necessary
busname = "xyz.openbmc_project.Inventory.Manager"
def cppTypeName(yaml_type):
''' Convert yaml types to cpp types.'''
return sdbusplus.property.Property(type=yaml_type).cppTypeName
class InterfaceComposite(object):
'''Compose interface properties.'''
def __init__(self, dict):
self.dict = dict
def properties(self, interface):
return self.dict[interface]
def interfaces(self):
return self.dict.keys()
def names(self, interface):
names = []
if self.dict[interface]:
names = [x["name"] for x in self.dict[interface]]
return names
class Interface(list):
'''Provide various interface transformations.'''
def __init__(self, iface):
super(Interface, self).__init__(iface.split('.'))
def namespace(self):
'''Represent as an sdbusplus namespace.'''
return '::'.join(['sdbusplus'] + self[:-1] + ['server', self[-1]])
def header(self):
'''Represent as an sdbusplus server binding header.'''
return os.sep.join(self + ['server.hpp'])
def __str__(self):
return '.'.join(self)
class Indent(object):
'''Help templates be depth agnostic.'''
def __init__(self, depth=0):
self.depth = depth
def __add__(self, depth):
return Indent(self.depth + depth)
def __call__(self, depth):
'''Render an indent at the current depth plus depth.'''
return 4*' '*(depth + self.depth)
class Template(NamedElement):
'''Associate a template name with its namespace.'''
def __init__(self, **kw):
self.namespace = kw.pop('namespace', [])
super(Template, self).__init__(**kw)
def qualified(self):
return '::'.join(self.namespace + [self.name])
class FixBool(object):
'''Un-capitalize booleans.'''
def __call__(self, arg):
return '{0}'.format(arg.lower())
class Quote(object):
'''Decorate an argument by quoting it.'''
def __call__(self, arg):
return '"{0}"'.format(arg)
class Cast(object):
'''Decorate an argument by casting it.'''
def __init__(self, cast, target):
'''cast is the cast type (static, const, etc...).
target is the cast target type.'''
self.cast = cast
self.target = target
def __call__(self, arg):
return '{0}_cast<{1}>({2})'.format(self.cast, self.target, arg)
class Literal(object):
'''Decorate an argument with a literal operator.'''
integer_types = [
'int8',
'int16',
'int32',
'int64',
'uint8',
'uint16',
'uint32',
'uint64'
]
def __init__(self, type):
self.type = type
def __call__(self, arg):
if 'uint' in self.type:
arg = '{0}ull'.format(arg)
elif 'int' in self.type:
arg = '{0}ll'.format(arg)
if self.type in self.integer_types:
return Cast('static', '{0}_t'.format(self.type))(arg)
if self.type == 'string':
return '{0}s'.format(arg)
return arg
class Argument(NamedElement, Renderer):
'''Define argument type inteface.'''
def __init__(self, **kw):
self.type = kw.pop('type', None)
super(Argument, self).__init__(**kw)
def argument(self, loader, indent):
raise NotImplementedError
class TrivialArgument(Argument):
'''Non-array type arguments.'''
def __init__(self, **kw):
self.value = kw.pop('value')
self.decorators = kw.pop('decorators', [])
if kw.get('type', None) == 'string':
self.decorators.insert(0, Quote())
if kw.get('type', None) == 'boolean':
self.decorators.insert(0, FixBool())
super(TrivialArgument, self).__init__(**kw)
def argument(self, loader, indent):
a = str(self.value)
for d in self.decorators:
a = d(a)
return a
class InitializerList(Argument):
'''Initializer list arguments.'''
def __init__(self, **kw):
self.values = kw.pop('values')
super(InitializerList, self).__init__(**kw)
def argument(self, loader, indent):
return self.render(
loader,
'argument.mako.cpp',
arg=self,
indent=indent)
class DbusSignature(Argument):
'''DBus signature arguments.'''
def __init__(self, **kw):
self.sig = {x: y for x, y in kw.iteritems()}
kw.clear()
super(DbusSignature, self).__init__(**kw)
def argument(self, loader, indent):
return self.render(
loader,
'signature.mako.cpp',
signature=self,
indent=indent)
class MethodCall(Argument):
'''Render syntatically correct c++ method calls.'''
def __init__(self, **kw):
self.namespace = kw.pop('namespace', [])
self.templates = kw.pop('templates', [])
self.args = kw.pop('args', [])
super(MethodCall, self).__init__(**kw)
def call(self, loader, indent):
return self.render(
loader,
'method.mako.cpp',
method=self,
indent=indent)
def argument(self, loader, indent):
return self.call(loader, indent)
class Vector(MethodCall):
'''Convenience type for vectors.'''
def __init__(self, **kw):
kw['name'] = 'vector'
kw['namespace'] = ['std']
kw['args'] = [InitializerList(values=kw.pop('args'))]
super(Vector, self).__init__(**kw)
class Filter(MethodCall):
'''Convenience type for filters'''
def __init__(self, **kw):
kw['name'] = 'make_filter'
super(Filter, self).__init__(**kw)
class Action(MethodCall):
'''Convenience type for actions'''
def __init__(self, **kw):
kw['name'] = 'make_action'
super(Action, self).__init__(**kw)
class PathCondition(MethodCall):
'''Convenience type for path conditions'''
def __init__(self, **kw):
kw['name'] = 'make_path_condition'
super(PathCondition, self).__init__(**kw)
class GetProperty(MethodCall):
'''Convenience type for getting inventory properties'''
def __init__(self, **kw):
kw['name'] = 'make_get_property'
super(GetProperty, self).__init__(**kw)
class CreateObjects(MethodCall):
'''Assemble a createObjects functor.'''
def __init__(self, **kw):
objs = []
for path, interfaces in kw.pop('objs').iteritems():
key_o = TrivialArgument(
value=path,
type='string',
decorators=[Literal('string')])
value_i = []
for interface, properties, in interfaces.iteritems():
key_i = TrivialArgument(value=interface, type='string')
value_p = []
if properties:
for prop, value in properties.iteritems():
key_p = TrivialArgument(value=prop, type='string')
value_v = TrivialArgument(
decorators=[Literal(value.get('type', None))],
**value)
value_p.append(InitializerList(values=[key_p, value_v]))
value_p = InitializerList(values=value_p)
value_i.append(InitializerList(values=[key_i, value_p]))
value_i = InitializerList(values=value_i)
objs.append(InitializerList(values=[key_o, value_i]))
kw['args'] = [InitializerList(values=objs)]
kw['namespace'] = ['functor']
super(CreateObjects, self).__init__(**kw)
class DestroyObjects(MethodCall):
'''Assemble a destroyObject functor.'''
def __init__(self, **kw):
values = [{'value': x, 'type': 'string'} for x in kw.pop('paths')]
conditions = [
Event.functor_map[
x['name']](**x) for x in kw.pop('conditions', [])]
conditions = [PathCondition(args=[x]) for x in conditions]
args = [InitializerList(
values=[TrivialArgument(**x) for x in values])]
args.append(InitializerList(values=conditions))
kw['args'] = args
kw['namespace'] = ['functor']
super(DestroyObjects, self).__init__(**kw)
class SetProperty(MethodCall):
'''Assemble a setProperty functor.'''
def __init__(self, **kw):
args = []
value = kw.pop('value')
prop = kw.pop('property')
iface = kw.pop('interface')
iface = Interface(iface)
namespace = iface.namespace().split('::')[:-1]
name = iface[-1]
t = Template(namespace=namespace, name=iface[-1])
member = '&%s' % '::'.join(
namespace + [name, NamedElement(name=prop).camelCase])
member_type = cppTypeName(value['type'])
member_cast = '{0} ({1}::*)({0})'.format(member_type, t.qualified())
paths = [{'value': x, 'type': 'string'} for x in kw.pop('paths')]
args.append(InitializerList(
values=[TrivialArgument(**x) for x in paths]))
conditions = [
Event.functor_map[
x['name']](**x) for x in kw.pop('conditions', [])]
conditions = [PathCondition(args=[x]) for x in conditions]
args.append(InitializerList(values=conditions))
args.append(TrivialArgument(value=str(iface), type='string'))
args.append(TrivialArgument(
value=member, decorators=[Cast('static', member_cast)]))
args.append(TrivialArgument(**value))
kw['templates'] = [Template(name=name, namespace=namespace)]
kw['args'] = args
kw['namespace'] = ['functor']
super(SetProperty, self).__init__(**kw)
class PropertyChanged(MethodCall):
'''Assemble a propertyChanged functor.'''
def __init__(self, **kw):
args = []
args.append(TrivialArgument(value=kw.pop('interface'), type='string'))
args.append(TrivialArgument(value=kw.pop('property'), type='string'))
args.append(TrivialArgument(
decorators=[
Literal(kw['value'].get('type', None))], **kw.pop('value')))
kw['args'] = args
kw['namespace'] = ['functor']
super(PropertyChanged, self).__init__(**kw)
class PropertyIs(MethodCall):
'''Assemble a propertyIs functor.'''
def __init__(self, **kw):
args = []
path = kw.pop('path', None)
if not path:
path = TrivialArgument(value='nullptr')
else:
path = TrivialArgument(value=path, type='string')
args.append(path)
iface = TrivialArgument(value=kw.pop('interface'), type='string')
args.append(iface)
prop = TrivialArgument(value=kw.pop('property'), type='string')
args.append(prop)
args.append(TrivialArgument(
decorators=[
Literal(kw['value'].get('type', None))], **kw.pop('value')))
service = kw.pop('service', None)
if service:
args.append(TrivialArgument(value=service, type='string'))
dbusMember = kw.pop('dbusMember', None)
if dbusMember:
# Inventory manager's service name is required
if not service or service != busname:
args.append(TrivialArgument(value=busname, type='string'))
gpArgs = []
gpArgs.append(path)
gpArgs.append(iface)
# Prepend '&' and append 'getPropertyByName' function on dbusMember
gpArgs.append(TrivialArgument(
value='&'+dbusMember+'::getPropertyByName'))
gpArgs.append(prop)
fArg = MethodCall(
name='getProperty',
namespace=['functor'],
templates=[Template(
name=dbusMember,
namespace=[])],
args=gpArgs)
# Append getProperty functor
args.append(GetProperty(
templates=[Template(
name=dbusMember+'::PropertiesVariant',
namespace=[])],
args=[fArg]))
kw['args'] = args
kw['namespace'] = ['functor']
super(PropertyIs, self).__init__(**kw)
class Event(MethodCall):
'''Assemble an inventory manager event.'''
functor_map = {
'destroyObjects': DestroyObjects,
'createObjects': CreateObjects,
'propertyChangedTo': PropertyChanged,
'propertyIs': PropertyIs,
'setProperty': SetProperty,
}
def __init__(self, **kw):
self.summary = kw.pop('name')
filters = [
self.functor_map[x['name']](**x) for x in kw.pop('filters', [])]
filters = [Filter(args=[x]) for x in filters]
filters = Vector(
templates=[Template(name='Filter', namespace=[])],
args=filters)
event = MethodCall(
name='make_shared',
namespace=['std'],
templates=[Template(
name=kw.pop('event'),
namespace=kw.pop('event_namespace', []))],
args=kw.pop('event_args', []) + [filters])
events = Vector(
templates=[Template(name='EventBasePtr', namespace=[])],
args=[event])
action_type = Template(name='Action', namespace=[])
action_args = [
self.functor_map[x['name']](**x) for x in kw.pop('actions', [])]
action_args = [Action(args=[x]) for x in action_args]
actions = Vector(
templates=[action_type],
args=action_args)
kw['name'] = 'make_tuple'
kw['namespace'] = ['std']
kw['args'] = [events, actions]
super(Event, self).__init__(**kw)
class MatchEvent(Event):
'''Associate one or more dbus signal match signatures with
a filter.'''
def __init__(self, **kw):
kw['event'] = 'DbusSignal'
kw['event_namespace'] = []
kw['event_args'] = [
DbusSignature(**x) for x in kw.pop('signatures', [])]
super(MatchEvent, self).__init__(**kw)
class StartupEvent(Event):
'''Assemble a startup event.'''
def __init__(self, **kw):
kw['event'] = 'StartupEvent'
kw['event_namespace'] = []
super(StartupEvent, self).__init__(**kw)
class Everything(Renderer):
'''Parse/render entry point.'''
class_map = {
'match': MatchEvent,
'startup': StartupEvent,
}
@staticmethod
def load(args):
# Aggregate all the event YAML in the events.d directory
# into a single list of events.
events = []
events_dir = os.path.join(args.inputdir, 'events.d')
if os.path.exists(events_dir):
yaml_files = filter(
lambda x: x.endswith('.yaml'),
os.listdir(events_dir))
for x in yaml_files:
with open(os.path.join(events_dir, x), 'r') as fd:
for e in yaml.safe_load(fd.read()).get('events', {}):
events.append(e)
interfaces, interface_composite = Everything.get_interfaces(
args.ifacesdir)
extra_interfaces, extra_interface_composite = \
Everything.get_interfaces(
os.path.join(args.inputdir, 'extra_interfaces.d'))
interface_composite.update(extra_interface_composite)
interface_composite = InterfaceComposite(interface_composite)
# Update busname if configured differenly than the default
busname = args.busname
return Everything(
*events,
interfaces=interfaces + extra_interfaces,
interface_composite=interface_composite)
@staticmethod
def get_interfaces(targetdir):
'''Scan the interfaces directory for interfaces that PIM can create.'''
yaml_files = []
interfaces = []
interface_composite = {}
if targetdir and os.path.exists(targetdir):
for directory, _, files in os.walk(targetdir):
if not files:
continue
yaml_files += map(
lambda f: os.path.relpath(
os.path.join(directory, f),
targetdir),
filter(lambda f: f.endswith('.interface.yaml'), files))
for y in yaml_files:
# parse only phosphor dbus related interface files
if not y.startswith('xyz'):
continue
with open(os.path.join(targetdir, y)) as fd:
i = y.replace('.interface.yaml', '').replace(os.sep, '.')
# PIM can't create interfaces with methods.
parsed = yaml.safe_load(fd.read())
if parsed.get('methods', None):
continue
# Cereal can't understand the type sdbusplus::object_path. This
# type is a wrapper around std::string. Ignore interfaces having
# a property of this type for now. The only interface that has a
# property of this type now is xyz.openbmc_project.Association,
# which is an unused interface. No inventory objects implement
# this interface.
# TODO via openbmc/openbmc#2123 : figure out how to make Cereal
# understand sdbusplus::object_path.
properties = parsed.get('properties', None)
if properties:
if any('path' in p['type'] for p in properties):
continue
interface_composite[i] = properties
interfaces.append(i)
return interfaces, interface_composite
def __init__(self, *a, **kw):
self.interfaces = \
[Interface(x) for x in kw.pop('interfaces', [])]
self.interface_composite = \
kw.pop('interface_composite', {})
self.events = [
self.class_map[x['type']](**x) for x in a]
super(Everything, self).__init__(**kw)
def generate_cpp(self, loader):
'''Render the template with the provided events and interfaces.'''
with open(os.path.join(
args.outputdir,
'generated.cpp'), 'w') as fd:
fd.write(
self.render(
loader,
'generated.mako.cpp',
events=self.events,
interfaces=self.interfaces,
indent=Indent()))
def generate_serialization(self, loader):
with open(os.path.join(
args.outputdir,
'gen_serialization.hpp'), 'w') as fd:
fd.write(
self.render(
loader,
'gen_serialization.mako.hpp',
interfaces=self.interfaces,
interface_composite=self.interface_composite))
if __name__ == '__main__':
script_dir = os.path.dirname(os.path.realpath(__file__))
valid_commands = {
'generate-cpp': 'generate_cpp',
'generate-serialization': 'generate_serialization',
}
parser = argparse.ArgumentParser(
description='Phosphor Inventory Manager (PIM) YAML '
'scanner and code generator.')
parser.add_argument(
'-o', '--output-dir', dest='outputdir',
default='.', help='Output directory.')
parser.add_argument(
'-i', '--interfaces-dir', dest='ifacesdir',
help='Location of interfaces to be supported.')
parser.add_argument(
'-d', '--dir', dest='inputdir',
default=os.path.join(script_dir, 'example'),
help='Location of files to process.')
parser.add_argument(
'-b', '--bus-name', dest='busname',
default='xyz.openbmc_project.Inventory.Manager',
help='Inventory manager busname.')
parser.add_argument(
'command', metavar='COMMAND', type=str,
choices=valid_commands.keys(),
help='%s.' % " | ".join(valid_commands.keys()))
args = parser.parse_args()
if sys.version_info < (3, 0):
lookup = mako.lookup.TemplateLookup(
directories=[script_dir],
disable_unicode=True)
else:
lookup = mako.lookup.TemplateLookup(
directories=[script_dir])
function = getattr(
Everything.load(args),
valid_commands[args.command])
function(lookup)
# vim: tabstop=8 expandtab shiftwidth=4 softtabstop=4
|
#!/usr/bin/env python
'''Phosphor Inventory Manager YAML parser and code generator.
The parser workflow is broken down as follows:
1 - Import YAML files as native python type(s) instance(s).
2 - Create an instance of the Everything class from the
native python type instance(s) with the Everything.load
method.
3 - The Everything class constructor orchestrates conversion of the
native python type(s) instances(s) to render helper types.
Each render helper type constructor imports its attributes
from the native python type(s) instances(s).
4 - Present the converted YAML to the command processing method
requested by the script user.
'''
import sys
import os
import argparse
import subprocess
import yaml
import mako.lookup
import sdbusplus.property
from sdbusplus.namedelement import NamedElement
from sdbusplus.renderer import Renderer
# Global busname for use within classes where necessary
busname = "xyz.openbmc_project.Inventory.Manager"
def cppTypeName(yaml_type):
''' Convert yaml types to cpp types.'''
return sdbusplus.property.Property(type=yaml_type).cppTypeName
class InterfaceComposite(object):
'''Compose interface properties.'''
def __init__(self, dict):
self.dict = dict
def properties(self, interface):
return self.dict[interface]
def interfaces(self):
return self.dict.keys()
def names(self, interface):
names = []
if self.dict[interface]:
names = [x["name"] for x in self.dict[interface]]
return names
class Interface(list):
'''Provide various interface transformations.'''
def __init__(self, iface):
super(Interface, self).__init__(iface.split('.'))
def namespace(self):
'''Represent as an sdbusplus namespace.'''
return '::'.join(['sdbusplus'] + self[:-1] + ['server', self[-1]])
def header(self):
'''Represent as an sdbusplus server binding header.'''
return os.sep.join(self + ['server.hpp'])
def __str__(self):
return '.'.join(self)
class Indent(object):
'''Help templates be depth agnostic.'''
def __init__(self, depth=0):
self.depth = depth
def __add__(self, depth):
return Indent(self.depth + depth)
def __call__(self, depth):
'''Render an indent at the current depth plus depth.'''
return 4*' '*(depth + self.depth)
class Template(NamedElement):
'''Associate a template name with its namespace.'''
def __init__(self, **kw):
self.namespace = kw.pop('namespace', [])
super(Template, self).__init__(**kw)
def qualified(self):
return '::'.join(self.namespace + [self.name])
class FixBool(object):
'''Un-capitalize booleans.'''
def __call__(self, arg):
return '{0}'.format(arg.lower())
class Quote(object):
'''Decorate an argument by quoting it.'''
def __call__(self, arg):
return '"{0}"'.format(arg)
class Cast(object):
'''Decorate an argument by casting it.'''
def __init__(self, cast, target):
'''cast is the cast type (static, const, etc...).
target is the cast target type.'''
self.cast = cast
self.target = target
def __call__(self, arg):
return '{0}_cast<{1}>({2})'.format(self.cast, self.target, arg)
class Literal(object):
'''Decorate an argument with a literal operator.'''
integer_types = [
'int8',
'int16',
'int32',
'int64',
'uint8',
'uint16',
'uint32',
'uint64'
]
def __init__(self, type):
self.type = type
def __call__(self, arg):
if 'uint' in self.type:
arg = '{0}ull'.format(arg)
elif 'int' in self.type:
arg = '{0}ll'.format(arg)
if self.type in self.integer_types:
return Cast('static', '{0}_t'.format(self.type))(arg)
if self.type == 'string':
return '{0}s'.format(arg)
return arg
class Argument(NamedElement, Renderer):
'''Define argument type inteface.'''
def __init__(self, **kw):
self.type = kw.pop('type', None)
super(Argument, self).__init__(**kw)
def argument(self, loader, indent):
raise NotImplementedError
class TrivialArgument(Argument):
'''Non-array type arguments.'''
def __init__(self, **kw):
self.value = kw.pop('value')
self.decorators = kw.pop('decorators', [])
if kw.get('type', None) == 'string':
self.decorators.insert(0, Quote())
if kw.get('type', None) == 'boolean':
self.decorators.insert(0, FixBool())
super(TrivialArgument, self).__init__(**kw)
def argument(self, loader, indent):
a = str(self.value)
for d in self.decorators:
a = d(a)
return a
class InitializerList(Argument):
'''Initializer list arguments.'''
def __init__(self, **kw):
self.values = kw.pop('values')
super(InitializerList, self).__init__(**kw)
def argument(self, loader, indent):
return self.render(
loader,
'argument.mako.cpp',
arg=self,
indent=indent)
class DbusSignature(Argument):
'''DBus signature arguments.'''
def __init__(self, **kw):
self.sig = {x: y for x, y in kw.iteritems()}
kw.clear()
super(DbusSignature, self).__init__(**kw)
def argument(self, loader, indent):
return self.render(
loader,
'signature.mako.cpp',
signature=self,
indent=indent)
class MethodCall(Argument):
'''Render syntatically correct c++ method calls.'''
def __init__(self, **kw):
self.namespace = kw.pop('namespace', [])
self.templates = kw.pop('templates', [])
self.args = kw.pop('args', [])
super(MethodCall, self).__init__(**kw)
def call(self, loader, indent):
return self.render(
loader,
'method.mako.cpp',
method=self,
indent=indent)
def argument(self, loader, indent):
return self.call(loader, indent)
class Vector(MethodCall):
'''Convenience type for vectors.'''
def __init__(self, **kw):
kw['name'] = 'vector'
kw['namespace'] = ['std']
kw['args'] = [InitializerList(values=kw.pop('args'))]
super(Vector, self).__init__(**kw)
class Filter(MethodCall):
'''Convenience type for filters'''
def __init__(self, **kw):
kw['name'] = 'make_filter'
super(Filter, self).__init__(**kw)
class Action(MethodCall):
'''Convenience type for actions'''
def __init__(self, **kw):
kw['name'] = 'make_action'
super(Action, self).__init__(**kw)
class PathCondition(MethodCall):
'''Convenience type for path conditions'''
def __init__(self, **kw):
kw['name'] = 'make_path_condition'
super(PathCondition, self).__init__(**kw)
class GetProperty(MethodCall):
'''Convenience type for getting inventory properties'''
def __init__(self, **kw):
kw['name'] = 'make_get_property'
super(GetProperty, self).__init__(**kw)
class CreateObjects(MethodCall):
'''Assemble a createObjects functor.'''
def __init__(self, **kw):
objs = []
for path, interfaces in kw.pop('objs').iteritems():
key_o = TrivialArgument(
value=path,
type='string',
decorators=[Literal('string')])
value_i = []
for interface, properties, in interfaces.iteritems():
key_i = TrivialArgument(value=interface, type='string')
value_p = []
if properties:
for prop, value in properties.iteritems():
key_p = TrivialArgument(value=prop, type='string')
value_v = TrivialArgument(
decorators=[Literal(value.get('type', None))],
**value)
value_p.append(InitializerList(values=[key_p, value_v]))
value_p = InitializerList(values=value_p)
value_i.append(InitializerList(values=[key_i, value_p]))
value_i = InitializerList(values=value_i)
objs.append(InitializerList(values=[key_o, value_i]))
kw['args'] = [InitializerList(values=objs)]
kw['namespace'] = ['functor']
super(CreateObjects, self).__init__(**kw)
class DestroyObjects(MethodCall):
'''Assemble a destroyObject functor.'''
def __init__(self, **kw):
values = [{'value': x, 'type': 'string'} for x in kw.pop('paths')]
conditions = [
Event.functor_map[
x['name']](**x) for x in kw.pop('conditions', [])]
conditions = [PathCondition(args=[x]) for x in conditions]
args = [InitializerList(
values=[TrivialArgument(**x) for x in values])]
args.append(InitializerList(values=conditions))
kw['args'] = args
kw['namespace'] = ['functor']
super(DestroyObjects, self).__init__(**kw)
class SetProperty(MethodCall):
'''Assemble a setProperty functor.'''
def __init__(self, **kw):
args = []
value = kw.pop('value')
prop = kw.pop('property')
iface = kw.pop('interface')
iface = Interface(iface)
namespace = iface.namespace().split('::')[:-1]
name = iface[-1]
t = Template(namespace=namespace, name=iface[-1])
member = '&%s' % '::'.join(
namespace + [name, NamedElement(name=prop).camelCase])
member_type = cppTypeName(value['type'])
member_cast = '{0} ({1}::*)({0})'.format(member_type, t.qualified())
paths = [{'value': x, 'type': 'string'} for x in kw.pop('paths')]
args.append(InitializerList(
values=[TrivialArgument(**x) for x in paths]))
conditions = [
Event.functor_map[
x['name']](**x) for x in kw.pop('conditions', [])]
conditions = [PathCondition(args=[x]) for x in conditions]
args.append(InitializerList(values=conditions))
args.append(TrivialArgument(value=str(iface), type='string'))
args.append(TrivialArgument(
value=member, decorators=[Cast('static', member_cast)]))
args.append(TrivialArgument(**value))
kw['templates'] = [Template(name=name, namespace=namespace)]
kw['args'] = args
kw['namespace'] = ['functor']
super(SetProperty, self).__init__(**kw)
class PropertyChanged(MethodCall):
'''Assemble a propertyChanged functor.'''
def __init__(self, **kw):
args = []
args.append(TrivialArgument(value=kw.pop('interface'), type='string'))
args.append(TrivialArgument(value=kw.pop('property'), type='string'))
args.append(TrivialArgument(
decorators=[
Literal(kw['value'].get('type', None))], **kw.pop('value')))
kw['args'] = args
kw['namespace'] = ['functor']
super(PropertyChanged, self).__init__(**kw)
class PropertyIs(MethodCall):
'''Assemble a propertyIs functor.'''
def __init__(self, **kw):
args = []
path = kw.pop('path', None)
if not path:
path = TrivialArgument(value='nullptr')
else:
path = TrivialArgument(value=path, type='string')
args.append(path)
iface = TrivialArgument(value=kw.pop('interface'), type='string')
args.append(iface)
prop = TrivialArgument(value=kw.pop('property'), type='string')
args.append(prop)
args.append(TrivialArgument(
decorators=[
Literal(kw['value'].get('type', None))], **kw.pop('value')))
service = kw.pop('service', None)
if service:
args.append(TrivialArgument(value=service, type='string'))
dbusMember = kw.pop('dbusMember', None)
if dbusMember:
# Inventory manager's service name is required
if not service or service != busname:
args.append(TrivialArgument(value=busname, type='string'))
gpArgs = []
gpArgs.append(path)
gpArgs.append(iface)
# Prepend '&' and append 'getPropertyByName' function on dbusMember
gpArgs.append(TrivialArgument(
value='&'+dbusMember+'::getPropertyByName'))
gpArgs.append(prop)
fArg = MethodCall(
name='getProperty',
namespace=['functor'],
templates=[Template(
name=dbusMember,
namespace=[])],
args=gpArgs)
# Append getProperty functor
args.append(GetProperty(
templates=[Template(
name=dbusMember+'::PropertiesVariant',
namespace=[])],
args=[fArg]))
kw['args'] = args
kw['namespace'] = ['functor']
super(PropertyIs, self).__init__(**kw)
class Event(MethodCall):
'''Assemble an inventory manager event.'''
functor_map = {
'destroyObjects': DestroyObjects,
'createObjects': CreateObjects,
'propertyChangedTo': PropertyChanged,
'propertyIs': PropertyIs,
'setProperty': SetProperty,
}
def __init__(self, **kw):
self.summary = kw.pop('name')
filters = [
self.functor_map[x['name']](**x) for x in kw.pop('filters', [])]
filters = [Filter(args=[x]) for x in filters]
filters = Vector(
templates=[Template(name='Filter', namespace=[])],
args=filters)
event = MethodCall(
name='make_shared',
namespace=['std'],
templates=[Template(
name=kw.pop('event'),
namespace=kw.pop('event_namespace', []))],
args=kw.pop('event_args', []) + [filters])
events = Vector(
templates=[Template(name='EventBasePtr', namespace=[])],
args=[event])
action_type = Template(name='Action', namespace=[])
action_args = [
self.functor_map[x['name']](**x) for x in kw.pop('actions', [])]
action_args = [Action(args=[x]) for x in action_args]
actions = Vector(
templates=[action_type],
args=action_args)
kw['name'] = 'make_tuple'
kw['namespace'] = ['std']
kw['args'] = [events, actions]
super(Event, self).__init__(**kw)
class MatchEvent(Event):
'''Associate one or more dbus signal match signatures with
a filter.'''
def __init__(self, **kw):
kw['event'] = 'DbusSignal'
kw['event_namespace'] = []
kw['event_args'] = [
DbusSignature(**x) for x in kw.pop('signatures', [])]
super(MatchEvent, self).__init__(**kw)
class StartupEvent(Event):
'''Assemble a startup event.'''
def __init__(self, **kw):
kw['event'] = 'StartupEvent'
kw['event_namespace'] = []
super(StartupEvent, self).__init__(**kw)
class Everything(Renderer):
'''Parse/render entry point.'''
class_map = {
'match': MatchEvent,
'startup': StartupEvent,
}
@staticmethod
def load(args):
# Aggregate all the event YAML in the events.d directory
# into a single list of events.
events = []
events_dir = os.path.join(args.inputdir, 'events.d')
if os.path.exists(events_dir):
yaml_files = filter(
lambda x: x.endswith('.yaml'),
os.listdir(events_dir))
for x in yaml_files:
with open(os.path.join(events_dir, x), 'r') as fd:
for e in yaml.safe_load(fd.read()).get('events', {}):
events.append(e)
interfaces, interface_composite = Everything.get_interfaces(
args.ifacesdir)
extra_interfaces, extra_interface_composite = \
Everything.get_interfaces(
os.path.join(args.inputdir, 'extra_interfaces.d'))
interface_composite.update(extra_interface_composite)
interface_composite = InterfaceComposite(interface_composite)
# Update busname if configured differenly than the default
busname = args.busname
return Everything(
*events,
interfaces=interfaces + extra_interfaces,
interface_composite=interface_composite)
@staticmethod
def get_interfaces(targetdir):
'''Scan the interfaces directory for interfaces that PIM can create.'''
yaml_files = []
interfaces = []
interface_composite = {}
if targetdir and os.path.exists(targetdir):
for directory, _, files in os.walk(targetdir):
if not files:
continue
yaml_files += map(
lambda f: os.path.relpath(
os.path.join(directory, f),
targetdir),
filter(lambda f: f.endswith('.interface.yaml'), files))
for y in yaml_files:
# parse only phosphor dbus related interface files
if not y.startswith('xyz'):
continue
with open(os.path.join(targetdir, y)) as fd:
i = y.replace('.interface.yaml', '').replace(os.sep, '.')
# PIM can't create interfaces with methods.
parsed = yaml.safe_load(fd.read())
if parsed.get('methods', None):
continue
# Cereal can't understand the type sdbusplus::object_path. This
# type is a wrapper around std::string. Ignore interfaces having
# a property of this type for now. The only interface that has a
# property of this type now is xyz.openbmc_project.Association,
# which is an unused interface. No inventory objects implement
# this interface.
# TODO via openbmc/openbmc#2123 : figure out how to make Cereal
# understand sdbusplus::object_path.
properties = parsed.get('properties', None)
if properties:
if any('path' in p['type'] for p in properties):
continue
interface_composite[i] = properties
interfaces.append(i)
return interfaces, interface_composite
def __init__(self, *a, **kw):
self.interfaces = \
[Interface(x) for x in kw.pop('interfaces', [])]
self.interface_composite = \
kw.pop('interface_composite', {})
self.events = [
self.class_map[x['type']](**x) for x in a]
super(Everything, self).__init__(**kw)
def generate_cpp(self, loader):
'''Render the template with the provided events and interfaces.'''
with open(os.path.join(
args.outputdir,
'generated.cpp'), 'w') as fd:
fd.write(
self.render(
loader,
'generated.mako.cpp',
events=self.events,
interfaces=self.interfaces,
indent=Indent()))
def generate_serialization(self, loader):
with open(os.path.join(
args.outputdir,
'gen_serialization.hpp'), 'w') as fd:
fd.write(
self.render(
loader,
'gen_serialization.mako.hpp',
interfaces=self.interfaces,
interface_composite=self.interface_composite))
if __name__ == '__main__':
script_dir = os.path.dirname(os.path.realpath(__file__))
valid_commands = {
'generate-cpp': 'generate_cpp',
'generate-serialization': 'generate_serialization',
}
parser = argparse.ArgumentParser(
description='Phosphor Inventory Manager (PIM) YAML '
'scanner and code generator.')
parser.add_argument(
'-o', '--output-dir', dest='outputdir',
default='.', help='Output directory.')
parser.add_argument(
'-i', '--interfaces-dir', dest='ifacesdir',
help='Location of interfaces to be supported.')
parser.add_argument(
'-d', '--dir', dest='inputdir',
default=os.path.join(script_dir, 'example'),
help='Location of files to process.')
parser.add_argument(
'-b', '--bus-name', dest='busname',
default='xyz.openbmc_project.Inventory.Manager',
help='Inventory manager busname.')
parser.add_argument(
'command', metavar='COMMAND', type=str,
choices=valid_commands.keys(),
help='%s.' % " | ".join(valid_commands.keys()))
args = parser.parse_args()
if sys.version_info < (3, 0):
lookup = mako.lookup.TemplateLookup(
directories=[script_dir],
disable_unicode=True)
else:
lookup = mako.lookup.TemplateLookup(
directories=[script_dir])
function = getattr(
Everything.load(args),
valid_commands[args.command])
function(lookup)
# vim: tabstop=8 expandtab shiftwidth=4 softtabstop=4
|
en
| 0.767482
|
#!/usr/bin/env python Phosphor Inventory Manager YAML parser and code generator. The parser workflow is broken down as follows: 1 - Import YAML files as native python type(s) instance(s). 2 - Create an instance of the Everything class from the native python type instance(s) with the Everything.load method. 3 - The Everything class constructor orchestrates conversion of the native python type(s) instances(s) to render helper types. Each render helper type constructor imports its attributes from the native python type(s) instances(s). 4 - Present the converted YAML to the command processing method requested by the script user. # Global busname for use within classes where necessary Convert yaml types to cpp types. Compose interface properties. Provide various interface transformations. Represent as an sdbusplus namespace. Represent as an sdbusplus server binding header. Help templates be depth agnostic. Render an indent at the current depth plus depth. Associate a template name with its namespace. Un-capitalize booleans. Decorate an argument by quoting it. Decorate an argument by casting it. cast is the cast type (static, const, etc...). target is the cast target type. Decorate an argument with a literal operator. Define argument type inteface. Non-array type arguments. Initializer list arguments. DBus signature arguments. Render syntatically correct c++ method calls. Convenience type for vectors. Convenience type for filters Convenience type for actions Convenience type for path conditions Convenience type for getting inventory properties Assemble a createObjects functor. Assemble a destroyObject functor. Assemble a setProperty functor. Assemble a propertyChanged functor. Assemble a propertyIs functor. # Inventory manager's service name is required # Prepend '&' and append 'getPropertyByName' function on dbusMember # Append getProperty functor Assemble an inventory manager event. Associate one or more dbus signal match signatures with a filter. Assemble a startup event. Parse/render entry point. # Aggregate all the event YAML in the events.d directory # into a single list of events. # Update busname if configured differenly than the default Scan the interfaces directory for interfaces that PIM can create. # parse only phosphor dbus related interface files # PIM can't create interfaces with methods. # Cereal can't understand the type sdbusplus::object_path. This # type is a wrapper around std::string. Ignore interfaces having # a property of this type for now. The only interface that has a # property of this type now is xyz.openbmc_project.Association, # which is an unused interface. No inventory objects implement # this interface. # TODO via openbmc/openbmc#2123 : figure out how to make Cereal # understand sdbusplus::object_path. Render the template with the provided events and interfaces. # vim: tabstop=8 expandtab shiftwidth=4 softtabstop=4
| 2.707089
| 3
|
award/models.py
|
ivxxi/Django3
| 0
|
6625828
|
from django.db import models
from tinymce.models import HTMLField
from django.contrib.auth.models import User
# Create your models here.
class Profile(models.Model):
user = models.OneToOneField(User, on_delete=models.CASCADE)
profile_picture = models.ImageField(upload_to='images/')
bio = models.TextField(max_length=500)
contact = models.CharField(max_length=200)
def __str__(self):
return self.bio
def save_profile(self):
self.save()
def delete_profile(self):
self.delete()
class Project(models.Model):
title = models.CharField(max_length=155)
description = models.TextField(max_length=255)
photo = models.ImageField(upload_to='pics/')
user = models.ForeignKey(User)
link = models.URLField(max_length=200)
design = models.IntegerField(choices=list(zip(range(0,11), range(0,11))), default=0)
usability = models.IntegerField(choices=list(zip(range(0,11), range(0,11))), default=0)
content = models.IntegerField(choices=list(zip(range(0,11), range(0,11))), default=0)
vote_submissions = models.IntegerField(default=0)
def __str__(self):
return f'{self.title}'
def save_project(self):
self.save()
def delete_project(self):
self.delete()
@classmethod
def search_by_title(cls,search_term):
projects = cls.objects.filter(title__icontains=search_term)
return projects
@classmethod
def get_all_images(cls):
images=cls.objects.all().prefetch_related('comment_set')
return images
class Comment(models.Model):
posted_by=models.ForeignKey(User, on_delete=models.CASCADE,null=True)
comment_image=models.ForeignKey(Project,on_delete=models.CASCADE,null=True)
comment=models.CharField(max_length=20,null=True)
def __str__(self):
return self.posted_by
|
from django.db import models
from tinymce.models import HTMLField
from django.contrib.auth.models import User
# Create your models here.
class Profile(models.Model):
user = models.OneToOneField(User, on_delete=models.CASCADE)
profile_picture = models.ImageField(upload_to='images/')
bio = models.TextField(max_length=500)
contact = models.CharField(max_length=200)
def __str__(self):
return self.bio
def save_profile(self):
self.save()
def delete_profile(self):
self.delete()
class Project(models.Model):
title = models.CharField(max_length=155)
description = models.TextField(max_length=255)
photo = models.ImageField(upload_to='pics/')
user = models.ForeignKey(User)
link = models.URLField(max_length=200)
design = models.IntegerField(choices=list(zip(range(0,11), range(0,11))), default=0)
usability = models.IntegerField(choices=list(zip(range(0,11), range(0,11))), default=0)
content = models.IntegerField(choices=list(zip(range(0,11), range(0,11))), default=0)
vote_submissions = models.IntegerField(default=0)
def __str__(self):
return f'{self.title}'
def save_project(self):
self.save()
def delete_project(self):
self.delete()
@classmethod
def search_by_title(cls,search_term):
projects = cls.objects.filter(title__icontains=search_term)
return projects
@classmethod
def get_all_images(cls):
images=cls.objects.all().prefetch_related('comment_set')
return images
class Comment(models.Model):
posted_by=models.ForeignKey(User, on_delete=models.CASCADE,null=True)
comment_image=models.ForeignKey(Project,on_delete=models.CASCADE,null=True)
comment=models.CharField(max_length=20,null=True)
def __str__(self):
return self.posted_by
|
en
| 0.963489
|
# Create your models here.
| 2.257877
| 2
|
protonfixes/gamefixes/200260.py
|
Citiroller/protonfixes
| 213
|
6625829
|
""" Game fix Batman Arkham City
"""
#pylint: disable=C0103
from protonfixes import util
from protonfixes.protonversion import DeprecatedSince
@DeprecatedSince("5.0-3")
def main():
""" Probably not needed when proton will be merged with newer wine
"""
util.protontricks('dotnet20')
util.protontricks('dotnet35')
util.protontricks('physx')
util.protontricks('mdx')
util.protontricks('d3dcompiler_43')
util.protontricks('d3dx9_43')
util.protontricks('win10')
util._mk_syswow64() #pylint: disable=protected-access
#TODO Checking possibly some tweak for language detection
|
""" Game fix Batman Arkham City
"""
#pylint: disable=C0103
from protonfixes import util
from protonfixes.protonversion import DeprecatedSince
@DeprecatedSince("5.0-3")
def main():
""" Probably not needed when proton will be merged with newer wine
"""
util.protontricks('dotnet20')
util.protontricks('dotnet35')
util.protontricks('physx')
util.protontricks('mdx')
util.protontricks('d3dcompiler_43')
util.protontricks('d3dx9_43')
util.protontricks('win10')
util._mk_syswow64() #pylint: disable=protected-access
#TODO Checking possibly some tweak for language detection
|
en
| 0.745645
|
Game fix Batman Arkham City #pylint: disable=C0103 Probably not needed when proton will be merged with newer wine #pylint: disable=protected-access #TODO Checking possibly some tweak for language detection
| 1.441947
| 1
|
tests/components/mqtt/test_light.py
|
europrimus/core
| 0
|
6625830
|
<filename>tests/components/mqtt/test_light.py
"""The tests for the MQTT light platform.
Configuration for RGB Version with brightness:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
qos: 0
payload_on: "on"
payload_off: "off"
Configuration for XY Version with brightness:
light:
platform: mqtt
name: "Office Light XY"
state_topic: "office/xy1/light/status"
command_topic: "office/xy1/light/switch"
brightness_state_topic: "office/xy1/brightness/status"
brightness_command_topic: "office/xy1/brightness/set"
xy_state_topic: "office/xy1/xy/status"
xy_command_topic: "office/xy1/xy/set"
qos: 0
payload_on: "on"
payload_off: "off"
config without RGB:
light:
platform: mqtt
name: "Office Light"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
qos: 0
payload_on: "on"
payload_off: "off"
config without RGB and brightness:
light:
platform: mqtt
name: "Office Light"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
qos: 0
payload_on: "on"
payload_off: "off"
config for RGB Version with brightness and scale:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_scale: 99
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
rgb_scale: 99
qos: 0
payload_on: "on"
payload_off: "off"
config with brightness and color temp
light:
platform: mqtt
name: "Office Light Color Temp"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_scale: 99
color_temp_state_topic: "office/rgb1/color_temp/status"
color_temp_command_topic: "office/rgb1/color_temp/set"
qos: 0
payload_on: "on"
payload_off: "off"
config with brightness and effect
light:
platform: mqtt
name: "Office Light Color Temp"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_scale: 99
effect_state_topic: "office/rgb1/effect/status"
effect_command_topic: "office/rgb1/effect/set"
effect_list:
- rainbow
- colorloop
qos: 0
payload_on: "on"
payload_off: "off"
config for RGB Version with white value and scale:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
white_value_state_topic: "office/rgb1/white_value/status"
white_value_command_topic: "office/rgb1/white_value/set"
white_value_scale: 99
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
rgb_scale: 99
qos: 0
payload_on: "on"
payload_off: "off"
config for RGB Version with RGB command template:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
rgb_command_template: "{{ '#%02x%02x%02x' | format(red, green, blue)}}"
qos: 0
payload_on: "on"
payload_off: "off"
Configuration for HS Version with brightness:
light:
platform: mqtt
name: "Office Light HS"
state_topic: "office/hs1/light/status"
command_topic: "office/hs1/light/switch"
brightness_state_topic: "office/hs1/brightness/status"
brightness_command_topic: "office/hs1/brightness/set"
hs_state_topic: "office/hs1/hs/status"
hs_command_topic: "office/hs1/hs/set"
qos: 0
payload_on: "on"
payload_off: "off"
Configuration with brightness command template:
light:
platform: mqtt
name: "Office Light"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_command_template: '{ "brightness": "{{ value }}" }'
qos: 0
payload_on: "on"
payload_off: "off"
Configuration with effect command template:
light:
platform: mqtt
name: "Office Light Color Temp"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
effect_state_topic: "office/rgb1/effect/status"
effect_command_topic: "office/rgb1/effect/set"
effect_command_template: '{ "effect": "{{ value }}" }'
effect_list:
- rainbow
- colorloop
qos: 0
payload_on: "on"
payload_off: "off"
"""
import copy
from unittest.mock import call, patch
import pytest
from homeassistant.components import light
from homeassistant.components.mqtt.light.schema_basic import (
CONF_BRIGHTNESS_COMMAND_TOPIC,
CONF_COLOR_TEMP_COMMAND_TOPIC,
CONF_EFFECT_COMMAND_TOPIC,
CONF_EFFECT_LIST,
CONF_HS_COMMAND_TOPIC,
CONF_RGB_COMMAND_TOPIC,
CONF_RGBW_COMMAND_TOPIC,
CONF_RGBWW_COMMAND_TOPIC,
CONF_WHITE_VALUE_COMMAND_TOPIC,
CONF_XY_COMMAND_TOPIC,
MQTT_LIGHT_ATTRIBUTES_BLOCKED,
)
from homeassistant.const import (
ATTR_ASSUMED_STATE,
ATTR_SUPPORTED_FEATURES,
STATE_OFF,
STATE_ON,
STATE_UNKNOWN,
)
import homeassistant.core as ha
from homeassistant.setup import async_setup_component
from .test_common import (
help_test_availability_when_connection_lost,
help_test_availability_without_topic,
help_test_custom_availability_payload,
help_test_default_availability_payload,
help_test_discovery_broken,
help_test_discovery_removal,
help_test_discovery_update,
help_test_discovery_update_attr,
help_test_discovery_update_unchanged,
help_test_encoding_subscribable_topics,
help_test_entity_debug_info_message,
help_test_entity_device_info_remove,
help_test_entity_device_info_update,
help_test_entity_device_info_with_connection,
help_test_entity_device_info_with_identifier,
help_test_entity_id_update_discovery_update,
help_test_entity_id_update_subscriptions,
help_test_publishing_with_custom_encoding,
help_test_reloadable,
help_test_reloadable_late,
help_test_setting_attribute_via_mqtt_json_message,
help_test_setting_attribute_with_template,
help_test_setting_blocked_attribute_via_mqtt_json_message,
help_test_setup_manual_entity_from_yaml,
help_test_unique_id,
help_test_update_with_json_attrs_bad_JSON,
help_test_update_with_json_attrs_not_dict,
)
from tests.common import assert_setup_component, async_fire_mqtt_message
from tests.components.light import common
DEFAULT_CONFIG = {
light.DOMAIN: {"platform": "mqtt", "name": "test", "command_topic": "test-topic"}
}
async def test_fail_setup_if_no_command_topic(hass, mqtt_mock_entry_no_yaml_config):
"""Test if command fails with command topic."""
assert await async_setup_component(
hass, light.DOMAIN, {light.DOMAIN: {"platform": "mqtt", "name": "test"}}
)
await hass.async_block_till_done()
await mqtt_mock_entry_no_yaml_config()
assert hass.states.get("light.test") is None
async def test_legacy_rgb_white_light(hass, mqtt_mock_entry_with_yaml_config):
"""Test legacy RGB + white light flags brightness support."""
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"white_value_command_topic": "test_light_rgb/white/set",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
expected_features = (
light.SUPPORT_COLOR | light.SUPPORT_BRIGHTNESS | light.SUPPORT_WHITE_VALUE
)
assert state.attributes.get(ATTR_SUPPORTED_FEATURES) == expected_features
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == ["hs", "rgbw"]
async def test_no_color_brightness_color_temp_hs_white_xy_if_no_topics(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test if there is no color and brightness if no topic."""
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == ["onoff"]
async_fire_mqtt_message(hass, "test_light_rgb/status", "ON")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "onoff"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == ["onoff"]
async_fire_mqtt_message(hass, "test_light_rgb/status", "OFF")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "None")
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
async def test_legacy_controlling_state_via_topic(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the controlling of the state via topic for legacy light (white_value)."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_state_topic": "test_light_rgb/white_value/status",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs", "rgbw"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 100
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("color_temp") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes["white_value"] == 100
assert light_state.attributes["color_temp"] == 300
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "rainbow")
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "rainbow"
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "125,125,125")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 187, 131)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "0")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 255, 255)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "0.675,0.322")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.672, 0.324)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_controlling_state_via_topic(hass, mqtt_mock_entry_with_yaml_config):
"""Test the controlling of the state via topic."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") == 100
assert light_state.attributes["color_temp"] == 300
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "rainbow")
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "rainbow"
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "125,125,125")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (125, 125, 125)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "80,40,20,10")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbw_color") == (80, 40, 20, 10)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "80,40,20,10,8")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbww_color") == (80, 40, 20, 10, 8)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "0.675,0.322")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.675, 0.322)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_legacy_invalid_state_via_topic(
hass, mqtt_mock_entry_with_yaml_config, caplog
):
"""Test handling of empty data via topic."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_state_topic": "test_light_rgb/white_value/status",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "255,255,255")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "255")
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "none")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 255, 255)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (0, 0)
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") == (0.323, 0.329)
async_fire_mqtt_message(hass, "test_light_rgb/status", "")
assert "Ignoring empty state message" in caplog.text
light_state = hass.states.get("light.test")
assert state.state == STATE_ON
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "")
assert "Ignoring empty brightness message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 255
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "")
assert "Ignoring empty effect message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "none"
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "")
assert "Ignoring empty rgb message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 255, 255)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "")
assert "Ignoring empty hs message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "bad,bad")
assert "Failed to parse hs state update" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "")
assert "Ignoring empty xy-color message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.323, 0.329)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "153")
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "255")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 254, 250)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") == 153
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (54.768, 1.6)
assert state.attributes.get("white_value") == 255
assert state.attributes.get("xy_color") == (0.326, 0.333)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "")
assert "Ignoring empty color temp message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["color_temp"] == 153
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "")
assert "Ignoring empty white value message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["white_value"] == 255
async def test_invalid_state_via_topic(hass, mqtt_mock_entry_with_yaml_config, caplog):
"""Test handling of empty data via topic."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"color_mode_state_topic": "test_light_rgb/color_mode/status",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("xy_color") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgb")
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "255,255,255")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "255")
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "none")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 255, 255)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (0, 0)
assert state.attributes.get("xy_color") == (0.323, 0.329)
assert state.attributes.get("color_mode") == "rgb"
async_fire_mqtt_message(hass, "test_light_rgb/status", "")
assert "Ignoring empty state message" in caplog.text
light_state = hass.states.get("light.test")
assert state.state == STATE_ON
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "")
assert "Ignoring empty brightness message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 255
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "")
assert "Ignoring empty color mode message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "none"
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "")
assert "Ignoring empty effect message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "none"
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "")
assert "Ignoring empty rgb message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 255, 255)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "")
assert "Ignoring empty hs message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "bad,bad")
assert "Failed to parse hs state update" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "")
assert "Ignoring empty xy-color message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.323, 0.329)
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "255,255,255,1")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbw")
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "")
assert "Ignoring empty rgbw message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbw_color") == (255, 255, 255, 1)
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "255,255,255,1,2")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbww")
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "")
assert "Ignoring empty rgbww message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbww_color") == (255, 255, 255, 1, 2)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "153")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "color_temp")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 254, 250)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") == 153
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (54.768, 1.6)
assert state.attributes.get("xy_color") == (0.326, 0.333)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "")
assert "Ignoring empty color temp message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["color_temp"] == 153
async def test_brightness_controlling_scale(hass, mqtt_mock_entry_with_yaml_config):
"""Test the brightness controlling scale."""
with assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_scale/status",
"command_topic": "test_scale/set",
"brightness_state_topic": "test_scale/brightness/status",
"brightness_command_topic": "test_scale/brightness/set",
"brightness_scale": "99",
"qos": 0,
"payload_on": "on",
"payload_off": "off",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_scale/status", "on")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") is None
async_fire_mqtt_message(hass, "test_scale/status", "off")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_scale/status", "on")
async_fire_mqtt_message(hass, "test_scale/brightness/status", "99")
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 255
async def test_brightness_from_rgb_controlling_scale(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the brightness controlling scale."""
with assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_scale_rgb/status",
"command_topic": "test_scale_rgb/set",
"rgb_state_topic": "test_scale_rgb/rgb/status",
"rgb_command_topic": "test_scale_rgb/rgb/set",
"qos": 0,
"payload_on": "on",
"payload_off": "off",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_scale_rgb/status", "on")
async_fire_mqtt_message(hass, "test_scale_rgb/rgb/status", "255,0,0")
state = hass.states.get("light.test")
assert state.attributes.get("brightness") == 255
async_fire_mqtt_message(hass, "test_scale_rgb/rgb/status", "127,0,0")
state = hass.states.get("light.test")
assert state.attributes.get("brightness") == 127
async def test_legacy_white_value_controlling_scale(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the white_value controlling scale."""
with assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_scale/status",
"command_topic": "test_scale/set",
"white_value_state_topic": "test_scale/white_value/status",
"white_value_command_topic": "test_scale/white_value/set",
"white_value_scale": "99",
"qos": 0,
"payload_on": "on",
"payload_off": "off",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("white_value") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_scale/status", "on")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("white_value") is None
async_fire_mqtt_message(hass, "test_scale/status", "off")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_scale/status", "on")
async_fire_mqtt_message(hass, "test_scale/white_value/status", "99")
light_state = hass.states.get("light.test")
assert light_state.attributes["white_value"] == 255
async def test_legacy_controlling_state_via_topic_with_templates(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the setting of the state with a template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"effect_state_topic": "test_light_rgb/effect/status",
"hs_state_topic": "test_light_rgb/hs/status",
"rgb_state_topic": "test_light_rgb/rgb/status",
"white_value_state_topic": "test_light_rgb/white_value/status",
"xy_state_topic": "test_light_rgb/xy/status",
"state_value_template": "{{ value_json.hello }}",
"brightness_value_template": "{{ value_json.hello }}",
"color_temp_value_template": "{{ value_json.hello }}",
"effect_value_template": "{{ value_json.hello }}",
"hs_value_template": '{{ value_json.hello | join(",") }}',
"rgb_value_template": '{{ value_json.hello | join(",") }}',
"white_value_template": "{{ value_json.hello }}",
"xy_value_template": '{{ value_json.hello | join(",") }}',
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", '{"hello": [1, 2, 3]}')
async_fire_mqtt_message(hass, "test_light_rgb/status", '{"hello": "ON"}')
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", '{"hello": "50"}')
async_fire_mqtt_message(
hass, "test_light_rgb/color_temp/status", '{"hello": "300"}'
)
async_fire_mqtt_message(
hass, "test_light_rgb/effect/status", '{"hello": "rainbow"}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("rgb_color") == (84, 169, 255)
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") == "rainbow"
assert state.attributes.get("white_value") is None
async_fire_mqtt_message(
hass, "test_light_rgb/white_value/status", '{"hello": "75"}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("rgb_color") == (255, 187, 131)
assert state.attributes.get("color_temp") == 300
assert state.attributes.get("effect") == "rainbow"
assert state.attributes.get("white_value") == 75
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", '{"hello": [100,50]}')
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", '{"hello": "0"}')
state = hass.states.get("light.test")
assert state.attributes.get("hs_color") == (100, 50)
async_fire_mqtt_message(
hass, "test_light_rgb/xy/status", '{"hello": [0.123,0.123]}'
)
state = hass.states.get("light.test")
assert state.attributes.get("xy_color") == (0.14, 0.131)
async_fire_mqtt_message(hass, "test_light_rgb/status", '{"hello": null}')
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
async def test_controlling_state_via_topic_with_templates(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the setting of the state with a template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_command_topic": "test_light_rgb/rgbw/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"effect_state_topic": "test_light_rgb/effect/status",
"hs_state_topic": "test_light_rgb/hs/status",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"xy_state_topic": "test_light_rgb/xy/status",
"state_value_template": "{{ value_json.hello }}",
"brightness_value_template": "{{ value_json.hello }}",
"color_temp_value_template": "{{ value_json.hello }}",
"effect_value_template": "{{ value_json.hello }}",
"hs_value_template": '{{ value_json.hello | join(",") }}',
"rgb_value_template": '{{ value_json.hello | join(",") }}',
"rgbw_value_template": '{{ value_json.hello | join(",") }}',
"rgbww_value_template": '{{ value_json.hello | join(",") }}',
"xy_value_template": '{{ value_json.hello | join(",") }}',
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", '{"hello": [1, 2, 3]}')
async_fire_mqtt_message(hass, "test_light_rgb/status", '{"hello": "ON"}')
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", '{"hello": "50"}')
async_fire_mqtt_message(
hass, "test_light_rgb/effect/status", '{"hello": "rainbow"}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("rgb_color") == (1, 2, 3)
assert state.attributes.get("effect") == "rainbow"
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/rgbw/status", '{"hello": [1, 2, 3, 4]}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgbw_color") == (1, 2, 3, 4)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/rgbww/status", '{"hello": [1, 2, 3, 4, 5]}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgbww_color") == (1, 2, 3, 4, 5)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/color_temp/status", '{"hello": "300"}'
)
state = hass.states.get("light.test")
assert state.attributes.get("color_temp") == 300
assert state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", '{"hello": [100,50]}')
state = hass.states.get("light.test")
assert state.attributes.get("hs_color") == (100, 50)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/xy/status", '{"hello": [0.123,0.123]}'
)
state = hass.states.get("light.test")
assert state.attributes.get("xy_color") == (0.123, 0.123)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_legacy_sending_mqtt_commands_and_optimistic(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of command in optimistic mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"effect_list": ["colorloop", "random"],
"qos": 2,
"payload_on": "on",
"payload_off": "off",
}
}
color_modes = ["color_temp", "hs", "rgbw"]
fake_state = ha.State(
"light.test",
"on",
{
"brightness": 95,
"hs_color": [100, 100],
"effect": "random",
"color_temp": 100,
# TODO: Test restoring state with white_value
"white_value": 0,
},
)
with patch(
"homeassistant.helpers.restore_state.RestoreEntity.async_get_last_state",
return_value=fake_state,
), assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 95
assert state.attributes.get("hs_color") == (100, 100)
assert state.attributes.get("effect") == "random"
assert state.attributes.get("color_temp") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get(ATTR_ASSUMED_STATE)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"test_light_rgb/set", "on", 2, False
)
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"test_light_rgb/set", "off", 2, False
)
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_OFF
mqtt_mock.reset_mock()
await common.async_turn_on(
hass, "light.test", brightness=50, xy_color=[0.123, 0.123]
)
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", brightness=50, hs_color=[359, 78])
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/rgb/set", "255,128,0", 2, False),
call("test_light_rgb/brightness/set", "50", 2, False),
call("test_light_rgb/hs/set", "359.0,78.0", 2, False),
call("test_light_rgb/xy/set", "0.14,0.131", 2, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgb_color"] == (255, 128, 0)
assert state.attributes["brightness"] == 50
assert state.attributes["hs_color"] == (30.118, 100)
assert state.attributes.get("white_value") is None
assert state.attributes["xy_color"] == (0.611, 0.375)
assert state.attributes.get("color_temp") is None
await common.async_turn_on(hass, "light.test", white_value=80, color_temp=125)
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/white_value/set", "80", 2, False),
call("test_light_rgb/color_temp/set", "125", 2, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (221, 229, 255)
assert state.attributes["brightness"] == 50
assert state.attributes.get("hs_color") == (224.772, 13.249)
assert state.attributes["white_value"] == 80
assert state.attributes.get("xy_color") == (0.296, 0.301)
assert state.attributes["color_temp"] == 125
async def test_sending_mqtt_commands_and_optimistic(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of command in optimistic mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_command_topic": "test_light_rgb/xy/set",
"effect_list": ["colorloop", "random"],
"qos": 2,
"payload_on": "on",
"payload_off": "off",
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
fake_state = ha.State(
"light.test",
"on",
{
"brightness": 95,
"hs_color": [100, 100],
"effect": "random",
"color_temp": 100,
"color_mode": "hs",
},
)
with patch(
"homeassistant.helpers.restore_state.RestoreEntity.async_get_last_state",
return_value=fake_state,
), assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 95
assert state.attributes.get("hs_color") == (100, 100)
assert state.attributes.get("effect") == "random"
assert state.attributes.get("color_temp") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert state.attributes.get(ATTR_ASSUMED_STATE)
await common.async_turn_on(hass, "light.test", effect="colorloop")
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/effect/set", "colorloop", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 2
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("effect") == "colorloop"
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"test_light_rgb/set", "off", 2, False
)
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_OFF
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(
hass, "light.test", brightness=10, rgb_color=[80, 40, 20]
)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "10", 2, False),
call("test_light_rgb/rgb/set", "80,40,20", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 10
assert state.attributes.get("rgb_color") == (80, 40, 20)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(
hass, "light.test", brightness=20, rgbw_color=[80, 40, 20, 10]
)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "20", 2, False),
call("test_light_rgb/rgbw/set", "80,40,20,10", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 20
assert state.attributes.get("rgbw_color") == (80, 40, 20, 10)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(
hass, "light.test", brightness=40, rgbww_color=[80, 40, 20, 10, 8]
)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "40", 2, False),
call("test_light_rgb/rgbww/set", "80,40,20,10,8", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 40
assert state.attributes.get("rgbww_color") == (80, 40, 20, 10, 8)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", brightness=50, hs_color=[359, 78])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "50", 2, False),
call("test_light_rgb/hs/set", "359.0,78.0", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("hs_color") == (359.0, 78.0)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", brightness=60, xy_color=[0.2, 0.3])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "60", 2, False),
call("test_light_rgb/xy/set", "0.2,0.3", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 60
assert state.attributes.get("xy_color") == (0.2, 0.3)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", color_temp=125)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/color_temp/set", "125", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 2
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 60
assert state.attributes.get("color_temp") == 125
assert state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_sending_mqtt_rgb_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of RGB command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgb_command_template": '{{ "#%02x%02x%02x" | '
"format(red, green, blue)}}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 64])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 0, False),
call("test_light_rgb/rgb/set", "#ff8040", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgb_color"] == (255, 128, 64)
async def test_sending_mqtt_rgbw_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of RGBW command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbw_command_template": '{{ "#%02x%02x%02x%02x" | '
"format(red, green, blue, white)}}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", rgbw_color=[255, 128, 64, 32])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 0, False),
call("test_light_rgb/rgbw/set", "#ff804020", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgbw_color"] == (255, 128, 64, 32)
async def test_sending_mqtt_rgbww_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of RGBWW command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"rgbww_command_template": '{{ "#%02x%02x%02x%02x%02x" | '
"format(red, green, blue, cold_white, warm_white)}}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", rgbww_color=[255, 128, 64, 32, 16])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 0, False),
call("test_light_rgb/rgbww/set", "#ff80402010", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgbww_color"] == (255, 128, 64, 32, 16)
async def test_sending_mqtt_color_temp_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of Color Temp command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_color_temp/set",
"color_temp_command_topic": "test_light_color_temp/color_temp/set",
"color_temp_command_template": "{{ (1000 / value) | round(0) }}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", color_temp=100)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_color_temp/set", "on", 0, False),
call("test_light_color_temp/color_temp/set", "10", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["color_temp"] == 100
async def test_on_command_first(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command being sent before brightness."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
"on_command_type": "first",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=50)
# Should get the following MQTT messages.
# test_light/set: 'ON'
# test_light/bright: 50
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/set", "ON", 0, False),
call("test_light/bright", "50", 0, False),
],
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_last(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command being sent after brightness."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=50)
# Should get the following MQTT messages.
# test_light/bright: 50
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/bright", "50", 0, False),
call("test_light/set", "ON", 0, False),
],
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_brightness(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command being sent as only brightness."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
"rgb_command_topic": "test_light/rgb",
"on_command_type": "brightness",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
# Turn on w/ no brightness - should set to max
await common.async_turn_on(hass, "light.test")
# Should get the following MQTT messages.
# test_light/bright: 255
mqtt_mock.async_publish.assert_called_once_with(
"test_light/bright", "255", 0, False
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ brightness
await common.async_turn_on(hass, "light.test", brightness=50)
mqtt_mock.async_publish.assert_called_once_with("test_light/bright", "50", 0, False)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
# Turn on w/ just a color to ensure brightness gets
# added and sent.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/bright", "50", 0, False),
],
any_order=True,
)
async def test_on_command_brightness_scaled(hass, mqtt_mock_entry_with_yaml_config):
"""Test brightness scale."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
"brightness_scale": 100,
"rgb_command_topic": "test_light/rgb",
"on_command_type": "brightness",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
# Turn on w/ no brightness - should set to max
await common.async_turn_on(hass, "light.test")
# Should get the following MQTT messages.
# test_light/bright: 100
mqtt_mock.async_publish.assert_called_once_with(
"test_light/bright", "100", 0, False
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ brightness
await common.async_turn_on(hass, "light.test", brightness=50)
mqtt_mock.async_publish.assert_called_once_with("test_light/bright", "20", 0, False)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ max brightness
await common.async_turn_on(hass, "light.test", brightness=255)
mqtt_mock.async_publish.assert_called_once_with(
"test_light/bright", "100", 0, False
)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ min brightness
await common.async_turn_on(hass, "light.test", brightness=1)
mqtt_mock.async_publish.assert_called_once_with("test_light/bright", "1", 0, False)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
# Turn on w/ just a color to ensure brightness gets
# added and sent.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/bright", "1", 0, False),
],
any_order=True,
)
async def test_legacy_on_command_rgb(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGB brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgb_command_topic": "test_light/rgb",
"white_value_command_topic": "test_light/white_value",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgb: '1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,128,0'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgb(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGB brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgb_command_topic": "test_light/rgb",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgb: '1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,128,0'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgbw(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBW brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbw_command_topic": "test_light/rgbw",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgbw: '127,127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "127,127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbw: '255,255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "255,255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgbw: '1,1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "1,1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgbw_color=[255, 128, 0, 16])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "1,0,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbw: '255,128,0'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "255,128,0,16", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgbww(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBWW brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbww_command_topic": "test_light/rgbww",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgbww: '127,127,127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "127,127,127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbww: '255,255,255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "255,255,255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgbww: '1,1,1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "1,1,1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgbww_color=[255, 128, 0, 16, 32])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "1,0,0,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbww: '255,128,0,16,32'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "255,128,0,16,32", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgb_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGB brightness mode with RGB template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgb_command_topic": "test_light/rgb",
"rgb_command_template": "{{ red }}/{{ green }}/{{ blue }}",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127/127/127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "127/127/127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_rgbw_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBW brightness mode with RGBW template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbw_command_topic": "test_light/rgbw",
"rgbw_command_template": "{{ red }}/{{ green }}/{{ blue }}/{{ white }}",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127/127/127/127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "127/127/127/127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_rgbww_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBWW brightness mode with RGBWW template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbww_command_topic": "test_light/rgbww",
"rgbww_command_template": "{{ red }}/{{ green }}/{{ blue }}/{{ cold_white }}/{{ warm_white }}",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127/127/127/127/127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "127/127/127/127/127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_white(hass, mqtt_mock_entry_with_yaml_config):
"""Test sending commands for RGB + white light."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "tasmota_B94927/cmnd/POWER",
"state_value_template": "{{ value_json.POWER }}",
"payload_off": "OFF",
"payload_on": "ON",
"brightness_command_topic": "tasmota_B94927/cmnd/Dimmer",
"brightness_scale": 100,
"on_command_type": "brightness",
"brightness_value_template": "{{ value_json.Dimmer }}",
"rgb_command_topic": "tasmota_B94927/cmnd/Color2",
"rgb_value_template": "{{value_json.Color.split(',')[0:3]|join(',')}}",
"white_command_topic": "tasmota_B94927/cmnd/White",
"white_scale": 100,
"color_mode_value_template": "{% if value_json.White %} white {% else %} rgb {% endif %}",
"qos": "0",
}
}
color_modes = ["rgb", "white"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert state.attributes.get(ATTR_ASSUMED_STATE)
await common.async_turn_on(hass, "light.test", brightness=192)
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/Dimmer", "75", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", white=255)
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/White", "100", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", white=64)
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/White", "25", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test")
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/Dimmer", "25", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"tasmota_B94927/cmnd/POWER", "OFF", 0, False
)
async def test_explicit_color_mode(hass, mqtt_mock_entry_with_yaml_config):
"""Test explicit color mode over mqtt."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"color_mode_state_topic": "test_light_rgb/color_mode/status",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "rainbow")
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "rainbow"
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "125,125,125")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "80,40,20,10")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "80,40,20,10,8")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "0.675,0.322")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "color_temp")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgb")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (125, 125, 125)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbw")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbw_color") == (80, 40, 20, 10)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbww")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbww_color") == (80, 40, 20, 10, 8)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "hs")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "xy")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.675, 0.322)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_explicit_color_mode_templated(hass, mqtt_mock_entry_with_yaml_config):
"""Test templated explicit color mode over mqtt."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"color_mode_state_topic": "test_light_rgb/color_mode/status",
"color_mode_value_template": "{{ value_json.color_mode }}",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/color_mode/status", '{"color_mode":"color_temp"}'
)
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/color_mode/status", '{"color_mode":"hs"}'
)
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_white_state_update(hass, mqtt_mock_entry_with_yaml_config):
"""Test state updates for RGB + white light."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "tasmota_B94927/tele/STATE",
"command_topic": "tasmota_B94927/cmnd/POWER",
"state_value_template": "{{ value_json.POWER }}",
"payload_off": "OFF",
"payload_on": "ON",
"brightness_command_topic": "tasmota_B94927/cmnd/Dimmer",
"brightness_state_topic": "tasmota_B94927/tele/STATE",
"brightness_scale": 100,
"on_command_type": "brightness",
"brightness_value_template": "{{ value_json.Dimmer }}",
"rgb_command_topic": "tasmota_B94927/cmnd/Color2",
"rgb_state_topic": "tasmota_B94927/tele/STATE",
"rgb_value_template": "{{value_json.Color.split(',')[0:3]|join(',')}}",
"white_command_topic": "tasmota_B94927/cmnd/White",
"white_scale": 100,
"color_mode_state_topic": "tasmota_B94927/tele/STATE",
"color_mode_value_template": "{% if value_json.White %} white {% else %} rgb {% endif %}",
"qos": "0",
}
}
color_modes = ["rgb", "white"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(
hass,
"tasmota_B94927/tele/STATE",
'{"POWER":"ON","Dimmer":50,"Color":"0,0,0,128","White":50}',
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 128
assert state.attributes.get("rgb_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "white"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass,
"tasmota_B94927/tele/STATE",
'{"POWER":"ON","Dimmer":50,"Color":"128,64,32,0","White":0}',
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 128
assert state.attributes.get("rgb_color") == (128, 64, 32)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_effect(hass, mqtt_mock_entry_with_yaml_config):
"""Test effect."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"effect_command_topic": "test_light/effect/set",
"effect_list": ["rainbow", "colorloop"],
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", effect="rainbow")
# Should get the following MQTT messages.
# test_light/effect/set: 'rainbow'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/effect/set", "rainbow", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_availability_when_connection_lost(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test availability after MQTT disconnection."""
await help_test_availability_when_connection_lost(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_availability_without_topic(hass, mqtt_mock_entry_with_yaml_config):
"""Test availability without defined availability topic."""
await help_test_availability_without_topic(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_default_availability_payload(hass, mqtt_mock_entry_with_yaml_config):
"""Test availability by default payload with defined topic."""
await help_test_default_availability_payload(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_custom_availability_payload(hass, mqtt_mock_entry_with_yaml_config):
"""Test availability by custom payload with defined topic."""
await help_test_custom_availability_payload(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_setting_attribute_via_mqtt_json_message(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the setting of attribute via MQTT with JSON payload."""
await help_test_setting_attribute_via_mqtt_json_message(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_setting_blocked_attribute_via_mqtt_json_message(
hass, mqtt_mock_entry_no_yaml_config
):
"""Test the setting of attribute via MQTT with JSON payload."""
await help_test_setting_blocked_attribute_via_mqtt_json_message(
hass,
mqtt_mock_entry_no_yaml_config,
light.DOMAIN,
DEFAULT_CONFIG,
MQTT_LIGHT_ATTRIBUTES_BLOCKED,
)
async def test_setting_attribute_with_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test the setting of attribute via MQTT with JSON payload."""
await help_test_setting_attribute_with_template(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_update_with_json_attrs_not_dict(
hass, mqtt_mock_entry_with_yaml_config, caplog
):
"""Test attributes get extracted from a JSON result."""
await help_test_update_with_json_attrs_not_dict(
hass, mqtt_mock_entry_with_yaml_config, caplog, light.DOMAIN, DEFAULT_CONFIG
)
async def test_update_with_json_attrs_bad_JSON(
hass, mqtt_mock_entry_with_yaml_config, caplog
):
"""Test attributes get extracted from a JSON result."""
await help_test_update_with_json_attrs_bad_JSON(
hass, mqtt_mock_entry_with_yaml_config, caplog, light.DOMAIN, DEFAULT_CONFIG
)
async def test_discovery_update_attr(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test update of discovered MQTTAttributes."""
await help_test_discovery_update_attr(
hass, mqtt_mock_entry_no_yaml_config, caplog, light.DOMAIN, DEFAULT_CONFIG
)
async def test_unique_id(hass, mqtt_mock_entry_with_yaml_config):
"""Test unique id option only creates one light per unique_id."""
config = {
light.DOMAIN: [
{
"platform": "mqtt",
"name": "Test 1",
"state_topic": "test-topic",
"command_topic": "test_topic",
"unique_id": "TOTALLY_UNIQUE",
},
{
"platform": "mqtt",
"name": "<NAME>",
"state_topic": "test-topic",
"command_topic": "test_topic",
"unique_id": "TOTALLY_UNIQUE",
},
]
}
await help_test_unique_id(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, config
)
async def test_discovery_removal_light(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test removal of discovered light."""
data = (
'{ "name": "test",'
' "state_topic": "test_topic",'
' "command_topic": "test_topic" }'
)
await help_test_discovery_removal(
hass, mqtt_mock_entry_no_yaml_config, caplog, light.DOMAIN, data
)
async def test_discovery_deprecated(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test discovery of mqtt light with deprecated platform option."""
await mqtt_mock_entry_no_yaml_config()
data = (
'{ "name": "Beer",' ' "platform": "mqtt",' ' "command_topic": "test_topic"}'
)
async_fire_mqtt_message(hass, "homeassistant/light/bla/config", data)
await hass.async_block_till_done()
state = hass.states.get("light.beer")
assert state is not None
assert state.name == "Beer"
async def test_discovery_update_light_topic_and_template(
hass, mqtt_mock_entry_no_yaml_config, caplog
):
"""Test update of discovered light."""
config1 = {
"name": "Beer",
"state_topic": "test_light_rgb/state1",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state1",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state1",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state1",
"color_temp_state_topic": "test_light_rgb/state1",
"effect_state_topic": "test_light_rgb/state1",
"hs_state_topic": "test_light_rgb/state1",
"rgb_state_topic": "test_light_rgb/state1",
"white_value_state_topic": "test_light_rgb/state1",
"xy_state_topic": "test_light_rgb/state1",
"state_value_template": "{{ value_json.state1.state }}",
"brightness_value_template": "{{ value_json.state1.brightness }}",
"color_temp_value_template": "{{ value_json.state1.ct }}",
"effect_value_template": "{{ value_json.state1.fx }}",
"hs_value_template": "{{ value_json.state1.hs }}",
"rgb_value_template": "{{ value_json.state1.rgb }}",
"white_value_template": "{{ value_json.state1.white }}",
"xy_value_template": "{{ value_json.state1.xy }}",
}
config2 = {
"name": "Milk",
"state_topic": "test_light_rgb/state2",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state2",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state2",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state2",
"color_temp_state_topic": "test_light_rgb/state2",
"effect_state_topic": "test_light_rgb/state2",
"hs_state_topic": "test_light_rgb/state2",
"rgb_state_topic": "test_light_rgb/state2",
"white_value_state_topic": "test_light_rgb/state2",
"xy_state_topic": "test_light_rgb/state2",
"state_value_template": "{{ value_json.state2.state }}",
"brightness_value_template": "{{ value_json.state2.brightness }}",
"color_temp_value_template": "{{ value_json.state2.ct }}",
"effect_value_template": "{{ value_json.state2.fx }}",
"hs_value_template": "{{ value_json.state2.hs }}",
"rgb_value_template": "{{ value_json.state2.rgb }}",
"white_value_template": "{{ value_json.state2.white }}",
"xy_value_template": "{{ value_json.state2.xy }}",
}
state_data1 = [
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "white":100, "fx":"cycle"}}',
)
],
"on",
[
("brightness", 100),
("color_temp", 123),
("white_value", 100),
("effect", "cycle"),
],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2", "white":0}}',
)
],
"on",
[("hs_color", (1, 2)), ("white_value", None)],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
)
],
"on",
[("rgb_color", (255, 127, 63))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"xy":"0.3, 0.4"}}',
)
],
"on",
[("xy_color", (0.3, 0.401))],
),
]
state_data2 = [
(
[
(
"test_light_rgb/state2",
'{"state2":{"state":"ON", "brightness":50, "ct":200, "white":50, "fx":"loop"}}',
)
],
"on",
[
("brightness", 50),
("color_temp", 200),
("white_value", 50),
("effect", "loop"),
],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
],
"on",
[("brightness", 50), ("color_temp", 200), ("effect", "loop")],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state1", '{"state2":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state2", '{"state1":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state2", '{"state2":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state2",
'{"state2":{"state":"ON", "hs":"1.2,2.2", "white":0}}',
)
],
"on",
[("hs_color", (1.2, 2.2)), ("white_value", None)],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "hs":"1,2"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"state":"ON", "hs":"1,2"}}',
),
],
"on",
[("hs_color", (1.2, 2.2))],
),
(
[
(
"test_light_rgb/state2",
'{"state2":{"rgb":"63,127,255"}}',
)
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"rgb":"255,127,63"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"rgb":"255,127,63"}}',
),
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state2",
'{"state2":{"xy":"0.4, 0.3"}}',
)
],
"on",
[("xy_color", (0.4, 0.3))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"white":50, "xy":"0.3, 0.4"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"white":50, "xy":"0.3, 0.4"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"white":50, "xy":"0.3, 0.4"}}',
),
],
"on",
[("xy_color", (0.4, 0.3))],
),
]
await help_test_discovery_update(
hass,
mqtt_mock_entry_no_yaml_config,
caplog,
light.DOMAIN,
config1,
config2,
state_data1=state_data1,
state_data2=state_data2,
)
async def test_discovery_update_light_template(
hass, mqtt_mock_entry_no_yaml_config, caplog
):
"""Test update of discovered light."""
config1 = {
"name": "Beer",
"state_topic": "test_light_rgb/state1",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state1",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state1",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state1",
"color_temp_state_topic": "test_light_rgb/state1",
"effect_state_topic": "test_light_rgb/state1",
"hs_state_topic": "test_light_rgb/state1",
"rgb_state_topic": "test_light_rgb/state1",
"white_value_state_topic": "test_light_rgb/state1",
"xy_state_topic": "test_light_rgb/state1",
"state_value_template": "{{ value_json.state1.state }}",
"brightness_value_template": "{{ value_json.state1.brightness }}",
"color_temp_value_template": "{{ value_json.state1.ct }}",
"effect_value_template": "{{ value_json.state1.fx }}",
"hs_value_template": "{{ value_json.state1.hs }}",
"rgb_value_template": "{{ value_json.state1.rgb }}",
"white_value_template": "{{ value_json.state1.white }}",
"xy_value_template": "{{ value_json.state1.xy }}",
}
config2 = {
"name": "Milk",
"state_topic": "test_light_rgb/state1",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state1",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state1",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state1",
"color_temp_state_topic": "test_light_rgb/state1",
"effect_state_topic": "test_light_rgb/state1",
"hs_state_topic": "test_light_rgb/state1",
"rgb_state_topic": "test_light_rgb/state1",
"white_value_state_topic": "test_light_rgb/state1",
"xy_state_topic": "test_light_rgb/state1",
"state_value_template": "{{ value_json.state2.state }}",
"brightness_value_template": "{{ value_json.state2.brightness }}",
"color_temp_value_template": "{{ value_json.state2.ct }}",
"effect_value_template": "{{ value_json.state2.fx }}",
"hs_value_template": "{{ value_json.state2.hs }}",
"rgb_value_template": "{{ value_json.state2.rgb }}",
"white_value_template": "{{ value_json.state2.white }}",
"xy_value_template": "{{ value_json.state2.xy }}",
}
state_data1 = [
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "white":100, "fx":"cycle"}}',
)
],
"on",
[
("brightness", 100),
("color_temp", 123),
("white_value", 100),
("effect", "cycle"),
],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2", "white":0}}',
)
],
"on",
[("hs_color", (1, 2))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
)
],
"on",
[("rgb_color", (255, 127, 63))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"white":0, "xy":"0.3, 0.4"}}',
)
],
"on",
[("white_value", None), ("xy_color", (0.3, 0.401))],
),
]
state_data2 = [
(
[
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "brightness":50, "ct":200, "white":50, "fx":"loop"}}',
)
],
"on",
[
("brightness", 50),
("color_temp", 200),
("white_value", 50),
("effect", "loop"),
],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
],
"on",
[("brightness", 50), ("color_temp", 200), ("effect", "loop")],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state1", '{"state2":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "hs":"1.2,2.2", "white":0}}',
)
],
"on",
[("hs_color", (1.2, 2.2))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2"}}',
)
],
"on",
[("hs_color", (1.2, 2.2))],
),
(
[
(
"test_light_rgb/state1",
'{"state2":{"rgb":"63,127,255"}}',
)
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
)
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state1",
'{"state2":{"xy":"0.4, 0.3"}}',
)
],
"on",
[("white_value", None), ("xy_color", (0.4, 0.3))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"white":50, "xy":"0.3, 0.4"}}',
)
],
"on",
[("white_value", None), ("xy_color", (0.4, 0.3))],
),
]
await help_test_discovery_update(
hass,
mqtt_mock_entry_no_yaml_config,
caplog,
light.DOMAIN,
config1,
config2,
state_data1=state_data1,
state_data2=state_data2,
)
async def test_discovery_update_unchanged_light(
hass, mqtt_mock_entry_no_yaml_config, caplog
):
"""Test update of discovered light."""
data1 = (
'{ "name": "Beer",'
' "state_topic": "test_topic",'
' "command_topic": "test_topic" }'
)
with patch(
"homeassistant.components.mqtt.light.schema_basic.MqttLight.discovery_update"
) as discovery_update:
await help_test_discovery_update_unchanged(
hass,
mqtt_mock_entry_no_yaml_config,
caplog,
light.DOMAIN,
data1,
discovery_update,
)
@pytest.mark.no_fail_on_log_exception
async def test_discovery_broken(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test handling of bad discovery message."""
data1 = '{ "name": "Beer" }'
data2 = (
'{ "name": "Milk",'
' "state_topic": "test_topic",'
' "command_topic": "test_topic" }'
)
await help_test_discovery_broken(
hass, mqtt_mock_entry_no_yaml_config, caplog, light.DOMAIN, data1, data2
)
async def test_entity_device_info_with_connection(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT light device registry integration."""
await help_test_entity_device_info_with_connection(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_device_info_with_identifier(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT light device registry integration."""
await help_test_entity_device_info_with_identifier(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_device_info_update(hass, mqtt_mock_entry_no_yaml_config):
"""Test device registry update."""
await help_test_entity_device_info_update(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_device_info_remove(hass, mqtt_mock_entry_no_yaml_config):
"""Test device registry remove."""
await help_test_entity_device_info_remove(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_id_update_subscriptions(hass, mqtt_mock_entry_with_yaml_config):
"""Test MQTT subscriptions are managed when entity_id is updated."""
await help_test_entity_id_update_subscriptions(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_id_update_discovery_update(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT discovery update when entity_id is updated."""
await help_test_entity_id_update_discovery_update(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_debug_info_message(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT debug info."""
await help_test_entity_debug_info_message(
hass,
mqtt_mock_entry_no_yaml_config,
light.DOMAIN,
DEFAULT_CONFIG,
light.SERVICE_TURN_ON,
)
async def test_max_mireds(hass, mqtt_mock_entry_with_yaml_config):
"""Test setting min_mireds and max_mireds."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_max_mireds/set",
"color_temp_command_topic": "test_max_mireds/color_temp/set",
"max_mireds": 370,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.attributes.get("min_mireds") == 153
assert state.attributes.get("max_mireds") == 370
@pytest.mark.parametrize(
"service,topic,parameters,payload,template,tpl_par,tpl_output",
[
(
light.SERVICE_TURN_ON,
"command_topic",
None,
"ON",
None,
None,
None,
),
(
light.SERVICE_TURN_ON,
"white_command_topic",
{"white": "255"},
255,
None,
None,
None,
),
(
light.SERVICE_TURN_ON,
"brightness_command_topic",
{"color_temp": "200", "brightness": "50"},
50,
"brightness_command_template",
"value",
b"5",
),
(
light.SERVICE_TURN_ON,
"effect_command_topic",
{"rgb_color": [255, 128, 0], "effect": "color_loop"},
"color_loop",
"effect_command_template",
"value",
b"c",
),
(
light.SERVICE_TURN_ON,
"color_temp_command_topic",
{"color_temp": "200"},
200,
"color_temp_command_template",
"value",
b"2",
),
(
light.SERVICE_TURN_ON,
"rgb_command_topic",
{"rgb_color": [255, 128, 0]},
"255,128,0",
"rgb_command_template",
"red",
b"2",
),
(
light.SERVICE_TURN_ON,
"hs_command_topic",
{"rgb_color": [255, 128, 0]},
"30.118,100.0",
None,
None,
None,
),
(
light.SERVICE_TURN_ON,
"xy_command_topic",
{"hs_color": [30.118, 100.0]},
"0.611,0.375",
None,
None,
None,
),
(
light.SERVICE_TURN_OFF,
"command_topic",
None,
"OFF",
None,
None,
None,
),
],
)
async def test_publishing_with_custom_encoding(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
service,
topic,
parameters,
payload,
template,
tpl_par,
tpl_output,
):
"""Test publishing MQTT payload with different encoding."""
domain = light.DOMAIN
config = copy.deepcopy(DEFAULT_CONFIG[domain])
if topic == "effect_command_topic":
config["effect_list"] = ["random", "color_loop"]
elif topic == "white_command_topic":
config["rgb_command_topic"] = "some-cmd-topic"
await help_test_publishing_with_custom_encoding(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
domain,
config,
service,
topic,
parameters,
payload,
template,
tpl_par=tpl_par,
tpl_output=tpl_output,
)
async def test_reloadable(hass, mqtt_mock_entry_with_yaml_config, caplog, tmp_path):
"""Test reloading the MQTT platform."""
domain = light.DOMAIN
config = DEFAULT_CONFIG[domain]
await help_test_reloadable(
hass, mqtt_mock_entry_with_yaml_config, caplog, tmp_path, domain, config
)
async def test_reloadable_late(hass, mqtt_client_mock, caplog, tmp_path):
"""Test reloading the MQTT platform with late entry setup."""
domain = light.DOMAIN
config = DEFAULT_CONFIG[domain]
await help_test_reloadable_late(hass, caplog, tmp_path, domain, config)
@pytest.mark.parametrize(
"topic,value,attribute,attribute_value,init_payload",
[
("state_topic", "ON", None, "on", None),
("brightness_state_topic", "60", "brightness", 60, ("state_topic", "ON")),
(
"color_mode_state_topic",
"200",
"color_mode",
"200",
("state_topic", "ON"),
),
("color_temp_state_topic", "200", "color_temp", 200, ("state_topic", "ON")),
("effect_state_topic", "random", "effect", "random", ("state_topic", "ON")),
("hs_state_topic", "200,50", "hs_color", (200, 50), ("state_topic", "ON")),
(
"xy_state_topic",
"128,128",
"xy_color",
(128, 128),
("state_topic", "ON"),
),
(
"rgb_state_topic",
"255,0,240",
"rgb_color",
(255, 0, 240),
("state_topic", "ON"),
),
],
)
async def test_encoding_subscribable_topics(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
topic,
value,
attribute,
attribute_value,
init_payload,
):
"""Test handling of incoming encoded payload."""
config = copy.deepcopy(DEFAULT_CONFIG[light.DOMAIN])
config[CONF_EFFECT_COMMAND_TOPIC] = "light/CONF_EFFECT_COMMAND_TOPIC"
config[CONF_RGB_COMMAND_TOPIC] = "light/CONF_RGB_COMMAND_TOPIC"
config[CONF_BRIGHTNESS_COMMAND_TOPIC] = "light/CONF_BRIGHTNESS_COMMAND_TOPIC"
config[CONF_COLOR_TEMP_COMMAND_TOPIC] = "light/CONF_COLOR_TEMP_COMMAND_TOPIC"
config[CONF_HS_COMMAND_TOPIC] = "light/CONF_HS_COMMAND_TOPIC"
config[CONF_RGB_COMMAND_TOPIC] = "light/CONF_RGB_COMMAND_TOPIC"
config[CONF_RGBW_COMMAND_TOPIC] = "light/CONF_RGBW_COMMAND_TOPIC"
config[CONF_RGBWW_COMMAND_TOPIC] = "light/CONF_RGBWW_COMMAND_TOPIC"
config[CONF_XY_COMMAND_TOPIC] = "light/CONF_XY_COMMAND_TOPIC"
config[CONF_EFFECT_LIST] = ["colorloop", "random"]
if attribute and attribute == "brightness":
config[CONF_WHITE_VALUE_COMMAND_TOPIC] = "light/CONF_WHITE_VALUE_COMMAND_TOPIC"
await help_test_encoding_subscribable_topics(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
light.DOMAIN,
config,
topic,
value,
attribute,
attribute_value,
init_payload,
)
async def test_sending_mqtt_brightness_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of Brightness command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_brightness/set",
"brightness_command_topic": "test_light_brightness/brightness/set",
"brightness_command_template": "{{ (1000 / value) | round(0) }}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=100)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_brightness/set", "on", 0, False),
call("test_light_brightness/brightness/set", "10", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["brightness"] == 100
async def test_sending_mqtt_effect_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of Effect command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_brightness/set",
"brightness_command_topic": "test_light_brightness/brightness/set",
"effect_command_topic": "test_light_brightness/effect/set",
"effect_command_template": '{ "effect": "{{ value }}" }',
"effect_list": ["colorloop", "random"],
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", effect="colorloop")
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_brightness/set", "on", 0, False),
call(
"test_light_brightness/effect/set",
'{ "effect": "colorloop" }',
0,
False,
),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("effect") == "colorloop"
async def test_setup_manual_entity_from_yaml(hass):
"""Test setup manual configured MQTT entity."""
platform = light.DOMAIN
config = copy.deepcopy(DEFAULT_CONFIG[platform])
config["name"] = "test"
del config["platform"]
await help_test_setup_manual_entity_from_yaml(hass, platform, config)
assert hass.states.get(f"{platform}.test") is not None
|
<filename>tests/components/mqtt/test_light.py
"""The tests for the MQTT light platform.
Configuration for RGB Version with brightness:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
qos: 0
payload_on: "on"
payload_off: "off"
Configuration for XY Version with brightness:
light:
platform: mqtt
name: "Office Light XY"
state_topic: "office/xy1/light/status"
command_topic: "office/xy1/light/switch"
brightness_state_topic: "office/xy1/brightness/status"
brightness_command_topic: "office/xy1/brightness/set"
xy_state_topic: "office/xy1/xy/status"
xy_command_topic: "office/xy1/xy/set"
qos: 0
payload_on: "on"
payload_off: "off"
config without RGB:
light:
platform: mqtt
name: "Office Light"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
qos: 0
payload_on: "on"
payload_off: "off"
config without RGB and brightness:
light:
platform: mqtt
name: "Office Light"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
qos: 0
payload_on: "on"
payload_off: "off"
config for RGB Version with brightness and scale:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_scale: 99
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
rgb_scale: 99
qos: 0
payload_on: "on"
payload_off: "off"
config with brightness and color temp
light:
platform: mqtt
name: "Office Light Color Temp"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_scale: 99
color_temp_state_topic: "office/rgb1/color_temp/status"
color_temp_command_topic: "office/rgb1/color_temp/set"
qos: 0
payload_on: "on"
payload_off: "off"
config with brightness and effect
light:
platform: mqtt
name: "Office Light Color Temp"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_scale: 99
effect_state_topic: "office/rgb1/effect/status"
effect_command_topic: "office/rgb1/effect/set"
effect_list:
- rainbow
- colorloop
qos: 0
payload_on: "on"
payload_off: "off"
config for RGB Version with white value and scale:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
white_value_state_topic: "office/rgb1/white_value/status"
white_value_command_topic: "office/rgb1/white_value/set"
white_value_scale: 99
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
rgb_scale: 99
qos: 0
payload_on: "on"
payload_off: "off"
config for RGB Version with RGB command template:
light:
platform: mqtt
name: "Office Light RGB"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
rgb_state_topic: "office/rgb1/rgb/status"
rgb_command_topic: "office/rgb1/rgb/set"
rgb_command_template: "{{ '#%02x%02x%02x' | format(red, green, blue)}}"
qos: 0
payload_on: "on"
payload_off: "off"
Configuration for HS Version with brightness:
light:
platform: mqtt
name: "Office Light HS"
state_topic: "office/hs1/light/status"
command_topic: "office/hs1/light/switch"
brightness_state_topic: "office/hs1/brightness/status"
brightness_command_topic: "office/hs1/brightness/set"
hs_state_topic: "office/hs1/hs/status"
hs_command_topic: "office/hs1/hs/set"
qos: 0
payload_on: "on"
payload_off: "off"
Configuration with brightness command template:
light:
platform: mqtt
name: "Office Light"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
brightness_state_topic: "office/rgb1/brightness/status"
brightness_command_topic: "office/rgb1/brightness/set"
brightness_command_template: '{ "brightness": "{{ value }}" }'
qos: 0
payload_on: "on"
payload_off: "off"
Configuration with effect command template:
light:
platform: mqtt
name: "Office Light Color Temp"
state_topic: "office/rgb1/light/status"
command_topic: "office/rgb1/light/switch"
effect_state_topic: "office/rgb1/effect/status"
effect_command_topic: "office/rgb1/effect/set"
effect_command_template: '{ "effect": "{{ value }}" }'
effect_list:
- rainbow
- colorloop
qos: 0
payload_on: "on"
payload_off: "off"
"""
import copy
from unittest.mock import call, patch
import pytest
from homeassistant.components import light
from homeassistant.components.mqtt.light.schema_basic import (
CONF_BRIGHTNESS_COMMAND_TOPIC,
CONF_COLOR_TEMP_COMMAND_TOPIC,
CONF_EFFECT_COMMAND_TOPIC,
CONF_EFFECT_LIST,
CONF_HS_COMMAND_TOPIC,
CONF_RGB_COMMAND_TOPIC,
CONF_RGBW_COMMAND_TOPIC,
CONF_RGBWW_COMMAND_TOPIC,
CONF_WHITE_VALUE_COMMAND_TOPIC,
CONF_XY_COMMAND_TOPIC,
MQTT_LIGHT_ATTRIBUTES_BLOCKED,
)
from homeassistant.const import (
ATTR_ASSUMED_STATE,
ATTR_SUPPORTED_FEATURES,
STATE_OFF,
STATE_ON,
STATE_UNKNOWN,
)
import homeassistant.core as ha
from homeassistant.setup import async_setup_component
from .test_common import (
help_test_availability_when_connection_lost,
help_test_availability_without_topic,
help_test_custom_availability_payload,
help_test_default_availability_payload,
help_test_discovery_broken,
help_test_discovery_removal,
help_test_discovery_update,
help_test_discovery_update_attr,
help_test_discovery_update_unchanged,
help_test_encoding_subscribable_topics,
help_test_entity_debug_info_message,
help_test_entity_device_info_remove,
help_test_entity_device_info_update,
help_test_entity_device_info_with_connection,
help_test_entity_device_info_with_identifier,
help_test_entity_id_update_discovery_update,
help_test_entity_id_update_subscriptions,
help_test_publishing_with_custom_encoding,
help_test_reloadable,
help_test_reloadable_late,
help_test_setting_attribute_via_mqtt_json_message,
help_test_setting_attribute_with_template,
help_test_setting_blocked_attribute_via_mqtt_json_message,
help_test_setup_manual_entity_from_yaml,
help_test_unique_id,
help_test_update_with_json_attrs_bad_JSON,
help_test_update_with_json_attrs_not_dict,
)
from tests.common import assert_setup_component, async_fire_mqtt_message
from tests.components.light import common
DEFAULT_CONFIG = {
light.DOMAIN: {"platform": "mqtt", "name": "test", "command_topic": "test-topic"}
}
async def test_fail_setup_if_no_command_topic(hass, mqtt_mock_entry_no_yaml_config):
"""Test if command fails with command topic."""
assert await async_setup_component(
hass, light.DOMAIN, {light.DOMAIN: {"platform": "mqtt", "name": "test"}}
)
await hass.async_block_till_done()
await mqtt_mock_entry_no_yaml_config()
assert hass.states.get("light.test") is None
async def test_legacy_rgb_white_light(hass, mqtt_mock_entry_with_yaml_config):
"""Test legacy RGB + white light flags brightness support."""
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"white_value_command_topic": "test_light_rgb/white/set",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
expected_features = (
light.SUPPORT_COLOR | light.SUPPORT_BRIGHTNESS | light.SUPPORT_WHITE_VALUE
)
assert state.attributes.get(ATTR_SUPPORTED_FEATURES) == expected_features
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == ["hs", "rgbw"]
async def test_no_color_brightness_color_temp_hs_white_xy_if_no_topics(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test if there is no color and brightness if no topic."""
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == ["onoff"]
async_fire_mqtt_message(hass, "test_light_rgb/status", "ON")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "onoff"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == ["onoff"]
async_fire_mqtt_message(hass, "test_light_rgb/status", "OFF")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "None")
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
async def test_legacy_controlling_state_via_topic(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the controlling of the state via topic for legacy light (white_value)."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_state_topic": "test_light_rgb/white_value/status",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs", "rgbw"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 100
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("color_temp") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes["white_value"] == 100
assert light_state.attributes["color_temp"] == 300
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "rainbow")
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "rainbow"
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "125,125,125")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 187, 131)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "0")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 255, 255)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "0.675,0.322")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.672, 0.324)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_controlling_state_via_topic(hass, mqtt_mock_entry_with_yaml_config):
"""Test the controlling of the state via topic."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") == 100
assert light_state.attributes["color_temp"] == 300
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "rainbow")
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "rainbow"
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "125,125,125")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (125, 125, 125)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "80,40,20,10")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbw_color") == (80, 40, 20, 10)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "80,40,20,10,8")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbww_color") == (80, 40, 20, 10, 8)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "0.675,0.322")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.675, 0.322)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_legacy_invalid_state_via_topic(
hass, mqtt_mock_entry_with_yaml_config, caplog
):
"""Test handling of empty data via topic."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_state_topic": "test_light_rgb/white_value/status",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "255,255,255")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "255")
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "none")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 255, 255)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (0, 0)
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") == (0.323, 0.329)
async_fire_mqtt_message(hass, "test_light_rgb/status", "")
assert "Ignoring empty state message" in caplog.text
light_state = hass.states.get("light.test")
assert state.state == STATE_ON
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "")
assert "Ignoring empty brightness message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 255
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "")
assert "Ignoring empty effect message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "none"
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "")
assert "Ignoring empty rgb message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 255, 255)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "")
assert "Ignoring empty hs message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "bad,bad")
assert "Failed to parse hs state update" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "")
assert "Ignoring empty xy-color message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.323, 0.329)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "153")
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "255")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 254, 250)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") == 153
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (54.768, 1.6)
assert state.attributes.get("white_value") == 255
assert state.attributes.get("xy_color") == (0.326, 0.333)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "")
assert "Ignoring empty color temp message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["color_temp"] == 153
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", "")
assert "Ignoring empty white value message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["white_value"] == 255
async def test_invalid_state_via_topic(hass, mqtt_mock_entry_with_yaml_config, caplog):
"""Test handling of empty data via topic."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"color_mode_state_topic": "test_light_rgb/color_mode/status",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("xy_color") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgb")
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "255,255,255")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "255")
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "none")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 255, 255)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (0, 0)
assert state.attributes.get("xy_color") == (0.323, 0.329)
assert state.attributes.get("color_mode") == "rgb"
async_fire_mqtt_message(hass, "test_light_rgb/status", "")
assert "Ignoring empty state message" in caplog.text
light_state = hass.states.get("light.test")
assert state.state == STATE_ON
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "")
assert "Ignoring empty brightness message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 255
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "")
assert "Ignoring empty color mode message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "none"
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "")
assert "Ignoring empty effect message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "none"
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "")
assert "Ignoring empty rgb message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (255, 255, 255)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "")
assert "Ignoring empty hs message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "bad,bad")
assert "Failed to parse hs state update" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (0, 0)
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "")
assert "Ignoring empty xy-color message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.323, 0.329)
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "255,255,255,1")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbw")
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "")
assert "Ignoring empty rgbw message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbw_color") == (255, 255, 255, 1)
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "255,255,255,1,2")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbww")
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "")
assert "Ignoring empty rgbww message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbww_color") == (255, 255, 255, 1, 2)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "153")
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "color_temp")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (255, 254, 250)
assert state.attributes.get("brightness") == 255
assert state.attributes.get("color_temp") == 153
assert state.attributes.get("effect") == "none"
assert state.attributes.get("hs_color") == (54.768, 1.6)
assert state.attributes.get("xy_color") == (0.326, 0.333)
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "")
assert "Ignoring empty color temp message" in caplog.text
light_state = hass.states.get("light.test")
assert light_state.attributes["color_temp"] == 153
async def test_brightness_controlling_scale(hass, mqtt_mock_entry_with_yaml_config):
"""Test the brightness controlling scale."""
with assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_scale/status",
"command_topic": "test_scale/set",
"brightness_state_topic": "test_scale/brightness/status",
"brightness_command_topic": "test_scale/brightness/set",
"brightness_scale": "99",
"qos": 0,
"payload_on": "on",
"payload_off": "off",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_scale/status", "on")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") is None
async_fire_mqtt_message(hass, "test_scale/status", "off")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_scale/status", "on")
async_fire_mqtt_message(hass, "test_scale/brightness/status", "99")
light_state = hass.states.get("light.test")
assert light_state.attributes["brightness"] == 255
async def test_brightness_from_rgb_controlling_scale(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the brightness controlling scale."""
with assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_scale_rgb/status",
"command_topic": "test_scale_rgb/set",
"rgb_state_topic": "test_scale_rgb/rgb/status",
"rgb_command_topic": "test_scale_rgb/rgb/set",
"qos": 0,
"payload_on": "on",
"payload_off": "off",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_scale_rgb/status", "on")
async_fire_mqtt_message(hass, "test_scale_rgb/rgb/status", "255,0,0")
state = hass.states.get("light.test")
assert state.attributes.get("brightness") == 255
async_fire_mqtt_message(hass, "test_scale_rgb/rgb/status", "127,0,0")
state = hass.states.get("light.test")
assert state.attributes.get("brightness") == 127
async def test_legacy_white_value_controlling_scale(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the white_value controlling scale."""
with assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(
hass,
light.DOMAIN,
{
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_scale/status",
"command_topic": "test_scale/set",
"white_value_state_topic": "test_scale/white_value/status",
"white_value_command_topic": "test_scale/white_value/set",
"white_value_scale": "99",
"qos": 0,
"payload_on": "on",
"payload_off": "off",
}
},
)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("white_value") is None
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_scale/status", "on")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("white_value") is None
async_fire_mqtt_message(hass, "test_scale/status", "off")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_scale/status", "on")
async_fire_mqtt_message(hass, "test_scale/white_value/status", "99")
light_state = hass.states.get("light.test")
assert light_state.attributes["white_value"] == 255
async def test_legacy_controlling_state_via_topic_with_templates(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the setting of the state with a template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"effect_state_topic": "test_light_rgb/effect/status",
"hs_state_topic": "test_light_rgb/hs/status",
"rgb_state_topic": "test_light_rgb/rgb/status",
"white_value_state_topic": "test_light_rgb/white_value/status",
"xy_state_topic": "test_light_rgb/xy/status",
"state_value_template": "{{ value_json.hello }}",
"brightness_value_template": "{{ value_json.hello }}",
"color_temp_value_template": "{{ value_json.hello }}",
"effect_value_template": "{{ value_json.hello }}",
"hs_value_template": '{{ value_json.hello | join(",") }}',
"rgb_value_template": '{{ value_json.hello | join(",") }}',
"white_value_template": "{{ value_json.hello }}",
"xy_value_template": '{{ value_json.hello | join(",") }}',
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", '{"hello": [1, 2, 3]}')
async_fire_mqtt_message(hass, "test_light_rgb/status", '{"hello": "ON"}')
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", '{"hello": "50"}')
async_fire_mqtt_message(
hass, "test_light_rgb/color_temp/status", '{"hello": "300"}'
)
async_fire_mqtt_message(
hass, "test_light_rgb/effect/status", '{"hello": "rainbow"}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("rgb_color") == (84, 169, 255)
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") == "rainbow"
assert state.attributes.get("white_value") is None
async_fire_mqtt_message(
hass, "test_light_rgb/white_value/status", '{"hello": "75"}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("rgb_color") == (255, 187, 131)
assert state.attributes.get("color_temp") == 300
assert state.attributes.get("effect") == "rainbow"
assert state.attributes.get("white_value") == 75
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", '{"hello": [100,50]}')
async_fire_mqtt_message(hass, "test_light_rgb/white_value/status", '{"hello": "0"}')
state = hass.states.get("light.test")
assert state.attributes.get("hs_color") == (100, 50)
async_fire_mqtt_message(
hass, "test_light_rgb/xy/status", '{"hello": [0.123,0.123]}'
)
state = hass.states.get("light.test")
assert state.attributes.get("xy_color") == (0.14, 0.131)
async_fire_mqtt_message(hass, "test_light_rgb/status", '{"hello": null}')
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
async def test_controlling_state_via_topic_with_templates(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the setting of the state with a template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_command_topic": "test_light_rgb/rgbw/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/brightness/status",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"effect_state_topic": "test_light_rgb/effect/status",
"hs_state_topic": "test_light_rgb/hs/status",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"xy_state_topic": "test_light_rgb/xy/status",
"state_value_template": "{{ value_json.hello }}",
"brightness_value_template": "{{ value_json.hello }}",
"color_temp_value_template": "{{ value_json.hello }}",
"effect_value_template": "{{ value_json.hello }}",
"hs_value_template": '{{ value_json.hello | join(",") }}',
"rgb_value_template": '{{ value_json.hello | join(",") }}',
"rgbw_value_template": '{{ value_json.hello | join(",") }}',
"rgbww_value_template": '{{ value_json.hello | join(",") }}',
"xy_value_template": '{{ value_json.hello | join(",") }}',
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", '{"hello": [1, 2, 3]}')
async_fire_mqtt_message(hass, "test_light_rgb/status", '{"hello": "ON"}')
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", '{"hello": "50"}')
async_fire_mqtt_message(
hass, "test_light_rgb/effect/status", '{"hello": "rainbow"}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("rgb_color") == (1, 2, 3)
assert state.attributes.get("effect") == "rainbow"
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/rgbw/status", '{"hello": [1, 2, 3, 4]}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgbw_color") == (1, 2, 3, 4)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/rgbww/status", '{"hello": [1, 2, 3, 4, 5]}'
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgbww_color") == (1, 2, 3, 4, 5)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/color_temp/status", '{"hello": "300"}'
)
state = hass.states.get("light.test")
assert state.attributes.get("color_temp") == 300
assert state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", '{"hello": [100,50]}')
state = hass.states.get("light.test")
assert state.attributes.get("hs_color") == (100, 50)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/xy/status", '{"hello": [0.123,0.123]}'
)
state = hass.states.get("light.test")
assert state.attributes.get("xy_color") == (0.123, 0.123)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_legacy_sending_mqtt_commands_and_optimistic(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of command in optimistic mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"effect_list": ["colorloop", "random"],
"qos": 2,
"payload_on": "on",
"payload_off": "off",
}
}
color_modes = ["color_temp", "hs", "rgbw"]
fake_state = ha.State(
"light.test",
"on",
{
"brightness": 95,
"hs_color": [100, 100],
"effect": "random",
"color_temp": 100,
# TODO: Test restoring state with white_value
"white_value": 0,
},
)
with patch(
"homeassistant.helpers.restore_state.RestoreEntity.async_get_last_state",
return_value=fake_state,
), assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 95
assert state.attributes.get("hs_color") == (100, 100)
assert state.attributes.get("effect") == "random"
assert state.attributes.get("color_temp") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get(ATTR_ASSUMED_STATE)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"test_light_rgb/set", "on", 2, False
)
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"test_light_rgb/set", "off", 2, False
)
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_OFF
mqtt_mock.reset_mock()
await common.async_turn_on(
hass, "light.test", brightness=50, xy_color=[0.123, 0.123]
)
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", brightness=50, hs_color=[359, 78])
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/rgb/set", "255,128,0", 2, False),
call("test_light_rgb/brightness/set", "50", 2, False),
call("test_light_rgb/hs/set", "359.0,78.0", 2, False),
call("test_light_rgb/xy/set", "0.14,0.131", 2, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgb_color"] == (255, 128, 0)
assert state.attributes["brightness"] == 50
assert state.attributes["hs_color"] == (30.118, 100)
assert state.attributes.get("white_value") is None
assert state.attributes["xy_color"] == (0.611, 0.375)
assert state.attributes.get("color_temp") is None
await common.async_turn_on(hass, "light.test", white_value=80, color_temp=125)
state = hass.states.get("light.test")
assert state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/white_value/set", "80", 2, False),
call("test_light_rgb/color_temp/set", "125", 2, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") == (221, 229, 255)
assert state.attributes["brightness"] == 50
assert state.attributes.get("hs_color") == (224.772, 13.249)
assert state.attributes["white_value"] == 80
assert state.attributes.get("xy_color") == (0.296, 0.301)
assert state.attributes["color_temp"] == 125
async def test_sending_mqtt_commands_and_optimistic(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of command in optimistic mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_command_topic": "test_light_rgb/xy/set",
"effect_list": ["colorloop", "random"],
"qos": 2,
"payload_on": "on",
"payload_off": "off",
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
fake_state = ha.State(
"light.test",
"on",
{
"brightness": 95,
"hs_color": [100, 100],
"effect": "random",
"color_temp": 100,
"color_mode": "hs",
},
)
with patch(
"homeassistant.helpers.restore_state.RestoreEntity.async_get_last_state",
return_value=fake_state,
), assert_setup_component(1, light.DOMAIN):
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 95
assert state.attributes.get("hs_color") == (100, 100)
assert state.attributes.get("effect") == "random"
assert state.attributes.get("color_temp") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert state.attributes.get(ATTR_ASSUMED_STATE)
await common.async_turn_on(hass, "light.test", effect="colorloop")
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/effect/set", "colorloop", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 2
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("effect") == "colorloop"
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"test_light_rgb/set", "off", 2, False
)
mqtt_mock.async_publish.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_OFF
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(
hass, "light.test", brightness=10, rgb_color=[80, 40, 20]
)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "10", 2, False),
call("test_light_rgb/rgb/set", "80,40,20", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 10
assert state.attributes.get("rgb_color") == (80, 40, 20)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(
hass, "light.test", brightness=20, rgbw_color=[80, 40, 20, 10]
)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "20", 2, False),
call("test_light_rgb/rgbw/set", "80,40,20,10", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 20
assert state.attributes.get("rgbw_color") == (80, 40, 20, 10)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(
hass, "light.test", brightness=40, rgbww_color=[80, 40, 20, 10, 8]
)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "40", 2, False),
call("test_light_rgb/rgbww/set", "80,40,20,10,8", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 40
assert state.attributes.get("rgbww_color") == (80, 40, 20, 10, 8)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", brightness=50, hs_color=[359, 78])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "50", 2, False),
call("test_light_rgb/hs/set", "359.0,78.0", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 50
assert state.attributes.get("hs_color") == (359.0, 78.0)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", brightness=60, xy_color=[0.2, 0.3])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 2, False),
call("test_light_rgb/brightness/set", "60", 2, False),
call("test_light_rgb/xy/set", "0.2,0.3", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 3
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 60
assert state.attributes.get("xy_color") == (0.2, 0.3)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
await common.async_turn_on(hass, "light.test", color_temp=125)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/color_temp/set", "125", 2, False),
],
any_order=True,
)
assert mqtt_mock.async_publish.call_count == 2
mqtt_mock.reset_mock()
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 60
assert state.attributes.get("color_temp") == 125
assert state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_sending_mqtt_rgb_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of RGB command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgb_command_template": '{{ "#%02x%02x%02x" | '
"format(red, green, blue)}}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 64])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 0, False),
call("test_light_rgb/rgb/set", "#ff8040", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgb_color"] == (255, 128, 64)
async def test_sending_mqtt_rgbw_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of RGBW command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbw_command_template": '{{ "#%02x%02x%02x%02x" | '
"format(red, green, blue, white)}}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", rgbw_color=[255, 128, 64, 32])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 0, False),
call("test_light_rgb/rgbw/set", "#ff804020", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgbw_color"] == (255, 128, 64, 32)
async def test_sending_mqtt_rgbww_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of RGBWW command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_rgb/set",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"rgbww_command_template": '{{ "#%02x%02x%02x%02x%02x" | '
"format(red, green, blue, cold_white, warm_white)}}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", rgbww_color=[255, 128, 64, 32, 16])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_rgb/set", "on", 0, False),
call("test_light_rgb/rgbww/set", "#ff80402010", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["rgbww_color"] == (255, 128, 64, 32, 16)
async def test_sending_mqtt_color_temp_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of Color Temp command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_color_temp/set",
"color_temp_command_topic": "test_light_color_temp/color_temp/set",
"color_temp_command_template": "{{ (1000 / value) | round(0) }}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", color_temp=100)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_color_temp/set", "on", 0, False),
call("test_light_color_temp/color_temp/set", "10", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["color_temp"] == 100
async def test_on_command_first(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command being sent before brightness."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
"on_command_type": "first",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=50)
# Should get the following MQTT messages.
# test_light/set: 'ON'
# test_light/bright: 50
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/set", "ON", 0, False),
call("test_light/bright", "50", 0, False),
],
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_last(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command being sent after brightness."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=50)
# Should get the following MQTT messages.
# test_light/bright: 50
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/bright", "50", 0, False),
call("test_light/set", "ON", 0, False),
],
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_brightness(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command being sent as only brightness."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
"rgb_command_topic": "test_light/rgb",
"on_command_type": "brightness",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
# Turn on w/ no brightness - should set to max
await common.async_turn_on(hass, "light.test")
# Should get the following MQTT messages.
# test_light/bright: 255
mqtt_mock.async_publish.assert_called_once_with(
"test_light/bright", "255", 0, False
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ brightness
await common.async_turn_on(hass, "light.test", brightness=50)
mqtt_mock.async_publish.assert_called_once_with("test_light/bright", "50", 0, False)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
# Turn on w/ just a color to ensure brightness gets
# added and sent.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/bright", "50", 0, False),
],
any_order=True,
)
async def test_on_command_brightness_scaled(hass, mqtt_mock_entry_with_yaml_config):
"""Test brightness scale."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"brightness_command_topic": "test_light/bright",
"brightness_scale": 100,
"rgb_command_topic": "test_light/rgb",
"on_command_type": "brightness",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
# Turn on w/ no brightness - should set to max
await common.async_turn_on(hass, "light.test")
# Should get the following MQTT messages.
# test_light/bright: 100
mqtt_mock.async_publish.assert_called_once_with(
"test_light/bright", "100", 0, False
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ brightness
await common.async_turn_on(hass, "light.test", brightness=50)
mqtt_mock.async_publish.assert_called_once_with("test_light/bright", "20", 0, False)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ max brightness
await common.async_turn_on(hass, "light.test", brightness=255)
mqtt_mock.async_publish.assert_called_once_with(
"test_light/bright", "100", 0, False
)
mqtt_mock.async_publish.reset_mock()
# Turn on w/ min brightness
await common.async_turn_on(hass, "light.test", brightness=1)
mqtt_mock.async_publish.assert_called_once_with("test_light/bright", "1", 0, False)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
# Turn on w/ just a color to ensure brightness gets
# added and sent.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/bright", "1", 0, False),
],
any_order=True,
)
async def test_legacy_on_command_rgb(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGB brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgb_command_topic": "test_light/rgb",
"white_value_command_topic": "test_light/white_value",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgb: '1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,128,0'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgb(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGB brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgb_command_topic": "test_light/rgb",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgb: '1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgb_color=[255, 128, 0])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "1,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgb: '255,128,0'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "255,128,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgbw(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBW brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbw_command_topic": "test_light/rgbw",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgbw: '127,127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "127,127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbw: '255,255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "255,255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgbw: '1,1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "1,1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgbw_color=[255, 128, 0, 16])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "1,0,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbw: '255,128,0'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "255,128,0,16", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgbww(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBWW brightness mode."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbww_command_topic": "test_light/rgbww",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgbww: '127,127,127,127,127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "127,127,127,127,127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbww: '255,255,255,255,255'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "255,255,255,255,255", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=1)
# Should get the following MQTT messages.
# test_light/rgbww: '1,1,1,1,1'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "1,1,1,1,1", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
# Ensure color gets scaled with brightness.
await common.async_turn_on(hass, "light.test", rgbww_color=[255, 128, 0, 16, 32])
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "1,0,0,0,0", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", brightness=255)
# Should get the following MQTT messages.
# test_light/rgbww: '255,128,0,16,32'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "255,128,0,16,32", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
async def test_on_command_rgb_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGB brightness mode with RGB template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgb_command_topic": "test_light/rgb",
"rgb_command_template": "{{ red }}/{{ green }}/{{ blue }}",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127/127/127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgb", "127/127/127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_rgbw_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBW brightness mode with RGBW template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbw_command_topic": "test_light/rgbw",
"rgbw_command_template": "{{ red }}/{{ green }}/{{ blue }}/{{ white }}",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127/127/127/127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbw", "127/127/127/127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_rgbww_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test on command in RGBWW brightness mode with RGBWW template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"rgbww_command_topic": "test_light/rgbww",
"rgbww_command_template": "{{ red }}/{{ green }}/{{ blue }}/{{ cold_white }}/{{ warm_white }}",
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=127)
# Should get the following MQTT messages.
# test_light/rgb: '127/127/127/127/127'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/rgbww", "127/127/127/127/127", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_on_command_white(hass, mqtt_mock_entry_with_yaml_config):
"""Test sending commands for RGB + white light."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "tasmota_B94927/cmnd/POWER",
"state_value_template": "{{ value_json.POWER }}",
"payload_off": "OFF",
"payload_on": "ON",
"brightness_command_topic": "tasmota_B94927/cmnd/Dimmer",
"brightness_scale": 100,
"on_command_type": "brightness",
"brightness_value_template": "{{ value_json.Dimmer }}",
"rgb_command_topic": "tasmota_B94927/cmnd/Color2",
"rgb_value_template": "{{value_json.Color.split(',')[0:3]|join(',')}}",
"white_command_topic": "tasmota_B94927/cmnd/White",
"white_scale": 100,
"color_mode_value_template": "{% if value_json.White %} white {% else %} rgb {% endif %}",
"qos": "0",
}
}
color_modes = ["rgb", "white"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert state.attributes.get(ATTR_ASSUMED_STATE)
await common.async_turn_on(hass, "light.test", brightness=192)
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/Dimmer", "75", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", white=255)
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/White", "100", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test", white=64)
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/White", "25", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_on(hass, "light.test")
mqtt_mock.async_publish.assert_has_calls(
[
call("tasmota_B94927/cmnd/Dimmer", "25", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with(
"tasmota_B94927/cmnd/POWER", "OFF", 0, False
)
async def test_explicit_color_mode(hass, mqtt_mock_entry_with_yaml_config):
"""Test explicit color mode over mqtt."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"color_mode_state_topic": "test_light_rgb/color_mode/status",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"rgb_state_topic": "test_light_rgb/rgb/status",
"rgb_command_topic": "test_light_rgb/rgb/set",
"rgbw_state_topic": "test_light_rgb/rgbw/status",
"rgbw_command_topic": "test_light_rgb/rgbw/set",
"rgbww_state_topic": "test_light_rgb/rgbww/status",
"rgbww_command_topic": "test_light_rgb/rgbww/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"effect_state_topic": "test_light_rgb/effect/status",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"xy_state_topic": "test_light_rgb/xy/status",
"xy_command_topic": "test_light_rgb/xy/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs", "rgb", "rgbw", "rgbww", "xy"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("effect") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get("rgbw_color") is None
assert state.attributes.get("rgbww_color") is None
assert state.attributes.get("white_value") is None
assert state.attributes.get("xy_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/effect/status", "rainbow")
light_state = hass.states.get("light.test")
assert light_state.attributes["effect"] == "rainbow"
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgb/status", "125,125,125")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbw/status", "80,40,20,10")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/rgbww/status", "80,40,20,10,8")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/xy/status", "0.675,0.322")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "color_temp")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgb")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgb_color") == (125, 125, 125)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbw")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbw_color") == (80, 40, 20, 10)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbw"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "rgbww")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("rgbww_color") == (80, 40, 20, 10, 8)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "rgbww"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "hs")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_mode/status", "xy")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("xy_color") == (0.675, 0.322)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "xy"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_explicit_color_mode_templated(hass, mqtt_mock_entry_with_yaml_config):
"""Test templated explicit color mode over mqtt."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "test_light_rgb/status",
"command_topic": "test_light_rgb/set",
"color_mode_state_topic": "test_light_rgb/color_mode/status",
"color_mode_value_template": "{{ value_json.color_mode }}",
"brightness_state_topic": "test_light_rgb/brightness/status",
"brightness_command_topic": "test_light_rgb/brightness/set",
"color_temp_state_topic": "test_light_rgb/color_temp/status",
"color_temp_command_topic": "test_light_rgb/color_temp/set",
"hs_state_topic": "test_light_rgb/hs/status",
"hs_command_topic": "test_light_rgb/hs/set",
"qos": "0",
"payload_on": 1,
"payload_off": 0,
}
}
color_modes = ["color_temp", "hs"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") is None
assert state.attributes.get("color_temp") is None
assert state.attributes.get("hs_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/status", "0")
state = hass.states.get("light.test")
assert state.state == STATE_OFF
async_fire_mqtt_message(hass, "test_light_rgb/status", "1")
async_fire_mqtt_message(hass, "test_light_rgb/brightness/status", "100")
light_state = hass.states.get("light.test")
assert light_state.attributes.get("brightness") is None
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/color_temp/status", "300")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(hass, "test_light_rgb/hs/status", "200,50")
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "unknown"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/color_mode/status", '{"color_mode":"color_temp"}'
)
light_state = hass.states.get("light.test")
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "color_temp"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass, "test_light_rgb/color_mode/status", '{"color_mode":"hs"}'
)
light_state = hass.states.get("light.test")
assert light_state.attributes.get("hs_color") == (200, 50)
assert light_state.attributes.get(light.ATTR_COLOR_MODE) == "hs"
assert light_state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_white_state_update(hass, mqtt_mock_entry_with_yaml_config):
"""Test state updates for RGB + white light."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"state_topic": "tasmota_B94927/tele/STATE",
"command_topic": "tasmota_B94927/cmnd/POWER",
"state_value_template": "{{ value_json.POWER }}",
"payload_off": "OFF",
"payload_on": "ON",
"brightness_command_topic": "tasmota_B94927/cmnd/Dimmer",
"brightness_state_topic": "tasmota_B94927/tele/STATE",
"brightness_scale": 100,
"on_command_type": "brightness",
"brightness_value_template": "{{ value_json.Dimmer }}",
"rgb_command_topic": "tasmota_B94927/cmnd/Color2",
"rgb_state_topic": "tasmota_B94927/tele/STATE",
"rgb_value_template": "{{value_json.Color.split(',')[0:3]|join(',')}}",
"white_command_topic": "tasmota_B94927/cmnd/White",
"white_scale": 100,
"color_mode_state_topic": "tasmota_B94927/tele/STATE",
"color_mode_value_template": "{% if value_json.White %} white {% else %} rgb {% endif %}",
"qos": "0",
}
}
color_modes = ["rgb", "white"]
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
assert state.attributes.get("brightness") is None
assert state.attributes.get("rgb_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) is None
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
assert not state.attributes.get(ATTR_ASSUMED_STATE)
async_fire_mqtt_message(
hass,
"tasmota_B94927/tele/STATE",
'{"POWER":"ON","Dimmer":50,"Color":"0,0,0,128","White":50}',
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 128
assert state.attributes.get("rgb_color") is None
assert state.attributes.get(light.ATTR_COLOR_MODE) == "white"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async_fire_mqtt_message(
hass,
"tasmota_B94927/tele/STATE",
'{"POWER":"ON","Dimmer":50,"Color":"128,64,32,0","White":0}',
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("brightness") == 128
assert state.attributes.get("rgb_color") == (128, 64, 32)
assert state.attributes.get(light.ATTR_COLOR_MODE) == "rgb"
assert state.attributes.get(light.ATTR_SUPPORTED_COLOR_MODES) == color_modes
async def test_effect(hass, mqtt_mock_entry_with_yaml_config):
"""Test effect."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light/set",
"effect_command_topic": "test_light/effect/set",
"effect_list": ["rainbow", "colorloop"],
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", effect="rainbow")
# Should get the following MQTT messages.
# test_light/effect/set: 'rainbow'
# test_light/set: 'ON'
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light/effect/set", "rainbow", 0, False),
call("test_light/set", "ON", 0, False),
],
any_order=True,
)
mqtt_mock.async_publish.reset_mock()
await common.async_turn_off(hass, "light.test")
mqtt_mock.async_publish.assert_called_once_with("test_light/set", "OFF", 0, False)
async def test_availability_when_connection_lost(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test availability after MQTT disconnection."""
await help_test_availability_when_connection_lost(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_availability_without_topic(hass, mqtt_mock_entry_with_yaml_config):
"""Test availability without defined availability topic."""
await help_test_availability_without_topic(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_default_availability_payload(hass, mqtt_mock_entry_with_yaml_config):
"""Test availability by default payload with defined topic."""
await help_test_default_availability_payload(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_custom_availability_payload(hass, mqtt_mock_entry_with_yaml_config):
"""Test availability by custom payload with defined topic."""
await help_test_custom_availability_payload(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_setting_attribute_via_mqtt_json_message(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the setting of attribute via MQTT with JSON payload."""
await help_test_setting_attribute_via_mqtt_json_message(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_setting_blocked_attribute_via_mqtt_json_message(
hass, mqtt_mock_entry_no_yaml_config
):
"""Test the setting of attribute via MQTT with JSON payload."""
await help_test_setting_blocked_attribute_via_mqtt_json_message(
hass,
mqtt_mock_entry_no_yaml_config,
light.DOMAIN,
DEFAULT_CONFIG,
MQTT_LIGHT_ATTRIBUTES_BLOCKED,
)
async def test_setting_attribute_with_template(hass, mqtt_mock_entry_with_yaml_config):
"""Test the setting of attribute via MQTT with JSON payload."""
await help_test_setting_attribute_with_template(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_update_with_json_attrs_not_dict(
hass, mqtt_mock_entry_with_yaml_config, caplog
):
"""Test attributes get extracted from a JSON result."""
await help_test_update_with_json_attrs_not_dict(
hass, mqtt_mock_entry_with_yaml_config, caplog, light.DOMAIN, DEFAULT_CONFIG
)
async def test_update_with_json_attrs_bad_JSON(
hass, mqtt_mock_entry_with_yaml_config, caplog
):
"""Test attributes get extracted from a JSON result."""
await help_test_update_with_json_attrs_bad_JSON(
hass, mqtt_mock_entry_with_yaml_config, caplog, light.DOMAIN, DEFAULT_CONFIG
)
async def test_discovery_update_attr(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test update of discovered MQTTAttributes."""
await help_test_discovery_update_attr(
hass, mqtt_mock_entry_no_yaml_config, caplog, light.DOMAIN, DEFAULT_CONFIG
)
async def test_unique_id(hass, mqtt_mock_entry_with_yaml_config):
"""Test unique id option only creates one light per unique_id."""
config = {
light.DOMAIN: [
{
"platform": "mqtt",
"name": "Test 1",
"state_topic": "test-topic",
"command_topic": "test_topic",
"unique_id": "TOTALLY_UNIQUE",
},
{
"platform": "mqtt",
"name": "<NAME>",
"state_topic": "test-topic",
"command_topic": "test_topic",
"unique_id": "TOTALLY_UNIQUE",
},
]
}
await help_test_unique_id(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, config
)
async def test_discovery_removal_light(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test removal of discovered light."""
data = (
'{ "name": "test",'
' "state_topic": "test_topic",'
' "command_topic": "test_topic" }'
)
await help_test_discovery_removal(
hass, mqtt_mock_entry_no_yaml_config, caplog, light.DOMAIN, data
)
async def test_discovery_deprecated(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test discovery of mqtt light with deprecated platform option."""
await mqtt_mock_entry_no_yaml_config()
data = (
'{ "name": "Beer",' ' "platform": "mqtt",' ' "command_topic": "test_topic"}'
)
async_fire_mqtt_message(hass, "homeassistant/light/bla/config", data)
await hass.async_block_till_done()
state = hass.states.get("light.beer")
assert state is not None
assert state.name == "Beer"
async def test_discovery_update_light_topic_and_template(
hass, mqtt_mock_entry_no_yaml_config, caplog
):
"""Test update of discovered light."""
config1 = {
"name": "Beer",
"state_topic": "test_light_rgb/state1",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state1",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state1",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state1",
"color_temp_state_topic": "test_light_rgb/state1",
"effect_state_topic": "test_light_rgb/state1",
"hs_state_topic": "test_light_rgb/state1",
"rgb_state_topic": "test_light_rgb/state1",
"white_value_state_topic": "test_light_rgb/state1",
"xy_state_topic": "test_light_rgb/state1",
"state_value_template": "{{ value_json.state1.state }}",
"brightness_value_template": "{{ value_json.state1.brightness }}",
"color_temp_value_template": "{{ value_json.state1.ct }}",
"effect_value_template": "{{ value_json.state1.fx }}",
"hs_value_template": "{{ value_json.state1.hs }}",
"rgb_value_template": "{{ value_json.state1.rgb }}",
"white_value_template": "{{ value_json.state1.white }}",
"xy_value_template": "{{ value_json.state1.xy }}",
}
config2 = {
"name": "Milk",
"state_topic": "test_light_rgb/state2",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state2",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state2",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state2",
"color_temp_state_topic": "test_light_rgb/state2",
"effect_state_topic": "test_light_rgb/state2",
"hs_state_topic": "test_light_rgb/state2",
"rgb_state_topic": "test_light_rgb/state2",
"white_value_state_topic": "test_light_rgb/state2",
"xy_state_topic": "test_light_rgb/state2",
"state_value_template": "{{ value_json.state2.state }}",
"brightness_value_template": "{{ value_json.state2.brightness }}",
"color_temp_value_template": "{{ value_json.state2.ct }}",
"effect_value_template": "{{ value_json.state2.fx }}",
"hs_value_template": "{{ value_json.state2.hs }}",
"rgb_value_template": "{{ value_json.state2.rgb }}",
"white_value_template": "{{ value_json.state2.white }}",
"xy_value_template": "{{ value_json.state2.xy }}",
}
state_data1 = [
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "white":100, "fx":"cycle"}}',
)
],
"on",
[
("brightness", 100),
("color_temp", 123),
("white_value", 100),
("effect", "cycle"),
],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2", "white":0}}',
)
],
"on",
[("hs_color", (1, 2)), ("white_value", None)],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
)
],
"on",
[("rgb_color", (255, 127, 63))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"xy":"0.3, 0.4"}}',
)
],
"on",
[("xy_color", (0.3, 0.401))],
),
]
state_data2 = [
(
[
(
"test_light_rgb/state2",
'{"state2":{"state":"ON", "brightness":50, "ct":200, "white":50, "fx":"loop"}}',
)
],
"on",
[
("brightness", 50),
("color_temp", 200),
("white_value", 50),
("effect", "loop"),
],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
],
"on",
[("brightness", 50), ("color_temp", 200), ("effect", "loop")],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state1", '{"state2":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state2", '{"state1":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state2", '{"state2":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state2",
'{"state2":{"state":"ON", "hs":"1.2,2.2", "white":0}}',
)
],
"on",
[("hs_color", (1.2, 2.2)), ("white_value", None)],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "hs":"1,2"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"state":"ON", "hs":"1,2"}}',
),
],
"on",
[("hs_color", (1.2, 2.2))],
),
(
[
(
"test_light_rgb/state2",
'{"state2":{"rgb":"63,127,255"}}',
)
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"rgb":"255,127,63"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"rgb":"255,127,63"}}',
),
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state2",
'{"state2":{"xy":"0.4, 0.3"}}',
)
],
"on",
[("xy_color", (0.4, 0.3))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"white":50, "xy":"0.3, 0.4"}}',
),
(
"test_light_rgb/state1",
'{"state2":{"white":50, "xy":"0.3, 0.4"}}',
),
(
"test_light_rgb/state2",
'{"state1":{"white":50, "xy":"0.3, 0.4"}}',
),
],
"on",
[("xy_color", (0.4, 0.3))],
),
]
await help_test_discovery_update(
hass,
mqtt_mock_entry_no_yaml_config,
caplog,
light.DOMAIN,
config1,
config2,
state_data1=state_data1,
state_data2=state_data2,
)
async def test_discovery_update_light_template(
hass, mqtt_mock_entry_no_yaml_config, caplog
):
"""Test update of discovered light."""
config1 = {
"name": "Beer",
"state_topic": "test_light_rgb/state1",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state1",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state1",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state1",
"color_temp_state_topic": "test_light_rgb/state1",
"effect_state_topic": "test_light_rgb/state1",
"hs_state_topic": "test_light_rgb/state1",
"rgb_state_topic": "test_light_rgb/state1",
"white_value_state_topic": "test_light_rgb/state1",
"xy_state_topic": "test_light_rgb/state1",
"state_value_template": "{{ value_json.state1.state }}",
"brightness_value_template": "{{ value_json.state1.brightness }}",
"color_temp_value_template": "{{ value_json.state1.ct }}",
"effect_value_template": "{{ value_json.state1.fx }}",
"hs_value_template": "{{ value_json.state1.hs }}",
"rgb_value_template": "{{ value_json.state1.rgb }}",
"white_value_template": "{{ value_json.state1.white }}",
"xy_value_template": "{{ value_json.state1.xy }}",
}
config2 = {
"name": "Milk",
"state_topic": "test_light_rgb/state1",
"command_topic": "test_light_rgb/set",
"brightness_command_topic": "test_light_rgb/state1",
"rgb_command_topic": "test_light_rgb/rgb/set",
"color_temp_command_topic": "test_light_rgb/state1",
"effect_command_topic": "test_light_rgb/effect/set",
"hs_command_topic": "test_light_rgb/hs/set",
"white_value_command_topic": "test_light_rgb/white_value/set",
"xy_command_topic": "test_light_rgb/xy/set",
"brightness_state_topic": "test_light_rgb/state1",
"color_temp_state_topic": "test_light_rgb/state1",
"effect_state_topic": "test_light_rgb/state1",
"hs_state_topic": "test_light_rgb/state1",
"rgb_state_topic": "test_light_rgb/state1",
"white_value_state_topic": "test_light_rgb/state1",
"xy_state_topic": "test_light_rgb/state1",
"state_value_template": "{{ value_json.state2.state }}",
"brightness_value_template": "{{ value_json.state2.brightness }}",
"color_temp_value_template": "{{ value_json.state2.ct }}",
"effect_value_template": "{{ value_json.state2.fx }}",
"hs_value_template": "{{ value_json.state2.hs }}",
"rgb_value_template": "{{ value_json.state2.rgb }}",
"white_value_template": "{{ value_json.state2.white }}",
"xy_value_template": "{{ value_json.state2.xy }}",
}
state_data1 = [
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "white":100, "fx":"cycle"}}',
)
],
"on",
[
("brightness", 100),
("color_temp", 123),
("white_value", 100),
("effect", "cycle"),
],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2", "white":0}}',
)
],
"on",
[("hs_color", (1, 2))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
)
],
"on",
[("rgb_color", (255, 127, 63))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"white":0, "xy":"0.3, 0.4"}}',
)
],
"on",
[("white_value", None), ("xy_color", (0.3, 0.401))],
),
]
state_data2 = [
(
[
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "brightness":50, "ct":200, "white":50, "fx":"loop"}}',
)
],
"on",
[
("brightness", 50),
("color_temp", 200),
("white_value", 50),
("effect", "loop"),
],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "brightness":100, "ct":123, "fx":"cycle"}}',
),
],
"on",
[("brightness", 50), ("color_temp", 200), ("effect", "loop")],
),
(
[("test_light_rgb/state1", '{"state1":{"state":"OFF"}}')],
"on",
None,
),
(
[("test_light_rgb/state1", '{"state2":{"state":"OFF"}}')],
"off",
None,
),
(
[
(
"test_light_rgb/state1",
'{"state2":{"state":"ON", "hs":"1.2,2.2", "white":0}}',
)
],
"on",
[("hs_color", (1.2, 2.2))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"state":"ON", "hs":"1,2"}}',
)
],
"on",
[("hs_color", (1.2, 2.2))],
),
(
[
(
"test_light_rgb/state1",
'{"state2":{"rgb":"63,127,255"}}',
)
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"rgb":"255,127,63"}}',
)
],
"on",
[("rgb_color", (63, 127, 255))],
),
(
[
(
"test_light_rgb/state1",
'{"state2":{"xy":"0.4, 0.3"}}',
)
],
"on",
[("white_value", None), ("xy_color", (0.4, 0.3))],
),
(
[
(
"test_light_rgb/state1",
'{"state1":{"white":50, "xy":"0.3, 0.4"}}',
)
],
"on",
[("white_value", None), ("xy_color", (0.4, 0.3))],
),
]
await help_test_discovery_update(
hass,
mqtt_mock_entry_no_yaml_config,
caplog,
light.DOMAIN,
config1,
config2,
state_data1=state_data1,
state_data2=state_data2,
)
async def test_discovery_update_unchanged_light(
hass, mqtt_mock_entry_no_yaml_config, caplog
):
"""Test update of discovered light."""
data1 = (
'{ "name": "Beer",'
' "state_topic": "test_topic",'
' "command_topic": "test_topic" }'
)
with patch(
"homeassistant.components.mqtt.light.schema_basic.MqttLight.discovery_update"
) as discovery_update:
await help_test_discovery_update_unchanged(
hass,
mqtt_mock_entry_no_yaml_config,
caplog,
light.DOMAIN,
data1,
discovery_update,
)
@pytest.mark.no_fail_on_log_exception
async def test_discovery_broken(hass, mqtt_mock_entry_no_yaml_config, caplog):
"""Test handling of bad discovery message."""
data1 = '{ "name": "Beer" }'
data2 = (
'{ "name": "Milk",'
' "state_topic": "test_topic",'
' "command_topic": "test_topic" }'
)
await help_test_discovery_broken(
hass, mqtt_mock_entry_no_yaml_config, caplog, light.DOMAIN, data1, data2
)
async def test_entity_device_info_with_connection(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT light device registry integration."""
await help_test_entity_device_info_with_connection(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_device_info_with_identifier(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT light device registry integration."""
await help_test_entity_device_info_with_identifier(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_device_info_update(hass, mqtt_mock_entry_no_yaml_config):
"""Test device registry update."""
await help_test_entity_device_info_update(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_device_info_remove(hass, mqtt_mock_entry_no_yaml_config):
"""Test device registry remove."""
await help_test_entity_device_info_remove(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_id_update_subscriptions(hass, mqtt_mock_entry_with_yaml_config):
"""Test MQTT subscriptions are managed when entity_id is updated."""
await help_test_entity_id_update_subscriptions(
hass, mqtt_mock_entry_with_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_id_update_discovery_update(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT discovery update when entity_id is updated."""
await help_test_entity_id_update_discovery_update(
hass, mqtt_mock_entry_no_yaml_config, light.DOMAIN, DEFAULT_CONFIG
)
async def test_entity_debug_info_message(hass, mqtt_mock_entry_no_yaml_config):
"""Test MQTT debug info."""
await help_test_entity_debug_info_message(
hass,
mqtt_mock_entry_no_yaml_config,
light.DOMAIN,
DEFAULT_CONFIG,
light.SERVICE_TURN_ON,
)
async def test_max_mireds(hass, mqtt_mock_entry_with_yaml_config):
"""Test setting min_mireds and max_mireds."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_max_mireds/set",
"color_temp_command_topic": "test_max_mireds/color_temp/set",
"max_mireds": 370,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.attributes.get("min_mireds") == 153
assert state.attributes.get("max_mireds") == 370
@pytest.mark.parametrize(
"service,topic,parameters,payload,template,tpl_par,tpl_output",
[
(
light.SERVICE_TURN_ON,
"command_topic",
None,
"ON",
None,
None,
None,
),
(
light.SERVICE_TURN_ON,
"white_command_topic",
{"white": "255"},
255,
None,
None,
None,
),
(
light.SERVICE_TURN_ON,
"brightness_command_topic",
{"color_temp": "200", "brightness": "50"},
50,
"brightness_command_template",
"value",
b"5",
),
(
light.SERVICE_TURN_ON,
"effect_command_topic",
{"rgb_color": [255, 128, 0], "effect": "color_loop"},
"color_loop",
"effect_command_template",
"value",
b"c",
),
(
light.SERVICE_TURN_ON,
"color_temp_command_topic",
{"color_temp": "200"},
200,
"color_temp_command_template",
"value",
b"2",
),
(
light.SERVICE_TURN_ON,
"rgb_command_topic",
{"rgb_color": [255, 128, 0]},
"255,128,0",
"rgb_command_template",
"red",
b"2",
),
(
light.SERVICE_TURN_ON,
"hs_command_topic",
{"rgb_color": [255, 128, 0]},
"30.118,100.0",
None,
None,
None,
),
(
light.SERVICE_TURN_ON,
"xy_command_topic",
{"hs_color": [30.118, 100.0]},
"0.611,0.375",
None,
None,
None,
),
(
light.SERVICE_TURN_OFF,
"command_topic",
None,
"OFF",
None,
None,
None,
),
],
)
async def test_publishing_with_custom_encoding(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
service,
topic,
parameters,
payload,
template,
tpl_par,
tpl_output,
):
"""Test publishing MQTT payload with different encoding."""
domain = light.DOMAIN
config = copy.deepcopy(DEFAULT_CONFIG[domain])
if topic == "effect_command_topic":
config["effect_list"] = ["random", "color_loop"]
elif topic == "white_command_topic":
config["rgb_command_topic"] = "some-cmd-topic"
await help_test_publishing_with_custom_encoding(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
domain,
config,
service,
topic,
parameters,
payload,
template,
tpl_par=tpl_par,
tpl_output=tpl_output,
)
async def test_reloadable(hass, mqtt_mock_entry_with_yaml_config, caplog, tmp_path):
"""Test reloading the MQTT platform."""
domain = light.DOMAIN
config = DEFAULT_CONFIG[domain]
await help_test_reloadable(
hass, mqtt_mock_entry_with_yaml_config, caplog, tmp_path, domain, config
)
async def test_reloadable_late(hass, mqtt_client_mock, caplog, tmp_path):
"""Test reloading the MQTT platform with late entry setup."""
domain = light.DOMAIN
config = DEFAULT_CONFIG[domain]
await help_test_reloadable_late(hass, caplog, tmp_path, domain, config)
@pytest.mark.parametrize(
"topic,value,attribute,attribute_value,init_payload",
[
("state_topic", "ON", None, "on", None),
("brightness_state_topic", "60", "brightness", 60, ("state_topic", "ON")),
(
"color_mode_state_topic",
"200",
"color_mode",
"200",
("state_topic", "ON"),
),
("color_temp_state_topic", "200", "color_temp", 200, ("state_topic", "ON")),
("effect_state_topic", "random", "effect", "random", ("state_topic", "ON")),
("hs_state_topic", "200,50", "hs_color", (200, 50), ("state_topic", "ON")),
(
"xy_state_topic",
"128,128",
"xy_color",
(128, 128),
("state_topic", "ON"),
),
(
"rgb_state_topic",
"255,0,240",
"rgb_color",
(255, 0, 240),
("state_topic", "ON"),
),
],
)
async def test_encoding_subscribable_topics(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
topic,
value,
attribute,
attribute_value,
init_payload,
):
"""Test handling of incoming encoded payload."""
config = copy.deepcopy(DEFAULT_CONFIG[light.DOMAIN])
config[CONF_EFFECT_COMMAND_TOPIC] = "light/CONF_EFFECT_COMMAND_TOPIC"
config[CONF_RGB_COMMAND_TOPIC] = "light/CONF_RGB_COMMAND_TOPIC"
config[CONF_BRIGHTNESS_COMMAND_TOPIC] = "light/CONF_BRIGHTNESS_COMMAND_TOPIC"
config[CONF_COLOR_TEMP_COMMAND_TOPIC] = "light/CONF_COLOR_TEMP_COMMAND_TOPIC"
config[CONF_HS_COMMAND_TOPIC] = "light/CONF_HS_COMMAND_TOPIC"
config[CONF_RGB_COMMAND_TOPIC] = "light/CONF_RGB_COMMAND_TOPIC"
config[CONF_RGBW_COMMAND_TOPIC] = "light/CONF_RGBW_COMMAND_TOPIC"
config[CONF_RGBWW_COMMAND_TOPIC] = "light/CONF_RGBWW_COMMAND_TOPIC"
config[CONF_XY_COMMAND_TOPIC] = "light/CONF_XY_COMMAND_TOPIC"
config[CONF_EFFECT_LIST] = ["colorloop", "random"]
if attribute and attribute == "brightness":
config[CONF_WHITE_VALUE_COMMAND_TOPIC] = "light/CONF_WHITE_VALUE_COMMAND_TOPIC"
await help_test_encoding_subscribable_topics(
hass,
mqtt_mock_entry_with_yaml_config,
caplog,
light.DOMAIN,
config,
topic,
value,
attribute,
attribute_value,
init_payload,
)
async def test_sending_mqtt_brightness_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of Brightness command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_brightness/set",
"brightness_command_topic": "test_light_brightness/brightness/set",
"brightness_command_template": "{{ (1000 / value) | round(0) }}",
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", brightness=100)
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_brightness/set", "on", 0, False),
call("test_light_brightness/brightness/set", "10", 0, False),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes["brightness"] == 100
async def test_sending_mqtt_effect_command_with_template(
hass, mqtt_mock_entry_with_yaml_config
):
"""Test the sending of Effect command with template."""
config = {
light.DOMAIN: {
"platform": "mqtt",
"name": "test",
"command_topic": "test_light_brightness/set",
"brightness_command_topic": "test_light_brightness/brightness/set",
"effect_command_topic": "test_light_brightness/effect/set",
"effect_command_template": '{ "effect": "{{ value }}" }',
"effect_list": ["colorloop", "random"],
"payload_on": "on",
"payload_off": "off",
"qos": 0,
}
}
assert await async_setup_component(hass, light.DOMAIN, config)
await hass.async_block_till_done()
mqtt_mock = await mqtt_mock_entry_with_yaml_config()
state = hass.states.get("light.test")
assert state.state == STATE_UNKNOWN
await common.async_turn_on(hass, "light.test", effect="colorloop")
mqtt_mock.async_publish.assert_has_calls(
[
call("test_light_brightness/set", "on", 0, False),
call(
"test_light_brightness/effect/set",
'{ "effect": "colorloop" }',
0,
False,
),
],
any_order=True,
)
state = hass.states.get("light.test")
assert state.state == STATE_ON
assert state.attributes.get("effect") == "colorloop"
async def test_setup_manual_entity_from_yaml(hass):
"""Test setup manual configured MQTT entity."""
platform = light.DOMAIN
config = copy.deepcopy(DEFAULT_CONFIG[platform])
config["name"] = "test"
del config["platform"]
await help_test_setup_manual_entity_from_yaml(hass, platform, config)
assert hass.states.get(f"{platform}.test") is not None
|
en
| 0.76188
|
The tests for the MQTT light platform. Configuration for RGB Version with brightness: light: platform: mqtt name: "Office Light RGB" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" brightness_state_topic: "office/rgb1/brightness/status" brightness_command_topic: "office/rgb1/brightness/set" rgb_state_topic: "office/rgb1/rgb/status" rgb_command_topic: "office/rgb1/rgb/set" qos: 0 payload_on: "on" payload_off: "off" Configuration for XY Version with brightness: light: platform: mqtt name: "Office Light XY" state_topic: "office/xy1/light/status" command_topic: "office/xy1/light/switch" brightness_state_topic: "office/xy1/brightness/status" brightness_command_topic: "office/xy1/brightness/set" xy_state_topic: "office/xy1/xy/status" xy_command_topic: "office/xy1/xy/set" qos: 0 payload_on: "on" payload_off: "off" config without RGB: light: platform: mqtt name: "Office Light" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" brightness_state_topic: "office/rgb1/brightness/status" brightness_command_topic: "office/rgb1/brightness/set" qos: 0 payload_on: "on" payload_off: "off" config without RGB and brightness: light: platform: mqtt name: "Office Light" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" qos: 0 payload_on: "on" payload_off: "off" config for RGB Version with brightness and scale: light: platform: mqtt name: "Office Light RGB" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" brightness_state_topic: "office/rgb1/brightness/status" brightness_command_topic: "office/rgb1/brightness/set" brightness_scale: 99 rgb_state_topic: "office/rgb1/rgb/status" rgb_command_topic: "office/rgb1/rgb/set" rgb_scale: 99 qos: 0 payload_on: "on" payload_off: "off" config with brightness and color temp light: platform: mqtt name: "Office Light Color Temp" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" brightness_state_topic: "office/rgb1/brightness/status" brightness_command_topic: "office/rgb1/brightness/set" brightness_scale: 99 color_temp_state_topic: "office/rgb1/color_temp/status" color_temp_command_topic: "office/rgb1/color_temp/set" qos: 0 payload_on: "on" payload_off: "off" config with brightness and effect light: platform: mqtt name: "Office Light Color Temp" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" brightness_state_topic: "office/rgb1/brightness/status" brightness_command_topic: "office/rgb1/brightness/set" brightness_scale: 99 effect_state_topic: "office/rgb1/effect/status" effect_command_topic: "office/rgb1/effect/set" effect_list: - rainbow - colorloop qos: 0 payload_on: "on" payload_off: "off" config for RGB Version with white value and scale: light: platform: mqtt name: "Office Light RGB" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" white_value_state_topic: "office/rgb1/white_value/status" white_value_command_topic: "office/rgb1/white_value/set" white_value_scale: 99 rgb_state_topic: "office/rgb1/rgb/status" rgb_command_topic: "office/rgb1/rgb/set" rgb_scale: 99 qos: 0 payload_on: "on" payload_off: "off" config for RGB Version with RGB command template: light: platform: mqtt name: "Office Light RGB" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" rgb_state_topic: "office/rgb1/rgb/status" rgb_command_topic: "office/rgb1/rgb/set" rgb_command_template: "{{ '#%02x%02x%02x' | format(red, green, blue)}}" qos: 0 payload_on: "on" payload_off: "off" Configuration for HS Version with brightness: light: platform: mqtt name: "Office Light HS" state_topic: "office/hs1/light/status" command_topic: "office/hs1/light/switch" brightness_state_topic: "office/hs1/brightness/status" brightness_command_topic: "office/hs1/brightness/set" hs_state_topic: "office/hs1/hs/status" hs_command_topic: "office/hs1/hs/set" qos: 0 payload_on: "on" payload_off: "off" Configuration with brightness command template: light: platform: mqtt name: "Office Light" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" brightness_state_topic: "office/rgb1/brightness/status" brightness_command_topic: "office/rgb1/brightness/set" brightness_command_template: '{ "brightness": "{{ value }}" }' qos: 0 payload_on: "on" payload_off: "off" Configuration with effect command template: light: platform: mqtt name: "Office Light Color Temp" state_topic: "office/rgb1/light/status" command_topic: "office/rgb1/light/switch" effect_state_topic: "office/rgb1/effect/status" effect_command_topic: "office/rgb1/effect/set" effect_command_template: '{ "effect": "{{ value }}" }' effect_list: - rainbow - colorloop qos: 0 payload_on: "on" payload_off: "off" Test if command fails with command topic. Test legacy RGB + white light flags brightness support. Test if there is no color and brightness if no topic. Test the controlling of the state via topic for legacy light (white_value). Test the controlling of the state via topic. Test handling of empty data via topic. Test handling of empty data via topic. Test the brightness controlling scale. Test the brightness controlling scale. Test the white_value controlling scale. Test the setting of the state with a template. Test the setting of the state with a template. Test the sending of command in optimistic mode. # TODO: Test restoring state with white_value Test the sending of command in optimistic mode. Test the sending of RGB command with template. Test the sending of RGBW command with template. Test the sending of RGBWW command with template. Test the sending of Color Temp command with template. Test on command being sent before brightness. # Should get the following MQTT messages. # test_light/set: 'ON' # test_light/bright: 50 Test on command being sent after brightness. # Should get the following MQTT messages. # test_light/bright: 50 # test_light/set: 'ON' Test on command being sent as only brightness. # Turn on w/ no brightness - should set to max # Should get the following MQTT messages. # test_light/bright: 255 # Turn on w/ brightness # Turn on w/ just a color to ensure brightness gets # added and sent. Test brightness scale. # Turn on w/ no brightness - should set to max # Should get the following MQTT messages. # test_light/bright: 100 # Turn on w/ brightness # Turn on w/ max brightness # Turn on w/ min brightness # Turn on w/ just a color to ensure brightness gets # added and sent. Test on command in RGB brightness mode. # Should get the following MQTT messages. # test_light/rgb: '127,127,127' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgb: '255,255,255' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgb: '1,1,1' # test_light/set: 'ON' # Ensure color gets scaled with brightness. # Should get the following MQTT messages. # test_light/rgb: '255,128,0' # test_light/set: 'ON' Test on command in RGB brightness mode. # Should get the following MQTT messages. # test_light/rgb: '127,127,127' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgb: '255,255,255' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgb: '1,1,1' # test_light/set: 'ON' # Ensure color gets scaled with brightness. # Should get the following MQTT messages. # test_light/rgb: '255,128,0' # test_light/set: 'ON' Test on command in RGBW brightness mode. # Should get the following MQTT messages. # test_light/rgbw: '127,127,127,127' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgbw: '255,255,255,255' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgbw: '1,1,1,1' # test_light/set: 'ON' # Ensure color gets scaled with brightness. # Should get the following MQTT messages. # test_light/rgbw: '255,128,0' # test_light/set: 'ON' Test on command in RGBWW brightness mode. # Should get the following MQTT messages. # test_light/rgbww: '127,127,127,127,127' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgbww: '255,255,255,255,255' # test_light/set: 'ON' # Should get the following MQTT messages. # test_light/rgbww: '1,1,1,1,1' # test_light/set: 'ON' # Ensure color gets scaled with brightness. # Should get the following MQTT messages. # test_light/rgbww: '255,128,0,16,32' # test_light/set: 'ON' Test on command in RGB brightness mode with RGB template. # Should get the following MQTT messages. # test_light/rgb: '127/127/127' # test_light/set: 'ON' Test on command in RGBW brightness mode with RGBW template. # Should get the following MQTT messages. # test_light/rgb: '127/127/127/127' # test_light/set: 'ON' Test on command in RGBWW brightness mode with RGBWW template. # Should get the following MQTT messages. # test_light/rgb: '127/127/127/127/127' # test_light/set: 'ON' Test sending commands for RGB + white light. Test explicit color mode over mqtt. Test templated explicit color mode over mqtt. Test state updates for RGB + white light. Test effect. # Should get the following MQTT messages. # test_light/effect/set: 'rainbow' # test_light/set: 'ON' Test availability after MQTT disconnection. Test availability without defined availability topic. Test availability by default payload with defined topic. Test availability by custom payload with defined topic. Test the setting of attribute via MQTT with JSON payload. Test the setting of attribute via MQTT with JSON payload. Test the setting of attribute via MQTT with JSON payload. Test attributes get extracted from a JSON result. Test attributes get extracted from a JSON result. Test update of discovered MQTTAttributes. Test unique id option only creates one light per unique_id. Test removal of discovered light. Test discovery of mqtt light with deprecated platform option. Test update of discovered light. Test update of discovered light. Test update of discovered light. Test handling of bad discovery message. Test MQTT light device registry integration. Test MQTT light device registry integration. Test device registry update. Test device registry remove. Test MQTT subscriptions are managed when entity_id is updated. Test MQTT discovery update when entity_id is updated. Test MQTT debug info. Test setting min_mireds and max_mireds. Test publishing MQTT payload with different encoding. Test reloading the MQTT platform. Test reloading the MQTT platform with late entry setup. Test handling of incoming encoded payload. Test the sending of Brightness command with template. Test the sending of Effect command with template. Test setup manual configured MQTT entity.
| 1.755629
| 2
|
tools/telemetry/telemetry/core/platform/profiler/android_profiling_helper_unittest.py
|
tmpsantos/chromium
| 0
|
6625831
|
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import glob
import os
import pickle
import re
import shutil
import tempfile
import unittest
from telemetry import benchmark
from telemetry.core import util
from telemetry.core.platform.profiler import android_profiling_helper
from telemetry.unittest import simple_mock
from telemetry.unittest import tab_test_case
def _GetLibrariesMappedIntoProcesses(device, pids):
libs = set()
for pid in pids:
maps_file = '/proc/%d/maps' % pid
maps = device.ReadFile(maps_file, as_root=True)
for map_line in maps:
lib = re.match(r'.*\s(/.*[.]so)$', map_line)
if lib:
libs.add(lib.group(1))
return libs
class TestAndroidProfilingHelper(unittest.TestCase):
def testGetRequiredLibrariesForPerfProfile(self):
perf_output = os.path.join(
util.GetUnittestDataDir(), 'sample_perf_report_output.txt')
with open(perf_output) as f:
perf_output = f.read()
mock_popen = simple_mock.MockObject()
mock_popen.ExpectCall('communicate').WillReturn([None, perf_output])
mock_subprocess = simple_mock.MockObject()
mock_subprocess.ExpectCall(
'Popen').WithArgs(simple_mock.DONT_CARE).WillReturn(mock_popen)
mock_subprocess.SetAttribute('PIPE', simple_mock.MockObject())
real_subprocess = android_profiling_helper.subprocess
android_profiling_helper.subprocess = mock_subprocess
try:
libs = android_profiling_helper.GetRequiredLibrariesForPerfProfile('foo')
self.assertEqual(libs, set([
'/data/app-lib/com.google.android.apps.chrome-2/libchrome.2016.0.so',
'/system/lib/libart.so',
'/system/lib/libc.so',
'/system/lib/libm.so']))
finally:
android_profiling_helper.subprocess = real_subprocess
@benchmark.Enabled('android')
def testGetRequiredLibrariesForVTuneProfile(self):
vtune_db_output = os.path.join(
util.GetUnittestDataDir(), 'sample_vtune_db_output')
with open(vtune_db_output, 'rb') as f:
vtune_db_output = pickle.load(f)
mock_cursor = simple_mock.MockObject()
mock_cursor.ExpectCall(
'execute').WithArgs(simple_mock.DONT_CARE).WillReturn(vtune_db_output)
mock_conn = simple_mock.MockObject()
mock_conn.ExpectCall('cursor').WillReturn(mock_cursor)
mock_conn.ExpectCall('close')
mock_sqlite3 = simple_mock.MockObject()
mock_sqlite3.ExpectCall(
'connect').WithArgs(simple_mock.DONT_CARE).WillReturn(mock_conn)
real_sqlite3 = android_profiling_helper.sqlite3
android_profiling_helper.sqlite3 = mock_sqlite3
try:
libs = android_profiling_helper.GetRequiredLibrariesForVTuneProfile('foo')
self.assertEqual(libs, set([
'/data/app-lib/com.google.android.apps.chrome-1/libchrome.2019.0.so',
'/system/lib/libdvm.so',
'/system/lib/libc.so',
'/system/lib/libm.so']))
finally:
android_profiling_helper.sqlite3 = real_sqlite3
class TestAndroidProfilingHelperTabTestCase(tab_test_case.TabTestCase):
def setUp(self):
super(TestAndroidProfilingHelperTabTestCase, self).setUp()
# pylint: disable=W0212
browser_backend = self._browser._browser_backend
try:
self._device = browser_backend.adb.device()
except AttributeError:
pass
@benchmark.Enabled('android')
def testCreateSymFs(self):
# pylint: disable=W0212
browser_pid = self._browser._browser_backend.pid
pids = ([browser_pid] +
self._browser._platform_backend.GetChildPids(browser_pid))
libs = _GetLibrariesMappedIntoProcesses(self._device, pids)
assert libs
symfs_dir = tempfile.mkdtemp()
try:
kallsyms = android_profiling_helper.CreateSymFs(self._device, symfs_dir,
libs)
# Make sure we found at least one unstripped library.
unstripped_libs = glob.glob(os.path.join(symfs_dir,
'data', 'app-lib', '*', '*.so'))
assert unstripped_libs
# Check that we have kernel symbols.
assert os.path.exists(kallsyms)
# Check that all requested libraries are present.
for lib in libs:
assert os.path.exists(os.path.join(symfs_dir, lib[1:])), \
'%s not found in symfs' % lib
finally:
shutil.rmtree(symfs_dir)
@benchmark.Enabled('android')
def testGetToolchainBinaryPath(self):
with tempfile.NamedTemporaryFile() as libc:
self._device.PullFile('/system/lib/libc.so', libc.name)
path = android_profiling_helper.GetToolchainBinaryPath(libc.name,
'objdump')
assert os.path.exists(path)
|
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import glob
import os
import pickle
import re
import shutil
import tempfile
import unittest
from telemetry import benchmark
from telemetry.core import util
from telemetry.core.platform.profiler import android_profiling_helper
from telemetry.unittest import simple_mock
from telemetry.unittest import tab_test_case
def _GetLibrariesMappedIntoProcesses(device, pids):
libs = set()
for pid in pids:
maps_file = '/proc/%d/maps' % pid
maps = device.ReadFile(maps_file, as_root=True)
for map_line in maps:
lib = re.match(r'.*\s(/.*[.]so)$', map_line)
if lib:
libs.add(lib.group(1))
return libs
class TestAndroidProfilingHelper(unittest.TestCase):
def testGetRequiredLibrariesForPerfProfile(self):
perf_output = os.path.join(
util.GetUnittestDataDir(), 'sample_perf_report_output.txt')
with open(perf_output) as f:
perf_output = f.read()
mock_popen = simple_mock.MockObject()
mock_popen.ExpectCall('communicate').WillReturn([None, perf_output])
mock_subprocess = simple_mock.MockObject()
mock_subprocess.ExpectCall(
'Popen').WithArgs(simple_mock.DONT_CARE).WillReturn(mock_popen)
mock_subprocess.SetAttribute('PIPE', simple_mock.MockObject())
real_subprocess = android_profiling_helper.subprocess
android_profiling_helper.subprocess = mock_subprocess
try:
libs = android_profiling_helper.GetRequiredLibrariesForPerfProfile('foo')
self.assertEqual(libs, set([
'/data/app-lib/com.google.android.apps.chrome-2/libchrome.2016.0.so',
'/system/lib/libart.so',
'/system/lib/libc.so',
'/system/lib/libm.so']))
finally:
android_profiling_helper.subprocess = real_subprocess
@benchmark.Enabled('android')
def testGetRequiredLibrariesForVTuneProfile(self):
vtune_db_output = os.path.join(
util.GetUnittestDataDir(), 'sample_vtune_db_output')
with open(vtune_db_output, 'rb') as f:
vtune_db_output = pickle.load(f)
mock_cursor = simple_mock.MockObject()
mock_cursor.ExpectCall(
'execute').WithArgs(simple_mock.DONT_CARE).WillReturn(vtune_db_output)
mock_conn = simple_mock.MockObject()
mock_conn.ExpectCall('cursor').WillReturn(mock_cursor)
mock_conn.ExpectCall('close')
mock_sqlite3 = simple_mock.MockObject()
mock_sqlite3.ExpectCall(
'connect').WithArgs(simple_mock.DONT_CARE).WillReturn(mock_conn)
real_sqlite3 = android_profiling_helper.sqlite3
android_profiling_helper.sqlite3 = mock_sqlite3
try:
libs = android_profiling_helper.GetRequiredLibrariesForVTuneProfile('foo')
self.assertEqual(libs, set([
'/data/app-lib/com.google.android.apps.chrome-1/libchrome.2019.0.so',
'/system/lib/libdvm.so',
'/system/lib/libc.so',
'/system/lib/libm.so']))
finally:
android_profiling_helper.sqlite3 = real_sqlite3
class TestAndroidProfilingHelperTabTestCase(tab_test_case.TabTestCase):
def setUp(self):
super(TestAndroidProfilingHelperTabTestCase, self).setUp()
# pylint: disable=W0212
browser_backend = self._browser._browser_backend
try:
self._device = browser_backend.adb.device()
except AttributeError:
pass
@benchmark.Enabled('android')
def testCreateSymFs(self):
# pylint: disable=W0212
browser_pid = self._browser._browser_backend.pid
pids = ([browser_pid] +
self._browser._platform_backend.GetChildPids(browser_pid))
libs = _GetLibrariesMappedIntoProcesses(self._device, pids)
assert libs
symfs_dir = tempfile.mkdtemp()
try:
kallsyms = android_profiling_helper.CreateSymFs(self._device, symfs_dir,
libs)
# Make sure we found at least one unstripped library.
unstripped_libs = glob.glob(os.path.join(symfs_dir,
'data', 'app-lib', '*', '*.so'))
assert unstripped_libs
# Check that we have kernel symbols.
assert os.path.exists(kallsyms)
# Check that all requested libraries are present.
for lib in libs:
assert os.path.exists(os.path.join(symfs_dir, lib[1:])), \
'%s not found in symfs' % lib
finally:
shutil.rmtree(symfs_dir)
@benchmark.Enabled('android')
def testGetToolchainBinaryPath(self):
with tempfile.NamedTemporaryFile() as libc:
self._device.PullFile('/system/lib/libc.so', libc.name)
path = android_profiling_helper.GetToolchainBinaryPath(libc.name,
'objdump')
assert os.path.exists(path)
|
en
| 0.902095
|
# Copyright 2014 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. # pylint: disable=W0212 # pylint: disable=W0212 # Make sure we found at least one unstripped library. # Check that we have kernel symbols. # Check that all requested libraries are present.
| 1.95963
| 2
|
ansible/modules/utilities/helper/meta.py
|
EnjoyLifeFund/macHighSierra-py36-pkgs
| 1
|
6625832
|
<reponame>EnjoyLifeFund/macHighSierra-py36-pkgs
#!/usr/bin/python
# -*- coding: utf-8 -*-
# (c) 2016, Ansible, a Red Hat company
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'core'}
DOCUMENTATION = '''
module: meta
short_description: Execute Ansible 'actions'
version_added: "1.2"
description:
- Meta tasks are a special kind of task which can influence Ansible internal execution or state. Prior to Ansible 2.0,
the only meta option available was `flush_handlers`. As of 2.2, there are five meta tasks which can be used.
Meta tasks can be used anywhere within your playbook.
- This module is also supported for Windows targets.
options:
free_form:
description:
- This module takes a free form command, as a string. There's not an actual option named "free form". See the examples!
- >
C(flush_handlers) makes Ansible run any handler tasks which have thus far been notified. Ansible inserts these tasks internally at certain
points to implicitly trigger handler runs (after pre/post tasks, the final role execution, and the main tasks section of your plays).
- >
C(refresh_inventory) (added in 2.0) forces the reload of the inventory, which in the case of dynamic inventory scripts means they will be
re-executed. This is mainly useful when additional hosts are created and users wish to use them instead of using the `add_host` module."
- "C(noop) (added in 2.0) This literally does 'nothing'. It is mainly used internally and not recommended for general use."
- "C(clear_facts) (added in 2.1) causes the gathered facts for the hosts specified in the play's list of hosts to be cleared, including the fact cache."
- "C(clear_host_errors) (added in 2.1) clears the failed state (if any) from hosts specified in the play's list of hosts."
- "C(end_play) (added in 2.2) causes the play to end without failing the host."
- "C(reset_connection) (added in 2.3) interrupts a persistent connection (i.e. ssh + control persist)"
choices: ['noop', 'flush_handlers', 'refresh_inventory', 'clear_facts', 'clear_host_errors', 'end_play', 'reset_connection']
required: true
notes:
- C(meta) is not really a module nor action_plugin as such it cannot be overwritten.
- This module is also supported for Windows targets.
author:
- "Ansible Core Team"
'''
EXAMPLES = '''
- template:
src: new.j2
dest: /etc/config.txt
notify: myhandler
- name: force all notified handlers to run at this point, not waiting for normal sync points
meta: flush_handlers
- name: reload inventory, useful with dynamic inventories when play makes changes to the existing hosts
cloud_guest: # this is fake module
name: newhost
state: present
- name: Refresh inventory to ensure new instaces exist in inventory
meta: refresh_inventory
- name: Clear gathered facts from all currently targeted hosts
meta: clear_facts
- name: bring host back to play after failure
copy:
src: file
dest: /etc/file
remote_user: imightnothavepermission
- meta: clear_host_errors
- user: name={{ansible_user}} groups=input
- name: reset ssh connection to allow user changes to affect 'current login user'
meta: reset_connection
'''
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
# (c) 2016, Ansible, a Red Hat company
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'core'}
DOCUMENTATION = '''
module: meta
short_description: Execute Ansible 'actions'
version_added: "1.2"
description:
- Meta tasks are a special kind of task which can influence Ansible internal execution or state. Prior to Ansible 2.0,
the only meta option available was `flush_handlers`. As of 2.2, there are five meta tasks which can be used.
Meta tasks can be used anywhere within your playbook.
- This module is also supported for Windows targets.
options:
free_form:
description:
- This module takes a free form command, as a string. There's not an actual option named "free form". See the examples!
- >
C(flush_handlers) makes Ansible run any handler tasks which have thus far been notified. Ansible inserts these tasks internally at certain
points to implicitly trigger handler runs (after pre/post tasks, the final role execution, and the main tasks section of your plays).
- >
C(refresh_inventory) (added in 2.0) forces the reload of the inventory, which in the case of dynamic inventory scripts means they will be
re-executed. This is mainly useful when additional hosts are created and users wish to use them instead of using the `add_host` module."
- "C(noop) (added in 2.0) This literally does 'nothing'. It is mainly used internally and not recommended for general use."
- "C(clear_facts) (added in 2.1) causes the gathered facts for the hosts specified in the play's list of hosts to be cleared, including the fact cache."
- "C(clear_host_errors) (added in 2.1) clears the failed state (if any) from hosts specified in the play's list of hosts."
- "C(end_play) (added in 2.2) causes the play to end without failing the host."
- "C(reset_connection) (added in 2.3) interrupts a persistent connection (i.e. ssh + control persist)"
choices: ['noop', 'flush_handlers', 'refresh_inventory', 'clear_facts', 'clear_host_errors', 'end_play', 'reset_connection']
required: true
notes:
- C(meta) is not really a module nor action_plugin as such it cannot be overwritten.
- This module is also supported for Windows targets.
author:
- "Ansible Core Team"
'''
EXAMPLES = '''
- template:
src: new.j2
dest: /etc/config.txt
notify: myhandler
- name: force all notified handlers to run at this point, not waiting for normal sync points
meta: flush_handlers
- name: reload inventory, useful with dynamic inventories when play makes changes to the existing hosts
cloud_guest: # this is fake module
name: newhost
state: present
- name: Refresh inventory to ensure new instaces exist in inventory
meta: refresh_inventory
- name: Clear gathered facts from all currently targeted hosts
meta: clear_facts
- name: bring host back to play after failure
copy:
src: file
dest: /etc/file
remote_user: imightnothavepermission
- meta: clear_host_errors
- user: name={{ansible_user}} groups=input
- name: reset ssh connection to allow user changes to affect 'current login user'
meta: reset_connection
'''
|
en
| 0.828389
|
#!/usr/bin/python # -*- coding: utf-8 -*- # (c) 2016, Ansible, a Red Hat company # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) module: meta short_description: Execute Ansible 'actions' version_added: "1.2" description: - Meta tasks are a special kind of task which can influence Ansible internal execution or state. Prior to Ansible 2.0, the only meta option available was `flush_handlers`. As of 2.2, there are five meta tasks which can be used. Meta tasks can be used anywhere within your playbook. - This module is also supported for Windows targets. options: free_form: description: - This module takes a free form command, as a string. There's not an actual option named "free form". See the examples! - > C(flush_handlers) makes Ansible run any handler tasks which have thus far been notified. Ansible inserts these tasks internally at certain points to implicitly trigger handler runs (after pre/post tasks, the final role execution, and the main tasks section of your plays). - > C(refresh_inventory) (added in 2.0) forces the reload of the inventory, which in the case of dynamic inventory scripts means they will be re-executed. This is mainly useful when additional hosts are created and users wish to use them instead of using the `add_host` module." - "C(noop) (added in 2.0) This literally does 'nothing'. It is mainly used internally and not recommended for general use." - "C(clear_facts) (added in 2.1) causes the gathered facts for the hosts specified in the play's list of hosts to be cleared, including the fact cache." - "C(clear_host_errors) (added in 2.1) clears the failed state (if any) from hosts specified in the play's list of hosts." - "C(end_play) (added in 2.2) causes the play to end without failing the host." - "C(reset_connection) (added in 2.3) interrupts a persistent connection (i.e. ssh + control persist)" choices: ['noop', 'flush_handlers', 'refresh_inventory', 'clear_facts', 'clear_host_errors', 'end_play', 'reset_connection'] required: true notes: - C(meta) is not really a module nor action_plugin as such it cannot be overwritten. - This module is also supported for Windows targets. author: - "Ansible Core Team" - template: src: new.j2 dest: /etc/config.txt notify: myhandler - name: force all notified handlers to run at this point, not waiting for normal sync points meta: flush_handlers - name: reload inventory, useful with dynamic inventories when play makes changes to the existing hosts cloud_guest: # this is fake module name: newhost state: present - name: Refresh inventory to ensure new instaces exist in inventory meta: refresh_inventory - name: Clear gathered facts from all currently targeted hosts meta: clear_facts - name: bring host back to play after failure copy: src: file dest: /etc/file remote_user: imightnothavepermission - meta: clear_host_errors - user: name={{ansible_user}} groups=input - name: reset ssh connection to allow user changes to affect 'current login user' meta: reset_connection
| 1.769556
| 2
|
utils/helper.py
|
avalanchesiqi/twitter-sampling
| 1
|
6625833
|
<gh_stars>1-10
import time
from datetime import datetime, timedelta
class Timer:
def __init__(self):
self.start_time = None
def start(self):
self.start_time = time.time()
def stop(self):
print('>>> Elapsed time: {0}\n'.format(str(timedelta(seconds=time.time() - self.start_time))[:-3]))
def strify(iterable_obj, delimiter=','):
return delimiter.join(iterable_obj)
date_format = {'tweet': '%a %b %d %H:%M:%S %z %Y',
'youtube': '%Y-%m-%d'}
def str2obj(str, fmt='youtube'):
if fmt == 'tweet' or fmt == 'youtube':
return datetime.strptime(str, date_format[fmt])
else:
return datetime.strptime(str, fmt)
def obj2str(obj, fmt='youtube'):
if fmt == 'tweet' or fmt == 'youtube':
return obj.strftime(date_format[fmt])
else:
return obj.strftime(fmt)
# twitter's snowflake parameters
twepoch = 1288834974657
datacenter_id_bits = 5
worker_id_bits = 5
sequence_id_bits = 12
max_datacenter_id = 1 << datacenter_id_bits
max_worker_id = 1 << worker_id_bits
max_sequence_id = 1 << sequence_id_bits
max_timestamp = 1 << (64 - datacenter_id_bits - worker_id_bits - sequence_id_bits)
def make_snowflake(timestamp_ms, datacenter_id, worker_id, sequence_id, twepoch=twepoch):
"""generate a twitter-snowflake id, based on
https://github.com/twitter/snowflake/blob/master/src/main/scala/com/twitter/service/snowflake/IdWorker.scala
:param: timestamp_ms time since UNIX epoch in milliseconds"""
timestamp_ms = int(timestamp_ms)
sid = ((timestamp_ms - twepoch) % max_timestamp) << datacenter_id_bits << worker_id_bits << sequence_id_bits
sid += (datacenter_id % max_datacenter_id) << worker_id_bits << sequence_id_bits
sid += (worker_id % max_worker_id) << sequence_id_bits
sid += sequence_id % max_sequence_id
return sid
def melt_snowflake(snowflake_id, twepoch=twepoch):
"""inversely transform a snowflake id back to its components."""
snowflake_id = int(snowflake_id)
sequence_id = snowflake_id & (max_sequence_id - 1)
worker_id = (snowflake_id >> sequence_id_bits) & (max_worker_id - 1)
datacenter_id = (snowflake_id >> sequence_id_bits >> worker_id_bits) & (max_datacenter_id - 1)
timestamp_ms = snowflake_id >> sequence_id_bits >> worker_id_bits >> datacenter_id_bits
timestamp_ms += twepoch
return timestamp_ms, datacenter_id, worker_id, sequence_id
def count_track(track_list, start_with_rate=False, subcrawler=False):
if subcrawler:
total_track_cnt = 0
for i in range(len(track_list)):
total_track_cnt += count_track(track_list[i], start_with_rate=start_with_rate, subcrawler=False)
return total_track_cnt
else:
if len(track_list) == 0:
return 0
if start_with_rate:
track_cnt = -track_list[0]
else:
track_cnt = 0
if len(track_list) == 1:
return track_cnt + track_list[0]
for i in range(len(track_list) - 1):
if track_list[i + 1] <= track_list[i]:
track_cnt += track_list[i]
track_cnt += track_list[-1]
return track_cnt
|
import time
from datetime import datetime, timedelta
class Timer:
def __init__(self):
self.start_time = None
def start(self):
self.start_time = time.time()
def stop(self):
print('>>> Elapsed time: {0}\n'.format(str(timedelta(seconds=time.time() - self.start_time))[:-3]))
def strify(iterable_obj, delimiter=','):
return delimiter.join(iterable_obj)
date_format = {'tweet': '%a %b %d %H:%M:%S %z %Y',
'youtube': '%Y-%m-%d'}
def str2obj(str, fmt='youtube'):
if fmt == 'tweet' or fmt == 'youtube':
return datetime.strptime(str, date_format[fmt])
else:
return datetime.strptime(str, fmt)
def obj2str(obj, fmt='youtube'):
if fmt == 'tweet' or fmt == 'youtube':
return obj.strftime(date_format[fmt])
else:
return obj.strftime(fmt)
# twitter's snowflake parameters
twepoch = 1288834974657
datacenter_id_bits = 5
worker_id_bits = 5
sequence_id_bits = 12
max_datacenter_id = 1 << datacenter_id_bits
max_worker_id = 1 << worker_id_bits
max_sequence_id = 1 << sequence_id_bits
max_timestamp = 1 << (64 - datacenter_id_bits - worker_id_bits - sequence_id_bits)
def make_snowflake(timestamp_ms, datacenter_id, worker_id, sequence_id, twepoch=twepoch):
"""generate a twitter-snowflake id, based on
https://github.com/twitter/snowflake/blob/master/src/main/scala/com/twitter/service/snowflake/IdWorker.scala
:param: timestamp_ms time since UNIX epoch in milliseconds"""
timestamp_ms = int(timestamp_ms)
sid = ((timestamp_ms - twepoch) % max_timestamp) << datacenter_id_bits << worker_id_bits << sequence_id_bits
sid += (datacenter_id % max_datacenter_id) << worker_id_bits << sequence_id_bits
sid += (worker_id % max_worker_id) << sequence_id_bits
sid += sequence_id % max_sequence_id
return sid
def melt_snowflake(snowflake_id, twepoch=twepoch):
"""inversely transform a snowflake id back to its components."""
snowflake_id = int(snowflake_id)
sequence_id = snowflake_id & (max_sequence_id - 1)
worker_id = (snowflake_id >> sequence_id_bits) & (max_worker_id - 1)
datacenter_id = (snowflake_id >> sequence_id_bits >> worker_id_bits) & (max_datacenter_id - 1)
timestamp_ms = snowflake_id >> sequence_id_bits >> worker_id_bits >> datacenter_id_bits
timestamp_ms += twepoch
return timestamp_ms, datacenter_id, worker_id, sequence_id
def count_track(track_list, start_with_rate=False, subcrawler=False):
if subcrawler:
total_track_cnt = 0
for i in range(len(track_list)):
total_track_cnt += count_track(track_list[i], start_with_rate=start_with_rate, subcrawler=False)
return total_track_cnt
else:
if len(track_list) == 0:
return 0
if start_with_rate:
track_cnt = -track_list[0]
else:
track_cnt = 0
if len(track_list) == 1:
return track_cnt + track_list[0]
for i in range(len(track_list) - 1):
if track_list[i + 1] <= track_list[i]:
track_cnt += track_list[i]
track_cnt += track_list[-1]
return track_cnt
|
en
| 0.624142
|
# twitter's snowflake parameters generate a twitter-snowflake id, based on https://github.com/twitter/snowflake/blob/master/src/main/scala/com/twitter/service/snowflake/IdWorker.scala :param: timestamp_ms time since UNIX epoch in milliseconds inversely transform a snowflake id back to its components.
| 3.197995
| 3
|
app/gui.py
|
jakubsolecki/Team-Locator
| 0
|
6625834
|
from time import sleep
from kivy.app import App
from kivy.properties import ObjectProperty, StringProperty
from kivy.uix.gridlayout import GridLayout
from kivy.uix.screenmanager import ScreenManager, Screen
from kivy.uix.treeview import TreeViewLabel
from kivy.uix.popup import Popup
from kivy.uix.floatlayout import FloatLayout
from kivy.uix.widget import Widget
from kivy.utils import get_color_from_hex
from kivy.metrics import *
from client import Client # from app.client import Client
from colordict import color_dictionary
from gpsblinker import GpsBlinker
from kivy.storage.jsonstore import JsonStore
import atexit
import os
import glob
from returnbinder import ReturnBinder
class WindowManager(ScreenManager):
pass
class MapWindow(Screen):
pass
class TokenWindow(Screen):
nick = ObjectProperty(None)
code = ObjectProperty(None)
ip_address = ObjectProperty(None)
client = Client.get_instance()
colornum = 10 # Expected to change. If players stay black something is wrong
current_blinker = None
stored_data = JsonStore('data.json')
def __disconnect(self):
files = glob.glob('cache/*.png')
for f in files:
if not f.endswith(".png"): # Additional safety, should never happen
print("ERROR WHILE CLEARING CACHE, FOUND NON-PNG FILE, ABORTING")
break
os.remove(f)
self.client.send_message(self.client.DISCONNECT_MESSAGE, self.code.text)
sleep(1)
def __connect(self):
if 'host-' in self.nick.text or ':' in self.nick.text or\
len(self.nick.text) >= 16 or\
len(self.code.text) > 10 or\
len(self.ip_address.text) > 16:
return
self.client.connect(server_ip=self.ip_address.text)
# after pressing "Host Game" button:
def host_connect(self):
self.__connect()
if not self.client.is_connected():
return
atexit.register(self.__disconnect)
screen = App.get_running_app().root
screen.current = "host"
ReturnBinder.get_instance().current_screen = "host"
self.stored_data.clear()
self.stored_data.put('credentials', ip_address=self.ip_address.text, nick=self.nick.text)
# after pressing "Connect Game" button:
def player_connect(self):
self.__connect()
if not self.client.is_connected():
return
atexit.register(self.__disconnect)
message = self.code.text + ":" + self.nick.text
print("Message being sent to server: " + message)
self.client.send_message(self.client.INIT_MESSAGE, message)
sleep(1)
if self.client.get_token() is None:
return
# Takes first letter as number from 0 to 9: || #1ABCD means color 1 ||
if len(self.code.text) >= 1 and self.code.text[0].isdigit():
self.colornum = int(self.code.text[0])
# GPS always starts in AGH WIEiT faculty building
self.current_blinker = blinker = GpsBlinker(lon=19.9125399, lat=50.0680966,
nick=self.nick.text, color_number=self.colornum)
team_map = App.get_running_app().root.ids.mw.ids.map
team_map.add_widget(blinker)
team_map.start_checking = True
blinker.blink()
App.get_running_app().gps_mod.start_updating(blinker)
self.stored_data.clear()
self.stored_data.put('credentials', ip_address=self.ip_address.text, nick=self.nick.text)
screen = App.get_running_app().root
screen.current = "viewer"
ReturnBinder.get_instance().current_screen = "viewer"
class HostWindow(Screen): # Window for setting game rules
switch = ObjectProperty(None) # Set to None because it is created before actual switch from .kv file
slider = ObjectProperty(None)
tv = ObjectProperty(None)
hostVisible = False
teamNumber = 0
def create_nodes(self):
if int(self.slider.value) == self.teamNumber:
return
self.teamNumber = int(self.slider.value)
for node in [i for i in self.tv.iterate_all_nodes()]:
self.tv.remove_node(node)
for i in range(int(self.slider.value)):
self.teamNumber = i + 1
name = 'Druzyna ' + str(i + 1)
color = get_color_from_hex(color_dictionary[i])
self.tv.add_node(TreeViewLabel(text=name, color=color))
def host_to_server(self):
self.hostVisible = self.switch.active
nickname = App.get_running_app().root.ids.tw.nick.text
password = App.get_running_app().root.ids.tw.code.text
message = password + ":" + nickname + ":" + str(int(self.hostVisible)) + ":" + str(self.teamNumber)
print("Message sent to server: " + message)
client = Client.get_instance()
client.send_message(client.INIT_MESSAGE, message)
sleep(1)
if client.get_token is None:
return
tw = App.get_running_app().root.ids.tw
tw.current_blinker = blinker = GpsBlinker(lon=19.9125399, lat=50.0680966, nick=nickname, color_number=10)
team_map = App.get_running_app().root.ids.mw.ids.map
team_map.add_widget(blinker)
team_map.add_host_buttons()
blinker.blink()
App.get_running_app().gps_mod.start_updating(blinker)
screen = App.get_running_app().root
screen.current = "viewer"
ReturnBinder.get_instance().current_screen = "viewer"
# -----------------------------These classes made for pop window of team tokens-----------------------------------------
def show_popup(text):
show = Pop(text)
popupWindow = Popup(title="Password for teams:", content=show, size_hint=(None, None), size=(sp(200), sp(250)))
popupWindow.open()
class Pop(FloatLayout):
text = "placeholder"
def __init__(self, text, **kwargs):
self.text = text
super(FloatLayout, self).__init__(**kwargs)
class BtnPopup(Widget):
text = ''
def __init__(self, text="PLACEHOLDER", *args, **kwargs):
super().__init__(**kwargs)
self.text = text
def click(self):
show_popup(text=self.text)
def terminate_game_remove_host_privileges(self):
content = ConfirmPopup(text='Are you sure?')
content.bind(on_answer=self._on_answer)
self.popup = Popup(title="Terminating game",
content=content,
size_hint=(None, None),
size=(sp(200), sp(200)))
self.popup.open()
def _on_answer(self, instance, answer):
if answer is 'yes':
client = Client.get_instance()
client.send_message(client.CLOSE_GAME, None)
team_map = App.get_running_app().root.ids.mw.ids.map
team_map.remove_host_buttons()
tw = App.get_running_app().root.ids.tw
team_map.remove_widget(tw.current_blinker)
team_map.host_buttons = None
App.get_running_app().root.current = "menu"
ReturnBinder.get_instance().current_screen = "menu"
self.popup.dismiss()
class ConfirmPopup(GridLayout):
text = StringProperty()
def __init__(self, **kwargs):
self.register_event_type('on_answer')
super(ConfirmPopup, self).__init__(**kwargs)
def on_answer(self, *args):
pass
|
from time import sleep
from kivy.app import App
from kivy.properties import ObjectProperty, StringProperty
from kivy.uix.gridlayout import GridLayout
from kivy.uix.screenmanager import ScreenManager, Screen
from kivy.uix.treeview import TreeViewLabel
from kivy.uix.popup import Popup
from kivy.uix.floatlayout import FloatLayout
from kivy.uix.widget import Widget
from kivy.utils import get_color_from_hex
from kivy.metrics import *
from client import Client # from app.client import Client
from colordict import color_dictionary
from gpsblinker import GpsBlinker
from kivy.storage.jsonstore import JsonStore
import atexit
import os
import glob
from returnbinder import ReturnBinder
class WindowManager(ScreenManager):
pass
class MapWindow(Screen):
pass
class TokenWindow(Screen):
nick = ObjectProperty(None)
code = ObjectProperty(None)
ip_address = ObjectProperty(None)
client = Client.get_instance()
colornum = 10 # Expected to change. If players stay black something is wrong
current_blinker = None
stored_data = JsonStore('data.json')
def __disconnect(self):
files = glob.glob('cache/*.png')
for f in files:
if not f.endswith(".png"): # Additional safety, should never happen
print("ERROR WHILE CLEARING CACHE, FOUND NON-PNG FILE, ABORTING")
break
os.remove(f)
self.client.send_message(self.client.DISCONNECT_MESSAGE, self.code.text)
sleep(1)
def __connect(self):
if 'host-' in self.nick.text or ':' in self.nick.text or\
len(self.nick.text) >= 16 or\
len(self.code.text) > 10 or\
len(self.ip_address.text) > 16:
return
self.client.connect(server_ip=self.ip_address.text)
# after pressing "Host Game" button:
def host_connect(self):
self.__connect()
if not self.client.is_connected():
return
atexit.register(self.__disconnect)
screen = App.get_running_app().root
screen.current = "host"
ReturnBinder.get_instance().current_screen = "host"
self.stored_data.clear()
self.stored_data.put('credentials', ip_address=self.ip_address.text, nick=self.nick.text)
# after pressing "Connect Game" button:
def player_connect(self):
self.__connect()
if not self.client.is_connected():
return
atexit.register(self.__disconnect)
message = self.code.text + ":" + self.nick.text
print("Message being sent to server: " + message)
self.client.send_message(self.client.INIT_MESSAGE, message)
sleep(1)
if self.client.get_token() is None:
return
# Takes first letter as number from 0 to 9: || #1ABCD means color 1 ||
if len(self.code.text) >= 1 and self.code.text[0].isdigit():
self.colornum = int(self.code.text[0])
# GPS always starts in AGH WIEiT faculty building
self.current_blinker = blinker = GpsBlinker(lon=19.9125399, lat=50.0680966,
nick=self.nick.text, color_number=self.colornum)
team_map = App.get_running_app().root.ids.mw.ids.map
team_map.add_widget(blinker)
team_map.start_checking = True
blinker.blink()
App.get_running_app().gps_mod.start_updating(blinker)
self.stored_data.clear()
self.stored_data.put('credentials', ip_address=self.ip_address.text, nick=self.nick.text)
screen = App.get_running_app().root
screen.current = "viewer"
ReturnBinder.get_instance().current_screen = "viewer"
class HostWindow(Screen): # Window for setting game rules
switch = ObjectProperty(None) # Set to None because it is created before actual switch from .kv file
slider = ObjectProperty(None)
tv = ObjectProperty(None)
hostVisible = False
teamNumber = 0
def create_nodes(self):
if int(self.slider.value) == self.teamNumber:
return
self.teamNumber = int(self.slider.value)
for node in [i for i in self.tv.iterate_all_nodes()]:
self.tv.remove_node(node)
for i in range(int(self.slider.value)):
self.teamNumber = i + 1
name = 'Druzyna ' + str(i + 1)
color = get_color_from_hex(color_dictionary[i])
self.tv.add_node(TreeViewLabel(text=name, color=color))
def host_to_server(self):
self.hostVisible = self.switch.active
nickname = App.get_running_app().root.ids.tw.nick.text
password = App.get_running_app().root.ids.tw.code.text
message = password + ":" + nickname + ":" + str(int(self.hostVisible)) + ":" + str(self.teamNumber)
print("Message sent to server: " + message)
client = Client.get_instance()
client.send_message(client.INIT_MESSAGE, message)
sleep(1)
if client.get_token is None:
return
tw = App.get_running_app().root.ids.tw
tw.current_blinker = blinker = GpsBlinker(lon=19.9125399, lat=50.0680966, nick=nickname, color_number=10)
team_map = App.get_running_app().root.ids.mw.ids.map
team_map.add_widget(blinker)
team_map.add_host_buttons()
blinker.blink()
App.get_running_app().gps_mod.start_updating(blinker)
screen = App.get_running_app().root
screen.current = "viewer"
ReturnBinder.get_instance().current_screen = "viewer"
# -----------------------------These classes made for pop window of team tokens-----------------------------------------
def show_popup(text):
show = Pop(text)
popupWindow = Popup(title="Password for teams:", content=show, size_hint=(None, None), size=(sp(200), sp(250)))
popupWindow.open()
class Pop(FloatLayout):
text = "placeholder"
def __init__(self, text, **kwargs):
self.text = text
super(FloatLayout, self).__init__(**kwargs)
class BtnPopup(Widget):
text = ''
def __init__(self, text="PLACEHOLDER", *args, **kwargs):
super().__init__(**kwargs)
self.text = text
def click(self):
show_popup(text=self.text)
def terminate_game_remove_host_privileges(self):
content = ConfirmPopup(text='Are you sure?')
content.bind(on_answer=self._on_answer)
self.popup = Popup(title="Terminating game",
content=content,
size_hint=(None, None),
size=(sp(200), sp(200)))
self.popup.open()
def _on_answer(self, instance, answer):
if answer is 'yes':
client = Client.get_instance()
client.send_message(client.CLOSE_GAME, None)
team_map = App.get_running_app().root.ids.mw.ids.map
team_map.remove_host_buttons()
tw = App.get_running_app().root.ids.tw
team_map.remove_widget(tw.current_blinker)
team_map.host_buttons = None
App.get_running_app().root.current = "menu"
ReturnBinder.get_instance().current_screen = "menu"
self.popup.dismiss()
class ConfirmPopup(GridLayout):
text = StringProperty()
def __init__(self, **kwargs):
self.register_event_type('on_answer')
super(ConfirmPopup, self).__init__(**kwargs)
def on_answer(self, *args):
pass
|
en
| 0.872304
|
# from app.client import Client # Expected to change. If players stay black something is wrong # Additional safety, should never happen # after pressing "Host Game" button: # after pressing "Connect Game" button: # Takes first letter as number from 0 to 9: || #1ABCD means color 1 || # GPS always starts in AGH WIEiT faculty building # Window for setting game rules # Set to None because it is created before actual switch from .kv file # -----------------------------These classes made for pop window of team tokens-----------------------------------------
| 2.28657
| 2
|
k2/python/tests/shortest_path_test.py
|
Jarvan-Wang/k2
| 0
|
6625835
|
<gh_stars>0
#!/usr/bin/env python3
#
# Copyright (c) 2020 Mobvoi Inc. (authors: <NAME>)
#
# See ../../../LICENSE for clarification regarding multiple authors
# To run this single test, use
#
# ctest --verbose -R shortest_path_test_py
import unittest
import k2
import torch
class TestShortestPath(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.devices = [torch.device('cpu')]
if torch.cuda.is_available() and k2.with_cuda:
cls.devices.append(torch.device('cuda', 0))
if torch.cuda.device_count() > 1:
torch.cuda.set_device(1)
cls.devices.append(torch.device('cuda', 1))
def test_single_fsa(self):
s = '''
0 4 1 1
0 1 1 1
1 2 1 2
1 3 1 3
2 7 1 4
3 7 1 5
4 6 1 2
4 8 1 3
5 9 -1 4
6 9 -1 3
7 9 -1 5
8 9 -1 6
9
'''
for device in self.devices:
fsa = k2.Fsa.from_str(s).to(device)
fsa = k2.create_fsa_vec([fsa])
fsa.requires_grad_(True)
best_path = k2.shortest_path(fsa, use_double_scores=False)
# we recompute the total_scores for backprop
total_scores = best_path.scores.sum()
assert total_scores == 14
expected = torch.zeros(12)
expected[torch.tensor([1, 3, 5, 10])] = 1
total_scores.backward()
assert torch.allclose(fsa.scores.grad, expected.to(device))
def test_fsa_vec(self):
# best path:
# states: 0 -> 1 -> 3 -> 7 -> 9
# arcs: 1 -> 3 -> 5 -> 10
s1 = '''
0 4 1 1
0 1 1 1
1 2 1 2
1 3 1 3
2 7 1 4
3 7 1 5
4 6 1 2
4 8 1 3
5 9 -1 4
6 9 -1 3
7 9 -1 5
8 9 -1 6
9
'''
# best path:
# states: 0 -> 2 -> 3 -> 4 -> 5
# arcs: 1 -> 4 -> 5 -> 7
s2 = '''
0 1 1 1
0 2 2 6
1 2 3 3
1 3 4 2
2 3 5 4
3 4 6 3
3 5 -1 2
4 5 -1 0
5
'''
# best path:
# states: 0 -> 2 -> 3
# arcs: 1 -> 3
s3 = '''
0 1 1 10
0 2 2 100
1 3 -1 3.5
2 3 -1 5.5
3
'''
for device in self.devices:
fsa1 = k2.Fsa.from_str(s1).to(device)
fsa2 = k2.Fsa.from_str(s2).to(device)
fsa3 = k2.Fsa.from_str(s3).to(device)
fsa1.requires_grad_(True)
fsa2.requires_grad_(True)
fsa3.requires_grad_(True)
fsa_vec = k2.create_fsa_vec([fsa1, fsa2, fsa3])
assert fsa_vec.shape == (3, None, None)
best_path = k2.shortest_path(fsa_vec, use_double_scores=False)
# we recompute the total_scores for backprop
total_scores = best_path.scores.sum()
total_scores.backward()
fsa1_best_arc_indexes = torch.tensor([1, 3, 5, 10], device=device)
assert torch.all(
torch.eq(fsa1.scores.grad[fsa1_best_arc_indexes],
torch.ones(4, device=device)))
assert fsa1.scores.grad.sum() == 4
fsa2_best_arc_indexes = torch.tensor([1, 4, 5, 7], device=device)
assert torch.all(
torch.eq(fsa2.scores.grad[fsa2_best_arc_indexes],
torch.ones(4, device=device)))
assert fsa2.scores.grad.sum() == 4
fsa3_best_arc_indexes = torch.tensor([1, 3], device=device)
assert torch.all(
torch.eq(fsa3.scores.grad[fsa3_best_arc_indexes],
torch.ones(2, device=device)))
assert fsa3.scores.grad.sum() == 2
if __name__ == '__main__':
unittest.main()
|
#!/usr/bin/env python3
#
# Copyright (c) 2020 Mobvoi Inc. (authors: <NAME>)
#
# See ../../../LICENSE for clarification regarding multiple authors
# To run this single test, use
#
# ctest --verbose -R shortest_path_test_py
import unittest
import k2
import torch
class TestShortestPath(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.devices = [torch.device('cpu')]
if torch.cuda.is_available() and k2.with_cuda:
cls.devices.append(torch.device('cuda', 0))
if torch.cuda.device_count() > 1:
torch.cuda.set_device(1)
cls.devices.append(torch.device('cuda', 1))
def test_single_fsa(self):
s = '''
0 4 1 1
0 1 1 1
1 2 1 2
1 3 1 3
2 7 1 4
3 7 1 5
4 6 1 2
4 8 1 3
5 9 -1 4
6 9 -1 3
7 9 -1 5
8 9 -1 6
9
'''
for device in self.devices:
fsa = k2.Fsa.from_str(s).to(device)
fsa = k2.create_fsa_vec([fsa])
fsa.requires_grad_(True)
best_path = k2.shortest_path(fsa, use_double_scores=False)
# we recompute the total_scores for backprop
total_scores = best_path.scores.sum()
assert total_scores == 14
expected = torch.zeros(12)
expected[torch.tensor([1, 3, 5, 10])] = 1
total_scores.backward()
assert torch.allclose(fsa.scores.grad, expected.to(device))
def test_fsa_vec(self):
# best path:
# states: 0 -> 1 -> 3 -> 7 -> 9
# arcs: 1 -> 3 -> 5 -> 10
s1 = '''
0 4 1 1
0 1 1 1
1 2 1 2
1 3 1 3
2 7 1 4
3 7 1 5
4 6 1 2
4 8 1 3
5 9 -1 4
6 9 -1 3
7 9 -1 5
8 9 -1 6
9
'''
# best path:
# states: 0 -> 2 -> 3 -> 4 -> 5
# arcs: 1 -> 4 -> 5 -> 7
s2 = '''
0 1 1 1
0 2 2 6
1 2 3 3
1 3 4 2
2 3 5 4
3 4 6 3
3 5 -1 2
4 5 -1 0
5
'''
# best path:
# states: 0 -> 2 -> 3
# arcs: 1 -> 3
s3 = '''
0 1 1 10
0 2 2 100
1 3 -1 3.5
2 3 -1 5.5
3
'''
for device in self.devices:
fsa1 = k2.Fsa.from_str(s1).to(device)
fsa2 = k2.Fsa.from_str(s2).to(device)
fsa3 = k2.Fsa.from_str(s3).to(device)
fsa1.requires_grad_(True)
fsa2.requires_grad_(True)
fsa3.requires_grad_(True)
fsa_vec = k2.create_fsa_vec([fsa1, fsa2, fsa3])
assert fsa_vec.shape == (3, None, None)
best_path = k2.shortest_path(fsa_vec, use_double_scores=False)
# we recompute the total_scores for backprop
total_scores = best_path.scores.sum()
total_scores.backward()
fsa1_best_arc_indexes = torch.tensor([1, 3, 5, 10], device=device)
assert torch.all(
torch.eq(fsa1.scores.grad[fsa1_best_arc_indexes],
torch.ones(4, device=device)))
assert fsa1.scores.grad.sum() == 4
fsa2_best_arc_indexes = torch.tensor([1, 4, 5, 7], device=device)
assert torch.all(
torch.eq(fsa2.scores.grad[fsa2_best_arc_indexes],
torch.ones(4, device=device)))
assert fsa2.scores.grad.sum() == 4
fsa3_best_arc_indexes = torch.tensor([1, 3], device=device)
assert torch.all(
torch.eq(fsa3.scores.grad[fsa3_best_arc_indexes],
torch.ones(2, device=device)))
assert fsa3.scores.grad.sum() == 2
if __name__ == '__main__':
unittest.main()
|
en
| 0.467052
|
#!/usr/bin/env python3 # # Copyright (c) 2020 Mobvoi Inc. (authors: <NAME>) # # See ../../../LICENSE for clarification regarding multiple authors # To run this single test, use # # ctest --verbose -R shortest_path_test_py 0 4 1 1 0 1 1 1 1 2 1 2 1 3 1 3 2 7 1 4 3 7 1 5 4 6 1 2 4 8 1 3 5 9 -1 4 6 9 -1 3 7 9 -1 5 8 9 -1 6 9 # we recompute the total_scores for backprop # best path: # states: 0 -> 1 -> 3 -> 7 -> 9 # arcs: 1 -> 3 -> 5 -> 10 0 4 1 1 0 1 1 1 1 2 1 2 1 3 1 3 2 7 1 4 3 7 1 5 4 6 1 2 4 8 1 3 5 9 -1 4 6 9 -1 3 7 9 -1 5 8 9 -1 6 9 # best path: # states: 0 -> 2 -> 3 -> 4 -> 5 # arcs: 1 -> 4 -> 5 -> 7 0 1 1 1 0 2 2 6 1 2 3 3 1 3 4 2 2 3 5 4 3 4 6 3 3 5 -1 2 4 5 -1 0 5 # best path: # states: 0 -> 2 -> 3 # arcs: 1 -> 3 0 1 1 10 0 2 2 100 1 3 -1 3.5 2 3 -1 5.5 3 # we recompute the total_scores for backprop
| 2.815456
| 3
|
train_quant.py
|
Roxbili/kws-demo
| 0
|
6625836
|
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
#
# Modifications Copyright 2017 Arm Inc. All Rights Reserved.
# Added model dimensions as command line argument and changed to Adam optimizer
#
#
"""Simple speech recognition to spot a limited number of keywords.
This is a self-contained example script that will train a very basic audio
recognition model in TensorFlow. It downloads the necessary training data and
runs with reasonable defaults to train within a few hours even only using a CPU.
For more information, please see
https://www.tensorflow.org/tutorials/audio_recognition.
It is intended as an introduction to using neural networks for audio
recognition, and is not a full speech recognition system. For more advanced
speech systems, I recommend looking into Kaldi. This network uses a keyword
detection style to spot discrete words from a small vocabulary, consisting of
"yes", "no", "up", "down", "left", "right", "on", "off", "stop", and "go".
To run the training process, use:
bazel run tensorflow/examples/speech_commands:train
This will write out checkpoints to /tmp/speech_commands_train/, and will
download over 1GB of open source training data, so you'll need enough free space
and a good internet connection. The default data is a collection of thousands of
one-second .wav files, each containing one spoken word. This data set is
collected from https://aiyprojects.withgoogle.com/open_speech_recording, please
consider contributing to help improve this and other models!
As training progresses, it will print out its accuracy metrics, which should
rise above 90% by the end. Once it's complete, you can run the freeze script to
get a binary GraphDef that you can easily deploy on mobile applications.
If you want to train on your own data, you'll need to create .wavs with your
recordings, all at a consistent length, and then arrange them into subfolders
organized by label. For example, here's a possible file structure:
my_wavs >
up >
audio_0.wav
audio_1.wav
down >
audio_2.wav
audio_3.wav
other>
audio_4.wav
audio_5.wav
You'll also need to tell the script what labels to look for, using the
`--wanted_words` argument. In this case, 'up,down' might be what you want, and
the audio in the 'other' folder would be used to train an 'unknown' category.
To pull this all together, you'd run:
bazel run tensorflow/examples/speech_commands:train -- \
--data_dir=my_wavs --wanted_words=up,down
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import os.path
import sys
import numpy as np
from six.moves import xrange # pylint: disable=redefined-builtin
import tensorflow as tf
import input_data
import models
from tensorflow.python.platform import gfile
from tensorflow.contrib import slim as slim
def main(_):
# We want to see all the logging messages for this tutorial.
tf.logging.set_verbosity(tf.logging.INFO)
# Start a new TensorFlow session.
sess = tf.InteractiveSession()
# Begin by making sure we have the training data we need. If you already have
# training data of your own, use `--data_url= ` on the command line to avoid
# downloading.
model_settings = models.prepare_model_settings(
len(input_data.prepare_words_list(FLAGS.wanted_words.split(','))),
FLAGS.sample_rate, FLAGS.clip_duration_ms, FLAGS.window_size_ms,
FLAGS.window_stride_ms, FLAGS.dct_coefficient_count)
# print(model_settings['label_count'])
# sys.exit(0)
audio_processor = input_data.AudioProcessor(
FLAGS.data_url, FLAGS.data_dir, FLAGS.silence_percentage,
FLAGS.unknown_percentage,
FLAGS.wanted_words.split(','), FLAGS.validation_percentage,
FLAGS.testing_percentage, model_settings)
fingerprint_size = model_settings['fingerprint_size']
label_count = model_settings['label_count']
time_shift_samples = int((FLAGS.time_shift_ms * FLAGS.sample_rate) / 1000)
# Figure out the learning rates for each training phase. Since it's often
# effective to have high learning rates at the start of training, followed by
# lower levels towards the end, the number of steps and learning rates can be
# specified as comma-separated lists to define the rate at each stage. For
# example --how_many_training_steps=10000,3000 --learning_rate=0.001,0.0001
# will run 13,000 training loops in total, with a rate of 0.001 for the first
# 10,000, and 0.0001 for the final 3,000.
training_steps_list = list(map(int, FLAGS.how_many_training_steps.split(',')))
learning_rates_list = list(map(float, FLAGS.learning_rate.split(',')))
if len(training_steps_list) != len(learning_rates_list):
raise Exception(
'--how_many_training_steps and --learning_rate must be equal length '
'lists, but are %d and %d long instead' % (len(training_steps_list),
len(learning_rates_list)))
fingerprint_input = tf.placeholder(
tf.float32, [None, fingerprint_size], name='fingerprint_input')
# is_training = tf.placeholder(shape=(), dtype=tf.bool)
is_training = True
logits = models.create_model(
fingerprint_input,
model_settings,
FLAGS.model_architecture,
FLAGS.model_size_info,
is_training=is_training)
# Trainable vars has to be collected before adding quant ops.
trainable_vars = tf.trainable_variables()
# Define loss and optimizer
ground_truth_input = tf.placeholder(
tf.float32, [None, label_count], name='groundtruth_input')
# Optionally we can add runtime checks to spot when NaNs or other symptoms of
# numerical errors start occurring during training.
control_dependencies = []
if FLAGS.check_nans:
checks = tf.add_check_numerics_ops()
control_dependencies = [checks]
if FLAGS.quant:
tf.logging.info("Adding quantization ops...")
tf.contrib.quantize.experimental_create_training_graph(sess.graph,
weight_bits=FLAGS.bits,
activation_bits=FLAGS.bits,
quant_delay=2400,
symmetric=True)
print("Done")
# Now, create dependencies for quantizing weights
with tf.name_scope('cross_entropy'):
cross_entropy_mean = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(
labels=ground_truth_input, logits=logits))
tf.summary.scalar('cross_entropy', cross_entropy_mean)
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
global_step = tf.train.get_or_create_global_step()
increment_global_step = tf.assign(global_step, global_step + 1)
start_step = 1
tf.logging.info('Training from step: %d ', start_step)
with tf.name_scope('train'), tf.control_dependencies(update_ops), tf.control_dependencies(control_dependencies):
learning_rate_input = tf.placeholder(
tf.float32, [], name='learning_rate_input')
train_op = tf.train.AdamOptimizer(
learning_rate_input)
train_step = slim.learning.create_train_op(cross_entropy_mean, train_op)
# train_step = tf.train.GradientDescentOptimizer(
# learning_rate_input).minimize(cross_entropy_mean)
predicted_indices = tf.argmax(logits, 1)
expected_indices = tf.argmax(ground_truth_input, 1)
correct_prediction = tf.equal(predicted_indices, expected_indices)
confusion_matrix = tf.confusion_matrix(
expected_indices, predicted_indices, num_classes=label_count)
evaluation_step = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
tf.summary.scalar('accuracy', evaluation_step)
saver = tf.train.Saver(tf.global_variables())
# Merge all the summaries and write them out to /tmp/retrain_logs (by default)
merged_summaries = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(FLAGS.summaries_dir + '/train',
sess.graph)
validation_writer = tf.summary.FileWriter(FLAGS.summaries_dir + '/validation')
tf.global_variables_initializer().run()
if FLAGS.start_checkpoint:
try:
models.load_variables_from_checkpoint(sess, FLAGS.start_checkpoint, trainable_vars)
except Exception:
pass
start_step = global_step.eval(session=sess)
# Parameter counts
params = tf.trainable_variables()
num_params = sum(map(lambda t: np.prod(tf.shape(t.value()).eval()), params))
print('Total number of Parameters: ', num_params)
# Save graph.pbtxt.
tf.train.write_graph(sess.graph_def, FLAGS.train_dir,
FLAGS.model_architecture + '.pbtxt')
# Save list of words.
with gfile.GFile(
os.path.join(FLAGS.train_dir, FLAGS.model_architecture + '_labels.txt'),
'w') as f:
f.write('\n'.join(audio_processor.words_list))
# Training loop.
best_accuracy = 0
training_steps_max = np.sum(training_steps_list)
for training_step in xrange(start_step, training_steps_max + 1):
# Figure out what the current learning rate is.
training_steps_sum = 0
for i in range(len(training_steps_list)):
training_steps_sum += training_steps_list[i]
if training_step <= training_steps_sum:
learning_rate_value = learning_rates_list[i]
break
# Pull the audio samples we'll use for training.
train_fingerprints, train_ground_truth = audio_processor.get_data(
FLAGS.batch_size, 0, model_settings, FLAGS.background_frequency,
FLAGS.background_volume, time_shift_samples, 'training', sess)
# Run the graph with this batch of training data.
train_summary, train_accuracy, cross_entropy_value, _, _ = sess.run(
[
merged_summaries, evaluation_step, cross_entropy_mean, train_step,
increment_global_step
],
feed_dict={
fingerprint_input: train_fingerprints,
ground_truth_input: train_ground_truth,
learning_rate_input: learning_rate_value,
})
train_writer.add_summary(train_summary, training_step)
tf.logging.info('Step #%d: rate %f, accuracy %.2f%%, cross entropy %f' %
(training_step, learning_rate_value, train_accuracy * 100,
cross_entropy_value))
is_last_step = (training_step == training_steps_max)
"""
if (training_step % FLAGS.eval_step_interval) == 0 or is_last_step:
set_size = audio_processor.set_size('validation')
total_accuracy = 0
total_conf_matrix = None
for i in xrange(0, set_size, FLAGS.batch_size):
validation_fingerprints, validation_ground_truth = (
audio_processor.get_data(FLAGS.batch_size, i, model_settings, 0.0,
0.0, 0, 'validation', sess))
# Run a validation step and capture training summaries for TensorBoard
# with the `merged` op.
validation_summary, validation_accuracy, conf_matrix = sess.run(
[merged_summaries, evaluation_step, confusion_matrix],
feed_dict={
fingerprint_input: validation_fingerprints,
ground_truth_input: validation_ground_truth,
})
validation_writer.add_summary(validation_summary, training_step)
batch_size = min(FLAGS.batch_size, set_size - i)
total_accuracy += (validation_accuracy * batch_size) / set_size
if total_conf_matrix is None:
total_conf_matrix = conf_matrix
else:
total_conf_matrix += conf_matrix
tf.logging.info('Confusion Matrix:\n %s' % (total_conf_matrix))
tf.logging.info('Step %d: Validation accuracy = %.2f%% (N=%d)' %
(training_step, total_accuracy * 100, set_size))
"""
# Save the model checkpoint when validation accuracy improves
"""
if total_accuracy > best_accuracy:
best_accuracy = total_accuracy
checkpoint_path = os.path.join(FLAGS.train_dir, 'best',
FLAGS.model_architecture + '_' + str(int(best_accuracy * 10000)) + '.ckpt')
tf.logging.info('Saving best model to "%s-%d"', checkpoint_path, training_step)
saver.save(sess, checkpoint_path, global_step=training_step)
tf.logging.info('So far the best validation accuracy is %.2f%%' % (best_accuracy * 100))
"""
if (training_step % FLAGS.eval_step_interval) == 0 or is_last_step:
checkpoint_path = os.path.join(FLAGS.train_dir, 'best',
FLAGS.model_architecture + ".ckpt")
tf.logging.info('Saving best model to "%s-%d"', checkpoint_path, training_step)
saver.save(sess, checkpoint_path, global_step=training_step)
set_size = audio_processor.set_size('testing')
tf.logging.info('set_size=%d', set_size)
total_accuracy = 0
total_conf_matrix = None
for i in xrange(0, set_size, FLAGS.batch_size):
test_fingerprints, test_ground_truth = audio_processor.get_data(
FLAGS.batch_size, i, model_settings, 0.0, 0.0, 0, 'testing', sess)
test_accuracy, conf_matrix = sess.run(
[evaluation_step, confusion_matrix],
feed_dict={
fingerprint_input: test_fingerprints,
ground_truth_input: test_ground_truth,
})
batch_size = min(FLAGS.batch_size, set_size - i)
total_accuracy += (test_accuracy * batch_size) / set_size
if total_conf_matrix is None:
total_conf_matrix = conf_matrix
else:
total_conf_matrix += conf_matrix
tf.logging.info('Confusion Matrix:\n %s' % (total_conf_matrix))
tf.logging.info('Final test accuracy = %.2f%% (N=%d)' % (total_accuracy * 100,
set_size))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'--data_url',
type=str,
# pylint: disable=line-too-long
default='http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz',
# pylint: enable=line-too-long
help='Location of speech training data archive on the web.')
parser.add_argument(
'--data_dir',
type=str,
default='/tmp/speech_dataset/',
help="""\
Where to download the speech training data to.
""")
parser.add_argument(
'--background_volume',
type=float,
default=0.1,
help="""\
How loud the background noise should be, between 0 and 1.
""")
parser.add_argument(
'--background_frequency',
type=float,
default=0.8,
help="""\
How many of the training samples have background noise mixed in.
""")
parser.add_argument(
'--silence_percentage',
type=float,
default=10.0,
help="""\
How much of the training data should be silence.
""")
parser.add_argument(
'--unknown_percentage',
type=float,
default=10.0,
help="""\
How much of the training data should be unknown words.
""")
parser.add_argument(
'--time_shift_ms',
type=float,
default=100.0,
help="""\
Range to randomly shift the training audio by in time.
""")
parser.add_argument(
'--testing_percentage',
type=int,
default=10,
help='What percentage of wavs to use as a test set.')
parser.add_argument(
'--validation_percentage',
type=int,
default=10,
help='What percentage of wavs to use as a validation set.')
parser.add_argument(
'--sample_rate',
type=int,
default=16000,
help='Expected sample rate of the wavs',)
parser.add_argument(
'--clip_duration_ms',
type=int,
default=1000,
help='Expected duration in milliseconds of the wavs',)
parser.add_argument(
'--window_size_ms',
type=float,
default=30.0,
help='How long each spectrogram timeslice is',)
parser.add_argument(
'--window_stride_ms',
type=float,
default=10.0,
help='How long each spectrogram timeslice is',)
parser.add_argument(
'--dct_coefficient_count',
type=int,
default=40,
help='How many bins to use for the MFCC fingerprint',)
parser.add_argument(
'--how_many_training_steps',
type=str,
default='15000,3000',
help='How many training loops to run',)
parser.add_argument(
'--eval_step_interval',
type=int,
default=400,
help='How often to evaluate the training results.')
parser.add_argument(
'--learning_rate',
type=str,
default='0.001,0.0001',
help='How large a learning rate to use when training.')
parser.add_argument(
'--batch_size',
type=int,
default=100,
help='How many items to train with at once',)
parser.add_argument(
'--summaries_dir',
type=str,
default='/tmp/retrain_logs',
help='Where to save summary logs for TensorBoard.')
parser.add_argument(
'--wanted_words',
type=str,
default='yes,no,up,down,left,right,on,off,stop,go',
help='Words to use (others will be added to an unknown label)',)
parser.add_argument(
'--train_dir',
type=str,
default='/tmp/speech_commands_train',
help='Directory to write event logs and checkpoint.')
parser.add_argument(
'--save_step_interval',
type=int,
default=100,
help='Save model checkpoint every save_steps.')
parser.add_argument(
'--start_checkpoint',
type=str,
default='',
help='If specified, restore this pretrained model before any training.')
parser.add_argument(
'--model_architecture',
type=str,
default='dnn',
help='What model architecture to use')
parser.add_argument(
'--model_size_info',
type=int,
nargs="+",
default=[128,128,128],
help='Model dimensions - different for various models')
parser.add_argument(
'--check_nans',
type=bool,
default=False,
help='Whether to check for invalid numbers during processing')
parser.add_argument("--quant", action='store_true',
default=False)
parser.add_argument("--bits", type=int, # 只有当quant参数有效的时候这个参数才能生效
default=8)
FLAGS, unparsed = parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
|
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
#
# Modifications Copyright 2017 Arm Inc. All Rights Reserved.
# Added model dimensions as command line argument and changed to Adam optimizer
#
#
"""Simple speech recognition to spot a limited number of keywords.
This is a self-contained example script that will train a very basic audio
recognition model in TensorFlow. It downloads the necessary training data and
runs with reasonable defaults to train within a few hours even only using a CPU.
For more information, please see
https://www.tensorflow.org/tutorials/audio_recognition.
It is intended as an introduction to using neural networks for audio
recognition, and is not a full speech recognition system. For more advanced
speech systems, I recommend looking into Kaldi. This network uses a keyword
detection style to spot discrete words from a small vocabulary, consisting of
"yes", "no", "up", "down", "left", "right", "on", "off", "stop", and "go".
To run the training process, use:
bazel run tensorflow/examples/speech_commands:train
This will write out checkpoints to /tmp/speech_commands_train/, and will
download over 1GB of open source training data, so you'll need enough free space
and a good internet connection. The default data is a collection of thousands of
one-second .wav files, each containing one spoken word. This data set is
collected from https://aiyprojects.withgoogle.com/open_speech_recording, please
consider contributing to help improve this and other models!
As training progresses, it will print out its accuracy metrics, which should
rise above 90% by the end. Once it's complete, you can run the freeze script to
get a binary GraphDef that you can easily deploy on mobile applications.
If you want to train on your own data, you'll need to create .wavs with your
recordings, all at a consistent length, and then arrange them into subfolders
organized by label. For example, here's a possible file structure:
my_wavs >
up >
audio_0.wav
audio_1.wav
down >
audio_2.wav
audio_3.wav
other>
audio_4.wav
audio_5.wav
You'll also need to tell the script what labels to look for, using the
`--wanted_words` argument. In this case, 'up,down' might be what you want, and
the audio in the 'other' folder would be used to train an 'unknown' category.
To pull this all together, you'd run:
bazel run tensorflow/examples/speech_commands:train -- \
--data_dir=my_wavs --wanted_words=up,down
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import os.path
import sys
import numpy as np
from six.moves import xrange # pylint: disable=redefined-builtin
import tensorflow as tf
import input_data
import models
from tensorflow.python.platform import gfile
from tensorflow.contrib import slim as slim
def main(_):
# We want to see all the logging messages for this tutorial.
tf.logging.set_verbosity(tf.logging.INFO)
# Start a new TensorFlow session.
sess = tf.InteractiveSession()
# Begin by making sure we have the training data we need. If you already have
# training data of your own, use `--data_url= ` on the command line to avoid
# downloading.
model_settings = models.prepare_model_settings(
len(input_data.prepare_words_list(FLAGS.wanted_words.split(','))),
FLAGS.sample_rate, FLAGS.clip_duration_ms, FLAGS.window_size_ms,
FLAGS.window_stride_ms, FLAGS.dct_coefficient_count)
# print(model_settings['label_count'])
# sys.exit(0)
audio_processor = input_data.AudioProcessor(
FLAGS.data_url, FLAGS.data_dir, FLAGS.silence_percentage,
FLAGS.unknown_percentage,
FLAGS.wanted_words.split(','), FLAGS.validation_percentage,
FLAGS.testing_percentage, model_settings)
fingerprint_size = model_settings['fingerprint_size']
label_count = model_settings['label_count']
time_shift_samples = int((FLAGS.time_shift_ms * FLAGS.sample_rate) / 1000)
# Figure out the learning rates for each training phase. Since it's often
# effective to have high learning rates at the start of training, followed by
# lower levels towards the end, the number of steps and learning rates can be
# specified as comma-separated lists to define the rate at each stage. For
# example --how_many_training_steps=10000,3000 --learning_rate=0.001,0.0001
# will run 13,000 training loops in total, with a rate of 0.001 for the first
# 10,000, and 0.0001 for the final 3,000.
training_steps_list = list(map(int, FLAGS.how_many_training_steps.split(',')))
learning_rates_list = list(map(float, FLAGS.learning_rate.split(',')))
if len(training_steps_list) != len(learning_rates_list):
raise Exception(
'--how_many_training_steps and --learning_rate must be equal length '
'lists, but are %d and %d long instead' % (len(training_steps_list),
len(learning_rates_list)))
fingerprint_input = tf.placeholder(
tf.float32, [None, fingerprint_size], name='fingerprint_input')
# is_training = tf.placeholder(shape=(), dtype=tf.bool)
is_training = True
logits = models.create_model(
fingerprint_input,
model_settings,
FLAGS.model_architecture,
FLAGS.model_size_info,
is_training=is_training)
# Trainable vars has to be collected before adding quant ops.
trainable_vars = tf.trainable_variables()
# Define loss and optimizer
ground_truth_input = tf.placeholder(
tf.float32, [None, label_count], name='groundtruth_input')
# Optionally we can add runtime checks to spot when NaNs or other symptoms of
# numerical errors start occurring during training.
control_dependencies = []
if FLAGS.check_nans:
checks = tf.add_check_numerics_ops()
control_dependencies = [checks]
if FLAGS.quant:
tf.logging.info("Adding quantization ops...")
tf.contrib.quantize.experimental_create_training_graph(sess.graph,
weight_bits=FLAGS.bits,
activation_bits=FLAGS.bits,
quant_delay=2400,
symmetric=True)
print("Done")
# Now, create dependencies for quantizing weights
with tf.name_scope('cross_entropy'):
cross_entropy_mean = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(
labels=ground_truth_input, logits=logits))
tf.summary.scalar('cross_entropy', cross_entropy_mean)
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
global_step = tf.train.get_or_create_global_step()
increment_global_step = tf.assign(global_step, global_step + 1)
start_step = 1
tf.logging.info('Training from step: %d ', start_step)
with tf.name_scope('train'), tf.control_dependencies(update_ops), tf.control_dependencies(control_dependencies):
learning_rate_input = tf.placeholder(
tf.float32, [], name='learning_rate_input')
train_op = tf.train.AdamOptimizer(
learning_rate_input)
train_step = slim.learning.create_train_op(cross_entropy_mean, train_op)
# train_step = tf.train.GradientDescentOptimizer(
# learning_rate_input).minimize(cross_entropy_mean)
predicted_indices = tf.argmax(logits, 1)
expected_indices = tf.argmax(ground_truth_input, 1)
correct_prediction = tf.equal(predicted_indices, expected_indices)
confusion_matrix = tf.confusion_matrix(
expected_indices, predicted_indices, num_classes=label_count)
evaluation_step = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
tf.summary.scalar('accuracy', evaluation_step)
saver = tf.train.Saver(tf.global_variables())
# Merge all the summaries and write them out to /tmp/retrain_logs (by default)
merged_summaries = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(FLAGS.summaries_dir + '/train',
sess.graph)
validation_writer = tf.summary.FileWriter(FLAGS.summaries_dir + '/validation')
tf.global_variables_initializer().run()
if FLAGS.start_checkpoint:
try:
models.load_variables_from_checkpoint(sess, FLAGS.start_checkpoint, trainable_vars)
except Exception:
pass
start_step = global_step.eval(session=sess)
# Parameter counts
params = tf.trainable_variables()
num_params = sum(map(lambda t: np.prod(tf.shape(t.value()).eval()), params))
print('Total number of Parameters: ', num_params)
# Save graph.pbtxt.
tf.train.write_graph(sess.graph_def, FLAGS.train_dir,
FLAGS.model_architecture + '.pbtxt')
# Save list of words.
with gfile.GFile(
os.path.join(FLAGS.train_dir, FLAGS.model_architecture + '_labels.txt'),
'w') as f:
f.write('\n'.join(audio_processor.words_list))
# Training loop.
best_accuracy = 0
training_steps_max = np.sum(training_steps_list)
for training_step in xrange(start_step, training_steps_max + 1):
# Figure out what the current learning rate is.
training_steps_sum = 0
for i in range(len(training_steps_list)):
training_steps_sum += training_steps_list[i]
if training_step <= training_steps_sum:
learning_rate_value = learning_rates_list[i]
break
# Pull the audio samples we'll use for training.
train_fingerprints, train_ground_truth = audio_processor.get_data(
FLAGS.batch_size, 0, model_settings, FLAGS.background_frequency,
FLAGS.background_volume, time_shift_samples, 'training', sess)
# Run the graph with this batch of training data.
train_summary, train_accuracy, cross_entropy_value, _, _ = sess.run(
[
merged_summaries, evaluation_step, cross_entropy_mean, train_step,
increment_global_step
],
feed_dict={
fingerprint_input: train_fingerprints,
ground_truth_input: train_ground_truth,
learning_rate_input: learning_rate_value,
})
train_writer.add_summary(train_summary, training_step)
tf.logging.info('Step #%d: rate %f, accuracy %.2f%%, cross entropy %f' %
(training_step, learning_rate_value, train_accuracy * 100,
cross_entropy_value))
is_last_step = (training_step == training_steps_max)
"""
if (training_step % FLAGS.eval_step_interval) == 0 or is_last_step:
set_size = audio_processor.set_size('validation')
total_accuracy = 0
total_conf_matrix = None
for i in xrange(0, set_size, FLAGS.batch_size):
validation_fingerprints, validation_ground_truth = (
audio_processor.get_data(FLAGS.batch_size, i, model_settings, 0.0,
0.0, 0, 'validation', sess))
# Run a validation step and capture training summaries for TensorBoard
# with the `merged` op.
validation_summary, validation_accuracy, conf_matrix = sess.run(
[merged_summaries, evaluation_step, confusion_matrix],
feed_dict={
fingerprint_input: validation_fingerprints,
ground_truth_input: validation_ground_truth,
})
validation_writer.add_summary(validation_summary, training_step)
batch_size = min(FLAGS.batch_size, set_size - i)
total_accuracy += (validation_accuracy * batch_size) / set_size
if total_conf_matrix is None:
total_conf_matrix = conf_matrix
else:
total_conf_matrix += conf_matrix
tf.logging.info('Confusion Matrix:\n %s' % (total_conf_matrix))
tf.logging.info('Step %d: Validation accuracy = %.2f%% (N=%d)' %
(training_step, total_accuracy * 100, set_size))
"""
# Save the model checkpoint when validation accuracy improves
"""
if total_accuracy > best_accuracy:
best_accuracy = total_accuracy
checkpoint_path = os.path.join(FLAGS.train_dir, 'best',
FLAGS.model_architecture + '_' + str(int(best_accuracy * 10000)) + '.ckpt')
tf.logging.info('Saving best model to "%s-%d"', checkpoint_path, training_step)
saver.save(sess, checkpoint_path, global_step=training_step)
tf.logging.info('So far the best validation accuracy is %.2f%%' % (best_accuracy * 100))
"""
if (training_step % FLAGS.eval_step_interval) == 0 or is_last_step:
checkpoint_path = os.path.join(FLAGS.train_dir, 'best',
FLAGS.model_architecture + ".ckpt")
tf.logging.info('Saving best model to "%s-%d"', checkpoint_path, training_step)
saver.save(sess, checkpoint_path, global_step=training_step)
set_size = audio_processor.set_size('testing')
tf.logging.info('set_size=%d', set_size)
total_accuracy = 0
total_conf_matrix = None
for i in xrange(0, set_size, FLAGS.batch_size):
test_fingerprints, test_ground_truth = audio_processor.get_data(
FLAGS.batch_size, i, model_settings, 0.0, 0.0, 0, 'testing', sess)
test_accuracy, conf_matrix = sess.run(
[evaluation_step, confusion_matrix],
feed_dict={
fingerprint_input: test_fingerprints,
ground_truth_input: test_ground_truth,
})
batch_size = min(FLAGS.batch_size, set_size - i)
total_accuracy += (test_accuracy * batch_size) / set_size
if total_conf_matrix is None:
total_conf_matrix = conf_matrix
else:
total_conf_matrix += conf_matrix
tf.logging.info('Confusion Matrix:\n %s' % (total_conf_matrix))
tf.logging.info('Final test accuracy = %.2f%% (N=%d)' % (total_accuracy * 100,
set_size))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'--data_url',
type=str,
# pylint: disable=line-too-long
default='http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz',
# pylint: enable=line-too-long
help='Location of speech training data archive on the web.')
parser.add_argument(
'--data_dir',
type=str,
default='/tmp/speech_dataset/',
help="""\
Where to download the speech training data to.
""")
parser.add_argument(
'--background_volume',
type=float,
default=0.1,
help="""\
How loud the background noise should be, between 0 and 1.
""")
parser.add_argument(
'--background_frequency',
type=float,
default=0.8,
help="""\
How many of the training samples have background noise mixed in.
""")
parser.add_argument(
'--silence_percentage',
type=float,
default=10.0,
help="""\
How much of the training data should be silence.
""")
parser.add_argument(
'--unknown_percentage',
type=float,
default=10.0,
help="""\
How much of the training data should be unknown words.
""")
parser.add_argument(
'--time_shift_ms',
type=float,
default=100.0,
help="""\
Range to randomly shift the training audio by in time.
""")
parser.add_argument(
'--testing_percentage',
type=int,
default=10,
help='What percentage of wavs to use as a test set.')
parser.add_argument(
'--validation_percentage',
type=int,
default=10,
help='What percentage of wavs to use as a validation set.')
parser.add_argument(
'--sample_rate',
type=int,
default=16000,
help='Expected sample rate of the wavs',)
parser.add_argument(
'--clip_duration_ms',
type=int,
default=1000,
help='Expected duration in milliseconds of the wavs',)
parser.add_argument(
'--window_size_ms',
type=float,
default=30.0,
help='How long each spectrogram timeslice is',)
parser.add_argument(
'--window_stride_ms',
type=float,
default=10.0,
help='How long each spectrogram timeslice is',)
parser.add_argument(
'--dct_coefficient_count',
type=int,
default=40,
help='How many bins to use for the MFCC fingerprint',)
parser.add_argument(
'--how_many_training_steps',
type=str,
default='15000,3000',
help='How many training loops to run',)
parser.add_argument(
'--eval_step_interval',
type=int,
default=400,
help='How often to evaluate the training results.')
parser.add_argument(
'--learning_rate',
type=str,
default='0.001,0.0001',
help='How large a learning rate to use when training.')
parser.add_argument(
'--batch_size',
type=int,
default=100,
help='How many items to train with at once',)
parser.add_argument(
'--summaries_dir',
type=str,
default='/tmp/retrain_logs',
help='Where to save summary logs for TensorBoard.')
parser.add_argument(
'--wanted_words',
type=str,
default='yes,no,up,down,left,right,on,off,stop,go',
help='Words to use (others will be added to an unknown label)',)
parser.add_argument(
'--train_dir',
type=str,
default='/tmp/speech_commands_train',
help='Directory to write event logs and checkpoint.')
parser.add_argument(
'--save_step_interval',
type=int,
default=100,
help='Save model checkpoint every save_steps.')
parser.add_argument(
'--start_checkpoint',
type=str,
default='',
help='If specified, restore this pretrained model before any training.')
parser.add_argument(
'--model_architecture',
type=str,
default='dnn',
help='What model architecture to use')
parser.add_argument(
'--model_size_info',
type=int,
nargs="+",
default=[128,128,128],
help='Model dimensions - different for various models')
parser.add_argument(
'--check_nans',
type=bool,
default=False,
help='Whether to check for invalid numbers during processing')
parser.add_argument("--quant", action='store_true',
default=False)
parser.add_argument("--bits", type=int, # 只有当quant参数有效的时候这个参数才能生效
default=8)
FLAGS, unparsed = parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
|
en
| 0.822123
|
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== # # Modifications Copyright 2017 Arm Inc. All Rights Reserved. # Added model dimensions as command line argument and changed to Adam optimizer # # Simple speech recognition to spot a limited number of keywords. This is a self-contained example script that will train a very basic audio recognition model in TensorFlow. It downloads the necessary training data and runs with reasonable defaults to train within a few hours even only using a CPU. For more information, please see https://www.tensorflow.org/tutorials/audio_recognition. It is intended as an introduction to using neural networks for audio recognition, and is not a full speech recognition system. For more advanced speech systems, I recommend looking into Kaldi. This network uses a keyword detection style to spot discrete words from a small vocabulary, consisting of "yes", "no", "up", "down", "left", "right", "on", "off", "stop", and "go". To run the training process, use: bazel run tensorflow/examples/speech_commands:train This will write out checkpoints to /tmp/speech_commands_train/, and will download over 1GB of open source training data, so you'll need enough free space and a good internet connection. The default data is a collection of thousands of one-second .wav files, each containing one spoken word. This data set is collected from https://aiyprojects.withgoogle.com/open_speech_recording, please consider contributing to help improve this and other models! As training progresses, it will print out its accuracy metrics, which should rise above 90% by the end. Once it's complete, you can run the freeze script to get a binary GraphDef that you can easily deploy on mobile applications. If you want to train on your own data, you'll need to create .wavs with your recordings, all at a consistent length, and then arrange them into subfolders organized by label. For example, here's a possible file structure: my_wavs > up > audio_0.wav audio_1.wav down > audio_2.wav audio_3.wav other> audio_4.wav audio_5.wav You'll also need to tell the script what labels to look for, using the `--wanted_words` argument. In this case, 'up,down' might be what you want, and the audio in the 'other' folder would be used to train an 'unknown' category. To pull this all together, you'd run: bazel run tensorflow/examples/speech_commands:train -- \ --data_dir=my_wavs --wanted_words=up,down # pylint: disable=redefined-builtin # We want to see all the logging messages for this tutorial. # Start a new TensorFlow session. # Begin by making sure we have the training data we need. If you already have # training data of your own, use `--data_url= ` on the command line to avoid # downloading. # print(model_settings['label_count']) # sys.exit(0) # Figure out the learning rates for each training phase. Since it's often # effective to have high learning rates at the start of training, followed by # lower levels towards the end, the number of steps and learning rates can be # specified as comma-separated lists to define the rate at each stage. For # example --how_many_training_steps=10000,3000 --learning_rate=0.001,0.0001 # will run 13,000 training loops in total, with a rate of 0.001 for the first # 10,000, and 0.0001 for the final 3,000. # is_training = tf.placeholder(shape=(), dtype=tf.bool) # Trainable vars has to be collected before adding quant ops. # Define loss and optimizer # Optionally we can add runtime checks to spot when NaNs or other symptoms of # numerical errors start occurring during training. # Now, create dependencies for quantizing weights # train_step = tf.train.GradientDescentOptimizer( # learning_rate_input).minimize(cross_entropy_mean) # Merge all the summaries and write them out to /tmp/retrain_logs (by default) # Parameter counts # Save graph.pbtxt. # Save list of words. # Training loop. # Figure out what the current learning rate is. # Pull the audio samples we'll use for training. # Run the graph with this batch of training data. #%d: rate %f, accuracy %.2f%%, cross entropy %f' % if (training_step % FLAGS.eval_step_interval) == 0 or is_last_step: set_size = audio_processor.set_size('validation') total_accuracy = 0 total_conf_matrix = None for i in xrange(0, set_size, FLAGS.batch_size): validation_fingerprints, validation_ground_truth = ( audio_processor.get_data(FLAGS.batch_size, i, model_settings, 0.0, 0.0, 0, 'validation', sess)) # Run a validation step and capture training summaries for TensorBoard # with the `merged` op. validation_summary, validation_accuracy, conf_matrix = sess.run( [merged_summaries, evaluation_step, confusion_matrix], feed_dict={ fingerprint_input: validation_fingerprints, ground_truth_input: validation_ground_truth, }) validation_writer.add_summary(validation_summary, training_step) batch_size = min(FLAGS.batch_size, set_size - i) total_accuracy += (validation_accuracy * batch_size) / set_size if total_conf_matrix is None: total_conf_matrix = conf_matrix else: total_conf_matrix += conf_matrix tf.logging.info('Confusion Matrix:\n %s' % (total_conf_matrix)) tf.logging.info('Step %d: Validation accuracy = %.2f%% (N=%d)' % (training_step, total_accuracy * 100, set_size)) # Save the model checkpoint when validation accuracy improves if total_accuracy > best_accuracy: best_accuracy = total_accuracy checkpoint_path = os.path.join(FLAGS.train_dir, 'best', FLAGS.model_architecture + '_' + str(int(best_accuracy * 10000)) + '.ckpt') tf.logging.info('Saving best model to "%s-%d"', checkpoint_path, training_step) saver.save(sess, checkpoint_path, global_step=training_step) tf.logging.info('So far the best validation accuracy is %.2f%%' % (best_accuracy * 100)) # pylint: disable=line-too-long # pylint: enable=line-too-long \ Where to download the speech training data to. \ How loud the background noise should be, between 0 and 1. \ How many of the training samples have background noise mixed in. \ How much of the training data should be silence. \ How much of the training data should be unknown words. \ Range to randomly shift the training audio by in time. # 只有当quant参数有效的时候这个参数才能生效
| 2.429794
| 2
|
click2pass/urls.py
|
iwagaki/click2pass
| 0
|
6625837
|
<filename>click2pass/urls.py
from django.conf.urls import patterns, include, url
from django.contrib import admin
admin.autodiscover()
urlpatterns = patterns('',
# Examples:
# url(r'^$', 'click2pass.views.home', name='home'),
# url(r'^blog/', include('blog.urls')),
url(r'^admin/', include(admin.site.urls)),
url(r'^service/$', 'service.views.index'),
url(r'^service/add_bookmark/$', 'service.views.add_bookmark'),
url(r'^service/delete_bookmark/(?P<objid>\d+)/$', 'service.views.delete_bookmark'),
url(r'^service/update_bookmark/(?P<objid>\d+)/$', 'service.views.update_bookmark'),
)
|
<filename>click2pass/urls.py
from django.conf.urls import patterns, include, url
from django.contrib import admin
admin.autodiscover()
urlpatterns = patterns('',
# Examples:
# url(r'^$', 'click2pass.views.home', name='home'),
# url(r'^blog/', include('blog.urls')),
url(r'^admin/', include(admin.site.urls)),
url(r'^service/$', 'service.views.index'),
url(r'^service/add_bookmark/$', 'service.views.add_bookmark'),
url(r'^service/delete_bookmark/(?P<objid>\d+)/$', 'service.views.delete_bookmark'),
url(r'^service/update_bookmark/(?P<objid>\d+)/$', 'service.views.update_bookmark'),
)
|
en
| 0.264136
|
# Examples: # url(r'^$', 'click2pass.views.home', name='home'), # url(r'^blog/', include('blog.urls')),
| 1.994119
| 2
|
net/net_nacl.gyp
|
domenic/mojo
| 5
|
6625838
|
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
{
'variables': {
'chromium_code': 1,
},
'includes': [
'../native_client/build/untrusted.gypi',
'net.gypi',
],
'targets': [
{
'target_name': 'net_nacl',
'type': 'none',
'variables': {
'nacl_untrusted_build': 1,
'nlib_target': 'libnet_nacl.a',
'build_glibc': 0,
'build_newlib': 0,
'build_pnacl_newlib': 1,
},
'dependencies': [
'../crypto/crypto_nacl.gyp:crypto_nacl',
'../native_client/tools.gyp:prep_toolchain',
'../native_client_sdk/native_client_sdk_untrusted.gyp:nacl_io_untrusted',
'../third_party/boringssl/boringssl_nacl.gyp:boringssl_nacl',
'../url/url_nacl.gyp:url_nacl',
'net.gyp:net_derived_sources',
'net.gyp:net_resources',
],
'defines': [
'NET_IMPLEMENTATION',
],
'pnacl_compile_flags': [
'-Wno-bind-to-temporary-copy',
],
'sources': [
'<@(net_nacl_common_sources)',
],
},
],
}
|
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
{
'variables': {
'chromium_code': 1,
},
'includes': [
'../native_client/build/untrusted.gypi',
'net.gypi',
],
'targets': [
{
'target_name': 'net_nacl',
'type': 'none',
'variables': {
'nacl_untrusted_build': 1,
'nlib_target': 'libnet_nacl.a',
'build_glibc': 0,
'build_newlib': 0,
'build_pnacl_newlib': 1,
},
'dependencies': [
'../crypto/crypto_nacl.gyp:crypto_nacl',
'../native_client/tools.gyp:prep_toolchain',
'../native_client_sdk/native_client_sdk_untrusted.gyp:nacl_io_untrusted',
'../third_party/boringssl/boringssl_nacl.gyp:boringssl_nacl',
'../url/url_nacl.gyp:url_nacl',
'net.gyp:net_derived_sources',
'net.gyp:net_resources',
],
'defines': [
'NET_IMPLEMENTATION',
],
'pnacl_compile_flags': [
'-Wno-bind-to-temporary-copy',
],
'sources': [
'<@(net_nacl_common_sources)',
],
},
],
}
|
en
| 0.917765
|
# Copyright 2014 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file.
| 1.173097
| 1
|
itdagene/core/migrations/0017_remove_user_mail_prefix.py
|
itdagene-ntnu/itdagene
| 9
|
6625839
|
<reponame>itdagene-ntnu/itdagene<filename>itdagene/core/migrations/0017_remove_user_mail_prefix.py<gh_stars>1-10
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [("core", "0016_auto_20141007_2055")]
operations = [migrations.RemoveField(model_name="user", name="mail_prefix")]
|
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [("core", "0016_auto_20141007_2055")]
operations = [migrations.RemoveField(model_name="user", name="mail_prefix")]
|
none
| 1
| 1.390406
| 1
|
|
tests/vfs/encrypted_stream_file_system.py
|
Acidburn0zzz/dfvfs
| 1
|
6625840
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests for the encrypted stream file system implementation."""
from __future__ import unicode_literals
import unittest
from dfvfs.lib import definitions
from dfvfs.path import encrypted_stream_path_spec
from dfvfs.path import os_path_spec
from dfvfs.resolver import context
from dfvfs.resolver import resolver
from dfvfs.vfs import encrypted_stream_file_system
from tests import test_lib as shared_test_lib
class EncryptedStreamFileSystemTest(shared_test_lib.BaseTestCase):
"""Tests the compressed stream file system."""
_RC4_KEY = b'rc4test'
def setUp(self):
"""Sets up the needed objects used throughout the test."""
self._resolver_context = context.Context()
test_file = self._GetTestFilePath(['syslog.rc4'])
self._SkipIfPathNotExists(test_file)
path_spec = os_path_spec.OSPathSpec(location=test_file)
self._encrypted_stream_path_spec = (
encrypted_stream_path_spec.EncryptedStreamPathSpec(
encryption_method=definitions.ENCRYPTION_METHOD_RC4,
parent=path_spec))
resolver.Resolver.key_chain.SetCredential(
self._encrypted_stream_path_spec, 'key', self._RC4_KEY)
def testOpenAndClose(self):
"""Test the open and close functionality."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
file_system.Close()
def testFileEntryExistsByPathSpec(self):
"""Test the file entry exists by path specification functionality."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
self.assertTrue(file_system.FileEntryExistsByPathSpec(
self._encrypted_stream_path_spec))
file_system.Close()
def testGetFileEntryByPathSpec(self):
"""Tests the GetFileEntryByPathSpec function."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
file_entry = file_system.GetFileEntryByPathSpec(
self._encrypted_stream_path_spec)
self.assertIsNotNone(file_entry)
self.assertEqual(file_entry.name, '')
file_system.Close()
def testGetRootFileEntry(self):
"""Test the get root file entry functionality."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
file_entry = file_system.GetRootFileEntry()
self.assertIsNotNone(file_entry)
self.assertEqual(file_entry.name, '')
file_system.Close()
if __name__ == '__main__':
unittest.main()
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests for the encrypted stream file system implementation."""
from __future__ import unicode_literals
import unittest
from dfvfs.lib import definitions
from dfvfs.path import encrypted_stream_path_spec
from dfvfs.path import os_path_spec
from dfvfs.resolver import context
from dfvfs.resolver import resolver
from dfvfs.vfs import encrypted_stream_file_system
from tests import test_lib as shared_test_lib
class EncryptedStreamFileSystemTest(shared_test_lib.BaseTestCase):
"""Tests the compressed stream file system."""
_RC4_KEY = b'rc4test'
def setUp(self):
"""Sets up the needed objects used throughout the test."""
self._resolver_context = context.Context()
test_file = self._GetTestFilePath(['syslog.rc4'])
self._SkipIfPathNotExists(test_file)
path_spec = os_path_spec.OSPathSpec(location=test_file)
self._encrypted_stream_path_spec = (
encrypted_stream_path_spec.EncryptedStreamPathSpec(
encryption_method=definitions.ENCRYPTION_METHOD_RC4,
parent=path_spec))
resolver.Resolver.key_chain.SetCredential(
self._encrypted_stream_path_spec, 'key', self._RC4_KEY)
def testOpenAndClose(self):
"""Test the open and close functionality."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
file_system.Close()
def testFileEntryExistsByPathSpec(self):
"""Test the file entry exists by path specification functionality."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
self.assertTrue(file_system.FileEntryExistsByPathSpec(
self._encrypted_stream_path_spec))
file_system.Close()
def testGetFileEntryByPathSpec(self):
"""Tests the GetFileEntryByPathSpec function."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
file_entry = file_system.GetFileEntryByPathSpec(
self._encrypted_stream_path_spec)
self.assertIsNotNone(file_entry)
self.assertEqual(file_entry.name, '')
file_system.Close()
def testGetRootFileEntry(self):
"""Test the get root file entry functionality."""
file_system = encrypted_stream_file_system.EncryptedStreamFileSystem(
self._resolver_context)
self.assertIsNotNone(file_system)
file_system.Open(self._encrypted_stream_path_spec)
file_entry = file_system.GetRootFileEntry()
self.assertIsNotNone(file_entry)
self.assertEqual(file_entry.name, '')
file_system.Close()
if __name__ == '__main__':
unittest.main()
|
en
| 0.852492
|
#!/usr/bin/env python # -*- coding: utf-8 -*- Tests for the encrypted stream file system implementation. Tests the compressed stream file system. Sets up the needed objects used throughout the test. Test the open and close functionality. Test the file entry exists by path specification functionality. Tests the GetFileEntryByPathSpec function. Test the get root file entry functionality.
| 2.393392
| 2
|
pyalect/shims.py
|
rmorshea/pyalect
| 4
|
6625841
|
import ast
import sys
from traceback import print_exc
from typing import Any, List, Optional, Type
from .dialect import DialectReducer, dialect_reducer
try:
from IPython.core.interactiveshell import InteractiveShell
from IPython.core.magic import magics_class, Magics, cell_magic
except ImportError:
pass
else:
_dialect_reducer_fifo_queue: List[DialectReducer] = []
class DialectNodeTransformer(ast.NodeTransformer):
"""Node transformer defined to hook into IPython."""
def visit(self, node: ast.AST) -> ast.AST:
try:
if isinstance(node, ast.Module):
first_node = next(ast.iter_child_nodes(node))
if (
isinstance(first_node, ast.Assign)
and isinstance(first_node.targets[0], ast.Name)
and first_node.targets[0].id == "_DIALECT_"
and isinstance(first_node.value, ast.Str)
):
node.body.pop(0)
node = _dialect_reducer_fifo_queue.pop(0).transform_ast(node)
return node
except Exception:
print_exc(file=sys.stderr)
return node
else:
return node
def register_to_ipython_shell(shell: Optional[InteractiveShell] = None) -> None:
"""Register transpiler hooks to IPython shell."""
shell_inst: InteractiveShell = shell or InteractiveShell.instance()
@magics_class
class DialectMagics(Magics): # type: ignore
def __init__(self, shell: InteractiveShell, **kwargs: Any) -> None:
super().__init__(shell, **kwargs)
for transformer in shell.ast_transformers:
if isinstance(transformer, DialectNodeTransformer):
break
else:
shell.ast_transformers.insert(0, DialectNodeTransformer())
@cell_magic # type: ignore
def dialect(self, cell_dialect: str, raw_cell: str) -> None:
reducer = dialect_reducer(cell_dialect)
_dialect_reducer_fifo_queue.append(reducer)
self.shell.run_cell(
# We need to prepend this since we can't look for
# the dialect comment when transforming the AST.
f"_DIALECT_ = {cell_dialect!r}\n"
+ reducer.transform_src(raw_cell)
)
shell_inst.register_magics(DialectMagics)
if InteractiveShell.initialized():
register_to_ipython_shell()
else:
original = InteractiveShell.instance.__func__
def wrapper(
cls: Type[InteractiveShell], *args: Any, **kwargs: Any
) -> InteractiveShell:
inst = original(cls, *args, **kwargs)
register_to_ipython_shell(inst)
return inst
InteractiveShell.instance = classmethod(wrapper)
|
import ast
import sys
from traceback import print_exc
from typing import Any, List, Optional, Type
from .dialect import DialectReducer, dialect_reducer
try:
from IPython.core.interactiveshell import InteractiveShell
from IPython.core.magic import magics_class, Magics, cell_magic
except ImportError:
pass
else:
_dialect_reducer_fifo_queue: List[DialectReducer] = []
class DialectNodeTransformer(ast.NodeTransformer):
"""Node transformer defined to hook into IPython."""
def visit(self, node: ast.AST) -> ast.AST:
try:
if isinstance(node, ast.Module):
first_node = next(ast.iter_child_nodes(node))
if (
isinstance(first_node, ast.Assign)
and isinstance(first_node.targets[0], ast.Name)
and first_node.targets[0].id == "_DIALECT_"
and isinstance(first_node.value, ast.Str)
):
node.body.pop(0)
node = _dialect_reducer_fifo_queue.pop(0).transform_ast(node)
return node
except Exception:
print_exc(file=sys.stderr)
return node
else:
return node
def register_to_ipython_shell(shell: Optional[InteractiveShell] = None) -> None:
"""Register transpiler hooks to IPython shell."""
shell_inst: InteractiveShell = shell or InteractiveShell.instance()
@magics_class
class DialectMagics(Magics): # type: ignore
def __init__(self, shell: InteractiveShell, **kwargs: Any) -> None:
super().__init__(shell, **kwargs)
for transformer in shell.ast_transformers:
if isinstance(transformer, DialectNodeTransformer):
break
else:
shell.ast_transformers.insert(0, DialectNodeTransformer())
@cell_magic # type: ignore
def dialect(self, cell_dialect: str, raw_cell: str) -> None:
reducer = dialect_reducer(cell_dialect)
_dialect_reducer_fifo_queue.append(reducer)
self.shell.run_cell(
# We need to prepend this since we can't look for
# the dialect comment when transforming the AST.
f"_DIALECT_ = {cell_dialect!r}\n"
+ reducer.transform_src(raw_cell)
)
shell_inst.register_magics(DialectMagics)
if InteractiveShell.initialized():
register_to_ipython_shell()
else:
original = InteractiveShell.instance.__func__
def wrapper(
cls: Type[InteractiveShell], *args: Any, **kwargs: Any
) -> InteractiveShell:
inst = original(cls, *args, **kwargs)
register_to_ipython_shell(inst)
return inst
InteractiveShell.instance = classmethod(wrapper)
|
en
| 0.835855
|
Node transformer defined to hook into IPython. Register transpiler hooks to IPython shell. # type: ignore # type: ignore # We need to prepend this since we can't look for # the dialect comment when transforming the AST.
| 2.034158
| 2
|
medium/260-Single Number III.py
|
Davidxswang/leetcode
| 2
|
6625842
|
<reponame>Davidxswang/leetcode
"""
https://leetcode.com/problems/single-number-iii/
Given an array of numbers nums, in which exactly two elements appear only once and all the other elements appear exactly twice. Find the two elements that appear only once.
Example:
Input: [1,2,1,3,2,5]
Output: [3,5]
Note:
The order of the result is not important. So in the above example, [5, 3] is also correct.
Your algorithm should run in linear runtime complexity. Could you implement it using only constant space complexity?
"""
# time complexity: O(n), space complexity: O(1)
# the solution is inspired by @zhiqing_xiao in the discussion area.
# the key here is to use one bit to separate the nums into two groups and use the xor(n1,n2) to find out the n1 in one group and n2 in the other group.
class Solution:
def singleNumber(self, nums: List[int]) -> List[int]:
if len(nums) == 2:
return nums
xor = 0
for num in nums:
xor ^= num
testbit = 1
while testbit & xor == 0:
testbit <<= 1
xor_set = xor
xor_unset = xor
for num in nums:
if testbit & num != 0:
xor_set ^= num
else:
xor_unset ^= num
return [xor_set, xor_unset]
|
"""
https://leetcode.com/problems/single-number-iii/
Given an array of numbers nums, in which exactly two elements appear only once and all the other elements appear exactly twice. Find the two elements that appear only once.
Example:
Input: [1,2,1,3,2,5]
Output: [3,5]
Note:
The order of the result is not important. So in the above example, [5, 3] is also correct.
Your algorithm should run in linear runtime complexity. Could you implement it using only constant space complexity?
"""
# time complexity: O(n), space complexity: O(1)
# the solution is inspired by @zhiqing_xiao in the discussion area.
# the key here is to use one bit to separate the nums into two groups and use the xor(n1,n2) to find out the n1 in one group and n2 in the other group.
class Solution:
def singleNumber(self, nums: List[int]) -> List[int]:
if len(nums) == 2:
return nums
xor = 0
for num in nums:
xor ^= num
testbit = 1
while testbit & xor == 0:
testbit <<= 1
xor_set = xor
xor_unset = xor
for num in nums:
if testbit & num != 0:
xor_set ^= num
else:
xor_unset ^= num
return [xor_set, xor_unset]
|
en
| 0.890938
|
https://leetcode.com/problems/single-number-iii/ Given an array of numbers nums, in which exactly two elements appear only once and all the other elements appear exactly twice. Find the two elements that appear only once. Example: Input: [1,2,1,3,2,5] Output: [3,5] Note: The order of the result is not important. So in the above example, [5, 3] is also correct. Your algorithm should run in linear runtime complexity. Could you implement it using only constant space complexity? # time complexity: O(n), space complexity: O(1) # the solution is inspired by @zhiqing_xiao in the discussion area. # the key here is to use one bit to separate the nums into two groups and use the xor(n1,n2) to find out the n1 in one group and n2 in the other group.
| 3.899644
| 4
|
tests/test_target_space.py
|
1aut/BayesianOptimization
| 6,106
|
6625843
|
import pytest
import numpy as np
from bayes_opt.target_space import TargetSpace
def target_func(**kwargs):
# arbitrary target func
return sum(kwargs.values())
PBOUNDS = {'p1': (0, 1), 'p2': (1, 100)}
def test_keys_and_bounds_in_same_order():
pbounds = {
'p1': (0, 1),
'p3': (0, 3),
'p2': (0, 2),
'p4': (0, 4),
}
space = TargetSpace(target_func, pbounds)
assert space.dim == len(pbounds)
assert space.empty
assert space.keys == ["p1", "p2", "p3", "p4"]
assert all(space.bounds[:, 0] == np.array([0, 0, 0, 0]))
assert all(space.bounds[:, 1] == np.array([1, 2, 3, 4]))
def test_params_to_array():
space = TargetSpace(target_func, PBOUNDS)
assert all(space.params_to_array({"p1": 2, "p2": 3}) == np.array([2, 3]))
assert all(space.params_to_array({"p2": 2, "p1": 9}) == np.array([9, 2]))
with pytest.raises(ValueError):
space.params_to_array({"p2": 1})
with pytest.raises(ValueError):
space.params_to_array({"p2": 1, "p1": 7, "other": 4})
with pytest.raises(ValueError):
space.params_to_array({"other": 1})
def test_array_to_params():
space = TargetSpace(target_func, PBOUNDS)
assert space.array_to_params(np.array([2, 3])) == {"p1": 2, "p2": 3}
with pytest.raises(ValueError):
space.array_to_params(np.array([2]))
with pytest.raises(ValueError):
space.array_to_params(np.array([2, 3, 5]))
def test_as_array():
space = TargetSpace(target_func, PBOUNDS)
x = space._as_array([0, 1])
assert x.shape == (2,)
assert all(x == np.array([0, 1]))
x = space._as_array({"p2": 1, "p1": 2})
assert x.shape == (2,)
assert all(x == np.array([2, 1]))
with pytest.raises(ValueError):
x = space._as_array([2, 1, 7])
with pytest.raises(ValueError):
x = space._as_array({"p2": 1, "p1": 2, "other": 7})
with pytest.raises(ValueError):
x = space._as_array({"p2": 1})
with pytest.raises(ValueError):
x = space._as_array({"other": 7})
def test_register():
space = TargetSpace(target_func, PBOUNDS)
assert len(space) == 0
# registering with dict
space.register(params={"p1": 1, "p2": 2}, target=3)
assert len(space) == 1
assert all(space.params[0] == np.array([1, 2]))
assert all(space.target == np.array([3]))
# registering with array
space.register(params={"p1": 5, "p2": 4}, target=9)
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
with pytest.raises(KeyError):
space.register(params={"p1": 1, "p2": 2}, target=3)
with pytest.raises(KeyError):
space.register(params={"p1": 5, "p2": 4}, target=9)
def test_probe():
space = TargetSpace(target_func, PBOUNDS)
assert len(space) == 0
# probing with dict
space.probe(params={"p1": 1, "p2": 2})
assert len(space) == 1
assert all(space.params[0] == np.array([1, 2]))
assert all(space.target == np.array([3]))
# probing with array
space.probe(np.array([5, 4]))
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
# probing same point with dict
space.probe(params={"p1": 1, "p2": 2})
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
# probing same point with array
space.probe(np.array([5, 4]))
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
def test_random_sample():
pbounds = {
'p1': (0, 1),
'p3': (0, 3),
'p2': (0, 2),
'p4': (0, 4),
}
space = TargetSpace(target_func, pbounds, random_state=8)
for _ in range(50):
random_sample = space.random_sample()
assert len(random_sample) == space.dim
assert all(random_sample >= space.bounds[:, 0])
assert all(random_sample <= space.bounds[:, 1])
def test_max():
space = TargetSpace(target_func, PBOUNDS)
assert space.max() == {}
space.probe(params={"p1": 1, "p2": 2})
space.probe(params={"p1": 5, "p2": 4})
space.probe(params={"p1": 2, "p2": 3})
space.probe(params={"p1": 1, "p2": 6})
assert space.max() == {"params": {"p1": 5, "p2": 4}, "target": 9}
def test_res():
space = TargetSpace(target_func, PBOUNDS)
assert space.res() == []
space.probe(params={"p1": 1, "p2": 2})
space.probe(params={"p1": 5, "p2": 4})
space.probe(params={"p1": 2, "p2": 3})
space.probe(params={"p1": 1, "p2": 6})
expected_res = [
{"params": {"p1": 1, "p2": 2}, "target": 3},
{"params": {"p1": 5, "p2": 4}, "target": 9},
{"params": {"p1": 2, "p2": 3}, "target": 5},
{"params": {"p1": 1, "p2": 6}, "target": 7},
]
assert len(space.res()) == 4
assert space.res() == expected_res
def test_set_bounds():
pbounds = {
'p1': (0, 1),
'p3': (0, 3),
'p2': (0, 2),
'p4': (0, 4),
}
space = TargetSpace(target_func, pbounds)
# Ignore unknown keys
space.set_bounds({"other": (7, 8)})
assert all(space.bounds[:, 0] == np.array([0, 0, 0, 0]))
assert all(space.bounds[:, 1] == np.array([1, 2, 3, 4]))
# Update bounds accordingly
space.set_bounds({"p2": (1, 8)})
assert all(space.bounds[:, 0] == np.array([0, 1, 0, 0]))
assert all(space.bounds[:, 1] == np.array([1, 8, 3, 4]))
if __name__ == '__main__':
r"""
CommandLine:
python tests/test_target_space.py
"""
pytest.main([__file__])
|
import pytest
import numpy as np
from bayes_opt.target_space import TargetSpace
def target_func(**kwargs):
# arbitrary target func
return sum(kwargs.values())
PBOUNDS = {'p1': (0, 1), 'p2': (1, 100)}
def test_keys_and_bounds_in_same_order():
pbounds = {
'p1': (0, 1),
'p3': (0, 3),
'p2': (0, 2),
'p4': (0, 4),
}
space = TargetSpace(target_func, pbounds)
assert space.dim == len(pbounds)
assert space.empty
assert space.keys == ["p1", "p2", "p3", "p4"]
assert all(space.bounds[:, 0] == np.array([0, 0, 0, 0]))
assert all(space.bounds[:, 1] == np.array([1, 2, 3, 4]))
def test_params_to_array():
space = TargetSpace(target_func, PBOUNDS)
assert all(space.params_to_array({"p1": 2, "p2": 3}) == np.array([2, 3]))
assert all(space.params_to_array({"p2": 2, "p1": 9}) == np.array([9, 2]))
with pytest.raises(ValueError):
space.params_to_array({"p2": 1})
with pytest.raises(ValueError):
space.params_to_array({"p2": 1, "p1": 7, "other": 4})
with pytest.raises(ValueError):
space.params_to_array({"other": 1})
def test_array_to_params():
space = TargetSpace(target_func, PBOUNDS)
assert space.array_to_params(np.array([2, 3])) == {"p1": 2, "p2": 3}
with pytest.raises(ValueError):
space.array_to_params(np.array([2]))
with pytest.raises(ValueError):
space.array_to_params(np.array([2, 3, 5]))
def test_as_array():
space = TargetSpace(target_func, PBOUNDS)
x = space._as_array([0, 1])
assert x.shape == (2,)
assert all(x == np.array([0, 1]))
x = space._as_array({"p2": 1, "p1": 2})
assert x.shape == (2,)
assert all(x == np.array([2, 1]))
with pytest.raises(ValueError):
x = space._as_array([2, 1, 7])
with pytest.raises(ValueError):
x = space._as_array({"p2": 1, "p1": 2, "other": 7})
with pytest.raises(ValueError):
x = space._as_array({"p2": 1})
with pytest.raises(ValueError):
x = space._as_array({"other": 7})
def test_register():
space = TargetSpace(target_func, PBOUNDS)
assert len(space) == 0
# registering with dict
space.register(params={"p1": 1, "p2": 2}, target=3)
assert len(space) == 1
assert all(space.params[0] == np.array([1, 2]))
assert all(space.target == np.array([3]))
# registering with array
space.register(params={"p1": 5, "p2": 4}, target=9)
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
with pytest.raises(KeyError):
space.register(params={"p1": 1, "p2": 2}, target=3)
with pytest.raises(KeyError):
space.register(params={"p1": 5, "p2": 4}, target=9)
def test_probe():
space = TargetSpace(target_func, PBOUNDS)
assert len(space) == 0
# probing with dict
space.probe(params={"p1": 1, "p2": 2})
assert len(space) == 1
assert all(space.params[0] == np.array([1, 2]))
assert all(space.target == np.array([3]))
# probing with array
space.probe(np.array([5, 4]))
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
# probing same point with dict
space.probe(params={"p1": 1, "p2": 2})
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
# probing same point with array
space.probe(np.array([5, 4]))
assert len(space) == 2
assert all(space.params[1] == np.array([5, 4]))
assert all(space.target == np.array([3, 9]))
def test_random_sample():
pbounds = {
'p1': (0, 1),
'p3': (0, 3),
'p2': (0, 2),
'p4': (0, 4),
}
space = TargetSpace(target_func, pbounds, random_state=8)
for _ in range(50):
random_sample = space.random_sample()
assert len(random_sample) == space.dim
assert all(random_sample >= space.bounds[:, 0])
assert all(random_sample <= space.bounds[:, 1])
def test_max():
space = TargetSpace(target_func, PBOUNDS)
assert space.max() == {}
space.probe(params={"p1": 1, "p2": 2})
space.probe(params={"p1": 5, "p2": 4})
space.probe(params={"p1": 2, "p2": 3})
space.probe(params={"p1": 1, "p2": 6})
assert space.max() == {"params": {"p1": 5, "p2": 4}, "target": 9}
def test_res():
space = TargetSpace(target_func, PBOUNDS)
assert space.res() == []
space.probe(params={"p1": 1, "p2": 2})
space.probe(params={"p1": 5, "p2": 4})
space.probe(params={"p1": 2, "p2": 3})
space.probe(params={"p1": 1, "p2": 6})
expected_res = [
{"params": {"p1": 1, "p2": 2}, "target": 3},
{"params": {"p1": 5, "p2": 4}, "target": 9},
{"params": {"p1": 2, "p2": 3}, "target": 5},
{"params": {"p1": 1, "p2": 6}, "target": 7},
]
assert len(space.res()) == 4
assert space.res() == expected_res
def test_set_bounds():
pbounds = {
'p1': (0, 1),
'p3': (0, 3),
'p2': (0, 2),
'p4': (0, 4),
}
space = TargetSpace(target_func, pbounds)
# Ignore unknown keys
space.set_bounds({"other": (7, 8)})
assert all(space.bounds[:, 0] == np.array([0, 0, 0, 0]))
assert all(space.bounds[:, 1] == np.array([1, 2, 3, 4]))
# Update bounds accordingly
space.set_bounds({"p2": (1, 8)})
assert all(space.bounds[:, 0] == np.array([0, 1, 0, 0]))
assert all(space.bounds[:, 1] == np.array([1, 8, 3, 4]))
if __name__ == '__main__':
r"""
CommandLine:
python tests/test_target_space.py
"""
pytest.main([__file__])
|
en
| 0.734463
|
# arbitrary target func # registering with dict # registering with array # probing with dict # probing with array # probing same point with dict # probing same point with array # Ignore unknown keys # Update bounds accordingly CommandLine: python tests/test_target_space.py
| 2.173089
| 2
|
wevote_functions/tests.py
|
adborden/WeVoteBase
| 0
|
6625844
|
<reponame>adborden/WeVoteBase
# wevote_functions/tests.py
# Brought to you by We Vote. Be good.
# -*- coding: UTF-8 -*-
from django.test import TestCase
# Create your tests here.
|
# wevote_functions/tests.py
# Brought to you by We Vote. Be good.
# -*- coding: UTF-8 -*-
from django.test import TestCase
# Create your tests here.
|
en
| 0.841974
|
# wevote_functions/tests.py # Brought to you by We Vote. Be good. # -*- coding: UTF-8 -*- # Create your tests here.
| 1.233027
| 1
|
nova/api/openstack/compute/plugins/v3/instance_actions.py
|
bopopescu/nova-master
| 3
|
6625845
|
<reponame>bopopescu/nova-master<filename>nova/api/openstack/compute/plugins/v3/instance_actions.py<gh_stars>1-10
# Copyright 2013 Rackspace Hosting
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from webob import exc
from nova.api.openstack import common
from nova.api.openstack import extensions
from nova.api.openstack import wsgi
from nova import compute
from nova.openstack.common.gettextutils import _
ALIAS = "os-instance-actions"
authorize_actions = extensions.extension_authorizer('compute',
'v3:' + ALIAS)
authorize_events = extensions.soft_extension_authorizer('compute',
'v3:' + ALIAS + ':events')
ACTION_KEYS = ['action', 'instance_uuid', 'request_id', 'user_id',
'project_id', 'start_time', 'message']
EVENT_KEYS = ['event', 'start_time', 'finish_time', 'result', 'traceback']
class InstanceActionsController(wsgi.Controller):
def __init__(self):
super(InstanceActionsController, self).__init__()
self.compute_api = compute.API()
self.action_api = compute.InstanceActionAPI()
def _format_action(self, action_raw):
action = {}
for key in ACTION_KEYS:
action[key] = action_raw.get(key)
return action
def _format_event(self, event_raw):
event = {}
for key in EVENT_KEYS:
event[key] = event_raw.get(key)
return event
@extensions.expected_errors(404)
def index(self, req, server_id):
"""Returns the list of actions recorded for a given instance."""
context = req.environ["nova.context"]
instance = common.get_instance(self.compute_api, context, server_id)
authorize_actions(context, target=instance)
actions_raw = self.action_api.actions_get(context, instance)
actions = [self._format_action(action) for action in actions_raw]
return {'instance_actions': actions}
@extensions.expected_errors(404)
def show(self, req, server_id, id):
"""Return data about the given instance action."""
context = req.environ['nova.context']
instance = common.get_instance(self.compute_api, context, server_id)
authorize_actions(context, target=instance)
action = self.action_api.action_get_by_request_id(context, instance,
id)
if action is None:
msg = _("Action %s not found") % id
raise exc.HTTPNotFound(msg)
action_id = action['id']
action = self._format_action(action)
if authorize_events(context):
events_raw = self.action_api.action_events_get(context, instance,
action_id)
action['events'] = [self._format_event(evt) for evt in events_raw]
return {'instance_action': action}
class InstanceActions(extensions.V3APIExtensionBase):
"""View a log of actions and events taken on an instance."""
name = "InstanceActions"
alias = ALIAS
version = 1
def get_resources(self):
ext = extensions.ResourceExtension('os-instance-actions',
InstanceActionsController(),
parent=dict(
member_name='server',
collection_name='servers'))
return [ext]
def get_controller_extensions(self):
"""It's an abstract function V3APIExtensionBase and the extension
will not be loaded without it.
"""
return []
|
# Copyright 2013 Rackspace Hosting
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from webob import exc
from nova.api.openstack import common
from nova.api.openstack import extensions
from nova.api.openstack import wsgi
from nova import compute
from nova.openstack.common.gettextutils import _
ALIAS = "os-instance-actions"
authorize_actions = extensions.extension_authorizer('compute',
'v3:' + ALIAS)
authorize_events = extensions.soft_extension_authorizer('compute',
'v3:' + ALIAS + ':events')
ACTION_KEYS = ['action', 'instance_uuid', 'request_id', 'user_id',
'project_id', 'start_time', 'message']
EVENT_KEYS = ['event', 'start_time', 'finish_time', 'result', 'traceback']
class InstanceActionsController(wsgi.Controller):
def __init__(self):
super(InstanceActionsController, self).__init__()
self.compute_api = compute.API()
self.action_api = compute.InstanceActionAPI()
def _format_action(self, action_raw):
action = {}
for key in ACTION_KEYS:
action[key] = action_raw.get(key)
return action
def _format_event(self, event_raw):
event = {}
for key in EVENT_KEYS:
event[key] = event_raw.get(key)
return event
@extensions.expected_errors(404)
def index(self, req, server_id):
"""Returns the list of actions recorded for a given instance."""
context = req.environ["nova.context"]
instance = common.get_instance(self.compute_api, context, server_id)
authorize_actions(context, target=instance)
actions_raw = self.action_api.actions_get(context, instance)
actions = [self._format_action(action) for action in actions_raw]
return {'instance_actions': actions}
@extensions.expected_errors(404)
def show(self, req, server_id, id):
"""Return data about the given instance action."""
context = req.environ['nova.context']
instance = common.get_instance(self.compute_api, context, server_id)
authorize_actions(context, target=instance)
action = self.action_api.action_get_by_request_id(context, instance,
id)
if action is None:
msg = _("Action %s not found") % id
raise exc.HTTPNotFound(msg)
action_id = action['id']
action = self._format_action(action)
if authorize_events(context):
events_raw = self.action_api.action_events_get(context, instance,
action_id)
action['events'] = [self._format_event(evt) for evt in events_raw]
return {'instance_action': action}
class InstanceActions(extensions.V3APIExtensionBase):
"""View a log of actions and events taken on an instance."""
name = "InstanceActions"
alias = ALIAS
version = 1
def get_resources(self):
ext = extensions.ResourceExtension('os-instance-actions',
InstanceActionsController(),
parent=dict(
member_name='server',
collection_name='servers'))
return [ext]
def get_controller_extensions(self):
"""It's an abstract function V3APIExtensionBase and the extension
will not be loaded without it.
"""
return []
|
en
| 0.860044
|
# Copyright 2013 Rackspace Hosting # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. Returns the list of actions recorded for a given instance. Return data about the given instance action. View a log of actions and events taken on an instance. It's an abstract function V3APIExtensionBase and the extension will not be loaded without it.
| 1.734924
| 2
|
src/euler_python_package/euler_python/medium/p318.py
|
wilsonify/euler
| 0
|
6625846
|
def problem318():
pass
|
def problem318():
pass
|
none
| 1
| 0.875471
| 1
|
|
nodular_JJ/finite_sc/Vj scan/E_Vj.py
|
tbcole/majoranaJJ
| 0
|
6625847
|
<reponame>tbcole/majoranaJJ<filename>nodular_JJ/finite_sc/Vj scan/E_Vj.py<gh_stars>0
import sys
import os
import numpy as np
import gc
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.patches as patches
import scipy.sparse as sparse
import scipy.linalg as LA
import scipy.sparse.linalg as spLA
import majoranaJJ.operators.sparse.qmsops as spop #sparse operators
import majoranaJJ.lattice.nbrs as nb #neighbor arrays
import majoranaJJ.lattice.shapes as shps #lattice shapes
import majoranaJJ.modules.plots as plots #plotting functions
from majoranaJJ.operators.sparse.potentials import Vjj #potential JJ
dir = os.getcwd()
###################################################
#Defining System
Nx = 20 #Number of lattice sites along x-direction
Ny = 408 #Number of lattice sites along y-direction
ax = 50 #lattice spacing in x-direction: [A]
ay = 50 #lattice spacing in y-direction: [A]
Wj = 11 #Junction region
cutx = 0 #width of nodule
cuty = 0 #height of nodule
Junc_width = Wj*ay*.1 #nm
SC_width = ((Ny - Wj)*ay*.10)/2 #nm
Nod_widthx = cutx*ax*.1 #nm
Nod_widthy = cuty*ay*.1 #nm
print("Nodule Width in x-direction = ", Nod_widthx, "(nm)")
print("Nodule Width in y-direction = ", Nod_widthy, "(nm)")
print("Junction Width = ", Junc_width, "(nm)")
print("Supercondicting Lead Width = ", SC_width, "(nm)")
###################################################
coor = shps.square(Nx, Ny) #square lattice
NN = nb.NN_Arr(coor) #neighbor array
NNb = nb.Bound_Arr(coor) #boundary array
lat_size = coor.shape[0]
Lx = (max(coor[:, 0]) - min(coor[:, 0]) + 1)*ax #Unit cell size in x-direction
Ly = (max(coor[:, 1]) - min(coor[:, 1]) + 1)*ay #Unit cell size in y-direction
print("Lattice size in x-direction", Lx*.1, "(nm)")
print("Lattice size in y-direction", Ly*.1, "(nm)")
###################################################
#Hamiltonian Parameters
alpha = 100 #Spin-Orbit Coupling constant: [meV*A]
gx = 0 #parallel to junction: [meV]
gz = 0 #normal to plane of junction: [meV]
delta = 1.0 #Superconducting Gap: [meV]
Vsc = -30 #Amplitude of potential: [meV]
V = Vjj(coor, Wj = Wj, Vsc = Vsc, Vj = 0, cutx = cutx, cuty = cuty)
#####################################
k = 44 #This is the number of eigenvalues and eigenvectors you want
v_steps = 500 #Number of kx values that are evaluated
v_i = -100
v_f = -50
Vj = np.linspace(v_i, v_f, v_steps) #Chemical Potential: [meV]
bands = np.zeros((v_steps, k))
cmap = cm.get_cmap('Oranges')
dirS = 'e_mu_data'
if not os.path.exists(dirS):
os.makedirs(dirS)
try:
PLOT = str(sys.argv[1])
except:
PLOT = 'F'
if PLOT != 'P':
for j in range(v_steps):
V = Vjj(coor, Wj = Wj, Vsc = Vsc, Vj = Vj[j], cutx = cutx, cuty = cuty)
print(v_steps - j)
H = spop.HBDG(coor, ax, ay, NN, NNb=NNb, Wj=Wj, cutx=cutx, cuty=cuty, V=V, mu=0, alpha=alpha, delta=delta, phi=0, qx=0, periodicX=True)
eigs, vecs = spLA.eigsh(H, k=k, sigma=0, which='LM')
idx_sort = np.argsort(eigs)
eigs = eigs[idx_sort]
bands[j, :] = eigs
np.save("%s/bands Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f), bands)
np.save("%s/V0 Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f), Vj)
else:
bands = np.load("%s/bands Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f))
mu = np.load("%s/V0 Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f))
fig = plt.figure()
for j in range(bands.shape[1]):
plt.plot(Vj, bands[:, j], c='r')
plt.xlabel(r"$V_{j}$ (meV)")
plt.ylabel("E (meV)")
plt.title(r"Lx = %.1f nm, Ly = %.1f nm, $\Delta$ = %.2f meV, $\alpha$ = %.2f meV A, $W_{sc}$ = %.1f nm, $W_J$ = %.1f nm, $Nodule_x$ = %.1f nm, $Nodule_y$ = %.1f nm" % (Lx*.1, Ly*.1, delta, alpha, SC_width, Junc_width, Nod_widthx, Nod_widthy), loc = 'center', wrap=True)
plt.ylim(-1.5, 1.5)
plt.subplots_adjust(top=0.85)
plt.savefig("nodx={} nody={}.png".format(Nod_widthx, Nod_widthy))
plt.show()
|
scan/E_Vj.py<gh_stars>0
import sys
import os
import numpy as np
import gc
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.patches as patches
import scipy.sparse as sparse
import scipy.linalg as LA
import scipy.sparse.linalg as spLA
import majoranaJJ.operators.sparse.qmsops as spop #sparse operators
import majoranaJJ.lattice.nbrs as nb #neighbor arrays
import majoranaJJ.lattice.shapes as shps #lattice shapes
import majoranaJJ.modules.plots as plots #plotting functions
from majoranaJJ.operators.sparse.potentials import Vjj #potential JJ
dir = os.getcwd()
###################################################
#Defining System
Nx = 20 #Number of lattice sites along x-direction
Ny = 408 #Number of lattice sites along y-direction
ax = 50 #lattice spacing in x-direction: [A]
ay = 50 #lattice spacing in y-direction: [A]
Wj = 11 #Junction region
cutx = 0 #width of nodule
cuty = 0 #height of nodule
Junc_width = Wj*ay*.1 #nm
SC_width = ((Ny - Wj)*ay*.10)/2 #nm
Nod_widthx = cutx*ax*.1 #nm
Nod_widthy = cuty*ay*.1 #nm
print("Nodule Width in x-direction = ", Nod_widthx, "(nm)")
print("Nodule Width in y-direction = ", Nod_widthy, "(nm)")
print("Junction Width = ", Junc_width, "(nm)")
print("Supercondicting Lead Width = ", SC_width, "(nm)")
###################################################
coor = shps.square(Nx, Ny) #square lattice
NN = nb.NN_Arr(coor) #neighbor array
NNb = nb.Bound_Arr(coor) #boundary array
lat_size = coor.shape[0]
Lx = (max(coor[:, 0]) - min(coor[:, 0]) + 1)*ax #Unit cell size in x-direction
Ly = (max(coor[:, 1]) - min(coor[:, 1]) + 1)*ay #Unit cell size in y-direction
print("Lattice size in x-direction", Lx*.1, "(nm)")
print("Lattice size in y-direction", Ly*.1, "(nm)")
###################################################
#Hamiltonian Parameters
alpha = 100 #Spin-Orbit Coupling constant: [meV*A]
gx = 0 #parallel to junction: [meV]
gz = 0 #normal to plane of junction: [meV]
delta = 1.0 #Superconducting Gap: [meV]
Vsc = -30 #Amplitude of potential: [meV]
V = Vjj(coor, Wj = Wj, Vsc = Vsc, Vj = 0, cutx = cutx, cuty = cuty)
#####################################
k = 44 #This is the number of eigenvalues and eigenvectors you want
v_steps = 500 #Number of kx values that are evaluated
v_i = -100
v_f = -50
Vj = np.linspace(v_i, v_f, v_steps) #Chemical Potential: [meV]
bands = np.zeros((v_steps, k))
cmap = cm.get_cmap('Oranges')
dirS = 'e_mu_data'
if not os.path.exists(dirS):
os.makedirs(dirS)
try:
PLOT = str(sys.argv[1])
except:
PLOT = 'F'
if PLOT != 'P':
for j in range(v_steps):
V = Vjj(coor, Wj = Wj, Vsc = Vsc, Vj = Vj[j], cutx = cutx, cuty = cuty)
print(v_steps - j)
H = spop.HBDG(coor, ax, ay, NN, NNb=NNb, Wj=Wj, cutx=cutx, cuty=cuty, V=V, mu=0, alpha=alpha, delta=delta, phi=0, qx=0, periodicX=True)
eigs, vecs = spLA.eigsh(H, k=k, sigma=0, which='LM')
idx_sort = np.argsort(eigs)
eigs = eigs[idx_sort]
bands[j, :] = eigs
np.save("%s/bands Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f), bands)
np.save("%s/V0 Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f), Vj)
else:
bands = np.load("%s/bands Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f))
mu = np.load("%s/V0 Lx = %.1f Ly = %.1f Wsc = %.1f Wj = %.1f nodx = %.1f nody = %.1f alpha = %.1f delta = %.2f v_i = %.1f v_f = %.1f.npy" % (dirS, Lx*.1, Ly*.1, SC_width, Junc_width, Nod_widthx, Nod_widthy, alpha, delta, v_i, v_f))
fig = plt.figure()
for j in range(bands.shape[1]):
plt.plot(Vj, bands[:, j], c='r')
plt.xlabel(r"$V_{j}$ (meV)")
plt.ylabel("E (meV)")
plt.title(r"Lx = %.1f nm, Ly = %.1f nm, $\Delta$ = %.2f meV, $\alpha$ = %.2f meV A, $W_{sc}$ = %.1f nm, $W_J$ = %.1f nm, $Nodule_x$ = %.1f nm, $Nodule_y$ = %.1f nm" % (Lx*.1, Ly*.1, delta, alpha, SC_width, Junc_width, Nod_widthx, Nod_widthy), loc = 'center', wrap=True)
plt.ylim(-1.5, 1.5)
plt.subplots_adjust(top=0.85)
plt.savefig("nodx={} nody={}.png".format(Nod_widthx, Nod_widthy))
plt.show()
|
en
| 0.509114
|
#sparse operators #neighbor arrays #lattice shapes #plotting functions #potential JJ ################################################### #Defining System #Number of lattice sites along x-direction #Number of lattice sites along y-direction #lattice spacing in x-direction: [A] #lattice spacing in y-direction: [A] #Junction region #width of nodule #height of nodule #nm #nm #nm #nm ################################################### #square lattice #neighbor array #boundary array #Unit cell size in x-direction #Unit cell size in y-direction ################################################### #Hamiltonian Parameters #Spin-Orbit Coupling constant: [meV*A] #parallel to junction: [meV] #normal to plane of junction: [meV] #Superconducting Gap: [meV] #Amplitude of potential: [meV] ##################################### #This is the number of eigenvalues and eigenvectors you want #Number of kx values that are evaluated #Chemical Potential: [meV]
| 2.245164
| 2
|
congress/api/row_model.py
|
poobalan-arumugam/congress
| 0
|
6625848
|
# Copyright (c) 2014 VMware, Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
from oslo_log import log as logging
from congress.api import api_utils
from congress.api import base
from congress.api import webservice
from congress import exception
LOG = logging.getLogger(__name__)
class RowModel(base.APIModel):
"""Model for handling API requests about Rows."""
# TODO(thinrichs): No rows have IDs right now. Maybe eventually
# could make ID the hash of the row, but then might as well
# just make the ID a string repr of the row. No use case
# for it as of now since all rows are read-only.
# def get_item(self, id_, context=None):
# """Retrieve item with id id\_ from model.
# Args:
# id_: The ID of the item to retrieve
# context: Key-values providing frame of reference of request
# Returns:
# The matching item or None if item with id\_ does not exist.
# """
# Note(thread-safety): blocking function
def get_items(self, params, context=None):
"""Get items in model.
:param: params: A dict-like object containing parameters
from the request query string and body.
:param: context: Key-values providing frame of reference of request
:returns: A dict containing at least a 'results' key whose value is
a list of items in the model. Additional keys set in the
dict will also be rendered for the user.
"""
LOG.info("get_items(context=%s)", context)
gen_trace = False
if 'trace' in params and params['trace'].lower() == 'true':
gen_trace = True
# Get the caller, it should be either policy or datasource
# Note(thread-safety): blocking call
caller, source_id = api_utils.get_id_from_context(context)
# FIXME(threod-safety): in DSE2, the returned caller can be a
# datasource name. But the datasource name may now refer to a new,
# unrelated datasource. Causing the rest of this code to operate on
# an unintended datasource.
# It would have saved us if table_id was an UUID rather than a name,
# but it appears that table_id is just another word for tablename.
# Fix: check UUID of datasource before operating. Abort if mismatch
table_id = context['table_id']
try:
args = {'table_id': table_id, 'source_id': source_id,
'trace': gen_trace}
if caller is base.ENGINE_SERVICE_ID:
# allow extra time for row policy engine query
# Note(thread-safety): blocking call
result = self.invoke_rpc(
caller, 'get_row_data', args,
timeout=self.dse_long_timeout)
else:
# Note(thread-safety): blocking call
result = self.invoke_rpc(caller, 'get_row_data', args)
except exception.CongressException as e:
m = ("Error occurred while processing source_id '%s' for row "
"data of the table '%s'" % (source_id, table_id))
LOG.exception(m)
raise webservice.DataModelException.create(e)
if gen_trace and caller is base.ENGINE_SERVICE_ID:
# DSE2 returns lists instead of tuples, so correct that.
results = [{'data': tuple(x['data'])} for x in result[0]]
return {'results': results,
'trace': result[1] or "Not available"}
else:
result = [{'data': tuple(x['data'])} for x in result]
return {'results': result}
# Note(thread-safety): blocking function
def replace_items(self, items, params, context=None):
"""Replaces all data in a table.
:param: id\_: A table id for replacing all row
:param: items: A data for new rows
:param: params: A dict-like object containing parameters from
request query
:param: context: Key-values providing frame of reference of request
:returns: None
:raises KeyError: table id doesn't exist
:raises DataModelException: any error occurs during replacing rows.
"""
LOG.info("replace_items(context=%s)", context)
# Note(thread-safety): blocking call
caller, source_id = api_utils.get_id_from_context(context)
# FIXME(threod-safety): in DSE2, the returned caller can be a
# datasource name. But the datasource name may now refer to a new,
# unrelated datasource. Causing the rest of this code to operate on
# an unintended datasource.
# It would have saved us if table_id was an UUID rather than a name,
# but it appears that table_id is just another word for tablename.
# Fix: check UUID of datasource before operating. Abort if mismatch
table_id = context['table_id']
try:
args = {'table_id': table_id, 'source_id': source_id,
'objs': items}
# Note(thread-safety): blocking call
self.invoke_rpc(caller, 'replace_entire_table_data', args)
except exception.CongressException as e:
LOG.exception("Error occurred while processing updating rows "
"for source_id '%s' and table_id '%s'",
source_id, table_id)
raise webservice.DataModelException.create(e)
LOG.info("finish replace_items(context=%s)", context)
LOG.debug("replaced table %s with row items: %s",
table_id, str(items))
# TODO(thinrichs): It makes sense to sometimes allow users to create
# a new row for internal data sources. But since we don't have
# those yet all tuples are read-only from the API.
# def add_item(self, item, id_=None, context=None):
# """Add item to model.
# Args:
# item: The item to add to the model
# id_: The ID of the item, or None if an ID should be generated
# context: Key-values providing frame of reference of request
# Returns:
# Tuple of (ID, newly_created_item)
# Raises:
# KeyError: ID already exists.
# """
# TODO(thinrichs): once we have internal data sources,
# add the ability to update a row. (Or maybe not and implement
# via add+delete.)
# def update_item(self, id_, item, context=None):
# """Update item with id\_ with new data.
# Args:
# id_: The ID of the item to be updated
# item: The new item
# context: Key-values providing frame of reference of request
# Returns:
# The updated item.
# Raises:
# KeyError: Item with specified id\_ not present.
# """
# # currently a noop since the owner_id cannot be changed
# if id_ not in self.items:
# raise KeyError("Cannot update item with ID '%s': "
# "ID does not exist")
# return item
# TODO(thinrichs): once we can create, we should be able to delete
# def delete_item(self, id_, context=None):
# """Remove item from model.
# Args:
# id_: The ID of the item to be removed
# context: Key-values providing frame of reference of request
# Returns:
# The removed item.
# Raises:
# KeyError: Item with specified id\_ not present.
# """
|
# Copyright (c) 2014 VMware, Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
from oslo_log import log as logging
from congress.api import api_utils
from congress.api import base
from congress.api import webservice
from congress import exception
LOG = logging.getLogger(__name__)
class RowModel(base.APIModel):
"""Model for handling API requests about Rows."""
# TODO(thinrichs): No rows have IDs right now. Maybe eventually
# could make ID the hash of the row, but then might as well
# just make the ID a string repr of the row. No use case
# for it as of now since all rows are read-only.
# def get_item(self, id_, context=None):
# """Retrieve item with id id\_ from model.
# Args:
# id_: The ID of the item to retrieve
# context: Key-values providing frame of reference of request
# Returns:
# The matching item or None if item with id\_ does not exist.
# """
# Note(thread-safety): blocking function
def get_items(self, params, context=None):
"""Get items in model.
:param: params: A dict-like object containing parameters
from the request query string and body.
:param: context: Key-values providing frame of reference of request
:returns: A dict containing at least a 'results' key whose value is
a list of items in the model. Additional keys set in the
dict will also be rendered for the user.
"""
LOG.info("get_items(context=%s)", context)
gen_trace = False
if 'trace' in params and params['trace'].lower() == 'true':
gen_trace = True
# Get the caller, it should be either policy or datasource
# Note(thread-safety): blocking call
caller, source_id = api_utils.get_id_from_context(context)
# FIXME(threod-safety): in DSE2, the returned caller can be a
# datasource name. But the datasource name may now refer to a new,
# unrelated datasource. Causing the rest of this code to operate on
# an unintended datasource.
# It would have saved us if table_id was an UUID rather than a name,
# but it appears that table_id is just another word for tablename.
# Fix: check UUID of datasource before operating. Abort if mismatch
table_id = context['table_id']
try:
args = {'table_id': table_id, 'source_id': source_id,
'trace': gen_trace}
if caller is base.ENGINE_SERVICE_ID:
# allow extra time for row policy engine query
# Note(thread-safety): blocking call
result = self.invoke_rpc(
caller, 'get_row_data', args,
timeout=self.dse_long_timeout)
else:
# Note(thread-safety): blocking call
result = self.invoke_rpc(caller, 'get_row_data', args)
except exception.CongressException as e:
m = ("Error occurred while processing source_id '%s' for row "
"data of the table '%s'" % (source_id, table_id))
LOG.exception(m)
raise webservice.DataModelException.create(e)
if gen_trace and caller is base.ENGINE_SERVICE_ID:
# DSE2 returns lists instead of tuples, so correct that.
results = [{'data': tuple(x['data'])} for x in result[0]]
return {'results': results,
'trace': result[1] or "Not available"}
else:
result = [{'data': tuple(x['data'])} for x in result]
return {'results': result}
# Note(thread-safety): blocking function
def replace_items(self, items, params, context=None):
"""Replaces all data in a table.
:param: id\_: A table id for replacing all row
:param: items: A data for new rows
:param: params: A dict-like object containing parameters from
request query
:param: context: Key-values providing frame of reference of request
:returns: None
:raises KeyError: table id doesn't exist
:raises DataModelException: any error occurs during replacing rows.
"""
LOG.info("replace_items(context=%s)", context)
# Note(thread-safety): blocking call
caller, source_id = api_utils.get_id_from_context(context)
# FIXME(threod-safety): in DSE2, the returned caller can be a
# datasource name. But the datasource name may now refer to a new,
# unrelated datasource. Causing the rest of this code to operate on
# an unintended datasource.
# It would have saved us if table_id was an UUID rather than a name,
# but it appears that table_id is just another word for tablename.
# Fix: check UUID of datasource before operating. Abort if mismatch
table_id = context['table_id']
try:
args = {'table_id': table_id, 'source_id': source_id,
'objs': items}
# Note(thread-safety): blocking call
self.invoke_rpc(caller, 'replace_entire_table_data', args)
except exception.CongressException as e:
LOG.exception("Error occurred while processing updating rows "
"for source_id '%s' and table_id '%s'",
source_id, table_id)
raise webservice.DataModelException.create(e)
LOG.info("finish replace_items(context=%s)", context)
LOG.debug("replaced table %s with row items: %s",
table_id, str(items))
# TODO(thinrichs): It makes sense to sometimes allow users to create
# a new row for internal data sources. But since we don't have
# those yet all tuples are read-only from the API.
# def add_item(self, item, id_=None, context=None):
# """Add item to model.
# Args:
# item: The item to add to the model
# id_: The ID of the item, or None if an ID should be generated
# context: Key-values providing frame of reference of request
# Returns:
# Tuple of (ID, newly_created_item)
# Raises:
# KeyError: ID already exists.
# """
# TODO(thinrichs): once we have internal data sources,
# add the ability to update a row. (Or maybe not and implement
# via add+delete.)
# def update_item(self, id_, item, context=None):
# """Update item with id\_ with new data.
# Args:
# id_: The ID of the item to be updated
# item: The new item
# context: Key-values providing frame of reference of request
# Returns:
# The updated item.
# Raises:
# KeyError: Item with specified id\_ not present.
# """
# # currently a noop since the owner_id cannot be changed
# if id_ not in self.items:
# raise KeyError("Cannot update item with ID '%s': "
# "ID does not exist")
# return item
# TODO(thinrichs): once we can create, we should be able to delete
# def delete_item(self, id_, context=None):
# """Remove item from model.
# Args:
# id_: The ID of the item to be removed
# context: Key-values providing frame of reference of request
# Returns:
# The removed item.
# Raises:
# KeyError: Item with specified id\_ not present.
# """
|
en
| 0.802917
|
# Copyright (c) 2014 VMware, Inc. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # Model for handling API requests about Rows. # TODO(thinrichs): No rows have IDs right now. Maybe eventually # could make ID the hash of the row, but then might as well # just make the ID a string repr of the row. No use case # for it as of now since all rows are read-only. # def get_item(self, id_, context=None): # """Retrieve item with id id\_ from model. # Args: # id_: The ID of the item to retrieve # context: Key-values providing frame of reference of request # Returns: # The matching item or None if item with id\_ does not exist. # """ # Note(thread-safety): blocking function Get items in model. :param: params: A dict-like object containing parameters from the request query string and body. :param: context: Key-values providing frame of reference of request :returns: A dict containing at least a 'results' key whose value is a list of items in the model. Additional keys set in the dict will also be rendered for the user. # Get the caller, it should be either policy or datasource # Note(thread-safety): blocking call # FIXME(threod-safety): in DSE2, the returned caller can be a # datasource name. But the datasource name may now refer to a new, # unrelated datasource. Causing the rest of this code to operate on # an unintended datasource. # It would have saved us if table_id was an UUID rather than a name, # but it appears that table_id is just another word for tablename. # Fix: check UUID of datasource before operating. Abort if mismatch # allow extra time for row policy engine query # Note(thread-safety): blocking call # Note(thread-safety): blocking call # DSE2 returns lists instead of tuples, so correct that. # Note(thread-safety): blocking function Replaces all data in a table. :param: id\_: A table id for replacing all row :param: items: A data for new rows :param: params: A dict-like object containing parameters from request query :param: context: Key-values providing frame of reference of request :returns: None :raises KeyError: table id doesn't exist :raises DataModelException: any error occurs during replacing rows. # Note(thread-safety): blocking call # FIXME(threod-safety): in DSE2, the returned caller can be a # datasource name. But the datasource name may now refer to a new, # unrelated datasource. Causing the rest of this code to operate on # an unintended datasource. # It would have saved us if table_id was an UUID rather than a name, # but it appears that table_id is just another word for tablename. # Fix: check UUID of datasource before operating. Abort if mismatch # Note(thread-safety): blocking call # TODO(thinrichs): It makes sense to sometimes allow users to create # a new row for internal data sources. But since we don't have # those yet all tuples are read-only from the API. # def add_item(self, item, id_=None, context=None): # """Add item to model. # Args: # item: The item to add to the model # id_: The ID of the item, or None if an ID should be generated # context: Key-values providing frame of reference of request # Returns: # Tuple of (ID, newly_created_item) # Raises: # KeyError: ID already exists. # """ # TODO(thinrichs): once we have internal data sources, # add the ability to update a row. (Or maybe not and implement # via add+delete.) # def update_item(self, id_, item, context=None): # """Update item with id\_ with new data. # Args: # id_: The ID of the item to be updated # item: The new item # context: Key-values providing frame of reference of request # Returns: # The updated item. # Raises: # KeyError: Item with specified id\_ not present. # """ # # currently a noop since the owner_id cannot be changed # if id_ not in self.items: # raise KeyError("Cannot update item with ID '%s': " # "ID does not exist") # return item # TODO(thinrichs): once we can create, we should be able to delete # def delete_item(self, id_, context=None): # """Remove item from model. # Args: # id_: The ID of the item to be removed # context: Key-values providing frame of reference of request # Returns: # The removed item. # Raises: # KeyError: Item with specified id\_ not present. # """
| 2.299921
| 2
|
tools/plotjuggler/juggle.py
|
aolin480/openpilot
| 70
|
6625849
|
<filename>tools/plotjuggler/juggle.py
#!/usr/bin/env python3
import os
import sys
import multiprocessing
import platform
import shutil
import subprocess
import tarfile
import tempfile
import requests
import argparse
from common.basedir import BASEDIR
from selfdrive.test.process_replay.compare_logs import save_log
from tools.lib.api import CommaApi
from tools.lib.auth_config import get_token
from tools.lib.robust_logreader import RobustLogReader
from tools.lib.route import Route, SegmentName
from urllib.parse import urlparse, parse_qs
juggle_dir = os.path.dirname(os.path.realpath(__file__))
DEMO_ROUTE = "4cf7a6ad03080c90|2021-09-29--13-46-36"
RELEASES_URL="https://github.com/commaai/PlotJuggler/releases/download/latest"
INSTALL_DIR = os.path.join(juggle_dir, "bin")
def install():
m = f"{platform.system()}-{platform.machine()}"
supported = ("Linux-x86_64", "Darwin-arm64", "Darwin-x86_64")
if m not in supported:
raise Exception(f"Unsupported platform: '{m}'. Supported platforms: {supported}")
if os.path.exists(INSTALL_DIR):
shutil.rmtree(INSTALL_DIR)
os.mkdir(INSTALL_DIR)
url = os.path.join(RELEASES_URL, m + ".tar.gz")
with requests.get(url, stream=True) as r, tempfile.NamedTemporaryFile() as tmp:
r.raise_for_status()
with open(tmp.name, 'wb') as tmpf:
for chunk in r.iter_content(chunk_size=1024*1024):
tmpf.write(chunk)
with tarfile.open(tmp.name) as tar:
tar.extractall(path=INSTALL_DIR)
def load_segment(segment_name):
if segment_name is None:
return []
try:
return list(RobustLogReader(segment_name))
except ValueError as e:
print(f"Error parsing {segment_name}: {e}")
return []
def start_juggler(fn=None, dbc=None, layout=None):
env = os.environ.copy()
env["BASEDIR"] = BASEDIR
env["PATH"] = f"{INSTALL_DIR}:{os.getenv('PATH', '')}"
if dbc:
env["DBC_NAME"] = dbc
extra_args = ""
if fn is not None:
extra_args += f" -d {fn}"
if layout is not None:
extra_args += f" -l {layout}"
cmd = f'plotjuggler --plugin_folders {INSTALL_DIR}{extra_args}'
subprocess.call(cmd, shell=True, env=env, cwd=juggle_dir)
def juggle_route(route_or_segment_name, segment_count, qlog, can, layout):
segment_start = 0
if 'cabana' in route_or_segment_name:
query = parse_qs(urlparse(route_or_segment_name).query)
api = CommaApi(get_token())
logs = api.get(f'v1/route/{query["route"][0]}/log_urls?sig={query["sig"][0]}&exp={query["exp"][0]}')
elif route_or_segment_name.startswith("http://") or route_or_segment_name.startswith("https://") or os.path.isfile(route_or_segment_name):
logs = [route_or_segment_name]
else:
route_or_segment_name = SegmentName(route_or_segment_name, allow_route_name=True)
segment_start = max(route_or_segment_name.segment_num, 0)
if route_or_segment_name.segment_num != -1 and segment_count is None:
segment_count = 1
r = Route(route_or_segment_name.route_name.canonical_name)
logs = r.qlog_paths() if qlog else r.log_paths()
segment_end = segment_start + segment_count if segment_count else -1
logs = logs[segment_start:segment_end]
if None in logs:
ans = input(f"{logs.count(None)}/{len(logs)} of the rlogs in this segment are missing, would you like to fall back to the qlogs? (y/n) ")
if ans == 'y':
logs = r.qlog_paths()[segment_start:segment_end]
else:
print("Please try a different route or segment")
return
all_data = []
with multiprocessing.Pool(24) as pool:
for d in pool.map(load_segment, logs):
all_data += d
if not can:
all_data = [d for d in all_data if d.which() not in ['can', 'sendcan']]
# Infer DBC name from logs
dbc = None
for cp in [m for m in all_data if m.which() == 'carParams']:
try:
DBC = __import__(f"selfdrive.car.{cp.carParams.carName}.values", fromlist=['DBC']).DBC
dbc = DBC[cp.carParams.carFingerprint]['pt']
except Exception:
pass
break
with tempfile.NamedTemporaryFile(suffix='.rlog', dir=juggle_dir) as tmp:
save_log(tmp.name, all_data, compress=False)
del all_data
start_juggler(tmp.name, dbc, layout)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="A helper to run PlotJuggler on openpilot routes",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--demo", action="store_true", help="Use the demo route instead of providing one")
parser.add_argument("--qlog", action="store_true", help="Use qlogs")
parser.add_argument("--can", action="store_true", help="Parse CAN data")
parser.add_argument("--stream", action="store_true", help="Start PlotJuggler in streaming mode")
parser.add_argument("--layout", nargs='?', help="Run PlotJuggler with a pre-defined layout")
parser.add_argument("--install", action="store_true", help="Install or update PlotJuggler + plugins")
parser.add_argument("route_or_segment_name", nargs='?', help="The route or segment name to plot (cabana share URL accepted)")
parser.add_argument("segment_count", type=int, nargs='?', help="The number of segments to plot")
if len(sys.argv) == 1:
parser.print_help()
sys.exit()
args = parser.parse_args()
if args.install:
install()
sys.exit()
if args.stream:
start_juggler(layout=args.layout)
else:
route_or_segment_name = DEMO_ROUTE if args.demo else args.route_or_segment_name.strip()
juggle_route(route_or_segment_name, args.segment_count, args.qlog, args.can, args.layout)
|
<filename>tools/plotjuggler/juggle.py
#!/usr/bin/env python3
import os
import sys
import multiprocessing
import platform
import shutil
import subprocess
import tarfile
import tempfile
import requests
import argparse
from common.basedir import BASEDIR
from selfdrive.test.process_replay.compare_logs import save_log
from tools.lib.api import CommaApi
from tools.lib.auth_config import get_token
from tools.lib.robust_logreader import RobustLogReader
from tools.lib.route import Route, SegmentName
from urllib.parse import urlparse, parse_qs
juggle_dir = os.path.dirname(os.path.realpath(__file__))
DEMO_ROUTE = "4cf7a6ad03080c90|2021-09-29--13-46-36"
RELEASES_URL="https://github.com/commaai/PlotJuggler/releases/download/latest"
INSTALL_DIR = os.path.join(juggle_dir, "bin")
def install():
m = f"{platform.system()}-{platform.machine()}"
supported = ("Linux-x86_64", "Darwin-arm64", "Darwin-x86_64")
if m not in supported:
raise Exception(f"Unsupported platform: '{m}'. Supported platforms: {supported}")
if os.path.exists(INSTALL_DIR):
shutil.rmtree(INSTALL_DIR)
os.mkdir(INSTALL_DIR)
url = os.path.join(RELEASES_URL, m + ".tar.gz")
with requests.get(url, stream=True) as r, tempfile.NamedTemporaryFile() as tmp:
r.raise_for_status()
with open(tmp.name, 'wb') as tmpf:
for chunk in r.iter_content(chunk_size=1024*1024):
tmpf.write(chunk)
with tarfile.open(tmp.name) as tar:
tar.extractall(path=INSTALL_DIR)
def load_segment(segment_name):
if segment_name is None:
return []
try:
return list(RobustLogReader(segment_name))
except ValueError as e:
print(f"Error parsing {segment_name}: {e}")
return []
def start_juggler(fn=None, dbc=None, layout=None):
env = os.environ.copy()
env["BASEDIR"] = BASEDIR
env["PATH"] = f"{INSTALL_DIR}:{os.getenv('PATH', '')}"
if dbc:
env["DBC_NAME"] = dbc
extra_args = ""
if fn is not None:
extra_args += f" -d {fn}"
if layout is not None:
extra_args += f" -l {layout}"
cmd = f'plotjuggler --plugin_folders {INSTALL_DIR}{extra_args}'
subprocess.call(cmd, shell=True, env=env, cwd=juggle_dir)
def juggle_route(route_or_segment_name, segment_count, qlog, can, layout):
segment_start = 0
if 'cabana' in route_or_segment_name:
query = parse_qs(urlparse(route_or_segment_name).query)
api = CommaApi(get_token())
logs = api.get(f'v1/route/{query["route"][0]}/log_urls?sig={query["sig"][0]}&exp={query["exp"][0]}')
elif route_or_segment_name.startswith("http://") or route_or_segment_name.startswith("https://") or os.path.isfile(route_or_segment_name):
logs = [route_or_segment_name]
else:
route_or_segment_name = SegmentName(route_or_segment_name, allow_route_name=True)
segment_start = max(route_or_segment_name.segment_num, 0)
if route_or_segment_name.segment_num != -1 and segment_count is None:
segment_count = 1
r = Route(route_or_segment_name.route_name.canonical_name)
logs = r.qlog_paths() if qlog else r.log_paths()
segment_end = segment_start + segment_count if segment_count else -1
logs = logs[segment_start:segment_end]
if None in logs:
ans = input(f"{logs.count(None)}/{len(logs)} of the rlogs in this segment are missing, would you like to fall back to the qlogs? (y/n) ")
if ans == 'y':
logs = r.qlog_paths()[segment_start:segment_end]
else:
print("Please try a different route or segment")
return
all_data = []
with multiprocessing.Pool(24) as pool:
for d in pool.map(load_segment, logs):
all_data += d
if not can:
all_data = [d for d in all_data if d.which() not in ['can', 'sendcan']]
# Infer DBC name from logs
dbc = None
for cp in [m for m in all_data if m.which() == 'carParams']:
try:
DBC = __import__(f"selfdrive.car.{cp.carParams.carName}.values", fromlist=['DBC']).DBC
dbc = DBC[cp.carParams.carFingerprint]['pt']
except Exception:
pass
break
with tempfile.NamedTemporaryFile(suffix='.rlog', dir=juggle_dir) as tmp:
save_log(tmp.name, all_data, compress=False)
del all_data
start_juggler(tmp.name, dbc, layout)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="A helper to run PlotJuggler on openpilot routes",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--demo", action="store_true", help="Use the demo route instead of providing one")
parser.add_argument("--qlog", action="store_true", help="Use qlogs")
parser.add_argument("--can", action="store_true", help="Parse CAN data")
parser.add_argument("--stream", action="store_true", help="Start PlotJuggler in streaming mode")
parser.add_argument("--layout", nargs='?', help="Run PlotJuggler with a pre-defined layout")
parser.add_argument("--install", action="store_true", help="Install or update PlotJuggler + plugins")
parser.add_argument("route_or_segment_name", nargs='?', help="The route or segment name to plot (cabana share URL accepted)")
parser.add_argument("segment_count", type=int, nargs='?', help="The number of segments to plot")
if len(sys.argv) == 1:
parser.print_help()
sys.exit()
args = parser.parse_args()
if args.install:
install()
sys.exit()
if args.stream:
start_juggler(layout=args.layout)
else:
route_or_segment_name = DEMO_ROUTE if args.demo else args.route_or_segment_name.strip()
juggle_route(route_or_segment_name, args.segment_count, args.qlog, args.can, args.layout)
|
en
| 0.421663
|
#!/usr/bin/env python3 # Infer DBC name from logs
| 1.876137
| 2
|
nli_mixed_models/eval/nli_eval.py
|
wgantt/nli-mixed-models
| 1
|
6625850
|
<reponame>wgantt/nli-mixed-models
import torch
import logging
import numpy as np
import pandas as pd
from torch.optim import Adam
from torch.nn import CrossEntropyLoss, BCEWithLogitsLoss
from ..modules.nli_base import NaturalLanguageInference
from ..modules.nli_random_intercepts import (
UnitRandomIntercepts,
CategoricalRandomIntercepts,
)
from scripts.setup_logging import setup_logging
from ..modules.nli_random_slopes import UnitRandomSlopes, CategoricalRandomSlopes
from ..trainers.nli_trainer import BetaLogProbLoss, beta_mode
from scripts.eval_utils import (
accuracy,
absolute_error,
accuracy_best,
)
from torch.distributions import Beta
LOG = setup_logging()
class NaturalLanguageInferenceEval:
def __init__(
self, model: NaturalLanguageInference, subtask: str = "a", device="cpu"
):
self.nli = model
self.subtask = subtask
self.lossfunc = self.LOSS_CLASS()
self.device = device
def eval(self, test_data: pd.DataFrame, batch_size: int = 32):
self.nli.eval()
with torch.no_grad():
n_batches = np.ceil(test_data.shape[0] / batch_size)
test_data = test_data.sample(frac=1).reset_index(drop=True)
test_data.loc[:, "batch_idx"] = np.repeat(np.arange(n_batches), batch_size)[
: test_data.shape[0]
]
loss_trace = []
fixed_loss_trace = []
random_loss_trace = []
metric_trace = []
best_trace = []
# Tensors for accumulating predictions, targets, and modal
# responses across batches.
if isinstance(self.nli, CategoricalRandomIntercepts) or isinstance(
self.nli, CategoricalRandomSlopes
):
all_predictions = torch.FloatTensor().to(self.device)
all_targets = torch.LongTensor().to(self.device)
all_modal_responses = torch.LongTensor().to(self.device)
all_best = torch.LongTensor().to(self.device)
naive_prediction = test_data.target.mode().item()
naive_acc = len(test_data[test_data.target == naive_prediction]) / len(
test_data
)
LOG.info(f"naive accuracy across fold: {naive_acc}")
else:
all_predictions = torch.FloatTensor().to(self.device)
all_targets = torch.FloatTensor().to(self.device)
all_modal_responses = torch.FloatTensor().to(self.device)
all_best = torch.LongTensor().to(self.device)
# Calculate metrics for each batch in test set
for batch, items in test_data.groupby("batch_idx"):
LOG.info("evaluating batch [%s/%s]" % (int(batch), int(n_batches)))
if self.subtask == "a":
participant = torch.LongTensor(items.participant.values)
else:
participant = None
# Get target values of appropriate type
if isinstance(self.nli, CategoricalRandomIntercepts) or isinstance(
self.nli, CategoricalRandomSlopes
):
target = torch.LongTensor(items.target.values).to(self.device)
modal_response = torch.LongTensor(items.modal_response.values).to(
self.device
)
else:
target = torch.FloatTensor(items.target.values).to(self.device)
modal_response = torch.FloatTensor(items.modal_response.values).to(
self.device
)
all_targets = torch.cat((all_targets, target))
all_modal_responses = torch.cat((all_modal_responses, modal_response))
# Embed items
embedding = self.nli.embed(items)
# Calculate model prediction and compute fixed & random loss
if isinstance(self.nli, UnitRandomIntercepts) or isinstance(
self.nli, UnitRandomSlopes
):
prediction, random_loss = self.nli(embedding, participant)
alpha, beta = prediction
prediction = alpha / (alpha + beta)
fixed_loss = self.lossfunc(alpha, beta, target)
else:
prediction, random_loss = self.nli(embedding, participant)
fixed_loss = self.lossfunc(prediction, target)
all_predictions = torch.cat((all_predictions, prediction))
random_loss = (
random_loss
if isinstance(random_loss, float)
else random_loss.item()
)
# Add total loss to trace
loss = fixed_loss + random_loss
loss_trace.append(loss.item())
fixed_loss_trace.append(fixed_loss.item())
random_loss_trace.append(random_loss)
# If categorical, calculate accuracy (and Spearman's coefficient)
if isinstance(self.nli, CategoricalRandomIntercepts) or isinstance(
self.nli, CategoricalRandomSlopes
):
acc = accuracy(prediction, target)
best = accuracy_best(items)
metric_trace.append(acc)
best_trace.append(acc / best)
# If unit, calculate absolute error
else:
error = absolute_error(prediction, target)
best = absolute_error(modal_response, target)
metric_trace.append(error)
best_trace.append(1 - (error - best) / best)
# Calculate Spearman's correlation coefficient between
# 1. Best possible (i.e. modal) responses and true responses
# 2. Predicted responses and true responses
"""
spearman_df = pd.DataFrame()
spearman_df["true"] = pd.Series(all_targets.cpu().detach().numpy())
spearman_df["predicted"] = pd.Series(
all_predictions.cpu().detach().numpy()
)
spearman_df["best"] = pd.Series(
all_modal_responses.cpu().detach().numpy()
)
spearman_predicted = (
spearman_df[["true", "predicted"]]
.corr(method="spearman")
.iloc[0, 1]
)
spearman_best = (
spearman_df[["true", "best"]].corr(method="spearman").iloc[0, 1]
)
"""
# Calculate and return mean of metrics across all batches
loss_mean = np.round(np.mean(loss_trace), 4)
fixed_loss_mean = np.round(np.mean(fixed_loss_trace), 4)
random_loss_mean = np.round(np.mean(random_loss_trace), 4)
metric_mean = np.round(np.mean(metric_trace), 4)
best_mean = np.round(np.mean(best_trace), 4)
"""
spearman_predicted = np.round(spearman_predicted, 4)
spearman_best = np.round(spearman_best, 4)
"""
spearman_predicted = 0
spearman_best = 1
# Macroaverage
best_mean = (all_modal_responses == all_targets).cpu().numpy().mean()
worst_mean = naive_acc
metric_mean = accuracy(all_predictions, all_targets)
# An undefined Spearman means that all the predicted values are
# the same. This is unlikely to occur across an entire test fold,
# but not impossible. As noted in the paper, an undefined Spearman
# correlation essentially represents *0* correlation.
if np.isnan(spearman_predicted):
spearman_predicted = 0.0
return (
loss_mean,
fixed_loss_mean,
random_loss_mean,
metric_mean,
best_mean,
spearman_predicted,
spearman_best,
worst_mean,
)
# Unit eval
class UnitEval(NaturalLanguageInferenceEval):
LOSS_CLASS = BetaLogProbLoss
TARGET_TYPE = torch.FloatTensor
# Categorical eval
class CategoricalEval(NaturalLanguageInferenceEval):
LOSS_CLASS = CrossEntropyLoss
TARGET_TYPE = torch.LongTensor
|
import torch
import logging
import numpy as np
import pandas as pd
from torch.optim import Adam
from torch.nn import CrossEntropyLoss, BCEWithLogitsLoss
from ..modules.nli_base import NaturalLanguageInference
from ..modules.nli_random_intercepts import (
UnitRandomIntercepts,
CategoricalRandomIntercepts,
)
from scripts.setup_logging import setup_logging
from ..modules.nli_random_slopes import UnitRandomSlopes, CategoricalRandomSlopes
from ..trainers.nli_trainer import BetaLogProbLoss, beta_mode
from scripts.eval_utils import (
accuracy,
absolute_error,
accuracy_best,
)
from torch.distributions import Beta
LOG = setup_logging()
class NaturalLanguageInferenceEval:
def __init__(
self, model: NaturalLanguageInference, subtask: str = "a", device="cpu"
):
self.nli = model
self.subtask = subtask
self.lossfunc = self.LOSS_CLASS()
self.device = device
def eval(self, test_data: pd.DataFrame, batch_size: int = 32):
self.nli.eval()
with torch.no_grad():
n_batches = np.ceil(test_data.shape[0] / batch_size)
test_data = test_data.sample(frac=1).reset_index(drop=True)
test_data.loc[:, "batch_idx"] = np.repeat(np.arange(n_batches), batch_size)[
: test_data.shape[0]
]
loss_trace = []
fixed_loss_trace = []
random_loss_trace = []
metric_trace = []
best_trace = []
# Tensors for accumulating predictions, targets, and modal
# responses across batches.
if isinstance(self.nli, CategoricalRandomIntercepts) or isinstance(
self.nli, CategoricalRandomSlopes
):
all_predictions = torch.FloatTensor().to(self.device)
all_targets = torch.LongTensor().to(self.device)
all_modal_responses = torch.LongTensor().to(self.device)
all_best = torch.LongTensor().to(self.device)
naive_prediction = test_data.target.mode().item()
naive_acc = len(test_data[test_data.target == naive_prediction]) / len(
test_data
)
LOG.info(f"naive accuracy across fold: {naive_acc}")
else:
all_predictions = torch.FloatTensor().to(self.device)
all_targets = torch.FloatTensor().to(self.device)
all_modal_responses = torch.FloatTensor().to(self.device)
all_best = torch.LongTensor().to(self.device)
# Calculate metrics for each batch in test set
for batch, items in test_data.groupby("batch_idx"):
LOG.info("evaluating batch [%s/%s]" % (int(batch), int(n_batches)))
if self.subtask == "a":
participant = torch.LongTensor(items.participant.values)
else:
participant = None
# Get target values of appropriate type
if isinstance(self.nli, CategoricalRandomIntercepts) or isinstance(
self.nli, CategoricalRandomSlopes
):
target = torch.LongTensor(items.target.values).to(self.device)
modal_response = torch.LongTensor(items.modal_response.values).to(
self.device
)
else:
target = torch.FloatTensor(items.target.values).to(self.device)
modal_response = torch.FloatTensor(items.modal_response.values).to(
self.device
)
all_targets = torch.cat((all_targets, target))
all_modal_responses = torch.cat((all_modal_responses, modal_response))
# Embed items
embedding = self.nli.embed(items)
# Calculate model prediction and compute fixed & random loss
if isinstance(self.nli, UnitRandomIntercepts) or isinstance(
self.nli, UnitRandomSlopes
):
prediction, random_loss = self.nli(embedding, participant)
alpha, beta = prediction
prediction = alpha / (alpha + beta)
fixed_loss = self.lossfunc(alpha, beta, target)
else:
prediction, random_loss = self.nli(embedding, participant)
fixed_loss = self.lossfunc(prediction, target)
all_predictions = torch.cat((all_predictions, prediction))
random_loss = (
random_loss
if isinstance(random_loss, float)
else random_loss.item()
)
# Add total loss to trace
loss = fixed_loss + random_loss
loss_trace.append(loss.item())
fixed_loss_trace.append(fixed_loss.item())
random_loss_trace.append(random_loss)
# If categorical, calculate accuracy (and Spearman's coefficient)
if isinstance(self.nli, CategoricalRandomIntercepts) or isinstance(
self.nli, CategoricalRandomSlopes
):
acc = accuracy(prediction, target)
best = accuracy_best(items)
metric_trace.append(acc)
best_trace.append(acc / best)
# If unit, calculate absolute error
else:
error = absolute_error(prediction, target)
best = absolute_error(modal_response, target)
metric_trace.append(error)
best_trace.append(1 - (error - best) / best)
# Calculate Spearman's correlation coefficient between
# 1. Best possible (i.e. modal) responses and true responses
# 2. Predicted responses and true responses
"""
spearman_df = pd.DataFrame()
spearman_df["true"] = pd.Series(all_targets.cpu().detach().numpy())
spearman_df["predicted"] = pd.Series(
all_predictions.cpu().detach().numpy()
)
spearman_df["best"] = pd.Series(
all_modal_responses.cpu().detach().numpy()
)
spearman_predicted = (
spearman_df[["true", "predicted"]]
.corr(method="spearman")
.iloc[0, 1]
)
spearman_best = (
spearman_df[["true", "best"]].corr(method="spearman").iloc[0, 1]
)
"""
# Calculate and return mean of metrics across all batches
loss_mean = np.round(np.mean(loss_trace), 4)
fixed_loss_mean = np.round(np.mean(fixed_loss_trace), 4)
random_loss_mean = np.round(np.mean(random_loss_trace), 4)
metric_mean = np.round(np.mean(metric_trace), 4)
best_mean = np.round(np.mean(best_trace), 4)
"""
spearman_predicted = np.round(spearman_predicted, 4)
spearman_best = np.round(spearman_best, 4)
"""
spearman_predicted = 0
spearman_best = 1
# Macroaverage
best_mean = (all_modal_responses == all_targets).cpu().numpy().mean()
worst_mean = naive_acc
metric_mean = accuracy(all_predictions, all_targets)
# An undefined Spearman means that all the predicted values are
# the same. This is unlikely to occur across an entire test fold,
# but not impossible. As noted in the paper, an undefined Spearman
# correlation essentially represents *0* correlation.
if np.isnan(spearman_predicted):
spearman_predicted = 0.0
return (
loss_mean,
fixed_loss_mean,
random_loss_mean,
metric_mean,
best_mean,
spearman_predicted,
spearman_best,
worst_mean,
)
# Unit eval
class UnitEval(NaturalLanguageInferenceEval):
LOSS_CLASS = BetaLogProbLoss
TARGET_TYPE = torch.FloatTensor
# Categorical eval
class CategoricalEval(NaturalLanguageInferenceEval):
LOSS_CLASS = CrossEntropyLoss
TARGET_TYPE = torch.LongTensor
|
en
| 0.673311
|
# Tensors for accumulating predictions, targets, and modal # responses across batches. # Calculate metrics for each batch in test set # Get target values of appropriate type # Embed items # Calculate model prediction and compute fixed & random loss # Add total loss to trace # If categorical, calculate accuracy (and Spearman's coefficient) # If unit, calculate absolute error # Calculate Spearman's correlation coefficient between # 1. Best possible (i.e. modal) responses and true responses # 2. Predicted responses and true responses spearman_df = pd.DataFrame() spearman_df["true"] = pd.Series(all_targets.cpu().detach().numpy()) spearman_df["predicted"] = pd.Series( all_predictions.cpu().detach().numpy() ) spearman_df["best"] = pd.Series( all_modal_responses.cpu().detach().numpy() ) spearman_predicted = ( spearman_df[["true", "predicted"]] .corr(method="spearman") .iloc[0, 1] ) spearman_best = ( spearman_df[["true", "best"]].corr(method="spearman").iloc[0, 1] ) # Calculate and return mean of metrics across all batches spearman_predicted = np.round(spearman_predicted, 4) spearman_best = np.round(spearman_best, 4) # Macroaverage # An undefined Spearman means that all the predicted values are # the same. This is unlikely to occur across an entire test fold, # but not impossible. As noted in the paper, an undefined Spearman # correlation essentially represents *0* correlation. # Unit eval # Categorical eval
| 2.092568
| 2
|